Rava Azeredo da Silveira

Ecole Normale Supérieure de Paris | ENS · Département de Physique

The efficient coding approach proposes that neural systems represent as much sensory information as biological constraints allow. It aims at formalizing encoding as a constrained optimal process. A different approach, that aims at formalizing decoding, proposes that neural systems instantiate a generative model of the sensory world. Here, we put fo...

An abundant literature reports on ‘sequential effects’ observed when humans make predictions on the basis of stochastic sequences of stimuli. Such sequential effects represent departures from an optimal, Bayesian process. A prominent explanation posits that humans are adapted to changing environments, and erroneously assume non-stationarity of the...

Perception and action are inherently entangled: our world view is shaped by how we explore and navigate our environment through complex and variable self-motion. Even when fixating on a stable stimulus, our eyes undergo small, involuntary movements. Fixational eye movements (FEM) render a stable world jittery on our retinae, which contributes noise...

Classical models of efficient coding in neurons assume simple mean responses--'tuning curves'--such as bell shaped or monotonic functions of a stimulus feature. Real neurons, however, can be more complex: grid cells, for example, exhibit periodic responses which impart the neural population code with high accuracy. But do highly accurate codes requ...

To make informed decisions in natural environments that change over time, humans must update their beliefs as new observations are gathered. Studies exploring human inference as a dynamical process that unfolds in time have focused on situations in which the statistics of observations are history-independent. Yet, temporal structure is everywhere i...

Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an o...

When humans infer underlying probabilities from stochastic observations, they exhibit biases and variability that cannot be explained on the basis of sound, Bayesian manipulations of probability. This is especially salient when beliefs are updated as a function of sequential observations. We introduce a theoretical framework in which biases and var...

When humans infer underlying probabilities from stochastic observations, they exhibit biases and variability that cannot be explained on the basis of sound, Bayesian manipulations of probability. This is especially salient when beliefs are updated as a function of sequential observations. We introduce a theoretical framework in which biases and var...

Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an o...

To make informed decisions in natural environments that change over time, humans must update their beliefs as new observations are gathered. Studies exploring human inference as a dynamical process that unfolds in time have focused on situations in which the statistics of observations are history-independent. Yet temporal structure is everywhere in...

In past decades, the Bayesian paradigm has gained traction as a principled account of human behavior in inference tasks. Yet this success is tainted by the ubiquity of behavioral suboptimality and variability. We explore these discrepancies using an online inference task, in which we modulate the temporal statistics of hidden change points. We show...

We propose a model of optimal decision-making subject to a memory constraint. The constraint is a limit on the complexity of memory measured using Shannon's mutual information, as in models of rational inattention. We show that the model implies that both forecasts and actions will exhibit idiosyncratic random variation; that beliefs will fluctuate...

Within a given brain region, individual neurons exhibit a wide variety of different feature selectivities. Here,we investigated the impact of this extensive functional diversity on the population neural code. Our approach was to build optimal decoders to discriminate among stimuli using the spiking output of a real,measured neural population and co...

Many brain regions contain local interneurons of distinct types. How does an interneuron type contribute to the input-output transformations of a given brain region? We addressed this question in the mouse retina by chemogenetically perturbing horizontal cells, an interneuron type providing feedback at the first visual synapse, while monitoring the...

Effect of covariances on stimulus discrimination, in the models of feed-forward networks with shared input and with common gain fluctuation. (Compare to Fig 4). Parameters for the feed-forward network with shared input are as in Fig 2. As average responses are arbitrary in the gain fluctuation model, identical average responses as in the shared inp...

Details of derivations, numerical simulations, fits to data. (PDF)

Simple two-population model. (PDF)

Multivariate decoding methods, such as multivoxel pattern analysis (MVPA), are highly effective at extracting information from brain imaging data. Yet, the precise nature of the information that MVPA draws upon remains controversial. Most current theories emphasize the enhanced sensitivity imparted by aggregating across voxels that have mixed and w...

