bioRxiv Subject Collection: Neuroscience's Journal

Patterns of Ongoing Thought in the Real World and Their Link to Mental Health and Well-Being
The thoughts we experience in daily life have important implications for our health and well-being. However, it is often difficult to measure thoughts patterns outside of laboratory conditions due to concerns about the voracity of measurements taken outside of controlled laboratory conditions. To address this gap in the literature, our study set out to measure patterns of thought as they occur in daily life and assess the robustness of these measures and their associations with traits measurements of health and well-being. A sample of undergraduate participants completed multi-dimensional experience sampling (mDES) surveys eight times per day for five days in daily life. Principal component analysis (PCA) reduced these data to identify the dimensions that explained the patterns of thoughts reported in our study. We used (LMM) modelling to map how these thought patterns relate to the activities taking place, highlighting good consistency within the sample, as well as substantial overlap with prior work. Multiple regression was used to examine the association between patterns of ongoing thought and aspects of mental health and well-being, highlighting a pattern of negative intrusive distraction that had a positive association with anxiety, and a negative association with social well-being. Notably, states of intrusive distraction tended to be most prevalent in solo activities and was relatively suppressed when interacting with other people (either in person or virtually). Our study, therefore, highlights the use of mDES as a tool to understand how thoughts in daily life impact on our mental health and well-being and highlight an important role in social connectedness in the etiology of intrusive thinking.

Neurotoxic Methamphetamine Doses Alter CDCel-1 Levels and Its Interaction with Vesicular Monoamine Transporter-2 in Rat Striatum
In recent years, methamphetamine METH misuse in the US has been rapidly increasing and there is no FDA-approved pharmacotherapy for METH use disorder (MUD). In addition to being dependent on the drug, people with MUD develop a variety of neurological problems related to the toxicity of this drug. A variety of molecular mechanisms underlying METH neurotoxicity has been identified, including dysfunction of the neuroprotective protein parkin. However, it is not known whether parkin loss of function within striatal dopaminergic (DAergic) terminals translates into a decrease in DA storage capacity. This study examined the relationship between parkin, its substrate cell division cycle related-1 (CDCrel-1), and vesicular monoamine transporter-2 (VMAT2) in METH neurotoxicity in male Sprague Dawley rats. To also assess individual differences in response to METH neurotoxic effects, a large group of rats was treated with binge METH or saline and sacrificed 1h or 24h later. This study is the first to show that binge METH alters the levels and subcellular localization of CDCrel-1 and that CDCrel-1 interacts with VMAT2 and increases its levels at the plasma membrane. Furthermore, we found wide individual differences in the responses of measured indices to METH. Proteomic analysis of VMAT-2-associated proteins revealed upregulation of several proteins involved in the exocytosis/endocytosis cycle. The results suggest that at 1h after METH binge, DAergic neurons are engaged in counteracting METH-induced toxic effects, including oxidative stress- and hyperthermia-induced inhibition of synaptic vesicle cycling, with the responses varying between individual rats. Studying CDCrel-1, VMAT2, and other proteins in large groups of outbred rats can help define individual genetic and molecular differences in responses to METH neurotoxicity which, in turn, will aid treating humans suffering from METH use disorder and its neurological consequences.

Characterizing the heterogeneity of neurodegenerative diseases through EEG normative modeling
Neurodegenerative diseases such as Parkinson's (PD) and Alzheimer's (AD) exhibit considerable heterogeneity of functional brain features within patient populations, complicating diagnosis, treatment, prognosis, and drug discovery. Here, we use electroencephalography (EEG) and normative modeling to investigate neurophysiological oscillatory mechanisms underpinning this heterogeneity. To this aim, we use resting-state EEG activity collected by 14 clinical units, in healthy older persons (n=499) and patients with PD (n=237) and AD (n=197), aged over 40 years old. Spectral and source connectivity analyses of EEG activity provided EEG features for normative modeling and deviation measures in the PD and AD patients. Normative models confirmed significant deviations of the EEG features in PD and AD patients over population norms, characterized by high heterogeneity and frequency-dependence. The percentage of patients with at least one deviating EEG feature was ~30% for spectral measures and ~80% for functional source connectivity. Notably, the spatial overlap of the deviant EEG features did not exceed 60% for spectral analysis and 25% for functional source connectivity analysis. Furthermore, the patient-specific deviations were correlated with relevant clinical measures, such as the UPDRS for PD (=0.24, p=0.025) and the MMSE for AD (=-0.26, p=0.01), indicating that greater deviations from normative EEG features are associated with worsening score values. These results suggest that the deviation percentage from EEG norms may enrich clinical assessment in PD and AD patients at individual levels in the framework of Precision Neurology.

Disposition of the chemosensory neurons in the neurotransmitter-release mutant unc-13
Secretion of neurotransmitters- and neuropeptides-containing vesicles is a regulated process orchestrated by multiple proteins. Of these, mutants, defective in the unc-13 and unc-31 genes, responsible for neurotransmitter and neuropeptide release, respectively, are routinely used to elucidate neural and circuitry functions. While these mutants result in severe functional deficits, their neuroanatomy is assumed to be intact. Here, using C. elegans as the model animal system, we find that the head sensory neurons show aberrant positional layout in neurotransmitter (unc-13), but not in neuropeptide (unc-31), release mutants. This finding suggests that synaptic activity may be important for proper cell migration during neurodevelopment and warrants considering possible anatomical defects when using unc-13 neurotransmitter release mutants.

Stiffness-tunable neurotentacles for minimally invasive implantation and long-term neural activity recordings
Flexible implantable microelectrodes have been demonstrated to exhibit excellent biocompatibility for chronic neural activity recordings. However, the low bending strength of the commonly employed flexible materials presents a significant challenge for probe insertion into the brain. Traditional implantation methods for flexible electrodes generally require additional auxiliary materials or tools, which tend to have a much larger footprint than the probes themselves, greatly increasing the damage to neurons during insertion. Here we have proposed a stiffness-tunable polyimide probe for deep brain implantation, referred to as Neurotentacle, enabled by embedded microchannels in which the liquid pressure is controllable (from 0.1MPa to more than 2.0MPa). During the insertion phase into the brain, the neurotentacle can pose a high stiffness under elevated internal pressure to penetrate the brain tissues without the use of any additional materials or tools. Once the device has been successfully inserted, it can regain its flexibility by reducing the internal pressure. Importantly, the novel multilayer microfabrication process keeps the structural dimensions of the neurotentacle similar to those of a regular flexible probe. Therefore, the neurotentacle can produce an extremely low level of damage to brain tissue during its insertion phase, while extending its long-term biocompatibility and stability, which has been experimentally verified in histological evaluations conducted on both acute and chronic animal specimens. In addition, the chronically implanted neurotentacles enabled stable neural activity recordings in mice with an average spike yield of 96% and an average signal-to-noise ratio of 15.2. The proposed neurotentacle does not necessitate the use of complex devices and its insertion process is straightforward and highly controllable, thus rendering it an appealing technique for minimally invasive implantation and long-term neural recording of flexible electrodes.

Reduced learning rate and E/I imbalance drive Peripersonal Space boundaries expansion in Schizophrenia
Background and Hypothesis: Abnormalities in the encoding of the space close to the body, named peripersonal space (PPS), is thought to play a crucial role in the disruption of the bodily self observed in schizophrenia (SCZ). Empirical evidence indicates a narrower extension of the PPS in SCZ compared to controls but preserved plasticity of the PPS. Computational studies suggest that increased excitation of sensory neurons could explain the smaller PPS observed in SCZ. However, it is unclear why SCZ patients preserve PPS plasticity and how such an excitation imbalance influences learning during the extension of the PPS boundaries. Study Design: We hypothesise that Hebbian plasticity can account for PPS expansion after active tool use training, which occurs in spite of E/I imbalance and reduced synaptic density. Using simulations in a SCZ network model, we explored the effects of such impairments on PPS plasticity and fitted the model to behavioural data before and after a training routine. Study Results: We found that increased excitation of sensory neurons does not impede the expansion of PPS and could explain a sharper demarcation of PPS boundaries after training. In addition, we found that a reduction in the learning rate is required to reproduce the post-training PPS representation of SCZ patients. Conclusion: We discuss how the neural mechanisms behind the plasticity of PPS in the SCZ spectrum are related to the core pathophysiology of the disease.

