bioRxiv Subject Collection: Neuroscience's Journal

Integrative transcriptomics and electrophysiological profiling of hiPSC-derived neurons identifies novel druggable pathways in Koolen-de Vries Syndrome
Koolen-de Vries Syndrome (KdVS) is a neurodevelopmental disorder (NDD) with no treatment options due to a lack of understanding of its underlying pathophysiology. To investigate neuronal activity in KdVS, human induced pluripotent stem cell (hiPSC)-derived neurons from KdVS and control subjects were cultured on microelectrode arrays (MEAs). Our study identified reduced network burst rates, indicating disorganized network activity in KdVS neurons. To bridge molecular and functional aspects of the syndrome, we developed an experimental framework, MEA-seq, that integrates network activity measurements with high-throughput transcriptome profiling. This approach identified a negative correlation between the expression of the NDD-associated gene CLCN4 and the network burst rate. Consequently, knockdown of CLCN4 in KdVS neurons restored the activity to control level, confirming a causal relationship between increased CLCN4 expression and reduced network burst rate. Additionally, we identified a positive correlation between mitochondrial gene expression and the network burst rate, and identified impaired mitochondrial function in KdVS hiPSC-derived neurons. The transcriptomic signature of KdVS neurons was then used for computational screening against drug perturbation signatures of the LINCS Consortium database, predicting other drug targets and compounds capable of reversing the expression of affected genes in KdVS neurons. We selected 10 compounds for experimental validation, identifying the antioxidant phloretin and the Rho-kinase inhibitor fasudil as potential candidates for restoring the network activity dysfunction in KdVS. We conclude that the integrative molecular and electrophysiological of hiPSC-derived neurons with MEA-seq has excellent potential for identifying novel drugs and druggable pathways for KdVS and other NDDs.

Stable White Matter Structure in the First Three Years after Psychosis Onset
Background White matter alterations observed using diffusion weighted imaging have become a hallmark of chronic schizophrenia, but it is unclear when these changes arise over the course of the disease. Nearly all studies thus far have been cross-sectional, so despite their large sample sizes, they cannot determine if changes accumulate as a degenerative process, or if patients with pre-existing white matter damage are predisposed to more chronic forms of schizophrenia. Methods We examined 160 scans comprising two years of annual follow-up data from n=42 controls and n=28 schizophrenia patients recruited in the first two years since their diagnosis, totalling two to three scans per subject. We additionally examined six-month follow-up data obtained from an ultra-high field (7 Tesla) scanner (n=68 scans; n=19 first-episode schizophrenia patients; n=15 controls) as a validation dataset. A longitudinal model was used to compare the trajectory of diffusion tenor parameters between patients and controls. Positive and negative symptom scores were correlated with diffusion parameters using ROI- and clustering-based approaches. Results We failed to observe any longitudinal differences in any diffusion tensor imaging parameters between patients and controls in either dataset. We did, however, observe consistent associations between white matter alterations and negative symptoms in both datasets. Conclusions White matter does not appear susceptible to schizophrenia-linked degeneration in the early stages of disease, but pre-existing pathology may be linked to disease severity.

The lincRNA Pantr1 is a FOXG1 target gene conferring site-specific chromatin binding of FOXG1
Derailed gene expression programs within the developing nervous system, encompassing both transcriptional and posttranscriptional processes, can cause diverse neurodevelopmental diseases (NDD). The NDD FOXG1-syndrome lacks full understanding of the mechanistic role of its eponymous gene product. While it is known that FOXG1 acts in part at the chromatin by binding to regulative regions, it is unclear what factors control its presence at specific sites. Long non-coding RNAs (lncRNAs) can mediate site-directed transcription factor binding, but their potential role in FOXG1-syndrome has not been described. Here, we show that FOXG1 localisation is regulated at selected loci through the lncRNA Pantr1. We identified FOXG1 as an upstream transcriptional activator of Pantr1 in human and mice. Further, we discovered that FOXG1 has the ability to associate with RNAs. Both, transcriptional regulation of Pantr1 by FOXG1 and association of both partners, build up a regulative network that impacts the localisation of FOXG1 at selected genomic loci. Specifically, Pantr1 facilitates cooperative presence of FOXG1/NEUROD1 at specific sites, and Pantr1 reduction leads to redistribution of FOXG1 to comparably more generic binding sites. The rescue of impaired dendritic outgrowth upon FOXG1 reduction by simultaneous overexpression of Pantr1 underlines the importance of the FOXG1/Pantr1 regulative network.

The Balanced Mind and its Intrinsic Neural Timescales in Advanced Meditators
A balanced mind, or equanimity, cultivated through meditation and other spiritual practices, is considered one of the highest mental states. Its core features include deidentification and non-duality. Despite its significance, its neural correlates remain unknown. To address this, we acquired 128-channel EEG data (n = 103) from advanced and novice meditators (from the Isha Yoga tradition) and controls during an internal attention task (breath-watching) and an external attention task (visual-oddball paradigm). We calculated the auto-correlation window (ACW), a measure of the brain's intrinsic neural timescales (INTs), and assessed equanimity through self-report questionnaires. Advanced meditators showed higher levels of equanimity and a shorter duration of INTs (shorter ACW) during breath-watching, indicating deidentification with mental contents. Furthermore, they demonstrated no significant differences in INTs between tasks, indicating non-dual awareness. Finally, the shorter duration of INTs correlated with the participants' subjective perceptions of equanimity. In conclusion, we show that the shorter duration of the brain's INT may serve as a neural marker of equanimity.

