Lateralization of Minicolumns in Human Planum temporale Is Absent in Nonhuman Primate Cortex

Buxhoeveden, Daniel P.; Switala, Andrew E.; Litaker, Mark S.; Roy, Emil; Casanova, Manuel F.

doi:10.1159/000047253

Cited by 153 publications

(118 citation statements)

References 74 publications

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“…Also, Urbanc et al (25) used a crosscorrelation density-map method to study spatial relationships between the position and morphology of plaques with changes in neuronal architecture and revealed a focal neuronal toxicity associated with thioflavin S-positive plaque deposits in both AD and transgenic mice. Others, such as Casanova and Buxhoeveden, developed a method to quantify individually identified microcolumns, applying it to different human brain disorders (e.g., autism) (9)(10)(11)27), ʈ and to identify microcolumnar organization across species (28)(29). ** Their method requires that sections be oriented so that visually observed microcolumns align vertically.…”

Section: Discussionmentioning

confidence: 99%

Age-related reduction in microcolumnar structure in area 46 of the rhesus monkey correlates with behavioral decline

Cruz

Roe

Urbanc

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

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Many age-related declines in cognitive function are attributed to the prefrontal cortex, area 46 being especially critical. Yet in normal aging, studies indicate that neurons are not lost in area 46, suggesting that impairments result from more subtle processes. One cortical feature that is functionally important, but that has not been examined in normal aging because of a lack of efficient quantitative methods, is the vertical arrangement of neurons into microcolumns, a fundamental computational unit of the cortex. By using a density-map method derived from condensed-matter physics, we quantified microcolumns in area 46 of seven young and seven aged rhesus monkeys that had been cognitively tested. This analysis demonstrated that there is no age-related reduction in total neuronal density or in microcolumn width, length, or periodicity. There was, however, a statistically significant decrease in the strength of microcolumns, indicating microcolumnar disorganization. This reduction in strength was significantly correlated with age-related cognitive decline on tests of spatial working memory and recognition memory independent of the effect of age. Modeling demonstrated that random neuron displacements of Ϸ30% of a neuronal diameter (<3 m) produced the observed reduction in strength. Hence, it is possible that, with changes in dendrites and myelinated axons, subtle displacements of neurons occur that alter microcolumnar structure and correlate with ageinduced dysfunction. Therefore, quantitative measurement of microcolumnar structure may provide a sensitive morphological method to assay microcolumnar function in aging and other conditions. minicolumns ͉ density map ͉ cerebral cortex ͉ primate brain ͉ modeling

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Section: Discussionmentioning

confidence: 99%

Age-related reduction in microcolumnar structure in area 46 of the rhesus monkey correlates with behavioral decline

Cruz

Roe

Urbanc

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

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“…These differences suggest that alterations in minicolumn organization-in autism-may have a profound impact on hemispheric specialization and functions that dependent on hemispheric specialization (such as language). In normal brain, the width of minicolumns and the distance between the columns is larger on the left than on the right [Seldon, 1981a[Seldon, , 1981b[Seldon, , 1982Buxhoeveden et al, 2001]. Seldon [1981aSeldon [ , 1981bSeldon [ , 1982 also showed that pyramidal cells in the posterior language cortex on the left contacted fewer columnar units than on the right.…”

Section: Brain Serotonin In Autistic Childrenmentioning

confidence: 97%

Serotonin in autism and pediatric epilepsies

Chugani

2004

Ment. Retard. Dev. Disabil. Res. Rev.

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Serotonergic abnormalities have been reported in both autism and epilepsy. This association may provide insights into underlying mechanisms of these disorders because serotonin plays an important neurotrophic role during brain development-and there is evidence for abnormal cortical development in both autism and some forms of epilepsy. This review explores the hypothesis that an early disturbance in the serotonin system affects cortical development and the development of thalamocortical innervation, and is a potential mechanism, common to autism and pediatric epilepsies associated with cortical dysplasia. An argument is made that cortical malformation leads to abnormalities of thalamocortical connectivity, and that serotonin plays a critical role in this process. Finally, a role for altered metabolism of the serotonin precursur, tryptophan, in both epilepsy and autism is discussed. Key Words: serotonin; autism; epilepsy; tryptophan; cortical development; kynurenine E pilepsy is more common among autistic children than in the general population; conversely, autism (or milder pervasive developmental disorders) is more common in epileptic children than in the general population. There is evidence for abnormalities of the neurotransmitter serotonin in both epilepsy and autism. The role of serotonin in brain development is briefly reviewed here and then the evidence considered for a role of an altered serotonin system in these developmental disorders. We hypothesize that serotonergic abnormalities during prenatal and early postnatal development may lead to changes in thalamocortical connectivity, which results in a predisposition for autism and epilepsy. In addition, we discuss the involvement of aberrant metabolism of tryptophan-the metabolic precursor of serotonin-as a potential mechanism for alterations in serotonin availability.

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“…This implies that unique aspects of human language may result from derived changes in one or more of these regions, along with, perhaps, changes in how they interface with each other during development and language processing. One example may be the planum temporale, a region associated with language processing that appears to have undergone internal changes in the organization of minicolumns compared with chimpanzees, and specifically in the left hemisphere (85). Some regions involved in human language processing exhibit substantial laterality (83), have greater connectivity between them via white matter pathways (86), and have greater connectivity to other brain areas than do orthologous regions in nonhuman primates (87).…”

Section: Explaining Human Cognitionmentioning

confidence: 99%

A hierarchical model of the evolution of human brain specializations

Barrett

2012

Proc. Natl. Acad. Sci. U.S.A.

120

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The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domainspecific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised.hat is the nature of the brain mechanisms that give rise to human cognition, and how do these mechanisms evolve? Although it is clear that human cognition, like all organismal traits, must be accounted for by some combination of ancestral and derived brain processes, attempts to decompose human mental processes into functional components whose features have been shaped by the process of natural selection-i.e., adaptations-have been highly contested and controversial (1). The controversy centers on the difficulty of establishing whether a particular aspect of cognition or behavior is the result of an adaptation or adaptations, and in what way. Is a given cognitive ability in humans or any other species-for example, the ability to discriminate between different quantities of objects, to navigate spatially, or to learn to speak a language-the product of an adaptation specifically for that ability? Or is it just a specific instantiation of a more general ability, such as associative learning, or the general computational properties of neural networks? Or is it not the result of adaptations at all? Proposals about functional specialization have long been a source of debate in psychology and the brain sciences. In particular, there is little agreement over whether cognitive processes other than perceptual and motor processes-i.e., so-called higher-level processes-are specialized, and if so, how (2). At stake are both theoretical and empirical issues. Theoretically, although it is clear that the brain is the product of evolutionary processes, including natural selection, we cannot move past this simple truism if we are unable to answer the question of what adaptations it contains, or to distinguish the results of natural selection from the results of other processes. Empirically, a v...

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Lateralization of Minicolumns in Human Planum temporale Is Absent in Nonhuman Primate Cortex

Cited by 153 publications

References 74 publications

Age-related reduction in microcolumnar structure in area 46 of the rhesus monkey correlates with behavioral decline

Age-related reduction in microcolumnar structure in area 46 of the rhesus monkey correlates with behavioral decline

Serotonin in autism and pediatric epilepsies

A hierarchical model of the evolution of human brain specializations

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