bioRxiv Subject Collection: Neuroscience's Journal

Connectome-based brain fingerprints predict early cognitive decline in Parkinson's patients with minor hallucinations
Individual variability in connectome organization offers a unique framework for capturing patient-specific alterations and advancing personalized models in medicine. Minor hallucinations (MH) affect up to 40% of Parkinson's disease (PD) patients and are early indicators of cognitive decline and dementia, hence crucial for early intervention. While previous studies focused on group-level differences, connectome-based brain fingerprinting enables deeper, individualized analysis of neural change. Applying this approach to PD patients with and without MH using resting-state fMRI, we show that each patient exhibited unique brain fingerprint, revealing rich quantifiable personalized features with medical relevance. MH-patients showed a loss of subject-specific features in brain networks linked to cognitive health, while somatosensory regions - typically less distinctive - became more prominent, emphasizing their role in MH pathogenesis. These differences enabled to identify - in an entirely data driven manner - patient-specific networks linked to early subclinical cognitive alterations, as well differential spatial fingerprinting organization linked to cortical densities of neurotransmitters. These findings reveal a distinct, patient-specific connectomic signature that differentiates PD patients with MH, uncovering early neural markers for precision medicine in PD.

Charting the transition from in vitro gliogenesis to the in vivo maturation of transplanted human glial progenitor cells
Neither rodent models nor in vitro studies of human cells adequately describe the molecular ontogeny of human glial progenitor cells (hGPCs). Here, we used scRNA-seq together with scATAC-Seq and CUT&TAG assessment of chromatin availability to track the in vitro genesis and in vivo differentiation of hGPCs from pluripotent stem cells (PSCs). In vitro, the hGPC pool comprised 4 transcriptionally-distinct subpopulations, each associated with a distinct pattern of chromatin accessibility and histone modification of stage-dependent genes. After the neonatal transplant of these cells into myelin-deficient shiverer mice, they differentiated further as astrocytes and oligodendrocytes. A combination of gene co-expression, motif enrichment, cell-trajectory, and cell-cell interaction analyses revealed that the host environment potentiated the context-dependent differentiation of the hGPCs, via their activation of distinct gene regulatory networks. Together, these data chart the process by which human PSC-derived GPCs are generated in vitro and diversify in vivo to mature as astrocytes and oligodendrocytes.

Region-specific mechanosensation in Drosophila postural control behaviour
The relation between regional morphological features derived from the bilaterian body plan and the fundamental behaviours necessary to extract utility from such structures is not well understood. Here we use the Drosophila larva to investigate this problem focusing on the mapping of the regional stimuli that trigger an adaptive and evolutionarily conserved behaviour termed self-righting: a postural control system that allows the animal to restore its natural position if turned upside-down. Through the development of new methodologies that allow regionally-restricted mechanical stimulation and region-specific neuronal optogenetics, we find that multidendritic sensory neuron inhibition in anterior areas (thoracic/anterior abdominal) has a profound effect on self-righting performance, whilst inhibition of posterior sensory elements (mid and posterior abdomen) produces no effects. Using a deep neural network automated tracking method to examine how neuronal inhibition impacted different subcomponents of the self-righting sequence we learned that inhibition of anterior sensory neurons increases head casting behaviour, and that this is strongly correlated with abnormally long self-righting times. To explore the mechanistic bases of our behavioural observations, we considered the hypothesis that the Hox genes, well known for their roles in axial developmental patterning, might play a role in the functional specification of multidendritic sensory neurons along the body axis. Molecular expression analysis of FACS-sorted neural populations, fluorescent immunolabelling and neuron-specific knock-down experiments demonstrated that normal sensory neuron expression of the Hox genes Antennapedia and abdominal-b is necessary for self-righting in the Drosophila larva. Altogether, our work shows that region-specific mechanosensory processes mediated by multidendritic sensory neurons and instructed via Hox gene inputs are essential for self-righting, providing a link between regional structural features and an adaptive and widely evolutionarily conserved postural control behaviour.

