bioRxiv Subject Collection: Neuroscience's Journal

CRITICAL ROLE OF ADULT-BORN DENTATE GRANULE NEURONS IN PATTERN COMPLETION
The dentate gyrus contains neurons generated during development and adulthood, yet their distinct roles remain unclear. Using a transgenic mouse model, we show that adult-born neurons contribute to pattern completion, essential for episodic memory. This has implications for aging, PTSD, and addiction, where excessive pattern completion leads to maladaptive memories. Targeting ABNs could offer new therapeutic strategies to regulate memory processes and improve mental health.

Aperiodic slope reflects glutamatergic tone in the human brain
Excitatory and inhibitory neural processes are essential for every aspect of brain function, but the current, non-invasive, neuroimaging methods to study these in the human brain are limited. Recent studies which separate oscillatory and aperiodic components of electrophysiological power spectra have highlighted a relationship between aperiodic activity and functional brain states. Studies in both animal models and humans suggest that the aperiodic slope of electrophysiological power spectra reflects the local balance of excitatory:inhibitory (E:I) synaptic transmission. Aperiodic slope varies across individuals, brain states, and clinical populations, which may reflect important differences in E:I balance. However, there is currently a lack of evidence linking aperiodic slope to other measures of excitation and inhibition in the human brain. Here, we show that flatter (less steep) aperiodic slopes from human electroencephalography (EEG) are associated with higher concentrations of the excitatory neurotransmitter glutamate measured with 7 tesla magnetic resonance spectroscopy (MRS) in the occipital lobe at rest. This suggests that individual differences in aperiodic neural activity reflect cortical glutamate concentrations, providing important insight for understanding changes in neural excitation across brain states and neuropsychiatric populations (e.g., schizophrenia) where glutamatergic function may differ. Our results support the use of aperiodic slope as a non-invasive marker for excitatory tone in the human brain.

Targeted Neuromodulation of Perceptual Decision-Making Networks Causally Dissociates Sensory and Metacognitive performance
Perceptual judgements and their subjective evaluation (i.e., metacognition) are considered tightly coupled aspects of decision-making. Yet, emerging evidence suggests that distinct neural mechanisms underlie these processes. In motion perception, studies have identified a neural network involving visual and associative parietal areas supporting these abilities. Whilst early (V1/V2) and specialized (V5/MT+) visual areas are associated with motion discrimination accuracy, the intraparietal sulcus (IPS/LIP) plays a critical role in the formation of subjective confidence for sensory decision, given its functionally coupling with the V5/MT+_V1/V2 network. Previous studies have consistently reported that increasing connectivity in the human V5/MT+ to V1/V2 pathway by means of cortico-cortical paired associative stimulation (ccPAS), a neurostimulation protocol inducing Hebbian-like changes in neuronal pathways, improves our perceptual ability to discriminate motion. Notably, we recently demonstrated that strengthening V5/MT+ influence over V1/V2 also leads to overconfidence, altering metacognitive bias for motion discrimination, suggesting that the manipulation of V5/MT+_V1/V2 network might functionally affect IPS/LIP activity. Here, we directly investigated this possibility by first strengthening the V5/MT+_V1 pathway with ccPAS, and subsequently interfering with IPS/LIP activity by means of continuous theta-burst stimulation (cTBS). In line with previous evidence, our results corroborate that enhancing V5/MT+_V1/V2 connectivity affects both motion discrimination and metacognitive bias. Crucially, IPS/LIP disruption through cTBS selectively affects metacognitive performance while leaving motion discrimination unaltered. These findings highlight distinct neural substrates for perceptual sensitivity and visual metacognition linked to V5/MT+ and IPS/LIP, respectively, opening to potential tailored applications of non-invasive brain stimulation (NIBS) to functionally improve sensory and metacognitive decision-making processes

Evaluating the dependence of ADC-fMRI on haemodynamics inbreath-hold and resting-state conditions
Apparent diffusion coefficient (ADC)-fMRI offers a promising functional contrast, capable of mapping neuronal activity directly in both grey and white matter. However, previous studies have shown that diffusion-weighted fMRI (dfMRI), from which ADC-fMRI derives, is influenced by BOLD effects, leading to a concern that the dfMRI contrast is still rooted in neurovascular rather than neuromorphological coupling. Mitigation strategies have been proposed to remove vascular contributions while retaining neuromorphological coupling, by: i) analysing ADC timecourses calculated from two interleaved diffusion-weightings, known as ADC-fMRI; ii) using b-values of at least 200 s mm-2 ; and iii) using a sequence compensated for cross-terms with fluctuating background field gradients associated with blood oxygenation. Respiration-induced haemodynamic fluctuations, which are dissociated from neural activity, are an excellent test-bed for the robustness of ADC-fMRI to vascular contributions. In this study, we investigate the association between end-tidal CO2 and ADC-fMRI, in comparison with dfMRI and BOLD, in both breath-hold and resting-state paradigms in the human brain. We confirm a strong dependence of the BOLD signal on respiration, and find a pattern of delayed haemodynamic response to respiration in regions comprising the default mode network. While dfMRI mitigates much of the vascular contribution, it retains some association with respiration, as expected. Conversely, ADC-fMRI is mostly unaffected by vascular contribution, exhibiting minimal correlation between expired CO2 and ADC timeseries, as well as low inter- and intra-subject reproducibility in correlation maps. These findings validate ADC-fMRI as a predominantly non-vascular contrast sensitive to microstructural dynamics, enabling whole-brain functional imaging unconstrained by vascular confounds.

The functional neurobiology of negative affective traits across regions, networks, signatures, and a machine learning multiverse
Understanding the neural basis of negative affective traits like neuroticism remains a critical challenge across psychology, neuroscience, and psychiatry. Here, we investigate which level of brain organization - regions, networks, or validated whole-brain machine-learning signatures - best explains negative affective traits in a community sample of 458 adults performing the two most widely used affective fMRI tasks, viewing emotional faces and scenes. Neuroticism could not be predicted from brain activity, with Bayesian evidence against all theory-guided neural measures. However, preregistered whole-brain models successfully decoded vulnerability to stress, a lower-level facet of neuroticism, with results replicating in a hold-out sample. The neural stress vulnerability pattern demonstrated good psychometric properties and indicated that negative affective traits are best represented by distributed whole-brain patterns related to domain-general stimulation rather than localized activity. Together with results from a comprehensive multiverse analysis across 14 traits and 1,176 models - available for exploration in an online app - the findings speak against simplistic neurobiological theories of negative affective traits, highlight a striking gap between predicting individual differences (r<.35) and within-person emotional states (r=.88), and underscore the importance of aligning psychological constructs with neural measures at the appropriate level of granularity.

Breathing strategies to influence perception: Evidence for interoceptive and exteroceptive active sensing
Recent research indicates that humans continuously and automatically modulate their breathing to temporally align exteroceptive stimuli with specific phases of the respiratory cycle. This process has been interpreted as a form of active sensing and is associated with faster responses and improved perceptual accuracy. While converging evidence suggests that respiration also shapes interoceptive processing at both neural and behavioural levels, it remains unclear whether individuals actively adjust their breathing to optimize interoceptive performance. In this study, we examined whether healthy participants modulated their respiration during an interoceptive (heartbeat discrimination) and an exteroceptive (tactile detection) task. We analysed respiration both in terms of time-locked activity and inter-trial phase coherence relative to stimulus onset and assessed their relationship with perceptual accuracy. Our results demonstrated that participants systematically adjust their breathing in both amplitude and phase, synchronizing respiration to the anticipated (i.e., cued) onset of stimuli in both tasks. Crucially, task performance was enhanced during exhalation compared to inhalation, suggesting that respiratory modulation supports the perception of both interoceptive and exteroceptive signals.

Graphene Micro-transistor Arrays Reveal Perfusion-Dependent Electrophysiological and Haemodynamic Signatures of Cortical Spreading Depolarizations in Ischaemic Stroke
Cortical spreading depolarizations (CSDs) are large scale disruptions of neuronal homeostasis that contribute to secondary injury in ischaemic stroke. In healthy cortex, CSDs induce vasodilation to meet metabolic demand, whereas in ischaemic tissue, they can provoke vasoconstriction and sustained hypoperfusion, exacerbating damage. We present a multimodal neurotechnology platform integrating flexible, transparent graphene solution-gated field-effect transistor (gSGFET) arrays with laser speckle contrast imaging (LSCI), enabling simultaneous DC coupled electrophysiological recordings and cerebral blood flow imaging with high spatiotemporal fidelity. gSGFETs enable stable, distortion-free recording of infraslow potentials essential for resolving CSD waveforms in vivo. In two murine stroke models, we show that CSD waveform duration and morphology scale with local perfusion, delineating electrophysiological subtypes predictive of tissue viability and haemodynamic response. In metabolically compromised cortex, CSDs exhibit double peaks or negative ultraslow components that result in vasoconstriction, contrasting with narrow, monophasic waveforms eliciting vasodilation in healthy regions. Systemic ketamine shortens CSD duration and converts vasoconstriction to vasodilation in perfusion deficit tissue, revealing a mechanism for its neuroprotective action. This platform enables high-fidelity investigation of brain blood flow interactions in vivo.

Age- and Sex-Related Differences in Sleep Patterns and Their Relations to Self-Reported Sleep and Mood
Robust age- and sex-related differences in sleep were identified (n=38,546) and replicated (n=38,547) from week-long passive actigraphy data in UK Biobank participants ages 44-82. Sleep patterns reflected reliable non-linear interactions between age and sex. Younger women slept about 17 min more than their male counterparts, though this difference diminished with age, with both sexes reducing total sleep duration in later life. Middle-aged individuals exhibited shorter sleep durations during the week, with weekend sleep increasing by as much as 50 min. Participants in their seventh and eighth decades showed more consistent sleep patterns throughout the week. Sleep patterns also suggest maintenance of total sleep duration: individuals reporting waking too early maintain sleep duration by going to sleep earlier, while individuals reporting sleeping too much fall asleep later but also wake later, again maintaining sleep duration. Self-reported depression and anhedonia were associated with reduced total sleep duration across multiple age groups and both sexes. These collective results indicate that the timing, consistency, and overall amount of sleep differs by age and is affected by individual factors.