Multimodal brain imaging of insomnia, depression and anxiety symptoms: transdiagnostic commonalities and differences
Insomnia disorder, major depressive disorder and anxiety disorders are the most common mental health conditions, with high comorbidity and genetic overlap suggesting shared brain mechanisms. Studies on brain correlates of these disorders have not fully addressed this overlap. Aiming to distinguish shared from specific brain structural and functional properties associated with symptoms of these disorders, this study analyzed multimodal brain imaging data from over 40,000 UK Biobank participants. Functional enrichment analyses were conducted to understand the cognitive-emotional and neurotransmission implications of the identified brain regions and connections. Results showed that smaller cortical surfaces, smaller thalamic volumes, and weaker functional connectivity were linked to more severe symptoms across all symptom types. Several symptom-specific associations were revealed, most commonly in different parts of the amygdala-hippocampal-medial prefrontal circuit. These findings revealed both transdiagnostically shared and unique brain properties that could lead to more directed treatment targets for insomnia, depression, and anxiety.

The Impact of Brain-Derived Neurotrophic Factor rs6265 (Val66Met) Polymorphism on Therapeutic Electrical Stimulation for Peripheral Nerve Regeneration: A Preclinical Study of Therapy-Genotype Interactions
Introduction: Peripheral nerve injuries (PNIs) significantly impact patient quality of life. Therapeutic electrical stimulation (TES) shows promise in enhancing nerve regeneration, but outcomes vary widely. This study investigates the impact of the rs6265 single nucleotide polymorphism (SNP) on TES efficacy in a preclinical rat model and human stem cell-derived motor neurons. Methods: Wild-type (WT) and rs6265 variant rats underwent sciatic nerve transection and received either TES or sham treatment. Muscle reinnervation was assessed through compound muscle action potentials and muscle fiber cross-sectional area. Isogenic human iPSC-derived motor neurons were used to study activity-dependent BDNF secretion. Results: TES improved muscle reinnervation and fiber size in WT but not rs6265 allele carriers. rs6265 allele carriers exhibited impaired activity-dependent BDNF secretion in vitro. Discussion: The rs6265 polymorphism influences TES efficacy, highlighting the need for personalized approaches in PNI treatment. These findings suggest that genetic screening could optimize therapeutic outcomes. Clinical Relevance: Understanding genetic factors affecting TES response can enhance treatment strategies for PNI, potentially improving patient recovery and reducing outcome variability.

Learning-Induced Effects of Practice Schedule Variability on Stimuli Discrimination Efficiency: High-Density EEG Multi-scale Analyses of Contextual Interference Effect
Contextual interference (CI) enhances motor learning by practicing skill variations in a random rather than blocked order. It has been demonstrated that performing aiming distances in a random order increased electrophysiological (EEG) markers of perceptual, attentional, and working memory processes. However, only the effect of CI on these markers before training was assessed, without evaluating whether they would decrease with learning in participants trained under the random compared to the blocked condition, indicating enhanced neural efficiency. To address this, 35 participants practiced an aiming task involving three distances over nine sessions across three weeks. They were divided into two groups: one trained with distances in a random order (HCI group) and the other in a blocked order (LCI group). Electrophysiological activity was recorded for all participants in the random condition before and after the training program using a high-density EEG multiscale approach, including topographical, source estimation, and source connectivity analyses. EEG analyses revealed post-training neural dynamic differences between groups. The HCI group showed reduced and shorter P3a-like activity, while the LCI group displayed greater occipito-temporal-frontal gamma-band synchronization. These findings suggest that random practice enhances the efficiency of perceptual and attentional processes, particularly of stimuli discrimination, compared to blocked practice.

Distinct functional domains of Dystroglycan regulate inhibitory synapse formation and maintenance in cerebellar Purkinje cells
Dystroglycan is a cell adhesion molecule that localizes to synapses throughout the nervous system. While Dystroglycan is required to maintain inhibitory synapses from cerebellar molecular layer interneurons (MLIs) onto Purkinje cells (PCs) whether initial synaptogenesis during development is dependent on Dystroglycan has not been examined. We show that conditional deletion of Dystroglycan from Purkinje cells prior to synaptogenesis results in impaired MLI:PC synapse formation and function due to reduced presynaptic inputs and abnormal postsynaptic GABAA receptor clustering. Using genetic manipulations that disrupt glycosylation of Dystroglycan or truncate its cytoplasmic domain, we show that Dystroglycan's role in synapse function requires both extracellular and intracellular interactions, whereas synapse formation requires only extracellular interactions. Together, these findings provide molecular insight into the mechanism of inhibitory synapse formation and maintenance in cerebellar cortex.

Epigenomic anomalies in induced pluripotent stem cells from Alzheimer disease cases
Reprogramming of adult somatic cells into induced pluripotent stem cells (iPSCs) resets the aging clock. However, primed iPSCs can retain cell-of-origin epigenomic marks, especially those linked to heterochromatin and lamina-associated regions. Here we show that iPSCs produced from dermal fibroblasts of late-onset sporadic Alzheimer disease (AD) cases retain epigenomic anomalies that supersede developmental defects and neurodegeneration. When compared to iPSCs from elderly controls, AD iPSCs show reduced BMI1 expression, lower H3K9me3 levels, and an altered DNA methylome. Gene Ontology analysis of differentially methylated DNA regions (DMRs) reveals terms linked to cell-cell adhesion and synapse, with the cognitive resilience-associated MEF2 family of transcription factors being the most enriched binding sites at DMRs. Upon noggin exposure, AD iPSCs show lesser efficient neural induction and forebrain specification, together with increased ZIC2, ZIC5 and WNT-related gene expression. Long-term AD neuronal cultures present a dedifferentiation and loss-of-cell identity phenotype. Despite these epigenomic anomalies, AD iPSCs generate cortical neurons in normal proportion and readily form cerebral organoids developing amyloid and Tau pathology. BMI1 overexpression in AD neurons mitigates amyloid and tau accumulation, heterochromatin fragmentation, and G4 DNA induction. These findings implicate reprogramming resistant epigenomic anomalies or uncharacterized genetic alterations working in trans on the epigenome in AD pathophysiology.

