Biology subjects

Bosman, C. A.

Publications and source records attributed to Bosman, C. A..

14 recordsLinked to original sources

bioRxiv2026

Neuroline: an integrated modular pipeline for FAIR multimodal neurophysiology data processing

The adoption of FAIR principles for code and data sharing in systems neuroscience is hindered by the size and diversity of datasets, the multitude of data formats and the complexity of analysis workflows. These challenges have led to the development of various data standards and modality-specific processing and analysis tools. However, it remains difficult to integrate the diverse processed data streams originating from state-of-the-art neurophysiology experiments into a common format, which is crucial for cross-modal analyses and open, FAIR sharing of data. To address this, we developed Neuroline, a Python package for processing neurophysiology data (electrophysiology, optical imaging, and behaviour) that combines multimodal integration, modularity, and standardised output within a single pipeline. It leverages established packages and consolidates the resulting processed data into the standardised Neurodata Without Borders (NWB) format. Neuroline provides a unified interface while preserving flexibility and extensibility. Here we describe the implementation and challenges of a pipeline capable of integrating different types of neuroscientific data and packages. Finally, we address how Neuroline contributes to the sustainability and accessibility of neuroscience data and software.

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bioRxiv2025

Audiovisual processing is selectively impaired in the primary visual cortex but not in the posterior parietal cortex of a mouse model of Fragile X syndrome

Sensory processing disruptions are a common feature in various forms of autism spectrum disorders (ASD), yet the circuit-level mechanisms underlying these deficits remain poorly understood. Here, we examined differences in audiovisual processing between wild-type and Fmr1-knockout (KO) mice, a model of Fragile X syndrome, which itself represents the most common hereditary cause of autism. We performed multi-area Neuropixels probe recordings in the primary visual cortex (V1) and posterior parietal cortex (PPC) of head-fixed, anesthetized mice being shown visual and auditory stimuli. Previous studies generally reported sensory hypersensitivity in Fragile X mice. In contrast, we observed reduced visual and auditory responses in V1 (but not PPC) of Fragile X compared to wild-type mice. Auditory stimuli reduced the amplitude of visual responses in both V1 and PPC across the two lines, but a dependency on the relative timing of the two sensory modalities was only observed in wild-type mice. Our results provide evidence for a region-specific sensory-processing phenotype of ASD, something that needs to be taken into account when evaluating the efficacy of pharmacological and behavioral strategies to address ASD symptoms.

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bioRxiv2025

On variability in local field potentials

Neuronal coding and decoding would be compromised if neuronal responses were highly variable. Intriguingly, neuronal spike counts (SCs) show a reduction in across-trial variance (ATV) in response to sensory stimulation, when SC variance is normalized by SC mean, that is, when using the Fano factor 1. Inspired by this seminal finding, ATV has also been studied in electroencephalography (EEG) signals, revealing effects of various stimulus and cognitive factors as well as disease states. Here, we empirically show that outside of evoked potentials, the ATV of the EEG or local field potential (LFP) is very highly correlated to the intra-trial variance (ITV), which corresponds to the well-known power metric. We propose that the LFP power, rather than the raw LFP signal, should be considered with regard to putative changes of its variability. We quantify LFP power variability as the standard deviation of the logarithm of the power ratio between an active and a baseline condition, normalized by the mean of that log(power ratio), that is the coefficient of variation (CV) of the log(power ratio). This CV(log(power ratio)) is reduced for gamma and alpha power when they are enhanced by stimulation, and it is enhanced for alpha power when it is reduced by stimulation. This suggests a potential inverse relation between changes in band-limited power and the corresponding CV. We propose that the CV(log(power ratio)) is a useful metric that can be computed for numerous existing and future LFP, EEG or MEG datasets, which will provide insights into those signals frequency-specific variability and how they might be used for neuronal coding and decoding.