Decoding the epistemic arc: Distinct physiological signatures for curiosity, insight, understanding and liking during interactions with visual art
Recent work on insight and information processing suggested feelings of aha as a metacognitive feedback signal. A series of processes, from curiosity (drive state) to insight (uncertainty reduction) to pleasure (reward and reinforcement), might represent a fundamental epistemic arc for motivated learning. Here, we present a paradigm that combines measurement of curiosity, insight (aha), understanding and liking to outline the contours of this epistemic arc and study their neuronal mechanisms. In two preregistered experiments we employ the so called "title effect" - the fact that additional semantic information accompanying an artwork (such as titles) can change how an observer understands and enjoys a piece of visual art. Participants viewed paintings (5s trials) and rated their curiosity for seeing the title. This was followed either by the original title or a dummy title lacking additional information ("untitled"), and a second presentation of the painting, after which participants rated strength of aha, aesthetic liking, and feeling of understanding the artwork. In a behavioral online study (N=55 participants) we replicate a set of previous findings and established that visual art together with their titles can prompt strong feelings of aha. The association between the collected ratings is complex, partly nonlinear, and shaped by the type and amount of information provided by the stimulus material. In an EEG, ECG and eye tracking study with the same paradigm (N=49 participants) we aimed to characterize the temporal sequence of processing. Using a time-resolved decoding approach we were able to recover the categorical experimental conditions and the graded ratings: curiosity for the title could be decoded late in pretitle trials and early in the posttitle trials; aha could be decoded in posttitle trials; felt understanding had the most robust signature among the ratings and could be decoded from multiple signals in both pre and posttitle trials. Lastly, ratings of aesthetic liking were hard to decode from the data with only a short significant timewindow early during posttitle trials.

Can Pupillometry Reveal Perturbation Detection in Sensorimotor Adaptation during Grasping?
Humans adjust their motor actions to correct for errors both with and without being aware of doing so. Little is known, however, about what makes errors detectable for the actor. Here, we replicate and extend prior work showing that motor adjustments may mask the very errors they correct for. We also investigated pupillometry as an unobtrusive no-report marker of perturbation detection. N=48 participants grasped objects while a visuo-haptic size mismatch was applied either sinusoidally or abruptly. When mismatches started abruptly and thereafter stayed the same, participants adapted well but also showed decreasing discrimination performance and decreasing confidence in their responses. This was not the case for sinusoidally introduced perturbations. We also show that parameters that characterize phasic and tonic pupil responses were predicted by stimulus parameters and differed depending on participants' grasping and behavioral responses. However, predicting response characteristics from pupil-dilation features using support-vector machine classifiers was not successful. This shows that while pupillometry may yet prove to be a useful no-report marker of perturbation and error detection, there are some challenges for trial-by-trial prediction.

Dynamic Resting-State Network Markers of Disruptive Behavior Problems in Youth
Background: Childhood disruptive behavior problems are linked to aberrant integrity within large-scale cognitive control networks. However, it is unclear if transitory or dynamic variation in the functional brain architecture is a marker of disruptive behavior problems. The current study tested whether functional connectivity across dynamic networks is distinctly associated with the transdiagnostic symptom domain of disruptive behavior problems in children. Methods: Participants were aged 9-10 years from the Adolescent Brain Cognitive Development (ABCD) Study, who completed resting-state fMRI (N=877). We employed a dynamic connectivity approach leveraging a hidden semi-Markov model (HSMM) to identify transient properties of brain networks and states. Models estimated the time spent in each state (occupancy time) and the number of consecutive timepoints in a state (dwell time) for each participant. Linear regression models were utilized to identify distinct associations between dynamic properties (occupancy and sojourn times) and severity of disruptive behavior problems, accounting for other commonly co-occurring symptoms. Results: Dynamic network markers of disruptive behavior problems included increased time in network states characterized by globally aberrant connectivity patterns in circuitry involved in cognitive control including frontoparietal and dorsal attention networks. Replication of findings was found in a held-out sample of resting-state fMRI runs in which greater severity of disruptive behavior problems was uniquely linked to greater occupancy time in similarly characterized brain states. Conclusion: Transdiagnostic, dynamic resting-state markers of disruptive behavior problems in youth may assist in the development of brain-based biomarkers for monitoring treatment outcomes, assessing circuit target engagement and informing clinical decisions.

Autonomous Retrieval for Continuous Learning in Associative Memory Networks
The brains faculty to assimilate and retain information, continually updating its memory while limiting the loss of valuable past knowledge, remains largely a mystery. We address this challenge related to continuous learning in the context of associative memory networks, where the sequential storage of correlated patterns typically requires non-local learning rules or external memory systems. Our work demonstrates how incorporating biologically-inspired inhibitory plasticity enables networks to autonomously explore their attractor landscape. The algorithm presented here allows for the autonomous retrieval of stored patterns, enabling the progressive incorporation of correlated memories. This mechanism is reminiscent of memory consolidation during sleep-like states in biological systems. The resulting framework provides insights into how neural circuits might maintain memories through purely local interactions, and takes a step forward towards a more biologically plausible mechanism for continuous learning.

Somato-Motor Network Neural Connectivity Correlates with Visuomotor Adaptation
Humans show tremendous individual differences in learning motor skills. Prediction of individual differences in motor learning is of theoretical significance and practical relevance. Brain as the central neural apparatus supporting motor control and learning has attracted considerable research efforts on examining brain functional and structural predictors of individual differences in motor learning. Many previous studies applied a resting state (RS) approach in recording brain activity, selected the contralateral primary motor cortex (M1) a priori as a seed or region of interest (ROI), and reported that functional connectivity between M1 and other brain regions predicted individual differences in tasks mostly on motor sequence learning. However, task-evoked brain neural activity and connectivity that represent different brain dynamics from spontaneous brain dynamics have not been studied in this line of research. This study presents findings on RS and finger-tapping evoked cortical somato-motor network (SMN) neural connectivity correlates with individual performances in a visuomotor adaptation (VMA) task, based on analysis of multimodal data from the Cam-CAN study. SMN nodes were initially localized through finger-tapping evoked brain magnetic fields as sampled with magnetoencephalography (MEG). It was found that SMN node specific neural connectivity strength at the contralateral primary somatosensory cortex (S1), supplementary motor area (SMA), and dorsal premotor cortex (PMd) during different stages around finger tapping but not in RS were significantly correlated with individual mean target errors in the final adaptation stage. The results imply critical roles of somatosensory and secondary motor areas in human motor learning.

Differential Effects of Meditation States and Traits on the Neural Mechanisms of Pain Processing
Objectives. The main objective of the present study was to explore the effects of different types of meditation on the neurophysiologic mechanisms of pain processing. Methods. EEG responses to electric median nerve stimulation were recorded in short-term and long-term meditators (STM, LTM) during rest and three forms of meditation engaging attentional and affective regulation in different ways: focused attention meditation (FAM), open monitoring meditation (OMM) and loving kindness meditation (LKM). EEG responses were analysed in the time- and time-frequency domains to compute local components, and temporal and spatial synchronizations of multi-spectral pain-related oscillations (PROs) in order to characterize bottom-up processes, pro-active modulation of cortical excitability, cognitive/affective appraisal, and the connectivity of performance monitoring (fronto-medial) and attentional (fronto-parietal) networks during pain processing. Results. STM manifested a significant decrease in the connectedness of the fronto-medial theta-alpha network and a significant reduction of the P3b during LKM. In contrast, changes in LTM were observed during FAM and OMM. They were characterized by pre-stimulus alpha increase at somatosensory areas, and modulations of fronto-medial and fronto-parietal theta-alpha synchronizations. Conclusions. Different meditation states do not influence bottom-up sensory pain processing. However, they significantly alter cognitive/affective pain mechanisms in state- and trait-dependent ways. In novice meditators, a positive emotional disposition during meditation can suppress the distribution and cognitive/affective appraisal of nociceptive signals. In expert meditators, effects of meditation states on pain processing are critically guided by advanced control of internal attention leading to fine-tuned involvement and functional segregation of cognitive control and attention networks.

Differential expression of spatiotemporal sleep spindle clusters in ageing
Objectives: Sleep spindles are potential biomarkers for memory decline in aging. However, significant within-person variability in spindle attributes complicates their utility in predicting cognitive deterioration. This study aimed to uncover distinct spindle types and their relevance to memory decline using data-driven clustering. Methods: Polysomnography was collected from younger (n = 43, ages 20-45 years) and older cognitively healthy adults (n = 34, ages 60-81 years). Spindles were clustered into four groups using multiple features and spatiotemporal context, irrespective of participant age. Results: Resulting clusters were hierarchically defined by the sleep stage, slow oscillation concurrence, and hemisphere. Stage N3 spindles (15%; predominantly coinciding with slow oscillations) formed a distinct group, followed by N2 spindles coinciding with slow oscillations (27%). Remaining N2 spindles were categorized into unilateral (41%) and bilateral clusters (17%). In older adults, there was a reduced proportion of N2 bilateral spindles and an increased proportion of N2 spindles concurrent with slow oscillations. Reduced proportion of N2 bilateral spindles was associated with better composite memory performance in younger adults, whereas higher spindle power, regardless of cluster belonging, was associated with reduced memory benefit from sleep compared with wakefulness. Conclusions: Our results indicate differing expression of spatiotemporal spindle clusters in older age, as well as intertwined dynamics between spindle propagation, SO concurrence, and frequency shifts in ageing. In addition, spindle heterogeneity aligned with global sleep stage dynamics. These results emphasize the interconnectedness of spindle activity with overall sleep patterns, underscoring the importance of spatiotemporal context within and across sleep stages.

Stimulant medications affect arousal and reward, not attention
Prescription stimulants such as methylphenidate are being used by an increasing portion of the population, primarily children. These potent norepinephrine and dopamine reuptake inhibitors promote wakefulness, suppress appetite, enhance physical performance, and are purported to increase attentional abilities. Prior functional magnetic resonance imaging (fMRI) studies have yielded conflicting results about the effects of stimulants on the brain's attention, action/motor, and salience regions that are difficult to reconcile with their proposed attentional effects. Here, we utilized resting-state fMRI (rs-fMRI) data from the large Adolescent Brain Cognitive Development (ABCD) Study to understand the effects of stimulants on brain functional connectivity (FC) in children (n = 11,875; 8-11 years old) using network level analysis (NLA). We validated these brain-wide association study (BWAS) findings in a controlled, precision imaging drug trial (PIDT) with highly-sampled (165-210 minutes) healthy adults receiving high-dose methylphenidate (Ritalin, 40 mg). In both studies, stimulants were associated with altered FC in action and motor regions, matching patterns of norepinephrine transporter expression. Connectivity was also changed in the salience (SAL) and parietal memory networks (PMN), which are important for reward-motivated learning and closely linked to dopamine, but not the brain's attention systems (e.g. dorsal attention network, DAN). Stimulant-related differences in FC closely matched the rs-fMRI pattern of getting enough sleep, as well as EEG- and respiration-derived brain maps of arousal. Taking stimulants rescued the effects of sleep deprivation on brain connectivity and school grades. The combined noradrenergic and dopaminergic effects of stimulants may drive brain organization towards a more wakeful and rewarded configuration, explaining improved task effort and persistence without direct effects on attention networks.

