bioRxiv Subject Collection: Neuroscience's Journal

Frontopolar cortex stimulation induces prolonged disruption to counterfactual processing: insights from altered local field potentials
Frontopolar cortex (FPC) is a large, anterior sub-region of prefrontal cortex found in both humans and non-human primates (NHPs) and is thought to support monitoring the value of switching between alternative goals. However, the neuronal mechanisms underlying this function are unclear. Here we used multielectrode arrays to record the local field potentials (LFPs) in the FPC of two macaques performing a Wisconsin Card Sorting Test analogue and found that bursts of gamma and beta in FPC tracked counterfactual not current rule value. Moreover, we show that brief high-frequency microstimulation to a single trial causally affects both LFP activity in FPC, as well as rule-guided decision-making across successive trials. Following stimulation of FPC we observed reduced exploration of the counterfactual rule pre-rule-change, as well as a delayed adaptation to the newly relevant following post-rule-change. A similar, multi-trial time-course disturbance to beta and gamma activity within FPC was also induced following single-trial microstimulation. These findings conclusively link neuronal activity in FPC with behavioural monitoring of the value of counterfactual rules and provide neural mechanistic insights into how FPC supports rule-based decision-making.

Reading Acquisition Drives Linguistic Cross-Modal Convergence in The Left Ventral Occipitotemporal Cortex
Reading acquisition requires linking visual symbols with speech sounds, leading to the development of neural sensitivity to print. While prior studies have shown the importance of cross-modal integration in spoken language areas, the higher-level visual area (lvOT) processing printed words remained more context-dependent. This longitudinal study investigated whether the lvOT undergoes cross-modal reorganization to facilitate print-speech integration during reading development and how these changes relate to reading skills. We followed children over two years, beginning at the onset of formal reading instruction. We examine lvOT responses to print-specific, speech-specific, and its convergence at whole-brain, region of interest and voxel-based levels. Results showed that with reading experience, the Initial print-specific responses in the lvOT are transformed into responses to both print and speech input. This transformation positively correlates with reading skills, especially in early acquisition stages. These findings suggest that reading acquisition drives cross-modal reorganization within the lvOT, enabling the area to integrate print and speech. They shed light on the broader neural mechanisms supporting reading development.

Adolescent-like Processing of Behaviorally Salient Cues in Sensory and Prefrontal Cortices of Adult Preterm-Born Mice
Preterm birth is a leading risk factor for atypicalities in cognitive and sensory processing, but it is unclear how prematurity impacts circuits that support these functions. To address this, we trained adult mice born a day early (preterm mice) on a visual discrimination task and found that they commit more errors and fail to achieve high levels of performance. Using in vivo electrophysiology, we found that the neurons in the primary visual cortex (V1) and the V1-projecting prefrontal anterior cingulate cortex (ACC) are hyper-responsive to the reward, reminiscent of cue processing in adolescence. Moreover, the non-rewarded cue fails to robustly activate the V1 and V1-projecting ACC neurons during error trials, in contrast to prefrontal fast-spiking (FS) interneurons which show elevated error-related activity, suggesting that preterm birth impairs the function of prefrontal circuits for error monitoring. Finally, environmental enrichment, a well-established paradigm that promotes sensory maturation, failed to improve the performance of preterm mice, suggesting limited capacity of early interventions for reducing the risk of cognitive deficits after preterm birth. Altogether, our study for the first time identifies potential circuit mechanisms of cognitive atypicalities in the preterm population and highlights the vulnerability of prefrontal circuits to advanced onset of extrauterine experience.

Variation in the geometry of concept manifolds acrosshuman visual cortex
Brain activity patterns in high-level visual cortex support accurate linear classification of visual concepts (e.g., objects or scenes). It has long been appreciated that the accuracy of linear classification in any brain area depends on the geometry of its concept manifolds---sets of brain activity patterns that encode images of a concept. However, it is unclear how the geometry of concept manifolds differs between regions of visual cortex that support accurate classification and those that don't, or how it differs between visual cortex and deep neural networks (DNNs). We estimated geometric properties of concept manifolds that, per a recent theory, directly determine the accuracy of simple "few-shot" linear classifiers. Using a large fMRI dataset, we show that variation in classification accuracy across human visual cortex is driven by a variation in a single geometric property: the distance between manifold centers ("geometric Signal"). In contrast, variation in classification accuracy across most DNN layers is driven by an increase in the effective number of manifold dimensions ("Dimensionality"). Despite this difference in the geometric properties that affect few-shot classification performance in the brain and DNNs, we find that Signal and Dimensionality are strongly, negatively correlated: when Signal increases across brain regions or DNN layers, Dimensionality decreases, and vice versa. We conclude that visual cortex and DNNs deploy different geometric strategies for accurate linear classification of concepts, even though both are subject to the same constraint.