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bioRxiv2024

Circuit-Level Dynamics of Slow Wave Activity and Propagation During the Awakening Process

Slow-wave activity (SWA) is a hallmark of the loss of consciousness in non-REM sleep and anesthesia. The mechanistic underpinnings of SWA, and its evolution when transitioning towards the conscious brain state is poorly understood. We address this topic by recording multi-area and laminar activity in posterior parietal (PPC) and primary visual (V1) cortices of mice spontaneously awakening from isoflurane anesthesia. Spectral power is stronger in PPC (especially in superficial layers) during deep unconsciousness, but stronger in V1 when awakening. Rostro-caudal (feedback-like) propagation of SWA also shows state-dependent modulation, particularly in layer 5. The excitability of layer 2/3 neurons, hindered at high isoflurane, recovers during awakening, when V1 and the feedforward pathway reacquire a strong role. Detailing the hierarchical and laminar properties of spontaneous traveling oscillations, we provide evidence that SWA is a multiscale phenomenon. Explicating the functional role of these processes is critical to understand the neuronal mechanisms of consciousness.

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bioRxiv2024

Stimulus-repetition effects on macaque V1 and V4 microcircuits explain gamma-synchronization increase

Under natural conditions, animals repeatedly encounter the same visual scenes, objects or patterns repeatedly. These repetitions constitute statistical regularities, which the brain captures in an internal model through learning. A signature of such learning in primate visual areas V1 and V4 is the gradual strengthening of gamma synchronization. We used a V1-V4 Dynamic Causal Model (DCM) to explain visually induced responses in early and late epochs from a sequence of several hundred grating presentations. The DCM reproduced the empirical increase in local and inter-areal gamma synchronization, revealing specific intrinsic connectivity effects that could explain the phenomenon. In a sensitivity analysis, the isolated modulation of several connection strengths induced increased gamma. Comparison of alternative models showed that empirical gamma increases are better explained by (1) repetition effects in both V1 and V4 intrinsic connectivity (alone or together with extrinsic) than in extrinsic connectivity alone, and (2) repetition effects on V1 and V4 population input rather than output gain. The best input gain model included effects in V1 granular and superficial excitatory populations and in V4 granular and deep excitatory populations. Our findings are consistent with gamma reflecting bottom-up signal precision, which increases with repetition and, therefore, with predictability and learning. HighlightsO_LIWe model learning effects in macaque visual cortex using Dynamic Causal Modeling. C_LIO_LIMicrocircuit-level changes explain the repetition-induced gamma increases. C_LIO_LIThe best models include changes 1) within V1 and V4 and 2) in neuronal input gain. C_LIO_LIGamma may reflect bottom-up signal precision. C_LI

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bioRxiv2023

Enhanced Behavioral Performance through Interareal Gamma and Beta Synchronization

Cognitive functioning requires coordination between brain areas. Between visual areas, feedforward gamma synchronization improves behavioral performance. Here, we investigate whether similar principles hold across brain regions and frequency bands, using simultaneous local field potential recordings from 15 areas during performance of a selective attention task. Short behavioral reaction times (RTs), an index of efficient interareal communication, occurred when occipital areas V1, V2, V4, DP showed gamma synchronization, and fronto-central areas S1, 5, F1, F2, F4 showed beta synchronization. For both area clusters and corresponding frequency bands, deviations from the typically observed phase relations increased RTs. Across clusters and frequency bands, good phase relations occurred in a correlated manner specifically when they processed the behaviorally relevant stimulus. Furthermore, the fronto- central cluster exerted a beta-band influence onto the occipital cluster whose strength predicted short RTs. These results suggest that local gamma and beta synchronization and their inter-regional coordination jointly improve behavioral performance.

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bioRxiv2022

Spontaneous Variations in Arousal Modulate Subsequent Visual Processing and Local Field Potential Dynamics in the Ferret during Quiet Wakefulness

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent, but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in primary visual cortex (V1) and posterior parietal cortex (PPc) in awake ferrets, using the pupil diameter as an indicator of arousal. We observed that during low arousal, low- frequency power increases during visual stimulation, and that the peak alpha frequency shifted depending on the arousal state. High arousal increased gamma power as well as low-frequency inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area PPc and supragranular layers in V1. Neurons in V1 displayed higher firing rates at their preferred orientations on high-arousal trials. Broad-spiking cells in V1 entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons phase-locked to low (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