Western diet reversibly alters the olfactory mucosa and impairs the response to appetitive food cues
Current feeding behaviors contribute to the epidemic levels of obesity and diabetes observed in Europe and worldwide. Together with other sensory modalities, olfaction is involved in the control of food intake. Olfactory cues can influence eating behaviors, yet the nutritional status and diet can also alter olfactory abilities. Patients with metabolic disorders present impaired olfactory sensitivity which could in turn worsen their eating behaviors. Here we examined the short-term impact of a Western diet enriched in fat and sugar (High-Fat High-Sugar, HFHS) on the anatomy and physiology of the olfactory epithelium of mice. After 8 weeks of diet, HFHS fed animals presented higher adiposity without overweight, were glucose intolerant without any change in basal blood glucose or plasma insulin. A buried food test indicated impaired olfactory capacities in the HFHS group. Whereas food related odours increased food intake in control chow fed animals, HFHS mice showed an altered response to olfactory appetitive food cues. HFHS fed mice presented olfactory sensory neurons (OSN) with shorter cilia. Finally, electro-olfactogram (EOG) recorded in response to different odorant molecules showed lower amplitudes in HFHS fed mice. HFHS diet withdrawal during one month at the end of the HFHS diet exposure improved metabolic parameters and restored both the OSN cilia length and EOGs. Our results show that diet enriched in fat and sugar can rapidly alter the physiology of the olfactory epithelium before the development of significant metabolic disorders. Anatomical changes of individual olfactory sensory neurons may participate to the reduced olfactory sensitivity.

A Neurocognitive Shift in Midlife: Linking Cognitive Flexibility and Functional-Metabolic Adaptation with the SENECA model
Cognitive flexibility in the human brain engages dynamic interactions between the Default Mode Network (DMN) and the Fronto-Parietal Network (FPN), a functional architecture that is metabolically demanding and thus potentially susceptible to age-related decline. How the aging brain reorganizes its functional architecture to sustain cognitive flexibility under metabolic constraints remains an open question. In this study, we modeled resting-state functional flexibility across the adult lifespan (ages 18-88) using structural balance theory. Our findings align with the predictions of the SENECA model (Synergistic, Economical, Nonlinear, Emergent, Cognitive Aging), revealing a midlife neurocognitive transition: (i) from a metabolically costly, flexible DMN-FPN architecture, toward (ii) a more redundant configuration dominated by low-cost, sensory-driven interactions. The medio-parietal DMN and the Cingulo-Opercular Network (CON) are crucial to this transition, contributing to maintain global brain activity near a critical dynamic regime in older adulthood that optimizes for cognitive flexibility in face of declining metabolic resources. These findings advance a theoretical and methodological framework for understanding neurocognitive flexibility in aging and underscore the importance of multimodal fMRI-PET studies in midlife. They also open promising avenues for translational applications in neuropathology.

Neural Sharpening of Object Categories Through Parafoveal Priming
During natural vision, humans make saccades approximately every 250 - 300 ms to fixate on important objects in a scene. Given this rapid succession of eye movements, it has been proposed that visual processing begins in the parafovea, prior to fixation. Such parafoveal previewing may serve as a form of priming, facilitating subsequent processing at fixation. In this study, we investigated whether parafoveal priming leads to both a reduced neural response - akin to repetition suppression - and a more selective neural representation, consistent with neuronal sharpening. Participants performed a visual exploration task involving natural object images that were either parafoveally previewed or not, while magnetoencephalographic (MEG) data were recorded. Event-related fields revealed a reduced neural response when an image had been parafoveally presented 250 ms earlier. Moreover, multivariate pattern analysis showed enhanced decoding of object category following parafoveal priming, suggesting increased neural specificity. These findings support the idea that parafoveal previewing contributes to neural sharpening, potentially aiding evidence accumulation by forming sparse and precise representations of objects during visual scene exploration.

Off-target interaction of the amyloid PET imaging tracer PiB with acetylcholinesterase
Pittsburgh compound B (PiB) is a widely used Positron Emission Tomography (PET) tracer for detecting amyloid-{beta} (A{beta}) deposits in Alzheimer's disease (AD). While PiB is assumed to bind selectively to A{beta}, emerging evidence suggests off-target interactions that may complicate PET signal interpretation. Here, we report that PiB can interact with acetylcholinesterase (AchE), a key enzyme in the cholinergic system. Similarity screening identified the AchE ligand thioflavin T (ThT) as the top structural analog of PiB. Docking studies and molecular dynamics simulations showed that PiB stably binds the peripheral anionic site (PAS) of AchE, with binding energies comparable to ThT and clinically relevant AchE inhibitors. In vitro fluorescence-based assays confirmed this interaction and suggest an involvement of the PAS. These findings indicate a stable off-target interaction between PiB and AChE with implications for interpreting PiB-PET signals in AD, particularly in regions with altered AchE expression or under AchE inhibitor therapy.

Understanding the Neuro-Cognitive Mechanisms of Orthographic Learning in Humans and Baboons: A Comparative Study Using Domain-Specific Mechanistic and Domain-General Connectionist Models
Script is a key technology for humans, as mastering reading is essential for successful social participation. Hence, understanding the neuro-cognitive mechanisms underpinning the processes of learning to read is highly relevant. Here, we use two orthographic learning datasets from baboons and humans to investigate how they implement visual orthographic representations in a learning task of known and novel letter strings. We use two connectionist models (i.e., CORnet-Z and ResNet-18) and a mechanistic model (i.e., the Speechless Reader model, SLR) to investigate orthographic learning and infer the underlying neuro-cognitive processes. The connectionist models employ neuronally plausible architectures. The SLR versions are transparent neuro-cognitive models of orthographic decision behavior. Central to the SLR implementations are three types of prediction error representations that we use for computational phenotyping (i.e., pixel, letter, and letter-sequence level prediction errors). This approach allows us to infer the underlying representations in orthographic decisions. First, we fit the models and simulate the datasets to compare their performance (i.e., all models see the same sequence of stimuli as humans and baboons). Second, after comparing the model performance, we evaluate how the orthographic decisions have been implemented based on the representations used in the SLR models. We find that the SLR, especially on the trial-wise metrics, outperforms the CNNs in both datasets, with both connectionist models generating behavioral responses without a considerable overlap with individual human or baboon responses. Inspecting the SLR representations, we found that both species implemented the most informative representations that developed from visual to more complex orthographic representations with increased learning. Thus, we show that domain-specific neuro-cognitive mechanistic models are highly valuable in understanding complex behavior and how it is learned across species.

Energy and time trade-offs explain everyday human reaching movements
Humans reach for everyday objects such as pens and cups with stereotypically smooth, relaxed movements, explained in part by optimality. Maximizing accuracy can explain the smoothness and minimizing effort the relaxed timing. But these aspects combined do not optimize the whole, nor do they explain why people vary their timing depending on context, or reach smoothly even when accuracy is not demanded. These realities either challenge the notion of optimality or demand its redefinition. Here we propose that everyday reaching is predicted more generally by minimizing energy expenditure plus a weighted cost of time, adjustable for individual and context. A model of this Energy-Time objective simultaneously predicts human speed trajectories, durations, and peak speeds, without needing separate theories for each. The time valuation is identifiable from a single observation of one's time to reach a fixed distance, which then independently predicts how they reach any other distance. This single context-specific parameter can similarly predict reaches with low accuracy or speed demand unexplained by previous theories. The energy term is physiologically measurable and explains that smoothness and slowness are economical. The competing time cost explains how everyday movements can be modulated about an individualistic preference. Energy and time exert systematic influence on the speeds and durations of everyday movements.

Neural correlates of consciousness in an auditory no-report fMRI study
In the search for neural correlates of consciousness (NCC), prominent theories disagree about the role of sensory versus wide-spread fronto-parietal brain activity. Research on auditory awareness has been widely neglected, and isolating NCC from correlates of task-related post-perceptual processes (e.g., report) is an ongoing challenge. The present study addressed these issues using functional magnetic resonance imaging (fMRI) during a no-report inattentional deafness paradigm. Sixty-three participants performed an auditory distractor task while supra-threshold but task-irrelevant sounds were presented in the background. Whereas one group was aware of these stimuli, another group remained unaware. Comparing brain responses to the critical sounds between aware and unaware participants while controlling for correlates of sensory and postperceptual processing revealed that auditory awareness was associated with significantly increased activity in secondary auditory but not in fronto-parietal areas. These findings suggest a dominant role of stimulus-specific sensory processing rather than widespread fronto-parietal information broadcasting in conscious perception.

Weight-bearing symmetry changes after asymmetric surface stiffness walking
Stroke is a leading cause of adult disability in the United States, often presenting as hemiparesis. A priority in hemiparetic gait rehabilitation is the restoration of gait symmetry. While split belt treadmill training has shown promise in correcting spatial gait asymmetry, weight bearing and propulsion asymmetry remain resistant to improvement. As an alternative approach, we tested asymmetric surface stiffness walking to induce signatures of neuromotor adaptation relevant to correcting weight bearing and propulsion asymmetries in hemiparetic stroke. We hypothesized that a bout of asymmetric stiffness walking would elicit aftereffects in the form of asymmetries in weight bearing, propulsion, and plantar flexor activity. Twelve healthy young adults performed a 10-minute bout of asymmetric stiffness walking on an adjustable stiffness treadmill. We measured baseline and post-perturbation ground reaction forces (GRF) and spatio-temporal measures during 5-minute walking bouts on a dual-belt instrumented treadmill. After asymmetric surface stiffness walking, participants walked with increased vertical GRF and plantar flexor muscle excitations during push-off on the perturbed side relative to unperturbed. Participants also decreased their mid-stance vertical GRF and increased their peak braking GRF on the perturbed side relative to unperturbed. Counter to our hypothesis, they did not increase their propulsion GRF on the perturbed side. We conclude that asymmetric stiffness walking elicited a neuromotor adaptation towards a relative increase in push-off in the target limb, albeit primarily vertically aligned in our cohort of healthy young adults, and that gait adaptation to asymmetric stiffness walking should be investigated in individuals with push-off asymmetries.

Machine Learning Matches Human Performance at Segmenting the Human Visual Cortex
A major problem in human visual neuroscience research is the localization of visual areas on the cortical surface. Currently available methods are capable of making detailed predictions about many areas, but human raters do not agree as well with these methods as they do with each other. Although highly accurate, human raters require substantial time and expertise that many researchers do not have. Additionally, human raters require functional data for drawing visual area boundaries that requires additional scan time, budget, and expertise to collect. Here, we train convolutional neural network (CNN) models to predict the boundaries and iso-eccentric regions of V1, V2, and V3 in both the Human Connectome Project dataset and the NYU Retinotopy dataset. CNNs trained to use the same functional data available to human raters predicted these boundaries with an accuracy similar to humans, while CNNs trained to use only anatomical data had a lower accuracy that was nonetheless higher than that of any currently available method. A comparison of the model accuracies when predicting eccentricity-based boundaries and polar angle-based boundaries suggests that eccentricity is substantially less closely tied to anatomical structure than polar angle and that the cortical magnification function, at least in terms of eccentricity, varies substantially between subjects. We further find that the fraction of V1, V2, and V3 that can be accurately parcellated into function regions using gray matter structural data alone is ~75% (~80% of the inter-rater reliability of human experts), implying a much tighter coupling between structure and function in these areas than previously estimated. We conclude that machine learning techniques such as CNNs provide a powerful tool for mapping the brain with human accuracy and predict that such tools will become integral to neuroscience research going forward.

