bioRxiv Subject Collection: Neuroscience's Journal

Temperature Induced Codimension-One and Codimension-Two Bifurcations in Hodgkin-Huxley Neurons
Temperature fluctuations can have detrimental effects on the firing pattern and electrical activity of biological neurons, eliciting diverse responses depending on the neuronal cell types and the underlying ion channels exhibited. Using the classical Hodgkin-Huxley (HH) model, we performed a comprehensive dynamical systems analysis to determine how temperature fluctuations alter neuronal excitability, spike morphology, and bifurcation structure. We first relied on experimentally-derived temperature coefficients, or Q10 values, associated with gating kinetics and conductances, and examined codimension-1 and codimension-2 bifurcations across a range of temperatures and standard HH parameters governing the intrinsic properties (firing frequency, spike amplitude, spike width, afterhyperpolarization (AHP), time-to-peak AHP, etc) of the model HH neuron. Our analysis revealed that increasing temperature accelerates gating dynamics, leading to narrower and higher-frequency spikes but reduced amplitudes, and ultimately to a loss of sustained firing via temperature-induced depolarization block. We identified generalized Hopf (Bautin) bifurcations as critical boundaries beyond which the system becomes strictly monostable. Extending the model to independently scale sodium activation, sodium inactivation, and potassium activation kinetics showed that excitability is particularly sensitive to potassium gating dynamics. Our findings provide a quantitative framework for understanding temperature modulations of neuronal activity, highlighting how temperature reshapes the excitability landscape, unveiling the intricate interplays between the activation/inactivation kinetics of ion channels, and identifying key parameters governing temperature robustness in neuronal models.

Early-onset β-amyloidosis in human brains with hematological malignances and cardiovascular diseases: Revisiting injury/stress induced axonal pathology
{beta}-Amyloid (A {beta}) and tau pathologies are hallmarks of Alzheimer's disease (AD) and they develop in human brain following differential spatiotemporal trajectories. As such, young/adult-onset tau-independent {beta}-amyloidosis is rare. We encountered four such cases among 397 banked brains, with the donors died of hematological malignances (blood cancers) or cardiovascular diseases. To explore the pathological implications, we examined 17 brains (10-87 year-old, y) from blood cancer patients and three (52-82 y) with cardiovascular diseases, focusing on vascular injury, axonal pathology and A{beta} formation. A{beta} plaques occurred in two adult brains (31 y, 63 y) with blood cancers and two (52 y, 65 y) with cardiovascular diseases in the absence of tau. In the blood cancer brains, 17/17 had vascular injuries seen in hematoxylin-eosin stained sections, 13/17 had iron leakage, and 13/17 had axonal pathology. Malignant cell infiltration was found in 5/14 brains with myeloid, lymphocytic and lymphoma malignances, with light chain infiltration in 3/3 brains with multiple myeloma. In the cardiovascular disease brains, A{beta} deposition primarily as diffuse plaques occurred in the cerebral cortex, with vascular and axonal pathologies in the white matter, striatum and internal capsule. Using a multi-labeling approach, the injury/stress induced axonal pathology was found to concur with {beta}-amyloid processor protein elevation and enhanced {beta}-secretase 1 processing but not intraneuronal A{beta} accumulation. The current findings suggest that hematological malignances and cardiovascular diseases are risk conditions for early-onset cerebral {beta}-amyloidosis, potentially attributable to vascular injury.

An Explainable Web-Based Diagnostic System for Alzheimer's Disease Using XRAI and Deep Learning on Brain MRI
Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by cognitive decline and memory loss. Despite advancements in AI-driven neuroimaging analysis for AD detection, clinical deployment remains limited due to challenges in model interpretability and usability. Explainable AI (XAI) frameworks such as XRAI offer potential to bridge this gap by providing clinically meaningful visualizations of model decision-making. Methods: This study developed a comprehensive, clinically deployable AI system for AD severity classification using 2D brain MRI data. Three deep learning architectures MobileNet-V3 Large, EfficientNet-B4, and ResNet-50 were trained on an augmented Kaggle dataset (33,984 images across four AD severity classes). The models were evaluated on both augmented and original datasets, with integrated XRAI explainability providing region-based attribution maps. A web-based clinical interface was built using Gradio to deliver real-time predictions and visual explanations. Results: MobileNet-V3 achieved the highest accuracy (99.18% on the augmented test set; 99.47% on the original dataset), while using the fewest parameters (4.2M), confirming its efficiency and suitability for clinical use. XRAI visualizations aligned with known neuroanatomical patterns of AD progression, enhancing clinical interpretability. The web interface delivered sub-20 second inference with high classification confidence across all AD severity levels, successfully supporting real-world diagnostic workflows. Conclusion: This research presents the first systematic integration of XRAI into AD severity classification using MRI and deep learning. The MobileNet-V3-based system offers high accuracy, computational efficiency, and interpretability through a user-friendly clinical interface. These contributions demonstrate a practical pathway toward real-world adoption of explainable AI for early and accurate Alzheimer's disease detection.

