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Related Concept Videos

System of Memory01:23

System of Memory

Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...
Chunking and Rehearsal in Sensory Memory01:22

Chunking and Rehearsal in Sensory Memory

Improving short-term memory can be achieved through techniques like chunking and rehearsal. Chunking involves organizing information into larger, more manageable units. This technique is particularly useful for information that exceeds the typical memory span of between five and nine items. For instance, logging into an online account with a password like "ta89vq0179gz" involves grouping letters and numbers into three chunks—ta89, vq01, and 79gz. It makes large amounts of information more...
Chunking01:12

Chunking

Chunking is a powerful cognitive technique that improves short-term memory retention by organizing information into smaller, more manageable units. The brain, limited by working memory capacity, can more easily process and store information when it is divided into "chunks" rather than presented as discrete, unrelated elements. Chunking is especially useful when dealing with large amounts of information, such as numerical sequences, words, or complex ideas.
The principle behind chunking is...
Long-Term Memory01:18

Long-Term Memory

Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
Long-term memory can be categorized into two primary types: explicit and implicit memory. Explicit memory, also known as declarative memory, involves the conscious recollection of information that we deliberately try to remember, recall, and articulate. This type of memory encompasses specific facts, events, and...
Buffers: Buffer Capacity01:09

Buffers: Buffer Capacity

Buffer capacity is the quantitative measure of a buffer to resist the change in pH. As shown in the following equation, the buffer capacity, denoted by 'beta', is expressed as the number of moles of acid or base needed to change the pH of a one-liter buffer solution by 1 unit. Here, Ca and Cb indicate the number of moles of acid and base, respectively. Note that dpH represents the change in pH.
In the graph, pH is plotted as a function of the number of moles of base (Cb) added to a weak acid...
Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

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Related Experiment Video

Updated: May 14, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

Random stride intervals with memory.

L Griffin1, D J West, B J West

  • 1Electrical and Computer Engineering, Duke University, Durham, NC U.S.A.

Journal of Biological Physics
|January 25, 2013
PubMed
Summary
This summary is machine-generated.

Human gait stride intervals exhibit long-time memory, challenging previous assumptions of random fluctuations. This study reveals a multiplicative timescale and fractal dimension, suggesting an allometric control process in normal walking.

Keywords:
Stride interval

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Related Experiment Videos

Last Updated: May 14, 2026

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task
10:39

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

Published on: May 3, 2018

Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment
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Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment

Published on: September 20, 2020

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

Area of Science:

  • Biomechanics
  • Human Gait Analysis
  • Complex Systems

Background:

  • Normal human gait stride intervals are assumed to fluctuate randomly.
  • Previous studies suggested uncorrelated random errors in stride intervals.

Purpose of the Study:

  • To investigate the nature of fluctuations in human gait stride intervals.
  • To determine if these fluctuations exhibit long-time memory and complex scaling properties.

Main Methods:

  • Analysis of stride interval data from normal human gait.
  • Application of multifractal analysis to characterize temporal correlations.
  • Investigation of multiplicative timescales and fractal dimensions.

Main Results:

  • Stride interval fluctuations in human gait display long-time memory.
  • The process is characterized by a multiplicative timescale and fractal dimension, not just random errors.
  • Findings indicate a departure from simple random walk models.

Conclusions:

  • Human gait control involves complex, long-range correlations.
  • An allometric control process is proposed to explain these observed gait dynamics.
  • This challenges traditional models of gait variability.