Succinate Modulation as a Novel Mechanism Underlying the Effects of Intermittent Fasting on Brain Function and Metabolism in Diet-Induced Obesity
Obesity significantly impacts the central nervous system (CNS), increasing risks of neuropsychiatric disorders and dementia. Intermittent fasting (IF) shows promise for improving peripheral and CNS health, but its mechanisms are unclear. Using a diet-induced obesity mouse model (10 weeks high fat diet (HFD), then 4 weeks intervention), we compared HFD, HFD-IF, ad libitum control chow (CC), and CC-IF groups. Switching to CC or IF reduced body weight, fat mass, and improved glucose tolerance. Notably, CC-IF uniquely enhanced exploration and reduced anxiety-like behavior. Transcriptomics revealed HFD-induced hippocampal neuroinflammation, while metabolomics identified a specific succinate signature in CC-IF mice: plasma concentration decreased while liver and brown adipose tissue (BAT) levels increased. Succinate supplementation mimicked CC-IF metabolic and behavioral benefits and reduced hippocampal inflammation. These findings suggest that regulating plasma succinate and its metabolism in liver and BAT may represent a novel mechanism underlying the metabolic, neuroinflammatory, and behavioral improvements induced by IF.

THC Reverses SIV-Induced Senescence in Astrocytes: Possible Compensatory Mechanism Against HIV Associated Brain Injury?
Despite effective combination antiretroviral therapy (cART), chronic neuroinflammation and glial dysfunction continues to be an important yet understudied issue with people living with HIV (PLWH). The endocannabinoid system is increasingly recognized as a potential therapeutic target for modulating neuroimmune environments, given its role in regulating synaptic plasticity, immune responses, and neuroinflammatory cascades. However, the extent to which cannabinoids influence HIV-associated neuroinflammation remains unclear. This study investigates the impact of {Delta}9-tetrahydrocannabinol (THC) on astrocyte growth characteristics, viability, and senescence-associated cytokine release following exposure to HIV Tat protein using primary mixed glial cultures derived from rhesus macaques. Real-time impedance-based cellular integrity assessments were conducted using the xCELLigence system, while morphological analyses and cytokine quantification were performed using phase-contrast microscopy and multiplex immunoassays. Treatment of macaques with THC protected the astrocytes from virus-induced senescence. Further, THC facilitated a rapid recovery from Tat-induced decline in astrocyte adhesion, suggesting a compensatory effect. THC promoted glial process elongation and morphological complexity, indicative of a shift toward a neuroprotective phenotype. Furthermore, THC significantly reduced inflammatory cytokine secretion, including TNF-, IL-6, and IL-1{beta}, in an apparently dose-dependent manner. These findings suggest that THC may modulate neuroinflammation in PLWH by promoting astrocytic survival, suppressing inflammatory cytokine secretion, and enhancing neurotrophic signaling. However, prolonged exposure to high-dose THC may negatively impact glial survival. The results underscore the complexity of cannabinoid signaling in the CNS and highlight the potential of cannabinoid-based interventions to mitigate HIV-associated neuroinflammation.

EEG entropy reflects both intrinsic and stimulation-induced corticospinal excitability
Background: Cortical excitability fluctuates throughout the day on multiple timescales, ranging from milliseconds to hours. This is reflected in the large variability of the brain's response to transcranial magnetic stimulation (TMS). However, robust and interpretable biomarkers of the brain's current excitability state are lacking. Objective: We investigated whether entropy derived from singular value decomposition of short electroencephalography (EEG) segments could serve as a biomarker of cortical excitability as probed by TMS. Methods: Entropy was computed from 1-second EEG segments preceding single-pulse TMS applied over the motor cortex. We assessed whether spontaneous fluctuations in pre-pulse entropy predicted trial-by-trial variability in TMS-induced motor-evoked potentials (MEPs). Additionally, we evaluated whether entropy tracked stimulation-induced changes in cortical excitability. Results: Higher pre-pulse entropy, particularly over frontal regions, was associated with larger MEP amplitudes. TMS locally increased entropy over the motor cortex, while entropy decreased in other regions during the intervention. Participants who showed greater local increases in entropy from pre- to post-intervention also demonstrated larger increases in corticospinal excitability. Conclusion: Entropy derived from short EEG segments reflects both intrinsic and stimulation-induced changes in cortical excitability. This marker may help optimize TMS interventions by informing brain state-dependent stimulation strategies and providing an index of intervention efficacy.

In vivo validation of novel non-invasive PHP.eB AAVs as a potential therapeutic approach for alpha-Synucleinopathies
Parkinson's disease (PD) is characterized by the accumulation of alpha-synuclein (aSyn) aggregates in specific brain regions, which are likely to be the disease-causing entities. Herein, we employed novel, systemically administered, brain-penetrating viral vectors (PHP.eB AAVs) to evaluate the potential therapeutic utility of lowering the endogenous aSyn protein burden in the aSyn pre-formed fibril (PFF)-mouse model. Such vectors expressing short hairpin RNAs or micro RNAs targeting the mouse Snca transcript (or respective scrambled control sequences) were intravenously administered in adult wild-type mice, and two weeks later, human aSyn PFFs were injected into the dorsal striatum. Following the administration of the Snca-targeting PHP.eB AAVs, a successful widespread viral transduction was achieved throughout the brain, accompanied by an efficient reduction of endogenous aSyn protein levels within transduced dopaminergic neurons. Intrastriatal injection of human aSyn PFFs led to the formation of pSer129-aSyn-rich cytoplasmic inclusions in brain regions connected to the PFF-injection site, nigrostriatal degeneration, and relevant behavioral motor deficits at 2.5 months post PFF-injection. Importantly, PHP.eB AAV-mediated down-regulation of endogenous aSyn reduced the accumulation of pSer129-aSyn+ inclusions, mitigated nigrostriatal degeneration, and alleviated motor impairments. Spread of pathology to other brain regions was also attenuated.

Chronic Treatment of a Mouse Model of Cerebral Amyloid Angiopathy and Brain AT1 Receptor Expression
Introduction: The renin-angiotensin-aldosterone system (RAAS) has been shown to be dysregulated in dementia, with elevated levels of angiotensin-converting enzyme (ACE), angiotensin (Ang) II, and Ang II type 1 receptors (AT1Rs). Cerebral amyloid angiopathy (CAA), a common cerebrovascular disease, currently has no treatment or cure available. We aimed to determine if a mouse model with CAA (Tg-SwDI) also exhibits elevated levels of AT1Rs and whether RAAS-targeting drugs (telmisartan and lisinopril) mitigate these effects. Materials and Methods: Tg-SwDI mice were treated with sub-depressor doses of either telmisartan or lisinopril from 3-8 months of age, with blood pressure being monitored 2 and 4 months after the start of treatment. Postmortem, receptor autoradiography was performed to determine levels of AT1R in 13 brain regions in untreated and treated Tg-SwDI mice compared to wild-type controls (C57Bl/6J). Results: No statistically significant differences among groups were observed in any of the 13 regions analyzed. However, trends with medium to large effect sizes were observed. Conclusions: CAA did not significantly dysregulate AT1R levels in the brains of Tg-SwDI mice compared to wild-type mice. Drug treatment caused no significant brain AT1R alterations. Further studies are required to determine if the trends observed are pathophysiological and pharmacologically significant.

Adaptive Evolution of Gene Regulatory Networks in Mammalian Neocortical Neurons
Mammals have evolved a plethora of adaptations that have enabled them to thrive in diverse environments. Among the most significant is the emergence of a more complex brain, exemplified by the dramatic transformation of the dorsal cortex from a single layer of excitatory projection neurons (ExNs) in ancestors to a multilayered cerebral neocortex enriched with diverse intratelencephalic (IT) and extratelencephalic (ET) ExN subtypes. These ExNs established specialized projection systems, such as the corticospinal tract and corpus callosum, enhancing brain connectivity and functionality. However, the evolutionary mechanisms underlying these mammalian-specific adaptations remain elusive. By comparing the landscape of gene expression and cis-regulatory elements (CREs) in mouse ExN subtypes and by cross-species examination of mammalian and non-mammalian CREs, we identified mammalian-specific CREs and expression patterns. The mammalian-specific CREs include a subset bound by ZBTB18 that are associated with genes defining IT and ET subtypes and connectivity. Both ZBTB18 and these target genes have previously been implicated in intellectual disability and autism. Deletion of Zbtb18 in mouse ExNs dysregulated target gene expression, reduced molecular diversity, diminished corticospinal and callosal projections, and increased intrahemispheric cortico-cortical association projections to the prefrontal cortex, resembling features of non-mammalian dorsal pallium. Interestingly, ZBTB18 binding motifs are highly enriched in callosally projecting IT-biased CREs, where they show higher conservation specifically in mammals. This study uncovers critical components and mammalian-specific evolutionary adaptations within a regulatory node essential for neocortical ExN identity and connectivity, with implications for neurodevelopmental and neuropsychiatric disorders.

An anthropoid/strepsirrhine divergence in ventral visual stream connectivity
The ventral visual stream has undergone extensive reorganisation within the primate lineage. While some work has examined restructuring of the ventral prefrontal cortical grey matter across primates, comparative studies of white matter connectivity are lacking primarily due to difficulties in data acquisition and processing. Here, we present a data-driven approach to the study of white matter connectivity using post-mortem diffusion MRI data. With this approach, we reconstruct anterior temporal-frontal and occipitotemporal-frontal connections across two anthropoids and one strepsirrhine: the rhesus macaque, the black-capped squirrel monkey, and the ring-tailed lemur. We find that the anthropoids exhibit more dorsal prefrontal innervation of these ventral visual connections. This study supports the hypothesis that anthropoid primates underwent extensive reorganisation of both grey and white matter during their emergence as visual foragers in a complex ecological niche. The data-driven techniques presented here enable further research on white matter connectivity in previously understudied species.

Differential patterns of cortical expansion in fetal and preterm brain development
The human cerebral cortex undergoes a complex developmental process during gestation, characterised by rapid cortical expansion and gyrification. This study investigates in vivo cortical growth trajectories using longitudinal MRI data from fetal and preterm cohorts. We employed anatomically constrained multimodal surface matching (aMSM) to quantify cortical surface area expansion and compare in-utero versus ex-utero cortical growth using cortical surface data from 22 to 45 weeks post-menstrual age (PMA), acquired as part of the Developing Human Connectome Project (dHCP). Our findings revealed distinct regional growth patterns during the 2nd and 3rd trimesters of fetal cortical expansion. Ex-utero brain development following preterm birth was shown to follow a modified trajectory compared to normal gestation, with potential implications for cortical organisation. Our methodology, combining biomechanically constrained surface registration with high quality fetal and neonatal imaging, provides a powerful framework for understanding early cortical development and deviations associated with preterm birth.

