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Lecoq, J.

Publications and source records attributed to Lecoq, J..

At least 19 recordsLinked to original sources
bioRxiv2026

Moving object generates topographic responses in the majority of entorhinal neurons

Vision is crucial in generating a complex array of responses in rodents during spatial exploration and in humans during memory tasks. These tasks involve other variables too, e.g. multisensory cues in rodents and complex memories in humans. Further, there are major differences between the medial and lateral entorhinal cortical (MEC and LEC) functional cell types. To understand the contribution of purely visual information to entorhinal responses, we presented a simple, moving vertical bar of light to head-fixed mice, without any task or reward. Surprisingly, 66% (2391/3601) of the MEC broad spiking neurons were significantly modulated by the bar position on the screen. Visual tuning in MEC had a pronounced dorsoventral topography --the tuning strength dropped from 79% in the dorsal most quartile to 40% in the ventral most quartile. Unlike major differences in spatial and other codes between MEC and LEC during free foraging experiments, LEC cells showed very similar visual tuning (392/606, 65%), including the dorso-ventral gradient in LEC5. Additionally, the majority of putative interneurons, from MEC as well as LEC, showed similar, widespread visual tuning, unlike spatial tasks. Neurons also encoded the object motion direction (naso-temporal vs. temporo-nasal visual motion) with changes in mean rate, tuning strength and/or tuning location. Such directional nature of visual tuning indicates significant history-dependence or sequence encoding. Consistently, replacing the continuous motion by randomly flashing bar of light abolished bar-tuning in two-thirds of continuous bar-tuned cells and substantially altered tuning in the rest. These results reveal the contribution of purely visual inputs in generating anatomically organized responses in the majority of entorhinal neurons. The prevalence and similarity of visual tuning across all layers of MEC as well as LEC exceeds that of other known functional cell types (like grid cells in MEC or egocentric object tuning/time-cells in LEC) during spatial navigation tasks and could be foundational in understanding entorhinal complexity.

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bioRxiv2025

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies

1In 1949, Donald Hebb proposed that groups of neurons that activate stereotypically form the organizational building blocks of perception, cognition, and behavior. Finding the structural underpinning of such assemblies has been technically challenging, due to a lack of large-scale structure-activity maps. Here, we analyze this relation using a novel dataset that links in vivo optical physiology to connectivity using postmortem elec-tron microscopy (EM). From the fluorescence traces, we extract neural assemblies from higher-order correlations in neural activity. Physiologically, we show that these assemblies exhibit properties consistent with Hebbs theory, including more reliable responses to repeated natural movie inputs than size-matched random ensembles and superior decoding of visual stimuli. Structurally, we find that neurons that participate in assemblies are significantly more integrated into the structural network than those that do not. Contrary to Hebbs original prediction, we do not observe a marked increase in the strength of monosynaptic excitatory connections between cells participating in the same assembly. However, we find significantly stronger indirect feed-forward inhibitory connections targeting cells in other assemblies. These results show that assemblies can be useful components of perception, and, surprisingly, they are delineated by mutual inhibition.

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bioRxiv2024

Unexpected events modulate context signaling in VIP and excitatory cells of the visual cortex

The visual cortex predicts incoming sensory stimuli through internal models of the world. Unexpected stimuli that violate these predictions update internal models and drive adaptation. Cortical inhibitory neurons, particularly VIP (vasoactive intestinal peptide) interneurons, are suggested to play a key role in representing unexpected stimuli, given their robust firing following unexpected omissions of familiar images. Importantly, this response is stimulus non-specific, raising an important question about what information it conveys. Given their unique connectivity with other cell types and brain areas, we hypothesized that during unexpected events, VIP neurons encode contextual information, defined as neuronal activity that is not driven by the stimulus itself. To test this hypothesis, we analyzed the Allen Institute Visual Behavior dataset, in which mice viewed repeated familiar images and unexpected omissions of these images while two-photon calcium imaging data from different cell types and visual areas were recorded. Using dimensionality reduction techniques, we found that omissions trigger contextual signaling in VIP neurons in the primary visual cortex (V1) and the lateral medial (LM) visual area, particularly in the superficial layers. Similarly, contextual coding was enhanced in excitatory neurons following omissions. This contrasted sharply with the excitatory response to expected images, during which contextual information was substantially suppressed. Our results suggest that unexpected events activate VIP neurons, which subsequently propagate contextual information across the cortical network. This potentially facilitates the integration of context within the cortical network, and leads to updated predictions about our dynamic environment.

