bioRxiv Subject Collection: Neuroscience's Journal

Morphological and functional alteration of light perception circuits in AD patients
Disruption of sleep and circadian rhythms is one of the earliest symptoms of Alzheimer's disease (AD). Circadian entrainment and the modulation of alertness are non-visual responses to light driven by intrinsically photosensitive retinal ganglion cells (ipRGCs). However, little is known about ipRGCs in the context of AD. To explore structural and functional changes of ipRGCs and ipRGC circuits, we analyzed the retinas and brains of 13 elderly patients (9 males, 4 females, aged 69-103) ranging from normal to neuropathologically defined AD. We performed extracellular electrophysiological recordings on freshly harvested retinas using multi-electrode arrays. While rod and cone responses were moderately affected, we found a decreased density of ipRGCs in donors with advanced AD pathology, which was confirmed by immunostaining. The remaining ipRGCs displayed morphological alterations as well as abnormal responses to light, including hyperexcitability. These changes appeared to be subtype-specific and correlated with the advancement of the disease. Altered ipRGCs circuits and function could contribute to the disruption of sleep and circadian rhythms reported in AD patients. The measurement of ipRGC-dependent responses to light could constitute a promising tool to predict or monitor pathological changes in the brain.

Reduced Fast Periodic Visual Stimulation Oddball Responses to Threatening Faces Associated with Anxiety
Facial expression processing is crucial for social communication and survival, with anxiety disorders often linked to alterations in attentional biases toward threat-related stimuli. While previous studies using event-related potentials (ERPs) have yielded conflicting findings regarding threat sensitivity in anxiety, Fast Periodic Visual Stimulation (FPVS) offers a high signal-to-noise, implicit alternative for assessing emotion processing. This study utilized FPVS to investigate neural responses to facial expressions in individuals with anxiety compared to healthy controls. Forty-one adults participated, with 17 classified into the anxiety group based on self-reported diagnosis or PROMIS Anxiety scores. EEG responses were recorded while participants viewed sequences of neutral faces interspersed with emotional oddball expressions (angry, fearful, happy, and sad). Results revealed robust individual- and group-level neural responses, with significantly reduced summed baseline-corrected amplitudes (BCA) in central-parietal regions for angry and happy faces in the anxiety group. These findings suggest that anxious individuals exhibit attenuated discrimination of emotional expressions, particularly in higher-order processing regions, which may reflect cognitive avoidance of threat or general disengagement from emotional stimuli. The study highlights the potential of FPVS as a clinically relevant tool for objectively assessing emotion processing in anxiety and related disorders.

Neural and Behavioral Adaptation to Listening with a Unilateral Cochlear Implant (CI)
The human auditory system must encode sounds and separate relevant input from noise. Hearing loss hurts both processes, but profound hearing loss and deafness can be treated with a Cochlear Implant (CI). Here, we probe the human brains adaptation to electrical hearing with a CI in unilaterally implanted CI users with normal or aided contralateral hearing, in the first and seventh month after CI activation. In addition to clinical measures of speech comprehension, electroencephalography (EEG) recordings during passive listening to amplitude-modulated (AM) sounds and an active spatial listening task with competing talkers were analyzed. We demonstrate that, first, adaptation to hearing with a CI is accompanied by decreasing cortical overrepresentation and increasing auditory temporal coding fidelity: After six month of CI use, auditory phase-locking during passive listening relatively decreased for 4-Hz AM sounds but increased for 40-Hz AM sounds. Second, strongest benefits of listening with the CI (i.e., CI on vs. off) in the spatial-listening task occurred when the CI ear was primarily exposed to target sound. Here, the power of lateralized alpha oscillations (~10 Hz) served as a robust signature of spatial attention, independent of time (1st vs 7th month) and listening modality (with vs. without CI). Stronger lateralized alpha modulation in the hemisphere contralateral to the non-implanted ear suggests asymmetrical allocation of auditory spatial attention, operating preferentially on the input to the non-implanted ear. These findings highlight CI-related plasticity in auditory perception and a persistent attentional bias toward the non-implanted ear, emphasizing the need to consider bilateral auditory input in CI rehabilitation.