CalliCog: an open-source cognitive neuroscience toolkit for freely behaving nonhuman primates
Nonhuman primates (NHPs) are pivotal for unlocking the complexities of human cognition, yet traditional cognitive studies remain constrained to specialized laboratories. To revolutionize this paradigm, we present CalliCog: an open-source, scalable in-cage platform tailored for freely behaving experiments in small primate species such as the common marmoset (Callithrix jacchus). CalliCog includes modular operant chambers that operate autonomously and integrate seamlessly with home cages, eliminating human intervention. Our results showcase the power of CalliCog to train experimentally naive marmosets in touchscreen-based cognitive tasks. Remarkably, across two independent facilities, marmosets achieved touchscreen proficiency within two weeks and successfully completed tasks probing behavioral flexibility and working memory. Moreover, CalliCog enabled precise synchronization of behavioral data with electrocorticography (ECoG) recordings from freely moving animals, opening new frontiers for neurobehavioral research. By making CalliCog openly accessible, we aim to democratize cognitive experimentation with small NHPs, narrowing the translational gap between preclinical models and human cognition.

Quantifying information stored in synaptic connections rather than in firing patterns of neural networks
A cornerstone of our understanding of both biological and artificial neural networks is that they store information in the strengths of connections among the constituent neurons. However, in contrast to the well-established theory for quantifying information encoded by the firing patterns of neural networks, little is known about quantifying information encoded by its synaptic connections. Here, we develop a theoretical framework using continuous Hopfield networks as an exemplar for associative neural networks, and data that follow mixtures of broadly applicable multivariate log-normal distributions. Specifically, we analytically derive the Shannon mutual information between the data and singletons, pairs, triplets, quadruplets, and arbitrary n-tuples of synaptic connections within the network. Our framework corroborates well-established insights about storage capacity of, and distributed coding by, neural firing patterns. Strikingly, it discovers synergistic interactions among synapses, revealing that the information encoded jointly by all the synapses exceeds the 'sum of its parts'. Taken together, this study introduces an interpretable framework for quantitatively understanding information storage in neural networks, one that illustrates the duality of synaptic connectivity and neural population activity in learning and memory.

Behavioral and Neural Correlates of Temperament Traits: Insights from Temperament and Character Inventory and fMRI-Based Choice Tasks
A cognitive conflict that is negatively arousing and results in a divergence in preference attitudes toward the chosen and rejected alternatives occurs when individuals are compelled to choose between alternatives that are similarly preferable. This phenomenon, which is frequently referred to as cognitive dissonance, is of interest in the fields of decision neuroscience and psychology. This study examines the behavioral and neural underpinnings of Cloninger's temperament traits Novelty Seeking (NS), Harm Avoidance (HA), Reward Dependence (RD), and Persistence (PS) in a decision-making context. Functional magnetic resonance imaging (fMRI) and a modified free-choice paradigm were used to formalize the effect of Cloninger temperaments on cognitive conflict induced by choice. Behavioral analysis revealed significant individual differences across the four TCI dimensions, highlighting distinct variability in participants' responses. Imaging data showed that participants with the highest and lowest scores in each temperament trait exhibited unique brain activation patterns during difficult and easy decision tasks. Notably, novelty-seeking was linked to heightened activation in brain regions associated with exploration and cognitive flexibility, while harm avoidance was associated with emotional processing and conflict detection. These findings provide deeper insights into how personality traits influence both behavior and neural responses during cognitive dissonance and decision-making tasks, offering implications for understanding individual differences in decision-related behaviors. The results of this study confirm the effect of temperaments on the degree of perceived dissonance of people, which can be used in many areas such as consumer behavior in marketing. The reason for this is the hesitancy of customers after purchasing the products.

Modeling speech adaptation to altered sensory feedback through continuous learning of internal sensory predictions
The paper presents a version of an optimization-based model of speech production that reproduces key acoustic and articulatory features of motorsensory adaptation to altered sensory feedback. In the presented approach, the mechanism of motorsensory adaptation is based on regular updates, based on the sensory feedback perceived by the speaker, of two of the speakers' internal models used for computing (near)-optimal articulation. These internal models, modeled as separate Artificial Neural Networks, are 1) a model that predicts the acoustic consequences of motor (articulatory commands) and 2) a model that predicts the somatosensory sensations from given motor commands. The paper presents simulations of adaptation experiments that successfully reproduce key acoustic and articulatory features of motorsensory adaptation of speech to altered sensory feedback. These include gradual and incomplete motorsensory adaptation when the auditory (or the somatosensory) feedback is suddenly altered (F1-shifted for the altered auditory feedback, forced jaw movement for altered somatosensory feedback). The presented simulations also show that the rate and magnitude of adaptation behavior depend on a small number of parameters. Variation in the values of these parameters can potentially explain inter-speaker differences in terms of adaptation behavior, including sensory preference.

