Neuroscience: Where is the brain in the Human Brain Project?

International audienc

Mean-field equations for stochastic firing-rate neural fields with delays: Derivation and noise-induced transitions

In this manuscript we analyze the collective behavior of mean-field limits of large-scale, spatially extended stochastic neuronal networks with delays. Rigorously, the asymptotic regime of such systems is characterized by a very intricate stochastic delayed integro-differential McKean-Vlasov equation that remain impenetrable, leaving the stochastic collective dynamics of such networks poorly understood. In order to study these macroscopic dynamics, we analyze networks of firing-rate neurons, i.e. with linear intrinsic dynamics and sigmoidal interactions. In that case, we prove that the solution of the mean-field equation is Gaussian, hence characterized by its two first moments, and that these two quantities satisfy a set of coupled delayed integro-differential equations. These equations are similar to usual neural field equations, and incorporate noise levels as a parameter, allowing analysis of noise-induced transitions. We identify through bifurcation analysis several qualitative transitions due to noise in the mean-field limit. In particular, stabilization of spatially homogeneous solutions, synchronized oscillations, bumps, chaotic dynamics, wave or bump splitting are exhibited and arise from static or dynamic Turing-Hopf bifurcations. These surprising phenomena allow further exploring the role of noise in the nervous system.Comment: Updated to the latest version published, and clarified the dependence in space of Brownian motion

Spatially Structured Sparse Morphological Component Separation for Voltage-Sensitive Dye Optical Imaging

International audienceBackground. Voltage-sensitive dye optical imaging is a promising technique for studying in vivo neural assemblies dynamics where functional clustering can be visualized in the imaging plane. Its practical potential is however limited by many artifacts. New Method. We present a novel method, that we call "SMCS" (Spatially Structured Sparse Morphological Component Separation), to separate the relevant biological signal from noise and artifacts. It extends Generalized Linear Models (GLM) by using a set of convex non-smooth regularization priors adapted to the morphology of the sources and artifacts to capture. Results. We make use of first order proximal splitting algorithms to solve the corresponding large scale optimization problem. We also propose an automatic parameters selection procedure based on statistical risk estimation methods. Comparison with Existing Methods. We compare this method with blank subtraction and GLM methods on both synthetic and real data. It shows encouraging perspectives for the observation of complex cortical dynamics. Conclusions. This work shows how recent advances in source separation can be integrated into a biophysical model of VSDOI. Going beyond GLM methods is important to capture transient cortical events such as propagating waves

Coordinated optimization of visual cortical maps (II) Numerical studies

It is an attractive hypothesis that the spatial structure of visual cortical architecture can be explained by the coordinated optimization of multiple visual cortical maps representing orientation preference (OP), ocular dominance (OD), spatial frequency, or direction preference. In part (I) of this study we defined a class of analytically tractable coordinated optimization models and solved representative examples in which a spatially complex organization of the orientation preference map is induced by inter-map interactions. We found that attractor solutions near symmetry breaking threshold predict a highly ordered map layout and require a substantial OD bias for OP pinwheel stabilization. Here we examine in numerical simulations whether such models exhibit biologically more realistic spatially irregular solutions at a finite distance from threshold and when transients towards attractor states are considered. We also examine whether model behavior qualitatively changes when the spatial periodicities of the two maps are detuned and when considering more than 2 feature dimensions. Our numerical results support the view that neither minimal energy states nor intermediate transient states of our coordinated optimization models successfully explain the spatially irregular architecture of the visual cortex. We discuss several alternative scenarios and additional factors that may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:1102.335

Foci of orientation plasticity in visual cortex

[Abstract] Cortical areas are generally assumed to be uniform in their capacity for adaptive changes or plasticity1, 2, 3, 4. Here we demonstrate, however, that neurons in the cat striate cortex (V1) show pronounced adaptation-induced short-term plasticity of orientation tuning primarily at specific foci. V1 neurons are clustered according to their orientation preference in iso-orientation domains5 that converge at singularities or pinwheel centres6, 7. Although neurons in pinwheel centres have similar orientation tuning and responses to those in iso-orientation domains, we find that they differ markedly in their capacity for adaptive changes. Adaptation with an oriented drifting grating stimulus alters responses of neurons located at and near pinwheel centres to a broad range of orientations, causing repulsive shifts in orientation preference and changes in response magnitude. In contrast, neurons located in iso-orientation domains show minimal changes in their tuning properties after adaptation. The anisotropy of adaptation-induced orientation plasticity is probably mediated by inhomogeneities in local intracortical interactions that are overlaid on the map of orientation preference in V1

The application of online transcranial random noise stimulation and perceptual learning in the improvement of visual functions in mild myopia

It has recently been demonstrated how perceptual learning, that is an improvement in a sensory/perceptual task upon practice, can be boosted by concurrent high-frequency transcranial random noise stimulation (tRNS). It has also been shown that perceptual learning can generalize and produce an improvement of visual functions in participants with mild refractive defects. By using three different groups of participants (single-blind study), we tested the efficacy of a short training (8 sessions) using a single Gabor contrast-detection task with concurrent hf-tRNS in comparison with the same training with sham stimulation or hf-tRNS with no concurrent training, in improving visual acuity (VA) and contrast sensitivity (CS) of individuals with uncorrected mild myopia. A short training with a contrast detection task is able to improve VA and CS only if coupled with hf-tRNS, whereas no effect on VA and marginal effects on CS are seen with the sole administration of hf-tRNS. Our results support the idea that, by boosting the rate of perceptual learning via the modulation of neuronal plasticity, hf-tRNS can be successfully used to reduce the duration of the perceptual training and/or to increase its efficacy in producing perceptual learning and generalization to improved VA and CS in individuals with uncorrected mild myopia

Reprogramming of orientation columns in visual cortex : a domino effect

Abstract : Cortical organization rests upon the fundamental principle that neurons sharing similar properties are co-located. In the visual cortex, neurons are organized into orientation columns. In a column, most neurons respond optimally to the same axis of an oriented edge, that is, the preferred orientation. This orientation selectivity is believed to be absolute in adulthood. However, in a fully mature brain, it has been established that neurons change their selectivity following sensory experience or visual adaptation. Here, we show that after applying an adapter away from the tested cells, neurons whose receptive fields were located remotely from the adapted site also exhibit a novel selectivity in spite of the fact that they were not adapted. These results indicate a robust reconfiguration and remapping of the orientation domains with respect to each other thus removing the possibility of an orientation hole in the new hypercolumn. These data suggest that orientation columns transcend anatomy, and are almost strictly functionally dynamic