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bioRxiv2023

Recurrent pattern completion drives the neocortical representation of sensory inference

When sensory information is incomplete or ambiguous, the brain relies on prior expectations to infer perceptual objects. Despite the centrality of this process to perception, the neural mechanism of sensory inference is not known. Illusory contours (ICs) are key tools to study sensory inference because they contain edges or objects that are implied only by their spatial context. Using cellular resolution, mesoscale two-photon calcium imaging and multi-Neuropixels recordings in the mouse visual cortex, we identified a sparse subset of neurons in the primary visual cortex (V1) and higher visual areas that respond emergently to ICs. We found that these highly selective IC-encoders mediate the neural representation of IC inference. Strikingly, selective activation of these neurons using two-photon holographic optogenetics was sufficient to recreate IC representation in the rest of the V1 network, in the absence of any visual stimulus. This outlines a model in which primary sensory cortex facilitates sensory inference by selectively strengthening input patterns that match prior expectations through local, recurrent circuitry. Our data thus suggest a clear computational purpose for recurrence in the generation of holistic percepts under sensory ambiguity. More generally, selective reinforcement of top-down predictions by pattern-completing recurrent circuits in lower sensory cortices may constitute a key step in sensory inference.

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bioRxiv2023

Stimulus novelty uncovers coding diversity in visual cortical circuits

Detecting novel stimuli in the environment is critical for learning and survival, yet the neural basis of novelty processing is not understood. To characterize cell type-specific novelty processing, we surveyed the activity of [~]15,000 excitatory and inhibitory neurons in mice performing a visual task with novel and familiar stimuli. Clustering revealed a dozen functional neuron types defined by experience-dependent encoding. Vasoactive-intestinal-peptide (Vip) expressing inhibitory neurons were diverse, encoding novel stimuli, omissions of familiar stimuli, or behavioral features. Distinct Somatostatin (Sst) expressing inhibitory neurons encoded either familiar or novel stimuli. Subsets of excitatory neurons co-clustered with specific Vip or Sst subpopulations, while Sst and Vip inhibitory clusters were non-overlapping. This study establishes that novelty processing is mediated by diverse functional neuron types in the visual cortex.

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bioRxiv2021

Fast and statistically robust cell extraction from large-scale neural calcium imaging datasets

State-of-the-art Ca2+ imaging studies that monitor large-scale neural dynamics can produce video datasets that tally up to [~]100 TB in size ([~]10 days transfer over 1 Gbit/s ethernet). Processing such data volumes requires automated, general-purpose and fast computational methods for cell identification that are robust to a wide variety of noise sources. We present EXTRACT, an algorithm that is based on robust estimation theory and uses graphical processing units (GPUs) to extract neural dynamics from a typical Ca2+ video in computing times up to [~]10-times faster than imaging durations. We extensively validated EXTRACT on simulated and experimental data and processed 199 public datasets ([~]12 TB) from the Allen Institute in a day. Showcasing its superiority over past cell extraction methods at removing noise contaminants, neural activity traces from EXTRACT allow more accurate decoding of animal behavior. Overall, EXTRACT is a powerful computational tool matched to the present challenges of neural Ca2+ imaging studies in behaving animals.

