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 language | English (US) |
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Article number | 95 |
Journal | Frontiers in Systems Neuroscience |
Volume | 10 |
Issue number | NOV |
DOIs | |
State | Published - Nov 15 2016 |
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