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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2023

Human Intelligence and the Connectome are Driven by Structural Brain Network Control

Research in network neuroscience demonstrates that human intelligence is shaped by the structural brain connectome, which enables a globally coordinated and dynamic architecture for general intelligence. Building on this perspective, the network neuroscience theory proposes that intelligence arises from system-wide network dynamics and the capacity to flexibly transition between network states. According to this view, network flexibility is made possible by network controllers that move the system into specific network states, enabling solutions to familiar problems by accessing nearby, easy-to-reach network states and adapting to novel situations by engaging distant, difficult-to-reach network states. Although this framework predicts that general intelligence depends on network controllability, the specific cortical regions that serve as network controllers and the nature of their control operations remain to be established. We therefore conducted a comprehensive investigation of the relationship between regional measures of network controllability and general intelligence within a sample of 275 healthy young adults using structural and diffusion-weighted MRI data. Our findings revealed significant associations between intelligence and network controllers located within the frontal, temporal and parietal cortex. Furthermore, we discovered that these controllers collectively enable access to both easy- and difficult-to-reach network states, aligning with the predictions made by the network neuroscience framework. Additionally, our research demonstrated that the identified network controllers are primarily localized within the left hemisphere and do not reside within regions or connections that possess the highest capacity for structural control in general. This discovery suggests that the identified regions may facilitate specialized control operations and motivates further exploration of the network topology and dynamics underlying intelligence in the human brain. SummaryThis study examines the relationship between regional measures of network controllability and general intelligence within a sample of 275 healthy young adults using structural and diffusion-weighted MRI data. We report that individual differences in general intelligence are associated average and modal controllability in specific left-hemisphere cortical regions, and further show that controller regions associated with intelligence are distinct from regions with the highest, centrality, controllability, or communication. These findings reveal a significant structural role for individual regions in controlling the trajectory of the connectome, advancing our understanding of the nature and mechanisms of network controllability in general intelligence.

neuroscience↗

bioRxiv2023

Normative Modelling of Molecular-based Functional Neurocircuits Captures Clinical Heterogeneity Transdiagnostically in Neuropsychiatric Patients

Clinical neuroscience principally aims to delineate the neurobiology underpinning the symptoms of various disorders, with the ultimate goal of developing mechanistically informed treatments for these conditions. This has been hindered by the complex hierarchical organisation of the brain and extreme heterogeneity of neuropsychiatric disorders. However, recent advances in multimodal analytic techniques - such as Receptor Enriched Analysis of Connectivity by Targets (REACT) - have allowed to integrate the functional dynamics seen in fMRI with the brains receptor landscape, providing novel trans-hierarchical insights. Similarly, normative modelling of brain features has allowed translational neuroscience to move beyond group average differences between patients and controls and characterise deviations from health at an individual level. Here, we bring these novel methods together for the first time in order to address these two longstanding translational barriers in clinical neuroscience. REACT was used create functional networks enriched with the main modulatory (noradrenaline, dopamine, serotonin, acetylcholine), inhibitory (GABA), and excitatory (glutamate) neurotransmitter systems in a large group of healthy participants [N=607]. Next, we generated normative models of these networks across the spectrum of healthy ageing and demonstrated that these capture deviations within and across patients with Schizophrenia, Bipolar-disorder, and ADHD [N=119]. Our results align with prior accounts of excitatory-inhibitory imbalance in schizophrenia and bipolar disorder, with the former also related to deviations within the cholinergic system. Our transdiagnostic analyses also emphasised the substantial overlap in symptoms and deviations across these disorders. Altogether, this work provides impetus for the development of novel biomarkers that characterise both molecular- and systems-level dysfunction at the individual level, helping facilitate the transition towards mechanistically targeted treatments. Significance statementHuman beings show enormous variability, with inter-individual differences spanning from neurotransmitters to networks. Understanding how these mechanisms interact across scales and produce heterogenous symptomatology within psychiatric disorders presents an enormous challenge. Here, we provide a novel analytic framework to overcome these barriers, combining molecular-enriched neuroimaging with normative modelling to examine neuropathology across scales at the individual level. Our results converge on prior neurobiological accounts of schizophrenia and bipolar disorder as well as the heterogeneity of ADHD. Moreover, we map symptomatology to molecular-enriched functional networks transdiagnostically across these disorders. By bridging the gap between dysfunctional brain networks and underlying neurotransmitter systems, these methods can facilitate the transition from one-size-fits-all approaches to personalized pharmacological interventions at the individual level.