MVPA without regularization. Classification accuracy decreased across the board when regularization was turned off, but remained better for voxels with high (green) vs. low (blue) noise correlations, with a similar interaction by bin size. Columns represent means and error bars represent SEM across participants. The dashed gray line denotes permute...

The correlated variability in the responses of a neural population to the repeated presentation of a sensory stimulus is a universally observed phenomenon. Such correlations have been studied in much detail, both with respect to their mechanistic origin and to their influence on stimulus discrimination and on the performance of population codes. In...

The neural representation of information suffers from “noise”—the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using...

Signal transmission across chemical synapses relies crucially on neurotransmitter receptor molecules, concentrated in postsynaptic membrane domains along with scaffold and other postsynaptic molecules. The strength of the transmitted signal depends on the number of receptor molecules in postsynaptic domains, and activity-induced variation in the re...

The brain decodes the visual-scene from the action potentials of ~ 20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction, by recording multiunit activity, mainly in the visual cortex. In this s...

Positive correlations in the activity of neurons are widely observed in the brain. Previous studies have shown these correlations to be detrimental to the fidelity of population codes, or at best marginally favorable compared to independent codes. Here, we show that positive correlations can enhance coding performance by astronomical factors. Speci...

Vertebrate vision relies on two types of photoreceptors, rods and cones, which signal increments in light intensity with graded hyperpolarizations. Rods operate in the lower range of light intensities while cones operate at brighter intensities. The receptive fields of both photoreceptors exhibit antagonistic center-surround organization. Here we s...

Author Summary Photoreceptors constitute the interface between the visual world and the cerebral world, as they convert light inputs into neural signals. This conversion is subject to continuous adaptation: response gain and time scale vary as a function of input history. This adaptation is ‘dynamical’ both because it depends upon the temporal stru...

Author Summary Traditionally, sensory neuroscience has focused on correlating inputs from the physical world with the response of a single neuron. Two stimuli can be distinguished solely from the response of one neuron if one stimulus elicits a response and the other does not. But as soon as one departs from extremely simple stimuli, single-cell co...

The number of possible activity patterns in a population of neurons grows exponentially with the size of the population. Typical experiments explore only a tiny fraction of the large space of possible activity patterns in the case of populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled regime, to estimate the pro...

Previous studies have shown that motion onset is very effective at capturing attention and is more salient than smooth motion. Here, we find that this salience ranking is present already in the firing rate of retinal ganglion cells. By stimulating the retina with a bar that appears, stays still, and then starts moving, we demonstrate that a subset...

Chemotaxis when Bacteria Remember: Drift versus Diffusion (Supporting Information). (PDF)

Author Summary The chemotaxis of Escherichia coli is a prototypical model of navigational strategy. The bacterium maneuvers by switching between near-straight motion, termed runs, and tumbles which reorient its direction. To reach regions of high nutrient concentration, the run-durations are modulated according to the nutrient concentration experie...

Neurotransmitter receptor molecules, concentrated in postsynaptic domains along with scaffold and a number of other molecules, are key regulators of signal transmission across synapses. Employing experiment and theory, we develop a quantitative description of synaptic receptor domains in terms of a reaction-diffusion model. We show that interaction...

How does the connectivity of a neuronal circuit, together with the individual properties of the cell types that take part in it, result in a given computation? We examine this question in the context of retinal circuits. We suggest that the retina can be viewed as a parallel assemblage of many small computational devices, highly stereotypical and t...

The detection of approaching objects, such as looming predators, is necessary for survival. Which neurons and circuits mediate this function? We combined genetic labeling of cell types, two-photon microscopy, electrophysiology and theoretical modeling to address this question. We identify an approach-sensitive ganglion cell type in the mouse retina...

