Biology subjects

Cottereau, B. R.

Publications and source records attributed to Cottereau, B. R..

10 recordsLinked to original sources

bioRxiv2026

Effects of aging on multiple object tracking under normal and altered viewing conditions

Multiple object tracking (MOT) is a core function of dynamic visual attention that relies on the ability to simultaneously monitor several moving objects. Although MOT performance is known to decline with age, and to depend on efficient oculomotor strategies, how these processes interact across the adult lifespan and under degraded visual input remains poorly understood. Here, we examined the effects of aging on MOT under normal and gaze-contingent viewing conditions simulating central and peripheral visual field loss. Sixty participants aged 20-80 years completed a MOT task while eye movements were recorded, enabling characterization of performance and oculomotor behavior across five viewing conditions. Behavioral results revealed a continuous decline in tracking performance across adulthood, indicating a graded rather than categorical effect of age. Performance was strongly reduced by visual-field restrictions, with the largest impairments under central vision occlusion. Eye-tracking analyses showed that better performance was associated with greater reliance on centroid-based gaze strategies, consistent with distributed monitoring of target configurations. Critically, older adults relied more on focal, target-based tracking under conditions simulating peripheral vision loss, and less on centroid-based strategies; this shift was associated with poorer performance. In contrast, oculomotor behavior during full-field viewing was largely preserved across age. Together, these findings suggest that aging affects multiple object tracking through combined sensory, attentional, and oculomotor mechanisms. Beyond a reduction in capacity, age-related decline also reflects systematic changes in visual sampling strategies during dynamic tracking.

animal behavior and cognition↗

bioRxiv2025

Cortical Processing for the Vestibular and Visual Input of Egomotion in Macaque Monkeys: Separate Networks with Targeted Convergence

The integration of visual and vestibular inputs during egomotion is fundamental for both postural and navigational control. In the present study, we used functional magnetic resonance imaging (fMRI) in four macaque monkeys to investigate cortical activation in response to galvanic vestibular stimulation (GVS), applied through transmastoid electrodes, and egomotion-compatible (EC) optic flow patterns. Visual and vestibular stimulations activate two largely independent cortical networks: the vestibular network encompasses the insular cortex, superior parietal lobule, frontal lobe, and cingulate cortex, while optic flow primarily activates regions in the superior temporal sulcus, temporo-parietal junction, inferior parietal lobule, and restricted portions of the cingulate and frontal cortices. Despite this segregation, several areas exhibit visuo-vestibular convergence: VPS in the temporo-parietal junction, area 7 in the inferior parietal lobule, VIP and LIP in the intraparietal sulcus, MSTd in the superior temporal sulcus, CSv in the cingulate sulcus, and FEFsem in the frontal cortex. These findings demonstrate that visual and vestibular signals generated by egomotion are processed in extended and distinct cortical networks with several narrow convergence sites, consistent with the idea that multisensory integration during self-motion is achieved through selective convergence rather than general network overlap.

neuroscience↗

bioRxiv2025

Motion processing in visual cortex of maculopathy patients

Previous studies on animal models suggested that visual areas involved in motion processing could undergo important cortical reorganizations following retinal damages. This could have major implications for patients suffering from macular degeneration (MD), one leading cause of vision loss. Here, we performed fMRI recordings in a group of maculopathy patients (including individuals suffering from age-related macular degeneration or from Stargardts Disease) and a control group to characterize the motion processing cortical network in MD patients and determine whether this network is modified following the onset of the scotoma. We used an experimental protocol based on random-dot kinematograms (RDKs) classically employed to characterize motion-selective areas in the brain. To ensure that the visual information processed by the two groups was equivalent, the visual field in each control participant was masked using an artificial scotoma directly derived from clinical measurements in their paired patient. We found that in MD patients, translational motion elicited significant and robust activations in a restricted cortical network which included the human V5/MT+ complex (hMT+), areas V3A and V6, and a portion of primary visual areas (V1, V2 and V3) connected to peripheral vision. Importantly, the same patterns of responses were also observed in control participants. Moreover, the extent and strength of activation within these motion-selective areas did not differ significantly between the two groups. Altogether, these results suggest that in humans, the motion-selective network does not undergo significant large-scale cortical reorganizations following the onset of MD. Significance statementMotion processing in the visual cortex of patients with macular degeneration has never been characterized. Here, we performed fMRI recordings in 7 maculopathy patients and found robust motion-selective activations in a cortical network which included the human V5/MT+ complex (hMT+), areas V3A and V6, and a portion of primary visual areas connected to peripheral vision. These activations closely align with those reported in participants with normal vision in the literature and do not significantly differ from those measured in a group of age and gender-matched control participants who viewed the motion stimuli with a matched artificial scotoma. Altogether, our results suggest that the motion-selective network does not undergo significant large-scale reorganizations in maculopathy patients following the onset of the scotoma.