Neuromodulators control neuronal dynamics through feature space reshaping
The activity of neurons in the central nervous system changes drastically across different states like asleep or awake, attentive or drowsy, executing motor commands or resting. Neuromodulation supports these changes by affecting neuronal excitability. Much work has been devoted to understanding the effects of neuromodulators on various neurons. However, we still lack a cohesive picture of how neuromodulation affects neuronal dynamics. Here, we analyzed electrophysiological data from published papers and extracted features for seven types of neurons from five areas of the human and rodent central nervous system, under the effect of five neuromodulators. We studied neuromodulation dynamics using the widespread, simple, yet biologically accurate, Adaptive Exponential Integrate-and-Fire model. We have found that different neuromodulators remap the feature space of neurons into non-overlapping clusters. This work organizes our knowledge about neuromodulation in a compact format, useful for modelers and theoreticians alike.

Hippocampal time cell dynamics evolve with learning to reflect cognitive demands
The hippocampus creates cognitive maps, or internal representations that reflect knowledge of the external world. Hippocampal time cells are thought to represent the temporal structure of experiences, or temporal context. However, it remains unknown whether hippocampal time cells display learning dynamics that reflect increased knowledge of the temporal relationships that define a context. To address this gap, we utilized a behavioral paradigm with a shaping curriculum that allows animals to systematically acquire knowledge of temporal structure, ultimately enabling them to perform a temporal Delayed Non-Match to Sample (tDNMS) task. We conducted two-photon calcium imaging on large populations of CA1 neurons as mice progressed through the curriculum, from their initial exposure to the task structure to their successful discrimination of context at the end of training. Time cells were present from the outset, yet their activity evolved with experience, both at the single-cell level and across the population. Notably, at key moments in the curriculum, time cell dynamics adapted to reflect whether mice generalized across contexts or discriminated between them. Our findings suggest that CA1 time cells not only represent temporal context but may also reflect the processes by which temporal relationships are utilized. Hippocampal time cells therefore serve as a cognitive map, representing temporal relationships in a manner that reflects cognitive demands.

GEM-pRF: GPU-Empowered Mapping of Population Receptive Fields for Large-Scale fMRI Analysis
Population receptive field (pRF) mapping is a fundamental technique for understanding retinotopic organization of the human visual system. Since its introduction in 2008, however, its scalability has been severely hindered by the computational bottleneck of iterative parameter refinement. Current state-of-the-art implementations either sacrifice precision for speed or rely on slow iterative parameter updates, limiting their applicability to large-scale datasets. Here, we present a novel mathematical reformulation of the General Linear Model (GLM), wrapped in a GPU-Empowered Mapping of population Receptive Fields (GEM-pRF) software implementation. By orthogonalizing the design matrix, our approach enables the direct and fast computation of the objective function's derivatives, which are used to eliminate the iterative refinement process. This approach dramatically accelerates pRF estimation while maintaining full accuracy. Validation using empirical and simulated data confirms GEM-pRF's accuracy, and benchmarking against established tools demonstrates an order-of-magnitude reduction in computation time. With its modular and extensible design, GEM-pRF provides a critical advancement for large-scale fMRI retinotopic mapping. Furthermore, our reformulated GLM approach in combination with GPU-based implementation offer a broadly applicable solution that may extend beyond visual neuroscience, accelerating computational modelling across various domains in neuroimaging and beyond.

Pupil responses indicate task-relevance and (unsuccessful) inhibition of background sounds during a dual, continuous listening task
Auditory attention can be voluntarily directed towards a sound source or automatically captured by background sounds, which may be either relevant or irrelevant. The ability to switch focus to a relevant sound source while inhibiting an irrelevant one requires attentional control and is crucial for navigating busy auditory scenes. Objective measures of attentional control could be beneficial in clinical contexts, such as fitting hearing aids. In a dual-task paradigm, we investigated whether pupil responses reflect relevance-dependent selectivity and if this selectivity correlates with selective behavioral performance. Participants with self-reported normal hearing (N = 21, Age: 27 to 66 years, pure tone average: -4 to +26 dB HL) listened to continuous speech from the front (primary task) while background sounds, consisting of a name followed by a two-digit number, were presented from the left and right. The secondary task involved memorizing and later recognizing numbers from either the right or left side (i.e., relevant). We observed increased pupil responses to sounds from the relevant side compared to the irrelevant side, indicating selectivity. Additionally, participants who exhibited stronger selectivity recognized more numbers correctly. Interestingly, pupil responses did not differ between hits and misses, but a stronger response to stream confusions versus correct rejections was found, suggesting that participants were more challenged by inhibiting irrelevant sounds than shifting attention to relevant sounds. In sum, our findings demonstrate that pupillometry provides valuable insights into attentional control abilities.

Mapping satellite glial cell heterogeneity reveals distinct spatial organization and signifies functional diversity in the dorsal root ganglion
Satellite glial cells (SGCs) envelop the somata, axon hillock, and initial axon segment of sensory neurons in the dorsal root ganglia (DRG), playing a critical role in regulating the neuronal microenvironment. While DRG neurons have been extensively studied and classified based on size, molecular markers, and functional characteristics, very little is still known about SGC heterogeneity and its potential implications on sensory processing in the DRG. Single cell transcriptional analyses have proposed the existence of SGC subtypes, yet in situ validation, spatial distribution, and potential functional implications of such subtypes are still largely unexplored. Here, we present the first comprehensive in situ characterization of SGC heterogeneity within the mouse DRG. By integrating single-cell RNA sequencing with immunohistochemistry, in situ hybridization, and advanced imaging techniques, distinct SGC subclusters were identified, validated, and spatially mapped within their native anatomical context. We visually identify four distinct subpopulations: 1) a predominant population of perisomatic SGC sheaths defined by the expression of marker proteins traditionally used to characterize the entire SGC population, including FABP7, KIR4.1, GS, and CX43. 2) OCT6+ SGCs occasionally being found in mosaic perisomatic sheaths, and consistently associated with axonal glomeruli, primarily ensheathing initial segment axon. 3) SCN7A+ SGCs, exhibiting no/low expression of traditional SGC markers and forming specialized homogenous sheaths around non-peptidergic neuron subtypes, implicating their potential role in pruritic (itch-related) conditions. 4) Interferon response gene-expressing SGCs, responding to Herpes Simplex Virus infection, suggesting potential involvement in antiviral protection. Finally, we investigate human DRG and find an inner perisomatic SGC layer surrounded by an outer SGC layer, with traditional and novel markers distinctively distributed between the two layers. Our results provide novel insight into SGC heterogeneity in the DRG and suggests distinct functional properties for such subtypes of relevance for the neuronal microenvironment.

Basophils activate splenic B cells and Dendritic cells via IL-13 signaling in acute Traumatic Brain Injury
Peripheral consequences following traumatic brain injury (TBI) are characterized by both systemic inflammatory responses and autonomic dysregulation, with almost all peripheral organs affected. One of the main immune regulatory organs, the spleen, shows high interaction with the brain which is controlled by both circulating mediators as well as autonomic fibers targeting splenic immune cells. The brain-spleen axis does not function as a one-way street, it also shows reciprocal effects where the spleen affects neuroinflammatory and cognitive functions post injury. To date, systemic and splenic inflammatory responses are measured by cells or mediators located in circulation. Nevertheless, most of the signaling and inflammation post injury takes place in the organs. Therefore, we set out to investigate the early signaling landscape in the spleen following TBI, using phospho-proteomic signaling approaches and immunofluorescence stainings to investigate novel molecular and cellular players. Based on the signaling signature, we found a rapid influx of basophil granulocytes towards the spleen, which are recruited via CXCL1 expressed by B-cells and dendritic cells. The basophils activate B cells and dendritic cells (DCs) via the IL-13/IL-13Ra1 signaling pathway to enhance protein translation through the long non-coding RNA NORAD. The early recruitment of basophils and subsequent activation of B cells and DCs, is short lived and sets at 3dpi. Interestingly, the rapid recruitment of basophils is inhibited by ethanol intoxication in TBI. In conclusion, basophils recruitment to the spleen may serve as an early mediator of systemic inflammatory responses to TBI with potential implications for research on biomarkers and therapeutic targets.

Estradiol treatment enhances neurovascular coupling independent of metabolic health status in a mouse model of menopause
The loss of ovarian estrogen during the menopause transition has been identified as a risk factor for increased cardiometabolic and neurovascular dysfunction, age-related cognitive decline, and Alzheimer's disease. A wealth of studies using rodent models of menopause have highlighted the cardio- and neuroprotective effects of 17{beta}-estradiol (E2) treatment when administered within a critical period, though these have yet to be successfully translated to human populations in clinical trials of hormone therapy. A proposed explanation for this mismatch in results is the "healthy cell bias," where estrogen is only beneficial when initiated in physiologically intact systems. Our study investigates whether pre-existing metabolic dysfunction attenuates the effects of E2 on neurovascular coupling (NVC) in a rodent model of menopause. Female mice were fed a high-fat diet (HFD) or control diet (CD) for 11 weeks to induce metabolic dysfunction, followed by ovariectomy (OVX) and subsequent E2 or vehicle (Veh) treatment. NVC was assessed in awake mice using two-photon laser scanning microscopy of penetrating arterioles (PAs) in the somatosensory cortex, barrel field. Mice developed glucose intolerance and increased adiposity yet displayed intact NVC following 11 weeks of HFD exposure. Following ovariectomy, E2 treatment enhanced NVC responses regardless of diet. Interestingly, in HFD-fed mice, E2 appeared to reduce basal PA diameter relative to Veh, suggesting health status-specific mechanisms of action. These results indicate that PAs retain functional sensitivity to estrogen treatment in the face of metabolic impairment, which has implications for the use of hormone therapy in women that arrive at the menopause transition with varied pre-existing cardiometabolic disorders.

Antibodies raised against a structurally defined Aβ oligomer mimic protect human iPSC neurons from Aβ toxicity at sub-stoichiometric concentrations
Anti-A{beta} antibodies are important tools for identifying structural features of aggregates of the A{beta} peptide and are used in many aspects of Alzheimer's disease (AD) research. Our laboratory recently reported the generation of a polyclonal antibody, pAb2AT-L, that is moderately selective for oligomeric A{beta} over monomeric and fibrillar A{beta} and recognizes the diffuse peripheries of A{beta} plaques in AD brain tissue but does not recognize the dense fibrillar plaque cores. This antibody was generated against 2AT-L, a structurally defined A{beta} oligomer mimic composed of three A{beta}-derived {beta}-hairpins arranged in a triangular fashion and covalently stabilized with three disulfide bonds. In the current study, we set out to determine if pAb2AT-L is neuroprotective against toxic aggregates of A{beta} and found that pAb2AT-L protects human iPSC-derived neurons from A{beta}42-mediated toxicity at molar ratios as low as 1:100 antibody to A{beta}42, with a ratio of 1:25 almost completely rescuing cell viability. Few other antibodies have been reported to exhibit neuroprotective effects at such low ratios of antibody to A{beta}. ThT and TEM studies indicate that pAb2AT-L delays but does not completely inhibit A{beta}42 fibrillization at sub-stoichiometric ratios. The ability of pAb2AT-L to inhibit A{beta}42 toxicity and aggregation at sub-stoichiometric ratios suggests that pAb2AT-L binds toxic A{beta}42 oligomers and does not simply sequester monomeric A{beta}42. These results further suggest that toxic oligomers of A{beta}42 share significant structural similarities with 2AT-L.

