bioRxiv Subject Collection: Neuroscience's Journal

Increasing the representation of minoritized youth for inclusive and reproducible brain-behavior associations
Population neuroscience datasets allow researchers to estimate reliable effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals. We employ motion-ordering and motion-ordering+resampling (bagging) to test if these methods preserve functional MRI (fMRI) data in the Adolescent Brain Cognitive Development Study (N=5,733). Black and Hispanic youth exhibited excess head motion relative to data collected from White youth, and were discarded disproportionately when using conventional approaches. Both methods retained more than 99% of Black and Hispanic youth. They produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data. The motion-ordering and bagging methods are two feasible approaches that can enhance sample representation for testing brain-behavior associations and fulfill the promise of consortia datasets to produce generalizable effect sizes across diverse populations.

Distinct visual processing networks for foveal and peripheral visual fields
Foveal and peripheral vision are two distinct modes of visual processing essential for navigating the world. However, it remains unclear if they engage different neural mechanisms and circuits within the visual attentional system. Here, we trained macaques to perform a free-gaze visual search task using natural face and object stimuli and recorded a large number of 14588 visually responsive neurons from a broadly distributed network of brain regions involved in visual attentional processing. Foveal and peripheral units had substantially different proportions across brain regions and exhibited systematic differences in encoding visual information and visual attention. The spike-LFP coherence of foveal units was more extensively modulated by both attention and visual selectivity, thus indicating differential engagement of the attention and visual coding network compared to peripheral units. Furthermore, we delineated the interaction and coordination between foveal and peripheral processing for spatial attention and saccade selection. Finally, the search became more efficient with increasing target-induced desynchronization, and foveal and peripheral units exhibited different correlations between neural responses and search behavior. Together, the systematic differences between foveal and peripheral processing provide valuable insights into how the brain processes and integrates visual information from different regions of the visual field.

Reduction in olfactory ability in aging Mitf mutant mice without neurodegeneration
Age-related decline occurs in most brain structures and sensory systems. An illustrative case is olfaction, where the olfactory bulb (OB) undergoes deterioration with age, resulting in reduced olfactory ability. Decline in olfaction is also associated with early symptoms of neurodegenerative diseases including Alzheimer's disease (AD) and Parkinson's disease (PD). However, the underlying reasons are unclear. The microphthalmia-associated transcription factor (MITF) is expressed in the projection neurons (PNs) of the OB - the mitral and tufted (M/T) cells. Primary M/T cells from Mitf mutant mice show hyperactivity, potentially attributed to reduced expression of a key potassium channel subunit, Kcnd3/Kv4.3. This influences intrinsic plasticity, an essential mechanism involving the non-synaptic regulation of neuronal activity. As neuronal hyperactivity often precedes neurodegenerative conditions, the current study aimed to determine whether the absence of Mitf has degenerative effects during aging. Aged Mitf mutant mice showed reduced olfactory ability without inflammation. However, an increase in the expression of potassium channel subunit genes in the OB suggests that during aging compensatory mechanisms lead to stabilization.

Loss of AMPK potentiates inflammation by activating the inflammasome after traumatic brain injury in mice.
Traumatic brain injury (TBI) is a significant public health concern characterized by a complex cascade of cellular events. TBI induces adenosine monophosphate activated protein kinase (AMPK) dysfunction impairs energy balance activates inflammatory cytokines and leads to neuronal damage. AMPK is a key regulator of cellular energy homeostasis during inflammatory responses. Recent research has revealed its key role in modulating the inflammatory process in TBI. Following TBI the activation of AMPK can influence various important pathways and mechanisms including metabolic pathways and inflammatory signaling. Our study investigated the effects of post TBI loss of AMPK function on functional outcomes inflammasome activation and inflammatory cytokine production. Male C57BL/6 adult wild type (WT) and AMPK knockout (AMPK-KO) mice were subjected to a controlled cortical impact (CCI) model of TBI or sham surgery. The mice were tested for behavioral impairment at 24 h post TBI thereafter mice were anesthetized and their brains were quickly removed for histological and biochemical evaluation. In vitro we investigated inflammasome activation in mixed glial cells stimulated with lipopolysaccharides+ Interferon gamma (LI) (0.1 g/20 ng/ml LPS/IFNg) for 6 h to induce an inflammatory response. Estimating the nucleotide-binding domain, leucine richcontaining family pyrin domain containing western blotting ELISA and qRT-PCR performed 3 (NLRP3) inflammasome activation and cytokine production. Our findings suggest that TBI leads to reduced AMPK phosphorylation in WT mice and that the loss of AMPK correlates with worsened behavioral deficits at 24 h post TBI in AMPK-KO mice as compared to WT mice. Moreover compared with the WT mice AMPK-KO mice exhibit exacerbated NLRP3 inflammasome activation and increased expression of proinflammatory mediators such as IL-1b IL-6 TNF-a iNOS and Cox 2. These results align with the in vitro studies using brain glial cells under inflammatory conditions, demonstrating greater activation of inflammasome components in AMPK-KO mice than in WT mice. Our results highlighted the critical role of AMPK in TBI outcomes. We found that the absence of AMPK worsens behavioral deficits and heightens inflammasome mediated inflammation thereby exacerbating brain injury after TBI. Restoring AMPK activity after TBI could be a promising therapeutic approach for alleviating TBI related damage.

Interleaved single and bursting spiking resonance in neurons
Under in vivo conditions, CA1 pyramidal cells from the hippocampus display transitions from single spikes to bursts. It is believed that subthreshold hyperpolarization and depolarization, also known as down and up-states, play a pivotal role in these transitions. Nevertheless, a central impediment to correlating suprathreshold (spiking) and subthreshold activity has been the technical difficulties of this type of recordings, even with widely used calcium imaging or multielectrode recordings. Recent work using voltage imaging with genetically encoded voltage indicators has been able to correlate spiking patterns with subthreshold activity in a variety of CA1 neurons, and recent computational models have been able to capture these transitions. In this work, we used a computational model of a CA1 pyramidal cell to investigate the role of intrinsic conductances and oscillatory patterns in generating down and up-states and their modulation in the transition from single spiking to bursting. Specifically, the emergence of distinct spiking resonances between these two spiking modes that share the same voltage traces in the presence of theta or gamma oscillatory inputs, a phenomenon we call interleaved single and bursting spiking resonance. We noticed that these resonances do not necessarily overlap in frequency or amplitude, underscoring their relevance for providing flexibility to neural processing. We studied the conductance values of three current types that are thought to be critical for the bursting behavior: persistent sodium current (INaP) and its conductance GNaP, delayed rectifier potassium (IKDR) and its conductance GKDR, and hyperpolarization-activated current (Ih) and its conductance Gh. We conclude that the intricate interplay of ionic currents significantly influences the neuronal firing patterns, transitioning from single to burst firing during sustained depolarization. Specifically, the intermediate levels of GNaP and GKDR facilitate spiking resonance at gamma frequency inputs. The resonance characteristics vary between single and burst firing modes, each displaying distinct amplitudes and resonant frequencies. Furthermore, low GNaP and high GKDR values lock bursting to theta frequencies, while high GNaP and low GKDR values lock single spiking to gamma frequencies. Lastly, the duration of quiet intervals plays a crucial role in determining the likelihood of transitioning to either bursting or single spiking modes. We confirmed that the same features were present in previously recorded in vivo voltage-imaging data. Understanding these dynamics provides valuable insights into the fundamental mechanisms underlying neuronal excitability under in vivo conditions.