Rapid visual engagement in neural processing of detailed touch interactions
Touch perception is an inherently multisensory process in which vision plays an essential role. However, our understanding of how vision encodes sensory and emotional-affective aspects of observed touch, and the timing of these processes, is still limited. Here we address this gap by investigating the neural dynamics of visual touch observation by analysing electroencephalographic (EEG) data from participants viewing detailed hand interactions from the Validated Touch-Video Database. We examined how the brain encodes basic body cues such as hand orientation and viewing perspective, in addition to sensory aspects, including the type of touch (e.g., stroking vs. pressing; hand vs. object touch) and the object involved (e.g., knife, brush), as well as emotional-affective dimensions. Using multivariate decoding, information about body cues was present within 60 ms, with sensory and emotional details, including valence, arousal, and pain present around 130 ms, demonstrating efficient early visual processing. Threat was most clearly identified by approximately 265 ms, similarly involving visual regions, suggesting that such evaluations require slightly extended neural engagement. Our findings reveal that bottom-up, automatic visual processing is integral to complex tactile assessments, important for rapidly extracting both the personal relevance and the sensory and emotional dimensions of touch.

Longitudinal mapping of cortical change during early adolescence associated with prenatal tobacco and/or alcohol exposure in the Adolescent Brain Cognitive DevelopmentSM Study
Importance: The effects of prenatal alcohol (PAE) and tobacco exposure (PTE) on adolescent neuroanatomical development are typically evaluated cross-sectionally. It is unclear if observed effects persist throughout life or reflect different developmental trajectories. Objective: To determine how PAE and PTE are associated with cortical structure and development across two timepoints in early adolescence. Design: Observational, longitudinal analyses of data within the Adolescent Brain Cognitive Development Study Setting: 21 study sites in the United States Participants: 5,417 youth participants, aged ~9-12 years old Exposures: PAE and PTE based on caregiver (self) reports of alcohol/tobacco use during pregnancy, before and after pregnancy recognition. Main Outcomes and Measures: Cortical thickness (mm) and cortical surface area (mm2) measured approximately 2 years apart in early adolescence, across 68 bilateral cortical regions. Results: At baseline data collection, youth participants were ~9.9 years old (SD=0.6). At the second neuroimaging appointment, youth participants were ~11.9 years old (SD=0.6). When modelling cortical thickness, we controlled for individuals' whole-brain volume; when modelling cortical surface area, individuals' total surface area. Cortical thickness generally declined with age. Cortical surface area either expanded or contracted with age, depending on region. PAE had minimal effects on cortical structure (main effects) and development (PAE*Age interactions). PTE had robust effects on cortical thickness and was associated with faster rates of cortical thinning in several regions within the frontal lobe. Post hoc analyses on (1) the effects of PTE for those who continued tobacco use after pregnancy recognition and (2) the effects of PTE in those who did not also use alcohol revealed weaker effects. Conclusions and Relevance: PTE had robust effects on neuroanatomical structure and longitudinal development, particularly cortical thickness. Analyzing developmental cortical trajectories informs how PTE and/or PAE not only affects cortical structure but how it develops long after those prenatal exposures occurred. Future analyses involving cotinine biomarkers of PTE would enhance the temporal resolution of the ABCD Study's PTE-related queries of tobacco use before and after learning of the pregnancy.

Inferring in vivo murine cerebrospinal fluid flow using artificial intelligence velocimetry with moving boundaries and uncertainty quantification
Cerebrospinal fluid (CSF) flow is crucial for clearing metabolic waste from the brain, a process whose dysregulation is linked to neurodegenerative diseases like Alzheimer's. Traditional approaches like particle tracking velocimetry (PTV) are limited by their reliance on single-plane two-dimensional measurements, which fail to capture the complex dynamics of CSF flow fully. To overcome these limitations, we employ Artificial Intelligence Velocimetry (AIV) to reconstruct three-dimensional velocities, infer pressure and wall shear stress, and quantify flow rates. Given the experimental nature of the data and inherent variability in biological systems, robust uncertainty quantification (UQ) is essential. Towards this end, we have modified the baseline AIV architecture to address aleatoric uncertainty caused by noisy experimental data, enhancing our measurement refinement capabilities. We also implement UQ for the model and epistemic uncertainties arising from the governing equations and network representation. Toward this end, we test multiple governing laws, representation models, and initializations. Our approach not only advances the accuracy of CSF flow quantification but also can be adapted to other applications that use physics-informed machine learning to reconstruct fields from experimental data, providing a versatile tool for inverse problems.

