Biology subjects

Chavane, F.

Publications and source records attributed to Chavane, F..

13 recordsLinked to original sources

bioRxiv2026

Improved detection and spatiotemporal spectral analysis of neural traveling waves

Traveling waves (TWs) are a fundamental mode of neural dynamics, yet existing detection methods are limited by sensor geometry, spatial-frequency resolution, signal amplitude, and ambiguity between propagating and standing-wave patterns. Here we introduce the Traveling Wave Index (TWINDEX), a framework for three-dimensional spatiotemporal spectral analysis of TWs across temporal frequency, spatial frequency, and propagation direction. TWINDEX generalizes to irregular sensor layouts, and quantifies wave strength as the reduction in circular phase variance produced by a candidate planar wave. This normalization yields robust behavior at both low and high spatial frequencies and suppresses coherent in-phase activity. Directional moments further separate planar from standing waves. We derive analytical links between TWINDEX, parametric planar-wave fit, and distance-phase correlation, and introduce projected distance-phase correlation (ProDPC) for sensitive single-trial planar-wave detection. Applying these methods to large-scale marmoset ECoG and human EEG, we identify alpha/low-beta TWs localized in spatial and temporal frequency, with physiologically plausible propagation speeds. Across trials and epochs, waves occur in oppositely directed propagation modes, demonstrating that alpha/beta activity is associated with both feedforward- and feedback-directed large-scale dynamics.

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bioRxiv2026

Information Flow and Traveling Waves show distinct cortical trajectories

Traveling waves (TWs) are a hallmark of cortical dynamics, proposed to organize neuronal activity across space and time. Yet their propagation can oppose the causal flow of information, challenging their functional interpretation. We demonstrate this using computational simulations and validate our predictions in electrophysiological recordings. We introduce the Directional Information Flow Field (DIFF), which adapts Granger causality to two-dimensional neural recordings to map directed interactions across cortical networks. In computational models, DIFF recovers the direction and sources of information flow, whereas delays and inhibition can cause TWs to propagate in opposing or orthogonal directions. We validate these findings in human and non-human primate electrophysiological recordings, revealing reversed or orthogonal flow axes, distinct spatial origins, and frequency-dependent differences in feedforward and feedback dynamics. These findings challenge the functional interpretation of TWs and establish DIFF as a complementary framework for revealing directed neural communication underlying cortical dynamics.

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bioRxiv2025

Cortical Origins of the Flash-Lag Effect distortions: The Influence of Retinotopic Map Architecture

The flash-lag effect (FLE) is an illusion whereby the position of a moving object is perceived as being offset in the direction of movement when compared to a flashed static stimulus. This perceptual misalignment has been posited as a key phenomenon in explaining our ability to accurately predict the future position of moving objects, despite the delays in neuronal processing. Our working hypothesis is that the FLE is resulting from the anticipation generated by propagation of neural activity within visual cortical retinotopical maps. According to this hypothesis, the FLE should be affected by discontinuities and anisotropies of the retinotopic map architecture. Using psychophysics we show that the FLE is strongly affected by crossing and the direction of motion in respect to retinotopic features, such as vertical and horizontal meridians and the fovea. The specificity of how early visual cortical retinotopic maps are splitted and magnified around these features led us to suggest that the FLE distortions emerge from propagation in retinotopically organized networks, particularly V1. This work bridges the gap between human psychophysics and the known constraints of retinotopic maps layout, offering a testable framework for future studies of motion position encoding in the visual hierarchy.

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bioRxiv2025

Chamber Implant for Chronic Optical Recordings from the Cerebral Cortex of Marmosets

We describe a novel imaging chamber for chronic optical recordings from the marmoset cerebral cortex, together with the surgery needed for its implantation and that of an associated headpost. MRI data allow optimizing positioning on the skull. The chamber is implanted into a precisely matched craniotomy, improving mechanical stability. For maximal biocompatibility, chamber and headpost are made out of titanium. It consists of an outer cylinder into which screws adjustably an inner one, called "well", with a glass window on its bottom. This allows easy opening and closing whenever access to the cortex is needed, while preserving a sterile seal when closed. Moreover, simply rotating the well allows fine adjustment of the windows distance with respect to the underlying cortex. Together with using a curved - rather than flat - glass window, this allows achieving gentle but continuous contact with the underlying cortex, which helps to delay tissue regrowth, notably of a neomembrane that must otherwise be surgically removed. The chambers sealing system combines a silicone elastomer and O-ring, minimizing infection risk and CSF leakage. Data from longitudinal two-photon imaging using genetically encoded fluorescent calcium sensors reveal high optical quality over months, with excellent resolution of neurons and their activity. We also demonstrate the feasibility of two-photon imaging of genetically encoded voltage sensors in the marmoset cortex in-vivo. Finally, although the chamber provides a durable, adaptable solution for long-term imaging studies in marmosets already in its current version, we discuss a few straightforward modifications that could likely improve its performance even further.

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bioRxiv2025

What do neural travelling waves tell us about information flow?