neuroscience↗

bioRxiv2024

The FinnBrain Multimodal Neonatal Template and Atlas Collection: T1, T2, and DTI brain templates, and accompanying cortical and subcortical atlases

The accurate processing of neonatal and infant brain MRI data is crucially important for developmental neuroscience, but presents challenges that child and adult data do not. Tissue segmentation and image coregistration accuracy can be improved by optimizing template images and / or related segmentation procedures. Here, we describe the construction of the FinnBrain Neonate (FBN-125) template; a multi-contrast template with T1- and T2-weighted as well as diffusion tensor imaging derived fractional anisotropy and mean diffusivity images. The template is symmetric and aligned to the Talairach-like MNI 152 template and has high spatial resolution (0.5 mm3). In addition, we provide atlas labels, constructed from manual segmentations, for cortical grey matter, white matter, cerebrospinal fluid, brainstem, and cerebellum as well as the bilateral hippocampi, amygdalae, caudate nuclei, putamina, globi pallidi, and thalami. We provide this multi-contrast template along with the labelled atlases for the use of the neuroscience community in the hope that it will prove useful in advancing developmental neuroscience, for example, by helping to achieve reliable means for spatial normalization and measures of neonate brain structure via automated computational methods. Additionally, we provide standard co-registration files that will enable investigators to reliably transform their statistical maps to the adult MNI space, which has the potential to improve the consistency and comparability of neonatal studies or the use of adult MNI space atlases in neonatal neuroimaging.

neuroscience↗

bioRxiv2024

Frequency-tagging of spatial attention using periliminal flickers

Steady-State Visually Evoked Potentials (SSVEP) manifest as a sustained rhythmic activity that can be observed in surface electroencephalography (EEG) in response to periodic visual stimuli, commonly referred to as flickers. SSVEPs are widely used in fundamental cognitive neuroscience paradigms and Brain-Computer Interfaces (BCI) due to their robust and rapid onset. However, they have drawbacks related to the intrusive saliency of flickering visual stimuli, which may induce eye strain, cognitive fatigue, and biases in visual exploration. Previous findings highlighted the potential of altering features of flicker stimuli to improve user experience. In this study, we propose to reduce the amplitude modulation depth of flickering stimuli down to the individuals perceptual visibility threshold (periliminal) and below (subliminal). The stimulus amplitude modulation depth represents the contrast difference between the two alternating states of a flicker. A simple visual attention task where participants responded to the presentation of spatially-cued target stimuli (left and right) was used to assess the validity of such periliminal and subliminal frequency-tagging probes to capture spatial attention. The left and right sides of the screen, where target stimuli were presented, were covered by large flickers (13 and 15 Hz respectively). The amplitude modulation depth of these flickers was manipulated across three conditions: control, periliminal, and subliminal. The latter two levels of flickers amplitude modulation depth were defined through a perceptual visibility threshold protocol on a single-subject basis. Subjective feedback indicated that the use of periliminal and subliminal flickers substantially improved user experience. The present study demonstrates that periliminal and subliminal flickers evoked SSVEP responses that can be used to derive spatial attention in frequency-tagging paradigms. The single-trial classification of attended space (left versus right) based on SSVEP response reached an average accuracy of 81.1% for the periliminal and 58% for the subliminal conditions. These findings reveal the promises held by the application of inconspicuous flickers to both cognitive neuroscience research and BCI development. HighlightsO_LIFrequency-tagging of spatial attention can be achieved through the presentation of flickering visual stimuli (flickers) whose contrast is reduced down to the individuals perceptual visibility threshold revealing the potential of periliminal flickers as reliable frequency-tagging probes of spatial attention C_LIO_LIBelow this perceptual visibility threshold, the signal-to-noise ratio of SSVEP responses was not sufficient to reliably distinguish the field upon which participants directed their attention C_LIO_LIThe subliminal and periliminal flickers ameliorated the overall user experience and represent effective solutions to reduce bottom-up distraction, eye strain, and fatigue related to the presentation of flickering stimulation C_LIO_LIThe present findings have implications for the design of minimally intrusive frequency-tagging probes used within the frame of both fundamental cognitive neuroscience research and Brain Computer Interface C_LI