Effect of sleep deprivation on fractal and oscillatory spectral measures of the sleep EEG: a window on basic regulatory processes
Sleep is vital for sustaining life; therefore, reliable measurement of its regulatory processes is of significant importance in research and medicine. Here we examine the effect of extended wakefulness on the putative indicators of fundamental sleep regulatory processes (spectral slope and spindle frequency) proposed by the Fractal and Oscillatory Adjustment model of sleep regulation by involving a healthy young adult sample in a 35-hour long sleep deprivation protocol. Wearable headband EEG-derived results revealed that NREM sleep electroencephalogram (EEG) spectral slope estimated in the 2-48 Hz range is an accurate indicator of the predicted changes in sleep depth induced by sleep deprivation (steepened slopes in recovery sleep) or by the overnight dissipation of sleep pressure (flattening slopes during successive sleep cycles). While the baseline overnight dynamics of the center frequency of the sleep spindle oscillations followed a U-shaped curve, and the timing of its minimum (the presumed phase indicator) correlated with questionnaire-based chronotype metrics as predicted, a different picture emerged during recovery sleep. Advanced recovery sleep advanced the timing of the minima of the oscillatory spindle frequency, reduced considerably its relationship with chronotype, but retained partially its U-shaped overnight evolution. Overall, our study supports the use of the spectral slope of the sleep EEG as a homeostatic marker of wake-sleep regulation, in addition, encourages further research on the EEG-derived measure of the circadian rhythm, primarily focusing on its interaction with the homeostatic process.

Neural representation of direct-to-reverberant energy ratio in recorded and simulated binaural room auralizations
In a complex acoustic environment, sound localization involves the extraction and integration of numerous interrelated auditory cues. To understand how these cues are processed in the brain, studies typically isolate a single cue in an artificial experimental framework, to evaluate what brain regions process individual auditory cues. However, multivariate analyses facilitate more complex manipulations with greater ecological validity by providing a method for comparing between brain activity to a quantitative breakdown of the experimental stimuli. Concurrent advancements in virtual acoustics enable a systematic examination of spatial acoustics in complex realistic environments. Although these simulations have a high perceptual plausibility, they still alter auditory reverberation cues in a perceptible way. The impact of these subtle differences on neural processing is unclear. Auditory distance perception is a particularly challenging perceptual process to study, due to the relative nature of the sensory cues. Therefore, we conducted an imaging study to investigate the representation of auditory cues in recorded and simulated acoustic environments, while performing a distance discrimination task. We recorded the actual MRI environment to reduce room divergence, and the auditory simulations modeled reverberation with different degrees of accuracy. We used an acoustic analysis to determine the differences between the acoustic environments and used these quantitative measures to compare to the pattern of brain activity. We found that although the room auralizations were highly similar, it was possible to decode them from brain activity. The ratio of direct-to-reverberant energy level (DRR) was the only acoustic parameter that made a relevant contribution to brain activity. The locus of this activity was in the posterior auditory cortex.

The relationship between confidence and gaze-at-nothing oculomotor dynamics during decision-making
How does confidence relate to oculomotor dynamics during decision-making? Do oculomotor dynamics reflect deliberation and the buildup of confidence in the absence of visual stimuli? Here we examine the hypothesis that working memory, deliberation, and confidence warp oculomotor dynamics, both in the presence and absence of visual stimuli. We analyzed oculomotor dynamics in a decision-making task in which participants were provided with an abstract context in which to make the decision, and two similar option images which became eventually invisible. We show that fixations between the empty locations in which the images were formerly shown continued after the options disappeared, consistently with a sustained deliberative process facilitated by oculomotor dynamics. Both, oculomotor dynamics and decision patterns remained unchanged regardless of whether the stimuli were visible. Furthermore, our analyses show that the number of alternative fixations between stimuli correlated negatively with the confidence reported after each decision, while the observation time of the selected target correlated positively. Given that decisions in our experimental paradigm are reported in the absence of the stimuli, this suggests a relationship between evidence retrieval from working memory, confidence gathering and oculomotor dynamics. Finally, we performed a model comparison based on predictions from drift-diffusion models to assess the relationship between sequential fixations between images, deliberation and confidence gathering, and the ensuing choice. These analyses supported confidence as a contributing cognitive process encompassing serial evidence-gathering and parallel option consideration during decision-making.

The dual interpretation of edge time series: Time-varying connectivity versus statistical interaction
Functional connectivity (FC) is frequently operationalized as a correlation. Many studies have examined changes in correlation networks across time, claiming to link time-varying fluctuations to ongoing mental operations and physiological processes. Other studies, however, have called these results into question, noting that statistically indistinguishable patterns of time-varying fluctuations can be obtained by windowing synthetic time series generated from ground-truth stationary correlation structure. Recently, we developed a technique for tracking rapid (framewise) fluctuations in network connectivity over time. Here, we show that these "edge time series" are mathematically equivalent to interaction terms in a specific family of general linear models. We exploit this fact to further demonstrate that time-varying connectivity carries explanatory power above and beyond brain activations. This observation suggests that time-varying connectivity is likely more than a statistical artifact.

Numerosity adaptation suppresses early visual responses
Humans and many animals rapidly and accurately perceive numerosity, the number of objects, in a visual image. The numerosity of recently viewed images influences our perception of the current image's numerosity: numerosity adaptation. How does numerosity adaptation affect responses to numerosity in the brain? Recent studies show both early visual responses that monotonically increase with numerosity, and later numerosity-tuned responses that peak at different (preferred) numerosities in different neural populations. We have recently shown that numerosity adaptation affects the preferred numerosity of numerosity-tuned neural populations. We have also shown that early visual monotonic responses reflect image contrast, which follows numerosity closely. Here we ask how monotonic responses in the early visual cortex are affected by adaptation to different numerosities, using ultra-high field (7T) fMRI and neural model-based analyses. FMRI response amplitudes increased monotonically with numerosity throughout the early visual field maps (V1-V3, hV4, LO1-LO2 & V3A/B). This increase in response amplitudes becomes less steep after adaptation to higher numerosities, with this effect becoming stronger through the early visual hierarchy. This suppression of responses to numerosity is consistent with perceptual effects where adaptation to high numerosities reduces the perceived numerosity. These results imply that numerosity adaptation effects in later numerosity-tuned neural populations may originate in early visual areas that respond to image contrast in the adapting image.