Distinct attentional profile and functional connectivity of neurons with visual feature coding in the primate brain
Visual attention and object recognition are two critical cognitive functions that significantly influence our perception of the world. While these neural processes converge on the temporal cortex, the exact nature of their interactions remains largely unclear. Here, we systematically investigated the interplay between visual attention and object feature coding by training macaques to perform a free-gaze visual search task using natural face and object stimuli. With a large number of units recorded from multiple brain areas, we discovered that units exhibiting visual feature coding displayed a distinct attentional response profile and functional connectivity compared to units not exhibiting feature coding. Attention directed towards search targets enhanced the pattern separation of stimuli across brain areas, and this enhancement was more pronounced for units encoding visual features. Our findings suggest two stages of neural processing, with the early stage primarily focused on processing visual features and the late stage dedicated to processing attention. Importantly, feature coding in the early stage could predict the attentional effect in the late stage. Together, our results suggest an intricate interplay between visual feature and attention coding in the primate brain, which can be attributed to the differential functional connectivity and neural networks engaged in these processes.

Repetitive Somatosensory Stimulation Shrinks The Body Image
Current models of mental body representations (MBRs) indicate that tactile inputs feed several of them for different functions, implying that altering tactile inputs may affect MBRs differently. Here we tested this hypothesis by leveraging Repetitive Somatosensory Stimulation (RSS), known to improve tactile perception by modulating primary somatosensory cortex (SI) activity, and measured its effects over the body image, the body model and the superficial schema in a randomized sham-controlled, double-blind cross-over study. Results show that RSS affected the body image, participants perceiving their finger size as being smaller after RSS. While previous work showed increase of finger size perception after tactile anesthesia (Gandevia & Phegan 1999), these findings reveal that tactile inputs can diametrically modulate the body image. In contrast, RSS did not alter the body model or superficial schema. In addition, we report a novel mislocalization pattern, with a bias towards the middle finger in the distal phalanges that reverses towards the thumb in the proximal phalanx, enriching the known distortions of the superficial schema. Overall, these findings provide novel insights into the functional organization of MBRs and their relationships with somatosensory information. Reducing the perceived body size through RSS could be useful in helping treat body image disturbance.

A neural mass model with neuromodulation
The study of brain activity and its function requires the development of computational models alongside experimental investigations to explore different effects of multiple mechanisms at play in the central nervous system. Chemical neuromodulators such as dopamine play central roles in regulating the dynamics of neuronal populations. In this work, we propose a modular framework to capture the effects of neuromodulators at the neural mass level. Using this framework, we formulate a specific model for dopamine dynamics affecting D1-type receptors. We detail the dynamical repertoire associated with dopamine concentration evolution. Finally, we give one example of use in a basal-ganglia network in healthy and pathological conditions.

Mitochondrial Dynamics and Bioenergetics in iPSC-Derived Neurons with Familial Alzheimer's Disease Mutations
Mitochondrial (MT) dysfunction is a hallmark of Alzheimer's Disease (AD), but the specific defects across forms of AD are unknown. We measured multiple parameters of MT dynamics and function, and neurite degeneration, in iPSC-derived human neurons possessing natural and engineered mutations in PS1, PS2, and APP genes. Mutations in all three genes altered MT function measured by basal, ATP-linked, and maximal oxygen consumption rate; and spare respiratory capacity, with PS1/PS2 alleles being more severe than APP mutations. Electron flow through Complexes I-IV was decreased in PS1/PS2 mutations but; in contrast, APP alleles had only modest impairments of CI and CII. We measured aspects of MT dynamics including fragmentation, and neurite degeneration, both of which were dramatic in PS1/PS2 alleles, but essentially absent in APP alleles. The marked differences in MT pathology may occur from the distinct ways APP is processed into amyloid beta; and may correlate with the disease severity.

Effects of Centrally Acting Analgesics on Resting-State Electroencephalography Biomarker Candidates of Chronic Pain
Resting-state electroencephalography (rsEEG) holds promise as a biomarker of chronic pain. However, the impact of centrally acting analgesics like opioids, antiepileptics, and antidepressants on rsEEG remains unclear. This confounds and limits the interpretability of previous studies and questions the validity of rsEEG biomarker candidates of chronic pain. We, therefore, aimed to elucidate the effects of opioids, antiepileptics, and antidepressants on common rsEEG biomarker candidates of chronic pain. To this end, we analyzed two large, independent rsEEG datasets, including 220 people with chronic pain. We performed preregistered multivariate Bayesian analyses and controlled for the potential confounds of age, pain intensity, and depression. The results predominantly provided evidence against effects of centrally acting analgesics on peak alpha frequency, oscillatory power in different frequency bands, and connectivity-based network measures. Although these findings do not rule out any effects of analgesics on rsEEG, they argue against medium to large effects of centrally acting analgesics on rsEEG. Thus, the findings strengthen the validity of rsEEG biomarker candidates of chronic pain and might thereby help to develop clinically valuable biomarkers of chronic pain.

Binary Brains: How Excitable Dynamics Simplify Neural Connectomes
Fiber networks connecting different brain regions are the structural foundation of brain dynamics and function. Recent studies have provided detailed characterizations of neural connectomes with weighted connections. However, the topological analysis of weighted networks still has conceptual and practical challenges. Consequently, many investigations of neural networks are performed on binarized networks, and the functional impact of unweighted versus weighted networks is unclear. Here we show, for the widespread case of excitable dynamics, that the excitation patterns observed in weighted and unweighted networks are nearly identical, if an appropriate network threshold is selected. We generalize this observation to different excitable models, and formally predict the network threshold from the intrinsic model features. The network-binarizing capacity of excitable dynamics suggests that neural activity patterns may primarily depend on the strongest structural connections. Our findings have practical advantages in terms of the computational cost of representing and analyzing complex networks. There are also fundamental implications for the computational simulation of connectivity-based brain dynamics and the computational function of diverse other systems governed by excitable dynamics such as artificial neural networks.