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bioRxiv2022

Selective V1-to-V4 communication of attended stimuli mediated by attentional effects in V1

Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modeled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing. HIGHLIGHTSO_LIWe model selective visual attention in macaques using Dynamic Causal Modeling. C_LIO_LIIntrinsic V1 modulation can explain attention effects in V1-V4 communication. C_LIO_LIModulation of superficial and granular inhibition is key to induce the effects. C_LIO_LIThose modulations increase V1-V4 communication in a feedforward manner. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/484223v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1cc79a7org.highwire.dtl.DTLVardef@146e6bdorg.highwire.dtl.DTLVardef@1d6bd6borg.highwire.dtl.DTLVardef@12dd663_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2022

Modelling non-local neural information processing in the brain

The representation of the surrounding world emerges through integration of sensory information and actions. We present a novel neural model which implements non-local, parallel information processing on a neocolumnar architecture with lateral interconnections. Information is integrated into a holographic wave interference pattern. We compare the simulated in silico pattern with observed in vivo invasive and non-invasive electrophysiological data in human and non-human primates. Our model replicates the modulation of neural high-frequency activity during visual perception showing that phase-locked low and high-frequency oscillations self-organize efficiently and carry high information content. The simulation further models how criticality (high content) of information processing emerges given a sufficiently high number of correlated neurons. Non-local information processing, forming one holographic wave pattern, suggests a platform for emergence of conscious perception. One sentence summarySimulated non-local information processing on a neocolumnar architecture models well multiple electrophysiological observations of brain activity, including high-frequency activity during visual perception in primates.

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bioRxiv2020

The role of anatomical connection strength for interareal communication in macaque cortex

What is the relationship between anatomical connection strength and rhythmic synchronization? Simultaneous recordings of 15 cortical areas in two macaque monkeys show that interareal networks are functionally organized in spatially distinct modules with specific synchronization frequencies, i.e. frequency-specific functional connectomes. We relate the functional interactions between 91 area pairs to their anatomical connection strength defined in a separate cohort of twenty six subjects. This reveals that anatomical connection strength predicts rhythmic synchronization and vice-versa, in a manner that is specific for frequency bands and for the feedforward versus feedback direction, even if interareal distances are taken into account. These results further our understanding of structure-function relationships in large-scale networks covering different modality-specific brain regions and provide strong constraints on mechanistic models of brain function. Because this approach can be adapted to non-invasive techniques, it promises to open new perspectives on the functional organization of the human brain.

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bioRxiv2019

Brain rhythms shift and deploy attention

One of the most central cognitive functions is attention. Its neuronal underpinnings have primarily been studied during conditions of sustained attention. Much less is known about the neuronal dynamics underlying the processes of shifting attention in space, as compared to maintaining it on one stimulus, and of deploying it to a particular stimulus. Here, we use ECoG to investigate four rhythms across large parts of the left hemisphere of two macaque monkeys during a task that allows investigation of deployment and shifting. Shifting involved a strong transient enhancement of power in a 2-7 Hz theta band in frontal, pre-motor and visual areas, and reductions of power in an 11-20 Hz beta band in a fronto-centro-parietal network and in a 29-36 Hz high-beta band in premotor cortex. Deployment of attention to the contralateral hemifield involved an enhancement of beta power in parietal areas, a concomitant reduction of high-beta power in pre-motor areas and an enhancement of power in a 60-76 Hz gamma band in extra-striate cortex. Effects due to shifting occurred earlier than effects due to deployment. These results demonstrate that the four investigated rhythms are involved in attentional allocation, with striking differences between shifting and deployment between different brain areas.\n\nSignificanceWe are often confronted by many visual stimuli, and attentional mechanisms select one stimulus for in-depth processing. This involves that attention is shifted between stimuli and deployed to one stimulus at a time. Prior studies have revealed that these processes are subserved by several brain rhythms. Therefore, we recorded brain activity in macaque monkeys with many electrodes distributed over large parts of their left hemisphere, while they performed a task that involved shifting and deploying attention. We found four dominant rhythms: theta (2-7 Hz), beta (11-20 Hz), high-beta (29-36 Hz) and gamma (60-76 Hz). Attentional shifting and deployment involved dynamic modulations in the strength of those rhythms with high specificity in space and time.