Functional characterisation of neuropeptides that act as ligands for both calcitonin-type and pigment-dispersing factor-type receptors in a deuterostome
The calcitonin (CT) family of related peptides exert their diverse physiological effects in mammals via two G-protein coupled receptors, CTR and the CTR-like receptor CLR. Analysis of the phylogenetic distribution of CT-type signaling has revealed the occurrence of CT-type peptides and CTR/CLR-type proteins in deuterostome and protostome invertebrates. Furthermore, experimental studies have revealed that in the protostome Drosophila melanogaster the CT-like peptide DH31 can act as a ligand for a CTR/CLR-type receptor and a pigment-dispersing factor (PDF) receptor. Here we investigated the signaling mechanisms and functions of CT-type neuropeptides in a deuterostome invertebrate, the sea cucumber Apostichopus japonicus (phylum Echinodermata). In A. japonicus, a single gene encodes two CT-type peptides (AjCT1 and AjCT2), both of which act as ligands for a CTR/CLR-type receptor (AjCTR) and two PDF-type receptors (AjPDFR1, AjPDFR2), but with differential activation of downstream cAMP/PKA, Gq/Ca2+/PKC and ERK1/2 signaling pathways. Analysis of the expression of the gene encoding AjCT1 and AjCT2 revealed transcripts in a variety of organ systems, but with highest expression in the circumoral nervous system. In vitro pharmacological experiments revealed that AjCT1 and/or AjCT2 cause dose-dependent relaxation of longitudinal body wall muscle and intestine preparations. Furthermore, in vivo pharmacological experiments and loss-of-function tests revealed a potential physiological role for AjCT2 signaling in promoting feeding and growth in A. japonicus. This is the first study to obtain evidence that CT-type peptides can act as ligands for both CTR/CLR-type and PDF-type receptors in a deuterostome. Furthermore, because of the economic importance of A. japonicus as a foodstuff, discovery of the potential role for CT-type peptides as regulators of feeding and growth in this species may provide a basis for practical applications in aquaculture.

A microendovascular system can record precise neural signals from cortical and deep vessels with minimal invasiveness
Minimally invasive intravascular electroencephalography (ivEEG) signals are a promising tool for developing clinically feasible brain-computer interfaces (BCIs) that restore communication and motor functions in paralyzed patients. However, current ivEEG techniques can only record signals from the superior sagittal sinus (SSS), making it challenging to record motor responses related to hand and mouth movements from brain regions distant from the SSS, despite their critical role in BCIs. Here, using micro intravascular electrodes, ivEEGs recorded from the cortical or deep veins of eight pigs could measure cortical activities with greater signal power and better spatial resolution than those recording in the SSS, thus allowing mapping of the sensorimotor and visual functional areas. Additionally, electrical stimulation in the cortical vein between the micro intravascular electrodes induced muscle contractions contralateral to the stimulated area in five anesthetized pigs. These results demonstrate that ivEEG using micro intravascular electrodes is a promising tool for developing BCIs.

Head And Shoulders - The Impact Of An Extended Head Model On The Simulation And Optimization Of Transcranial Electric Stimulation
Electric field calculations are increasingly used for dose characterization of transcranial electrical stimulation (tES), but existing open-source head models are inaccurate for extracephalic montages that include electrodes placed on the neck or shoulder. We introduce the 'Ernie Extended' model, an MRI- and CT-derived open-source head model extending to the upper shoulder region. Simulations of extracephalic tES targeting the cerebellum and supplementary motor area show significant differences in electric fields when using Ernie Extended compared to the non-extended Ernie model. Additionally, we propose an electrode layout that complements the electroencephalography 10-20 system with extracephalic electrode positions. We demonstrate the use of this layout for optimizing multi-electrode tES montages for cerebellar stimulation, enhancing focality and reducing off-target stimulation, particularly of the spinal cord. Our results highlight the practical value of the Ernie Extended model for accurately characterizing doses produced by extracephalic tES montages and when targeting more caudal brain regions.

Effect of high-intensity anaerobic exercise on electrocortical activity in athletes and non-athletes
Aim: The present study aims to verify the information processing in athletes through electroencephalography, analyze cortical areas responsible for cognitive functions related to attentional processing of visual stimuli, and investigate motor activity's influence on cognitive aspects. Material and Methods: The sample consisted of 29 subjects, divided into an experimental group (n = 13 modern pentathlon athletes) and a control group (n = 16 non-athletes). We collected the electrocortical activity before and after the Wingate Anaerobic Test. During the electrophysiological measures, the volunteers performed a saccadic eye movement paradigm. They also performed cognitive tasks, resting heart rate, and anthropometric measurements. Results: A mixed ANOVA was applied to analyze the statistical differences between groups (athletes and control) and moments (before and after exercise) for F3, F4, P3, and P4 electrodes during rest one and task (pre-stimulus GO). There was an interaction for the group vs. moment factors in F3 [F = 17,129; p = 0,000; eta2 = 0.512], F4 [F = 22,774; p = 0,000; eta2 = 0.510], P3 [F = 11,429; p = 0,001; eta2 = 0.405], and P4 electrodes [F = 18,651; p = 0,000; eta2 = 0.379]. We found the main effect for group factors in the frontal and parietal electrodes of the right hemisphere (F4 and P4) and a main effect of the moment factor on the frontal (F3 and F4) and parietal (P3 and P4) electrodes. There was an interaction between the group vs. moment factors for the reaction time. The groups were different in Peak Power (Watts/kg), Average Power (Watts/kg), Fatigue Index (%), and Maximum Power (ms). Conclusions: We identified chronic effects of exercise training on the cortical activity of modern pentathlon athletes, read-through differences in absolute alpha power, and acute effects of a high-intensity exercise session for athletes and non-athletes for electrocortical and behavioral responses.

