Brain computation is organized via power-of-two-based permutation logic

Kun Xie, Grace E. Fox, Jun Liu, Cheng Lyu, Jason C. Lee, Hui Kuang, Stephanie Jacobs, Meng Li, Tianming Liu, Sen Song, Joseph Zhuo Tsien

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i –1),producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories,as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive,emotional and social information. However,modulatory neurons,such as dopaminergic (DA) neurons,use a simpler logic despite their distinct subtypes. Interestingly,this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood,suggesting that the logic is developmentally pre-configured. Moreover,this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction,pattern-discrimination and pattern-categorization using sparse code,consequently explaining why it requires hippocampal offline-consolidation. In contrast,the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation,emotion,consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum,ranging from the simplest neural networks to the most complex.

Original languageEnglish (US)
Article number95
JournalFrontiers in Systems Neuroscience
Volume10
Issue numberNOV
DOIs
StatePublished - Nov 15 2016

Fingerprint

Brain
Power (Psychology)
Dopaminergic Neurons
N-Methylaspartate
Consciousness
Intelligence
Cognition
Motivation
Emotions
Learning
Neurons

Keywords

  • Appetitive behavior
  • Cell assembly
  • Computational algorithms
  • Computational logic
  • Cortex
  • NMDA receptor
  • Social behavior
  • Wiring logic

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Developmental Neuroscience
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

Cite this

Brain computation is organized via power-of-two-based permutation logic. / Xie, Kun; Fox, Grace E.; Liu, Jun; Lyu, Cheng; Lee, Jason C.; Kuang, Hui; Jacobs, Stephanie; Li, Meng; Liu, Tianming; Song, Sen; Tsien, Joseph Zhuo.

In: Frontiers in Systems Neuroscience, Vol. 10, No. NOV, 95, 15.11.2016.

Research output: Contribution to journalArticle

Xie, K, Fox, GE, Liu, J, Lyu, C, Lee, JC, Kuang, H, Jacobs, S, Li, M, Liu, T, Song, S & Tsien, JZ 2016, 'Brain computation is organized via power-of-two-based permutation logic', Frontiers in Systems Neuroscience, vol. 10, no. NOV, 95. https://doi.org/10.3389/fnsys.2016.00095
Xie, Kun ; Fox, Grace E. ; Liu, Jun ; Lyu, Cheng ; Lee, Jason C. ; Kuang, Hui ; Jacobs, Stephanie ; Li, Meng ; Liu, Tianming ; Song, Sen ; Tsien, Joseph Zhuo. / Brain computation is organized via power-of-two-based permutation logic. In: Frontiers in Systems Neuroscience. 2016 ; Vol. 10, No. NOV.
@article{03f06c8b1cad4a6aae8d975520cdc153,
title = "Brain computation is organized via power-of-two-based permutation logic",
abstract = "There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i –1),producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories,as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive,emotional and social information. However,modulatory neurons,such as dopaminergic (DA) neurons,use a simpler logic despite their distinct subtypes. Interestingly,this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood,suggesting that the logic is developmentally pre-configured. Moreover,this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction,pattern-discrimination and pattern-categorization using sparse code,consequently explaining why it requires hippocampal offline-consolidation. In contrast,the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation,emotion,consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum,ranging from the simplest neural networks to the most complex.",
keywords = "Appetitive behavior, Cell assembly, Computational algorithms, Computational logic, Cortex, NMDA receptor, Social behavior, Wiring logic",
author = "Kun Xie and Fox, {Grace E.} and Jun Liu and Cheng Lyu and Lee, {Jason C.} and Hui Kuang and Stephanie Jacobs and Meng Li and Tianming Liu and Sen Song and Tsien, {Joseph Zhuo}",
year = "2016",
month = "11",
day = "15",
doi = "10.3389/fnsys.2016.00095",
language = "English (US)",
volume = "10",
journal = "Frontiers in Systems Neuroscience",
issn = "1662-5137",
publisher = "Frontiers Research Foundation",
number = "NOV",

}

TY - JOUR

T1 - Brain computation is organized via power-of-two-based permutation logic

AU - Xie, Kun

AU - Fox, Grace E.

AU - Liu, Jun

AU - Lyu, Cheng

AU - Lee, Jason C.

AU - Kuang, Hui

AU - Jacobs, Stephanie

AU - Li, Meng

AU - Liu, Tianming

AU - Song, Sen

AU - Tsien, Joseph Zhuo

PY - 2016/11/15

Y1 - 2016/11/15

N2 - There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i –1),producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories,as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive,emotional and social information. However,modulatory neurons,such as dopaminergic (DA) neurons,use a simpler logic despite their distinct subtypes. Interestingly,this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood,suggesting that the logic is developmentally pre-configured. Moreover,this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction,pattern-discrimination and pattern-categorization using sparse code,consequently explaining why it requires hippocampal offline-consolidation. In contrast,the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation,emotion,consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum,ranging from the simplest neural networks to the most complex.

AB - There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i –1),producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories,as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive,emotional and social information. However,modulatory neurons,such as dopaminergic (DA) neurons,use a simpler logic despite their distinct subtypes. Interestingly,this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood,suggesting that the logic is developmentally pre-configured. Moreover,this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction,pattern-discrimination and pattern-categorization using sparse code,consequently explaining why it requires hippocampal offline-consolidation. In contrast,the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation,emotion,consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum,ranging from the simplest neural networks to the most complex.

KW - Appetitive behavior

KW - Cell assembly

KW - Computational algorithms

KW - Computational logic

KW - Cortex

KW - NMDA receptor

KW - Social behavior

KW - Wiring logic

UR - http://www.scopus.com/inward/record.url?scp=84996486164&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84996486164&partnerID=8YFLogxK

U2 - 10.3389/fnsys.2016.00095

DO - 10.3389/fnsys.2016.00095

M3 - Article

AN - SCOPUS:84996486164

VL - 10

JO - Frontiers in Systems Neuroscience

JF - Frontiers in Systems Neuroscience

SN - 1662-5137

IS - NOV

M1 - 95

ER -