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bioRxiv2021

Learning from unexpected events in the neocortical microcircuit

Scientists have long conjectured that the neocortex learns the structure of the environment in a predictive, hierarchical manner. According to this conjecture, expected, predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of information. It is theorized that the neocortex then changes the representation of incoming stimuli, guided by differences in the responses to expected and unexpected events. In line with this conjecture, different responses to expected and unexpected sensory features have been observed in spiking and somatic calcium events. However, it remains unknown whether these unexpected event signals occur in the distal apical dendrites where many top-down signals are received, and whether these signals govern subsequent changes in the brains stimulus representations. Here, we show that both somata and distal apical dendrites of cortical pyramidal neurons exhibit distinct unexpected event signals that systematically change over days. These findings were obtained by tracking the responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons over multiple days in primary visual cortex of awake, behaving mice using two-photon calcium imaging. Many neurons in both layers 2/3 and 5 showed large differences between their responses to expected and unexpected events. Interestingly, these responses evolved in opposite directions in the somata and distal apical dendrites. These differences between the somata and distal apical dendrites may be important for hierarchical computation, given that these two compartments tend to receive bottom-up and top-down information, respectively.

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bioRxiv2020

A standardized behavioral event equally impacts the activity of cortical visual areas and layers

Multiple recent studies have shown that motor activity greatly impacts the activity of primary sensory areas like V1. Yet, the role of this motor related activity in sensory processing is still unclear. Here we dissect how these behavior signals are broadcast to different layers and areas of the visual cortex. To do so, we leveraged a standardized and spontaneous behavioral fidget event in passively viewing mice. Importantly, this behavior event had no relevance to any ongoing task allowing us to compare its neuronal correlate with visually relevant behavior like running. A large two-photon Ca2+ imaging database of neuronal responses uncovered four neural response types during fidgets that were surprisingly consistent in their proportion and response patterns across all visual areas and layers of the visual cortex. Indeed, the layer and area identity could not be decoded above chance level based only on neuronal recordings. In contrast to running behavior, fidget evoked neural responses were independent to visual processing. The broad availability of visually orthogonal standardized behavior signals could be a key component in how the cortex selects, learns and binds local sensory information with motor outputs. Contrary to relevant motor outputs, irrelevant motor signals would use a separate neural subspaces. Significance StatementRecent studies have shown contextual and behavioral variables to dominate brain-wide activity, but yet it is unknown how this information is broadcast across cortical layers and areas. Using a large two-photon dataset collected in mice passively viewing a battery of visual stimuli, we characterized the neuronal response of neurons of the visual cortex to a standardized fidget behavior. We found that as much as 47% of excitatory neurons show significant co-activity with fidgets. Throughout all areas and layers we recorded from, those responses were distributed across surprisingly consistent three neural response types. Further analysis showed no interaction between fidget neural events and cells visual stimulus responses, contrasting with feedback neural signals induced by running. These contrasting response distribution patterns suggest that behavioral neuronal correlates are broadly available but will modulate sensory responses depending on their relevance to local sensory inputs.

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bioRxiv2020

Measuring stimulus-evoked neurophysiological differentiation in distinct populations of neurons in mouse visual cortex

Despite significant progress in understanding neural coding, it remains unclear how the coordinated activity of large populations of neurons relates to what an observer actually perceives. Since neurophysiological differences must underlie differences among percepts, differentiation analysis--quantifying distinct patterns of neurophysiological activity--is an "inside out" approach that addresses this question. We used two-photon calcium imaging in mice to systematically survey stimulus-evoked neurophysiological differentiation in excitatory populations across 3 cortical layers (L2/3, L4, and L5) in each of 5 visual cortical areas (primary, lateral, anterolateral, posteromedial, and anteromedial) in response to naturalistic and phase-scrambled movie stimuli. We find that unscrambled stimuli evoke greater neurophysiological differentiation than scrambled stimuli specifically in L2/3 of the anterolateral and anteromedial areas, and that this effect is modulated by arousal state and locomotion. Contrariwise, decoding performance was far above chance and did not vary substantially across areas and layers. Differentiation also differed within the unscrambled stimulus set, suggesting that differentiation analysis may be used to probe the ethological relevance of individual stimuli.