Neural contrast sensitivity is not affected by myopic blur
Purpose: The prevalence of myopia is increasing worldwide, accompanied by an increase of potentially under-corrected myopes. Because the neural pathways processing the retinal image are prone to adaptation in relation to the retinal image quality, we wondered to what extent neural contrast sensitivity (NCS) is altered in the presence of myopic blur. Additionally, the impact of retinal abnormalities like foveal hypoplasia with albinism on NCS was tested. Methods: NCS was psychophysically determined for 11 emmetropic, 23 myopic well-corrected and 15 myopic under-corrected otherwise healthy young (27 {+/-} 6 years) participants and 1 albinism patient. Aberration-free stimulation, independent of the eye's refractive state, was achieved by using a unique spatial light modulator-based interferometric system to bypass the eye's optics. Results: No significant differences in NCS were observed between the three groups (Median area-under-curve: 61.9, 62.1, and 62.9 for emmetropes, well-corrected, and under-corrected myopes, respectively; all p > 0.1) but were significantly equivalent between emmetropes and myopes (all p < 0.001). However, the NCS function of the albinism patient differed significantly from the here defined 'normal' NCS function. Conclusions: NCS is unaffected by myopic blur and remains stable even for under-correction of up to 1.5 D. This means, that long-term under-corrected myopes still can achieve normal visual acuity as soon as their refractive errors are sufficiently corrected. Furthermore, NCS testing can relate visual deficits to an underlying neurological disorder.

Implicit Neural Representation of Multi-shell Constrained Spherical Deconvolution for Continuous Modeling of Diffusion MRI
Diffusion magnetic resonance imaging (dMRI) provides insight into the micro and macro-structure of the brain. Multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) models the underlying local fiber orientation distributions (FODs) using the dMRI signal. While generally producing high-quality FODs, MSMT-CSD is a voxel-wise method that can be impacted by noise and produce erroneous FODs. Local models also do not make use of the spatial correlation that is present between neighboring voxels to increase inference power. In the case of MSMT-CSD, costly interpolation computations are necessary to obtain FODs outside of the voxel center points. Expanding upon previous work, we apply the implicit neural representation (INR) methodology to the MSMT-CSD model. This results in an unsupervised machine learning framework that generates a continuous representation of a given dMRI dataset. The input of the INR consists of coordinates in the volume, which produce the spherical harmonics coefficients parameterizing an FOD at any desired location. A key characteristic of our model is its ability to leverage spatial correlations in the volume, which acts as a form of regularization. We evaluate the output FODs quantitatively and qualitatively in synthetic and real dMRI datasets and compare them to existing methods.

Gaze biases can reflect task-specific spatial memorization strategies
Previous work has suggested that small directional eye movements not only reveal the focus of external spatial attention towards visible stimuli, but also accompany shifts of internal attention to stimuli in visual working memory (VWM) (van Ede et al., 2019). When the orientations of two bars are memorized and a subsequent retro-cue indicates which orientation needs to be reported, participants' gaze is systematically biased towards the former location of the cued item (Figure 1AB). This finding was interpreted as evidence that the oculomotor system indexes internal attention; that is, attention directed at the location of stimuli that are no longer presented but are maintained in VWM. Importantly, as the location of the bars is presumably not relevant to the memory report, the authors concluded that orientation features in VWM are automatically associated with locations, suggesting that VWM is inherently spatially organized. This conclusion depends on the key assumption that participants indeed memorize and subsequently attend orientation features. Here we reanalyse Experiment 1 by van Ede et al. (2019) and demonstrate that this assumption does not hold. Instead of memorizing orientation features, participants deployed an alternative spatial strategy by memorizing bar endpoints. Although we do not call into question the conclusion that internal attention is inherently spatially organized, our results do imply that directional gaze biases might also reflect attention directed at task-relevant stimulus endpoints, rather than internal attention directed at memorized orientations.

Predicting the irrelevant: Neural effects of distractor predictability depend on load
Distraction is ubiquitous in human environments. Distracting input is often predictable, but we do not understand whether and under which circumstances humans form and employ predictions about the identity of an expected distractor. Here we ask whether predictable distractors are able to reduce uncertainty in updating the internal predictive model. We show that utilising a predictable distractor identity is not fully automatic but in part dependent on available resources. In an auditory spatial n-back task, listeners (n = 33) attended to spoken numbers presented to one ear and detected repeating items. Distracting numbers presented to the other ear either followed a predictable (i.e., repetitive) sequence or were unpredictable. We used electroencephalography (EEG) to uncover neural responses to predictable versus unpredictable auditory distractors, as well as their dependence on perceptual and cognitive load. Neurally, unpredictable distractors induced a sign-reversed lateralization of pre-stimulus alpha oscillations (~10 Hz) and larger amplitude of the stimulus-evoked P2 event-related potential component. Under low versus high memory load, distractor predictability increased the magnitude of the frontal negativity component. Behaviourally, predictable distractors under low task demands (i.e., good signal-to-noise ratio and low memory load) made participants adopt a less conservative (i.e., more optimal) response strategy. We conclude that predictable distractors decrease uncertainty and reduce the need for updating the internal predictive model. In turn, unpredictable distractors mislead proactive spatial attention orientation, elicit larger neural responses and put higher demand on memory.