In many behavioral conditions, neural activity manifests itself within and across brain regions as traveling waves, revealing the importance of analyzing spatiotemporal dynamics in electrophysiological data. Most methods detect traveling waves by measuring spatial phase gradients, i.e., monotonic and ordered phase changes through space. It is unclear, however, how these traveling waves relate to the causal directionality of information flow. Here, we analyze systems of coupled nodes with an external input to one node. We demonstrate that the phase ordering in traveling waves does not always correspond to the direction of effective information flow. We show that discrepancies can emerge in the case of systems with delays and inhibitory influences. As a methodological solution, we show that Granger causality analysis can, in linear systems, recover the directionality of the information flow. We propose a new measure called DIFF, the Directional Information Flow Field. DIFF is constructed by analyzing directed causal influences in space and time between neighbours, yielding a vector field. As a proof of principle, we show that, in a 2D field where a connected network is perturbed by an external input, the Divergence of DIFF can identify the spatial source of the perturbations. We propose that causal inference methods provide complementary information to phase-based traveling wave methods in analyzing system dynamics and information flow.

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bioRxiv2021

Pooling in a predictive model of V1 explains functional and structural diversity across species

Neurons in the primary visual cortex are selective to orientation with various degrees of selectivity to the spatial phase, from high selectivity in simple cells to low selectivity in complex cells. Various computational models have suggested a possible link between the presence of phase invariant cells and the existence of cortical orientation maps in higher mammals V1. These models, however, do not explain the emergence of complex cells in animals that do not show orientation maps. In this study, we build a model of V1 based on a convolutional network called Sparse Deep Predictive Coding (SDPC) and show that a single computational mechanism, pooling, allows the SDPC model to account for the emergence of complex cells as well as cortical orientation maps in V1, as observed in distinct species of mammals. By using different pooling functions, our model developed complex cells in networks that exhibit orientation maps (e.g., like in carnivores and primates) or not (e.g., rodents and lagomorphs). The SDPC can therefore be viewed as a unifying framework that explains the diversity of structural and functional phenomena observed in V1. In particular, we show that orientation maps emerge naturally as the most cost-efficient structure to generate complex cells under the predictive coding principle. SignificanceCortical orientation maps are among the most fascinating structures observed in higher mammals brains: In such maps, similar orientations in the input image activate neighboring cells in the cortical surface. However, the computational advantage brought by these structures remains unclear, as some species (rodents and lagomorphs) completely lack orientation maps. In this study, we introduce a computational model that links the presence of orientation maps to a class of nonlinear neurons called complex cells. In particular, we propose that the presence or absence orientation maps correspond to different strategies employed by different species to generate invariance to complex stimuli.

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bioRxiv2021

Dynamical processing of orientation precision in the primary visual cortex

In our daily visual environment, the primary visual cortex (V1) processes distributions of oriented features as the basis of our visual computations. Changes of the global, median orientation of such inputs form the basis of our canonical knowledge about V1. However, another overlooked but defining characteristic of these sensory variables is their precision, which characterizes the level of variance in the input to V1. Such variability is an intrinsic part of natural images, yet it remains unclear if and how V1 accounts for the changes in orientation precision to achieve its robust orientation recognition performances. Here, we used naturalistic stimuli to characterize the response of V1 neurons to quantified variations of orientation precision. We found that about thirty percent of the recorded neurons showed a form of invariant responses to input precision. While feedforward mechanisms failed to account for the existence of these resilient neurons, neuronal competition within V1 explained the extent to which a neuron is invariant to precision. Using a decoding algorithm, we showed that the existence of such neurons in the population response of V1 can serve to encode both the orientation and its precision in the V1 population activity, which improves the robustness of the overall neural code. These precision-specific neurons operate with slow recurrent cortical dynamics, which supports the notion of predictive precisionweighted processes in V1.

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bioRxiv2020

Anticipatory responses along motion trajectories in awake monkey area V1

What are the neural mechanisms underlying motion integration of translating objects? Visual motion integration is generally conceived of as a feedforward, hierarchical, information processing. However, feedforward models fail to account for many contextual effects revealed using natural moving stimuli. In particular, a translating object evokes a sequence of transient feedforward responses in the primary visual cortex but also propagations of activity through horizontal and feedback pathways. We investigated how these pathways shape the representation of a translating bar in monkey V1. We show that, for long trajectories, spiking activity builds-up hundreds of milliseconds before the bar enters the neurons receptive fields. Using VSDI and LFP recordings guided by a phenomenological model of propagation dynamics, we demonstrate that this anticipatory response arises from the interplay between horizontal and feedback networks driving V1 neurons well ahead of their feedforward inputs. This mechanism could subtend several perceptual contextual effects observed with translating objects. HighlightsO_LIOur hypothesis is that lateral propagation of activity in V1 contributes to the integration of translating stimuli C_LIO_LIConsistent with this hypothesis, we find that a translating bar induces anticipatory spiking activity in V1 neurons. C_LIO_LIA V1 model describes how this anticipation can arise from inter and intra-cortical lateral propagation of activity. C_LIO_LIThe dynamic of VSDi and LFP signals in V1 is consistent with the predictions made by the model. C_LIO_LIThe intra-cortical origin is further confirmed by the fact that a bar moving from the ipsilateral hemifield does not evoke anticipation. C_LIO_LIHorizontal and feedback input are not only modulatory but can also drive spiking responses in specific contexts. C_LI