On-Body Measure of Reaction Time Correlates With Intoxication Level
Excessive alcohol use has profound effects on individual health and healthcare systems worldwide. Despite this, there is currently no system or device that can detect robustly the physiologic and functional effects of alcohol-based impairment in real-world conditions. A practical, on-body, device capable of rapidly and accurately determining the functional capacity of an individual to drive, before they can start the ignition of the automobile, is required. The goal of this pilot study was to evaluate the effect of acute alcohol intoxication on premotor time (PMT) and reaction time (RT), both highly sensitive of individual cognition, as evaluated by the Pison Technology wrist-worn wearable. Nineteen participants were included in the study, 14 subjects who consumed alcohol sufficient to raise blood alcohol concentration (BAC) to 0.12% within a 30-minute period and 5 controls who did not consume alcohol. Changes in reaction time data were correlated with blood alcohol levels as measured by breathalyzer testing, identifying a statistically significant difference between those participants under the legal limit and those over the legal limit. Both group and individual analyses confirmed that as the BAC increased in subjects, the PMT also increased. The PMT also decreased as the BAC returned to levels under the legal intoxication threshold (0.08%). A significant effect of BAC levels on changes in PMT at the p < 0.05 level for two conditions. This study demonstrated the first use case of an on-body, neuro-physiological sensor capable of detecting sensitive changes of reaction time, in real time, that serves as an easy-to-measure proxy for blood alcohol content and impairment.

How Acting Jointly Differs from Acting Side-by-Side: A Dual EEG Study
The distinction between acting jointly and acting side by side permeates our daily lives and is crucial for understanding the evolution and development of human sociality. While acting in parallel involves agents pursuing individual goals, acting jointly requires them to share a collective goal. Here, we used a dual electroencephalography (EEG) approach to explore the neural dynamics underlying joint and parallel action preparation. We recorded event-related potentials (ERPs) from 20 dyads while they had to transport an object in a video game, either jointly or in parallel, or individually. Both conditions were carefully matched for coordination demands and performance complexity, as confirmed by equal success rates. Our results revealed a distinctive pattern swap in ERPs during action preparation. In the early preparation phase, ERPs showed significantly higher amplitude during joint action than parallel action. This pattern reversed in the late preparation phase, with significantly reduced ERP amplitude in the joint compared to parallel action. Notably, the decrease in late ERPs correlated with higher reaction time (RT) variability in partners but not with participants' own RT variability. The dynamic swap in neural activity suggests that different cognitive processes operate at distinct stages of action preparation. While initially sharing a collective goal may impose cognitive costs (reflected in higher early ERPs), this is offset by facilitated late action preparation, likely due to enhanced predictability of partners' actions

Semaglutide, Tirzepatide, and Retatrutide Attenuate the Interoceptive Effects of Alcohol in Male and Female Rats
Rationale: Alcohol use disorder (AUD) remains a major public health challenge, yet effective pharmacotherapies are limited. As such, there is growing interest in repurposing medications with novel mechanisms of action. Glucagon-like peptide-1 (GLP-1) receptor agonists, originally developed for type 2 diabetes, have emerged as promising candidates due to effects on intake regulation and reward processing. GLP-1 receptor agonists, including semaglutide, reduce alcohol intake and relapse-like behaviors in rodent and non-human primate models, and a recent clinical trial found that semaglutide decreased alcohol craving and drinking in adults with AUD. Modulation of the subjective/interoceptive effects of alcohol may contribute to the therapeutic potential of GLP-1 receptor agonists. Objectives: This study used operant drug discrimination in male and female rats to assess how acute and repeated semaglutide treatment affects the discriminative stimulus (interoceptive) effects of alcohol. We hypothesized that GLP-1 receptor activation would disrupt these interoceptive effects. We also evaluated acute treatment with tirzepatide, a dual GLP-1/gastric inhibitory peptide (GIP) receptor agonist, and retatrutide, a triple GIP/GLP-1/glucagon receptor agonist, to determine whether broader receptor activity would differentially influence the subjective effects of alcohol. Results: Acute administration of semaglutide, tirzepatide, and retatrutide each attenuated alcohol discrimination, suggesting modulation of subjective alcohol effects. Repeated semaglutide maintained efficacy across the 15-day treatment period; alcohol discrimination returned to control levels three days after treatment cessation. Conclusions: Building on prior work with GLP-1 receptor agonists, these results provide important context for interpreting clinical observations of reduced drinking behavior among individuals receiving this class of therapeutics.

YOTO (You Only Think Once): A Human EEG Dataset for Multisensory Perception and Mental Imagery
The YOTO (You Only Think Once) dataset presents a human electroencephalography (EEG) resource for exploring multisensory perception and mental imagery. The study enrolled 26 participants who performed tasks involving both unimodal and multimodal stimuli. Researchers collected high-resolution EEG signals at a 1000 Hz sampling rate to capture fine-grained neural activity related to internal mental representations. The dataset includes resting-state and task-based recordings, which permits direct comparisons between spontaneous brain activity and controlled mental imagery. The protocol incorporated visual, auditory, and combined cues to investigate the integration of multiple sensory channels, and participants provided self-reported vividness ratings that indicate subjective perceptual strength. The YOTO dataset addresses challenges in mental imagery research by offering a systematic and standardized platform with rigorous artifact rejection methods. Technical validation involved event-related potentials (ERPs) and power spectral density (PSD) analyses, which demonstrated the reliability of the data and confirmed distinct neural responses across stimuli. This dataset aims to foster studies on neural decoding, perception, and cognitive modeling, and it is publicly accessible for researchers who seek to advance multimodal mental imagery research and related applications.

