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Related Concept Videos

Time-Series Graph00:54

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
Linear time-invariant Systems01:23

Linear time-invariant Systems

A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be calculated...
State Space Representation01:27

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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...
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
Basic Continuous Time Signals01:22

Basic Continuous Time Signals

Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...

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Related Experiment Video

Updated: May 9, 2026

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

[Neural representation of time].

Masaki Tanaka1, Jun Kunimatsu, Shogo Ohmae

  • 1Department of Physiology, Hokkaido University School of Medicine.

Brain and Nerve = Shinkei Kenkyu No Shinpo
|August 7, 2013
PubMed
Summary

Understanding how the brain processes time is key. This review classifies neural time representation models into prospective/retrospective and rate/temporal coding, aiding comprehension of brain timing mechanisms.

Area of Science:

  • Neuroscience
  • Cognitive Science

Context:

  • Temporal information is crucial for perception and behavior.
  • Neural mechanisms of time representation are not fully understood.
  • Existing models of neural time representation vary.

Purpose:

  • To review and classify existing models of neural time representation.
  • To propose a framework for understanding how neurons encode time.
  • To provide a basis for future research into brain timing mechanisms.

Summary:

  • Models of neural time representation are categorized based on two viewpoints: prospective vs. retrospective information and rate coding vs. temporal coding.
  • Rate coding models (accumulator, state-dependence) use firing rate modulation for prospective/retrospective timing.

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  • Temporal coding models (coincidence detection, entrainment/synchronization) use synchronous neural activity.

    • Impact:

    • This classification offers a comprehensive understanding of neuronal mechanisms for temporal processing.
    • It highlights the roles of intrinsic sensory properties and specialized timing networks.
    • A proposed serial processing model for fixed time intervals warrants further experimental validation.