Multiple scales of coordination along the body axis during Drosophila larval locomotion
Coordinated movement along the body axis is critical to locomotion. In segmented, limbless animals, anterior (head) and posterior (tail) segments play different roles in locomotion, leading to a need for flexible coordination across body regions. Larval Drosophila melanogaster present a tractable experimental model for limbless, segmented crawling given the extensive genetic tools available and the optical clarity of the body. Prior work has suggested that, during crawling, all larval body segments contract similarly, despite the fact that each crawl cycle comprises two overlapping phases: an piston involving the most posterior segments, and a peristaltic wave involving all body segments. To test whether coordination varies regionally during locomotion, we expressed GCaMP in all body wall muscles, and recorded segmental contraction kinematics and muscle recruitment during many cycles of locomotion in linear channels. Facilitated by machine vision techniques, we discovered new features of larval crawling at multiple scales. First, the propagation of both contraction and recruitment waves slowed approaching mid-body segments, then sped up towards the head. Second, the timing relationship between contraction and recruitment waves could be highly variable in anterior segments. Third, contraction durations showed particularly strong intersegmental correlations among posterior segments. These data suggest posterior segments coordinately power the piston phase while anterior segments tolerate greater flexibility to enable reorienting behaviors. Our results depict an unanticipated degree of axial heterogeneity in the coordination of limbless crawling, opening new avenues to study the origins of whole body coordination and the consequences of segmental diversity for locomotion.

Drosophila Pyruvate Kinase Links Metabolic State with Circadian Output via TARANIS and PDF
The circadian clock generates ~24-hour rhythms that anticipate daily environmental changes. Circadian clock and glucose metabolism are tightly interconnected, and both are disrupted in aging and disease. To examine how glucose hypometabolism impacts circadian rhythm, we downregulated glycolytic enzymes - Hexokinase-C (Hex-C), Phosphofructokinase (Pfk), and Pyruvate kinase (Pyk) - in Drosophila clock cells. Only Hex-C and Pyk knock-down (KD) altered period, lengthening and shortening rhythms, respectively. Notably, Pyk KD induced period shortening persisted in adult-specific KD (AKD), indicating a role independent of developmental effects. Pyk AKD reduced both PERIOD and Pigment-dispersing factor (PDF) protein levels, with PDF loss driving the short-period phenotype. Mechanistically, the transcriptional co-regulator TARANIS (TARA) was required: Pyk AKD lowered tara expression, while tara overexpression rescued PDF and circadian period. Our findings identify a novel PYK-TARA-PDF regulatory axis linking glycolytic activity to circadian neuropeptide output, providing mechanistic insight into how metabolic dysfunction contributes to circadian disruption in aging and neurodegenerative diseases.

From berries to brain: Assessing the impact of (poly)phenols in the MPTP mouse model of Parkinson's disease
The growing burden of chronic neurodegenerative diseases (NDs), particularly Parkinson's disease (PD), prompts the need for effective preventive strategies and treatments. Dietary (poly)phenols have emerged for their neuroprotective potential. This study investigated a (poly)phenol-enriched diet, comprising a berry mixture, to counteract key PD hallmarks in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-intoxicated mice and elucidate the phenolic metabolic fingerprint underlying these effects. The berry-enriched diet prevented motor deficits in the MPTP mice model, preserved dopaminergic neurons in the midbrain, reduced glial activation and gene expression of inflammatory cytokines. Notably, berries also attenuated macrophage infiltration observed in the substantia nigra 7 days post-MPTP. Metabolomic analysis revealed distinct phenolic signatures in plasma and brain tissue between standard- and berry-fed mice. Overall, this pioneering study provides compelling evidence that a (poly)phenol-enriched diet may play a protective role in neurodegenerative disorders, highlighting its potential for future strategies to prevent or slow PD progression.

Mice and humans evaluate odor stimulus strength using common psychophysical principles
Sensory systems translate physical stimuli from the environment--such as light, sound, or chemicals--into signals that the brain can interpret. Across these systems, the amplitude of a stimulus is represented by its perceived intensity (Stevens 1957). While previous research has largely focused on understanding how physical stimuli are represented in the brain, the neural representation of perceptual variables like stimulus intensity remains less explored. This is primarily due to the difficulty in measuring perceptual responses in animal models, where neural recordings are more accessible. In this study, we use mouse olfaction as a model system to develop a framework for measuring perceived odor intensity. We begin by employing a two-odor concentration classification task to demonstrate that both mice and humans assess stimulus amplitude using a common perceptual scale. We then show that this scale corresponds to intensity. Finally, we apply this method to determine iso-intense concentrations of different odorants in mice. Our approach offers a powerful tool for testing hypotheses about the neural mechanisms underlying perceived odor intensity, potentially enhancing our understanding of olfactory processing and its neural substrates.