neuroscience↗

bioRxiv2024

Different varieties of arousal converge on a shared cortical network

The term arousal is very often used, but classical textbooks from different domains of neuroscience and psychology offer surprisingly different views on what arousal is. The huge number of scientific articles with the term arousal ([~]50.000) highlights the importance of the concept but also explains why such a vast literature has never been systematically reviewed so far. Here, we leverage the tools of natural language processing to probe the nature of arousal in a data-driven, comprehensive manner. We show that arousal comes in seven varieties: cognitive, emotional, physiological, sexual, related to stress disorders, to sleep, or to sleep disorders. We then ask whether domain-general arousal exists, and run meta-analyses of the brain imaging literature to reveal that all varieties of arousal, except arousal in sleep disorders for lack of data, converge onto a cortical arousal network composed of the pre-supplementary motor area and the left and right dorsal anterior insula. More precisely, we find that activity in dysgranular insular area 7, the region with the highest convergence across varieties of arousal is also specific to arousal. Our results show that arousal corresponds to a construct at least partially shared across different domains of neuroscience and identify the domain-general cortical arousal network. Novel taxonomies of arousal reconciling seemingly opposing views on what arousal is should thus include domain-general arousal as a central component. Significance statementThe term arousal has been used in almost 50.000 scientific papers, but it is only loosely defined. The few attempts at defining arousal in neuroscience and psychology resulted in divergent views: arousal as a multi-dimensional construct or arousal as a global state. Is arousal an abstraction of the scientists mind reflecting a myriad of distinct processes, or is there some common neuronal feature? We used large-scale semi-automatic text mining methods and neuroimaging meta-analyses to review this vast and heterogeneous literature. Our results reveal the existence of domain-general arousal, a process shared by situations as different as a cognitive task, an emotional context, and the transition to wakefulness or sexual behavior. Domain-general arousal reconciles the concepts of general and multi-dimensional arousal.

neuroscience↗

bioRxiv2024

Social 'envirotyping' the ABCD study contextualizes dissociable brain organization and diverging outcomes

The environment, especially social features, plays a key role in shaping the development of the brain, notably during adolescence. To better understand variation in brain-environment coupling and its associated outcomes, we identified "envirotypes," or different patterns of social environment experience, in the Adolescent Brain Cognitive Development Study by hierarchically clustering subjects. Two focal clusters, which accounted for 89.3% of all participants, differed significantly on eight out of nine youth-report social environment quality measures, representing almost perfect complements. We then applied tools from network neuroscience to show different envirotypes are associated with different patterns of whole brain functional connectivity. Differences were distributed across the brain but were especially prominent in Default and Somatomotor Hand systems for these focal clusters. Finally, we examined how social envirotypes change over development and how these patterns of change are associated with a suite of outcomes. The resulting dynamic envirotypes differed along dimensions of stability and quality, but outcomes diverged based on stability. Specifically, the stable, high quality envirotype was most easily distinguished from the improving envirotype, while the unstable envirotype was associated with the worst outcomes. Altogether, our findings represent significant contributions to both social developmental neuroscience and network neuroscience, emphasizing the variability and dynamicity of brain-environment coupling and its consequences.

neuroscience↗

bioRxiv2024

Imaging the dancing brain: Decoding sensory, motor and social processes during dyadic dance