Single-cell transcriptome of retinal myeloid cells in response to transplantation of human neurons reveals reversibility of microglial activation
The host retinal microglia and macrophage activation remains a major challenge for the integration of donor neurons following transplantation. Previously, we and others have shown that it is possible to increase donor retinal ganglion cell (RGC) survival by inhibiting the microglia-RGC interaction with Annexin V or through reprogramming microglia with the soluble Fas ligand. However, the exact mechanisms of the microglia/macrophage activation and their heterogeneity following transplantation remain unknown. To address this question, the donor RGC were differentiated from Brn3b-Tdtomato-Thy1.2 human embryonic stem cells using a 3D protocol, followed by dissociation and RGC purification. RGC were delivered subretinally (1.5x104 viable cells/eye) into 3-6-month-old CX3CR1GFP knock-in mice. Three days after transplantation retinas were dissociated into single-cell suspension and GFP-positive myeloid cells isolated using FACS. Of the sorted cells, up to 10,000 viable cells per sample were used for single-cell RNA library preparation and sequenced using the 10X Genomics Chromium platform. In addition, several retinas were fixed and stained for donor RGC (mCherry) and host microglia/macrophages (Iba1). RNA Velocity was used to reconstruct the myeloid cell population and activation trajectory from scRNAseq data. We observed continuous bi-directional transition of microglia/macrophages from a homeostatic to an activated state. We also observed that the response to the transplant falls into the classic disease-associated-microglia (DAM) activation paradigm with a decrease in expression of the homeostatic gene Tmem119 and an increase in expression of disease-associated genes including Apoe, Lgals3, and Spp1. Our findings show that the host retinal myeloid cell population undergoes activation upon transplantation of stem-cell derived donor RGC, with a molecular profile of the activated cells similar to that of activated myeloid cells associated with neurodegenerative diseases of the brain and the eye. Advanced integrated transcriptomic analysis shows separate activated-to-homeostatic and homeostatic-to-activated trajectories suggesting the reversibility of this process.

Inhibitory Circuit Compensations in Female and Male Mice: Increased Synaptic Output Offsets Reduced Parvalbumin Interneuron Density
Parvalbumin inhibitory interneurons (PV-INs) are critical regulators of excitatory/inhibitory balance in the cortex, and their dysfunction has been observed in various neurological disorders. Despite increasing recognition of sex differences in brain function, little is known about how PV-INs differ between males and females under healthy conditions. Previous work has pointed to sex differences in PV-IN vulnerability in disease and injury models. Here, we investigated sex differences in PV-IN characteristics, connectivity, and function in the retrosplenial cortex (RSC) of healthy mice. We found that female mice have significantly fewer PV-INs in the RSC compared to males, yet exhibit comparable memory induced neuronal activation (fos expression). Despite their lower numbers, female PV-INs displayed greater synaptic connectivity, as evidenced by increased synaptotagmin-2 (Syt-2) puncta per PV-IN and higher axonal bouton density. Additionally, fewer female PV-INs were surrounded by perineuronal nets (PNNs), suggesting greater plasticity in female inhibitory networks. From ex vivo slice electrophysiology recordings we observed greater excitability in female PV-INs compared to male PV-INs and, a reduced incidence of IPSCs. These findings indicate that female mice may compensate for reduced PV-IN numbers through enhanced synaptic output, preserving inhibitory function in the RSC. Finally, using spatial transcriptomic profiling of PV-INs we observed a number of differentially expressed genes that are consistent with the observed structural and functional differences between female and male PV-INs. Understanding these sex-specific inhibitory mechanisms is crucial for developing more targeted interventions for conditions involving PV-IN impairment and for understanding sex specific vulnerabilities to certain conditions such as Alzheimer's disease.

Repetitive Levodopa Treatment Drives Cell Type-Specific Striatal Adaptations Associated With Progressive Dyskinesia in Parkinsonian Mice
The use of levodopa to manage Parkinson disease (PD) symptoms leads to levodopa-induced dyskinesia (LID) and other motor fluctuations, which worsen with disease progression and repeated treatment. Aberrant activity of striatal D1- and D2-expressing medium spiny neurons (D1-/D2-MSNs) underlies LID, but the mechanisms driving its progression remain unclear. Using the 6-OHDA mouse model of PD/LID, we combined in vivo and ex vivo recordings to isolate the effect of repeated treatment in LID worsening and other motor fluctuation-related phenotypes. We found that LID worsening is linked to potentiation of levodopa-evoked responses in both D1-/D2-MSNs, independent of changes in dopamine release or MSN intrinsic excitability. Instead, strengthening of glutamatergic synapses onto D1-MSNs emerged as a key driver. Moreover, we found changes in D2-MSN activity that specifically influenced LID duration, potentially contributing to motor fluctuations, which paralleled a reduction in D2R sensitivity. These findings reveal striatal adaptations contributing to worsening of levodopa-related complications.

Distinct subtypes of astrocytes selectively regulate specific inhibitory synapses
Astrocyte functional heterogeneity within a given neuronal circuit remains largely undetermined, particularly their role at tripartite synapses. Here, we examine multiple functional characteristics of astrocytes distinguished by their specific spatial relation to inhibitory synapses made on distinct hippocampal CA1 pyramidal cell domains: astrocytes covering the peri-somatic area in stratum pyramidale (SP) receiving input from Parvalbumin interneurons, or the apical dendritic area in stratum radiatum (SR) innervated by inhibitory inputs from Somatostatin interneurons. Whole-cell dye-filling and confocal imaging of SR astrocytes showed a typical bushy organization of processes while those of SP astrocytes were more polarized, indicating astrocyte morphological heterogeneity. In addition, SP astrocytes formed a smaller, yet polarised syncytium and displayed greater input resistance relative to SR astrocytes. The two populations of astrocyte are functionally different as indicated by their intrinsic Ca2+ signaling properties: SP astrocyte Ca2+ events had a lower frequency and temporal density, but greater amplitude, relative to SR astrocytes. Using the territorial segregation of inhibitory synapses, we observed that the selective activation using DREADD or blockade with intracellular BAPTA of the two populations of astrocytes regulated inhibitory synapses exclusively in their own syncytial territory. Furthermore, each astrocyte population selectively mediated long-term depression at the respective inhibitory synapses through Ca2+- dependent modulation of post-synaptic targets. These results indicate domain-specific regulation of inhibitory synapses by distinct SP and SR astrocyte syncytia. Transcriptional analysis revealed enriched gene expression in SP relative to SR astrocytes, notably for regulation of cell growth and morphology, synaptic function and signaling. Overall, our findings reveal a functional specialization of astrocyte subtypes in the hippocampus, highlighting heterogeneous astrocyte regulation of hippocampal synaptic networks important for learning and memory.

Age-related auditory nerve deficits propagate central gain throughout the auditory system: Associations with cortical microstructure and speech recognition
There is growing evidence that many perceptual difficulties associated with age-related hearing loss are not solely due to cochlear damage and are exacerbated by changes within the central nervous system. We examined electrophysiological (EEG) responses to clicks and diffusion kurtosis imaging (DKI) in 49 older (29 female) and 26 younger (20 female) adults to determine the extent to which auditory nerve (AN) deficits in older adults contributed to functional and structural changes throughout the auditory system. Older adults exhibited smaller AN responses, similar brainstem responses, and larger auditory cortex (AC) responses, demonstrating progressive central gain. Audiometric thresholds were not predictive of EEG measures. Reduced AN function predicted deficits in cortical microstructure (lower AC fractional anisotropy, FA) in older adults, consistent with myelin degeneration. These lower FA values in the AC of older adults also predicted larger AC responses and more central gain. Older adults exhibited significantly lower AC FA and higher mean diffusivity (MD) than younger adults, and AC FA and MD were significant predictors of speech-in-noise (SIN) recognition in older adults. The results suggest that reduced afferent input in older adults not only results in functional changes throughout the auditory system consistent with progressive gain, but also contributes to deficits in AC structure beyond those explained by age alone, contributing to SIN deficits. Understanding the complex effects of age, reduced AN input, central gain, and AC structure on SIN recognition may provide potential therapeutic targets for intervention.

Assessing the robustness of deep learning based brain age prediction models across multiple EEG datasets
The increasing availability of large electroencephalography (EEG) datasets enhances the potential clinical utility of deep learning (DL) for cognitive and pathological decoding. However, dataset shifts due to variations in the population and acquisition hardware can considerably degrade the model performance. We systematically investigated the generalisation of DL models to unseen datasets with different characteristics, using age as the target variable. Five datasets were used in two different experimental setups, including (1) leave-one-dataset-out (LODO) and (2) leave-one-dataset-in (LODI) cross validation. A comprehensive set of 1805 different hyperparameter configurations was tested, including variations in the DL architectures and data pre-processing. The performance varied across source/target dataset pair. Using LODO, we obtained Pearson's r values of {0.63, 0.84, 0.75, 0.23, 0.10} and R^2 values of {-0.01, 0.63, 0.41, -4.66, -70.98}. For LODI, the results varied in Pearson's r from -0.11 to 0.84 and R^2 values from -704.89 to 0.65, depending on the source and target dataset. Adjusting the model intercepts using the average age of the target dataset substantially improved some R^2 scores. Our results show that DL models can learn age-related EEG patterns which generalise with strong correlations to datasets with broad age spans. The most important hyperparameter was to use the frequency range between 1 and 45Hz, rather than a single frequency band. The second most important hyperparameter effect depended on the experimental setup. Our findings highlight the challenges of dataset shifts in EEG-based DL models and establish a benchmark for future studies aiming to improve the robustness of DL models across diverse datasets.

Neural mechanisms for visuomotor co-regulation in social synchronization
During social activities, people coordinate their movements by exchanging visuomotor information. Interpersonal coordination occurs from two complementary processes entailing voluntary (planned) and spontaneous (emergent) synchronization, of which neurofunctional underpinnings are unknown. We investigated the brain correlates of these two synchronization processes during an fMRI finger-tapping task. Dyads formed by IN and OUT scanner participants were instructed to reproduce a target tempo and concurrently try to synchronize to (Joint Action, JA) or resist synchronization with (Non-interactive, NI) the partner's tapping, whose hand was always visible to the IN participant. Faster, slower, or equal tempi were used to induce within-dyad co-regulation. Results revealed the emergence of tempo contagion: participants tapped faster in response to the partner's faster taps and vice versa for slower taps. The magnitude of such an interpersonal contagion effect was similar across conditions but associated with the activity of different neural structures. Tempo contagion correlated positively with lateral occipitotemporal cortex (LOTc) activations in the JA condition but negatively with cerebellar activations in the NI condition. This suggests visuomotor information is exploited in opposite ways depending on the task instructions: the LOTc promotes co-regulation to achieve synchronization in JA, whereas the cerebellum prevents tempo contagion to preserve individual stability in NI. This latter result is supported by a negative functional connectivity between the cerebellum and LOTc. These findings have implications for understating the interplay between planned and emergent synchronization during motor interactions.