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bioRxiv2020

Monocular vision is intrinsically unstable: a side-effect of binocular homeostasis

It is now accepted that short-term deprivation of one eye in adults results in not only a post-deprivation strengthening of the vision in the previously deprived eye but also a deterioration in the vision of the previously non-patched eye. Such monocular deprivation of 1-2 hours induces changes that last approximately 30-90 minutes. There is some support for this neuroplastic effect being the consequence of a change in the contrast gain within the binocular circuity. What is not known is when these changes in gain are initiated. One possibility is that they are initiated only once the patch is removed. The other possibility is that they are the result of a slow build up from the moment the patch is first applied. In this study, we measure monocular contrast detection thresholds of the non-deprived eye over time during the deprivation of the other eye. We show that contrast threshold increases over time during the deprivation of the other eye. This observation suggest that the patching effect is mediated by a slow build up over the deprivation period: reducing the vision of the non-deprived eye and enhancing the vision of the deprived eye reflecting reciprocal changes in sensitivity. These results highlight a hitherto unknown feature of human vision, namely that monocular vision per se is intrinsically unstable which is a consequence of the reciprocal inhibitory circuits that homeostatically regulate binocular vision. This questions a whole corpus of studies of visual function that rely on the assumption that monocular vision is intrinsically stable.

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bioRxiv2019

Revealing α oscillatory activity using voltage-sensitive dye imaging in monkey V1

The relevance of oscillations (7-12Hz) in neural processing, although recognized long ago, remains a major research question in the field. While intensively studied in humans, oscillations appear much less often investigated (and observed) in monkeys. Here we wish to provide data from non-human primates on stimulus-related rhythm. Indeed, in humans, EEG is enhanced in response to non-periodic dynamic visual stimulation ("perceptual echoes" or to a static stimulus ("flickering wheel illusion"). Do the same visual patterns induce an oscillatory response in monkey V1? We record voltage-sensitive dye signals from three anesthetized monkeys to investigate the population-based oscillatory neural response that is not resulting from attention-related feedback signals. We revealed oscillations in monkey V1 which, when they occur, react in a manner comparable to human studies.

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bioRxiv2019

Functional ultrasound imaging of deep visual cortex in awake non-human primates

Deep regions of the brain are not easily accessible to investigation at the mesoscale level in awake animals or humans. We have recently developed functional Ultrasound (fUS) imaging fUS imaging technique to uncover deep hemodynamic functional responses. Applying fUS imaging on two awake non-human primates performing a passive fixation task, we reconstructed their retinotopic maps down to the deep calcarine and lunate sulci on visual areas (V1, V2 and V3). These maps were acquired in a single hour session with very few stimuli presentation. The spatial resolution of the technology is illustrated by mapping of Ocular Dominance (OD) columns within superficial and deep layers of the primary visual cortex. These acquisitions showed that OD selectivity is mostly present in layer IV but with evidence also in layers II/III and V. The fUS imaging technology therefore provides a new mesoscale approach to map brain activities at high spatiotemporal resolution in awake subjects within the whole depth of the cortex.

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bioRxiv2018

Suppressive waves disambiguate the representation of long-range apparent motion in awake monkey V1

The \"apparent motion\" illusion is evoked when stationary stimuli are successively flashed in spatially separated positions. It depends on the precise spatial and temporal separations of the stimuli. For large spatiotemporal separation, the long-range apparent motion (lrAM), it remains unclear how the visual system computes unambiguous motion signals. Here we investigated whether intracortical interactions within retinotopic maps could shape a global motion representation at the level of V1 population in response to a lrAM. In fixating monkeys, voltage-sensitive dye imaging revealed the emergence of a spatio-temporal representation of the motion trajectory at the scale of V1 population activity, shaped by systematic backward suppressive waves. We show that these waves are the expected emergent property of a recurrent gain control fed by the horizontal intra-cortical network. Such non-linearities explain away ambiguous correspondence problems of the stimulus along the motion path, preformating V1 population response for an optimal read-out by downstream areas.

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bioRxiv2017

Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons

Voltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean-field formalism to model such signals. Here, we present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions. We study here a network of regular-spiking (RS) excitatory neurons and fast-spiking (FS) inhibitory neurons. We use a Master Equation formalism, together with a semi-analytic approach to the transfer function of AdEx neurons to describe the average dynamics of the coupled populations. We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the analytical description. Second, we investigate the response of the network to time-varying external input, and show that the mean-field model predicts the response time course of the population. Finally, to model VSDi signals, we consider a one-dimensional ring model made of interconnected RS-FS mean-field units. We found that this model can reproduce the spatio-temporal patterns seen in VSDi of awake monkey visual cortex as a response to local and transient visual stimuli. Conversely, we show that the model allows one to infer physiological parameters from the experimentally-recorded spatio-temporal patterns.

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