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Related Concept Videos

Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential.
Neuronal Communication01:28

Neuronal Communication

Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
Functional Divisions of the Nervous System01:23

Functional Divisions of the Nervous System

The nervous system, responsible for sensing, integrating, and responding to various stimuli, is divided into the central nervous system (CNS) and the peripheral nervous system (PNS). The PNS has two functional divisions: the sensory or afferent division and the motor or efferent division.
The sensory division transmits information from sensory receptors in the body to the CNS. It provides the CNS with knowledge about somatic senses (such as tactile, thermal, pain, and proprioceptive sensations)...
Integration of Synaptic Events01:28

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...

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Viral Tracing of Genetically Defined Neural Circuitry
13:06

Viral Tracing of Genetically Defined Neural Circuitry

Published on: October 17, 2012

Marginalization in neural circuits with divisive normalization.

Jeffrey M Beck1, Peter E Latham, Alexandre Pouget

  • 1Gatsby Computational Neuroscience Unit, UCL, London WC1N 3AR, United Kingdom.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|October 28, 2011
PubMed
Summary
This summary is machine-generated.

Neural circuits can perform marginalization, a key probabilistic inference, using specific spike train statistics. Networks with quadratic nonlinearity and divisive normalization enable near-optimal marginalization across diverse tasks.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cognitive Science

Background:

  • Marginalization is a fundamental probabilistic inference used in numerous nervous system computations.
  • Tasks include causal reasoning, sensory processing, motor control, and decision-making.
  • Understanding the neural implementation of marginalization is a key challenge.

Purpose of the Study:

  • To investigate how neural circuits can implement marginalization.
  • To identify the specific neural circuit properties that support this computation.

Main Methods:

  • Analysis of neural computation and circuit implementation.
  • Modeling neural networks with specific statistical properties (constant Fano factors, gain-invariant tuning curves).
  • Investigating the role of quadratic nonlinearity and divisive normalization.

Main Results:

  • Neural networks exhibiting specific spike train statistics can perform common marginalizations.
  • Quadratic nonlinearity coupled with divisive normalization is sufficient for near-optimal marginalization.
  • Divisive normalization, previously linked to gain control, may also implement marginalization.

Conclusions:

  • Neural circuits can implement marginalization through specific statistical properties and network architectures.
  • Divisive normalization plays a critical role in enabling efficient marginalization in the brain.
  • This finding expands the known functions of divisive normalization in neural processing.