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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...
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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...
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The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
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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.
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Competitive interactions shape brain dynamics and computation across species.

Andrea I Luppi1,2,3, Yonatan Sanz Perl4, Jakub Vohryzek4

  • 1University of Oxford, Oxford, UK.

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|November 1, 2024
PubMed
Summary
This summary is machine-generated.

The brain balances cooperation and competition using modular, local connections and diffuse, long-range ones. This network architecture enhances brain activity, information processing, and computational capacity.

Keywords:
Whole-brain modelinganticorrelationsbrain networkcooperation and competitiondynamicshierarchymetastabilityreservoir computingsynergy

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Network Science

Background:

  • Adaptive cognition requires cooperation between distributed brain circuits.
  • Neural systems compete for limited processing resources, posing a challenge for brain function.

Purpose of the Study:

  • To investigate how the brain's network architecture balances cooperative and competitive interactions.
  • To examine the dynamical and computational relevance of these interactions in the mammalian connectome.

Main Methods:

  • Utilized computational whole-brain modeling across human, macaque, and mouse connectomes.
  • Developed models incorporating both cooperative and competitive interactions to simulate brain activity.

Main Results:

  • Models accurately reproducing brain activity consistently combined modular cooperative interactions with diffuse, long-range competitive interactions.
  • The model with competitive interactions significantly outperformed the cooperative-only model in fitting spatial and dynamical brain properties.
  • Competitive interactions enhanced synergistic information, local-global hierarchy, and computational capacity.

Conclusions:

  • Established a mechanistic link between mammalian brain network architecture, dynamical properties, and computational capabilities.
  • Demonstrated that a balance of cooperation and competition is crucial for efficient brain function and computation.
  • Highlighted the importance of diffuse, long-range competitive interactions for superior brain performance.