Restoring hippocampal glucose metabolism rescues cognition across Alzheimer's disease pathologies
Impaired cerebral glucose metabolism is a pathologic feature of Alzheimer Disease (AD), and recent proteomic studies highlight a disruption of glial carbohydrate metabolism with disease progression. Here, we report that inhibition of indoleamine-2,3-dioxygenase 1 (IDO1), which metabolizes tryptophan to kynurenine (KYN) in the first step of the kynurenine pathway, rescues hippocampal memory function and plasticity in preclinical models of amyloid and tau pathology by restoring astrocytic metabolic support of neurons. Activation of IDO1 in astrocytes by amyloid-beta42 and tau oligomers, two major pathological effectors in AD, increases KYN and suppresses glycolysis in an AhR-dependent manner. Conversely, pharmacological IDO1 inhibition restores glycolysis and lactate production. In amyloid-producing APPSwe-PS1{triangleup}E9 and 5XFAD mice and in tau-producing P301S mice, IDO1 inhibition restores spatial memory and improves hippocampal glucose metabolism by metabolomic and MALDI-MS analyses. IDO1 blockade also rescues hippocampal long-term potentiation (LTP) in a monocarboxylate transporter (MCT)-dependent manner, suggesting that IDO1 activity disrupts astrocytic metabolic support of neurons. Indeed, in vitro mass-labeling of human astrocytes demonstrates that IDO1 regulates astrocyte generation of lactate that is then taken up by human neurons. In co-cultures of astrocytes and neurons derived from AD subjects, deficient astrocyte lactate transfer to neurons was corrected by IDO1 inhibition, resulting in improved neuronal glucose metabolism. Thus, IDO1 activity disrupts astrocytic metabolic support of neurons across both amyloid and tau pathologies and in a model of AD iPSC-derived neurons. These findings also suggest that IDO1 inhibitors developed for adjunctive therapy in cancer could be repurposed for treatment of amyloid- and tau-mediated neurodegenerative diseases.

Impact of dendritic non-linearities on the computational capabilities of neurons
Multiple neurophysiological experiments have shown that dendritic non-linearities can have a strong influence on synaptic input integration. In this work we model a single neuron as a two-layer computational unit with non-overlapping sign-constrained synaptic weights and a biologically plausible form of dendritic non-linearity, which is analytically tractable using statistical physics methods. Using both analytical and numerical tools, we demonstrate several key computational advantages of non-linear dendritic integration with respect to models with linear synaptic integration. We find that the dendritic non-linearity concurrently enhances the number of possible learned input-output associations and the learning velocity, and we characterize how capacity and learning speed depend on the implemented non-linearity and the levels of dendritic and somatic inhibition. We find that experimentally observed connection probabilities naturally emerge in neurons with sign-constrained synapses as a consequence of non-linear dendritic integration, while in models with linear integration, an additional robustness parameter must be introduced in order to reproduce realistic connection probabilities. Non-linearly induced sparsity comes with a second central advantage for neuronal information processing, i.e. input and synaptic noise robustness. By testing our model on standard real-world benchmark datasets inspired by deep learning practice, we observe empirically that the non-linearity provides an enhancement in generalization performance, showing that it enables to capture more complex input/output relations.

Exploration and exploitation are flexibly balanced during local search in flies
After finding food, a foraging animal must decide whether to continue feeding, or to explore the environment for potentially better options. One strategy to negotiate this tradeoff is to perform local searches around the food but repeatedly return to feed. We studied this behavior in flies and used genetic tools to uncover the underlying mechanisms. Over time, flies gradually expand their search, shifting from primarily exploiting food sources to exploring the environment, a change that is likely driven by increases in satiety. We found that flies' search patterns preserve these dynamics even as the overall scale of the search is modulated by starvation-induced changes in metabolic state. In contrast, search induced by optogenetic activation of sugar sensing neurons does not show these dynamics. We asked what navigational strategies underlie local search. Using a generative model, we found that a change in locomotor pattern after food consumption could account for repeated returns to the food, but failed to capture relatively direct, long return trajectories. Alternative strategies, such as path integration or sensory taxis could allow flies to return from larger distances. We tested this by individually silencing the fly's head direction system, olfaction and hygrosensation, and found that the only substantial effect was from perturbing hygrosensation, which reduced the number of long exploratory trips. Our study illustrates that local search is composed of multiple behavioral features that evolve over time based on both internal and external factors, providing a path towards uncovering the underlying neural mechanisms.

Strong, but not weak, noise correlations are beneficial for population coding
Neural correlations play a critical role in sensory information coding. They are of two kinds: signal correlations, when neurons have overlapping sensitivities, and noise correlations from network effects and shared noise. It is commonly thought that stimulus and noise correlations should have opposite signs to improve coding. However, experiments from early sensory systems and cortex typically show the opposite effect, with many pairs of neurons showing both types of correlations to be positive and large. Here, we develop a theory of information coding by correlated neurons which resolves this paradox. We show that noise correlations are always beneficial if they are strong enough. Extensive tests on retinal recordings under different visual stimuli confirm our predictions. Finally, using neuronal recordings and modeling, we show that for high dimensional stimuli noise correlation benefits the encoding of fine-grained details of visual stimuli, at the expense of large-scale features, which are already well encoded.

Propagating cortical waves coordinate sensory encoding and memory retrieval in the human brain
Complex behavior entails a balance between taking in sensory information from the environment and utilizing previously learned internal information. Experiments in behaving mice have demonstrated that the brain continually alternates between outward and inward modes of cognition, switching its mode of operation every few seconds. Further, each state transition is marked by a stereotyped cascade of neuronal spiking that pervades most forebrain structures. Here we analyzed large fMRI datasets to demonstrate that a similar switching mechanism governs the operation of the human brain. We found that human brain activity was punctuated every several seconds by coherent, propagating waves emerging in the exteroceptive sensorimotor regions and terminating in the interoceptive default mode network. As in the mouse, the issuance of such events coincided with fluctuations in pupil size, indicating a tight relationship with arousal fluctuations, and this phenomenon occurred across behavioral states. Strikingly, concurrent measurement of human performance in a visual memory task indicated that each cycle of propagating fMRI waves sequentially promoted the encoding of semantic information and self-directed retrieval of memories. Together, these findings indicate that human cognitive performance is governed by autonomous switching between exteroceptive and interoceptive states. This apparently conserved feature of mammalian brain physiology bears directly on the integration of sensory and mnemonic information during everyday behavior.

The Incisive Duct as a Pathway for Early Vomeronasal Communication in Neonatal Dogs
The detection of chemical signals by the vomeronasal organ (VNO) is critical for communication among mammals from an early age, influencing behaviors such as suckling and recognition of the mother and conspecifics. Located in a concealed position at the base of the nasal cavity, the VNO features a duct covered with a sensory epithelium rich in neuroreceptors. A critical aspect of VNO functionality is the efficient access of stimuli from the nasal and oral cavities to the receptors. In adult dogs, it has been demonstrated through in vivo magnetic resonance imaging and anatomically postmortem how the VNO duct (VD) communicates to the environment through the incisive duct (ID). However, in newborn puppies, the existence of functional communication between the ID and the VD has not been confirmed to date, raising doubts about the potential physiological obliteration of the ID due to its small size and the degree of immaturity of the puppies at birth. Determining this aspect is necessary to evaluate the role played by chemical communication in this critical phase for the survival and socialization of puppies. This study employs serial histological staining techniques to examine the presence and functionality of the incisive duct in neonatal dogs. The serial histological sections have confirmed both the existence of functional communication between both the vomeronasal and incisive ducts in perinatal puppies, and the dual functional communication of the incisive duct with the oral and nasal cavities. The ID shows an uninterrupted lumen along its path and is associated with a sophisticated cartilaginous complex that prevents its collapse, as well as erectile tissue rich in blood vessels and connective tissue that acts as a cushion, facilitating its action under pressure induced by sampling behaviors such as tonguing. This investigation demonstrates the communicative capabilities of the VNO during the perinatal stage in dogs.