Shaping the developing homunculus: the roles of deprivation and compensatory behaviour in sensory remapping
Some of the most dramatic examples of neuroplasticity in the human brain follow congenital sensory deprivation, though we have limited understanding of the plasticity mechanisms driving such large-scale remapping. Hand loss due to congenital limb differences (CLD) offers a unique temporal dissociation of developmental neuroplasticity mechanisms: While sensory deprivation is congenital, compensatory motor behaviours develop progressively across childhood. Using paediatric neuroimaging and semi-ecological behavioural analysis in children (5-7 years old) and adults (>25 years old) with unilateral upper-limb CLD, we studied deprivation- and use-dependent plasticity in the deprived primary somatosensory cortex and beyond. We reveal that global remapping, encompassing the entire sensory homunculus, is established early and maintained in adulthood. We demonstrate that deprivation-driven homeostatic plasticity can drive this global remapping, with Hebbian-based compensatory learning further contributing to inter-individual differences both in childhood and adulthood. Our findings emphasise the early establishment and stability of cortical maps, despite extensive daily-life behavioural adaptation.

Cortical assembloids support the development of fast-spiking human PVALB+ cortical interneurons and uncover schizophrenia-associated defects
Disruption of fast-spiking, parvalbumin positive (PVALB+) cortical interneurons is implicated in the pathogenesis of schizophrenia. However, how and when these defects emerge during development is not well understood. The protracted maturation of these cells during postnatal development has made their derivation from human pluripotent stem cells (hPSCs) extremely difficult, precluding studies on their role in neuropsychiatric diseases using hPSC-based disease models. Furthermore, the complex genetics of schizophrenia makes genetic background a confounding variable for studies using patient-specific hiPSC lines. Here we present a cortical assembloid system that supports the development of fast-spiking cortical interneurons which co-express LHX6 and PVALB, match the molecular profiles of primary PVALB+ interneurons by scRNAseq and display their distinctive electrophysiological features. The presence of PVALB+ interneurons in assembloids was correlated with gamma-band oscillatory rhythms at the network-level. We next characterized cortical interneuron development in a series of CRISPR-generated isogenic structural variants strongly associated with schizophrenia risk and identified variant-specific phenotypes both in cortical interneuron migration and in the molecular profile of PVALB+ cortical interneurons. These findings reveal plausible mechanisms on how disruption of cortical interneuron development may impact schizophrenia risk and provides an exciting human experimental platform to facilitate the study of authentic, fast-spiking cortical interneurons.

Metacognitive Introspection Alters the Dynamics of Pre-Decisional Neural Evidence Accumulation
Metacognitive introspection refers to the capacity to monitor and evaluate one's own performance, such as when expressing confidence in one's choice. In the context of perceptual decision making, current computational models of confidence typically assume that confidence is computed after the evidence collection process underlying the initial choice has unfolded. This account predicts that the act of introspection required in order to provide a confidence judgment about one's decision should have little impact on the dynamics of evidence accumulation leading up to that decision. We tested this by examining whether a neural proxy for perceptual evidence accumulation (the central-parietal positivity; CPP) exhibits different dynamics when participants do or do not rate confidence in their perceptual decisions. Behavioral results showed that confidence introspection increased decision accuracy and response time. Importantly, confidence introspection also resulted in a steeper CPP slope beginning shortly after (~250 ms) decision evidence was available. We further observed an effector-specific neural signal of confidence evidence which both built up prior to the perceptual choice and which was predictive of the amount of confidence subsequently expressed by the participants. Our results indicate that introspection can alter the dynamics of perceptual evidence accumulation, possibly by acting on the gain of evidence accumulation, and that motor-related confidence signals emerge in tandem with pre-decisional evidence accumulation signals rather than post-choice.

Behaviorally-relevant features of observed actions dominate cortical representational geometry in natural vision
We effortlessly extract behaviorally relevant information from dynamic visual input in order to understand the actions of others. In the current study, we develop and test a number of models to better understand the neural representational geometries supporting action understanding. Using fMRI, we measured brain activity as participants viewed a diverse set of 90 different video clips depicting social and nonsocial actions in real-world contexts. We developed five behavioral models using arrangement tasks: two models reflecting behavioral judgments of the purpose (transitivity) and the social content (sociality) of the actions depicted in the video stimuli; and three models reflecting behavioral judgments of the visual content (people, objects, and scene) depicted in still frames of the stimuli. We evaluated how well these models predict neural representational geometry and tested them against semantic models based on verb and nonverb embeddings and visual models based on gaze and motion energy. Our results revealed that behavioral judgments of similarity better reflect neural representational geometry than semantic or visual models throughout much of cortex. The sociality and transitivity models in particular captured a large portion of unique variance throughout the action observation network, extending into regions not typically associated with action perception, like ventral temporal cortex. Overall, our findings expand the action observation network and indicate that the social content and purpose of observed actions are predominant in cortical representation.

