66 research outputs found

    Meta-Learning the Inductive Bias of Simple Neural Circuits

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    General features of the retinal connectome determine the computation of motion anticipation

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    Motion anticipation allows the visual system to compensate for the slow speed of phototransduction so that a moving object can be accurately located. This correction is already present in the signal that ganglion cells send from the retina but the biophysical mechanisms underlying this computation are not known. Here we demonstrate that motion anticipation is computed autonomously within the dendritic tree of each ganglion cell and relies on feedforward inhibition. The passive and non-linear interaction of excitatory and inhibitory synapses enables the somatic voltage to encode the actual position of a moving object instead of its delayed representation. General rather than specific features of the retinal connectome govern this computation: an excess of inhibitory inputs over excitatory, with both being randomly distributed, allows tracking of all directions of motion, while the average distance between inputs determines the object velocities that can be compensated for

    Regulation of circuit organization and function through inhibitory synaptic plasticity

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    Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning

    Large-scale circuit reconstruction in medial entorhinal cortex

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    Es ist noch weitgehend ungeklärt, mittels welcher Mechanismen die elektrische Aktivität von Nervenzellpopulationen des Gehirns Verhalten ermöglicht. Die Orientierung im Raum ist eine Fähigkeit des Gehirns, für die im Säugetier der mediale entorhinale Teil der Großhirnrinde als entscheidende Struktur identifiziert wurde. Hier wurden Nervenzellen gefunden, die die Umgebung des Individuums in einer gitterartigen Anordnung repräsentieren. Die neuronalen Schaltkreise, welche diese geordnete Nervenzellaktivität im medialen entorhinalen Kortex (MEK) ermöglichen, sind noch wenig verstanden. Die vorliegende Dissertation hat eine Klärung der zellulären Architektur und der neuronalen Schaltkreise in der zweiten Schicht des MEK der Ratte zum Ziel. Zunächst werden die Beiträge zur Entdeckung der hexagonal angeordneten zellulären Anhäufungen in Schicht 2 des MEK sowie zur Beschreibung der Dichotomie der Haupt-Nervenzelltypen dargestellt. Im zweiten Teil wird erstmalig eine konnektomische Analyse des MEK beschrieben. Die detaillierte Untersuchung der Architektur einzelner exzitatorischer Axone ergab das überraschende Ergebnis der präzisen Sortierung von Synapsen entlang axonaler Pfade. Die neuronalen Schaltkreise, in denen diese Neurone eingebettet sind, zeigten eine starke zeitliche Bevorzugung der hemmenden Neurone. Die hier erhobenen Daten tragen zu einem detaillierteren Verständnis der neuronalen Schaltkreise im MEK bei. Sie enthalten die erste Beschreibung überraschend präziser axonaler synaptischer Ordnung im zerebralen Kortex der Säugetiere. Diese Schaltkreisarchitektur lässt einen Effekt auf die Weiterleitung synchroner elektrischer Populationsaktivität im MEK vermuten. In zukünftigen Studien muss insbesondere geklärt werden, ob es sich bei den hier berichteten Ergebnissen um eine Besonderheit des MEK oder ein generelles Verschaltungsprinzip der Hirnrinde des Säugetiers handelt.The mechanisms by which the electrical activity of ensembles of neurons in the brain give rise to an individual’s behavior are still largely unknown. Navigation in space is one important capacity of the brain, for which the medial entorhinal cortex (MEC) is a pivotal structure in mammals. At the cellular level, neurons that represent the surrounding space in a grid-like fashion have been identified in MEC. These so-called grid cells are located predominantly in layer 2 (L2) of MEC. The detailed neuronal circuits underlying this unique activity pattern are still poorly understood. This thesis comprises studies contributing to a mechanistic description of the synaptic architecture in rat MEC L2. First, this thesis describes the discovery of hexagonally arranged cell clusters and anatomical data on the dichotomy of the two principle cell types in L2 of the MEC. Then, the first connectomic study of the MEC is reported. An analysis of the axonal architecture of excitatory neurons revealed synaptic positional sorting along axons, integrated into precise microcircuits. These microcircuits were found to involve interneurons with a surprising degree of axonal specialization for effective and fast inhibition. Together, these results contribute to a detailed understanding of the circuitry in MEC. They provide the first description of highly precise synaptic arrangements along axons in the cerebral cortex of mammals. The functional implications of these anatomical features were explored using numerical simulations, suggesting effects on the propagation of synchronous activity in L2 of the MEC. These findings motivate future investigations to clarify the contribution of precise synaptic architecture to computations underlying spatial navigation. Further studies are required to understand whether the reported synaptic specializations are specific for the MEC or represent a general wiring principle in the mammalian cortex

    Micro-connectomics: probing the organization of neuronal networks at the cellular scale.

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    Defining the organizational principles of neuronal networks at the cellular scale, or micro-connectomics, is a key challenge of modern neuroscience. In this Review, we focus on graph theoretical parameters of micro-connectome topology, often informed by economical principles that conceptually originated with RamĂłn y Cajal's conservation laws. First, we summarize results from studies in intact small organisms and in samples from larger nervous systems. We then evaluate the evidence for an economical trade-off between biological cost and functional value in the organization of neuronal networks. Various results suggest that many aspects of neuronal network organization are indeed the outcome of competition between these two fundamental selection pressures.This work was supported by the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by the Nature Publishing Group
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