Synapse protein signatures in cerebrospinal fluid and plasma predict cognitive maintenance versus decline in Alzheimers disease
Rates of cognitive decline in Alzheimers disease (AD) are extremely heterogeneous, with ages of symptom onset ranging from age 40 to 100 years and conversion from mild cognitive impairment to AD dementia taking 2 to 20 years. Development of biomarkers for amyloid-beta (AB) and tau protein aggregates, the hallmark pathologies of AD, have improved patient monitoring/stratification and drug development, but they still only explain 20 to 40% of the variance in cognitive impairment (CI) in AD. To discover additional molecular drivers and biomarkers of AD dementia, we perform cerebrospinal fluid (CSF) proteomics on 3,416 individuals from six deeply phenotyped prospective AD case-control cohorts. We identify synapse proteins as the strongest correlates of CI, independent of AB; and tau. Using machine learning we derive the CSF YWHAG:NPTX2 synapse protein ratio, a robust correlate of CI, which explains 27% of the variance in CI beyond CSF PTau181:AB42, 10% beyond tau PET, and 50% beyond CSF NfL in AB positive individuals. We find YWHAG:NPTX2 also increases with normal aging as early as age 20 and increases at a faster rate in APOE4 carriers and autosomal dominant AD mutation carriers. Most notably, YWHAG:NPTX2 positive individuals (top 25th percentile) are 15 times (HR=15.4 [10.6 to 22.2]) more likely to experience cognitive decline over 15 years compared to YWHAG:NPTX2 negative individuals (bottom 25th percentile), and this rises to 19 times (HR=18.9 [10.83 to 32.9]) with additional stratification by AB and phosphorylated tau status. Lastly, we perform plasma proteomics on 4,245 individuals to develop a plasma-based signature of CI which partly recapitulates CSF YWHAG:NPTX2. Overall, our findings underscore CSF YWHAG:NPTX2 and the corresponding plasma signature as robust prognostic biomarkers for AD onset and progression beyond gold-standard biomarkers of AB, tau, and neurodegeneration and implicate synapse dysfunction as a core driver of AD dementia.

Recent odor experience selectively modulates olfactory sensitivity across the glomerular output in the mouse olfactory bulb
Although animals can reliably locate and recognize odorants embedded in complex environments, the neural circuits for accomplishing these tasks remain incompletely understood. Adaptation is likely to be important in this process as it could allow neurons in a brain area to adjust to the broader sensory environment. Adaptive processes must be flexible enough to allow the brain to make dynamic adjustments, while also maintaining sufficient stability such that organisms do not forget important olfactory associations. Processing within the mouse olfactory bulb is likely involved in generating adaptation, although there are conflicting models of how it transforms the glomerular output of the mouse olfactory bulb. Here we performed 2-photon Ca2+ imaging in awake mice to determine the time course of recovery from adaptation, and whether it acts broadly or selectively acts across the glomerular population. Individual glomerular responses, as well as the overall population odor representation was similar across imaging sessions. However, odor-concentration pairings presented with interstimulus intervals upwards of 30-s could evoke heterogeneous adaptation across the glomerular population. This adaptation was strongest at higher concentrations, unrelated to variations in respiration, and measurements from olfactory receptor neuron glomeruli indicate that it is unlikely to be inherited from the periphery. Our results indicate that the olfactory bulb output reliably transmits stable odor representations, although dynamic processes exist by which recent odor exposure can selectively impact odor sensitivity for upwards of 30 seconds. We propose that dynamic adaptation in subsets of glomeruli is necessary for making dynamic adjustments to complex odor environments.

Trait anxiety impairs reciprocity behavior: A multi-modal and computational modeling study
Anxiety significantly impacts reciprocal behavior, crucial for positive social interactions. The neurocomputational mechanisms of anxiety's effects on the core (individual propensity) and peripheral (decision context) factors shaping reciprocity remain unclear. Here, we investigated reciprocity in individuals with low and high trait anxiety using a binary trust game with gain/loss framing, combining computational modeling, eye-tracking, and event-related potentials (ERPs). Our computational model, validated by eye-tracking data, identified four psychological components driving reciprocal behavior: reward, guilt aversion, superiority aversion, and superiority attraction. Regarding the core of reciprocity, trait anxiety diminished both overall reciprocity and specific psychological components like guilt aversion and superiority attraction, irrespective of context. The reduction in guilt aversion was supported by ERP findings showing decreased P2 (selective attention) and increased LPP (emotion regulation) amplitudes in anxious individuals. Regarding the periphery of reciprocity, trait anxiety altered the contextual perception of both superiority aversion and reward. Further, trait anxiety reversed the perception of superiority aversion from gain to loss contexts, a pattern that was linked to the N2 amplitudes (cognitive control). Our findings revealed distinct effects of trait anxiety on core and peripheral factors in reciprocity, offering potential targets for interventions aimed at improving reciprocity in individuals with anxiety disorders.

A disinhibitory basal forebrain to cortex projection supports sustained attention
Sustained attention, as an essential cognitive faculty governing selective sensory processing, exhibits remarkable temporal fluctuations. However, the underlying neural circuits and computational mechanisms driving moment-to-moment attention fluctuations remain elusive. Here we demonstrate that cortex-projecting basal forebrain parvalbumin-expressing inhibitory neurons (BF-PV) mediate sustained attention in mice performing an attention task. BF-PV activity predicts the fluctuations of attentional performance metrics - reaction time and accuracy - trial-by-trial, and optogenetic activation of these neurons enhances performance. BF-PV neurons also respond to motivationally salient events, such as predictive cues, rewards, punishments, and surprises, which a computational model explains as representing motivational salience for allocating attention over time. Furthermore, we found that BF-PV neurons produce cortical disinhibition by inhibiting cortical PV+ inhibitory neurons, potentially underpinning the observed attentional gain modulation in the cortex. These findings reveal a disinhibitory BF-to-cortex projection that regulates cortical gain based on motivational salience, thereby promoting sustained attention.

Neural microstates in real-world behaviour captured on the smartphone
Microstates are periods of quasi-stability in large-scale neural networks, and they are ubiquitous spanning sleep, rest and behaviour. One possibility is that the temporal and spatial features of these states vary from person to person contributing to inter-individual behavioural differences. Another possibility is that the microstates support momentary behavioural needs and as a result their properties may vary with behavioural fluctuations in the same person. Here, we leverage the history of smartphone touchscreen interaction dynamics and combined smartphone and EEG recordings (N = 61), to address if and how microstates contribute to real-world behaviour. We find that microstates measured when at rest correlated with the history (~30 days) of smartphone interaction dynamics captured in the real world, indicating their role in the behaviour. During smartphone behaviour, the configuration of microstates varied over time. However, this variance was largely unrelated to the rich behavioural dynamics, as in similar temporal and spatial features were observed during rapid and slow smartphone interactions. We show that in the real world microstates do not respond to the fluctuations of the ongoing behaviour. Still, as microstates measured at rest are correlated to the inter-individual behavioural differences captured on the smartphone, we propose that microstates exert a top-down influence to broadly orchestrate real-world behaviour.