Semantic Influences on Object Detection: Drift Diffusion Modeling Provides Insights Regarding Mechanism
Research shows that semantics, activated by words, impacts object detection. Skocypec & Peterson (2022) indexed object detection via correct reports of where figures lie in bipartite displays depicting familiar objects on one side of a border. They reported 2 studies with intermixed Valid and Invalid labels shown before test displays and a third, control, study. Valid labels denoted display objects. Invalid labels denoted unrelated objects in a different or the same superordinate-level category in studies 1 & 2, respectively. We used drift diffusion modeling (DDM) to elucidate the mechanisms of their results. DDM revealed that, following Valid labels, drift rate toward the correct decision increased, i.e., SNR increased. Following Invalid labels, SNR was lower only for upright displays in study 2. Thresholds were higher in studies 1 & 2 than in control. That more evidence must be accumulated from displays that follow labels implies that familiar object detection entails semantic activation. Threshold was even higher following Invalid labels in study 2, suggesting that more evidence from the display is needed to resolve within- category conflicts. These results support the view that semantic networks are engaged in object detection.

Computational Models of Age-Associated Cognitive Slowing
Background: Cognitive slowing accompanies normal aging, yet understanding of the mechanisms of slowing is limited at the network and neuronal level. Relating the pathophysiological factors responsible for cognitive slowing, and interpreting its relationship to working memory, requires multiscale computer modeling. Objective: The aim of this research is to explore multiple mechanisms of cognitive slowing using computational modeling of the cortex to link neuronal activity with cognitive content. Method: We developed multiscale computer models of a simple cognitive task - Condition 1 of the Stroop recognition task - using the Nengo system, a cognitive simulation environment with a semantic pointer architecture developed to model cognitive tasks using spiking neural networks. We explored how changes associated with aging such as increased input noise, axonal loss, neuronal loss, and feedback would affect the function of the models. Results: Axonal loss and increased input noise produced profound slowing. High levels of neuronal loss severely impaired memory and paradoxically decreased slowing via the ability to respond more quickly by 'releasing' a prior memory. Increased feedback improved memory at the cost of increased slowing. Conclusion: Our simulations suggest that significant slowing could be caused by white matter loss (axonal loss) or input signal degradation (which could be caused by visual or other afferent system worsening). As neuronal loss markedly decreased the duration of working memory, we propose that physiological feedback is increased to preserve working memory at the cost of further cognitive slowing.

Robust sub-network fingerprints of brief signals in the MEGfunctional connectome for single-patient classification
Recent studies have shown that the Magnetoencephalography (MEG) functional connectome is differentiable in a same-day recording with only 20 latent components, showing variability across synchrony measures and spectral bands. Here, we succeed with 45/4,005 components of the functional connectome on a multi-day dataset of 43 subjects and link it to related clinical applications. By optimizing sub-networks of 10/90 regions with 30 seconds of broadband signal, we find robust fingerprinting performance, showing patterns of region re-occurrence. From a search space of 5.72 trillion, we find 46,071 of many more acceptable solutions, with minimal duplicates found in our optimization. Finally, we show that each of these sub-networks can identify thirty Parkinsons' patient sub-networks from thirty healthy controls' with a mean F1 score of 0.716 +/- 0.090SD. MEG fingerprints have previously been shown on multiple occasions to hold rich information on the stage and severity of progressive neurodegenerative diseases using significantly fewer features. Furthermore, these sub-networks may similarly be useful for identifying patterns across age, genetics, and cognition.

An Investigation of Parameter-Dependent Cell-Type Specific Effects of Transcranial Focused Ultrasound Stimulation Using an Awake Head-Fixed Rodent Model
Transcranial focused ultrasound (tFUS) is a promising neuromodulation technique able to target shallow and deep brain structures with high precision. Previous studies have demonstrated that tFUS stimulation responses are both cell-type specific and controllable through altering stimulation parameters. Specifically, tFUS can elicit time-locked neural activity in regular spiking units (RSUs) that is sensitive to increases in pulse repetition frequency (PRF), while time-locked responses are not seen in fast spiking units (FSUs). These findings suggest a unique capability of tFUS to alter circuit network dynamics with cell-type specificity; however, these results could be biased by the use of anesthesia, which significantly modulates neural activities. In this study, we develop an awake head-fixed rat model specifically designed for tFUS study, and address a key question if tFUS still has cell-type specificity under awake conditions. Using this novel animal model, we examined a series of PRFs and burst duty cycles (DCs) to determine their effects on neuronal subpopulations without anesthesia. We conclude that cell-type specific time-locked and delayed responses to tFUS as well as PRF and DC sensitivity are present in the awake animal model and that despite some differences in response, isoflurane anesthesia is not a major confound in studying the cell-type specificity of ultrasound neuromodulation. We further determine that, in an awake, head-fixed setting, the preferred PRF and DC for inducing time-locked excitation with our pulsed tFUS paradigm are 1500 Hz and 60%, respectively.

Behavioral and neural mechanisms of face-specific attention during goal-directed visual search
Goal-directed visual attention is a fundamental cognitive process that enables animals to selectively focus on specific regions of the visual field while filtering out irrelevant information. However, given the domain specificity of social behaviors, it remains unclear whether attention to faces versus non-faces recruits different neurocognitive processes. In this study, we simultaneously recorded activity from temporal and frontal nodes of the attention network while macaques performed a goal-directed visual search task. V4 and inferotemporal (IT) visual category-selective units, selected during cue presentation, discriminated fixations on targets and distractors during the search, but were differentially engaged by face and house targets. V4 and IT category-selective units also encoded fixation transitions and search dynamics. Compared to distractors, fixations on targets reduced spike-LFP coherence within the temporal cortex. Importantly, target-induced desynchronization between the temporal and prefrontal cortices was only evident for face targets, suggesting that attention to faces differentially engaged the prefrontal cortex. We further revealed bidirectional theta influence between the temporal and prefrontal cortices using Granger causality, which was again disproportionate for faces. Finally, we showed that the search became more efficient with increasing target-induced desynchronization. Together, our results suggest domain specificity for attending to faces and an intricate interplay between visual attention and social processing neural networks.