A biophysical model of synaptic tagging-and-capture based on actin dynamics
According to the synaptic tagging-and-capture hypothesis, long-lasting (late-phase) plasticity requires the synthesis of plasticity-related proteins and the setting of a synaptic tag at the stimulated synapse. It has been hypothesized that this tag is implemented by the complex interplay between dendritic spine geometry and the scaffolding protein actin. To test this, we propose a biophysically-grounded model of late-phase synaptic plasticity considering dynamic and stable actin pools and the size of the PSD in the synapse. In our model, the tag corresponds to the imbalance between the spine volume determined by actin and the volume that would be expected for the current PSD size. We demonstrate the viability of the proposed model by showing that it can account for the experimentally observed synaptic plasticity induced by stimulation of a single synapse, as well as tag-resetting protocols, and heterosynaptic plasticity protocols involving two synapses. Moreover, for the interaction of two consecutive stimuli at the same synapse within around up to an hour, plastic changes stack non-linearly, reminiscent of the spacing effect found in learning and memory studies. In summary, our model both matches experiments and extrapolates well to a wide range of stimulation protocols. Thus, it will be ideally suited to serve as a basis to predict the plasticity effects emerging from the complex activity patterns in recurrent networks.

Behavioural separation of face memory and face perception
A long-standing debate in neuropsychology concerns whether perception and memory function as independent systems or interact to support cognition. To investigate this, we developed the Face Memory and Perception (FMP) task, a novel paradigm designed to systematically disentangle whether and how these processes interact under different conditions. Across four independent datasets with over 800 participants in total, we observed consistent evidence that face perception and working memory operate independently when task demands are low, but in more complex conditions, these processes interact. Notably, this interaction emerged only when the interference directly involved face-processing mechanisms. This interaction did not arise from a general increase in cognitive load but rather was driven by a shift from holistic to feature-based face processing as a result of maintenance-disrupting interference. These results underscore both the fundamental independence of perception and working memory while also highlighting conditions under which they interact, contributing to a richer understanding of face processing.

Developmental gene expression patterns driving species-specific cortical features
The cerebral cortex shows species-specific variations in size and organization, likely accounting for distinct behavioral abilities. These structural differences may reflect evolutionary changes in the developmental expression of shared genes. To investigate this possibility, we compared cell-type-specific developmental gene expression across species in the developing mouse and human neocortex, and human cortical organoids, by developing a shared transcriptional reference framework. This identified genes with conserved/divergent expression patterns, providing a molecular foundation to interrogate species-specific cellular properties. Using this resource, we discovered that the transcription factor JUNB is expressed in human but not mouse progenitors. Through cell-typespecific gain- and loss-of-function experiments in mice and human organoids, we demonstrate that JUNB bidirectionally controls human cortical features, including progenitor proliferation rates, neuronal production timing, and total neuronal output. This reveals how cell-type-specific regulation of shared genes during development can drive species-specific cortical features, providing a framework for understanding the molecular basis of cortical evolution.

Quantifying state-dependent control properties of brain dynamics from perturbation responses
The brain can be conceptualized as a control system facilitating transitions between states, such as from rest to motor activity. Applying network control theory to measurements of brain signals enables characterization of brain dynamics through control properties, including controllability. However, most prior studies that have applied network control theory have evaluated brain dynamics under unperturbed conditions, neglecting the critical role of external perturbations in accurate system identification, which is a fundamental principle in control theory. The incorporation of perturbation inputs is therefore essential for precise characterization of brain dynamics. In this study, we combine a perturbation input paradigm with a network control theory framework and propose a novel method for estimating the controllability Gramian matrix in a simple, theoretically grounded manner. This method provides insights into brain dynamics, including overall controllability (quantified by the Gramian's eigenvalues) and specific controllable directions (represented by its eigenvectors). As a proof of concept, we applied our method to transcranial magnetic stimulation (TMS)-induced electroencephalographic (EEG) responses across four motor-related states and two resting states. We found that states such as open-eye rest, closed-eye rest, and motor-related states were more effectively differentiated using controllable directions than overall controllability. However, certain states, like motor execution and motor imagery, remained indistinguishable using these measures. These findings indicate that some brain states differ in their intrinsic control properties as dynamical systems, while others share similarities that make them less distinguishable. This study underscores the value of control theory-based analyses in quantitatively how intrinsic brain states shape the brain's responses to stimulation, providing deeper insights into the dynamic properties of these states. This methodology holds promise for diverse applications, including characterizing individual response variability and identifying conditions for optimal stimulation efficacy.