Phosphorylation at serine 214 correlates with tau seeding activity in an age-dependent manner in two mouse models for tauopathies and is required for tau transsynaptic propagation.
Pathological aggregation and propagation of hyperphosphorylated and aberrant forms of tau are critical features of the clinical progression of Alzheimer's disease and other tauopathies. To better understand the correlation between these pathological tau species and disease progression, we profiled the temporal progression of tau seeding activity and the levels of various phospho- and conformational tau species in the brains of two mouse models of human tauopathies. Our findings indicate that tau seeding is an early event that occurs well before the appearance of AT8-positive NFT. Specifically, we observed that tau phosphorylation in serine 214 (pTau-Ser214) positively correlates to tau seeding activity during disease progression in both mouse models. Furthermore, we found that the histopathology of pTau-Ser214 appears much earlier and has a distinct pattern and compartmentalization compared to the pathology of AT8, demonstrating the diversity of tau species within the same region of the brain. Importantly, we also observed that preventing the phosphorylation of tau at Ser214 significantly decreases tau propagation in mouse primary neurons, and seeding activity in a Drosophila model of tauopathy, suggesting a role for this tau phosphorylation in spreading pathological forms of tau. Together, these results suggest that the diverse spectrum of soluble pathological tau species could be responsible for the distinct pathological properties of tau and that it is critical to dissect the nature of the tau seed in the context of disease progression.

Secretome analysis of oligodendrocytes and precursors reveals their roles as contributors to the extracellular matrix and potential regulators of inflammation
Oligodendrocytes form myelin that ensheaths axons and accelerates the speed of action potential propagation. Oligodendrocyte progenitor cells (OPCs) proliferate and replenish oligodendrocytes. While the myelin-forming role of oligodendrocytes and OPCs is well-established, potential additional roles of these cells are yet to be fully explored. Here, we analyzed the secreted proteome of oligodendrocytes and OPCs in vitro to determine whether these cell types are major sources of secreted proteins in the central nervous system (CNS). Interestingly, we found that both oligodendrocytes and OPCs secret various extracellular matrix proteins. Considering the critical role of neuroinflammation in neurological disorders, we evaluated the responses and potential contributions of oligodendrocytes and OPCs to this process. By characterizing the secreted proteomes of these cells after pro-inflammatory cytokine treatment, we discovered the secretion of immunoregulators such as C2 and B2m. This finding sheds new light on the hitherto underappreciated role of oligodendrocytes and OPCs in actively modulating neuroinflammation. Our study provides a comprehensive and unbiased proteomic dataset of proteins secreted by oligodendrocyte and OPC under both physiological and inflammatory conditions. It revealed the potential of these cells to secrete matrix and signaling molecules, highlighting their multifaceted function beyond their conventional myelin-forming roles.

Nanoscale organization is changed in native, surface AMPARs by mouse brain region and tauopathy
Synaptic AMPA receptors (AMPARs) on neuronal plasma membranes are correlated with learning and memory. Using a unique labeling and super-resolution imaging, we have visualized the nanoscale synaptic and extra-synaptic organization of native surface AMPARs for the first time in mouse brain slices as a function of brain region and tauopathy. We find that the fraction of surface AMPARs organized in synaptic clusters is two-times smaller in the hippocampus compared to the motor and somatosensory cortex. In 6 months old PS19 model of tauopathy, synaptic and extrasynaptic distributions are disrupted in the hippocampus but not in the cortex. Thus, this optimized super-resolution imaging tool allows us to observe synaptic deterioration at the onset of tauopathy before apparent neurodegeneration.

The timing of preceding tactile inputs modulates cortical processing
Tactile experiences in the real world are rich in texture and temporal patterns. While the role of texture in driving somatosensory cortical activity is well established, there is emerging evidence that somatosensory activity is sensitive to tactile temporal statistics (i.e., the time intervals that separate stimuli in trains of successive tactile pulses). Cortical processing of tactile pulses may be shaped by preceding pulses, but this influence will vary with inter-stimulus intervals. It is possible that tactile information lingers only briefly in primary somatosensory cortex and will influence processing of the next pulse only at short intervals; in secondary somatosensory cortex it lingers longer, allowing it to shape the processing of even multiple successive pulses over more prolonged intervals. Here we recorded scalp EEG signals from somatosensory cortex in response to a train of tactile pulses presented to the fingertips with varying inter-stimulus intervals spanning 100 to 10,000 ms. We traced cortical tactile processing through its early (<75 ms), intermediate (75 to 150 ms) and late stages (150 to 300 ms). The early and late stages of somatosensory activity were similarly shaped by the preceding pulse; this influence declined with increasing inter-stimulus interval. The intermediate stage of somatosensory activity was sensitive to both the previous and the penultimate pulses, a sensitivity that was again modulated by their temporal dynamics. Our findings suggest that somatosensory cortex integrates complex temporal patterns during its intermediary processing stages, allowing previous and even penultimate stimuli to modulate ongoing processing of current stimuli.

Leveraging multivariate information for community detection in functional brain networks
Embedded in neuroscience is the concept that brain functioning is underpinned by specialized systems whose integration enables cognition and behavior. Modeling the brain as a network of interconnected brain regions, allowed us to capitalize on network science tools and identify these segregated systems (modules, or communities) by optimizing the weights of pairwise connections within them. However, just knowing how strongly two brain areas are connected does not paint the whole picture. Brain dynamics is also engendered by interactions involving more areas at the same time, namely, higher-order interactions. In this paper, we propose a community detection algorithm that accounts for higher-order interactions and finds modules of brain regions whose brain activity is maximally redundant. Compared to modules identified with methods based on bivariate interactions, our redundancy-dominated modules are more symmetrical between the hemispheres, they overlap with canonical systems at the level of the sensory cortex, but describe a new organization of the transmodal cortex. By detecting redundant modules across spatial scales, we identified a sweet spot of maximum balance between segregation and integration of information as that scale where redundancy within modules and synergy between modules peaked. Moreover, we defined a local index that distinguishes brain regions in segregators and integrators based on how much they participate in the redundancy of their modules versus the redundancy of the whole system. Finally, we applied the algorithm to a lifespan dataset and tracked how redundant subsystems change across time. The results of this paper serve as educated guesses on how the brain organizes itself into modules accounting for higher-order interactions of its fundamental units, and pave the way for further investigation that could link them to cognition, behavior, and disease.

The Unity/Diversity Framework of Executive Functions in Older Adults
Executive functions (EFs), encompassing inhibition, shifting, and updating as three fundamental subdomains, are typically characterized by a unity/diversity construct. However, given the dedifferentiation trend observed in aging, it remains controversial whether the construct of EFs in older adults becomes unidimensional or maintains unity/diversity. This study aims to explore and validate the construct of EFs in older adults. At the behavioral level, we conducted confirmatory factor analysis on data from 222 older adults who completed six tasks specifically targeting inhibition, shifting, and updating. One unidimensional model and six unity/diversity models of EFs were evaluated. Our results indicated that the EFs of older adults demonstrated greater congruence with the unity/diversity construct. At neural level, thirty older adults completed three thematically consistent fMRI tasks, targeting three subdomains of EFs respectively. Multivariate pattern analysis showed that rostromedia prefrontal cortex robustly showed similar neural representation across different tasks (unity). Meanwhile, the three EF domains were encoded by distinct global neural representation and the lateral prefrontal cortex play a crucial role in classification (diversity). These findings underscore the unity/diversity framework of EFs in older adults and offer important insights for designing interventions aimed at improving EFs in this population.