Wearable, High-Density, Time-Domain Diffuse Optical Tomography Array for Functional Neuroimaging
Noninvasive functional neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), are essential tools for understanding brain activity and cognition for various neurological and mental health conditions. While fMRI offers high spatial resolution, its limited temporal resolution and costly large-form-factor restricts its accessibility and practicality for many applications. In contrast, EEG is more affordable and portable but has limited spatial resolution. In the present study, we overcome the limitations of existing neuroimaging technologies with the development of Micro-DOT, a functional near-infrared spectroscopy (fNIRS) system capable of high-density, time-domain diffuse optical tomography (HD-TD-DOT). Micro-DOT tackles the tradeoff between form factor and spatial resolution that has been a longstanding issue with existing fNIRS systems through the use of a unique hardware architecture that arrays HD-TD-DOT-capable electronics directly at the tissue surface. This is made possible with complementary-metal-oxide-semiconductor (CMOS) source-detector chiplets that contain all the electronics and optics necessary for HD-TD-DOT operation, and can be mounted on flexible polyimide packaging with a very minimal footprint. Pairing these hardware innovations with an advanced volumetric reconstruction software, Micro-DOT achieves in-plane spatial resolution, depth resolution, and localization accuracy comparable to fMRI, while maintaining the wearable form factor and portability of EEG, making it a viable stand-alone system for measuring subject-specific brain activation.

Face-, color-, and word-specific patches in the human orbitofrontal cortex
The human ventral occipitotemporal cortex (VOTC) contains multiple category-specific areas, organized along posterior-to-anterior and medial-to-lateral axes. However, the role of regions beyond the VOTC in category-specific processing remains less explored. Here, we report the presence of face-, color- and word-specific patches in the human orbitofrontal cortex (OFC) and systematically describe their location, activity amplitude, category selectivity, representational content, and functional connectivity. We compare these features with those of corresponding VOTC category-specific patches. Our findings reveal that face- and color-specific patches in the OFC follow a similar medial-lateral organization to those in the VOTC and form continuous functional gradients with VOTC patches. These results suggest that the OFC contains a topographic organization similar to, but at a higher hierarchical level than, the VOTC object categorization system.

Transcriptomes of higher order thalamic nuclei in obsessive compulsive disorder
Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness associated with altered function in cortico-striatal-thalamo-cortical (CSTC) circuits. In this pilot study, we examined differential RNA expression in the thalamus using postmortem human brain tissue samples from 11 subjects with OCD and 10 unaffected subjects. We individually dissected the mediodorsal magnocellular, mediodorsal parvocellular, and ventral anterior nuclei, which participate in orbitofrontal and anterior cingulate CSTC circuits most frequently associated with OCD, and the posterior ventrolateral nucleus, which participates in premotor and motor circuits that are increasingly implicated in OCD. Preselected GABAergic, glutamatergic and ion channel genes were analyzed via qPCR. Two genes required for GABA synthesis and release, GAD1 and SLC32A1, were found to be downregulated in OCD subjects across all nuclei, and potassium channel KCNN3 was upregulated. In parallel, we performed an exploratory total RNAseq differential expression analysis. We identified few (12 - 52) differentially expressed genes (DEGs) in each nucleus, and only one DEG in a pooled analysis of all nuclei. No DEGs were significant after correction for multiple comparisons. Investigation by model selection indicated that OCD diagnosis was not a useful factor in modelling gene expression in our dataset. OCD was also not associated with any modules of co-expressed genes identified using weighted gene correlation network analysis. Overall, we found minimal evidence of differential RNA expression in these thalamic nuclei in OCD. These findings contrast with our previous work including many of the same subjects where we found widespread differential mRNA expression in the orbitofrontal cortex and striatum in OCD.

Synaptic Encoding of Time in Working Memory
The processing of temporally-extended sequences of stimuli critically relies on Working Memory (WM). Yet, how WM supports the encoding and retrieval of novel sequences is unknown. Existing theories rely on associative learning driven by repetitions and are, thus, unable to explain how people can reproduce novel sequences of stimuli immediately. Here, we propose that detailed temporal information about a novel sequence can be rapidly stored in WM by short-term synaptic plasticity over multiple time scales. To substantiate this proposal, we extend our previously-proposed synaptic theory of WM to include synaptic augmentation, besides more short-lived depression and facilitation, consistently with experimental observations. The long time scales associated with augmentation naturally lead to the emergence of a temporal gradient in the synaptic efficacies, which can be used to immediately replay, at normal speed or in a time-compressed way, novel sequences. The theory is consistent with behavioral and neurophysiological observations.