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bioRxiv2020

Removing independent noise in systems neuroscience data using DeepInterpolation

Progress in nearly every scientific discipline is hindered by the presence of independent noise in spatiotemporally structured datasets. Three widespread technologies for measuring neural activity--calcium imaging, extracellular electrophysiology, and fMRI--all operate in domains in which shot noise and/or thermal noise deteriorate the quality of measured physiological signals. Current denoising approaches sacrifice spatial and/or temporal resolution to increase the Signal-to-Noise Ratio of weak neuronal events, leading to missed opportunities for scientific discovery. Here, we introduce DeepInterpolation, a general-purpose denoising algorithm that trains a spatio-temporal nonlinear interpolation model using only noisy samples from the original raw data. Applying DeepInterpolation to in vivo two-photon Ca2+ imaging yields up to 6 times more segmented neuronal segments with a 15 fold increase in single pixel SNR, uncovering network dynamics at the single-trial level. In extracellular electrophysiology recordings, DeepInterpolation recovered 25% more high-quality spiking units compared to a standard data analysis pipeline. On fMRI datasets, DeepInterpolation increased the SNR of individual voxels 1.6-fold. All these improvements were attained without sacrificing spatial or temporal resolution. DeepInterpolation could well have a similar impact in other domains for which independent noise is present in experimental data.

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bioRxiv2020

Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of neurons in the brain. While these two modalities have distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging or electrophysiology. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging. This work explores which data transformations are most useful for explaining these modality-specific discrepancies. We show that the higher selectivity in imaging can be partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could not reconcile differences in responsiveness without sub-selecting neurons based on event rate or level of signal contamination. This suggests that differences in responsiveness more likely reflect neuronal sampling bias or cluster-merging artifacts during spike sorting of electrophysiological recordings, rather than flaws in event detection from fluorescence time series. This work establishes the dominant impacts of the two modalities respective biases on a set of functional metrics that are fundamental for characterizing sensory-evoked responses.

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bioRxiv2020

A standardized head-fixation system for performing large-scale, in-vivo physiological recordings in mice

BACKGROUNDThe Allen Institute recently built a set of high-throughput experimental pipelines to collect comprehensive in vivo surveys of physiological activity in the visual cortex of awake, head-fixed mice. Developing these large-scale, industrial-like pipelines posed many scientific, operational, and engineering challenges. NEW METHODOur strategies for creating a cross-platform reference space to which all pipeline datasets were mapped required development of 1) a robust headframe, 2) a reproducible clamping system, and 3) data-collection systems that are built, and maintained, around precise alignment with a reference artifact. RESULTSWhen paired with our pipeline clamping system, our headframe exceeded deflection and reproducibility requirements. By leveraging our headframe and clamping system we were able to create a cross-platform reference space to which multi-modal imaging datasets could be mapped. COMPARISON WITH EXISTING METHODSTogether, the Allen Brain Observatory headframe, surgical tooling, clamping system, and system registration strategy create a unique system for collecting large amounts of standardized in vivo datasets over long periods of time. Moreover, the integrated approach to cross-platform registration allows for multi-modal datasets to be collected within a shared reference space. CONCLUSIONSHere we report the engineering strategies that we implemented when creating the Allen Brain Observatory physiology pipelines. All of the documentation related to headframe, surgical tooling, and clamp design has been made freely available and can be readily manufactured or procured. The engineering strategy, or components of the strategy, described in this report can be tailored and applied by external researchers to improve data standardization and stability.

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bioRxiv2019

Widespread presence of direction-reversing neurons in the mouse visual system

Direction selectivity - the preference of motion in one direction over the opposite - is a fundamental property of visual neurons across species. We find that a substantial proportion of direction selective neurons in the mouse visual system reverse their preferred direction of motion in response to drifting gratings at different spatiotemporal parameters. A spatiotemporally asymmetric filter model recapitulates our experimental observations.

