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.
Highlights
The general clique is much higher in proportion (40% in KO vs. 16% in WT), whereas the numbers of specific cells in the KO mice were greatly reduced (9%) in comparison to the 28% in the WT mice. This occurred while the basal firing rates in the basolateral amygdala (BLA), retrosplenial cortex (RSC) and anterior cingulate cortex (ACC) in the KO mice were comparable to those of the WT mice. These results show that the specific-to-general permutation logic remained intact after the NMDA receptors were deleted from the principal neurons in the forebrain throughout adulthood
We found that specific clique cells were again overwhelmingly concentrated in the layers 2 and 3 (L2/3) of the hamster prelimbic cortex (PrL) cortex (Figure 10J), whereas the general responsive cells and most of the three-event cells concentrated in the layers 5 and 6 (L5/6) (Figure 10K)
We systematically tested the six predictions made by the Theory of Connectivity. We show that this powerof-two-based permutation logic operated in seven different brain regions and in two animal species during processing appetitive, emotional and social experiences
Summary
Our knowledge regarding specific genes, neuron types and circuitry functions has expanded substantially since Ramón y Cajal pioneered brain research more than a century ago (Mountcastle, 1957; Hubel and Wiesel, 1962; Carraway and Leeman, 1973; Hökfelt et al, 1977; O’keefe and Nadel, 1979; Seeburg et al, 1990; Buck and Axel, 1991; Ramón y Cajal, 1995; Tsien et al, 1996a,b; Tang et al, 1999; Houweling and Brecht, 2008; Klausberger and Somogyi, 2008; Grillner et al, 2013; Kvitsiani et al, 2013; Xu and Südhof, 2013; Alberini and Kandel, 2014; Brichta and Greengard, 2014; Moser et al, 2014; Basu et al, 2016; Tsien, 2016). The human brain is estimated to have approximately 86 billion neurons (HerculanoHouzel, 2009), and each neuron has tens of thousands of synapses (Andersen, 1990), leading to over one hundred trillion synaptic connections On top of this astronomical complexity, one needs to map each connection or neuron to a given stimulus, yet possible numbers of stimuli that can be used are infinite given the complex, ever-changing nature of the world we live in. The unifying mathematical principle upon which evolution constructs the brain’s basic wiring and computational logic represents one of the top most difficult and unsolved meta-problems in neuroscience (Adolphs, 2015; Geman and Geman, 2016)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