neuroscience↗

bioRxiv2025

Temporal recurrence as a general mechanism toexplain neural responses in the auditory system

Computational models of neural processing in the auditory cortex usually ignore that neurons have an internal memory: they characterize their responses from simple convolutions with a finite temporal window of arbitrary duration. To circumvent this limitation, we propose here a new, simple and fully recurrent neural network (RNN) architecture incorporating cutting-edge computational blocks from the deep learning community and constituting the first attempt to model auditory responses with deep RNNs. We evaluated the ability of this approach to fit neural responses from 8 publicly available datasets, spanning 3 animal species and 6 auditory brain areas, representing the largest compilation of this kind. Our recurrent models significantly out-perform previous methods and a new Transformer-based architecture of our design on this task, suggesting that temporal recurrence is the key to explain auditory responses. Finally, we developed a novel interpretation technique to reverse-engineer any pretrained model, regardless of their stateful or stateless nature. Largely inspired by works from explainable artificial intelligence (xAI), our method suggests that auditory neurons have much longer memory (several seconds) than indicated by current STRF techniques. Together, these results highly motivate the use of deep RNNs within computational models of sensory neurons, as protean building blocks capable of assuming any function.

neuroscience↗

bioRxiv2024

A general theoretical framework unifying the adaptive, transient and sustained properties of ON and OFF auditory neural responses

Sounds are temporal stimuli decomposed into numerous elementary components by the auditory nervous system. For instance, a temporal to spectro-temporal transformation modelling the frequency decomposition performed by the cochlea is a widely adopted first processing step in todays computational models of auditory neural responses. Similarly, increments and decrements in sound intensity (i.e., of the raw waveform itself or of its spectral bands) constitute critical features of the neural code, with high behavioural significance. However, despite the growing attention of the scientific community on auditory OFF responses, their relationship with transient ON, sustained responses and adaptation remains unclear. In this context, we propose a new general model, based on a pair of linear filters, named AdapTrans, that captures both sustained and transient ON and OFF responses into a unifying and easy to expand framework. We demonstrate that filtering audio cochleagrams with AdapTrans permits to accurately render known properties of neural responses measured in different mammal species such as the dependence of OFF responses on the stimulus fall time and on the preceding sound duration. Furthermore, by integrating our framework into gold standard and state-of-the-art machine learning models that predict neural responses from audio stimuli, following a supervised training on a large compilation of electrophysiology datasets (ready-to-deploy PyTorch models and pre-processed datasets shared publicly), we show that AdapTrans systematically improves the prediction accuracy of estimated responses within different cortical areas of the rat and ferret auditory brain. Together, these results motivate the use of our framework for computational and systems neuroscientists willing to increase the plausibility and performances of their models of audition.

neuroscience↗

bioRxiv2021

Symmetry processing in the macaque visual cortex

Symmetry is a highly salient feature of the natural world that is perceived by many species of the animal kingdom and that impacts a large array of behaviours such as partner selection or food choice. In humans, the cerebral areas processing symmetry are now well identified from neuroimaging measurements. However, we currently lack an animal model to explore the underlying neural mechanisms. Macaque is a potentially good candidate, but a previous comparative study (1) found that functional magnetic resonance imaging (fMRI) responses to mirror symmetry in this species were substantially weaker than those observed in humans under similar experimental conditions. Here, we re-examined symmetry processing in macaques from a broader perspective, using both rotation (experiment 1) and reflection (experiment 2) symmetry. Our experimental design was directly derived from that of a previous human fMRI study (2), in order to facilitate the comparison between the two primate species. Highly consistent responses to symmetry were found in a large network of areas (notably V3, V3A, V4, V4A and PITd), in line with what has been observed in humans. Within this network, response properties in areas V3 and V4 (notably their dependency on the rotation symmetry order) were strikingly similar to those observed in their human counterparts. Our results suggest that the cortical networks that process symmetry in humans and macaques are much more similar than previously reported and point toward macaque as a relevant model for understanding symmetry processing. Significance statementSymmetry processing is an important aspect of human visual perception. We currently lack an animal model for characterizing the neural mechanisms that underlie it at the microscopic scale. Here, we use fMRI measurements in macaques to demonstrate that the cortical responses to symmetry in this species are comparable to those observed in humans under similar experimental conditions to a much higher extent than previously documented. Our results call for a re-examination of the relevance of the macaque model for symmetry processing in humans and open the door to an exploration of the underlying neural mechanisms at the single-cell level, notably in V3, an area often neglected in most current models of visual processing.