Perceptual decision-making during whisker-guided navigation causally depends on a single cortical barrel column
Perceptually driven behavioral choices ae thought to develop gradually from sensation to perception in somatosensory cortex to guide decision-making in higher order cortical areas. Primary somatosensory cortex wS1 of rodents related to their mystacial whiskers has been a model system to study this information flow. However, the role of wS1 in this process is often debated based on controversial results of loss-of-function behavioral experiments that often require prolonged training and movement restraints. Here, to elucidate the role of wS1 in decision-making, we develop an ethological whisker-guided virtual reality (VR) paradigm that closely mimics natural navigation in underground burrows. Untrained mice are navigating at high speed the left and right turns by sensing VR walls with just a pair of their C2 whiskers. We inactivate less than 200 neurons in layer 4 of C2 barrel that results in loss of ability to produce turns contralateral to the lesion. Using probabilistic model of collision avoidance in the presence of noise and uncertainties we hypothesize that wS1 is involved in a feedback control loop that requires continuous updates and predictions to infer the optimal path for collision avoidance.

EPICURUS: E-field-based spatial filtering procedure for an accurate estimation of local EEG activity evoked by Transcranial Magnetic Stimulation
BackgroundThe concurrent use of Transcranial magnetic stimulation (TMS) with electroencephalography (EEG) is increasingly integrated in research and clinical protocols to provide proof of effect by magnetic pulses. However, a reliable identification of evoked local EEG activity over TMS targeted cortical sites remains still challenging.

MethodsHere we present EPICURUS, a novel EEG spatial filtering approach, by which, individual MRI based simulations of TMS- electrical fields (E-fields) guide the reconstruction of TMS evoked o EEG signals originated in the primary motor cortex, minimizing crosstalk from non relevant more distant sources.

ResultsA reduction of late Transcranial Evoked-Potentials (TEPs) components (>100 ms post pulse onset) suggest our E-field-based spatial filter approach efficiently reduced intrusion of non-locally relevant distant sources engaged by TMS, particularly when combined with a suppression of auditory entries.

ConclusionThe individually customized E-field-based spatial filtering procedure here developed for TMS- EEG datasets shows promise improving the spatio-temporal mapping of primary sources activated by magnetic pulses.

HIGHLIGHTSO_LIConcurrent TMS-EEG recordings are a well-established tool to monitor brain state of activity and provide proof of effect and target engagement.
C_LIO_LIThe lack of spatial specificity of EEG prevents an accurate estimation of the locally activated EEG sources, hindering the interpretation of TMS effects.
C_LIO_LIWe here developed a spatial filtering approach for TMS-EEG based on individual estimation of E- field spread following stimulation.
C_LIO_LIOur E-field spatial filter combined with auditory constraints reduced non-relevant distant signal components and improved the reliability of local EEG estimates.
C_LI

Robust single-trial estimates of electrocortical generalized aversive conditioning: Validation of a Bayesian multilevel learning model
Aversive conditioning changes visuocortical responses to conditioned cues, and the generalization of these changes to perceptually similar cues may provide mechanistic insights into anxiety and fear disorders. Yet, neuroimaging conditioning paradigms are challenged by poor single-trial signal-to-noise ratios (SNR), missing trials, and inter-individual differences in learning. Here, we address these issues with the validation of a steady-state visual evoked potential (ssVEP) generalization paradigm in conjunction with a Rescorla-Wagner inspired Bayesian multilevel learning model. A preliminary group of observers (N=24) viewed circular gratings varying in grating orientation, with only one orientation paired with an aversive outcome (noxious electric pulse). Gratings were flickered at 15 Hz to evoke ssVEPs recorded with 31 channels of EEG in an MRI scanner. The multilevel structure of the Bayesian model learning model informs and constrains estimates per participant providing an interpretable generative model. It led to superior cross-validation accuracy and insights into individual participant dynamics than simpler models. It also isolates the generalized effects of conditioning, providing improved statistical certainty. Lastly, the present report demonstrates that missing trials are interpolated and weighted appropriately using the full models structure. This is a critical aspect for single-trial analyses of simultaneously recorded physiological measures, because each added measure will typically increase the number of trials missing a complete set of observations. The present technical report validates a limited version of a learning model to illustrate the utility of this analytical framework. It shows how models may be iteratively built and compared in a modern Bayesian workflow. Future models may use different conceptualizations of learning, allow integration of clinically relevant factors, and enable the fusion of different simultaneous physiological recordings.