Perivascular space mediated the interaction between sleep, and brain functional connectivity in the healthy aging population
Perivascular space (PVS) surrounds the perforating arteries or draining veins of the cerebral cortex as part of the brain clearance system. Previous studies showed that sleep affects both brain clearance function and brain functional connectivity (FC). However, the impact of PVS characteristics on brain FC remains unclear. This study investigated these associations and their link to cognition. We utilized cross-sectional structural MRI and resting state-fMRI data from 512 health aging population in the HCP-Aging dataset, together with Pittsburgh Sleep Quality Index questionnaire and NIH cognitive tests. Our results showed that basal ganglia (BG)-PVS volume fraction (VF) was positively correlated with FC in the right anterior medial temporal gyrus (aMTG) and right temporal regions, while centrum-semiovale (CSO)-PVS VF was positively correlated with FC in the left hippocampus and right frontal regions. Increased CSO-PVS VF in early middle-aged adults showed higher hippocampal FC and better cognitive performance. Interestingly, individuals with longer time spent in bed had larger BG-PVS VF linked to higher FC in the right aMTG. Additionally, older adults with better sleep quality had larger BG-PVS VF linked to higher FC in the right aMTG. These findings suggest that PVS morphology may reflect changes in neural connections involved in memory-related regions.

The anterior olfactory nucleus mediates curious exploration evoked by novel odors
The spontaneous exploratory reaction to novel stimuli reflects a fundamental form of curiosity, which is widely observed in the animal kingdom. How sensory systems mediate the recognition of novel stimuli to evoke exploration is not well understood. To address this question, we presented novel and familiar olfactory stimuli to head-restrained mice, while measuring novelty-evoked exploratory behaviors. In parallel, we recorded neural activity in primary olfactory cortical structures, the anterior olfactory nucleus (AON) or the anterior piriform cortex (aPCx). Novelty strongly modulated odor responses in the AON, but only weakly in the aPCx. Pharmacological and chemogenetic inactivation of the AON but not the aPCx disrupted exploratory responses. During long-term habituation over multiple days, sensory representations were drifting in the AON whereas they became stable within one day in the aPCx. Our findings suggest that AON and aPCx play distinct roles in novelty-evoked exploration. While the AON mediates the immediate reaction to novel stimuli, the aPCx exhibits stable stimulus representations, consistent with supporting odor memory.

DJ-1 deficiency and aging: dual drivers of retinal mitochondrial dysfunction.
We have previously extensively characterized the role of DJ-1 in oxidative stress regulation in the retina and RPE during aging. However, the DJ-1 protein also plays a role in regulating mitochondria's response to oxidative stress by translocating to the mitochondria where it helps clear generated reactive oxygen species (ROS). To study the effects of aging and oxidative stress in the retina, the DJ-1 KO mouse was analyzed. Freshly dissected ex vivo retinal punches were analyzed for real-time live cell metabolism. Total DNA and protein were isolated from RPE, and retina of 3- and 15-month-old DJ-1 WT and DJ-1 KO mice. The mitochondrial DNA (mtDNA) genome was divided into four discrete regions (RI-RIV), and lesions/10kb were quantified using long-extension PCR. mtDNA content was analyzed using RT-qPCR. Protein levels of OXPHOS complexes, POLG, OGG1, SOD2, and PGC1a; were measured by western blotting. Seahorse analysis detected significantly decreased basal and maximal OCR in 3- and 15-month-old DJ-1 KO compared to age-matched DJ-1 WT. In the RPE, a significant decrease in the protein levels of the NDUFB8 subunit of CI, the SDHB subunit of CII, and MTCO1 of CIV in 15-month-old DJ-1 KO mice compared to 15-month-old DJ-1 WT, while the ATP5A subunit of CV was significantly decreased in 3-month-old DJ-1 KO mice compared to 3-month-old DJ-1 WT. In the retina, significantly decreased levels of NDUFB8 subunit of CI and MTCO1 of CIV were detected in the in 3-month-old DJ-1 KO mice compared to 3-month-old DJ-1 WT. We observed a significant increase in mtDNA gene content in 15-month-old DJ-1 KO RPE and retina compared to age-matched DJ-1 WT. The PGC1a; levels significantly decreased in 3- and 15-month-old RPE lysates compared to their age group DJ-1 WT. However, in the retina, there was only a decrease in DJ-1 WT with aging. The POLG levels increased when 15-month-old DJ-1 KO lysates were compared to 15-month-old DJ-1 WT. The mtDNA lesions in the RPE detected a trend of increase in 15-month-old DJ-1 WT and DJ-1 KO RPE in all regions compared to 3-month-old mice. In the retina, a significant increase in mtDNA lesions/10kb accumulation in the 15-month-old DJ-1 WT RIV was detected compared to 3-month-old DJ-1 WT. The OGG1 levels significantly increased in 3-month-old retinal lysates compared to the 3-month-old DJ-1 WT. Our findings suggest that DJ-1 is critical for mitochondrial regulation and function in RPE and retina. The observed changes reflect mitochondrial dysfunction related to absence of DJ-1.

Age as a moderator variable in the investigation of the relationship between brain structure and cognition
Understanding how differences in brain structure relate to differences in cognition across the lifespan is essential for addressing age-related cognitive decline. Since age is strongly associated with both brain structure and cognition, predictive models often risk simply capturing age effects. To mitigate this risk, deconfounding is typically applied to remove the linear effects of age. Here, we propose to treat age instead as a moderator variable, therefore capturing changes in how brain structure and cognitive abilities are statistically connected. For this view to hold, variations in brain structure linked to differences in cognitive performance in older subjects (e.g. related to disease) would differ from those in younger subjects. Using structural brain imaging data from the UK Biobank, we found evidence supporting this, and that the generalisability of prediction models depends on the age group used to train the model. These findings highlight the complex nature of age-related brain-cognition interactions, and suggest that the optimal modelling approach depends on the population under study.

Youth-associated protein TIMP2 alters microglial state and function in the context of aging
There is little understanding of how aging serves as the strongest risk factor for Alzheimer's disease (AD) and other neurological disorders. Specific neural cell types, such as microglia, undergo maladaptive changes with age, including increased inflammation, impaired debris clearance, and cellular senescence, yet specific mediators that regulate these processes remain unclear. The aged brain is rejuvenated by youth-associated plasma factors, including tissue inhibitor of metalloproteinases 2 (TIMP2), which we have shown acts on the extracellular matrix (ECM) to regulate synaptic plasticity. Given emerging roles for microglia in regulating plasticity and brain ECM dynamics, we examined the impact of TIMP2 on microglial function in the setting of aging. We show that TIMP2 deletion exacerbates microglial phenotypes associated with aging, including transcriptomic changes in cell activation, increased microgliosis, and increased levels of stress and inflammatory proteins measured in the brain extracellular space by in vivo microdialysis. Deleting specific cellular pools of TIMP2 in vivo increased microglial activation and altered myelin phagocytosis. Treating aged mice with TIMP2 reversed several phenotypes observed in our deletion models, resulting in decreased microglial activation, reduced proportions of proinflammatory microglia, and enhanced synapse phagocytosis. Our results identify TIMP2 as a key modulator of age-associated microglia dysfunction. Harnessing its activity may mitigate detrimental effects of age-associated insults on microglia function.

Sound offset responses become highly informative in the auditory cortex
The entire auditory system downstream of the cochlea features pronounced offset responses, which follow the termination of sounds. Because of their ubiquity, it is still an unsolved question whether offset responses are generated early in the auditory system and then propagated or recomputed at each processing stage. Here, we analysed large-scale sound responses datasets acquired in the cochlear nucleus, inferior colliculus, medial geniculate nucleus and auditory cortex of awake mice. All brain regions showed a significant proportion of offset responses often combined with onset and sustained responses in the same neuron. However, using population activity decoders, we observed that neural representations after the sound offset show a three-fold increase in sound encoding accuracy in the cortex relative to subcortical areas. This result indicates that cortical offsets encode a more precise short-term memory of the elapsed sound than subcortical offsets and that they likely result from specific computational steps.

Frequency-dependent diffusion tensor distribution imaging in the evaluation of ischemic stroke
Non-invasive magnetic resonance imaging (MRI) is considered the gold standard for the prognosis and monitoring of ischemic stroke. Still, the conventional methods used in clinics often fail to detect subtle changes and estimate tissue viability in the lesion, penumbra and distal regions. In this study, we combined frequency-dependent distribution tensor imaging ({omega}DTD) and clustering of the frequency dependent diffusion tensor distributions D({omega}) with multivariate regression modelling in a whole brain section to interpret ischemic changes in quantitative tissue microstructural parameters. We performed ex vivo {omega}DTD and histology in middle cerebral artery occlusion (MCAO) and sham-operated rats (P = 17) 24 hours post reperfusion. The lesions were characterised by cell loss and a presence of smaller cells, most likely glial cells. A random forest (RF) model was used to explain and predict the histological parameters based on diffusion tensor imaging (DTI), manually bin-resolved and cluster-resolved {omega}DTD parameters. Cross-validation with leave-one-animal-out (CV LOO) was used to evaluate our model. We found that {omega}DTD parameters were more representative of the number of cells compared to diffusion tensor imaging (DTI) metrics ({omega}DTD R^2 = 0.73 vs DTI R^2 = 0.49 with CV {omega}DTD R = 0.23 vs DTI R = 0.33), area and circularity of nucleus ({omega}DTD R^2 = 0.64 vs DTI R^2 = 0.40 and {omega}DTD R^2 = 0.61 vs DTI R^2 = 0.35 with CV {omega}DTD R = 0.13 vs DTI R = 0.26 and {omega}DTD R = 0.17 vs DTI R = 0.31) than DTI. We also found that a more flexible modelling approach, such as RF, was advantageous to represent the complex, non-linear relationship between MRI and tissue. In conclusion, this study shows that {omega}DTD, along with advanced machine learning methods, has the potential to help improve the understanding and interpretation of ischemic stroke related tissue damage in terms of advanced MRI.