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bioRxiv2019

Gamma-cycle duration predicts instantaneous amplitude, spike rate and synchrony in macaque V1.

Circuits of excitatory and inhibitory neurons can generate rhythmic activity in the gamma frequency-range (30-80Hz). Individual gamma-cycles show spontaneous variability in amplitude and duration. The mechanisms underlying this variability are not fully understood. We recorded local-field-potentials (LFPs) and spikes from awake macaque V1, and developed a noise-robust method to detect gamma-cycle amplitudes and durations. Amplitudes and durations showed a weak but positive correlation. This correlation, and the joint amplitude-duration distribution, is well reproduced by a dampened harmonic oscillator driven by stochastic noise. We show that this model accurately fits LFP power spectra and is equivalent to a linear PING (Pyramidal Interneuron Network Gamma) circuit. The model recapitulates two additional features of V1 gamma: (1) Amplitude-duration correlations decrease with oscillation strength; (2) Amplitudes and durations exhibit strong and weak autocorrelations, respectively, depending on oscillation strength. Finally, longer gamma-cycles are associated with stronger spike-synchrony, but lower spike-rates in both (putative) excitatory and inhibitory neurons. In sum, V1 gamma-dynamics are well described by the simplest possible model of gamma: A linear harmonic oscillator driven by noise.

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bioRxiv2018

Gamma synchronization between V1 and V4 improves behavioral performance

Motor behavior is often driven by visual stimuli, relying on efficient feedforward communication from lower to higher visual areas. The Communication-through-Coherence hypothesis proposes that interareal communication depends on coherence at an optimal phase relation. While previous studies have linked effective communication to enhanced interareal coherence, it remains unclear, whether this interareal coherence occurs at an optimal phase relation that actually improves the stimulus transmission to behavioral report. We recorded local field potentials simultaneously from areas V1 and V4 of macaque monkeys performing a selective visual attention task, during which they reported changes of the attended stimulus. Gamma synchronization between V1 and V4, immediately preceding the stimulus change, predicted subsequent reaction times (RTs). Crucially, RTs were systematically slowed as trial-by-trial interareal gamma phase relations deviated from the phase relation at which V1 and V4 synchronized on average. These effects were specific to the attended stimulus and not due to local power or phase inside V1 or V4. We conclude that interareal gamma synchronization occurs at the optimal phase relation and thereby improves interareal communication and the effective transformation of sensory inputs into motor responses.

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bioRxiv2017

A Theta Rhythm In Awake Macaque V1 And V4 And Its Attentional Modulation

Theta rhythms govern rodent sniffing and whisking, and human language processing. Human psychophysics suggests a role for theta also in visual attention. Yet, little is known about theta in visual areas and its attentional modulation. We used electrocorticography (ECoG) to record local field potentials (LFPs) simultaneously from areas V1, V2, V4 and TEO of two macaque monkeys performing a selective visual attention task. We found a {approx}4 Hz theta rhythm within both the V1-V2 and the V4-TEO region, and theta synchronization between them, with a predominantly feedforward directed influence. ECoG coverage of large parts of these regions revealed a surprising spatial correspondence between theta and visually induced gamma. Furthermore, gamma power was modulated with theta phase. Selective attention to the respective visual stimulus strongly reduced these theta-rhythmic processes, leading to an unusually strong attention effect for V1. Microsaccades (MSs) were partly locked to theta. Yet, neuronal theta rhythms tended to be even more pronounced for epochs devoid of MSs. Thus, we find an MS-independent theta rhythm specific to visually driven parts of V1-V2, which rhythmically modulates local gamma and entrains V4-TEO, and which is strongly reduced by attention. We propose that the less theta-rhythmic and thereby more continuous processing of the attended stimulus serves the exploitation of this behaviorally most relevant information. The theta-rhythmic and thereby intermittent processing of the unattended stimulus likely reflects the ecologically important exploration of less relevant sources of information.

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