Hugin-AstA circuitry is a novel central energy sensor that directly regulates sweet sensation in Drosophila and mouse
Taste sensation plays a crucial role in shaping feeding behavior and is intricately influenced by internal states like hunger or satiety. Despite the identification of numerous neural substrates regulating feeding behavior, the central neural substrate that linked energy-sensing and taste sensation remained elusive. Here, we identified a novel neural circuitry that could directly sense internal energy state and modulate sweet sensation in the Drosophila brain. Specifically, a subset of neuropeptidergic neurons expressing hugin directly detected elevated levels of circulating glucose via glucose transporter Glut1 and ATP-sensitive potassium channel. Upon activation, these neurons released hugin peptide and activated downstream Allatostatin A (AstA)+ neurons via its cognate receptor PK2-R1. Subsequently, the activation of AstA+ neurons then directly inhibited sweet sensation via AstA peptide and its cognate receptor AstA-R1 expressed in sweet-sensing Gr5a+ neurons. We also showed that neuromedin U (NMU), the mammalian homolog of fly hugin, served as an energy sensor to suppress sweet sensation. Therefore, these data identify hugin+ neuron as a central energy sensor responsible for regulating sweet sensation across species.

An optogenetic assay of Drosophila larval motor neuron performance in vivo
Background: Over fifty million people worldwide currently live with neurodegenerative diseases, many of which are the result of pathogenic gene variants. Genetically malleable model organisms provide an avenue for research into the genetic bases of these diseases, and the large motor neurons of fruit fly larvae provide a test bed for investigating neuronal mechanisms impacted by pathogenic gene variants. However, it is challenging to collect information from these neurons under physiological conditions as they terminate on muscle fibers that are perpetually contracting - driven by motor neuron burst-firing. New Method: As a test of in vivo neuronal performance, we expressed light-activated opsins in motor-neurons of unrestrained intact Drosophila larva and used light pulses to drive cyclical body-wall contractions that were captured on camera and analyzed offline. Results: We describe the assembly of an apparatus to systematically activate motor-neurons in Drosophila larvae and an image acquisition system to capture the resulting body-wall contractions. To test the utility of the assay we performed a motor-neuron specific knock-down of dMiro, an adaptor for mitochondrial transport into motor-neuron terminals. As predicted, contractions were poorly sustained in larvae with impaired axonal transport of mitochondria. Comparison with Existing Methods: This in vivo assay allows for a test of sustained neuronal performance while sidestepping the shortcomings of electrophysiological assays of neurotransmission in situ where hemolymph-like solutions may not recapitulate hemolymph properties, axons are severed and where recordings are mechanically disrupted at endogenous firing rates. Secondly, unlike adult climbing assays and larval locomotion assays, performance is assayed independently of the organism's motivation to perform or ability to detect stimuli. Conclusions: We demonstrated that Drosophila 3rd instar larvae cannot sustain body-wall contractions if mitochondria are not delivered to motor nerve terminals - validating a motor neuron performance assay in a model organism suited for molecular genetic analysis.

Octopamine and Tyramine Modulate Motor Program Competition in Drosophila larvae
Dynamic Interactions amongst competing motor programs shape behavioural output. Here, we use a combination of opto- and electro-physiology to explore how the tdc2+ adrenergic-like system modulates competition amongst central pattern generating (CPG) networks controlling locomotion in Drosophila larvae. Bath application of octopamine (OA) promoted fictive forwards locomotion, suppressed backwards locomotion, and induced bouts of fictive head sweeps during wash period that were proportional to the promotion of forward waves. In contrast, tyramine (TA), the conceptualised inhibitory antagonist to OA, promoted collisions and overlap of motor programmes, activity-dependent inhibition, and bouts of silence during wash periods. Dual-colour calcium imaging of the tdc2+ system with motor neurons revealed that the tdc2+ neurons are recruited phasically prior to a majority of fictive locomotor behaviours. Optogenetic manipulation of the tdc2+ system recapitulated a subset of effects and further revealed that activity in tdc2+ system neurons necessary and sufficient for locomotor CPG activity in the system. Overall, our work generates testable predictions for computational and connectomics studies for Drosophila motor competition and provides insights into how adrenergic-like systems can modulate dynamics of motor competition among interacting CPGs within locomotor networks.