Real-world social cognition requires processing and adapting to multiple dynamic information streams. Interpreting neural activity in such ecological conditions remains a key challenge for neuroscience. This study leverages advancements in de-noising techniques and multivariate modeling to extract interpretable EEG signals from pairs of participants (male-male, female-female, and male-female) engaged in spontaneous dyadic dance. Using multivariate temporal response functions (mTRFs), we investigated how music acoustics, self-generated kinematics, other-generated kinematics, and social coordination uniquely contributed to EEG activity. Electromyogram recordings from ocular, face, and neck muscles were also modeled to control for artifacts. The mTRFs effectively disentangled neural signals associated with four processes: (I) auditory tracking of music, (II) control of self-generated movements, (III) visual monitoring of partner movements, and (IV) visual tracking of social coordination. We show that the first three neural signals are driven by event-related potentials: the P50-N100-P200 triggered by acoustic events, the central lateralized movement-related cortical potentials triggered by movement initiation, and the occipital N170 triggered by movement observation. Notably, the (previously unknown) neural marker of social coordination encodes the spatiotemporal alignment between dancers, surpassing the encoding of self-or partner-related kinematics taken alone. This marker emerges when partners can see each other, exhibits a topographical distribution over occipital areas, and is specifically driven by movement observation rather than initiation. Using data-driven kinematic decomposition, we further show that vertical bounce movements best drive observers EEG activity. These findings highlight the potential of real-world neuroimaging, combined with multivariate modeling, to uncover the mechanisms underlying complex yet natural social behaviors. Significance statementReal-world brain function involves integrating multiple information streams simultaneously. However, due to a shortfall of computational methods, laboratory-based neuroscience often examines neural processes in isolation. Using multivariate modeling of EEG data from pairs of participants freely dancing to music, we demonstrate that it is possible to tease apart physiologically established neural processes associated with music perception, motor control, and observation of a partners movement. Crucially, we identify a previously unknown neural marker of social coordination that encodes the spatiotemporal alignment between dancers, beyond self- or partner-related kinematics alone. These findings highlight the potential of computational neuroscience to uncover the biological mechanisms underlying real-world social and motor behaviors, advancing our understanding of how the brain supports dynamic and interactive activities.

neuroscience↗

bioRxiv2025

SynAnno: Interactive Guided Proofreading of Synaptic Annotations

Connectomics, a subfield of neuroscience, aims to map and analyze synapse-level wiring diagrams of the nervous system. While recent advances in deep learning have accelerated automated neuron and synapse segmentation, reconstructing accurate connectomes still demands extensive human proofreading to correct segmentation errors. We present SynAnno, an interactive tool designed to streamline and enhance the proofreading of synaptic annotations in large-scale connectomics datasets. SynAnno integrates into existing neuroscience workflows by enabling guided, neuron-centric proofreading. To address the challenges posed by the complex spatial branching of neurons, it introduces a structured workflow with an optimized traversal path and a 3D mini-map for tracking progress. In addition, SynAnno incorporates fine-tuned machine learning models to assist with error detection and correction, reducing the manual burden and increasing proofreading efficiency. We evaluate SynAnno through a user and case study involving seven neuroscience experts. Results show that SynAnno significantly accelerates synapse proofreading while reducing cognitive load and annotation errors through structured guidance and visualization support. The source code and interactive demo are available at: https://github.com/PytorchConnectomics/SynAnno.

neuroscience↗

bioRxiv2025

The Turbulent Brain: a toolbox to compute the turbulent dynamical behaviour of whole-brain activity

Brain disorders remain one of the greatest challenges in neuroscience. Computational precision medicine offers a promising framework to reveal the mechanistic principles governing both healthy and pathological brain dynamics. In this context, we present The Turbulent Brain (TTB) toolbox, an open-source MATLAB platform that implements and disseminates the turbulence framework for immediate and widespread application in neuroscience research. The toolbox combines model-free and model-based analyses through an intuitive graphical interface, enabling customizable workflows across different parcellations and preprocessing pipelines. Our toolbox builds on recent advances demonstrating that turbulence physics can effectively capture the complex spatiotemporal dynamics of brain activity as a high-dimensional system operating far from equilibrium. This framework allows researchers to explore how fundamental mechanisms are modulated across distinct brain states and neurological and psychiatric disorders, including disorders of consciousness and major depressive disorder. As an illustrative application case, we used TTB to analyse fMRI data from 176 individuals from the Human Connectome Project during resting state and movie watching, showing that movie watching, as compared to resting state, significantly reduces information transmission in terms of turbulence measures, with stronger reductions observed during Creative Commons movie watching compared to Hollywood movies. In summary, the TTB toolbox establishes an accessible framework providing a methodological bridge between nonlinear physics and computational neuroscience, offering new tools for investigating psychiatric conditions and altered states of consciousness.

