Lateral inhibition

A large part of mammalian brains is dedicated to sensory processing. Sensory receptors extract distinct but partly correlated features of the environment that vary at different timescales, and then transmit them through subcortical structures and a succession of recurrently connected cortical areas. A general theory on how sensory pathways encode, propagate, and transform sensory features is still missing. To understand how biophysically realistic neural networks support these fundamental brain functions, we developed an analytical framework based on the principle of efficient coding (Barlow,

The hippocampal formation is a crucial region in the encoding and retrieval of memory, thought to be mediated through ensemble formation and recruitment or intrinsic attractor dynamics. Additionally, it has been shown that overall hippocampal population activity reflects environmental novelty. However, a common neural basis supporting these two processes remains unknown. Furthermore, many memories contain overlapping features, and it remains to be established how specific memories are retrieved without interference in the hippocampus. We propose that both engram and attractor models hinge on l

The brain computes internal representations by applying highly recurrent dynamics to feed-forward input. Such dynamics may be viewed as analogous to the inference step in latent variables models, where one usually follows the gradient of the latent posterior distribution until a stable state is reached. At the stable state, when this gradient has approximately zero norm, a parameter optimization step can be applied to slightly increase the likelihood of the current sample under the model. Here we suggest this procedure, which closely matches the expectation-maximization (EM) algorithm, can be

For the olfactory associative learning to be specific, stimulus representation in the Kenyon cell (KC) population should be accurate with minimal activity overlap between different stimuli, which is achieved by the sparse and highly odor-specific KC response patterns. While a multitude of cellular and network mechanisms substantially increase the KC population sparsity, the proportion of KCs responding unreliably to a given odor over multiple trials is roughly three times larger than that of reliable responders [1, 3], leading to substantial response correlations between different odors. Consi

Interactions between spiking units grouped in distinct excitatory (E) and inhibitory (I) populations can result in a complex dynamical landscape. Part of this complexity, namely dynamics that depend on undelayed connectivities and external inputs, is retained by a simplified model, the threshold-linear network (TLN), which allows to derive fully analytical conditions for the emergence of multistability [1], paradoxical perturbation effects [2,3], and some oscillations [4,5]. These results, however, have only been applied to specific architectures, such as canonical circuits or all-inhibitory n

…suggesting an influence of lateral inhibition, a process in which adjacent neurons inhibit each other. We investigated the role of spatial summation and lateral inhibition in thermosensation using computational modeling. We devised a perceptual decision-making task where thermal stimuli were applied to 16 participants' forearms, with temperatures increasing or decreasing fro

Early in development, spontaneous cortical activity in ferrets is organised into modular, low-dimensional patterns, and this organisation is highly similar across multiple cortical areas [1]. Currently, it is unclear how cortical activity changes in development, whether these changes reflect the different functional specialisations across cortical areas, and what circuit changes underlie these changes.Here, we investigated how the structure of spontaneous cortical activity changes over the course of development by recording it with two-photon calcium imaging before (P21-24), around (P27-32) an

…For instance, spatially isotropic lateral inhibition between neurons showing overlapping receptive fields allows contrast enhancement of primary stimulus representations in the visual system. In the olfactory bulb (OB), odorant identity is primarily represented as a spatially discontinuous map of activated glomeruli. Prior observations on mixture inhibition across glomeruli led us to hypothesize that so-called superficial short-axon-cells -a sub-population of GABAergic/dopaminergic juxtaglomerular cells- underlie a t

The internal and external world is thought to be represented by distributed patterns of cortical activity. The emergence of these cortical representations over the course of development remains an unresolved question. In this talk, I share results from a series of recent studies combining theory and experiments in the cortex of the ferret, a species with a well-defined columnar organization and modular network of orientation-selective responses in visual cortex. I show that prior to the onset of structured sensory experience, endogenous mechanisms set up a highly organized cortical network str

Decisions about where to move the eyes depend on neurons in frontal eye field (FEF). Movement neurons in FEF accumulate salience evidence derived from FEF visual neurons to select the location of a saccade target among distractors. How visual neurons achieve this salience representation is unknown. We present a neuro-computational model of target selection called Salience by Competitive and Recurrent Interactions (SCRI), based on the competitive interaction model of attentional selection and decision-making (Smith & Sewell, 2013). SCRI selects targets by synthesizing localization and identific

…within the same hair results in strong lateral inhibition, posing questions about the functional significance of the stereotyped organization. We developed a phenomenological model of coupled ORNs responding to odor mixture stimuli. Our model includes two forms of nonlinearity, essential to capture the nature of the coupling. First, ephaptic interac

The basal ganglia (BG) play a crucial role in action-selection and reinforcement learning (RL), but how multiple nuclei, transmitters and receptors realize computations for reward-based learning is still unclear. We built a topologically organized spiking BG model. Striatal medium spiny neurons (MSN) were classified based on the expression of dopamine D1 and D2 receptors. We implemented spike-timing dependent plasticity and structural parameters: i) the asymmetry of connections between MSN’s; and ii) the overlap between direct and indirect pathways. In action-selection simulations, we assume

…both with respect to recurrent and lateral inhibition. Here, I summarize recent results with regard to GABA release, leading to a novel hypothesis on granule cell function that has the potential to resolve most of these enigmas. I predict that granule cells provide dynamically switched later