Synaptic high-frequency jumping synchronises vision to high-speed behaviour
During high-speed behaviour, animals must predict, detect, process, and respond synchronously to rapid environmental changes, including those caused by their own movements. How neural systems achieve such precision remains unclear. Here, we investigate how the housefly (Musca domestica), renowned for agile aerial manoeuvres, maintains visual accuracy during ultrafast motion. Although rapid movements typically blur vision, houseflies exhibit remarkable visual acuity; their visual neurons achieve record-high rates of information sampling (~2,500 bits/s) and synaptic transmission (~4,100 bits/s), substantially surpassing previous estimates. Using intracellular and photomechanical recordings of photoreceptors exposed to rapid sequences of saccade-like stimuli, we traced information transmission to large monopolar cells (LMCs), the first interneurons in the visual pathway. We identify a previously unknown mechanism - synaptic high-frequency jumping - in which photoreceptor-LMC synapses dynamically shift transmission towards higher frequencies during saccadic input. This mechanism extends visual bandwidth to ~920 Hz, eliminates synaptic delays, and quadruples traditional flicker-fusion limits (~230 Hz). Ultrafast behavioural experiments confirm flies respond synchronously within ~13-20 ms, even while photoreceptor responses are still approaching their peak (9-16 ms), directly challenging classical sequential-processing models. Our biophysically realistic photoreceptor-LMC model demonstrates how photomechanical, quantal, and refractory sampling processes co-adapt dynamically with behaviour. Thus, flies actively shape their visual input through self-generated saccades, driving high-frequency jumping, efficient neural coding, hyperacute vision, and neural synchronisation. These findings redefine foundational principles of compound-eye function, uncovering a universal neural strategy underlying synchronous, high-speed predictive processing.

Semantic elaboration determines the time course of alpha-beta oscillations during the encoding and retrieval of narrative memories
Understanding and remembering everyday events requires us to retrieve semantic relationships between elements by activating prior knowledge, allowing us to form a deeper memory trace. However, the neural interplay between semantic and episodic systems to encode and retrieve recent memories remains unclear. The present study addresses how semantic elaboration enhances episodic memory formation through neural oscillations. We presented participants with continuous auditory verbal and non-verbal narratives to memorise. Participants rated the perceived coherence of each narrative to provide a subjective measure of semantic elaboration. We assessed memory of the narratives depending on semantic elaboration and modality of encoding with a subsequent retrieval test. We recorded their electroencephalogram (EEG) to establish how semantic elaboration modulated the representation of narrative information proxied by neocortical alpha-beta oscillations during the encoding and retrieval. First, we found that semantic elaboration facilitated narrative information processing by speeding perceived coherence responses during encoding. Second, the magnitude of alpha-beta desynchronisation across the semantic network progressively increased with the chronological position of the events indexing information accumulation as the narratives unfolded. Third, the coherence scores of the narratives negatively correlated with the magnitude of alpha-beta oscillation desynchronisation later during successful retrieval. Our findings provide direct behavioural and alpha-beta oscillatory evidence of how semantic elaboration influences the time course of neural operations supporting information representation and reinstatement mediated by neocortical alpha-beta oscillations.

Shared latent representations of speech production for cross-patient speech decoding
Speech brain-computer interfaces (BCIs) can restore communication in individuals with neuromotor disorders who are unable to speak. However, current speech BCIs limit patient usability and successful deployment by requiring large volumes of patient-specific data collected over long periods of time. A promising solution to facilitate usability and accelerate their successful deployment is to combine data from multiple patients. This has proven difficult, however, due to differences in user neuroanatomy, varied placement of electrode arrays, and sparse sampling of targeted anatomy. Here, by aligning patient-specific neural data to a shared latent space, we show that speech BCIs can be trained on data combined across patients. Using canonical correlation analysis and high-density micro-electrocorticography (ECoG), we uncovered shared neural latent dynamics with preserved micro-scale speech information. This approach enabled cross-patient decoding models to achieve improved accuracies relative to patient-specific models facilitated by the high resolution and broad coverage of ECoG. Our findings support future speech BCIs that are more accurate and rapidly deployable, ultimately improving the quality of life for people with impaired communication from neuromotor disorders.

Auditory-motor synchronization determines the use of predictions in music perception
When listening to music, our brain constantly generates predictions about the timing and pitch of upcoming sounds based on the structure of the music. Individual differences in the ability to make such rhythmic and melodic predictions shape music perception. Previous studies show that during rhythmic auditory-motor synchronization tasks, better performance is related to stronger motor system engagement. However, whether individual differences in auditory-motor interactions influence higher-level rhythmic predictions is unknown. Here, we used electroencephalography during a naturalistic music listening task to assess the neural tracking of rhythmic and melodic predictions generated from (short-term) local contextual information and (long-term) experience using the Information Dynamics of Music model. We combined a multivariate temporal response function approach with two behavioral measures of auditory-motor synchronization (whispering and finger tapping). We found that stronger auditory-motor synchronization predicted stronger neural tracking of lower-level temporal aspects of the music signal, i.e. acoustic envelope and note onset. Across participants, higher-level (short- and long-term) predictions were also neurally tracked, with neural tracking stronger for rhythmic than melodic predictions. Importantly, our evidence suggests individual differences in the weighting of musical predictions. Individuals with stronger auditory-motor synchronization showed stronger neural tracking of rhythmic compared to melodic predictions, and this effect was especially pronounced for short-term predictions. Our findings demonstrate that the motor system is critically involved at several processing levels even in purely perceptual music tasks, and pave the way for understanding individual differences in the weighting of rhythmic and melodic predictions during music listening.