Anatomy, histology and ultrastructure of the adult human olfactory peduncle: blood vessel and corpora amylacea assessment
The mammalian olfactory system is responsible for processing volatile chemical stimuli and is composed of several structures including the olfactory epithelium, olfactory bulb, olfactory peduncle (OP), and olfactory cortices. Despite the critical role played by the OP in the transport of olfactory information it has remained understudied. In this work, optical, confocal, and electron microscopy were employed to examine the anatomy, histology, and ultrastructure of six human OP specimens (ages 37,84 years). Three concentric layers were identified in coronal sections: the external layer (EL), the axonal layer (AL), and the internal layer (IL). Immunohistochemistry revealed the distribution of neurons and glial cells throughout the OP. Two neuronal morphologies were observed: granule cells and larger pyramidal cells, the latter associated with projection neurons of the anterior olfactory nucleus. Astrocytes were uniformly distributed with a more radial morphology in the EL. Oligodendrocytes were mainly located in the AL. Blood vessels (BVs) were evenly distributed along the OP, with a mean luminal area of 82.9 um2 and a density of 1.26 %, with a significant increase in the IL. Corpora amylacea were abundant, with an average size of 49.3 um2 and a density of 3.23 %. CA clustered near BVs, particularly at tissue edges, with both size and density increasing with age. Notably, CA showed strong associations with astrocytes. This study provides the first detailed qualitative and quantitative data on the internal organization of the human OP, which may contribute to a better understanding of the pathophysiology of some neuropathological disorders.

How sturdy is your memory palace? Reliable room representations predict subsequent reinstatement of placed objects
Our autobiographical experiences typically occur within the context of familiar spatial locations. When we encode these experiences into memory, we can use our spatial map of the world to help organize these memories and later retrieve their episodic details. However, it is still not well understood what psychological and neural factors make spatial contexts an effective scaffold for storing and accessing memories. We hypothesized that spatial locations with distinctive and stable neural representations would best support the encoding and robust reinstatement of new episodic memories. We developed a novel paradigm that allowed us to quantify the within-participant reliability of a spatial context ("room reliability") prior to memory encoding, which could then be used to predict the degree of successful re-activation of item memories. To do this, we constructed a virtual reality (VR) "memory palace", a custom-built environment made up of 23 distinct rooms that participants explored using a head-mounted VR display. The day after learning the layout of the environment, participants underwent whole-brain fMRI while being presented with videos of the rooms in the memory palace, allowing us to measure the reliability of the neural activity pattern associated with each room. Participants were taken back to VR and asked to memorize the locations of 23 distinct objects randomly placed within each of the 23 rooms, and then returned to the scanner as they recalled the objects and the rooms in which they appeared. We found that our room reliability measure was predictive of object reinstatement across cortex, and further showed that this was driven not only by the group-level reliability of a room across participants, but also the idiosyncratic reliability of rooms within each participant. Together, these results showcase how the quality of the neural representation of a spatial context can be quantified and used to 'audit' its utility as a memory scaffold for future experiences.

Neural Mechanisms of Intersensory Switching: Evidence for Delayed Sensory Processing and Increased Cognitive Effort
Intersensory switching (IS), the ability to shift attention between different sensory systems, is essential for cognitive flexibility, yet leads to slower responses compared to repeating the same sensory modality. The underlying neural mechanisms of IS remain largely unknown. In this study, high-density EEG was used to investigate these mechanisms in healthy adults (n=53) performing a speeded reaction time (RT) task involving visual and auditory stimuli. Trials were categorized as Repeat (same preceding modality) or Switch (different preceding modality). Switch trials showed slower RTs and delayed sensory responses (N1 and P2 components). Furthermore, across both Repeat and Switch trials, RT correlated with the latency of these neural responses. Additionally, lower alpha-band inter-trial phase coherence (ITPC) in primary sensory regions was noted for Switch compared to Repeat trials, suggesting reduced efficiency of sensory processing. Greater induced theta activity over fronto-central scalp regions in Switch trials suggested increased cognitive control demands, potentially involving the anterior cingulate cortex (ACC). These findings reveal that IS is characterized by delayed sensory processing and heightened cognitive load, supporting a model where prior stimulus primes the sensory cortex for faster processing in Repeat trials, while Switch trials demand more cognitive resources for adjustment. The similarity of effects across both auditory and visual sensory modalities suggests that IS effects represent core features of sensory processing, potentially reflecting a fundamental, modality-independent mechanism of attentional switching across sensory domains.

