Frédéric Chavane

Imaging cortical correlates of illusion in early visual cortex

Exploring visual illusions reveals fundamental principles of cortical processing. Illusory motion perception of non-moving stimuli was described almost a century ago by Gestalt psychologists. However, the underlying neuronal mechanisms remain unknown. To explore cortical mechanisms underlying the ‘line-motion’ illusion, we used real-time optical imaging, which is highly sensitive to subthreshold activity. We examined, in the visual cortex of the anaesthetized cat, responses to five stimuli: a stationary small square and a long bar; a moving square; a drawn-out bar; and the well-known line-motion illusion, a stationary square briefly preceding a long stationary bar presentation. Whereas flashing the bar alone evoked the expected localized, short latency and high amplitude activity patterns, presenting a square 60–100 ms before a bar induced the dynamic activity patterns resembling that of fast movement. The preceding square, even though physically non-moving, created gradually propagating subthreshold cortical activity that must contribute to illusory motion, because it was indistinguishable from cortical representations of real motion in this area. These findings demonstrate the effect of spatio-temporal patterns of subthreshold synaptic potentials on cortical processing and the shaping of perception.

Lateral Spread of Orientation Selectivity in V1 is Controlled by Intracortical Cooperativity

Neurons in the primary visual cortex receive subliminal information originating from the periphery of their receptive fields (RF) through a variety of cortical connections. In the cat primary visual cortex, long-range horizontal axons have been reported to preferentially bind to distant columns of similar orientation preferences, whereas feedback connections from higher visual areas provide a more diverse functional input. To understand the role of these lateral interactions, it is crucial to characterize their effective functional connectivity and tuning properties. However, the overall functional impact of cortical lateral connections, whatever their anatomical origin, is unknown since it has never been directly characterized. Using direct measurements of postsynaptic integration in cat areas 17 and 18, we performed multi-scale assessments of the functional impact of visually driven lateral networks. Voltage-sensitive dye imaging showed that local oriented stimuli evoke an orientation-selective activity that remains confined to the cortical feedforward imprint of the stimulus. Beyond a distance of one hypercolumn, the lateral spread of cortical activity gradually lost its orientation preference approximated as an exponential with a space constant of about 1 mm. Intracellular recordings showed that this loss of orientation selectivity arises from the diversity of converging synaptic input patterns originating from outside the classical RF. In contrast, when the stimulus size was increased, we observed orientation-selective spread of activation beyond the feedforward imprint. We conclude that stimulus-induced cooperativity enhances the long-range orientation-selective spread.

Dynamics of local input normalization result from balanced short- and long-range intracortical interactions in area V1.

To efficiently drive many behaviors, sensory systems have to integrate the activity of large neuronal populations within a limited time window. These populations need to rapidly achieve a robust representation of the input image, probably through canonical computations such as divisive normalization. However, little is known about the dynamics of the corticocortical interactions implementing these rapid and robust computations. Here, we measured the real-time activity of a large neuronal population in V1 using voltage-sensitive dye imaging in behaving monkeys. We found that contrast gain of the population increases over time with a time constant of ∼30 ms and propagates laterally over the cortical surface. This dynamic is well accounted for by a divisive normalization achieved through a recurrent network that transiently increases in size after response onset with a slow swelling speed of 0.007–0.014 m/s, suggesting a polysynaptic intracortical origin. In the presence of a surround, this normalization pool is gradually balanced by lateral inputs propagating from distant cortical locations. This results in a centripetal propagation of surround suppression at a speed of 0.1–0.3 m/s, congruent with horizontal intracortical axons speed. We propose that a simple generalized normalization scheme can account for both the dynamical contrast response function through recurrent polysynaptic intracortical loops and for the surround suppression through long-range monosynaptic horizontal spread. Our results demonstrate that V1 achieves a rapid and robust context-dependent input normalization through a timely push–pull between local and lateral networks. We suggest that divisive normalization, a fundamental canonical computation, should be considered as a dynamic process.

Inhibition of corneal neovascularization after alkali burn: comparison of different doses of bevacizumab in monotherapy or associated with dexamethasone.

Background:  To compare the effects of different doses of bevacizumab with both saline and dexamethasone on inflammatory angiogenesis in the rat cornea induced by small chemical lesions.

Linear model decomposition for voltage-sensitive dye imaging signals: application in awake behaving monkey.

Voltage sensitive dye imaging (VSDI) is the only technique that allows to directly measure neuronal activity over a large cortical population. It thus gives access to the dynamics of lateral interactions within or between cortical areas. However, VSDI signal suffers from a weak signal-to-noise ratio and processing methods are either rudimentary or dedicated to spatial or temporal denoising alone. Here we present an innovative method inspired by fMRI data processing, where the goal is to allow, for the first time, denoising of spatio-temporally inseparable VSDI signals and in the most challenging experimental condition, i.e. single trials in awake behaving monkeys. The method is based on a linear model (LM) decomposition of individual VSDI trials. The LM was designed meticulously by identifying all noise and signal components that are known to affect VSDI. We then compared its output against the classical methods based on blank division and detrending. LM proved to be significantly much more efficient to denoise spatial maps and temporal dynamics compared to these usual techniques. It also largely reduced trial-to-trial variability. These performances resulted in a four-fold improvement of signal-to-noise ratio and a two-fold increase of response detectability. Hence, with this method, fewer trials were needed to reach a high signal-to-noise ratio. Lastly, we showed that the LM method can accommodate for a large range of response dynamics, a crucial property for estimating spatial spread of activity or contrast dynamics. We believe that this method will make a strong contribution to imaging dynamics of population responses with high spatial and temporal resolution in trial-based experiments of awake animals.