Human induced pluripotent stem cell-derived microglia contribute to thepathophysiology of Fragile X syndrome via increased RAC1 signaling
Fragile X syndrome (FXS) is one of the most common monogenic causes of neurodevelopmental disorders characterized by intellectual disability, autism and epilepsy. Emerging evidence suggests a role for immune dysfunction in autism. Using induced pluripotent stem cell (iPSC)-derived microglial cells from FXS patients (mFXS-MG) and FMR1-deficient microglia from FMR1-knock out human embryonic stem cells (FMR1 KO-MG), we show that loss-of-function of Fragile X Messenger Ribonucleoprotein (FMRP) leads to cell autonomous phagocytic deficits and a proinflammatory state in microglia when compared to gene-corrected controls. Moreover, increased RAC1 signaling in mFXS-MG and FMR1 KO-MG results in increased actin polymerization and enhanced activation of NF-kB signaling. Exposure of control iPSC-derived cortical neuron cultures to conditioned medium from proinflammatory mFXS-MG results in hyperexcitability. Importantly, pharmacological inhibition of RAC1 signaling in mFXS-MG attenuates their proinflammatory profile and corrects the neuronal hyperexcitability caused by the conditioned medium. Our results suggest that microglia impair neuronal function in FXS, which can be prevented by targeting of RAC1 signaling.

Sequential estimation of nonstationary oscillator states and stimulus responses
Neural oscillations have been linked to multiple behaviors and neuropsychiatric disorders. The individual contributions to behavior from both oscillations and non-oscillatory activity are still unclear, complicating efforts to link neurophysiology to cognition, hindering the discovery of novel biomarkers, and preventing the development of effective therapeutics. To overcome these hurdles, it will be critical to investigate the biological origins of neural oscillations by characterizing the dynamic properties of different brain regions. The dynamical regime for a population of neurons generating oscillations in neural recordings can be discovered by stimulating the population and recording its subsequent response to stimulation. There are different dynamical regimes that can produce population-level neural oscillations. For certain dynamical regimes, like that of a nonlinear oscillator, the phase response curve (PRC) can help differentiate the dynamic state of the population. The PRC can be measured by stimulating the population across different phases of its oscillatory state. However, neural dynamics are non-stationary, so neural oscillations will vary in frequency and amplitude across a recording and the PRC can change over time. This non-stationarity could bias a PRC estimated from an electrophysiological experiment, preventing accurate characterization of a neural population's dynamics. This necessitates tools that can operate online to trigger stimulation and update PRC estimates. To that end, we develop online methods for tracking non-stationary oscillations and recovering PRCs corrupted by estimation errors. We validate the performance of our non-stationary oscillation estimator compared to both a known ground truth model and an alternative phase estimation approach. We demonstrate that a PRC can be recovered online under different random error conditions in silico and that a similar amplitude response curve (ARC) can be estimated from physiologic data using online methods compared to offline approaches.

Simply crushed Zizyphi spinosi semen prevents neurodegenerative diseases and reverses age-related cognitive decline in mice
Neurodegenerative diseases are age-related disorders characterized by the cerebral accumulation of amyloidogenic proteins, and cellular senescence underlies their pathogenesis. Thus, it is necessary for preventing these diseases to remove toxic proteins, repair damaged neurons, and suppress cellular senescence. As a source for such prophylactic agents, we selected Zizyphi spinosi semen (ZSS), a medicinal herb used in traditional Chinese medicine. ZSS hot water extract ameliorated A{beta} and tau pathology and cognitive impairment in mouse models of Alzheimers disease and frontotemporal dementia. Non-extracted ZSS simple crush powder showed stronger effects than the extract and improved -synuclein pathology and cognitive/motor function in Parkinsons disease model mice. Furthermore, when administered to normal aged mice, the ZSS powder suppressed cellular senescence, reduced DNA oxidation, promoted brain-derived neurotrophic factor expression and neurogenesis, and enhanced cognition to levels similar to those in young mice. The quantity of known active ingredients of ZSS, jujuboside A, jujuboside B, and spinosin, was not proportional to the nootropic activity of ZSS. These results suggest that ZSS simple crush powder is a promising dietary material for the prevention of neurodegenerative diseases and brain aging.

Spiking network model of the cerebellum as a reinforcement learning machine
The cerebellum has been considered to perform error-based supervised learning via long-term depression (LTD) at synapses between parallel fibers and Purkinje cells (PCs). Since the discovery of multiple synaptic plasticities other than LTD, recent studies have suggested that synergistic plasticity mechanisms could enhance the learning capability of the cerebellum. We have proposed that the mechanisms allow the cerebellar circuit to perform reinforcement learning (RL). However, its detailed spike-based implementation is still missing. In this research, we implemented a cerebellar spiking network as an actor-critic model based on known anatomical properties of the cerebellum. We confirmed that our model successfully learned a state value and solved the mountain car task, a simple RL benchmark. Furthermore, our model demonstrated the ability to solve the delay eyeblink conditioning task using biologically plausible internal dynamics. The study presents the implementation of the first cerebellar spiking network model capable of performing RL.

Attenuated processing of vowels in the left hemisphere predicts speech-in-noise perception deficit in children with autism
Background: Difficulties with speech-in-noise perception in autism spectrum disorders (ASD) may be associated with impaired analysis of speech sounds, such as vowels, which represent the fundamental phoneme constituents of human speech. Vowels elicit early (< 100 ms) sustained processing negativity (SPN) in the auditory cortex that reflects the detection of an acoustic pattern based on the presence of formant structure and/or periodic envelope information (f0) and its transformation into an auditory "object". Methods: We used magnetoencephalography (MEG) and individual brain models to investigate whether SPN is altered in children with ASD and whether this deficit is associated with impairment in their ability to perceive speech in the background of noise. MEG was recorded while boys with ASD and typically developing boys passively listened to sounds that differed in the presence/absence of f0 periodicity and formant structure. Word-in-noise perception was assessed in the separate psychoacoustic experiment using stationary and amplitude modulated noise with varying signal-to-noise ratio. Results: SPN was present in both groups with similarly early onset. In children with ASD, SPN associated with processing formant structure was reduced predominantly in the cortical areas lateral to and medial to the primary auditory cortex, starting at ~ 150 - 200 ms after the stimulus onset. In the left hemisphere, this deficit correlated with impaired ability of children with ASD to recognize words in amplitude-modulated noise, but not in stationary noise. Limitations: Our analysis was limited to the auditory cortical areas, while ASD vs TD differences in vowel processing may exist beyond these areas. It is not clear if the SPN group differences are specific to vowels or are also present for other acoustic patterns with coherent frequency structure. Conclusions: These results suggest that perceptual grouping of vowel formants into phonemes is impaired in children with ASD and that, in the left hemisphere, this deficit contributes to their difficulties with speech perception in fluctuating background noise.