Sympathetic Nervous System Overactivation Induces Colonic Eosinophil-Associated Microinflammation and Contributes to the Pathogenesis of Irritable Bowel Syndrome
Objective: Mucosal microinflammation is a characteristic clinical manifestation of irritable bowel syndrome (IBS), and its symptoms are often triggered by psychological stress. In the present study, we aimed to investigate the impact of early life stress-associated dysfunction of the sympathetic nervous system (SNS) on mucosal immune changes in the gastrointestinal tract (GI) and its contribution to IBS pathogenesis. Design: We utilised a traditional animal model of IBS with maternal separation (MS) and evaluated colorectal hypersensitivity, immune alterations, and SNS activity in adult rats with MS. We conducted a series of experiments to manipulate peripheral SNS activity pharmacologically and chemogenetically to explore the interaction between SNS activity and GI events. Results: The MS-induced IBS model exhibited visceral hypersensitivity and eosinophilic infiltration in the colonic mucosa, along with SNS overactivation. Degeneration of the SNS using 6-OHDA neurotoxin decreased eosinophil infiltration and visceral hypersensitivity in the MS model. Notably, specific chemogenetic activation of the peripheral SNS induced eosinophil infiltration in the intestinal mucosa through the noradrenergic signalling-mediated release of eotaxin-1 from mesenchymal cells. Conclusion: This study highlights the critical role of SNS overactivation in eotaxin-1-driven eosinophil infiltration in the colon, leading to the development of visceral hypersensitivity in IBS. The results provide important insights into the mechanistic links among increased sympathetic activity, mucosal microinflammation, and visceral hypersensitivity in individuals with IBS, suggesting potential therapeutic approaches.

Brief sleep disruption alters synaptic structures among hippocampal and neocortical somatostatin-expressing interneurons
Brief sleep loss can disrupt cognition, including information processing in neocortex and hippocampus. Recent studies have identified alterations in synaptic structures of principal neurons within these circuits. However, while in vivo recording and bioinformatic data suggest that inhibitory interneurons are more strongly affected by sleep loss, it is unclear how sleep and sleep deprivation affect interneuron synapses. Recent data suggest that activity among hippocampal somatostatin-expressing (SST+) interneurons is selectively increased by experimental sleep disruption. We used Brainbow 3.0 to label SST+ interneurons in the dorsal hippocampus, prefrontal cortex, and visual cortex of SST-CRE transgenic mice, then compared synaptic structures in labeled neurons after a 6-h period of ad lib sleep, or gentle handling sleep deprivation (SD) starting at lights on. We find that dendritic spine density among SST+ interneurons in both hippocampus and neocortex was altered in a subregion-specific manner, with increased overall and thin spine density in CA1, decreased mushroom spine density in CA3, and decreased overall and stubby spine density in V1 after SD. Spine size also changed significantly after SD, with dramatic increases in spine volume and surface area in CA3, and small but significant decreases in CA1, PFC and V1. Together, our data suggest that the synaptic connectivity of SST+ interneurons is significantly altered, in a brain region-specific manner, by a few hours of sleep loss. Further, they suggest that sleep loss can disrupt cognition by altering the balance of excitation and inhibition in hippocampal and neocortical networks.

Bayesian Prior Uncertainty and Surprisal Elicit Distinct Neural Patterns During Sound Localization in Dynamic Environments
Estimating the location of a stimulus is a key function in sensory processing, and widely considered to result from the integration of prior information and sensory input according to Bayesian principles. A deviation of sensory input from the prior elicits surprisal, depending on the uncertainty of the prior. While this mechanism is increasingly understood in the visual domain, much less is known about its implementation in audition, especially regarding spatial localization. Here, we combined human EEG with computational modeling to study auditory spatial inference in a noisy, volatile environment and analyzed behavioral and neural patterns associated with prior uncertainty and surprisal. First, our results demonstrate that participants indeed used prior information during periods of stable environmental statistics, but showed evidence of surprisal and discarded prior information following environmental changes. Second, we observed distinct EEG activity patterns associated with prior uncertainty and surprisal in both the time- and time-frequency domain, which are in line with previous studies using visual tasks. Third, these EEG activity patterns were predictive of our participants' sound localization error, response uncertainty, and prior bias on a trial-by-trial basis. In summary, our work provides novel behavioral and neural evidence for Bayesian inference during dynamic auditory localization.

Enhanced restoration of visual code after targeting on bipolar cells compared to retinal ganglion cells with optogenetic therapy
Optogenetic therapy is a promising vision restoration method where light sensitive opsins are introduced to the surviving inner retina following photoreceptor degeneration. The cell type targeted for opsin expression will likely influence the quality of restored vision. However, a like-for-like pre-clinical comparison of visual responses evoked following equivalent opsin expression in the two major targets, ON bipolar (ON BCs) or retinal ganglion cells (RGCs), is absent. We address this deficit by comparing stimulus-response characteristics at single unit resolution in retina and dorsal lateral geniculate nucleus (dLGN) of retinally degenerate mice genetically engineered to express the opsin ReaChR in Grm6- or Brn3c-expressing cells (ON BC vs RGCs respectively). For both targeting strategies, we find ReaChR-evoked responses have equivalent sensitivity and can encode contrast across different background irradiances. Compared to ON BCs, targeting RGCs decreased response reproducibility and resulted in more stereotyped responses with reduced diversity in response polarity, contrast sensitivity and temporal frequency tuning. Recording ReaChR-driven responses in visually intact retinas confirmed that RGC-targeted ReaChR expression disrupts visual feature selectivity of individual RGCs. Our data show that while both approaches restore visual responses with impressive fidelity, ON BC targeting produces a richer visual code better approaching that of wildtype mice.

A Hypothalamic Circuit that Modulates Feeding and Parenting Behaviors
Across mammalian species, new mothers undergo considerable behavioral changes to nurture their offspring and meet the caloric demands of milk production. While many neural circuits underlying feeding and parenting behaviors are well characterized, it is unclear how these different circuits interact and adapt during lactation. Here, we characterized the transcriptomic changes in the arcuate nucleus (ARC) and the medial preoptic area (MPOA) of the mouse hypothalamus in response to lactation and hunger. Furthermore, we showed that heightened appetite in lactating mice was accompanied by increased activity of hunger-promoting agouti-related peptide (AgRP) neurons in the ARC. To assess the strength of hunger versus maternal drives, we designed a conflict assay where female mice chose between a food source or a chamber containing pups and nesting material. Although food-deprived lactating mothers prioritized parenting over feeding, hunger reduced the duration and disrupted the sequences of parenting behaviors in both lactating and virgin females. We discovered that ARCAgRP neurons directly inhibit bombesin receptor subtype-3 (BRS3) neurons in the MPOA, a population that governs both parenting and satiety. Selective activation of this ARCAgRP to MPOABRS3 circuit shifted behaviors from parenting to food-seeking. Thus, hypothalamic networks are modulated by physiological states and work antagonistically during the prioritization of competing motivated behaviors.

Different timescales of neural activities introduce different representations of task-relevant information
Recent findings indicate significant variations in neuronal activity timescales across and within cortical areas, yet their impact on cognitive processing remains inadequately understood. This study explores the role of neurons with different timescales in information processing within the neural system, particularly during the execution of context-dependent working memory tasks. Especially, we hypothesized that neurons with varying timescales contribute distinctively to task performance by forming diverse representations of task-relevant information. To test this, the model was trained to perform a context-dependent working memory task with a machine-learning technique. Results revealed that slow timescale neurons maintained stable representations of contextual information throughout the trial, whereas fast timescale neurons responded transiently to immediate stimuli. This differentiation in neuronal function suggests a fundamental role for timescale diversity in supporting the neural system's ability to integrate and process information dynamically. Our findings contribute to understanding how neural timescale diversity underpins cognitive flexibility and task-specific information processing, highlighting implications for both theoretical neuroscience and practical applications in designing artificial neural networks.