Heart Rate Variability During REM Sleep is Associated with Reduced Negative Memory Bias
Emotional memories change over time, but the mechanisms supporting this change are not well understood. Memory consolidation during sleep has been shown to selectively prioritize negative experiences while forgetting neutral memories. Whereas studies examining the role of vagal heart rate variability (HRV) during waking in memory consolidation have shown that vagal HRV is associated with enhanced memory of positive experiences at the expense of negative ones. However, no studies have explored how HRV during sleep contributes to emotional memory processing. Accordingly, we aimed to investigate the neural and vagal contributions during sleep to the processing of neutral and negative memories. To do so, we examined the impact of pharmacological vagal suppression, using zolpidem, on overnight emotional memory consolidation in a double-blind, placebo-controlled, within-subject, cross-over design. Thirty-two participants encoded neutral and negative pictures in the morning, then were tested on picture recognition before and after a night of sleep. Zolpidem or a placebo drug were administered in the evening before overnight sleep, monitored with electroencephalography and electrocardiography. Results showed that higher vagal HRV in Non-Rapid Eye Movement Sleep slow wave sleep (NREM SWS) and Rapid Eye Movement Sleep (REM) was associated with greater overnight improvement for neutral pictures in the placebo condition. Additionally, higher vagal HRV during REM was associated with an emotional memory tradeoff (i.e., greater memory for neutral at the expense of negative images), indicating a potential role for REM vagal HRV in forming a positive memory bias overnight. As previously reported, zolpidem reduced vagal HRV during SWS and increased NREM sigma power, and this vagal suppression eliminated the positive memory bias. Lastly, we used a stepwise linear mixed effects regression framework to investigate how NREM sigma power and vagal HRV during REM independently explained the variance in the emotional memory tradeoff effect and found that including vagal HRV significantly improved the model's fit. Overall, these results suggest that neural and vagal signals synergistically interact in the processing of emotional memories, with REM vagal HRV playing a specific role in contributing to the positive memory bias.

Human deep sleep facilitates faster cerebrospinal fluid dynamics linked to brain oscillations for sleep homeostasis and memory
While cerebrospinal fluid (CSF) dynamics during sleep have been implicated in metabolic waste reduction in animals, how CSF dynamics are driven in the human brain remains elusive. Here, by leveraging a simultaneous sparse-fMRI and polysomnography method designed specifically for acquiring deep stable sleep data, we present the first evidence of deep sleep-specific faster CSF dynamics in healthy young human participants. Slow waves and sleep spindles during slow-wave sleep and rapid eye movements and sawtooth waves during rapid eye movement (REM) sleep induce frequent low-amplitude CSF fluctuations, contributing to faster CSF dynamics during deep sleep. In contrast, arousal-related brain activities during light sleep produced infrequent large CSF changes. Furthermore, these brain oscillations during light and deep sleep recruited essentially different brain networks, with deep sleep emphasizing memory and homeostatic circuits. Thus, human deep sleep has a unique way of enabling faster CSF dynamics that are distinctive from arousal mechanisms.

Computational Modeling shows Confirmation Bias during Formation and Revision of Self-Beliefs
Self-belief formation and revision strongly depend on social feedback. Accordingly, self-beliefs are subject to (re)evaluation and updating when facing new information. However, it has been shown that self-related learning is rarely purely information-driven. Instead, self-related learning is susceptible to a wide variety of biases. Among them is the confirmation bias, which can render updating insufficient, leading to inaccurate self-beliefs. To better understand these biases, it is important to delineate the effects of initial expectations towards the self and the confidence associated with the self-belief. In a novel behavioral approach, we introduced two learning phases during which participants completed an estimation task and received feedback allegedly related to their performance. In the first session (T1), participants established beliefs about their abilities in this task based on trial-by-trial feedback. In the second session (T2), participants received feedback that differed substantially from the feedback they had received at T1, thus creating the possibility for belief revision. Computational modeling was used to describe initial belief formation and later revision. The results showed confirmatory belief updating behavior on different levels: Participants did not, on average, revise their beliefs at T2, although they were constantly confronted with conflicting evidence. Instead, we observed that initial expectations were linked to biased learning from the received feedback, even at the beginning of the initial belief formation phase. Further, higher confidence in the beliefs was associated with attenuated revision. Together, the results underline the importance of individual priors when delineating learning biases.

Novel iGluSnFR3 variants with improved kinetics and dynamic range for tracking high frequency firing at glutamatergic synapses
The first genetically encoded single fluorescent protein-based glutamate sensor, iGluSnFR opened a new era of imaging neuronal activity at the level of circuits as well as at synapses. With slow off-kinetics, iGluSnFR could only resolve low frequency glutamate release. A binding site variant of iGluSnFR, iGluu with significantly faster off-kinetics, enabled the resolution of high (100 Hz) frequency glutamate release in hippocampal slices at individual CA3-CA1 synapses. Moreover, iGluu revealed impairment of glutamate retrieval in HD mice models pointing to defective glutamate transport. Recently, the iGluSnFR3 generation (SF-Venus-iGluSnFR. v857) has been developed with increased dynamic range and rapid on-kinetics, making it attractive for in vivo imaging. However, similarly to iGluSnFR, glutamate off-kinetics of iGluSnFR3 were predicted to limit it to resolving low frequency release only. We undertook to improve the kinetic properties of iGluSnFR3 for resolving high (100 Hz) frequency glutamate release. We generated and characterized iGlu3fast, an ultrafast decay variant of iGluSnFR3. For iGlu3Fast we obtained a decay rate constant of 340 {+/-} 48 s-1, [~]5-fold faster than iGluSnFR3 at 71 {+/-} 3 s-1, at 20{degrees}C. Furthermore, iGlu3Fast superseded iGluSnFR3 with a 42-fold glutamate-induced fluorescence increase compared to 26 for iGluSnFR3. Thus, with rapid off-kinetics comparable to that of iGluu as well as significantly increased fluorescence dynamic range and preserved rapid on-kinetics, iGlu3fast represents an excellent novel sensor for imaging high frequency glutamate release at all levels of organisation. Two novel variants with superslow off-kinetics are also reported, expanding the range of applications in neurobiology.