Auditory Brainstem Development in Autism: From Childhood Hypo-Responsivity to Adult Hyper-Reactivity
Background: Autism spectrum disorder (ASD) is characterized by sensory disruptions, including auditory processing differences, which can significantly impact social, emotional, and cognitive development. This study investigates auditory brainstem development in Autistic children and adults using auditory brainstem responses (ABRs) and acoustic startle responses (ASRs), two key measures of auditory processing. We hypothesize that early hypo-responsivity in children, measured with ABRs, may lead to compensatory neural adaptations, resulting in hyper-reactivity in adulthood, measured by ASRs. Methods: The study included 40 Autistic children, 57 non-Autistic children, 20 Autistic adults, and 21 non-Autistic adults. Participants underwent peripheral hearing screening, ABR testing at slow and fast click-rates, and ASR measurements. ABR wave and ASR latencies and amplitudes were analyzed. Statistical analyses included mixed-model ANOVAs and Spearmans correlations to examine group differences and associations with age. Results: Autistic children exhibited increased ABR wave latencies and reduced amplitudes, indicating slower neurotransmission and reduced neural responsivity in the ascending auditory pathway. In contrast, Autistic adults showed normalized ABR latencies but increased ASR magnitude, suggesting hyper-reactivity to auditory stimuli. Age-related correlations revealed that ABR latencies increased with age in non-Autistic participants, while ASR magnitude was negatively correlated with age in non-Autistic participants. The associations were significantly different between groups. Conclusion: The findings support the hypothesis that Autistic children experience auditory brainstem hypo-responsivity, which may normalize in adulthood but lead to maladaptive hyper-reactivity. These results highlight the role of early auditory disruptions in shaping long-term sensory processing and reactivity in Autism, emphasizing the need for further research into the neural mechanisms underlying these differences.

Altered auditory maturation in Fragile X syndrome and its involvement in audiogenic seizure susceptibility
BackgroundAuditory hypersensitivity is a prominent symptom in Fragile X syndrome (FXS), the most prevalent monogenic cause of autism and intellectual disability. FXS arises through the loss of the protein encoded by the FMR1 (Fragile X Messenger Ribonucleoprotein 1) gene, FMRP, required for normal neural circuit excitability. In the brainstem, FMRP is necessary for normal development of acoustic reactivity, and its loss has been implicated in audiogenic seizures (AGS) in Fmr1 knockout (KO) mice, modelling auditory hypersensitivity and seizures in FXS patients.

PurposeThe present study investigated the correlation between auditory brainstem function and behavioral expression of AGS at the early (postnatal day P20, infancy) and late (P32, juvenile) stage of auditory development in Fmr1 KO mice compared with wildtype (WT) mice, and in both females and males.

MethodsWe tested responsiveness to pure tones of select auditory pathway elements through auditory brainstem responses; and neural synchronization to amplitude envelopes of modulated acoustic stimuli through auditory steady-state responses. AGS behavior was categorized for severity during 5-minute exposure to loud sound. Expression of the immediate early gene cFos was quantified as a marker for neuronal activity in the inferior colliculus.

ResultsDuring infancy, more severe AGS expression in Fmr1 KO mice compared with WT mice was accompanied by increased responsiveness to acoustic stimuli at the level of the superior olivary complex and inferior colliculus, and stronger neural synchronicity in subcortical auditory neurons. Fmr1 KO mice also had higher cFos positive cell counts in the inferior colliculus after exposure to loud sound. With age, both AGS susceptibility and exaggerated acoustic stimulus-evoked activity in the Fmr1 KO mice subsided. Intriguingly, Fmr1 KO mice displayed altered developmental profile in both the threshold and amplitude of auditory brainstem response.

ConclusionOur findings support evidence that AGS activity relies upon hyperexcitability in the auditory system, including in the lower brainstem, possibly due to disturbed auditory maturation. Hyper-synchronization to modulated sounds in subcortical auditory neurons seemed to predict AGS severity. A better understanding of FXS-related circuit and behavioral symptoms of auditory processing across development provides the potential to identify therapeutic strategies to achieve auditory function recovery in FXS.