Parabrachial CGRP neurons modulates conditioned active defensive behavior under a naturalistic threat
Recent studies suggest that calcitonin gene-related peptide (CGRP) neurons in the parabrachial nucleus (PBN) represent aversive information and signal a general alarm to the forebrain. If CGRP neurons serve as a true general alarm, activation of CGRP neurons can trigger either freezing or fleeing defensive behavior, depending on the circumstances. However, the majority of previous findings have reported that CGRP neurons modulate only freezing behavior. Thus, the present study examined the role of CGRP neurons in active defensive behavior, using a predator-like robot programmed to chase mice in fear conditioning. Our electrophysiological results showed that CGRP neurons encoded the intensity of various unconditioned stimuli (US) through different firing durations and amplitudes. Optogenetic and behavioral results revealed that activation of CGRP neurons in the presence of the chasing robot intensified fear memory and significantly elevated conditioned fleeing behavior during recall of an aversive memory. Animals with inactivated CGRP neurons exhibited significantly low levels of fleeing behavior even when the robot was set to be more threatening during conditioning. Our findings expand the known role of CGRP neurons in the PBN as a crucial part of the brain's alarm system, showing they can regulate not only passive but also active defensive behaviors.

Noradrenergic and Dopaminergic Neural Correlates of Trait Anxiety: Unveiling the Impact of Maladaptive Emotion Regulation
Maladaptive emotion regulation plays a crucial role in the development and maintenance of elevated anxiety levels, both in patients and in individuals with subclinical symptomatology. While pharmacological treatments for anxiety target the emotion dysregulation through dopaminergic, noradrenergic and serotonergic systems, little is known about the underlying mechanisms. Therefore, the current study depicts the association of these neuromodulatory systems' resting-state functioning with trait-anxiety, investigating the role of maladaptive emotion regulation. Amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and whole-brain resting-state functional connectivity (rs-FC) were obtained from the ventral tegmental area (VTA), locus coeruleus (LC) and dorsal raphe, and correlated with trait-anxiety and self-reported maladaptive emotion regulation (N = 60). Trait-anxiety was positively associated with LC's fALFF and negatively with VTA's whole-brain rs-FC with the left inferior parietal lobule (L-IPL) and the left superior frontal gyrus (L-SFG). Maladaptive emotion regulation was negatively associated with VTA's rs-FC with these regions, with trait-anxiety fully mediating this association. VTA connectivity with the frontal region, but not parietal, positively predicted its amplitude of neural oscillations, an effect that was paralleled by stronger frontal dopaminergic innervation. In conclusion, noradrenergic and dopaminergic systems appear to contribute differently to subclinical anxiety. While noradrenaline likely acts through a more general mechanism, the dopaminergic dysconnectivity with the frontoparietal control network may act as one of the mechanisms of maladaptive emotion regulation, informing the models on the disorder development.

Inflammatory Neuropathy in Mouse and Primate Models of Colorectal Cancer
Colorectal cancer survivors are at increased risk of developing neurological issues, particularly peripheral neuropathy and chronic pain. Although pre-existing neuropathy is a risk factor for chronic pain, tumor-induced neuropathy has not been firmly established in pre-clinical models. Consistent with clinical observations, we show that mice with colorectal cancer develop peripheral neuropathy, which was associated with subtle locomotor deficits, without overt hypersensitivity. We detected widespread differences in pro-inflammatory cytokines and lipid metabolites in peripheral nerves from tumor-bearing mice. Macrophage accumulation, myelin decompaction and ryanodine receptor oxidation were associated with dysfunctional calcium homeostasis and reduced spike amplitude in sensory neurons. Inflammatory neuropathy and macrophage accumulation were also observed in peripheral nerves of rhesus macaques with colorectal cancer. These findings suggest colorectal cancer is causally linked to a subacute form of chronic inflammatory demyelinating polyneuropathy across species, which may represent an under-reported, yet important risk factor for neurological dysfunction in colorectal cancer survivors.

Gene expression changes in long-term memory unlikely to replicate in the long term
Identifying the cellular effects of memory-forming experiences on neurons which enable subsequent memory recall is a fundamental aim of neuroscience. The search for the engram could benefit from single cell RNA sequencing, which can estimate the mRNA expression of all genes in large samples of individual brain cells from animals exposed to specific experiences. A recent study used spatial transcriptomics and single cell RNA-sequencing to identify "transcriptional signatures in subpopulations of neurons and astrocytes that were memory-specific and persisted for weeks." However, because the authors did not account for multiple statistical comparisons and instead used an "unadjusted" threshold for statistical significance, the reported findings are likely dominated by false positives. Moreover, the statistical analysis treated individual cells as independent samples without accounting for correlations across cells derived from the same biological tissue sample. Reanalysis of the study's data using appropriate, widely accepted statistical procedures, identifies no significant differentially expressed genes. This suggests the data do not support the author's claim to have identified cell type-specific transcriptional signatures of memory in the mouse basolateral amygdala.

Pulsed inhibition of corticospinal excitability by the thalamocortical sleep spindle
Thalamocortical sleep spindles, i.e., oscillatory bursts at ~12-15 Hz of waxing and waning amplitude, are a hallmark feature of non-rapid eye movement (NREM) sleep and believed to play a key role in sleep-dependent memory reactivation and consolidation. Generated in the thalamus and projecting to neocortex and hippocampus, they are phasically modulated by neocortical slow oscillations (<1 Hz) and in turn phasically modulate hippocampal sharp-wave ripples (>80 Hz). This hierarchical cross-frequency nesting may enable phase-dependent plasticity in the neocortex, and spindles have thus been considered windows of plasticity in the sleeping brain. However, the assumed phasic excitability modulation had not yet been demonstrated for spindles. Utilizing a recently developed real-time spindle detection algorithm, we applied spindle phase-triggered transcranial magnetic stimulation (TMS) to the primary motor cortex (M1) hand area and measured motor evoked potentials (MEP) to characterize corticospinal excitability during sleep spindles. We found a net suppression of MEP amplitudes during spindles, driven by selective inhibition during the falling flank of the spindle oscillation, but no inhibition during its peak, rising flank, and trough. Importantly, this phasic inhibition occurred on top of the general sleep-related inhibition observed during spindle-free NREM sleep and did not extend into the immediate refractory post-spindle periods. We conclude that spindles exert asymmetric "pulsed inhibition" of corticospinal excitability, which is assumedly relevant for processes of phase-dependent plasticity. These findings and the developed real-time spindle targeting methods will enable future studies to uncover the causal role of spindles in synaptic plasticity and systems memory consolidation.

Therapeutic DBS for OCD Suppresses the Default Mode Network
Background: Deep brain stimulation (DBS) of the anterior limb of the internal capsule (ALIC) is an emerging treatment for severe, refractory obsessive-compulsive disorder (OCD). The therapeutic effects of DBS are hypothesized to be mediated by direct modulation of a distributed cortico-striato-thalmo-cortical network underlying OCD symptoms. However, the exact underlying mechanism by which DBS exerts its therapeutic effects still remains unclear. Method: In five participants receiving DBS for severe, refractory OCD (3 responders, 2 non-responders), we conducted a DBS On/Off cycling paradigm during the acquisition of functional MRI to determine the network effects of stimulation across a variety of bipolar configurations. We also performed tractography using diffusion-weighted imaging (DWI) to relate the functional impact of DBS to the underlying structural connectivity between active stimulation contacts and functional brain networks. Results: We found that therapeutic DBS had a distributed effect, suppressing BOLD activity within regions such as the orbitofrontal cortex, dorsomedial prefrontal cortex, and subthalamic nuclei compared to non-therapeutic configurations. Many of the regions suppressed by therapeutic DBS were components of the default mode network (DMN). Moreover, the estimated stimulation field from the therapeutic configurations exhibited significant structural connectivity to core nodes of the DMN. Conclusions: Therapeutic DBS for OCD suppresses BOLD activity within a distributed set of regions within the DMN relative to non-therapeutic configurations. We propose that these effects may be mediated by interruption of communication through structural white matter connections surrounding the DBS active contacts.