A biophysical cortical column model to study the multi-component origin of the VSDI signal

We propose a biological cortical column model, at an intermediate mesoscopic scale, in order to better understand and interpret biological sources of voltage-sensitive dye imaging signal (VSD signal). To perform a quantitative analysis of the relative contributions to the VSD signal, a detailed compartmental model was developed at a scale corresponding to one pixel of optical imaging. The generated model was used to solve the VSD direct problem, i.e. generate a VSD signal, given the neural substrate parameters and activities. Here, we confirm and quantify the fact that the VSD signal is the result of an average from multiple components. Not surprisingly, the compartments that mostly contribute to the signal are the upper layer dendrites of excitatory neurons. However, our model suggests that inhibitory cells, spiking activity and deep layers contributions are also significant and, more unexpected, are dynamically modulated with time and response strength.

Cortical travelling waves: mechanisms and computational principles

Multichannel recording technologies have revealed travelling waves of neural activity in multiple sensory, motor and cognitive systems. These waves can be spontaneously generated by recurrent circuits or evoked by external stimuli. They travel along brain networks at multiple scales, transiently modulating spiking and excitability as they pass. Here, we review recent experimental findings that have found evidence for travelling waves at single-area (mesoscopic) and whole-brain (macroscopic) scales. We place these findings in the context of the current theoretical understanding of wave generation and propagation in recurrent networks. During the large low-frequency rhythms of sleep or the relatively desynchronized state of the awake cortex, travelling waves may serve a variety of functions, from long-term memory consolidation to processing of dynamic visual stimuli. We explore new avenues for experimental and computational understanding of the role of spatiotemporal activity patterns in the cortex.

Post-implantation impedance spectroscopy of subretinal micro-electrode arrays, OCT imaging and numerical simulation: towards a more precise neuroprosthesis monitoring tool.

OBJECTIVE Previous studies have shown that single-frequency impedance measurements could provide useful information about the distance between the neuroprosthesis and the retina. This work investigates the use of impedance spectroscopy in monitoring subretinal implantations of flexible micro-electrode arrays and focuses on determining what is governing impedance profiles. APPROACH In this study, we use impedance spectroscopy together with optical coherence tomography imaging and numerical simulation to quantitatively evaluate the constituent elements of measured impedance. MAIN RESULTS We show the existence of specific impedance spectrum profiles for retinal detection and retinal detachment that are in good agreement with numerical simulations. These simulations suggest that monopolar impedance is mainly influenced by the subretinal space. Numerical simulations also provide a quantitative prediction of the lateral spread of current density in the vicinity of the measuring contact as a function of retina-electrode distance. SIGNIFICANCE In general, our results point to the need for scanning a large frequency range for impedance measurements since capacitive and resistive regimes are strongly dependent on retina-electrode proximity. We believe that these results will contribute to a better understanding of electrical stimulation in neuroprostheses and ultimately improve their efficiency.

Vobi One: a data processing software package for functional optical imaging.

Optical imaging is the only technique that allows to record the activity of a neuronal population at the mesoscopic scale. A large region of the cortex (10–20 mm diameter) is directly imaged with a CCD camera while the animal performs a behavioral task, producing spatio-temporal data with an unprecedented combination of spatial and temporal resolutions (respectively, tens of micrometers and milliseconds). However, researchers who have developed and used this technique have relied on heterogeneous software and methods to analyze their data. In this paper, we introduce Vobi One, a software package entirely dedicated to the processing of functional optical imaging data. It has been designed to facilitate the processing of data and the comparison of different analysis methods. Moreover, it should help bring good analysis practices to the community because it relies on a database and a standard format for data handling and it provides tools that allow producing reproducible research. Vobi One is an extension of the BrainVISA software platform, entirely written with the Python programming language, open source and freely available for download at https://trac.int.univ-amu.fr/vobi_one.

Probing the functional impact of sub-retinal prosthesis

Retinal prostheses are promising tools for recovering visual functions in blind patients but, unfortunately, with still poor gains in visual acuity. Improving their resolution is thus a key challenge that warrants understanding its origin through appropriate animal models. Here, we provide a systematic comparison between visual and prosthetic activations of the rat primary visual cortex (V1). We established a precise V1 mapping as a functional benchmark to demonstrate that sub-retinal implants activate V1 at the appropriate position, scalable to a wide range of visual luminance, but with an aspect-ratio and an extent much larger than expected. Such distorted activation profile can be accounted for by the existence of two sources of diffusion, passive diffusion and activation of ganglion cells’ axons en passant. Reverse-engineered electrical pulses based on impedance spectroscopy is the only solution we tested that decreases the extent and aspect-ratio, providing a promising solution for clinical applications. DOI: http://dx.doi.org/10.7554/eLife.12687.001