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Related Concept Videos

Neuronal Communication01:28

Neuronal Communication

Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
Overview of Synapses01:25

Overview of Synapses

A synapse is a specialized structure where two neurons connect, allowing them to pass an electrical or chemical signal to another neuron. It is the point of communication between neurons. The term "synapse" is derived from the Greek word "synapsis," which means "conjunction." The entire process of neural communication revolves around the synapse. When activated, a neuron releases chemicals known as neurotransmitters into the synapse. These neurotransmitters cross the synapse and bind to...
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system.
Intracellular Signaling Affects Focal Adhesions01:17

Intracellular Signaling Affects Focal Adhesions

Integrins act both as extracellular input receivers and as intracellular processing activators. As their name suggests, integrins are entirely integrated into the membrane structure. Their hydrophobic membrane-spanning regions interact with the phospholipid bilayer's hydrophobic region. These membrane receptors provide extracellular attachment sites for effectors like hormones and growth factors. They activate intracellular response cascades when their effectors are bound and active.
Some...
Cyclic Processes And Isolated Systems01:19

Cyclic Processes And Isolated Systems

A thermodynamic system with zero heat exchange and work is an isolated system. For these systems, the internal energy remains constant.
In the case of a non-isolated system, the change in the internal energy is zero only if the process is cyclic. A thermodynamic process is considered cyclic if the system undergoes a series of changes and returns to its initial state. 
Consider a cyclic process that returns to its initial state, undergoing a four-step process. The heat transfer along each path...
Integration of Synaptic Events01:28

Integration of Synaptic Events

Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...

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Updated: Jun 27, 2026

New Framework for Understanding Cross-Brain Coherence in Functional Near-Infrared Spectroscopy (fNIRS) Hyperscanning Studies
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Introduction to Focus Issue: synchronization in complex networks.

Johan A K Suykens, Grigory V Osipov

    Chaos (Woodbury, N.Y.)
    |December 3, 2008
    PubMed
    Summary
    This summary is machine-generated.

    Synchronization in large coupled systems is key to understanding networks in neuroscience, engineering, and social sciences. This research explores stability, chaos, and pattern formation in complex networks.

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    Area of Science:

    • Complex systems science
    • Network theory
    • Mathematical physics

    Background:

    • Synchronization is a fundamental phenomenon in diverse coupled systems, including neuronal, genetic, and mechanical networks.
    • Understanding synchronization dynamics is crucial for analyzing system stability, emergent behaviors, and pattern formation.
    • This field integrates mathematical and computational approaches to study complex network interactions.

    Discussion:

    • The study examines the interplay between synchronization and pattern formation in complex networks.
    • It delves into mathematical and computational analyses of system states, stability, clustering, bifurcations, and chaos.
    • Robustness and sensitivity analyses are critical for understanding network behavior under various conditions.

    Key Insights:

    • Focuses on generic methods applicable across different network types.
    • Includes specific model studies to illustrate synchronization principles.
    • Highlights practical applications of synchronization phenomena in real-world systems.

    Outlook:

    • Presents recent advancements and ongoing research in the field of network synchronization.
    • Encourages interdisciplinary collaboration to tackle complex network challenges.
    • Suggests future research directions in understanding and controlling synchronized behaviors.