Concurrent assessment of neurometabolism and brain hemodynamics to comprehensively characterize the functional brain response to psychotropic drugs: an S-ketamine study
Neuroimaging techniques are crucial for understanding pharmacological treatment effects in neuropsychiatric disorders. Here, we present a novel approach that simultaneously assesses hemodynamic and neurometabolic brain responses to psychotropic drugs using interleaved pharmacological magnetic resonance imaging (phMRI) and magnetic resonance spectroscopy (phMRS). This method was tested using a double-dose, placebo-controlled, randomized, crossover design using S-ketamine, and acquiring 7 Tesla phMRI and phMRS data to evaluate time- and dose-dependent effects in 32 healthy controls. S-ketamine elicited robust phMRI responses in the dorsal-frontal, cingulate, and insular cortices, which correlated with glutamate and opioid receptor maps and subjective dissociation scores. These hemodynamic changes were paralleled by increases in glutamate and lactate, especially at higher doses. Furthermore, accuracy in predicting received S-ketamine dose increased when combining both techniques. Here, we show for the first time that concurrent phMRI and phMRS assessments provide important complementary insights into the functional brain response to pharmacological interventions.

Sleep Fragmentation Modulates the Neurophysiological Correlates of Cognitive Fatigue
Cognitive fatigue (CF) is a critical factor affecting performance and well-being. It can be altered in suboptimal sleep quality conditions, e.g., in patients suffering from obstructive sleep apnea who experience both intermittent hypoxia and sleep fragmentation (SF). Understanding the neurophysiological basis of SF in healthy individuals can provide insights to improve cognitive functioning in disrupted sleep conditions. In this electroencephalographical (EEG) study, we investigated in 16 healthy young participants the impact of experimentally induced SF on the neurophysiological correlates of CF measured before, during, and after practice on the TloadDback, a working memory task tailored to each individual maximal cognitive resources. Participants spent two times three consecutive nights in the laboratory, once in an undisrupted sleep (UdS) condition and once in a SF condition induced by non-awakening auditory stimulations, counterbalanced, and performed the TloadDback task both in a high (HCL) and a low (LCL) cognitive load condition. EEG activity was recorded during wakefulness in the 5-minutes resting state immediately before and after, as well as during the 16-minutes of the TloadDback task practice. In the high cognitive load under sleep fragmentation (HCL-SF) condition, high beta power increased during the TloadDback indicating heightened cognitive effort, and beta and alpha power increased in the post- vs. pre task resting state, suggesting a relaxation rebound. In the low cognitive load/undisturbed sleep (LCL-UdS) condition, low beta activity increased suggesting a relaxed focus, as well as mid beta activity associated with active thinking. These findings highlight the dynamic impact of SF on the neurophysiological correlates of CF and underscore the importance of sleep quality and continuity to maintain optimal cognitive functioning.

Whole-Body Networks: A Holistic Approach for Studying Aging
Aging is a multiorgan disease, yet the traditional approach is to study each organ in isolation. Such organ-specific studies allowed us to gather invaluable information regarding the pathomechanisms that contribute to senescence. But we believe that a big-picture exploration of the whole-body network (WBN) during aging could be complementary. In this study, we analyzed the functional magnetic resonance imaging (fMRI), breathing rate and heart rate time series of a young and an elderly group during eyes-open resting-state. By exploring the time-lagged coupling between the different organs we constructed WBNs. First, we showed that our analytical pipeline could identify regional differences in the networks of both populations, allowing us to proceed with the remaining of the analysis. By comparing the WBNs of young and elderly, a complex relationship emerged where some connections were stronger and some weaker in the elderly. Finally, the interconnectivity and segregation of the WBNs negatively correlated with the short-term memory of the young participants. This study: i) validated our methods, ii) identified differences between the two groups and iii) showed correlation with behavioral metrics. We are at the edge of a paradigm shift on how aging-related research is conducted and we believe that our methodology should be implemented in more complex mental and/or physical tasks to better demonstrate the alterations of WBNs as we age.

Contrasting topologies of synchronous and asynchronous functional brain networks
We generated asynchronous functional networks (aFNs) using a novel method called optimal causation entropy (oCSE) and compared aFN topology to the correlation-based synchronous functional networks (sFNs) which are commonly used in network neuroscience studies. Functional magnetic resonance imaging (fMRI) time series from 212 participants of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to generate aFNs and sFNs. As a demonstration of how aFNs and sFNs can be used in tandem, we used multivariate mixed effects models to determine whether age interacted with node efficiency to influence connection probabilities in the two networks. After adjusting for differences in network density, aFNs had higher global efficiency but lower local efficiency than the sFNs. In the aFNs, nodes with the highest outgoing global efficiency tended to be in the brainstem and orbitofrontal cortex. aFN nodes with the highest incoming global efficiency tended to be members of the Default Mode Network (DMN) in sFNs. Age interacted with node global efficiency in aFNs and node local efficiency in sFNs to influence connection probability. We conclude that the sFN and aFN both offer information about functional brain connectivity which the other type of network does not.

Flexible hippocampal representation of abstract boundaries supports memory-guided choice.
Cognitive maps in the hippocampus encode the relative locations of spatial cues in an environment and dynamically adapt their representation when boundaries geometrically change. In parallel, hippocampal cognitive maps can represent abstract knowledge, yet it's unclear whether the hippocampus is sensitive to geometric changes to the borders, extreme coordinates, of abstract knowledge spaces. Here, we use a memory-guided decision making task to test whether the human hippocampus and medial prefrontal cortex(mPFC) flexibly learn abstract boundary representations in distinct two-dimensional(2D) knowledge spaces. Despite being unnecessary to accurately make decisions, participants conserve a 2D map-like representation of abstract boundaries after the task, where the precision of their representation relates to prior choice accuracy. Finding that the hippocampus and mPFC represent the Euclidean distance of a decision cue to the most proximal boundary during decision making, we then test whether there are brain regions sensitive to boundary-defined contextual changes in abstract spaces. We observe flexible hippocampal representation of abstract boundaries, where the fidelity of this representation relates to task performance. Taken together, our results highlight the importance of hippocampal boundary representations in facilitating flexible knowledge retrieval in dynamically changing abstract contexts.

Two-factor synaptic consolidation reconciles robust memory with pruning and homeostatic scaling
Memory consolidation involves a process of engram reorganization and stabilization that is thought to occur primarily during sleep through a combination of neural replay, homeostatic plasticity, synaptic maturation, and pruning. From a computational perspective, however, this process remains puzzling, as it is unclear how the underlying mechanisms can be incorporated into a common mathematical model of learning and memory. Here, we propose a solution by deriving a consolidation model that uses replay and two-factor synapses to store memories in recurrent neural networks with sparse connectivity and maximal noise robustness. The model offers a unified account of experimental observations of consolidation, such as multiplicative homeostatic scaling, task-driven synaptic pruning, increased neural stimulus selectivity, and preferential strengthening of weak memories. The model further predicts that intrinsic synaptic noise scales sublinearly with synaptic strength; this is supported by a meta-analysis of published synaptic imaging datasets.