Neurogenetic evidence for oscillatory behavior of Lgr3-positive growth control interneurons in Drosophila
The ability of animals to achieve a species-specific size and proportion even in the face of developmental or environmental perturbations is termed developmental stability. In Drosophila, the relaxin/insulin-like peptide 8 (Dilp8) mediates interorgan growth coordination during larval development acting upstream of the neuronal relaxin-like Leucine-rich repeat-containing G protein-coupled receptor (Lgr3). Previous reports have led to a model where Dilp8-dependent Lgr3 activation in two bilateral brain interneurons termed pars intercerebralis Lgr3-positive/growth-coordinating Lgr3 (PIL/GCL) neurons leads to their depolarization, which then triggers a neuroendocrine cascade that promotes developmental stability by delaying the larval-to-pupal transition and reducing organ growth concomitantly. However, many fundamental aspects of this model remained to be experimentally proven, most notably the specific requirement of Lgr3 and depolarization in PIL/GCL neurons for developmental stability. Here, we confirm the first part of the model regarding the specific requirement of Lgr3 in PIL/GCL neurons using improved genetic drivers, but, in contrast to the model predictions, we find that both hyper- and depolarized states of these neurons are required for their developmental delay-promoting activity in response to Dilp8. The simplest explanation for this finding is that Lgr3 activation by Dilp8 triggers oscillatory activity of PIL/GCL neurons, and that this is required for the Dilp8-dependent developmental delay. Whether or not such oscillatory behavior would arise from intrinsically pacemaker activity or from network connectivity properties such as feedback inhibition remains to be defined, although we present evidence that both could be involved. Namely, PIL/GCL neurons are positive for Cyclin A, which has been linked with sleep time coordination in adult postmitotic neurons. On the other hand, the neuroanatomy of PIL/GCL neurons is consistent with reciprocally-innervating loop-forming neurons, a common architecture in oscillating circuits and central pattern generators. Finally, we demonstrate through clonal analyses that PIL/GCL neurons represent two distinct neuronal types--a local and a projection neuron--instead of a homogeneous neuronal population as previously thought, revealing a new complexity layer in the developmental stability circuit. Our findings highlight the importance of cell-type specific neurogenetic manipulation, detailed neuroanatomical characterization, and reveal a critical and unanticipatedly complex role for PIL/GCL neurons in the Dilp8-dependent developmental stability pathway.

Procrustes Alignment in Individual-level Analyses of Functional Gradients
Functional connectivity (FC) gradients provide valuable insights into individual differences in brain organization, yet aligning these gradients across individuals poses challenges. Procrustes alignment is often employed to standardize gradients across multiple subjects, but the choice of the number of gradients used in alignment introduces complexities that may impact individual-level analyses. In this study, we systematically investigate the impact of varying gradient counts in Procrustes alignment on the principal FC gradient, using data from four resting state fMRI datasets, including the Human Connectome Project (HCP-YA), Amsterdam Open MRI Collection (AOMIC) PIOP1 and PIOP2, and Cambridge Centre for Ageing and Neuroscience (Cam-CAN). We find that increasing the number of gradients used in alignment enhances identification accuracy but can reduce differential identifiability, as additional gradients risk introducing nuisance signals such as motion back into the principal gradient. To further probe these effects, machine learning to predict fluid intelligence and age, and a motion prediction analysis, revealing that higher alignment gradient counts may leak information from lower gradients into the principal gradient for individual-level analyses. These findings highlight the trade-off between alignment precision and the potential reintroduction of noise.

A comparative study of rigid-body registration algorithms for the alignment of longitudinal structural MRI of the brain
Longitudinal structural MRI (sMRI) may be used to characterize brain morphological changes over time. A key requirement for this approach is accurate rigid-body alignment of longitudinal sMRI. We have recently developed the automatic temporal registration algorithm (ATRA) for this purpose. ATRA is a landmark-based approach capable of registering dozens of serial sMRI simultaneously in an unbiased manner. The aim of the research presented in this paper was to evaluate the accuracy and inverse-consistency of ATRA in comparison to three commonly used sMRI alignment methods: FSL, FreeSurfer, and ANTS. In the absence of a ground truth, it is only possible to quantitatively determine the degree of discrepancy between two algorithms. We propose that if the discrepancy exceeds a certain threshold, the relative accuracy of the two algorithms could be determined visually. We computed the discrepancy between ATRA and each of the three other methods for the alignment of 150 pairs of sMRI taken roughly one year apart. We visually rated the accuracy of alignments in cases where the discrepancy was greater than .5 mm while the rater was agnostic to the registration method. In those instances, ATRA was considered more accurate than FSL in 46 out of 48 cases, more accurate than FreeSurfer in 6 out of 7 cases, and more accurate than ANTS in all 6 cases. ATRA was also the most inverse-consistent method. In addition to being capable of performing unbiased group-wise registration, ATRA is the most accurate algorithm in comparison to several commonly used rigid-body alignment methods.

Impaired spatial coding and neuronal hyperactivity in the medial entorhinal cortex of APP NL-G-F mice
The progressive accumulation of amyloid beta (A{beta}) pathology in the brain has been associated with aberrant neuronal network activity and poor cognitive performance in preclinical mouse models of Alzheimer's disease (AD). Presently, our understanding of the mechanisms driving pathology-associated neuronal dysfunction and impaired information processing in the brain remains incomplete. Here, we assessed the impact of advanced A{beta} pathology on spatial information processing in the medial entorhinal cortex (MEC) of 18-month App NL-G-F/NL-G-F knock-in (APP KI) mice as they explored contextually novel and familiar open field arenas in a two-day, four-session recording paradigm. We tracked single unit firing activity across all sessions and found that spatial information scores were decreased in MEC neurons from APP KI mice versus those in age-matched C57BL/6J controls. MEC single unit spatial representations were also impacted in APP KI mice. Border cell firing preferences were unstable across sessions and spatial periodicity in putative grid cells was disrupted. In contrast, MEC border cells and grid cells in Control mice were intact and stable across sessions. We then quantified the stability of MEC spatial maps across sessions by utilizing a metric based on the Earth Mover's Distance (EMD). We found evidence for increased instability in spatially-tuned APP KI MEC neurons versus Controls when mice were re-exposed to familiar environments and exposed to a novel environment. Additionally, spatial decoding analysis of MEC single units revealed deficits in position and speed coding in APP KI mice in all session comparisons. Finally, MEC single unit analysis revealed a mild hyperactive phenotype in APP KI mice that appeared to be driven by narrow-spiking units (putative interneurons). These findings tie A{beta}-associated dysregulation in neuronal firing to disruptions in spatial information processing that may underlie certain cognitive deficits associated with AD.