Absence of testes at puberty impacts functional development of nigrostriatal but not mesoaccumbal dopamine terminals in a wild-derived mouse
The nigrostriatal and mesoaccumbal dopamine systems are thought to contribute to changes in behavior and learning during adolescence, yet it is unclear how the rise in gonadal hormones at puberty impacts the function of these systems. We studied the impact of prepubertal gonadectomy on evoked dopamine release in male Mus spicilegus, a mouse whose adolescent life history has been carefully characterized in the wild and laboratory. To examine how puberty impacts the dopamine systems in M. spicilegus males, we removed the gonads prepubertally at P25 and then examined evoked dopamine release in the dorsomedial, dorsolateral, and nucleus accumbens core regions of striatal slices at P60-70. To measure dopamine release, we used near-infrared catecholamine nanosensors (nIRCats) to enable study of spatial distribution of dopamine release sites in each striatal region. We found that prepubertal gonadectomy led to a significantly reduced density of dopamine release sites and reduced dopamine release at each site in the dorsolateral nigrostriatal system compared to sham controls. By contrast, mesoaccumbal dopamine release was comparable between sham and gonadectomized groups. Our data suggest that during adolescence the development of the nigrostriatal dopamine system is significantly affected by the rise in gonadal hormones in males, while the mesoaccumbal system shows no detectable sensitivity at this time point. These data are consistent with molecular studies in rodents that suggest nigrostriatal neurons are sensitive to androgens at puberty, and extend our understanding of how gonadal hormones could impact the spatial distribution and release potential of dopamine terminals in the striatum.

A comprehensive mechanosensory connectome reveals a somatotopically organized neural circuit architecture controlling stimulus-aimed grooming of the Drosophila head
Animals respond to tactile stimulations of the body with location appropriate behavior, such as aimed grooming. These responses are mediated by mechanosensory neurons distributed across the body, whose axons project into somatotopically organized brain regions corresponding to body location. How mechanosensory neurons interface with brain circuits to transform mechanical stimulations into location-appropriate behavior is unclear. We previously described the somatotopic organization of bristle mechanosensory neurons (BMNs) around the Drosophila head that elicit a sequence of location-aimed grooming movements (Eichler et al., 2024). Here, we use a serial section electron microscopy reconstruction of a full adult fly brain to identify nearly all of BMN pre- and postsynaptic partners, uncovering circuit pathways that control head grooming. Postsynaptic partners dominate the connectome, and are both excitatory and inhibitory. We identified an excitatory hemilineage of cholinergic interneurons (hemilineage 23b) that elicit aimed head grooming and exhibit varied connectivity to BMNs from different head locations, revealing lineage-based development of a somatotopic parallel circuit architecture. Presynaptic partners provide extensive BMN presynaptic inhibition, consistent with models of sensory gain control as a mechanism of suppressing grooming movements and controlling the sequence. This work provides the first comprehensive map of a somatotopically organized connectome, and reveals how this organization could shape grooming. It also reveals the mechanosensory interface with the brain, illuminating fundamental features of mechanosensory processing, including feedforward excitation and inhibition, feedback inhibition, somatotopy based circuit organization, and developmental origins.

Intersecting effects of social circumstances and transcendent thinking on mid-adolescents' longitudinal functional connectome development
Socially moderated variation in mid-adolescents' functional brain network (FBN) development is insufficiently studied, especially within low-SES contexts. Alongside demographic factors, evidence suggests adolescents' malleable psychological dispositions may contribute, with possible clinical and educational implications. We applied graph theory to a unique 2-year longitudinal fMRI dataset (N=65) with an ecologically valid 2-hour interview revealing an emergent mid-adolescent psychological disposition, transcendent thinking (TT): adolescents' tendency to consider systems-level, ethical, personal implications of social information. Overall, FBNs showed increased segregation and entropy but decreased integration and energy. Modularity increased particularly in somatosensory subnetworks. Classifying participants by two key demographic factors, parents' education (PE) and community violence exposure (CVE), FBN changes differed by group, and TT moderated changes in high-CVE/low-PE participants, arguably the most vulnerable group. Machine learning revealed TT and CVE, but not IQ, as principal FBN change predictors across groups. Findings suggest social context and psychological dispositions influence low-SES adolescents' FBN development.

Shared and distinct cortical mechanisms for working memory and decision-making.
The dorsolateral prefrontal cortex (DLPFC) and lateral intraparietal cortex (LIP) in the primate brain are critically involved in working memory during tasks that require the retention of information over a delay. These same regions have also been implicated in reinforcement learning (RL), where information about an animal's choice and its outcome is retained to update future reward expectations based on past experiences. We investigated whether spatial memory, required across different behavioral contexts, relies on a shared neural mechanism. To explore this, we analyzed neural activity recorded from rhesus monkeys engaged in three distinct tasks: the oculomotor delayed response task (ODR), a visual search task, and the matching pennies game, each requiring the retention and use of similar spatial information under different cognitive demands. The ODR task demands only prospective memory, as the selection of action is dictated by the location of visual cue, and the subject must retain this intended action for execution after a temporal delay. In contrast, the matching pennies task engages both retrospective and prospective memory: retrospective memory of previous choice and its outcome to inform decision-making, while prospective memory is needed to carry out that decision. Visual search task, by comparison, does not explicitly require either retrospective or prospective memory. Our analysis revealed that neural signals encoding retrospective memory of the animal's choice in the visual search and matching pennies tasks were not correlated with the prospective working memory signals of visually cued locations in the ODR task, in either the DLPFC or LIP. Moreover, retrospective choice signals in the visual search and matching pennies tasks were not correlated with each other. In contrast, neural activity related to upcoming choices (prospective memory) in the LIP showed significant correlations across all three tasks. In the DLPFC, prospective choice signals were correlated between the visual search and ODR tasks, but not between those tasks and matching pennies. Additionally, in the DLPFC, neural signals representing previously rewarded choices were significantly correlated with working memory signals during the ODR task. These results suggest that the LIP supports a consistent, shared mechanism for prospective memory linking a committed action to its eventual execution. In contrast, the DLPFC might mediate the transformation of retrospective memory, integrating past choices and outcomes into a decision and its associated prospective memory.

Stabilization of recurrent neural networks through divisive normalization
Stability is a fundamental requirement for both biological and engineered neural circuits, yet it is surprisingly difficult to guarantee in the presence of recurrent interactions. Standard linear dynamical models of recurrent networks are unreasonably sensitive to the precise values of the synaptic weights, since stability requires all eigenvalues of the recurrent matrix to lie within the unit circle. Here we demonstrate, both theoretically and numerically, that an arbitrary recurrent neural network can remain stable even when its spectral radius exceeds 1, provided it incorporates divisive normalization, a dynamical neural operation that suppresses the responses of individual neurons. Sufficiently strong recurrent weights lead to instability, but the approach to the unstable phase is preceded by a regime of critical slowing down, a well-known early warning signal for loss of stability. Remarkably, the onset of critical slowing down coincides with the breakdown of normalization, which we predict analytically as a function of the synaptic strength and the magnitude of the external input. Our findings suggest that the widespread implementation of normalization across neural systems may derive not only from its computational role, but also to enhance dynamical stability.

Exploring the association between walking, sleep patterns, brain perivascular spaces, and cognitive function in Parkinson's disease
Objective: Perivascular spaces (PVSs) surround cerebral blood vessels and support metabolic waste clearance, that is modulated by sleep. In Parkinson's disease (PD), motor impairments can affect sleep quality. This study explored the interrelationships between sleep disruption, gait difficulties, and cognition in PD, with a specific focus on the potential mediating role of PVS. Methods: 348 participants from the Parkinson's Progression Markers Initiative (PPMI) were divided into healthy controls (HC), prodromal individuals, and patients with PD. Insomnia levels indicated sleep disruption, and walking difficulties severity were considered. Cognition was measured with the Symbol Digit Modalities (SDM) test. PVS volume fractions in white matter (WM-PVS) and basal ganglia (BG-PVS) were quantified using an automated segmentation pipeline developed by our team. Mediation analyses were conducted to assess whether PVS mediated the relationship between gait impairment and cognition, as well as the relationship between sleep and gait problems. Finally, we examined whether baseline PVS volume fraction predicted disease progression, as indexed by cerebro-spinal fluid (CSF) biomarkers collected after five years. Results: PVS did not mediate the relationship between gait difficulties and cognition, or between sleep disruption and motor symptoms. Greater walking impairment was directly associated with poorer cognition. Insomnia severity was directly associated with greater walking problems. BG-PVS was negatively associated to cognition. Longitudinally, PVS burden was not predictive of disease progression. Conclusions: Our findings suggest that sleep and motor impairments independently contribute to cognitive function in PD, but these effects are not mediated by PVS burden.

Longitudinal functional connectivity during rest and task is differentially related to Alzheimer's pathology and episodic memory in older adults
Changes in functional connectivity (FC) strength involving the medial temporal lobe (MTL) and posteromedial cortex (PMC) are related to early Alzheimer's pathology and alterations in episodic memory performance in cognitively unimpaired older adults, but their dynamics remain unclear. We examined how longitudinal changes in FC involving MTL and PMC during resting-state, episodic memory encoding, and retrieval relate to subsequent amyloid- and tau-PET burden, longitudinal episodic memory performance, and the APOE4 genotype in 152 cognitively unimpaired older adults from the PREVENT-AD cohort. We found APOE4- and fMRI paradigm-dependent associations of change in FC strength with pathology burden and change in episodic memory performance. Decreasing FC over time, or ''hypoconnectivity'', within PMC during rest in APOE4 carriers and during retrieval in APOE4 non-carriers was related to more amyloid and tau, respectively. Conversely, increasing FC over time, or ''hyperconnectivity'', within MTL during encoding in APOE4 carriers and between MTL and PMC during retrieval independent of APOE4 status was related to more tau. Further, increasing FC between MTL and PMC during rest, unlike during encoding, was beneficial for episodic memory. Our study highlights that pathology-related episodic memory network changes manifest differently during rest and task and have differential implications for episodic memory trajectories.

3D organoids containing endothelial and neural cells generation by serial inductions of differentiation on human iPSC-derived embryoid bodies
3D brain organoids have been widely used as a tool to study human brain development and disorders. Although endothelial cells play important roles in the brain development and pathogenesis in neurological disorders, most 3D brain organoids lack inherent endothelial cells and need either the addition of endothelial cells or to be transplanted to animals to reconstitute such vascular structures, likely missing the developmental interactions of endothelial cells and other cells in the human brain. In order to reconstitute a 3D organoid mimicking the in vivo neural and endothelial cells development, we cultured iPSC-derived embryoid bodies in sequentially applied endothelial and neuronal induction media along with Matrigel embedding. The resulting 3D organoid consists of both neural cells and endothelial cells with vascular like structures, as determined by immunostaining. With scRNA-Seq analysis, the brain organoid was confirmed to contain neural cell types similar with human brains, including a variety of excitatory and inhibitory neurons and glia. Furthermore, when compared with traditional cerebral organoids without endothelial cells using RNA-Seq analysis, the endothelial containing neural organoids (EC-neural organoids) showed difference in gene profiles and favored angiogenesis and vasculogenesis. Of the differentially expressed genes, KRBA2 expression was found higher in neural cells and its inhibition by siRNA treatment resulted in decreased transcriptions of a variety of genes such as neuronal differentiation specific genes but not in genes specific to pluripotent stem cells such as OCT4. The EC-neural organoids also express receptors to SARS-CoV-2 similar to human brains. This 3D model provides a useful tool to study the interactions of endothelial cells and neural cells in the brain development and neural infectious disorders where endothelial cells and pericytes play pivotal roles.