Hippocampal stimulation reveals causal role of persistent neural activity in human working memory
Working memory (WM) enables the temporary maintenance and manipulation of information, supporting flexible, goal-directed behavior. While converging evidence suggests that the hippocampus contributes to WM storage, its causal role in WM remains unclear. Here, we combined simultaneous intracranial single-neuron recordings in the hippocampus and several cortical areas with focal electrical stimulation in the human hippocampus to test the causal necessity of hippocampal activity for WM. Thirty patients with implanted hybrid depth electrodes performed a WM task with images as memoranda. Electrical stimulation (2 s, 50 Hz, 1 mA) was delivered to the hippocampus during the maintenance period on a subset of trials. Behaviorally, stimulation impaired WM performance, reducing accuracy and increasing response times. Neuronally, stimulation reduced memoranda-selective persistent activity in hippocampus and ventral temporal cortex (VTC), thereby disrupting content-specific neural representations. The extent of neural disruption was correlated trial-by-trial with impaired WM-related behavior, establishing a causal link between disrupted neural activity and impaired WM. At the population level, stimulation shifted neural trajectories farther from attractor states, consistent with degraded mnemonic fidelity. Together, these data provide causal evidence that persistent activity of individual neurons in hippocampus and VTC supports WM maintenance in humans. Our results demonstrate that perturbing hippocampal dynamics disrupts both single-neuron coding and population-level attractor stability, linking cellular mechanisms to behavior and highlighting hippocampal contributions to WM maintenance.

Efficient coding in working memory is adapted to the structure of the environment
Working memory (WM) relies on efficient coding strategies to overcome its limited capacity, yet how the brain adaptively organizes WM representations to maximize coding efficiency based on environmental structure remains largely unknown. In our study, participants remembered a sequence of gratings defined in a two-dimensional feature space where we manipulated directional consistency, revealing enhanced performance for structured (consistent direction) vs non-strutured (non-consistent direction) contexts, particularly for individuals with lower WM capacity. Magnetoencephalography analyses uncovered dissociable neural bases: consistent sequences engaged anterior temporal and medial frontal cortices for abstract directional representations during maintenance, while inconsistent sequences preferentially reactivated item-specific representations in parietal regions. These neural patterns predicted behavioral performance, establishing a neural efficiency principle wherein the brain adaptively switches between relational and item-based coding strategies, mitigating WM constraints. These findings advance our understanding of how structures shape WM organization, offering insights into cognitive flexibility and neural resource allocation in complex environments.

Transcriptional profiling defines unique subtypes of transit amplifying neural progenitors within the neonatal mouse subventricular zone
While significant progress has been made in understanding the heterogeneity in the NSCs, our understanding of similar heterogeneity among the more abundant transit amplifying progenitors is lagging. Our work on the NPs of the neonatal subventricular zone (SVZ) began over a decade ago, when we used antibodies to the 4 antigens, Lex CD133,LeX,CD140a and NG2 and FACs to classify subsets of the neontal SVZ as either multi-potential (MP1, MP2, MP3, MP4 and PFMPs), glial-restricted (GRP1, GRP2, and GRP3), or neuron-astrocyte restricted (BNAP). Using RNAseq we have characterized the distinctive molecular fingerprint of 4 SVZ neural progenitors and compared their gene expression profiles to those of the NSCs. Overall, we identified 1581 genes that were upregulated in at least one NP compared to the NSCs. Of these genes, 796 genes were upregulated in BNAP/GRP1 compared to NSCs; 653 in GRP2/MP3; 440 in GRP3; 527 in PFMPs. One gene in particular that emerged from our analysis that can be used to distinguish the NPs from the NSCs is Etv1, also known as Er81. Interestingly, PFMPs expressed high levels of the transcription factor GSX1, which has been shown to play important roles in regulating interneuron development in the forebrain. PFMPs are also highly express PDGFR, CSPG4 (NG2+) Olig2 and transcripts for olfactory receptors. PFMPs also express Sox10, Gjb1, Zfp488 and Myt1 which have been shown to be important for oligodendrocyte development. The top transcription factors with unique upregulation in BNAP/GRP1s were Zfp57, Hoxac6, and Zfp955a. Unlike the other NPs, the GRP1 and GRP2 NPs expressed many proteins involved in immune cell function. In contrast, the top downregulated genes in the NPs are those involved in cilia formation, consistent with the loss of cilia as neural stem cells become multipotential progenitors. We performed bionformatic analyses to provide insights into the transcription factor interactions that are likely regulating their development as well as the functional consequences of these diffferences in gene expression. The present work will serve as an important resource for investigators interested in further defining the transit amplifying progenitors of the mammalian SVZ.