Cortical neural activity during responses to mechanical perturbation: Effects of hand preference and hand used
Handedness, as measured by self-reported hand preference, is an important feature of human behavioral lateralization that has often been associated with hemispheric specialization. We examined the extent to which hand preference and whether the dominant hand is used or not influence the motor and neural response during voluntary unimanual corrective actions. The experimental task involved controlling a robotic manipulandum to move a cursor from a center start point to a target presented above or below the start. In some trials, a mechanical perturbation of the hand was randomly applied by the robot either consistent or against the target direction, while electroencephalography (EEG) was recorded. Twelve left-handers and ten right-handers completed the experiment. Left-handed individuals had a greater negative peak in the frontal event-related potential (ERP) than right-handed participants during the initial response phase (N150) than right-handed individuals. Furthermore, left-handed individuals showed more symmetrical ERP distributions between two hemispheres than right-handed individuals in the frontal and parietal regions during the late voluntary response phase (P390). To the best of our knowledge, this is the first evidence that demonstrates the differences in the cortical control of voluntary corrective actions between left-handers and right-handers.

Microglia promote neurodegeneration and hyperkatifeia during withdrawal and prolonged abstinence from chronic binge alcohol
Proinflammatory microglial activation and hyperkatifeia during withdrawal are key features or Alcohol Use Disorder (AUD) as well as in rodent models of binge alcohol. However, it is unclear the role microglia play in the development of AUD behavioral phenotypes, particularly negative affect or hyperkatifeia. We hypothesized proinflammatory microglia promote neuronal death and hyperkatifeia during withdrawal and prolonged abstinence. METHODS: Inflammatory and affective responses were measured in adult mice 24h or 4 weeks after 4 or 10 daily binge ethanol exposures (5g/kg/d, i.g.). RT-PCR was used to measure expression of pro-inflammatory genes. FosB immunohistochemistry was measured in stress circuitry central amygdala (CeA), BNST, and infralimbic cortex (IL) as a proxy for neuronal activity. Behavioral testing was performed in additional cohorts to measure anxiety-like behavior (center time in the open field), hyperarousal (acoustic startle), and inflexible negative affect (conditioned fear memory with extinction). To determine the role of proinflammatory microglia, Gi DREADDs were activated in microglia (CX3CR1.CreERT2.hm4di+/-EtOH +/- CNO). RESULTS: Binge ethanol increased pro-inflammatory gene activation both 24h after EtOH and lasting weeks into withdrawal (type I IFNs). Ten ethanol binges increased FosB in stress circuitry during withdrawal while simultaneously reducing BDNF persistently in the dBNST and CeA. Ethanol-treated mice spent less time in the center of the open field (anxiety-like behavior), had increased magnitude of acoustic startle reflex (hyperarousal) during withdrawal with reduced extinction of conditioned fear memory (PTSD phenotype) 4-5 weeks into abstinence. Gi-DREADD inhibition of microglia during alcohol treatment blocked persistent increases in proinflammatory cytokines, prevented ethanol-induced neuronal death (TUNEL), and prevented ethanol-induced hyperkatifeia including anxiety-like behavior and persistent conditioned fear memory. CONCLUSION: These data find a causative role for microglia in the development of negative affect behaviors during alcohol withdrawal. The prevention of these pro-inflammatory effects and behaviors by microglial inhibition reveals the integral role microglia play in the acute and lasting effects of ethanol on behavior in AUD pathogenesis.

A domain-general process for theta-rhythmic sampling of either environmental information or internally stored information
Many everyday tasks, such as shopping for groceries, require the sampling of both environmental information and internally stored information. Selective attention involves the preferential processing and sampling of behaviorally important information from the external environment, while working memory involves the preferential processing and sampling of behaviorally important, internally stored information. These essential cognitive processes share neural resources within a large-scale network that includes frontal, parietal, and sensory cortices, and these shared neural resources can lead to between-domain interactions. Previous research has linked external sampling during selective attention and internal sampling during working memory to theta-rhythmic (3-8 Hz) neural activity in higher-order (e.g., frontal cortices) and sensory regions (e.g., visual cortices). Such theta-rhythmic neural activity might help to resolve the competition for shared neural resources by isolating neural activity associated with different functions over time. Here, we used EEG and a dual-task design (i.e., a task that required both external and internal sampling) to directly compare (i) theta-dependent fluctuations in behavioral performance during external sampling with (ii) theta-dependent fluctuations in behavioral performance during internal sampling. Our findings are consistent with a domain-general, theta-rhythmic process for sampling either external information or internal information. We further demonstrate that interactions between external and internal information (specifically, when to-be-detected information matches to-be-remembered information) are not dependent on theta-band activity (i.e., theta phase). Given that these theta-independent "match effects" occur during early processing stages (peaking at 75 ms), we propose that theta-rhythmic sampling modulates external and internal information during later processing stages.

