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

Neural Regulation

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 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.

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...

Neuroplasticity

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.

You might also read

Related Articles

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

Sort by

Same author

Latent subdimensions of anxiety and depression differentially influence exertion of effort in pursuit of reward versus avoidance of threat.

Translational psychiatry·2026

Same author

Neural signatures of model-based and model-free reinforcement learning across prefrontal cortex and striatum.

eLife·2026

Same author

Uncertainty for better and worse.

Current opinion in neurobiology·2026

Same author

Dopamine dynamics in human anterior cingulate cortex during Pavlovian-instrumental conflict.

bioRxiv : the preprint server for biology·2026

Same author

Modality-general sensitivity of pupil responses to regularity violations.

Cognitive, affective & behavioral neuroscience·2026

Same author

Metacognitive efficiency in learned value-based choice.

PLoS computational biology·2026

Same journal

Dynamic coordination and segregation mechanisms in higher cortex for parallel task processing.

Neuron·2026

Same journal

Higher-order thalamic bursts are drivers of attention control.

Neuron·2026

Same journal

Composing trajectories for rapid inference of navigational goals.

Neuron·2026

Same journal

Peri-head distance coding in the mouse brainstem.

Neuron·2026

Same journal

A two-timepoint framework for sensitive and specific single-cell activity screening.

Neuron·2026

Same journal

From first impressions to bonds: The neural dynamics of social relationships.

Neuron·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 20, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Twenty-five lessons from computational neuromodulation.

¹Gatsby Computational Neuroscience Unit, 17 Queen Square, London, UK. dayan@gatsby.ucl.ac.uk

|October 9, 2012

Summary

This summary is machine-generated.

Neuromodulators solve neural communication challenges by enabling flexible brain processing. These molecules adapt neural networks for changing conditions, improving decision-making under uncertainty.

More Related Videos

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

Published on: February 23, 2020

Related Experiment Videos

Last Updated: Jun 20, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments

Published on: November 12, 2019

Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

Published on: February 23, 2020

Area of Science:

Neuroscience
Computational Neuroscience
Neurobiology

Background:

Neural computation faces challenges with distributed processing, limited specific connections, and fixed brain structures.
These limitations hinder the brain's ability to adapt processing for varied inputs and changing conditions.

Purpose of the Study:

To review algorithmic and implementational motifs of neuromodulators.
To explore how neuromodulators address fundamental neural communication problems.

Main Methods:

Computationally focused review of existing literature.
Analysis of neuromodulator functions in neural processing.
Using decision-making under uncertainty as a case study.

Main Results:

Neuromodulators are broadly distributed with specialized receptors, enabling targeted information processing.
They dynamically influence neuronal activity, synaptic strength, and plasticity.
This allows the brain to adapt its processing strategies.

Conclusions:

Neuromodulators are crucial for overcoming neural communication limitations.
Their mechanisms support flexible and adaptive neural computation.
This is vital for functions like decision-making in dynamic environments.