neuroscience↗

bioRxiv2019

Sub-optimality of the early visual system explained through biologically plausible plasticity

The early visual cortex is the site of crucial pre-processing for more complex, biologically relevant computations that drive perception and, ultimately, behaviour. This pre-processing is often viewed as an optimisation which enables the most efficient representation of visual input. However, measurements in monkey and cat suggest that receptive fields in the primary visual cortex are often noisy, blobby, and symmetrical, making them sub-optimal for operations such as edge-detection. We propose that this suboptimality occurs because the receptive fields do not emerge through a global minimisation of the generative error, but through locally operating biological mechanisms such as spike-timing dependent plasticity. Using an orientation discrimination paradigm, we show that while sub-optimal, such models offer a much better description of biology at multiple levels: single-cell, population coding, and perception. Taken together, our results underline the need to carefully consider the distinction between information-theoretic and biological notions of optimality in early sensorial populations.

systems biology↗

bioRxiv2019

Stereomotion processing in the non-human primate brain

The cortical areas that process disparity-defined motion-in-depth (i.e. cyclopean stereomotion) were characterised with functional magnetic resonance imaging in two awake, behaving macaques. The experimental protocol was similar to previous human neuroimaging studies. We contrasted the responses to dynamic random-dot patterns that continuously changed their binocular disparity over time with those to a control condition that shared the same properties, except that the temporal frames were shuffled. A whole-brain voxel-wise analysis revealed that in all four cortical hemispheres, three areas showed consistent sensitivity to cyclopean stereomotion. Two of them were localised respectively in the lower bank of the superior temporal sulcus (CSMSTS) and on the neighbouring infero-temporal gyrus (CSMITG). The third area was situated in the posterior parietal cortex (CSMPPC). Additional ROIs-based analyses within retinotopic areas defined in both animals indicated weaker but significant responses to cyclopean stereomotion within the MT cluster (most notably in areas MSTv and FST). Altogether, our results are in agreement with previous findings in both human and macaque and suggest that the cortical networks that process cyclopean stereomotion is relatively well preserved between the two primate species.

neuroscience↗

bioRxiv2019

Antero-posterior versus lateral vestibular input processing in human visual cortex

Visuo-vestibular integration is crucial for locomotion, yet cortical mechanisms involved remain poorly understood. We combined binaural monopolar galvanic vestibular stimulation (GVS) and functional magnetic resonance imaging (fMRI) to characterize the cortical networks activated during antero-posterior and lateral stimulations in humans. We focused on functional areas that selectively respond to egomotion-consistent optic flow patterns: the human middle temporal complex (hMT+), V6, the ventral intraparietal (VIP) area, the cingulate sulcus visual (CSv) area and the posterior insular cortex (PIC). Areas hMT+, CSv, and PIC were equivalently responsive during lateral and antero-posterior GVS while areas VIP and V6 were highly activated during antero-posterior GVS but remained silent during lateral GVS. Using psychophysiological interaction (PPI) analyses, we confirmed that a cortical network including areas V6 and VIP is engaged during antero-posterior GVS. Our results suggest that V6 and VIP play a specific role in processing multisensory signals specific to locomotion during navigation.

neuroscience↗

bioRxiv2017

Emergence of binocular disparity selectivity through Hebbian learning

Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Foldiak, 1989; Atick and Redlich, 1992; Olshausen and Field, 1996), an explanation as to how the cortex develops the structures to support these encoding schemes remains elusive. Here, using the more realistic example of binocular vision as opposed to monocular luminance-field images, we show how a simple Hebbian coincidence-detector is capable of accounting for the emergence of binocular, disparity selective, receptive fields. We propose a model based on spike-timing dependent plasticity (STDP) which not only converges to realistic single-cell and population characteristics, but also demonstrates how known biases in natural statistics may influence population encoding and downstream correlates of behaviour. Furthermore, we show that the receptive fields we obtain are closer in structure to electrophysiological data than those predicted by normative encoding schemes (Ringach, 2002). We also demonstrate the robustness of our model to the input dataset, noise at various processing stages, and internal parameter variation. Taken together, our modelling results suggest that Hebbian coincidence-detection is an important computational principle and could provide a biologically plausible mechanism for the emergence of selectivity to natural statistics in the early sensory cortex.

neuroscience↗