A surprising link between cognitive maps, successor-relation based reinforcement learning, and BTSP
Recent recordings from the hippocampus of the human brain suggest that after a few presentations of sequences of unrelated natural images, correlations between emergent neural codes encode the sequential structure of these sequences. We show that this learning process, which is consistent with experimental data on BTSP (Behavioral Time Scale Synaptic Plasticity), creates a cognitive map that enables online-generation of plans for moving to any given goal, both in spatial environments and in abstract graphs. Furthermore, the resulting neural circuits and plasticity rules provide a biologically plausible implementation of Successor Relation based Reinforcement Learning. In addition, this brain-derived approach for learning cognitive maps provides a blueprint for implementing autonomous learning through on-chip plasticity in energy-efficient neuromorphic hardware.

A Dynamic Threshold-Based Method for Robust and Accurate Blink Detection in Eye-Tracking Data
Blink detection is a critical component of eye-tracking research, particularly in pupillometry, where data loss due to blinks can obscure meaningful insights. Existing methods often rely on fixed thresholds or device-specific noise profiles, which may lead to inaccuracies in detecting blink onsets and offsets, especially in heterogeneous datasets. This study introduces a novel blink detection model that dynamically adapts to varying pupil size distributions, ensuring robustness across different experimental conditions. The proposed method integrates dynamic thresholding, which adjusts based on the mean pupil size of valid samples, Gaussian smoothing, which reduces noise while preserving signal integrity, and adaptive boundary refinement, which refines blink onsets and offsets based on a trends in the smoothed data. Unlike traditional approaches that merge closely spaced blinks, this model treats each blink as an independent event, preserving temporal resolution, which is essential for cognitive and perceptual studies. The model is computationally efficient and adaptable to a wide range of sampling rates, from low-frequency (e.g., 250 Hz) to high-frequency (e.g., 2000 Hz) data, ensuring consistent blink detection across different eye-tracking setups, making it suitable for both real-time and offline eye-tracking applications. Experimental evaluations demonstrate its ability to accurately detect blinks across diverse datasets. By offering a more reliable and generalizable solution, this model advances blink detection methodologies and enhances the quality of eye-tracking data analysis across research domains.

Decisional reference point pathology: a mechanism and marker for major depressive disorder in humans
The decisional reference point, the central mechanism of behavioral economics, conditions our evaluations of reinforcers. It determines whether a given event is experienced as positive or negative. Here we show, for the first time, a significant and pathological elevation of the reference point in patients with depression that correlates with disease severity. We also show that the mechanism for reference point setting is profoundly impaired in patients with depression. These findings link the previously demonstrated treatment of depression by deep brain stimulation to modulation of the reference point in the anterior cingulate cortex and identify pathology in the dynamics of reference point setting as a novel mechanism in the disorder. Finally, these results lay the foundation for a three-minute virtual diagnostic test for depression.

Exploration of Novel Biomarkers through a Precision Medicine Approach Using Multi-omics and Brain Organoids in Patients with Atypical Depression and Psychotic Symptoms
Major depressive disorder (MDD) with atypical features accompanied by psychotic symptoms represents a severe and under-researched subtype of depression and severe mental illness, characterized by significant personal and social impact. This study aims to explore novel biomarkers through a precision medicine approach by integrating clinical data, white blood cell (WBC) single-cell RNA sequencing (scRNA-seq), plasma proteomics, and brain organoid models to uncover immunological and neurological alterations in patients with this condition. Patients exhibited elevated stress, anxiety, and depression levels, with increased WBC counts. Plasma proteomic profiling identified an upregulation of proteins implicated in synaptic formation, including Doublecortin-Like Kinase 3 (DCLK3) and Calcyon (CALY), as well as immune-related proteins such as Complement Component 5 (C5). WBC scRNA-seq revealed significant neutrophil and monocyte transcriptomic alterations, suggesting increased inflammation and immune dysregulation. Patient-derived brain organoids display reduced growth and distinct gene expression patterns compared to controls, particularly under dexamethasone-induced stress conditions. Integrating multi-omics data and brain organoid models offers a novel framework for understanding the pathophysiology of psychiatric disorder, which is one of the most complex disorders.

