Chaos in the brain: a short review alluding to epilepsy, depression, exercise and lateralization.

Journal Article (Review;Journal Article)

Electroencephalograms (EEGs) reflect the electrical activity of the brain. Even when they are analyzed from healthy individuals, they manifest chaos in the nervous system. EEGs are likely to be produced by a nonlinear system, since a nonlinear system with at least 3 degrees of freedom (or state variables) may exhibit chaotic behavior. Furthermore, such systems can have multiple stable states governed by "chaotic" ("strange") attractors. A key feature of chaotic systems is the presence of an infinite number of unstable periodic fixed points, which are found in spontaneously active neuronal networks (e.g., epilepsy). The brain has chemicals called neurotransmitters that convey the information through the 10(16) synapses residing there. However, each of these neurotransmitters acts through various receptors and their numerous subtypes, thereby exhibiting complex interactions. Albeit in epilepsy the role of chaos and EEG findings are well proven, in another condition, i.e., depression, the role of chaos is slowly gaining ground. The multifarious roles of exercise, neurotransmitters and (cerebral) hemispheric lateralization, in the case of depression, are also being established. The common point of reference could be nonlinear dynamics. The purpose of this review is to study those nonlinear/chaotic interactions and point towards new theoretical models incorporating the oscillation caused by the same neurotransmitter acting on its different receptor subtypes. This may lead to a better understanding of brain neurodynamics in health and disease.

Full Text

Duke Authors

Cited Authors

  • Sarbadhikari, SN; Chakrabarty, K

Published Date

  • September 2001

Published In

Volume / Issue

  • 23 / 7

Start / End Page

  • 445 - 455

PubMed ID

  • 11574252

Electronic International Standard Serial Number (EISSN)

  • 1873-4030

International Standard Serial Number (ISSN)

  • 1350-4533

Digital Object Identifier (DOI)

  • 10.1016/s1350-4533(01)00075-3


  • eng