neuroscience↗

bioRxiv2018

A compact head-mounted endoscope for in vivo calcium imaging in freely-behaving mice

Miniaturized fluorescence microscopes for imaging calcium transients are a promising tool for investigating the relationship between behaviour and population-level neuronal activity in rodents. However, commercially available miniature microscopes may be costly, and, because they are closed-source, may not be easily modified based on particular experimental requirements. Here, we describe how to build and use a low-cost compact head-mounted endoscope (CHEndoscope) system for in vivo calcium imaging. The CHEndoscope uses an implanted gradient index (GRIN) lens along with the genetically encoded calcium indicator GCaMP6 to image calcium transients from hundreds of neurons simultaneously in awake behaving mice. This system is affordable, open-source, and flexible, permitting modification depending on the particular experiment. This Unit describes in detail the assembly, surgical implantation, data collection, and processing of calcium signals using the CHEndoscope system. The aim of this open framework model is to provide an accessible set of miniaturized calcium imaging tools for the neuroscience research community.\n\nSignificance StatementThe ability to image calcium transients in awake, behaving rodents using miniature microscopes opens exciting and novel avenues for gaining insights into how information is encoded in neural circuits. The development of this tool has already had a significant impact on neuroscience research. The cost of commercial systems, however, may be prohibitive for many laboratories. Here, we describe an affordable, open-source compact head-mounted endoscope (CHEndoscope) system for performing in vivo calcium imaging in freely-behaving mice. CHEndoscopes may be manufactured by individual laboratories at relatively minor cost. Our hope is that greater availability of affordable, open-source tools (such as the one presented here) will accelerate the pace of discoveries in systems neuroscience.

neuroscience↗

bioRxiv2018

A Data Structure for real-time Aggregation Queries of Big Brain Networks

Recent advances in neuro-imaging allowed big brain-initiatives and consortia to create vast resources of brain data that can be mined by researchers for their individual projects. Exploring the relationship between genes, brain circuitry, and behavior is one of key elements of neuroscience research. This requires fusion of spatial connectivity data at varying scales, such as whole brain correlated gene expression, structural and functional connectivity. With ever-increasing resolution, those exceed the past state-of-the art in several orders of magnitude in size and complexity. Current analytical workflows in neuroscience involve time-consuming manual aggregation of the data and only sparsely incorporate spatial context to operate continuously on multiple scales. Incorporating techniques for handling big connectivity data is therefore a necessity.\n\nWe propose a data structure to explore heterogeneous neurobiological connectivity data for integrated visual analytics workflows. Aggregation Queries, i.e. the aggregated connectivity from, to or between brain areas allow experts the comparison of multimodal networks residing at different scales, or levels of hierarchically organized anatomical atlases. Executed on-demand on volumetric gene expression and connectivity data, they enable an interactive dissection of networks, with billions of edges, in real-time, and based on their spatial context. The data structure is optimized to be accessed directly from the hard disk, since connectivity of large-scale networks typically exceed the memory size of current consumer level PCs. This allows experts to embed and explore their own experimental data in the framework of public data resources without large-scale infrastructure.\n\nOur novel data structure outperforms state-of-the-art graph engines in retrieving connectivity of local brain areas experimentally. We demonstrate the application of our approach for neuroscience by analyzing fear-related functional neuroanatomy in mice. Further, we show its versatility by comparing multimodal brain networks linked to autism. Importantly, we achieve cross-species congruence in retrieving human psychiatric traits networks, which facilitates selection of neural substrates to be further studied in mouse models.