MICROBIOME-MODIFIED METABOLITES PREDICT ACUTE BRAIN INJURY OUTCOME
BACKGROUND. Acute brain injury (ABI)-mediated disruption of the microbiome may potentiate inflammation and secondary brain injury (SBI). However, microbial-specific mediators and mechanisms remain unclear. METHODS. Thirty-five consecutive patients with ABI admitted to the neuroscience critical care unit at the University of Chicago were prospectively studied. Injury severity at hospital admission was assessed using the Injury Severity Score (ISS) and the Glasgow Coma Scale (GCS). Final neurologic function was assessed via the Glasgow Outcome Score extended (GOSe). Serum, plasma, and stool targeted metabolomics, as well as stool shotgun metagenomics, were performed on longitudinal samples collected during hospitalization. RESULTS. Multivariate analysis identified microbiome-modified metabolites that were positively and negatively associated with functional outcomes after ABI. Novel identification of conjugated bile acid (BA) species and vitamin B12 precursors indicative of outcome were detected in the first collected samples (within 48 hours). Network analysis revealed greater integration of negatively associated metabolites across tissues and identified tauro-a/B-muricholic acid (TMCA) as central to the cross-tissue metabolomes. CONCLUSIONS. Microbiome metabolites may be useful in assessing brain injury outcomes to inform treatment. Bile acid species transformed by the gut microbiome are predictive of ABI outcome.

N2 Sleep Inspires Insight
Humans sometimes have an insight that leads to a sudden and drastic performance improvement on the task they are working on. The precise origins of such insights are unknown. Some evidence has shown that sleep facilitates insights, while other work has not found such a relationship. One recent suggestion that could explain this mixed evidence is that different sleep stages have differential effects on insight. In addition, computational work has suggested that neural variability and regularisation play a role in increasing the likelihood of insight. To investigate the link between insight and different sleep stages as well as regularisation, we conducted a preregistered study in which N=90 participants performed a perceptual insight task before and after a 20 minute daytime. Sleep EEG data showed that N2 sleep, but not N1 sleep, increases the likelihood of insight after a nap, suggesting a specific role of deeper sleep. Exploratory analyses of EEG power spectra showed that spectral slopes could predict insight beyond sleep stages, which is broadly in line with theoretical suggestions of a link between insight and regularisation. In combination, our findings point towards a role of N2 sleep and aperiodic, but not oscillatory, neural activity for insight.

The pathogenicity of PSEN2 variants is tied to Aβ production and homology to PSEN1
INTRODUCTION: Though recognized as a potential cause of Autosomal Dominant Alzheimers Disease, the pathogenicity of many PSEN2 variants remains uncertain. We compared A{beta} production across all missense PSEN2 variants in the Alzforum database and, when possible, to corresponding PSEN1 variants. METHODS: We expressed 74 PSEN2 variants, 21 of which had homologous PSEN1 variants with the same amino acid substitution, in HEK293 cells lacking PSN1/2. A{beta} production was compared to age at symptom onset (AAO) and between homologous PSEN1/2 variants. RESULTS: A{beta} 42/40 and A{beta} 37/42 ratios were associated with AAO across PSEN2 variants, strongly driven by PSEN2 variants with PSEN1 homologs. PSEN2 AAO was 18.3 years later compared to PSEN1 homologs. A{beta} ratios from PSEN1/2 homologs were highly correlated, suggesting a similar mechanism of {gamma}-secretase dysfunction. DISCUSSION: The existence of a PSEN1 homolog and patterns of A{beta} production are important considerations in assessing the pathogenicity of previously-reported and new PSEN2 variants.

Cell-specific wiring routes information flow through hippocampal CA3
The hippocampus is dogmatically described as a trisynaptic circuit. Dentate gyrus granule cells, CA3 pyramidal neurons (PNs), and CA1 PNs are serially connected, forming a circuit that critically enables memory storage in the brain. However, fundamental aspects of hippocampal function go beyond this simplistic 'trisynaptic' definition. CA3 PNs connect not only to CA1, but also establish the largest autoassociative network in the brain. In addition, CA3 PNs are not uniform, differing in their morphology, intrinsic properties, and even the extent of granule cell input. Understanding how these different subtypes of CA3 PNs are embedded in the hippocampal network is essential for our quest to understand learning and memory. Here, we performed simultaneous multi-cellular patch-clamp recordings from up to eight CA3 PNs in acute mouse hippocampal slices, testing 3114 possible connections between identified cells. Combined with post-hoc morphological analysis, this allowed full characterization of neuronal heterogeneity in functioning microcircuits. We demonstrate that CA3 PNs can be divided into distinct 'deep' and 'superficial' subclasses, with altered input-output balance. While both subtypes formed recurrent connectivity within classes, connectivity between subtypes was surprisingly asymmetric. Recurrent connectivity was abundant from superficial to deep, but almost absent from deep to superficial PNs, thereby splitting CA3 into parallel recurrent networks which will allow more complex information processing. Finally, we observed innervation of PN subclasses by distinct interneurons, a potential mechanism to gate information flow through CA3 sublayers. Together, our data present a major revision to the classical 'trisynaptic' view of the hippocampus, bringing us closer to understanding its complex action in information storage.

Binocular Listing's Law For Human Eyes' Misaligned Optical Components
Human eyes' optical components are misaligned. This study presents the geometric construction of ocular torsion in the binocular system, in which the eye model incorporates the fovea that is not located on and the lens that is tilted away from the eye's optical axis. The ocular torsion computation involves Euler's rotation theorem in the framework of Rodrigue's vector. When the eyes' binocular posture changes, each eye's torsional orientation transformations are visualized in GeoGebra's dynamic geometry environment. Listing's law, which originally restricts single-eye torsional positions and has imprecise binocular extensions, is formulated ab initio for binocular fixations using Euler's rotation theorem. It, however, replaces the Listing plane defined for the eyes looking straight ahead with the eyes' resting posture fixation related to the abathic distance fixation of the empirical horopter uniquely defined by its straight-line frontal orientation. Thus, Listing's law use in clinical diagnosis and management of strabismus should be updated.

Mapping the impact of age and APOE risk factors for late onset Alzheimer disease on long range brain connections through multiscale bundle analysis
Alzheimer disease currently has no cure and is usually detected too late for interventions to be effective. In this study we have focused on cognitively normal subjects to study the impact of risk factors on their long-range brain connections. To detect vulnerable connections, we devised a multiscale, hierarchical method for spatial clustering of the whole brain tractogram and examined the impact of age and APOE allelic variation on cognitive abilities and bundle properties including texture e.g., mean fractional anisotropy, variability, and geometric properties including streamline length, volume, and shape, as well as asymmetry. We found that the third level subdivision in the bundle hierarchy provided the most sensitive ability to detect age and genotype differences associated with risk factors. Our results indicate that frontal bundles were a major age predictor, while the occipital cortex and cerebellar connections were important risk predictors that were heavily genotype dependent, and showed accelerated decline in fractional anisotropy, shape similarity, and increased asymmetry. Cognitive metrics related to olfactory memory were mapped to bundles, providing possible early markers of neurodegeneration. In addition, physiological metrics such as diastolic blood pressure were associated with changes in white matter tracts. Our novel method for a data driven analysis of sensitive changes in tractography may differentiate populations at risk for AD and isolate specific vulnerable networks.

