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On The Biophysical Complexity of Brain Dynamics: An Outlook

Dynamics, ISSN: 2673-8716, Vol: 2, Issue: 2, Page: 114-148
2022
  • 13
    Citations
  • 0
    Usage
  • 24
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    13
    • Citation Indexes
      13
  • Captures
    24
  • Mentions
    2
    • Blog Mentions
      1
      • 1
    • News Mentions
      1
      • 1

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Dynamics, Vol. 2, Pages 114-148: On The Biophysical Complexity of Brain Dynamics: An Outlook

Dynamics, Vol. 2, Pages 114-148: On The Biophysical Complexity of Brain Dynamics: An Outlook Dynamics doi: 10.3390/dynamics2020006 Authors: Nandan Shettigar Chun-Lin Yang Kuang-Chung Tu C.

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Review Description

The human brain is a complex network whose ensemble time evolution is directed by the cumulative interactions of its cellular components, such as neurons and glia cells. Coupled through chemical neurotransmission and receptor activation, these individuals interact with one another to varying degrees by triggering a variety of cellular activity from internal biological reconfigurations to external interactions with other network agents. Consequently, such local dynamic connections mediating the magnitude and direction of influence cells have on one another are highly nonlinear and facilitate, respectively, nonlinear and potentially chaotic multicellular higher-order collaborations. Thus, as a statistical physical system, the nonlinear culmination of local interactions produces complex global emergent network behaviors, enabling the highly dynamical, adaptive, and efficient response of a macroscopic brain network. Microstate reconfigurations are typically facilitated through synaptic and structural plasticity mechanisms that alter the degree of coupling (magnitude of influence) neurons have upon each other, dictating the type of coordinated macrostate emergence in populations of neural cells. These can emerge in the form of local regions of synchronized clusters about a center frequency composed of individual neural cell collaborations as a fundamental form of collective organization. A single mode of synchronization is insufficient for the computational needs of the brain. Thus, as neural components influence one another (cellular components, multiple clusters of synchronous populations, brain nuclei, and even brain regions), different patterns of neural behavior interact with one another to produce an emergent spatiotemporal spectral bandwidth of neural activity corresponding to the dynamical state of the brain network. Furthermore, hierarchical and self-similar structures support these network properties to operate effectively and efficiently. Neuroscience has come a long way since its inception; however, a comprehensive and intuitive understanding of how the brain works is still amiss. It is becoming evident that any singular perspective upon the grandiose biophysical complexity within the brain is inadequate. It is the purpose of this paper to provide an outlook through a multitude of perspectives, including the fundamental biological mechanisms and how these operate within the physical constraints of nature. Upon assessing the state of prior research efforts, in this paper, we identify the path future research effort should pursue to inspire progress in neuroscience.

Bibliographic Details

Nandan Shettigar; Chun Lin Yang; Kuang Chung Tu; C. Steve Suh

MDPI AG

Engineering; Mathematics; Physics and Astronomy

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