The Effects of Antidepressants on the Hippocampus: A Meta-Analysis of Public Transcriptional Profiling Data
Background: Major depressive disorder (MDD) is characterised by persistent depressed mood and loss of interest and pleasure in life, known as anhedonia. The first line of treatment for MDD is antidepressant medication that enhances signaling by monoamine neurotransmitters, such as serotonin and dopamine. Other treatments include non-pharmaceutical treatments, such as electroconvulsive therapy and transmagnetic stimulation, and non-traditional pharmaceutical antidepressants that function via alternative, often unknown, mechanisms. Methods: To identify mechanisms of action shared across antidepressant categories, we examined changes in gene expression following treatment with both traditional and non-traditional antidepressants, using a meta-analysis of public transcriptional profiling data from laboratory rodents (rats, mice). We focused on the hippocampus, which is a brain region that is well-documented via neuro-imaging to show morphological changes in depression that reverse with antidepressant usage. We specifically focused on treatment during adulthood, and included both clinically-used antidepressants (both pharmaceutical and non-pharmaceutical) and treatments demonstrated to effectively treat depressive mood symptoms. The outcome variable was gene expression in bulk dissected hippocampus as measured by microarray or RNA-Seq. To conduct our project, we systematically reviewed available datasets in the Gemma database of curated, reprocessed transcriptional profiling data using pre-defined search terms and inclusion/exclusion criteria. We identified 15 relevant studies containing a total of 22 antidepressant vs. control group comparisons (collective n=352). For each gene, a random effects meta-analysis model was then fit to the antidepressant vs. control effect sizes (Log2 Fold Changes) extracted from each study. Results: Our meta-analysis yielded stable estimates for 16,439 genes, identifying 58 genes that were consistently differentially expressed (False Discovery Rate<0.05) across antidepressant experiments and categories. Of these genes, 23 were upregulated and 35 were downregulated. The functions associated with the differentially expressed genes were diverse, including modulation of the stress response, immune regulation, neurodevelopment and neuroplasticity. Conclusion: The genes that we identified as consistently differentially expressed across antidepressant categories may be worth investigating as potential linchpins for antidepressant efficacy or as targets for novel therapies.

DAGLα/β, 2-AG release, and Parkinson's Disease: Exploring a causal link.
The diacylglycerol lipases, DAGL and DAGL{beta}, hydrolyse diacylglycerol (DAG) to produce 2-arachidonoylglycerol (2-AG), a key endocannabinoid (eCB) and CB/CB2 receptor ligand. While DAGL is well established as a regulator of CB-dependent synaptic plasticity, recent studies have identified DAGLB mutations as a cause of autosomal recessive early-onset Parkinson's disease (PD). Here, we present a comprehensive analysis of DAGL{beta} mRNA expression, demonstrating its co-expression with DAGL mRNA predominantly in excitatory neurons throughout the adult nervous system. We see no evidence for enrichment of the DAGLs or CB transcripts in the striatum or in dopaminergic neurons. We discuss these findings within a review of recent literature that points to a wider involvement of the eCB system in PD. Notably, DAGL-dependent 2-AG release at synapses relies on -synuclein function - a protein central to PD pathophysiology-implicating both DAGLs in PD and pointing to widespread disruption in 2-AG release. Consistent with this, substantial reductions in 2-AG levels have been reported in the cerebrospinal fluid (CSF) of PD patients. Depression, a major non-motor symptom of PD, often precedes the onset of motor deficits by several years. Human and mouse genetic studies suggest that reduced DAGL activity may contribute to depression by impairing 2-AG-mediated CB receptor signalling, which is crucial for synaptic plasticity, stress resilience, and mood regulation. These findings point to a potential causal link between DAGL dysfunction and the non-motor symptoms in PD.

Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer's disease
In Alzheimer's disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale mechanistic disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional {beta}-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal functional networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.

Respiration shapes the neural dynamics of successful remembering in humans.
Respiration has been shown to impact memory retrieval, yet the neural dynamics underlying this effect remain unclear. Here, we investigated how respiration shapes both behavioral and neural expressions of memory retrieval by re-analyzing an existing dataset where scalp electroencephalography and respiration recordings were acquired while participants (N = 18) performed an episodic memory task. Our results unveil that respiration influences retrieval-related power fluctuations in the /{beta} band and concomitant memory reactivation. Specifically, we found that both key neural signatures of successful remembering were co-modulated during exhalation, with the strength of the interaction between respiration and reactivation processes being associated with memory performance. Together, these findings suggest that respiration may act as a scaffold for episodic memory retrieval in humans by coordinating the neural conditions that support effective remembering.