Flexible Control of Motor Units: Is the Multidimensionality of Motor Unit Manifolds a Sufficient Condition?
The level of flexibility in the neural control of motor units remains a topic of debate. Understanding this flexibility would require the identification of the distribution of common inputs to the motor units. In this study, we identified large samples of motor units from two lower limb muscles: the vastus lateralis (VL; up to 60 motor units/participant) and gastrocnemius medialis (GM; up to 67 motor units/participant). First, we applied a linear dimensionality reduction method to assess the dimensionality of the manifolds underlying the motor unit activity. We subsequently investigated the flexibility in motor unit control under two conditions: sinusoidal contractions with torque feedback, and online control with visual feedback on motor unit firing rates. Overall, we found that the activity of GM motor units was effectively captured by a single latent factor defining a unidimensional manifold, whereas the VL motor units were better represented by three latent factors defining a multidimensional manifold. Despite this difference in dimensionality, the recruitment of motor units in the two muscles exhibited similar but limited levels of flexibility. Using a spiking network model, we proposed that VL motor unit behaviors can be explained by a combination of a single common input of cortical origin with recurrent circuits involving connections with other motor unit pools. This study clarifies an important debated issue in motor unit control by showing that motor unit firings can lie in a multidimensional manifold; however, it may still be impossible for the central nervous system to flexibly control these motor units.

Methodological approaches to derive the heartbeat-evoked potential: pastpractices and future recommendations
The heartbeat-evoked potential (HEP), a cortical response time-locked to each heartbeat, is suggested as an implicit electrophysiological marker reflecting the cortical processing of heartbeats, and more broadly interoceptive processing. An increasing number of studies suggest that HEP may be a meaningful clinical measure. However, on the scalp, HEP are low amplitude signals that are mixed with direct cardiac field artefacts. Therefore, signal processing pipelines that separate the cortical HEP from cardiac field artefacts are required. With a view to establishing optimal and standardised HEP pipelines, this review aims to evaluate the current approaches to this analysis used within the literature, address gaps and inconsistencies in HEP pipelines, and highlight the impact of crucial parameter choices. To do this, a scoping review investigated current HEP processing methods and parameters used in EEG and MEG studies. Testing these processing methods on Temple University's normal scalp EEG data (Obeid and Picone, 2016), the effect of different methods/parameters (e.g. HEP window, electrodes, filters, independent component analysis (ICA) and artefact subspace reconstruction (ASR)) on HEP extraction was explored. EEG studies (N=101) demonstrated greater parameter variability and heterogeneity than MEG studies (N=10), although significantly more studies used EEG. ICA without cardiac field artefact and ASR at threshold 20 exhibit similar results for artefact removal. Statistical analysis revealed that the RR interval, the start and end of the HEP window and the start of the baseline correction window significantly affect HEP values in pre-frontal, frontal and centrotemporal electrodes. Publications should report critical values for reliable HEP extraction, emphasising the need for standardised methods to enhance study comparison and reproducibility and establish a gold standard in the field.

Assessing the balance between excitation and inhibition in chronic pain through the aperiodic component of EEG
Chronic pain is a prevalent and debilitating condition whose neural mechanisms are incompletely understood. An imbalance of cerebral excitation and inhibition (E/I), particularly in the medial prefrontal cortex (mPFC), is believed to represent a crucial mechanism in the development and maintenance of chronic pain. Thus, identifying a non-invasive, scalable marker of E/I could provide valuable insights into the neural mechanisms of chronic pain and aid in developing clinically useful biomarkers. Recently, the aperiodic component of the electroencephalography (EEG) power spectrum has been proposed to represent a noninvasive proxy for E/I. We, therefore, assessed the aperiodic component in the mPFC of resting-state EEG recordings in 149 people with chronic pain and 115 healthy participants. We found robust evidence against differences in the aperiodic component in the mPFC between people with chronic pain and healthy participants, and no correlation between the aperiodic component and pain intensity. These findings were consistent across different subtypes of chronic pain and were similarly found in a whole-brain analysis. Their robustness was supported by preregistration and multiverse analyses across many different methodological choices. Together, our results suggest that the EEG aperiodic component does not differentiate between people with chronic pain and healthy individuals. These findings and the rigorous methodological approach can guide future studies investigating non-invasive, scalable markers of cerebral dysfunction in people with chronic pain and beyond.

Effector-Specific Neural Representations of Perceptual Decisions Independent of Motor Actions and Sensory Modalities
Neuroscientific research has shown that perceptual decision-making occurs in effector-specific brain regions that are associated with the required motor response. Recent functional magnetic resonance imaging (fMRI) studies that dissociated decisions from coinciding processes, such as motor actions partly challenge this, indicating abstract representations that might vary across stimulus modalities. However, cross-modal comparisons have been difficult since most task designs differ not only in modality but also in effectors, motor response, and level of abstraction. Here, we describe an fMRI experiment where participants compared frequencies of two sequentially presented visual flicker stimuli in a delayed match-to-comparison task, which controlled for motor actions and stimulus sequence. Using Bayesian modelling, we estimated subjective frequency differences based on the time order effect. These values were applied in support vector regression analysis of a multi-voxel pattern whole-brain searchlight approach to identify brain regions containing information on subjective decision values. Furthermore, a conjunction analysis with data from a re-analyzed analogue vibrotactile study was conducted for a cross-modal comparison. Both analyses revealed significant activation patterns in the left dorsal (PMd) and ventral (PMv) premotor cortex as well as in the bilateral intraparietal sulcus (IPS). While previous primate and human imaging research have implicated these regions in transforming sensory information into action, our findings indicate that the IPS processes abstract decision signals while PMd and PMv represent an effector-specific, but motor response independent encoding of perceptual decisions that persists across sensory domains.

Entorhinal cortex represents task-relevant remote locations independent of CA1
Neurons can collectively represent the current sensory experience while an animal is exploring its environment or remote experiences while the animal is immobile. These remote representations can reflect learned associations and be required for learning. Neurons in the medial entorhinal cortex (MEC) reflect the animal's current location during movement, but little is known about what MEC neurons collectively represent during immobility. Here, we recorded thousands of neurons in superficial MEC and dorsal CA1 as mice learned to associate two pairs of rewarded locations. We found that during immobility, the MEC neural population frequently represented positions far from the animal's location, which we defined as 'non-local coding'. Cells with spatial firing fields at remote locations drove non-local coding, even as cells representing the current position remained active. While MEC non-local coding has been reported during sharp-wave ripples in downstream CA1, we observed non-local coding more often outside of ripples. In fact, CA1 activity was less coordinated with MEC during non-local coding. We further observed that non-local coding was pertinent to the task, as MEC preferentially represented remote task-relevant locations at appropriate times, while rarely representing task-irrelevant locations. Together, this work raises the possibility that MEC non-local coding could strengthen associations between locations independently from CA1.