Executive control in Obsessive-Compulsive Disorder: A worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium
Objective Obsessive-compulsive disorder (OCD) is associated with impaired executive function and altered activity in associated neural circuits, contributing to reduced goal-directed behavior. To investigate neural activation during executive control, we conducted a mega-analysis in the ENIGMA-OCD consortium pooling individual participant data from 475 individuals with OCD and 345 healthy controls across 15 fMRI tasks collected worldwide. Methods Individual participant data was uniformly processed using HALFpipe to construct voxelwise statistical images of executive control and task load contrasts. Parameter estimates extracted from regions of interest were entered into multilevel Bayesian models to examine regional and whole-brain effects of diagnosis, and, within OCD, the influence of medication status, symptom severity, and age of onset on task activation. Results We observed a robust task activation pattern across individuals with OCD and control participants in executive control regions across tasks. Relative to controls, individuals with OCD showed moderate to very strong evidence of weaker activation of the dorsolateral prefrontal cortex, precuneus, frontal eye fields, and inferior parietal lobule during executive control (all positive posterior probabilities [P+]<0.1). Individuals with OCD also showed stronger activation in regions of the default mode network during executive function relative to controls. We found little evidence for differential activation during executive control in task-positive regions related to disease onset, severity and medication status. Conclusion In the first mega-analysis of fMRI studies of executive function in OCD, we found strong evidence of weaker frontoparietal activation during executive control tasks. Our findings also suggest a failure of default mode network regions to appropriately disengage during task performance in OCD.

Anticipated Relevance Prepares Visual Processing for Efficient Memory-Guided Selection
Finding an object typically involves the use of working memory to prioritize relevant visual information at the right time. For example, successfully detecting a highway exit sign is useless when your announced exit is still ten minutes away, but becomes relevant with only thirty seconds to go. Using EEG, we investigated how predictable changes in stimulus relevance influence top-down (i.e., memory-guided) visual selection. Participants memorized an oriented grating, followed by a cue indicating which of two sequentially presented probes was relevant for a memory-match/-mismatch judgment. Consistent with earlier work, relevant probes evoked stronger univariate responses than irrelevant probes. Furthermore, multivariate responses to (memory-matching and memory-mismatching) probes were more distinct when they were relevant compared to irrelevant. Crucially, using rapid invisible frequency tagging (RIFT), we found that early visual responses to the (empty) probe location were enhanced even before the presentation of relevant (compared to irrelevant) probes. These results demonstrate that predictable changes in stimulus relevance induce both pro-active and re-active changes in visual processing. We conclude that anticipating the (ir)relevance of upcoming visual events enables the visual system to prepare ahead of time, enabling efficient memory-guided visual selection.

Frontal theta synchronization facilitates the acquisition of new statistical regularities, evidenced by predictive eye movements
Frontal midline theta oscillations are key neural markers for learning, set-shifting, and adaptive behavior, signaling cognitive control and the reorganization of neural representations. The present study explored how these oscillations mediate the extraction and updating of statistical regularities. We delivered 6 Hz in-phase transcranial alternating current stimulation (tACS) or sham tACS, synchronizing the bilateral prefrontal cortex during an eye-tracking probabilistic sequence learning task designed to test cognitive flexibility and assess pre-stimulus gaze direction changes. A novel probabilistic sequence with a partially overlapping structure was introduced that allowed us to distinguish between the retention of old sequences and the acquisition of new ones. Following comparable statistical learning in both groups during the practice session, our results showed that tACS reduced the incorrect anticipations of previously learned triplets that remained high-probability in the new sequence and allowed participants to more flexibly anticipate triplets newly becoming high-probability. These results suggest a role of frontal midline theta in the flexible rewiring of the mental representations of prior probabilistic structures.

Complement contributes to hyperactive behavior in the 16p11.2 hemideletion mouse model
The complement system is a major component of the innate immune system and plays an important role in immune surveillance. Recent research has demonstrated that the complement system also plays pivotal roles in brain development, and dysregulation of complement is involved in neurodegenerative and neuropsychiatric disorders. However, the mechanisms by which the complement system contributes to neurodevelopmental disorders (NDDs) remain poorly understood. In this study, we find that the expression of a central regulator of the complement cascade, complement component 3 (C3), is upregulated in the striatum of mice modeling the 16p11.2 hemideletion (16p11.2 del). 16p11.2 del is among the most common copy number variations associated with NDDs including attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and intellectual disability (ID). Pharmacological inhibition of the C3a receptor alleviates hyperactivity in 16p11.2 del mice, suggesting that elevated complement contributes to NDD-relevant behavioral changes. Due to the pro-inflammatory actions of the C3a receptor, we assess the cytokine environment in the striatum, a key neural substrate for locomotor behavior, and find that several inflammatory factors are upregulated in 16p11.2 del mice. Collectively, these results indicate that increased expression of the complement system, especially C3, mediates hyperactive behavior and is associated with a pro-inflammatory environment in the striatum of 16p11.2 del mice. Our results suggest that inhibition of an overactive complement system may be an effective strategy to ameliorate NDD symptoms resulting from 16p11.2 hemideletion including those associated with ADHD.

