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Hofman MA. The Fractal Geometry of the Human Brain: An Evolutionary Perspective. ADVANCES IN NEUROBIOLOGY 2024; 36:241-258. [PMID: 38468036 DOI: 10.1007/978-3-031-47606-8_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
The evolution of the brain in mammals is characterized by changes in size, architecture, and internal organization. Consequently, the geometry of the brain, and especially the size and shape of the cerebral cortex, has changed notably during evolution. Comparative studies of the cerebral cortex suggest that there are general architectural principles governing its growth and evolutionary development. In this chapter, some of the design principles and operational modes that underlie the fractal geometry and information processing capacity of the cerebral cortex in primates, including humans, will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains.
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Affiliation(s)
- Michel A Hofman
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands.
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Xie K, Fox GE, Liu J, Lyu C, Lee JC, Kuang H, Jacobs S, Li M, Liu T, Song S, Tsien JZ. Brain Computation Is Organized via Power-of-Two-Based Permutation Logic. Front Syst Neurosci 2016; 10:95. [PMID: 27895562 PMCID: PMC5108790 DOI: 10.3389/fnsys.2016.00095] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 11/07/2016] [Indexed: 11/17/2022] Open
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.
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Affiliation(s)
- Kun Xie
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta UniversityAugusta, GA, USA; The Brain Decoding Center, Banna Biomedical Research Institute, Yunnan Academy of Science and TechnologyYunnan, China
| | - Grace E Fox
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta University Augusta, GA, USA
| | - Jun Liu
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta UniversityAugusta, GA, USA; The Brain Decoding Center, Banna Biomedical Research Institute, Yunnan Academy of Science and TechnologyYunnan, China
| | - Cheng Lyu
- Department of Computer Science and Brain Imaging Center, University of GeorgiaAthens, GA, USA; School of Automation, Northwestern Polytechnical UniversityXi'an, China
| | - Jason C Lee
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta University Augusta, GA, USA
| | - Hui Kuang
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta University Augusta, GA, USA
| | - Stephanie Jacobs
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta University Augusta, GA, USA
| | - Meng Li
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta UniversityAugusta, GA, USA; The Brain Decoding Center, Banna Biomedical Research Institute, Yunnan Academy of Science and TechnologyYunnan, China
| | - Tianming Liu
- Department of Computer Science and Brain Imaging Center, University of Georgia Athens, GA, USA
| | - Sen Song
- McGovern Institute for Brain Research and Center for Brain-Inspired Computing Research, Tsinghua University Beijing, China
| | - Joe Z Tsien
- Brain and Behavior Discovery Institute and Department of Neurology, Medical College of Georgia, Augusta UniversityAugusta, GA, USA; The Brain Decoding Center, Banna Biomedical Research Institute, Yunnan Academy of Science and TechnologyYunnan, China
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Hofman MA. Evolution of the human brain: when bigger is better. Front Neuroanat 2014; 8:15. [PMID: 24723857 PMCID: PMC3973910 DOI: 10.3389/fnana.2014.00015] [Citation(s) in RCA: 138] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 03/10/2014] [Indexed: 12/24/2022] Open
Abstract
Comparative studies of the brain in mammals suggest that there are general architectural principles governing its growth and evolutionary development. We are beginning to understand the geometric, biophysical and energy constraints that have governed the evolution and functional organization of the brain and its underlying neuronal network. The object of this review is to present current perspectives on primate brain evolution, especially in humans, and to examine some hypothetical organizing principles that underlie the brain's complex organization. Some of the design principles and operational modes that underlie the information processing capacity of the cerebral cortex in primates will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains, then otherwise would have been possible. In view of the central importance placed on brain evolution in explaining the success of our own species, one may wonder whether there are physical limits that constrain its processing power and evolutionary potential. It will be argued that at a brain size of about 3500 cm(3), corresponding to a brain volume two to three times that of modern man, the brain seems to reach its maximum processing capacity. The larger the brain grows beyond this critical size, the less efficient it will become, thus limiting any improvement in cognitive power.
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Affiliation(s)
- Michel A Hofman
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences Amsterdam, Netherlands
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