Adolescent Binge Ethanol Exposure Confers Lasting Alcohol Tolerance across a Cumulative Ethanol Challenge in Adulthood: Involvement of Proinflammatory HMGB1 Signaling
Background. Epidemiological studies suggest heavy adolescent binge drinking is strongly associated with later development of an alcohol use disorder (AUD). Alcohol tolerance (i.e., an acquired reduction in acute alcohol responsivity) is a universally recognized symptom of AUD, but the direct contribution of adolescent binge drinking to adult alcohol tolerance is poorly understood. Methods and Materials. To investigate the contributions of adolescent binge ethanol exposure to lasting acquisition of acute tolerance, we used our ethanol response battery (ERB) to assess intoxication rating, hypothermia, motor coordination, and balance across cumulative ethanol doses (i.e., 0.0, 0.5, 1.0, 2.0, and 3.0 g/kg) in adult female Wistar rats following adolescent intermittent ethanol (AIE), lipopolysaccharide (LPS), and glycyrrhizic acid treatment following AIE. Results. We report AIE, which models human adolescent binge drinking, confers lasting alcohol tolerance across cumulative ethanol doses and blunts ethanol-induced increases in proinflammatory HMGB1 plasma levels. Adolescent LPS (1.0 mg/kg, i.p.) treatment, which mimics AIE-induced HMGB1-mediated neuroinflammation, induces adult alcohol tolerance and blunts HMGB1 release across cumulative ethanol doses on the ERB. Assessment of proinflammatory HMGB1 involvement in AIE-induced acquisition of lasting alcohol tolerance revealed that post-AIE administration of the HMGB1 inhibitor glycyrrhizic acid reversed the AIE-induced acquisition of alcohol tolerance in adulthood. Conclusions. These data reveal that (1) adolescent binge drinking confers long-lasting low ethanol responsivity, (2) proinflammatory neuroimmune activation contributes to the development of alcohol tolerance, and (3) blockade of proinflammatory HMGB1 signaling reverses AIE-induced acquisition of alcohol tolerance in adulthood. These findings suggest a potential mechanistic target for the development of novel therapeutics for the treatment of AUD.

M-ECG: Extracting Heart Signals with a Novel Computational Analysis of Magnetoencephalography Data
Magnetoencephalography (MEG) measures the magnetic fields generated by neural activity with high temporal and spatial resolution. Because of its focus on brain activity, other biopotentials, including muscle artifacts and heart signals, are typically filtered or rejected. In this study, the feasibility of extracting cardiac signals from MEG data, which is termed magnetoencephalographic electrocardiogram (M-ECG; in contrast to the electrocardiogram or ECG) is explored. Using the publicly available Brainstorm MEG auditory dataset CTF and OMEGA resting-state sample dataset, a novel algorithm is developed that utilizes either independent component analysis (ICA) or MEG reference sensors to extract M-ECG signals and compute heart rate variability (HRV) from MEG data reliably and accurately. Signal processing methods in the time, frequency, and time-frequency domains along with statistical tests such as Spearman correlation, root mean square error, mean absolute error, Bland-Altman mean difference, and Mann-Whitney U Test are employed to assess the similarities across the signals. The results indicate a significant alignment of temporal and frequency spectral power characteristics between M-ECG HRV and ECG HRV signals, suggesting a promising degree of similarity and correspondence. The findings highlight the feasibility of extracting M-ECG and computing HRV directly from raw MEG data. These insights hold the potential to enhance multimodal neuroimaging methodologies and further elucidate the intricate interplay between brain activity and cardiovascular function. The potential of HRV as a biomarker for brain disorders could improve diagnostic accuracy, prognostic assessment, and therapeutic strategies, particularly in neurological disorders with centrally mediated autonomic dysfunction.

Saccades orchestrate intraocular glucose to shape visual responses in birds
Birds exhibit remarkable vision despite lacking the typical network of blood vessels in their eyes. The characteristic poses a long-standing question about how avian retinas fulfill high energy demands necessary for sight. Here we show that natural, rhythmic eye movements, known as oscillatory saccades, orchestrate intraocular metabolic dynamics and attention-guided visual processing in pigeons. In a series of integrated experiments, we monitored eye movements along with glucose levels in the eye and neuronal activity in key brain regions receiving direct input from the retina. We found that these saccades generate fluctuations in intraocular glucose concentrations, closely linked to changes in neuronal visual responses over timescales of seconds to minutes. Moreover, pharmacological manipulations that altered glucose availability and eliminated these oscillatory saccades resulted in corresponding shifts in neuronal responses, demonstrating a causal linkage between oscillatory saccades, metabolic regulation, and visual processing. These findings reveal a mechanism by which birds actively evoked saccades during attention-driven information gathering, propelling retinal metabolism and facilitating their vision in the absence of retinal vasculature. This study underscores the interplay among eye movements, metabolic regulation, and high-level visual performance, suggesting broader implications for how eye movements contribute to retinal health, attention, and visual function across species.

