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

Sensation

Sensation

Sensory receptors are specialized neurons that respond to specific types of external stimuli, initiating the process known as sensation. This occurs when sensory input, such as light entering the eye, is detected by these receptors, causing chemical changes in the cells of the retina. These cells then convert the sensory stimulus into action potentials that are transmitted to the central nervous system, a process termed transduction.
Absolute thresholds can quantify the sensitivity of sensory...

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.

Channel Rhodopsins

Channel Rhodopsins

Most organisms use photoreceptors to sense and respond to light. Examples of photoreceptors include bacteriorhodopsins and bacteriophytochromes in some bacteria, phytochromes in plants, and rhodopsins in the photoreceptor cells of the vertebral retina. The light-sensitive property of these receptors is because of the bound chromophores, such as bilin in the phytochromes and retinal in the rhodopsins.
Rhodopsins belong to the family of cell surface proteins called G-protein coupled receptors,...

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...

Methods of Medium Optimization

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

Diversity in Cell Signaling Responses

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity.
Graded and Abrupt Responses
Some signaling systems generate...

You might also read

Related Articles

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

Sort by

Same author

NOTCH1 is a mechanosensor in adult arteries.

Nature communications·2017

Same author

Automated pulse discrimination of two freely-swimming weakly electric fish and analysis of their electrical behavior during dominance contest.

Journal of physiology, Paris·2017

Same author

Computational models to understand decision making and pattern recognition in the insect brain.

Current opinion in insect science·2015

Same author

Analytical results on Muller's ratchet effect in growing populations.

Physical review. E, Statistical, nonlinear, and soft matter physics·2009

Same author

The dynamical way to mutation-selection balance of an infinite population evolving on a truncated fitness landscape.

Journal of mathematical biology·2005

Same author

Effect of selection on the topology of genealogical trees.

Journal of theoretical biology·2003

Search research articles

Related Experiment Video

Updated: May 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Optimal channel efficiency in a sensory network.

Thiago S Mosqueiro¹, Leonardo P Maia

¹Instituto de Física de São Carlos, Universidade de São Paulo, 13560-970 São Carlos, SP, Brazil. thiago.mosqueiro@gmail.com

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|August 16, 2013

Summary

Spontaneous neural activity, specifically avalanche lifetimes, dictates sensory system dynamic range. Information efficiency and dynamic range optimize together at critical points in neural network models.

Related Experiment Videos

Last Updated: May 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Neuroscience
Computational Neuroscience
Complex Systems

Background:

Spontaneous neural activity exhibits complex spatiotemporal structures.
This activity is linked to stimulus-induced patterns and network organization.
The dynamic range of sensory systems is a key psychophysical measure.

Purpose of the Study:

To investigate the relationship between spontaneous neural activity and sensory system dynamic range.
To explore the role of avalanche lifetime distribution entropy (information efficiency) in regulating dynamic range.
To identify critical points of optimization in neural network models.

Main Methods:

Simulated the Kinouchi-Copelli (KC) model on diverse network families.
Analyzed the behavior of dynamic range and information efficiency as functions of the average branching ratio.
Utilized data collapses, rather than power laws, to identify signatures of criticality.

Main Results:

Information efficiency consistently accompanies the dynamic range in the KC model.
Both dynamic range and information efficiency increase or decrease together with the average branching ratio.
Critical optimization of information efficiency and dynamic range occurs simultaneously at a nonequilibrium phase transition point.
Critical optimization can occur even when avalanche lifetime distributions deviate from power laws.

Conclusions:

Stimulus-free features, like avalanche dynamics, significantly influence sensory system performance.
Information efficiency, derived from avalanche lifetimes, is a crucial factor for optimizing dynamic range.
Proper temporal matching of neuronal states, rather than sheer capacity, is key for efficient information processing.