Is it me or the train moving? Humans resolve sensory conflicts with a nonlinear feedback mechanism in balance control
AO_SCPLOWBSTRACTC_SCPLOWHumans use multiple sensory systems to estimate body orientation in space. A predominant concept for the underlying multisensory integration (MSI) is the linear summation of weighted inputs from individual sensory systems. The sensory contributions change depending on context and environmental conditions. These changes are typically attributed to reweighting by some higher order mechanism. We provide evidence for a conceptually different mechanism that combines 1) sensory inputs with fixed weights and 2) multisensory corrections, if the reference of the sensory inputs move in space and are therefore unreliable. This reconstruction of the sensory reference frame motion (RFM) allows humans to use vision and automatically counteract erroneous inputs, e.g. when looking at a moving train. The proposed RFM estimator contains a nonlinear dead-zone that blocks corrections at slow velocities. We first demonstrate that this mechanism accounts for changes in sensory contributions. Secondly, we hypothesized that such a nonlinearity would distort balance responses to perturbations in a very specific way. We predicted such distortions in body sway using a balance control model. Experiments using visual scene movements as a specific implementation of RFMs confirmed the predictions. The findings indicate that the central nervous system resolves sensory conflicts by an internal reconstruction of the cause of the conflict. Thus, the mechanism links the concept of causal inference to shifts in sensory contributions, providing a cohesive picture of MSI for the estimation of body orientation in space.

Anatomical Abnormalities Suggest a Compensatory Role of the Cerebellum in Early Parkinson's Disease
Brain atrophy is detected in early Parkinsons disease (PD) and accelerates over the first few years post-diagnosis. This was captured by multiple cross-sectional studies and a few longitudinal studies in early PD. Yet only a longitudinal study with a control group can capture accelerated atrophy in early PD and differentiate it from healthy ageing. Accordingly, we performed a multicohort longitudinal analysis between PD and healthy ageing, examining subcortical regions implicated in PD pathology, including the basal ganglia, thalamus, corpus callosum (CC), and cerebellum. Longitudinal volumetric analysis was performed on 56 early PD patients and 53 matched controls, with scans collected 2-3 years apart. At baseline, the PD group showed a greater volume in the pallidum, thalamus, and cerebellar white matter (WM), suggesting potential compensatory mechanisms in prodromal and early PD. After 2-3 years, accelerated atrophy in PD was observed in the putamen and cerebellar WM. Interestingly, healthy controls - but not PD patients - demonstrated a significant decline in Total Intracranial Volume (TIV), and atrophy in the thalamus and mid-CC. Between-group analysis revealed more severe atrophy in the right striatum and cerebellar WM in PD, and in the mid-posterior CC in controls. Using CEREbellum Segmentation (CERES) for lobule segmentation on the longitudinal PD cohort, we found a significant decline in the WM of non-motor regions in the cerebellum, specifically Crus I and lobule IX. Our results highlight an initial increase in cerebellar WM volume during prodromal PD, followed by significant degeneration over the first few years post-diagnosis.

Creating anatomically-derived, standardized, customizable, and three-dimensional printable head caps for functional neuroimaging
Significance: Consistent and accurate probe placement is a crucial step towards enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. While the selection of head gear is central to these efforts, there does not currently exist a standardized design that can accommodate diverse probe configurations and experimental procedures. Aim: We aim to provide the community with an open-source software pipeline for conveniently creating low-cost, 3-D printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap. Approach: We utilize our advanced 3-D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subject's anatomical scan or an atlas into a 3-D printable head cap model. The 3-D modeling environment of the open-source Blender platform permits advanced mesh processing features to customize the cap. The design process is streamlined into a Blender add-on named "NeuroCaptain". Results: Using the intuitive user interface, we create various head cap models using brain atlases, and share those with the community. The resulting mesh-based head cap designs are readily 3-D printable using off-the-shelf printers and filaments while accurately preserving the head topology and landmarks. Conclusions: The methods developed in this work result in a widely accessible tool for community members to design, customize and fabricate caps that incorporate anatomically derived landmarks. This not only permits personalized head cap designs to achieve improved accuracy, but also offers an open platform for the community to propose standardizable head caps to facilitate multi-centered data collection and sharing.

MorphoCellSorter: An Andrews plot-based sorting approach to rank microglia according to their morphological features
Microglia exhibit diverse morphologies reflecting environmental conditions, maturity or functional states. Thus, morphological characterization provides important information to understand microglial roles and functions. Most recent morphological analysis relies on classifying cells based on morphological parameters. However, this classification is not always biologically relevant, as microglial morphologies constitute a continuum rather than segregated groups. Instead, we propose a new open-source tool, MorphoCellSorter, which assesses microglial morphology by automatically computing morphological criteria, using principal component analysis and Andrews plots to rank cells. MorphoCellSorter accurately ranked cells from various microglia datasets in mice and rats of different age, from in vivo, in vitro and ex vivo models, that were acquired using diverse imaging techniques. This approach allowed for the discrimination of cell populations in various pathophysiological conditions. Finally, MorphoCellSorter offers a versatile, easy and ready-to-use method to evaluate microglial morphological diversity that could easily be generalized to standardize practices across laboratories.