Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Information Processing Approach

Information Processing Approach

The information-processing theory of cognitive development centers on fundamental mental processes, including attention, memory, and problem-solving skills. Researchers in this field examine how cognitive abilities, such as working memory, evolve and influence children's overall development. Studies indicate that children with stronger working memory tend to excel in reading comprehension, math, and problem-solving compared to peers with less efficient memory skills. Low working memory is also...

Neural Circuits

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...

The Role of Ion Channels in Neuronal Computation

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.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Towards a cognitive neuroscience of self-awareness.

Neuroscience and biobehavioral reviews·2016

Same author

Effects of local anesthetics and calcium on the interaction of cholinergic ligands with the nicotinic receptor protein from Torpedo marmorata.

Molecular pharmacology·2015

Same author

Comparison of embryonic and adult torpedo acetylcholine receptor by sedimentation characteristics and antigenicity.

International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience·2014

Same author

Errata.

The Journal of membrane biology·2013

Same author

Changes in extrinsic fluorescence intensity of the electroplax membrane during electrical excitation.

The Journal of membrane biology·2013

Same author

In Vitro excitation of purified membrane fragments by cholinergic agonists : I. Pharmalogical properties of the excitable membrane fragments.

The Journal of membrane biology·2013

Search research articles

Related Experiment Video

Updated: May 8, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Published on: August 28, 2021

Development of elementary numerical abilities: a neuronal model.

S Dehaene¹, J P Changeux

¹INSERM and CNRS, Paris.

Journal of Cognitive Neuroscience

|August 23, 2013

Summary

This summary is machine-generated.

Human infants and animals possess basic numerical processing skills. A neural network model explains how numerosity detection and comparison develop without counting, supporting infant abilities.

More Related Videos

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Published on: April 26, 2018

Related Experiment Videos

Last Updated: May 8, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Published on: August 28, 2021

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Assessment of the Effects of Endocrine Disrupting Compounds on the Development of Vertebrate Neural Network Function Using Multi-electrode Arrays

Published on: April 26, 2018

Area of Science:

Cognitive Science
Neuroscience
Developmental Psychology

Background:

Human infants and animals exhibit rudimentary numerical processing abilities, including numerosity recognition and comparison.
These abilities develop without language and may not require counting, challenging existing theories.

Purpose of the Study:

To propose and validate a formal neural network model for the development of numerical processing in infants and animals.
To explain numerosity detection and comparison abilities through a computational framework.

Main Methods:

Development of a formal neural network model with initial unordered numerosity detectors.
Integration of a short-term memory network to enable number comparison capabilities.
Computer simulations to test the model's explanatory power for numerical phenomena.

Main Results:

The model successfully explains numerosity detection without assuming counting abilities in infants.
Simulations replicate key numerical phenomena such as the distance effect and Fechner's law.
The addition of short-term memory was sufficient for developing number comparison abilities.

Conclusions:

A formal neural network model can account for the development of basic numerical processing in pre-linguistic subjects.
Infant numerosity detection can be explained through mechanisms other than counting.
The model provides insights into the neurobiological underpinnings of numerical cognition.