Translational control in the spinal cord regulates gene expression and pain hypersensitivity in the chronic phase of neuropathic pain
Sensitization of spinal nociceptive circuits plays a crucial role in neuropathic pain. This sensitization depends on new gene expression that is primarily regulated via transcriptional and translational control mechanisms. The relative roles of these mechanisms in regulating gene expression in the clinically relevant chronic phase of neuropathic pain are not well understood. Here, we show that changes in gene expression in the spinal cord during the chronic phase of neuropathic pain are substantially regulated at the translational level. Downregulating spinal translation at the chronic phase alleviated pain hypersensitivity. Cell-type-specific profiling revealed that spinal inhibitory neurons exhibited greater changes in translation after peripheral nerve injury compared to excitatory neurons. Notably, increasing translation selectively in all inhibitory neurons or parvalbumin-positive (PV+) interneurons, but not excitatory neurons, promoted mechanical pain hypersensitivity. Furthermore, increasing translation in PV+ neurons decreased their intrinsic excitability and spiking activity, whereas reducing translation in spinal PV+ neurons prevented the nerve injury-induced decrease in excitability. Thus, translational control mechanisms in the spinal cord, particularly in inhibitory neurons, play a role in mediating neuropathic pain hypersensitivity.

Exercise-induced pain modulation is sex, opioid, and fitness-dependent and mediated by the medial frontal cortex
Exercise leads to a release of endogenous opioids, potentially resulting in pain relief. However, the neurobiological underpinnings of this effect remain unclear, and studies in rodents and humans have mainly investigated this in male subjects. Using a pharmacological within-subject fMRI study with the opioid antagonist naloxone and different levels of exercise and pain we investigated exercise-induced hypoalgesia in a balanced sample (N = 39, 21 female). Overall, we were unable to detect exercise-induced pain modulation after exercise in heat pain. However, our data reveal a crucial interplay of drug, fitness level, and sex where males showed greater hypoalgesia through exercise with increasing fitness levels. This effect was attenuated by naloxone and mirrored by fMRI signal changes in the medial frontal cortex, where activation also varied with fitness level and sex, and was reversed by naloxone. These results indicate that exercise exerts a sex and fitness-dependent hypoalgesic effect mediated by endogenous opioids and the medial frontal cortex.

Layer Va neurons, as major presynaptic partners of corticospinal neurons, play critical roles in skilled movements
Corticospinal neurons (CSNs) are located in the cortex and projecting into the spinal cord. The activation of CSNs, which is associated with skilled motor behaviors, induces the activation of interneurons in the spinal cord. Eventually, motor neuron activation is induced by corticospinal circuits to coordinate muscle activation. Therefore, elucidating how the activation of CSNs in the brain is regulated is necessary for understanding the roles of CSNs in skilled motor behaviors. However, the presynaptic partners of CSNs in the brain remain to be identified. Here, we performed transsynaptic rabies virus-mediated brain-wide mapping to identify presynaptic partners of CSNs (pre-CSNs). We found that pre-CSNs are located in all cortical layers, but major pre-CSNs are located in layer Va. A small population of pre-CSNs are also located outside the cortex, such as in the thalamus. Inactivation of layer Va neurons in Tlx3-Cre mice results in deficits in skilled reaching and grasping behaviors, suggesting that, similar to CSNs, layer Va neurons are critical for skilled movements. Finally, we examined whether the connectivity of CSNs is altered after spinal cord injury (SCI). We found that unlike connections between CNSs and postsynaptic neurons, connections between pre-CSNs and CSNs do not change after SCI.

Control of innate olfactory valence by segregated cortical amygdala circuits
Animals perform innate behaviors that are stereotyped responses to specific evolutionarily relevant stimuli in the absence of prior learning or experience. These behaviors can be reduced to an axis of valence, whereby specific odors evoke approach or avoidance. The cortical amygdala (plCoA) mediates innate attraction and aversion to odor. However, little is known about how this brain area gives rise to behaviors of opposing motivational valence. Here, we sought to define the circuit features of plCoA that give rise to innate olfactory behaviors of valence. We characterized the physiology, gene expression, and projections of this structure, identifying a divergent, topographic organization that selectively controls innate attraction and avoidance to odor. First, we examined odor-evoked responses in these areas and found sparse encoding of odor identity, but not valence. We next considered a topographic organization and found that optogenetic stimulation of the anterior and posterior domains of plCoA elicits attraction and avoidance, respectively, suggesting a functional axis for valence. Using single cell and spatial RNA sequencing, we identified the molecular cell types in plCoA, revealing an anteroposterior gradient in cell types, whereby anterior glutamatergic neurons preferentially express Slc17a6 and posterior neurons express Slc17a7. Activation of these respective cell types recapitulates appetitive and aversive valence behaviors, and chemogenetic inhibition reveals partial necessity for valence responses to innate appetitive or aversive odors. Finally, we identified topographically organized circuits defined by projections, whereby anterior neurons preferentially project to medial amygdala, and posterior neurons preferentially project to nucleus accumbens, which are respectively sufficient and necessary for innate negative and positive olfactory valence. Together, these data advance our understanding of how the olfactory system generates stereotypic, hardwired attraction and avoidance, and supports a model whereby distinct, topographically distributed plCoA populations direct innate olfactory valence responses by signaling to divergent valence-specific targets, linking upstream olfactory identity to downstream valence behaviors, through a population code. This represents a novel circuit motif in which valence encoding is represented not by the firing properties of individual neurons, but by population level identity encoding that is routed through divergent targets to mediate distinct valence.

Integrative Transcriptomics Reveals Layer 1 Astrocytes Altered in Schizophrenia
Schizophrenia is one of the most prevalent psychiatric disorders with unclear pathophysiology despite a century-long history of intense research. Schizophrenia affects multiple networks across different brain regions. The anterior cingulate cortex (ACC) is the region that connects the limbic system to cognitive areas such as the prefrontal cortex and represents a pivotal region for the etiology of schizophrenia; however, the molecular pathology, considering its cellular and anatomical complexity, is not well understood. Here, we performed an integrative analysis of spatial and single-nucleus transcriptomics of the postmortem ACC of people with schizophrenia, together with a thorough histological analysis. The data revealed major transcriptomics signatures altered in schizophrenia, pointing at the dysregulation of glial cells, primarily in astrocytes. We further discovered a decrease in the cellular density and abundance of processes of interlaminar astrocytes, a subpopulation of astrocytes specific to primates that localize in the layer 1 and influence the superficial cortical microenvironment across layer 1 and layers 2/3 of the cortex. Our study suggests that aberrant changes in interlaminar astrocytes could explain the cell-to-cell circuit alterations found in schizophrenia and represent novel therapeutic targets to ameliorate schizophrenia-associated dysfunction.