Relative timing and coupling of neural population bursts in large-scale recordings from multiple neuron populations
The onset of a sensory stimulus elicits transient bursts of activity in neural populations, which are presumed to convey information about the stimulus to downstream populations. The time at which these synchronized bursts reach their peak is highly variable across stimulus presentations, but the relative timing of bursts across interconnected brain regions may be less variable, especially for regions that are strongly functionally coupled. We developed a simple analytical framework that obtains good estimates of population burst times on a trial-by-trial basis, and of the correlations in the timing of evoked population bursts across areas. We show that this method performs well on simulated data, and is 85 to 90% faster than an alternative, recently-published method while also being much easier to apply. Using this new approach, we examined the relative timing of the first two population bursts following the onset of a drifting grating stimulus in large-scale recordings of spiking activity from six cortical visual areas and one visual thalamic nucleus in thirteen mice. The new method allowed us to identify mouse-to-mouse variation in peak times and region-to-region functional coupling. While all results were consistent with known anatomy and physiology, we found some sequences of activity across areas to be the same across all mice, while others varied with the individual. The general approach can thus produce sensitive analyses of timing relationships across neural populations.

Congruent neuronal modulation across competing actions challenges the role of the substantia nigra in action selection
The basal ganglia are involved in the control of movement, but their exact role is unclear. Paradoxically, most of the inhibitory projection neurons in the main output nuclei increase firing around the time of movement; only a small fraction decrease firing. This antagonistic activity pattern could subserve action selection, with the small "decrease" population selectively disinhibiting the desired movement, and the larger "increase" population inhibiting competing movements. The action-selection hypothesis makes an implicit assumption: neurons that decrease firing to disinhibit a specific action should increase firing to inhibit that action when a different action is desired. To test this hypothesis, we recorded projection neurons in the substantia nigra pars reticulata (SNr) of mice trained to alternate between two different types of movements. Many SNr neurons showed a "ramping" pattern of pre-movement firing-rate modulation, with most neurons increasing firing, consistent with previous findings. However, contrary to the action-selection model, the overwhelming majority of SNr neurons exhibited congruent modulation between the competing actions, either increasing or decreasing their firing rates for both actions; only a small fraction of neurons exhibited opposite signs of modulation. We could not ascribe the congruent modulation to potential uninstructed movements. Our results are not easily reconciled with simple antagonistic mechanisms for action selection in the basal ganglia output nuclei. We also found that ramping activity in SNr neurons typically began hundreds of ms before self-timed and spontaneous movements, in contrast to previous findings suggesting that basal ganglia output is modulated too late to be involved in movement initiation. Our findings suggest constraints - and raise new questions - about the role of the basal ganglia in movement initiation and action selection.

Epigenetic changes, neuronal dysregulation and metabolomic abnormalities in Zmym2 mutant mice, a genetic model of schizophrenia and neurodevelopmental disorders
Loss-of-function mutations in ZMYM2 are associated with an increased risk of schizophrenia (SCZ) and neurodevelopmental disorders (NDD). ZMYM2 interacts with proteins involved in histone modification and gene regulation, including LSD1 and ADNP; however, its specific roles in the brain remain poorly understood. In this multi-omics study, we demonstrate that heterozygous knockout of Zmym2 in mice results in widespread disturbances in gene expression affecting diverse molecular pathways, including those related to histone modifications and neuronal activity. Proteomic analysis of synapses reveals dysregulation of lipid metabolism and neurofilament-associated pathways, while metabolomic profiling identifies alterations in sphingomyelin and ceramide levels. Furthermore, Zmym2 mutant mice exhibit abnormal brain oscillation patterns on EEG and locomotor hyperactivity in the open field test. Collectively, these findings underscore the critical role of ZMYM2 in brain development and function and highlight Zmym2 mutant mice as a genetic animal model for SCZ and NDD.