Multi-omic ADNI CSF and plasma data integration identifies distinct metabolic transitions in disease progression in Alzheimer's Disease
Age and APOE allele status are the two greatest risk factors for Alzheimer's disease, with microglial processing, recycling of debris and cholesterol transport emerging as other key genetic determinants from AD GWAS. How risk factors contribute to neuronal loss is an unanswered question. Using the ADNI dataset, we provide evidence for distinct processes driving neurodegeneration in AD across a range of ADAS13 scores binned into quartiles (Q1-4) found in ADNI. In Q1 individuals, we see evidence of white matter hyperintensities (WMH) associated with complement and HDL proteins, independent of tau and hippocampal atrophy rates. In Q2 individuals, we see specific protein/lipid correlation networks that are associated with tau and hippocampal atrophy. Also in Q2, we see variations in enzyme levels (LPA2G7, LPCAT2) that impact phosphatidylcholine availability for cholesterol efflux onto CNS lipoproteins. Low LPA2G7 and high LPCAT are associated with lower disruption of ANLS, while high LPA2G7 and low LPCAT are associated with higher disruption. In Q3 individuals, DHA and plasmalogens appear to be protective of astrogliosis, presumably by decreasing lipid droplet size, and increasing their lipid debris flux capacity. The networks we identify in this analysis provide evidence that progressively elevated cellular cholesterol levels, likely the result of accelerating neuronal and myelin debris, are perturbing homeostatic processes, resulting in disruption of astrocyte-neuron lactate shuttle (ANLS), contributing to lipid droplet formation, and astrogliosis. Existing studies have already identified elevated cellular cholesterol as the driver of increased access of APP to {beta}- and {gamma}-secretase for {beta}-amyloid production in late-onset AD. Importantly, we provide evidence that points to actionable variations in lipids associated with slower disease progression and decreased metabolic disruption and inflammation. We believe this positive feedback loop (neurodegeneration [->] lipid debris processing [->] metabolic disruption [->] neurodegeneration) is a key destabilizing cycle responsible for disease progression in AD, reinforcing the perspective that Alzheimer's is fundamentally a metabolic disease. Our findings are consistent with established lipid risk factor associations. We anticipate the mechanistic insights from our analysis will advance nutritional and pharmacological interventions and slow cognitive decline.

Examining the Central Auditory Processing Using a Multi-Feature ERP Paradigm to Phonetic, Prosodic and Acoustic Features
Previous studies have shown that multi-feature paradigms can be used for the investigation of the central auditory processing. In this study, we developed a speech multi-feature paradigm with phonetic, prosodic, and acoustic changes. Our aim was to examine the participants' involuntary discrimination of the changes of speech sound features while they were watching a movie without any sound or subtitles. All five deviant conditions (vowel, consonant, stress, intensity, frequency) elicited statistically significant MMN ERP responses which varied in amplitude depending on the condition; stress was also connected with the occurrence of the LDN component. With vowel, consonant and stress among the conditions that received the most statistically significant ERPs, we could suggest that the current multi-feature paradigm can be used to successfully elicit the MMN ERP component and potentially to assess phonological processing in children and adults.

Impaired experience-dependent inter-areal network connectivity across the visual cortex in Fmr1 KO mice
Fragile X syndrome (FX) is the most prevalent inheritable form of autism spectrum disorder (ASD), characterized by hypersensitivity, difficulty in habituating to new sensory stimuli, and intellectual disability. Individuals with FX often experience visual perception and learning deficits. Visual experience leads to the emergence of the familiarity-evoked theta band oscillations in the primary visual cortex (V1) and the lateromedial area (LM) of mice. These theta oscillations in V1 and LM are synchronized with each other, providing a mechanism of sensory multi-areal binding. However, how this multi-areal binding and the corresponding theta oscillations are altered in FX is not known. Using iDISCO whole brain clearing with light-sheet microscopy, we quantified immediate early gene Fos expression in V1 and LM, identifying deficits in experience-dependent neural activity in FX mice. We performed simultaneous in vivo recordings with silicon probes in V1 and LM of awake mice and channelrhodopsin-2-assisted circuit mapping (CRACM) in acute brain slices to examine the neural activity and strength of long-range synaptic connections between V1 and LM in both wildtype (WT) and Fmr1 knockout (KO) mice, the model of FX, before and after visual experience. Our findings reveal synchronized familiarity-evoked theta oscillations in V1 and LM, the increased strength of V1[->]LM functional and synaptic connections, which correlated with the corresponding changes of presynaptic short-term plasticity in WT mice. The LM oscillations were attenuated in FX mice and correlated with impaired functional and synaptic connectivity and short-term plasticity in the feedforward (FF) V1[->]LM and feedback (FB) LM[->]V1 pathways. Finally, using 4Pi single-molecule localization microscopy (SMLM) in thick brain tissue, we identified experience-dependent changes in the density and shape of dendritic spines in layer 5 pyramidal cells of WT mice, which correlated with the functional synaptic measurements. Interestingly, there was an increased dendritic spine density and length in naive FX mice that failed to respond to experience. Our study provides the first comprehensive characterization of the role of visual experience in triggering inter-areal neural synchrony and shaping synaptic connectivity in WT and FX mice.

Proprioception Impacts Body Perception in Healthy Aging: Insights from a Psychophysical and Computational Approach
The experience of owning a body (body ownership, BO) and the perception of our body dimensions (metric body representation, mBR) depend on the integration of multisensory cues. As the human sensory system is subjected to a decline along the lifespan, encompassing all sensory modalities, we hypothesize that body perception may be different in older, as compared to young adults. Here, we investigate this hypothesis by comparing the multisensory processing underlying BO and mBR in healthy older (> 65 years) and young individuals. First, we applied rigorous computational and psychophysical methods to assess alterations in mBR and BO quantitatively. We then modeled the manifold relationship between the observed body misperceptions and the potential underlying sensory, motor, and cognitive factors. The results highlight significant differences between the two groups, with higher distortions in perceived arm dimensions and an increased tendency to experience ownership towards a virtual hand in the aged group. These differences in both mBR and BO are explained by the reduced proprioceptive abilities of older adults, suggesting a crucial role of proprioception in driving age-dependent plasticity in body representations. Overall, our modeling and experimental approach provide new perspectives on altered body perception during aging, suggesting that they stem from the physiological proprioceptive decline occurring in older adults, and laying the groundwork to generate prevention and stimulation strategies to restore accurate body perception in aging.

Distinct subcircuits within the mesolimbic dopamine system encode the salience and valence of social stimuli
The mesolimbic dopamine (DA) system (MDS) is the canonical reward pathway that has been studied extensively in the context of the rewarding properties of sex, food, and drugs of abuse. In contrast, very little is known about the role of the MDS in the processing of the rewarding and aversive properties of social stimuli. Social interactions can be characterized by their salience (i.e., importance) and their rewarding or aversive properties (i.e., valence). Here, we test the novel hypothesis that projections from the medial ventral tegmental area (VTA) to the nucleus accumbens (NAc) core codes for the salience of social stimuli through the phasic release of DA in response to both rewarding and aversive social stimuli. In contrast, we hypothesize that projections from the lateral VTA to the NAc shell codes for the rewarding properties of social stimuli by increasing the tonic release of DA and the aversive properties of social stimuli by reducing the tonic release of DA. Using DA amperometry, which monitors DA signaling with a high degree of temporal and anatomical resolution, we measured DA signaling in the NAc core or shell while rewarding and aversive social interactions were taking place. These findings, as well as additional anatomical and functional studies, provide strong support for the proposed neural circuitry underlying the response of the MDS to social stimuli. Together, these data provide a novel conceptualization of how the functional and anatomical heterogeneity within the MDS detect and distinguish between social salience, social reward, and social aversion.

Lack of Single Amino Acids Transcriptionally Remodels Sensory Systems to Enhance the Intake of Protein and Microbiota
Adequate intake of dietary essential amino acids (eAAs) is vital for protein synthesis and metabolism. Any single eAA deprivation is sufficient to increase protein intake in Drosophila melanogaster. How such nutritional -needs- are transformed into behavioral -wants- remains poorly understood. We derived transcriptomes from the heads of flies deprived of individual eAAs to identify mechanisms by which this is achieved. We found that, while specific eAA deprivations have unique effects on gene expression, a large set of changes are shared across deprivations. We show that Or92a upregulation upon eAA deprivation increases the exploitation of yeast, the main protein source of flies. Furthermore, Ir76a upregulation was crucial for feeding on Lactobacillus, a gut bacterium that ameliorates the fitness of eAA-deprived flies. Our work uncovers common and unique transcriptional changes induced by individual eAA deprivations in an animal and reveals novel mechanisms underlying the organisms behavioral and physiological response to eAA challenges.