SynGAP forms biocondensates at sub-micromolar concentrations and recruits PSD95 and receptor oligomers, functioning as a key initiator of PSD formation
A key issue in neuronal circuit regulation is how synapse formation is initiated. Synapse formation could start when one or more synaptic scaffold proteins that can initiate synapse formation reach certain threshold concentrations in the dendritic shaft, which might lead to their oligomerization or even liquid-liquid phase separation (LLPS). By combining in vitro reconstitution of purified proteins with live-cell single-molecule and confocal imaging, we demonstrated that SynGAP alone forms assemblies of nanoscale clusters containing several to several tens of molecules at 10-nM order concentrations and micron-scale LLPS hydrogel-like condensates at submicromolar concentrations. The trimers of SynGAP's intrinsically disordered region (IDR) induced by its coiled-coil domain are responsible for SynGAP condensation. CaMKII-mediated phosphorylation moderately suppresses SynGAP condensation, and also increases condensate liquidity. While PSD95 fails to form assemblies under these conditions, it is recruited to SynGAP condensates by specifically binding to the PDZ-binding motif of SynGAP. SynGAP[PSD95] condensates selectively immobilize postsynaptic transmembrane proteins, Neuroligin1 and AMPAR-TARP2 complexes, in a manner dependent on their oligomerization state, indicating cooperative recruitment dynamics among SynGAP, PSD95, and transmembrane components, which might mimic initial PSD assembly. These findings suggest that SynGAP may act as a primary nucleator of postsynaptic density assembly, challenging the PSD95-centered models.

Small-world scale-free brain graphs from EEG
Developing individualized spatial models that capture the complex dynamics of multi-electrode EEG data is essential for accurately decoding global neural activity. A widely used approach is network modeling, where electrodes are represented as nodes. A key challenge lies in defining the network edges and weights, as precise connectivity estimation is critical for enhancing neural characterization and extracting discriminative features, such as those needed for task decoding. In this work, we propose a method for inferring subject-specific brain graphs from EEG data, explicitly designed to exhibit small-world and scale-free network properties. Our approach begins by computing phase-locking values between EEG channel pairs to build a backbone graph, which is then refined into an individualized small-world and scale-free network. To reduce computational complexity while preserving subject-specific characteristics, we apply Kron reduction to the resulting graph. We evaluated the proposed method on motor imagery decoding and brain fingerprinting tasks using two EEG datasets. Results show that our model consistently outperforms other benchmark graph models. Furthermore, we show that integrating classical EEG features with those derived using graph signal processing principles significantly improves performance. Overall, our findings highlight the potential of the proposed graph construction framework to enhance EEG analysis, with promising implications for a wide range of applications in cognitive neuroscience and brain-computer interface research.

A neuroprotective tetrapeptide for treatment of acute traumatic brain injury
Traumatic brain injury (TBI) is a major clinical problem because of the high incidence and the severity of the subsequent sequelae. Despite extensive efforts, there are no therapeutic drugs clinically approved for treating acute TBI patients. To address this unmet need, we assessed the activity of the tetrapeptide, CAQK, in mice. When administered intravenously shortly after moderate or severe TBI, CAQK accumulates in the injured brain in mice and pigs. CAQK binds to an extracellular matrix glycoprotein complex that is upregulated in injured brain. Treatment of TBI mice with CAQK resulted in reduction in the size of the injury compared to control mice. There was reduced upregulation of the glycoprotein complex, less apoptosis, and lower expression of inflammatory markers in the injured area, indicating that CAQK alleviates neuroinflammation and the ensuing secondary injury. CAQK treatment also improved functional deficit in TBI mice, with no overt toxicity. Our findings suggest that CAQK may have therapeutic applications in TBI.

Sex-dimorphic effects of neuromelanin buildup in rodent nigral dopamine neurons: implications for sex-biased vulnerability in Parkinson's disease
Neuromelanin (NM) is a dark pigment accumulating with age in human substantia nigra pars compacta (SNpc) dopamine (DA) neurons, conferring the dark look that inspired nigral area's name. Despite NM has long been associated with Parkinson's disease (PD), as melanized neurons favorably degenerate during disease development, NM functions within SNpc DA neurons are still mostly elusive. Here, by exploiting an NM-producing rat model generated by viral vector-induced expression of human Tyrosinase (hTyr), we inspected NM impact on nigral DA neurons' survival and activity, on mitochondrial functionality of SNpc, and behaviors resembling non-motor and motor PD symptoms. Our data reveal sex dimorphism in NM effects on nigrostriatal dopamine circuit, with sex-biased alterations in neuronal firing activity and underlying intrinsic currents, nigral mitochondrial functions, and non-motor PD symptoms (anxiety). In conclusion, this study discloses unrealized NM effects within nigral DA neurons, advancing our comprehension of sex-specific features shaping sex-biased vulnerability to PD.