Mapping individual differences in intermodal coupling in neurodevelopment
Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling. We propose a new method, called CIDeR, which is designed to simultaneously perform hypothesis testing in a way that limits false positive results and improve detection of true positive results. Through a comparison across different approaches to testing individual differences in intermodal coupling, we delineate subtle differences in the hypotheses they test, which may ultimately lead researchers to arrive at different results. Finally, we illustrate the utility of CIDeR in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.

Proteomic analysis of isolated nerve terminals from NaV1.9 knockout mice reveals pathways relevant for neuropathic pain signalling
Neuropathic pain substantially affects the mental and physical well-being of patients and magnifies the socio-economic burden on the healthcare system. It is important to understand the molecular mechanisms underlying chronic pain to effectively target it. To investigate peripheral mechanisms relevant to pain signaling, we isolated nerve terminals from mouse footpads. The isolated peripheral terminals contain both pre- and post-synaptic proteins and are deficient in keratin and histone in both mice and humans. We detected the protein translational machinery and mitochondria in nerve terminals and observed that they were capable of endocytosis. An unbiased proteomic analysis of nerve terminals from footpads of NaV1.9 knockout mice shows dysregulation of the p38 mitogen-activated protein kinase (MAPK) and extracellular regulated kinase 1/2 (ERK1/2) pathways, and of protein components involved in translation and energy metabolism. Isolation of human nerve terminals from skin punch biopsies, validated by proteomic analysis, highlights the broad and translational value of our approach. Our study thus reveals peripheral signaling mechanisms implicated in pain perception.

Gestational CBD shapes insular cortex in adulthood
Many expectant mothers use CBD to alleviate symptoms like nausea, insomnia, anxiety, and pain, despite limited research on its long-term effects. However, CBD passes through the placenta, affecting fetal development and impacting offspring behavior. We investigated how prenatal CBD exposure affects the insular cortex (IC), a brain region involved in emotional processing and linked to psychiatric disorders. The IC is divided into two territories: the anterior IC (aIC), processing socioemotional signals, and the posterior IC (pIC), specializing in interoception and pain perception. Pyramidal neurons in the aIC and pIC exhibit sex-specific electrophysiological properties, including variations in excitability and the excitatory/inhibitory balance. We investigated IC cellular properties and synaptic strength in the offspring of both sexes from mice exposed to low-dose CBD during gestation (E5-E18; 3mg/kg, s.c.). Prenatal CBD exposure induced sex-specific and territory-specific changes in the active and passive membrane properties, as well as intrinsic excitability and the excitatory/inhibitory balance, in the IC of adult offspring. The data indicate that in-utero CBD exposure disrupts IC neuronal development, leading to a loss of functional distinction between IC territories. These findings may have significant implications for understanding the effects of CBD on emotional behaviors in offspring.

Effects of transcranial photobiomodulation on peripheral biomarkers associated with oxidative stress and complex IV activity in the prefrontal cortex in rats subjected to chronic mild stress
Background: This study addresses the urgent need for effective alternatives to treat major depressive disorder (MDD) in patients who do not respond to conventional therapies Transcranial photobiomodulation therapy (tPBM) shows promise by enhancing mitochondrial function and reducing oxidative stress, as demonstrated in the chronic mild stress (CMS) rat model. To analyze the impact of tPBM with two wavelengths (red and infrared) on behavioral and biological parameters related to MDD in a CMS model. Methods: Male Wistar rats were subjected to CMS for five weeks and categorized into resilient (CMS-R) and susceptible (CMS-S) groups using the sucrose consumption test (SCT). The CMS-S group received tPBM treatment (600nm and 840nm) for five weeks. Biological measures included lipid damage (TBARS), antioxidant defense (TEAC), mitochondrial complex IV activity (CCO), and nitric oxide (NO) concentration in the prefrontal cortex and blood were measured. Results: As expected, post-tPBM treatment (both red and infrared groups) exhibited increased sucrose consumption compared to the sham (Kruskal Wallis chi-squared=26.131; p<0.001). The red and infrared presented higher serum TEAC levels than the sham and control groups, but these effects did not reach statistical significance (p=0.306). In contrast, the red group showed lower peripheral TBARS levels (M = 9.50, SD = 2.87) than the sham group (M = 13.66, SD = 2.20) (p=0.0048); such effect was similar to the control non-stress group. The infrared group showed higher NO levels within the hippocampus than the sham group (Mean = 107.83; SD = 6.48, Dunn Test p = 0.0134) and higher prefrontal CCO activity levels than the red group (p=0.012), which was similar to the control non-stress group. Conclusions: Our study demonstrated that tPBM using both red and infrared wavelengths significantly improved behavioral and biological parameters in the chronic mild stress (CMS) rat model. In particular, tPBM may offer therapeutic benefits by ameliorating oxidative stress and enhancing mitochondrial function, thereby presenting a promising alternative for the management of MDD.

Mapping the spectrotemporal regions influencing perception of French stop consonants in noise
Understanding how speech sounds are decoded into linguistic units has been a central research challenge over the last century. This study follows a reverse-correlation approach to reveal the acoustic cues listeners use to categorize French stop consonants in noise. Compared to previous methods, this approach ensures an unprecedented level of detail with only minimal theoretical assumptions. Thirty-two participants performed a speech-in-noise discrimination task based on natural /aCa/ utterances, with C = /b/, /d/, /g/, /p/, /t/, or /k/. The trial-by-trial analysis of their confusions enabled us to map the spectrotemporal information they relied on for their decisions. In place-of-articulation contrasts, the results confirmed the critical role of formant consonant-vowel transitions, used by all participants, and, to a lesser extent, vowel-consonant transitions and high-frequency release bursts. Similarly, for voicing contrasts, we validated the prominent role of the voicing bar cue, with some participants also using formant transitions and burst cues. This approach revealed that most listeners use a combination of several cues for each task, with significant variability within the participant group. These insights shed new light on decades-old debates regarding the relative importance of cues for phoneme perception and suggest that research on acoustic cues should not overlook individual variability in speech perception.

Corticostriatal ensemble dynamics across heroin self-administration to reinstatement
Corticostriatal projection neurons from prelimbic medial prefrontal cortex to the nucleus accumbens core critically regulate drug-seeking behaviors, yet the underlying encoding dynamics whereby these neurons contribute to drug seeking remain elusive. Here we use two-photon calcium imaging to visualize the activity of corticostriatal neurons in mice from the onset of heroin use to relapse. We find that the activity of these neurons is highly heterogeneous during heroin self-administration and seeking, with at least 8 distinct neuronal ensembles that display both excitatory and inhibitory encoding dynamics. These neuronal ensembles are particularly apparent during relapse, when excitatory responses are amplified compared to heroin self-administration. Moreover, we find that optogenetic inhibition of corticostriatal projection neurons attenuates heroin seeking regardless of the relapse trigger. Our results reveal the precise corticostriatal activity dynamics underlying drug-seeking behaviors and support a key role for this circuit in mediating relapse to drug seeking.