Processing negative words in pun-humor: dynamic representation of mixed feelings blending amusement and negativity
This study aims to investigate whether amusement and negativity counteract each other or are jointly intensified during the online processing of negative keywords in pun-humor sentences, and how mixed feelings blending these two emotional states are dynamically experienced over time. Participants read three types of sentences that included the same negative words as keywords: pun-humor (negative words can generate humorous effects by resonating with the context), non-humor (negative words seamlessly align with the context), and nonsensical (negative words cannot be integrated with the context) sentences. The behavioral ratings revealed that compared with non-humor and nonsensical sentences, pun-humor sentences evoked stronger amusement and intensified negative feelings, indicating that pun-humor sentences containing negative keywords can effectively elicit mixed feelings that encompass conflicting emotional states. The ERP results showed that the N400 (300-500 ms) elicited by negative words in pun-humor sentences was comparable to that in non-humor sentences, suggesting that negative words were connected contextually in both sentence types. Besides, negative words elicited greater LPC (600-800 ms) in pun-humor sentences than in non-humor and nonsensical sentences, suggesting that pun-humor sentences require additional semantic processing and more elaborate emotional processing. Moreover, the representational similarity analysis (RSA) results revealed that in pun-humor sentences, the representation of negativity persisted for a longer duration, and it occurred and peaked earlier than that of amusement. This implies that within the dynamic representation of mixed feelings, negativity was experienced first, whereas amusement was subsequently felt within a brief period, during which negativity was not offset but rather continued to be represented over a longer time span, resulting in the simultaneous presence of both amused and negative feelings. Taken together, these findings show that mixed feelings elicited during the online processing of negative keywords in pun-humor sentences can be dynamically experienced in a way that aligns with the highly simultaneous pattern and that negativity can be experienced before amusement during the dynamic representation of mixed feelings.

Functional Dichotomy of Orbitofrontal Cortex and Anterior Cingulate Cortex Subregions in Decision-Making and Brain-Body Regulation
Mood disorders are associated with complex disruptions in brain networks, including those associated with the orbitofrontal cortex (OFC) and pregenual anterior cingulate cortex (pACC). The functional contribution of the caudal OFC (cOFC) has remained largely unexplored. We investigated the functions of the cOFC and pACC in macaques performing an approach-avoidance task by the combination of multimodal recordings and electrical microstimulation (EMS) of the cOFC. We assessed neural, autonomic and behavioral responses. We found the cOFC to be sensitive to both positive and negative stimuli, whereas the pACC was singificantly more active during aversive outcomes. EMS of the cOFC increased avoidance behavior, suggesting a causal role for the OFC subdivision in cost-benefit decision-making. Physiological measurements were positively correlated with behavioral patterns, emphasizing body-brain synchronization during emotionally significant decision-making. We suggest that the cOFC contributes to inducing pessimistic states, thereby making its dysfunction a potential contributor to the etiology of mood disorders.

Selective Inhibition of Cytosolic PARylation via PARG99: A Targeted Approach for Mitigating FUS-associated Neurodegeneration
Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) are characterized by complex etiologies, often involving disruptions in functions of RNA/DNA binding proteins (RDBPs) such as FUS and TDP-43. The cytosolic mislocalization and aggregation of these proteins are linked to accumulation of unresolved stress granules (SGs), which exacerbate the disease progression. Poly-ADP-ribose polymerase (PARP)-mediated PARylation plays a critical role in this pathological cascade, making it a potential target for intervention. However, conventional PARP inhibitors are limited by their detrimental effects on DNA repair pathways, which are already compromised in ALS. To address this limitation, we investigated a strategy focused on targeting the cytosolic compartment by expressing the cytosol-specific, natural PAR-glycohydrolase (PARG) isoform, PARG99. Using ALS patient derived FUS mutant induced pluripotent cells (iPSCs) and differentiated neurons, we observed elevated levels of FUS in insoluble fractions in mutant cells compared to mutation-corrected isogenic lines. The insoluble FUS as well as TDP-43 levels increased further in sodium arsenite-treated or oxidatively stressed cells, correlating with accumulation of unresolved SGs. Notably, both PARG99 and PARP inhibitors reduced SG formation and insoluble FUS levels, however, PARG99 treated cells exhibited significantly lower DNA damage markers and improved viability under oxidative and arsenite stress. This study highlights the potential of PARG99 as a cytosol-specific intervention to mitigate FUS-associated toxicity while preserving critical nuclear DNA repair mechanisms, offering a promising strategy for addressing the underlying pathology of ALS and potentially other SG-associated neurodegenerative diseases.