The bacterium E. coli maneuvers itself to regions with high chemoattractant concentrations by performing two stereotypical moves: "runs," in which it moves in near-straight lines, and "tumbles," in which it does not advance but changes direction randomly. The duration of each move is stochastic and depends upon the chemoattractant concentration exp...

The bacterium E. coli maneuvers itself to regions with high chemoattractant concentrations by performing two stereotypical moves: `runs', in which it moves in near straight lines, and `tumbles', in which it does not advance but changes direction randomly. The duration of each move is stochastic and depends upon the chemoattractant concentration exp...

Critical hysteresis in ferromagnets is investigated through a $N$-component spin model with random anisotropies, more prevalent experimentally than the random fields used in most theoretical studies. Metastability, and the tensorial nature of anisotropy, dictate its physics. Generically, random field Ising criticality occurs, but other universality...

We consider generalizations of the Kardar-Parisi-Zhang equation that accommodate spatial anisotropies and the coupled evolution of several fields, and focus on their symmetries and nonperturbative properties. In particular, we derive generalized fluctuation-dissipation conditions on the form of the (nonlinear) equations for the realization of a Gau...

The responses of a $1+\epsilon $ dimensional directed path to temperature and to potential variations are calculated exactly, and are governed by the same scaling form. The short scale decorrelation (strong correlation regime) leads to the overlap length predicted by heuristic approaches; its temperature dependence and large absolute value agree wi...

The decay of metastable states is dominated by quantum tunneling at low temperatures and by thermal activation at high temperatures. The escape rate of a particle out of a square well is calculated within a semi-classical approximation and exhibits an `ultrasharp' crossover: a kink in the decay rate separates a purely quantum regime at low temperat...

The stress profile and reorientation of grains, in response to a point force applied to a preloaded two dimensional granular system, are calculated in the context of a continuum theory that incorporates the texture of the packing. When high friction prevents slip at the inter-grain contacts, an anisotropic packing propagates stress along two peaks...

A macroscopic elastic description of stresses in static, preloaded granular media is derived systematically from the microscopic elasticity of individual inter-grain contacts. The assumed preloaded state and friction at contacts ensure that the network of inter-grain contacts is not altered by small perturbations. The texture of this network, set b...

We introduce an approximate mapping between the random fuse network (RFN) and a random field dipolar Ising model (RFDIM). The state of the network damage is associated with a metastable spin configuration. A mean-field treatment, numerical solutions, and heuristic arguments support the broad validity of the approximation and yield a generic phase d...

When a bubble of air rises to the top of a highly viscous liquid, it forms a dome-shaped protuberance on the free surface. Unlike a soap bubble, it bursts so slowly as to collapse under its own weight simultaneously, and folds into a striking wavy structure. This rippling effect occurs in fact for both elastic and viscous sheets, and a theory for i...

The rupture of a medium under stress typifies breakdown phenomena. More generally, the latter encompass the dynamics of systems of many interacting elements governed by the interplay of a driving force with a pinning disorder, resulting in a macroscopic transition. A simple mean-field formalism incorporating these features is presented and applied...

When a bubble of air rises to the top of a highly viscous liquid, it forms a dome-shaped protuberance on the free surface. Unlike a soap bubble, it bursts so slowly as to collapse under its own weight simultaneously, and folds into a wavy structure. This rippling effect occurs for both elastic and viscous sheets, and a theory for its onset is formu...

Earlier work on dynamical critical phenomena in the context of magnetic hysteresis for uniaxial (scalar) spins, is extended to the case of a multicomponent (vector) field. From symmetry arguments and a perturbative renormalization group approach (in the path integral formalism), it is found that the generic behavior at long time and length scales i...

In their letter, Andersen, Sornette, and Leung [Phys. Rev. Lett. 78, 2140 (1997)] describe possible behaviors for rupture in disordered media, based on the mean field-like democratic fiber bundle model. In this model, fibers are pulled with a force which is distributed uniformly. A fiber breaks if the stress on it exceeds a threshold chosen from a...