Corticonic models of brain mechanisms underlying cognition and intelligence

Farhat, Nabil H.

doi:10.1016/j.plrev.2007.08.001

Cited by 2 publications

(2 citation statements)

References 95 publications

(105 reference statements)

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“…This thin outermost sheet of neural tissue that covers the brain is thought to be where higher cognition takes place in humans and the site of consciousness. (Miller et al, 2002a;Farhat, 2007;Fuster, 2008;Nieder, 2009;Noack, 2012).…”

Section: Introductionmentioning

confidence: 99%

The search of “canonical” explanations for the cerebral cortex

Plebe

2018

HPLS

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This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be "canonical". This "canonical" core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. It will highlight a bias that, in my opinion, has limited the success of this research project, that of overlooking the dimension of cortical development. The earliest explanation of the cerebral cortex as canonical was attempted by David Marr, deriving putative cortical circuits from general mathematical laws, loosely following a deductive-nomological account. Although Marr's theory turned out to be incorrect, one of its merits was to have put the issue of cortical circuit development at the top of his agenda. This aspect has been largely neglected in much of the research on canonical models that has followed. Models proposed in the 1980s were conceived as mechanistic. They identified a small number of components that interacted as a basic circuit, with each component defined as a function. More recent models have been presented as idealized canonical computations, distinct from mechanistic explanations, due to the lack of identifiable cortical components. Currently, the entire enterprise of coming up with a single canonical explanation has been criticized as being misguided, and the premise of the uniformity of the cortex has been strongly challenged. This debate is analyzed here. The legacy of the canonical circuit concept is reflected in both positive and negative ways in recent large-scale brain projects, such as the Human Brain Project. One positive aspect is that these projects might achieve the aim of producing detailed simulations of cortical electrical activity, a negative one regards whether they will be able to find ways of simulating how circuits actually develop.

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Section: Introductionmentioning

confidence: 99%

The search of “canonical” explanations for the cerebral cortex

Plebe

2018

HPLS

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“…This biologically inspired model incorporates several known or plausible organizational attributes of the cortex. The first model of this type was introduced and investigated earlier by Farhat [9]- [11].…”

Section: Introductionmentioning

confidence: 99%

Self-Organization in a Parametrically Coupled Logistic Map Network: A Model for Information Processing in the Visual Cortex

Pashaie

Farhat

2009

IEEE Trans. Neural Netw.

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In this paper, a new model seeking to emulate the way the visual cortex processes information and interacts with subcortical areas to produce higher level brain functions is described. We developed a macroscopic approach that incorporates salient attributes of the cortex based on combining tools of nonlinear dynamics, information theory, and the known organizational and anatomical features of cortex. Justifications for this approach and demonstration of its effectiveness are presented. We also demonstrate certain capabilities of this model in producing efficient sparse representations and providing the cortical computational maps. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This journal article is available at ScholarlyCommons: http://repository.upenn.edu/ese_papers/477 Abstract-In this paper, a new model seeking to emulate the way the visual cortex processes information and interacts with subcortical areas to produce higher level brain functions is described. We developed a macroscopic approach that incorporates salient attributes of the cortex based on combining tools of nonlinear dynamics, information theory, and the known organizational and anatomical features of cortex. Justifications for this approach and demonstration of its effectiveness are presented. We also demonstrate certain capabilities of this model in producing efficient sparse representations and providing the cortical computational maps.

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Corticonic models of brain mechanisms underlying cognition and intelligence

Cited by 2 publications

References 95 publications

The search of “canonical” explanations for the cerebral cortex

The search of “canonical” explanations for the cerebral cortex

Self-Organization in a Parametrically Coupled Logistic Map Network: A Model for Information Processing in the Visual Cortex

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