neuroscience↗

bioRxiv2018

Sulci of the canine brain: a review of terminology

Over the last decades there have been several publications of anatomical and neurological textbooks, which include descriptions about the dogs brain. However, the terminology used is inconsistent, partly due to individual differences in neocortical gyration and partly due to the common practice of adapting terms from human and murine anatomy. In order to identify such incongruences, in Study 1, we reviewed the existing literature and identified the common terms used as well as any discrepancies between textbooks. Three main forms of inconsistencies were found; a) the use of terms that are not included in the Nomina Anatomica Veterinaria (NAV), b) the inclusion of structures that are listed as not canine-specific, and c) the use of similar names to identify potentially different anatomical structures. To address these issues, in Study 2 we investigated the consistency in appearance of the cerebral sulci, performing a macroscopical examination on 79 canine brains obtained through the Canine Brain and Tissue Bank (CBTB). We then evaluated whether sulci on the frontal regions of brachycephalic breeds differed from those of mesocephalic and dolichocephalic groups, as frontal and olfactory regions are subjected to the most extreme modifications following the shortening of the skull. The statistical analysis showed no difference across the skull length types regarding the occurrence of these sulci, although furrows on the lateral side of the brain proved to be more stable than those on the medial side. In Study 3, we summarized the findings in accordance with the NAV to produce a definitive index of the terms that we recommend be used for each identified sulci. Such an index is beneficial for educational, clinical use, and research (e.g. neuroscience) purposes. The dog is emerging as a pioneering and exceptional model in comparative neuroscience, and therefore the implications for canine neuroscience research should not be underestimated.

neuroscience↗

bioRxiv2019

Chemogenetic inhibition of the amygdala modulates emotional behavior expression in infant rhesus monkeys

Manipulation of neuronal activity during the early postnatal period in monkeys has been largely limited to permanent lesion studies, which can be impacted by developmental plasticity leading to reorganization and compensation from other brain structures that can interfere with the interpretations of results. Chemogenetic tools, such as DREADDs (designer receptors exclusively activated by designer drugs), can transiently and reversibly activate or inactivate brain structures, avoiding the pitfalls of permanent lesions to better address important developmental neuroscience questions. We demonstrate that inhibitory DREADDs in the amygdala can be used to manipulate socioemotional behavior in infant monkeys. Two infant rhesus monkeys (1 male, 1 female) received AAV5-hSyn-HA-hM4Di-IRES-mCitrine injections bilaterally in the amygdala at 9 months of age. DREADD activation after systemic administration of either clozapine-N-oxide or low dose clozapine resulted in decreased freezing and anxiety on the human intruder paradigm and changed the looking patterns on a socioemotional attention eyetracking task, compared to vehicle administration. The DREADD-induced behaviors were reminiscent of, but not identical to, those seen after permanent lesions of the amygdala in infant monkeys, such that early amygdala lesions produce a more extensive array of behavioral changes in response to the human intruder task that were not seen with DREADD-evoked inhibition of this region. Our results support the notion that early permanent damage leads to brain reorganization manifesting in a broader impact on behavior. The current study provides a proof-of-principle that DREADDs can be used in young infant monkeys to transiently and reversibly manipulate behavior. Statement of SignificanceMany neurodevelopmental disorders exhibit abnormal structural or functional amygdala development and alterations in socioemotional behavior. To date, developmental neuroscience studies have relied on permanent lesions techniques to investigate how atypical amygdala development impacts socioemotional behaviors, which may not adequately recapitulate the role of amygdala dysfunction in the manifestation of aberrant behavior. The present study sought to demonstrate that the DREADDs (designer receptors exclusively activated by designer drugs) chemogenetic tool could transiently inhibit amygdala activity in infant monkeys resulting in alterations in socioemotional behavior. This proof-of-principle study supports the use of chemogenetics for developmental neuroscience research, providing an opportunity to broaden our understanding of how changes in neuronal activity across early postnatal development influences behavior and clinical symptoms.