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bioRxiv2019

A survey of spiking activity reveals a functional hierarchy of mouse corticothalamic visual areas

The mammalian visual system, from retina to neocortex, has been extensively studied at both anatomical and functional levels. Anatomy indicates the cortico-thalamic system is hierarchical, but characterization of cellular-level functional interactions across multiple levels of this hierarchy is lacking, partially due to the challenge of simultaneously recording activity across numerous regions. Here, we describe a large, open dataset (part of the Allen Brain Observatory) that surveys spiking from units in six cortical and two thalamic regions responding to a battery of visual stimuli. Using spike cross-correlation analysis, we find that inter-area functional connectivity mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas. Classical functional measures of hierarchy, including visual response latency, receptive field size, phase-locking to a drifting grating stimulus, and autocorrelation timescale are all correlated with the anatomical hierarchy. Moreover, recordings during a visual task support the behavioral relevance of hierarchical processing. Overall, this dataset and the hierarchy we describe provide a foundation for understanding coding and dynamics in the mouse cortico-thalamic visual system.

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bioRxiv2019

On the correspondence of electrical and optical physiology in in vivo population-scale two-photon calcium imaging.

Multiphoton calcium imaging is commonly used to monitor the spiking of large populations of neurons. Recovering action potentials from fluorescence necessitates calibration experiments, often with simultaneous imaging and cell-attached recording. Here we performed calibration for imaging conditions matching those of the Allen Brain Observatory. We developed a novel crowd-sourced, algorithmic approach to quality control. Our final data set was 50 recordings from 35 neurons in 3 mouse lines. Our calibration indicated that 3 or more spikes were required to produce consistent changes in fluorescence. Moreover, neither a simple linear model nor a more complex biophysical model accurately predicted fluorescence for small numbers of spikes (1-3). We observed increases in fluorescence corresponding to prolonged depolarizations, particularly in Emx1-IRES-Cre mouse line crosses. Our results indicate that deriving spike times from fluorescence measurements may be an intractable problem in some mouse lines.

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bioRxiv2019

Relationship between spiking activity and simultaneously recorded fluorescence signals in transgenic mice expressing GCaMP6

Two-photon calcium imaging is often used with genetically encoded calcium indicators (GECIs) to investigate neural dynamics, but the relationship between fluorescence and action potentials (spikes) remains unclear. Pioneering work linked electrophysiology and calcium imaging in vivo with viral GECI expression, albeit in a small number of cells. Here we characterized the spikefluorescence transfer function in vivo of 91 layer 2/3 pyramidal neurons in primary visual cortex in four transgenic mouse lines expressing GCaMP6s or GCaMP6f. We found that GCaMP6s cells have spike-triggered fluorescence responses of larger amplitude, lower variability and greater single-spike detectability than GCaMP6f. Mean single-spike detection rates at high spatiotemporal resolution measured in our data was >70% for GCaMP6s and ~40-50% for GCaMP6f (at 5% false positive rate). These rates are estimated to decrease to 25-35% for GCaMP6f under generally used population imaging conditions. Our ground-truth dataset thus supports more refined inference of neuronal activity from calcium imaging.

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bioRxiv2018

Remote focusing system for simultaneous dual-plane mesoscopic multiphoton imaging

We present a dual-plane mesoscopic imaging system capable of simultaneous image acquisition from two independent focal planes. The system was designed as an add-on to a recently introduced large field-of-view two-photon microscopy system, developed by Sofroniew, et al., eLife, 5, e14472, 2016. In this work, we merge two advanced multiphoton imaging technologies, i.e., temporal-division multiplexing and remote focusing, to maintain diffraction-limited resolution at both imaging planes, and achieve a more than 2-fold increase in the systems overall imaging throughput. We introduce a novel solution to decode temporally interleaved analog signals at nanosecond timescales to achieve high-speed time-multiplexed imaging. Detailed characterization and comparison of the modified and the original two-photon microscopy system was performed.\n\nOCIS Codes(190.4180) Multiphoton processes; (180.5810) Scanning microscopy; (170.2520) Fluorescence microscopy.

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