Microglia regulate neuronal activity via structural remodeling of astrocytes
Neuron-glia interactions play a central role in regulating synaptic transmission and neuronal excitability. Structural plasticity of astrocytes is associated with numerous physiological and pathological conditions, however, the mechanism underlying this process remains unknown. To examine the basis for structural astrocyte plasticity, we used the classic example of the loss of astrocytic processes that takes place in the hypothalamic magnocellular system during chronic high-salt intake. We discovered that a high-salt diet triggers a local accumulation of reactive microglia around vasopressin-secreting neurons, but not in other brain areas. Microglia phagocytose astrocytic processes, reducing astrocytic coverage of vasopressin neurons. The pruning of astrocytic processes impairs synaptic glutamate clearance, enabling activation of extrasynaptic glutamate NMDA receptors and increasing the activity of vasopressin neurons. Inhibiting microglia-mediated astrocyte pruning attenuates the increased neuronal activity and vasopressin-dependent hypertensive phenotype of rats fed high-salt diet. Thus, microglia orchestrate neuron-glia interactions and regulate neuronal activity through astrocyte pruning.

Convergent and selective representations of pain, appetitive processes, aversive processes, and cognitive control in the insula
Regions that respond to multiple types of information ("convergence zones") are crucial for the brain to generate coherent experiences and behaviors. The insular cortex, known for its functional diversity, has been hypothesized to be a key convergence hub, yet empirical evidence identifying how and where convergence occurs is incomplete. To address this gap, we analyzed functional convergence across four key task domains--somatic pain, non-somatic appetitive processes, aversive processes, and cognitive control--in a large-scale Bayesian mega-analysis of fMRI data (N=540, systematically sampled from 36 studies). Bayes Factor analyses identified both convergent zones responding to multiple domains and selective zones responding to single domains. Results revealed a hierarchical convergence architecture, with a multi-domain convergence zone in bilateral dorsal anterior insula surrounded by zones showing progressively increasing convergence. Functional decoding and coactivation analyses further support the insula's role as a convergence hub, while cytoarchitectonic and neurotransmitter profiling characterizes the potential neuroanatomical underpinnings subserving convergent and domain-selective function. Overall, our results demonstrate a structured functional topography in the insula that bridges specialized and convergent processing, providing a potential neural basis for how diverse information streams combine into unified subjective experiences.

Chronic social defeat causes dysregulation of systemic glucose metabolism via the cerebellar fastigial nucleus
Chronic psychological stress leads to hyperglycemia through the endocrine and sympathetic nervous systems, which contributes to the development of type II diabetes mellitus (T2DM). Higher plasma corticosteroids after stress is one well-established driver of insulin resistance in peripheral tissues. However, previous studies have indicated that only a fraction of patients with depression and post-traumatic disorder (PTSD) who develop T2DM exhibit hypocortisolism, so corticosteroids do not fully explain psychological stress-induced T2DM. Here, we find that chronic social defeat stress (CSDS) in mice enhances gluconeogenesis, which is accompanied by a decrease in plasma insulin, an increase in plasma catecholamines, and a drop in plasma corticosterone levels. We further reveal that these metabolic and endocrinological changes are mediated by the activation of neurons projecting from the cerebellar fastigial nucleus (FN) to the medullary parasolitary nucleus (PSol). These neurons are crucial in shifting the bodys primary energy source from glucose to lipids. Additionally, data from patients with depression reveal correlations between the presence of cerebellar abnormalities and both worsening depressive symptoms and elevated HbA1c levels. These findings highlight a previously unappreciated role of the cerebellum in metabolic regulation and its importance as a potential therapeutic target in depression, PTSD, and similar psychological disorders.

Autism-associated ASPM variant causes macrocephaly and social-cognitive deficits in mice
In autism spectrum disorder (ASD), a neurodevelopmental disorder with social-cognitive deficits, macrocephaly occurs in 20% of patients with severe symptoms. However, the role of macrocephaly in ASD pathogenesis remains unclear. Here, we address the mechanistic link between macrocephaly and ASD by investigating a novel ASD-associated gain-of-function A1877T mutation in ASPM (abnormal spindle-like microcephaly-associated). ASPM is a key regulator of cortical size and cell proliferation expressed in both excitatory and inhibitory neuronal progenitors but not in differentiated neurons. We found that Aspm gain-of-function knock-in mice exhibit macrocephaly, excessive embryonic neurogenesis with expanded outer radial glia, an increased excitatory-inhibitory (E-I) ratio, brain hyperconnectivity, and social-cognitive deficits with male specificity. Our results suggest that macrocephaly in ASD is not a proportional expansion of excitatory and inhibitory neurons, but a shift in the E-I ratio, independent of the expression patterns of the causative gene. Thus, macrocephaly alone can cause a subset of ASD-like symptoms.