neuroscience↗

bioRxiv2026

NEuRT: A Transformer-Based Model for Explainable Neuronal Activity Analysis

The study of neuronal activity is essential for understanding brain function and its alterations in neurode-generative diseases. Advances in in vivo imaging have enabled real-time observation of neuronal dynamics, but classical statistical methods struggle to capture the complex, time-dependent interactions within neuronal networks. Machine learning offers promising solutions for analyzing high-dimensional neuronal data, yet their application in neuroscience remains limited. Here, we introduce NEuRT, a Bidirectional Encoder Representations from Transformers (BERT)-based model adapted for neuronal activity analysis. NEuRT leverages self-attention mechanisms to interpret complex neuronal interactions, providing insights into patterns that traditional methods may overlook. Pre-trained on the recently introduced large annotated dataset MICrONS for signal reconstruction, NeuRT demonstrates strong generalization, effectively reconstructing activity from both visual cortex two-photon and hippocampal miniature fluorescence microscopy. Built on the BERT architecture, the NEuRT model can be efficiently fine-tuned for a wide range of downstream tasks. We showcase its application in classifying wild-type and transgenic Alzheimers disease model mice, based on hippocampal activity, revealing group-specific features through attention map analysis. By reducing reliance on extensive labeled data, addressing a critical challenge in neuroscience, NEuRT bridges fundamental neuroscience and disease research, offering a robust framework for AI-driven and explainable neuronal activity analysis.

neuroscience↗

bioRxiv2026

ABISS: An Open-Source, Low-Cost Platform for Auditory and Visual Intrinsic Optical Signal Imaging

Defining the boundaries of functional cortical areas is increasingly important for targeted electro-physiology, optical imaging, viral delivery, and circuit manipulation. Intrinsic optical signal imaging (IOSI) provides a rapid and minimally invasive approach for mapping stimulus-evoked cortical activity, but its implementation often requires laboratory-specific combinations of stimulus-generation hardware, experiment-control software, synchronization devices, and data-acquisition systems. These requirements limit accessibility and hinder the use of IOSI as a routine functional mapping tool. Here, we present the Arduino-Based Intrinsic Stimulation System (ABISS), an open-source platform that integrates auditory and visual stimulus generation, trial timing, and image-acquisition triggering into a single programmable device. ABISS generates auditory tone stimuli, VGA-based visual stimuli, and tightly synchronized camera-trigger pulses without requiring a dedicated experiment-control system. Stimulus protocols are also fully modifiable in firmware. Performance was evaluated in auditory and visual cortices of mice. Engineering validation demonstrated accurate stimulus generation and synchronization between stimulus delivery and camera triggering over extended recording sessions. Biological validation showed that ABISS output results in auditory and visual intrinsic signal maps comparable to those obtained using highly specialized or commercial platforms. Together, these findings demonstrate the utility of a low-cost open-source platform for experimental control of intrinsic optical signal imaging. By reducing the technical and financial barriers associated with routine intrinsic optical imaging, ABISS facilitates broader adoption of functional cortical mapping as a tool for improved cortical localization in neuroscience experiments. Significance StatementFunctional cortical mapping is an increasingly important element of neuroscience experimental design as anatomical coordinates alone are often insufficient for defining cortical boundaries in individual animals. Intrinsic optical signal imaging provides an effective solution but traditionally requires specialized hardware, commercial stimulus-generation systems, and laboratory-specific synchronization workflows. We developed ABISS, an inexpensive, open-source platform that integrates auditory and visual stimulus generation with synchronized camera triggering in a single programmable device. ABISS produces functional cortical maps comparable to those obtainable with commercial or specialized systems while substantially reducing hardware complexity and cost. By making intrinsic optical signal imaging more accessible, ABISS lowers the practical barriers for routine functional mapping of the brain and promotes adoption of this important neuroscience technique.

neuroscience↗

bioRxiv2026

The NeuroHab: A Low-Cost, Integrated System for Investigation of Neural Correlates of Behaviors