Modulation of motor cortical theta and gamma oscillations using phase-targeted, closed-loop optogenetic stimulation of local excitatory and inhibitory neurons
Theta and gamma oscillations are prominent features of cortical local field potentials (LFPs) and stimulation of the motor cortex at these frequencies can enhance motor learning. Phase-targeted closed-loop stimulation could provide a more precise and effective method to modulate these oscillations, particularly if stimulation parameters could harness the dynamics of the specific circuit mechanisms underpinning the generation of these activities. To address this question, we defined the response of theta- and gamma-frequency oscillations in the motor cortex to closed-loop optogenetic stimulation of excitatory pyramidal neurons and inhibitory interneurons transfected with Channelrhodopsin-2 in awake, head-fixed RBP4-Cre (retinol-binding-protein-4) and PV-Cre (parvalbumin) mice, respectively. Phase-targeted blue-light pulses were delivered using the OscillTrack algorithm to track theta phase in the cortical LFP in real time and trigger stimulation at one of four target theta phases. Stimulation was delivered over a quarter of the target theta cycle, either as a single continuous pulse (continuous protocol) or three short pulses at gamma (75Hz) frequency (gamma protocol). Stimulation of both neuron types, using either stimulation protocol, modulated theta power in a phase-dependent manner, with continuous stimulation of excitatory cells leading to stronger modulation. Phase-dependent amplification during stimulation of excitatory vs inhibitory neurons was offset by 90{degrees}, in line with predictions from computational models. Open-loop replay of previously recorded closed-loop stimulation patterns did not elicit the same phase-specific effects, demonstrating the necessity of the closed-loop interaction to produce these effects. Stimulation of pyramidal neurons using the gamma protocol amplified gamma power, independently of target theta phase. These findings reveal phase-dependent amplification of cortical theta power can be induced by stimulation of local excitatory or inhibitory neurons, with a phase-offset likely resulting from circuit interactions. This approach can be used to inform the development of brain stimulation methods to modulate these activities more effectively in humans.

Learning-Associated Flexibility of Cortical Taste Coding Is Impaired in Shank3 Knockout Mice
The ability to update the valence of sensory perception to influence behavior is crucial for survival. A common phenotype in autism spectrum disorders (ASDs) is defects in sensory processing, but whether these defects impair flexible sensory encoding is largely unexplored. In particular, how genetic risk factors such as Shank3 deletion affect the adaptability of cortical taste processing and downstream behavior is unknown. To address this gap, we performed two-photon calcium imaging during a conditioned taste aversion (CTA) learning paradigm, an ethologically relevant form of associative learning that depends on taste processing in the anterior insular cortex (AIC), to examine how Shank3 knockout alters taste-related neuronal activity in AIC and influences CTA learning. We found that AIC neurons in Shank3 knockout mice exhibited reduced stimulus-evoked suppression and increased trial-to-trial correlated variability during the acquisition of CTA memory. These activity changes, which likely reduced signal-to-noise ratio in AIC, were associated with slower CTA acquisition in knockout mice. In both genotypes, CTA learning enhanced, while subsequent extinction reduced, taste discriminability in AIC, and both extinction and the associated reduction in discriminability were faster in knockout than in wild-type mice. Together, these results show that Shank3 loss is associated with destabilized cortical activity dynamics in AIC, which may contribute to inefficient encoding and maintenance of learned taste aversion. These findings show that loss of Shank3 compromises the ability of animals to update behavior to incorporate negative outcomes, and suggest this loss of flexibility may be an important feature of monogenic ASDs.