Uncovering the electrical synapse proteome in retinal neurons via in vivo proximity labeling
Through decades of research, we have gained a comprehensive understanding of the protein complexes underlying function and regulation of chemical synapses in the nervous system. Despite the identification of key molecules such as ZO-1 or CaMKII, we currently lack a similar level of insight into the electrical synapse proteome. With the advancement of BioID as a tool for in vivo proteomics, it has become possible to identify complex interactomes of a given protein of interest by combining enzymatic biotinylation with subsequent streptavidin affinity capture. In the present study, we applied different BioID strategies to screen the interactomes of Connexin 36 (mouse) the major neuronal connexin and its zebrafish orthologue Cx35b in retinal neurons. For in vivo proximity labeling in mice, we took advantage of the Cx36-EGFP strain and expressed a GFP-nanobody-TurboID fusion construct selectively in AII amacrine cells. For in vivo BioID in zebrafish, we generated a transgenic line expressing a Cx35b-TurboID fusion under control of the Cx35b promoter. Both two strategies allowed us to capture a plethora of molecules that were associated with electrical synapses and showed a high degree of evolutionary conservation in the proteomes of both species. Besides known interactors of Cx36 such as ZO-1 and ZO-2 we have identified more than 50 new proteins, such as scaffold proteins, adhesion molecules and regulators of the cytoskeleton. We further determined the subcellular localization of these proteins in AII amacrine and tested potential binding interactions with Cx36. Of note, we identified signal induced proliferation associated 1 like 3 (SIPA1L3), a protein that has been implicated in cell junction formation and cell polarity as a new scaffold of electrical synapses. Interestingly, SIPA1L3 was able to interact with ZO-1, ZO-2 and Cx36, suggesting a pivotal role in electrical synapse function. In summary, our study provides a first detailed view of the electrical synapse proteome in retinal neurons.

Polarized ATP synthase in synaptic mitochondria induced by learning and plasticity signals
MINFLUX represents a state-of-the-art single-molecule localization microscopy technology that surpasses the conventional diffraction limit, enabling the visualization and analysis of nanostructures with exceptional precision. Despite its potential, the utilization of MINFLUX has been primarily confined to in vitro cultured cell environments. In this research, we have refined the sample preparation protocols to facilitate 3D MINFLUX imaging in fixed brain tissue sections, focusing on the mitochondrial distribution within dendritic spines and engram cells of the dentate gyrus. Probing single molecules in vivo reveals an interesting finding: the reorganization of mitochondrial inner membrane proteins during synaptic plasticity within dendritic spines of engram cells. Utilizing 3D MINFLUX nanoscopy, we identified a significant redistribution of -F1-ATP synthase, which correlates with learning related activities. This redistribution implies a pivotal function for polarized ATP synthesis in the vicinity of the postsynaptic zone, which may modulate both short-term and long-term synaptic modifications, thereby influencing synaptic plasticity and memory consolidation. Furthermore, dual-color 3D MINFLUX imaging has uncovered distinct patterns of mitochondrial reorganization involving both the inner and outer membranes within dendritic spines. These patterns, induced by plasticity signals, persist for up to 12 hours in neuronal cultures. This distinction highlights the presence of distinct regulatory mechanisms governing mitochondrial proteins during synaptic plasticity. These results offer new insights into the molecular mechanisms underlying synaptic plasticity and underscore the transformative potential of 3D MINFLUX imaging for studying neuronal processes in the brain.

PyRID: A Brownian dynamics simulator for reacting and interacting particles written in Python
Recent technological developments in molecular biology led to large data sets providing new insights into the molecular organisation of cells. To fully exploit their potential, these developments have to be complemented by computer simulations that allow to gain in-depth understanding on molecular principles. We developed the Python-based, reaction-diffusion simulator PyRID, integrating many features for the efficient simulation of molecular biological systems. Amongst others, PyRID is capable of simulating unimolecular and bimolecular reactions as well as pairinteractions to assess the dynamics resulting from individual interacting proteins to polydisperse substrates consisting of many different molecules. Furthermore, PyRID supports mesh-based compartments and surface diffusion of particles, enabling analyses of the interaction between (trans-)membrane proteins with intra- and extracellular proteins. PyRID is written entirely in Python, which is a programming language being known for its readability and easy accessibility, such that the scientific community can easily extend PyRID to its current and future needs.

NaviNIBS: a comprehensive and open-source software toolbox for neuronavigated noninvasive brain stimulation.
Image-guided positioning, or neuronavigation, is critical for precise targeting of transcranial magnetic stimulation (TMS) and other noninvasive brain stimulation. However, existing commercial systems have limitations in flexibility and extensibility for research applications. We present new open-source software for neuronavigated non-invasive brain stimulation (NaviNIBS) that provides comprehensive functionality for TMS experiments. NaviNIBS supports imaging data import, target planning, head registration, real-time tool tracking, and integration with robotic positioning and electrophysiology systems. Key features include flexible target specification, support for multiple tracking hardware options, refined head registration techniques, and an extensible addon system. We describe the software architecture, core functionality, characterization of tracking performance, and example applications of NaviNIBS. This software aims to facilitate methodological improvements and novel experimental paradigms in noninvasive brain stimulation research.