The development of a new integrated operant system was driven by two challenges in behavioral neuroscience: the high cost and technical complexity of commercial rigs, and their limited adaptability across experiments. We developed the NeuroHab, an integrated behavioral arena for high-fidelity operant conditioning and automated data collection in a single unified system. Food and water reward, conditioned-stimulus presentation, and event recording are tied together programmatically with easy-to-install open-source code to facilitate throughput and reproducibility. All behavioral events are processed by internal microcontrollers and logged with <1 ms latency (typical range 56-728 s). This precise timing is critical for integrating the system with two-photon imaging and electrophysiology, enabling real-time alignment of behavior with brain activity. The NeuroHab uses solenoid-actuated, capacitive-sensing Lickports that let an untethered mouse drink from an automated port, and delivers food via the Kravitz Lab FED3. Conditioned stimuli are presented by dedicated buzzer/LED modules. A central controller (the Core) coordinates all modules and logs event timestamps using TTL-low signaling between two microcontrollers, at a maximum recording rate of 16.67 Hz for single-pulse events. We have deployed the NeuroHab in over 50 behavior trials and over 20 sessions alongside a Mini two-photon microscope. At approximately $1,400, easily modified, and compatible with existing analysis tools, the NeuroHab lowers barriers to multimodal behavioral neuroscience. Significance StatementThe study of how neural activity gives rise to behavior depends on operant systems that are both temporally precise and affordable, yet commercial rigs are costly and difficult to adapt across experiments. We introduce the NeuroHab, an integrated, open-source operant platform that unifies reward delivery, conditioned-stimulus presentation, and event logging with sub-millisecond timing (typical latency 56-728 s). Built for approximately $1,400, the system forwards all behavioral timestamps to external acquisition hardware, enabling millisecond-scale alignment of behavior with two-photon imaging and electrophysiology. By lowering the cost and technical barriers to synchronized behavioral and neural recording, the NeuroHab makes multimodal, reproducible operant neuroscience accessible to a broad range of laboratories and adaptable to diverse experimental paradigms.

neuroscience↗

bioRxiv2020

Robotic Multi-Probe-Single-Actuator Inchworm Neural Microdrive

Electrophysiology is one of the major experimental techniques used in neuroscience. The favorable spatial and temporal resolution as well as the increasingly larger site counts of brain recording electrodes contribute to the popularity and importance of electrophysiology in neuroscience. Such electrodes are typically mechanically placed in the brain to perform acute or chronic freely moving animal measurements. The micro positioners currently used for such tasks employ a single translator per independent probe being placed into the targeted brain region, leading to significant size and weight restrictions. To overcome this limitation, we have developed a miniature robotic multi-probe neural microdrive that utilizes novel phase-change-material-filled resistive heater micro-grippers. The microscopic dimensions, gentle gripping action, independent electronic actuation control, and high packing density of the grippers allow for micrometer-precision independent positioning of multiple arbitrarily shaped parallel neural electrodes with only a single piezo actuator in an inchworm motor configuration. This multi-probe-single-actuator design allows for significant size and weight reduction, as well as remote control and potential automation of the microdrive. We demonstrate accurate placement of multiple independent recording electrodes into the CA1 region of the rat hippocampus in vivo in acute and chronic settings. Thus, our robotic neural microdrive technology is applicable towards basic neuroscience and clinical studies, as well as other multi-probe or multi-sensor micro-positioning applications. One Sentence SummaryMiniature robotic multi-probe single-actuator microdrive utilizing phase change material based micro-grippers.

bioengineering↗

bioRxiv2021

Making BrainWaves: Portable Brain Technologies in Biology Education

Neuroscience is one of the fastest growing STEM fields, yet its presence in K-12 science education is very limited, partially due to the lack of accessible teaching materials and tools. Here, we describe a new high school neuroscience curriculum ("BrainWaves"), where students utilize recent advances in low-cost, portable Electroencephalography (EEG) technology to investigate their own brain activity. This semester-long curriculum is supported by science mentors and an educational application that guides students through the process of recording and analyzing their own brain activity. Evaluation data collected in 5 public New York City schools in 2018/19 indicate significant positive shifts in content knowledge and self-efficacy among students who participated in BrainWaves compared to students in other courses of the same teacher. The quantitative findings are supported by interviews, where students reported increased appreciation for neuroscience and college readiness and discussed the benefits of collaborating with scientists and using portable brain technology in classrooms.

scientific communication and education↗