Co-infection with two α-synuclein strains reveals novel synergistic interactions
In synucleinopathies, the protein -synuclein misfolds into Lewy bodies (LBs) in patients with Lewy body disease (LBD) or into glial cytoplasmic inclusions (GCIs) in patients with multiple system atrophy (MSA). The ability of a single misfolded protein to cause disparate diseases is explained by the prion strain hypothesis, which argues that protein conformation is a major determinant of disease. While structural, biochemical, and biological studies show that LBD and MSA patient samples contain distinct -synuclein strains, we recently reported the unexpected finding of a novel -synuclein strain in a Parkinson's disease with dementia patient sample containing GCI-like co-pathology along with widespread LB pathology. This finding led us to question if two -synuclein strains can interact with one another in a patient and, if so, can strain competition occur. Notably, this would not only impact the clinical presentation of disease but would also have profound impacts on successful therapeutic development. To test this possibility, we used the strain interference superinfection model developed in the prion field, in which a slower replicating strain--in this study, mouse-passaged MSA--is used to compete with a faster replicating strain--here, recombinant preformed fibrils (PFFs)--following sciatic nerve (sc.n.) inoculation. Unexpectedly, we found that PFFs generated using the same method differed in their ability to neuroinvade following sc.n. inoculation based on -synuclein monomer source. Using a PFF preparation that does spread from the periphery, we conducted strain competition studies by first injecting TgM83+/- mice with mouse-passaged MSA into the sc.n. followed by a second injection with PFFs at 30, 45, and 60% of the MSA incubation period. Unlike in the prion field, where the faster replicating strain inhibits the slower strain at the 30 and 45% time points, we found that the two -synuclein strains exhibited a synergistic effect during neuroinvasion. Notably, disease onset across the three cohorts was shortened compared to MSA inoculation alone, and brains from terminal animals showed evidence of both the PFF and mouse-passaged MSA strains, suggesting the two strains worked together to accelerate neuroinvasion in the mice. These findings have important implications for disease progression in patients with -synuclein co-pathologies. The finding that two strains can synergize with one another to accelerate the progression of clinical disease represents a novel outcome in mixed infection studies and more broadly expands our understanding of the effect of prion strain biology on disease pathogenesis.

High-temporal resolution metabolic connectivity resolved by component-based noise correction
Recent advances in functional PET (fPET) allow for accurate modelling of metabolic processes with a temporal resolution in the range of seconds. This enables new applications such as imaging molecular connectivity at temporal resolutions comparable to fMRI. However, high-temporal resolution fPET data are more sensitive to noise and the extraction of a meaningful signal remains a challenge. We developed a component-based preprocessing approach adapted from fMRI, which models structured noise using tissue-specific regressors and removes low-frequency uptake trends from the fPET signal (CompCor). We applied this method to 20 high-temporal [18F]FDG fPET scans from a next-generation long-axial field of view PET/CT system (1s frames) and 16 scans from a conventional PET/MR scanner (3s frames). We compared filtering methods across frequency bands and examined their effects on metabolic connectivity (M-MC) estimates. Metabolic connectivity was markedly influenced by filtering strategy and scanner type. The CompCor filter produced more consistent and structured networks than standard bandpass filters. Intermediate frequency bands (0.01-0.1 Hz) yielded the most reliable connectivity patterns between PET/CT and PET/MR data (r=0.89). High sensitivity PET/CT data revealed structured connectivity patterns also at a higher frequency band (0.1-0.2 Hz). Compared to fMRI functional connectivity, fPET-derived networks were more spatially cohesive but less differentiated. High-temporal [18F]FDG fPET enables reliable estimation of individual resting-state M-MC when paired with appropriate denoising. Scanner choice and preprocessing significantly affect signal quality and interpretation, whereas the proposed physiologically informed pipeline improves comparability across systems and studies.

Co-allocation of distinct contextual memories within a wide time window temporal dynamics and neuronal co-reactivation during retrieval
Recent studies have shown that a shared neuronal ensemble in the hippocampus links distinct contextual memories encoded within a certain time window (specifically, 5 hours, 2 and 7 days). Here we explored the temporal dynamics of two contextual (neutral and aversive) memories linking and analysed neuronal ensembles in the hippocampus, amygdala and different cortical regions reactivated during retrieval. Firstly, we have found that memories integrated across different time-points including several hours, days and weeks but not if learning phases was separated by short-term and very long-term time intervals. Secondly, we have demonstrated a higher neuronal co-reactivation in the hippocampus and amygdala during retrieval in case of memories integration that supports the hypothesis that shared neuronal ensembles link distinct memories. Finally, we have elicited that proportions of reactivated neuronal ensembles in these brain regions are greater in case of contextual memories integration.

The Neural Consequences of Semantic Composition
Humans can create completely new concepts through semantic composition. These 'conceptual combinations' can be created by attributing the features of one concept to another (e.g., a lemon flamingo might be a yellow flamingo), or drawing on a relationship between concepts (e.g., a lemon flamingo might consume lemons). We ask how semantic composition modulates the neural representations of underlying concepts. Combining functional magnetic resonance imaging (fMRI) with multivariate pattern analysis, we interrogate neural patterns for concepts before and after they were subjected to semantic composition. We observe a post-composition shift in neural patterns underlying weakly constrained concepts in the visual system. The composition of strongly constrained combinations draws on a network of semantic regions that include the right inferior frontal gyrus, left angular gyrus, left lateral anterior temporal lobe, and posterior cingulate cortex. Finally, a subset of the semantic network, in left parahippocampal gyrus, distinguishes the manner of composition: relational or attributive. These findings reveal that semantic composition has neural consequences for the composed concepts, and that the manner of composition affects how the brain's semantic network is deployed.