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• W2031694025 abstract "Nothing defines the function of a neuron more faithfully than the nature of its inputs and outputs. Auditory cortex serves radically different functions from those of visual cortex not because of differences in genes, molecules, or transmitters, but because of differences in connectivity. Although neural connections have been investigated rigorously in many animal species, including monkeys, little progress has been made in the human. This gap is frequently overlooked so that pathways that have been verified only in animals become cited as if they also existed in the human, a leap of faith that may be particularly problematic when addressing substrates of uniquely human behaviors. In this issue of the Annals, Catani and colleagues address this area of research as they apply the method of diffusion tensor imaging (DTI) to the in vivo tracing of language-related pathways1. The connectivity of the human cerebral cortex became a favorite area of research in the second half of the 19th century. Charcot, Wernicke, Lichtheim and Freud, among others, published elaborate diagrams depicting cortical association pathways implicated in aphasias and kindred disorders2-5. The diagrams were ingenious but they were based on postulated rather than documented connections. The monumental work of Jules Dejerine provided one of the few exceptions. Using myelin stains, he reconstructed the trajectory of damaged pathways in aphasic and agnosic patients6. Although the method had poor anatomical resolution, it provided seminal insights concerning the role of cortico-cortical pathways in cognition. As the aftermath of WWI and WWII transformed English into the dominant language of science, the rich French and German literature on connectivity became overlooked, triggering a period of stagnation for behavioral neurology. The reawakening of this field can be traced to the publication of Norman Geschwind's 1965 papers on “Disconnexion Syndromes.” In these papers, Geschwind revisited the classic literature on connectivity and restated, in modern neuroscientific idiom, the view that aphasias, agnosias and apraxias were caused by the interruption of specific pathways connecting one region of association cortex to another7. This formulation was particularly daring since it was based on predictions rather than facts concerning the true connectivity of the cerebral cortex. At around that time, developments in the selective silver impregnation of axonal degeneration in monkeys confirmed many of Geschwind's predictions. Experiments based on these methods demonstrated monosynaptic pathways that mediated apparently serial transfers of information from primary sensory areas to 1st, 2nd, and 3rd order unimodal association areas and then to multimodal convergence zones in heteromodal, paralimbic, and limbic cortices8, 9. Damage to pathways leading to the multimodal convergence zones, assuming that such pathways are also present in the human, were proposed as the anatomical substrates for Geshwind's disconnection syndromes. A few years later, the development of more sensitive methods based on axonally transported tracers revealed an even more complex web of pathways that enabled not only serial but also parallel projections in ways that could greatly enhance the flexibility of information processing. These discoveries on the cortico-cortical connectivity of the monkey brain helped to introduce current concepts on the anatomical organization of behavior. According to these views, heteromodal, paralimbic and limbic cortices, collectively known as “transmodal” areas, are likely to play their critical roles in cognition by binding multiple cortical areas into integrated networks rather than by containing convergent end-products of knowledge10-13. Such distributed networks contain “essential” as well as “ancillary” components and are organized around a central axis of at least two interconnected transmodal epicenters (for example Broca's and Wernicke's areas in the case of language). Each network component, ancillary as well as essential, is interconnected with both epicenters. This arrangement enables a powerful computational architecture containing multiple nodes for serial-to-parallel transitions so that a cognitive problem (such as naming an object or reconstructing a memory) can trigger a rapid survey of a vast informational landscape until the entire system settles into a state of best fit through a simultaneous (parallel) consideration of goals and constraints10. The essential components of large-scale networks can be identified by the traditional localization of lesions in patients with cognitive impairments. However, the location of the ancillary components and the details of interconnectivity among network components had to be inferred from experiments in laboratory primates. This was relatively straightforward for domains such as spatial attention where analogous networks could be identified in monkeys14, 15, but daunting for domains such as language where homologies were not apparent. The advent of functional imaging, based on task-dependent hemodynamic changes, addressed this limitation by allowing the simultaneous visualization of nearly all network components, essential as well as ancillary, in subjects performing specific cognitive tasks. But currently available methods of functional imaging are unable to reveal how areas activated by a task are anatomically interconnected. Because of this limitation, functional imaging is at a stage where it may paradoxically promote a regression of behavioral neurology into a new sort of phrenology where the cerebral cortex becomes carved up into hyperspecialized patches that give no clue concerning how (or if) they are interconnected to form integrated networks. It is fortunate, therefore, that MRI, one of the major tools employed for hemodynamically-based functional imaging, can also yield information potentially relevant to neural connectivity. This aspect of MRI depends on the tendency of water molecules to diffuse in the direction of myelinated fiber bundles, enabling diffusion-weighted MRI to yield tensor maps of fiber orientation. Regions of interest, identified on the basis of prior anatomical hypotheses or lesion sites, can provide seeding points for three dimensional fiber reconstruction algorithms based on the direction of water diffusion so that the trajectory (or loss) of a pathway can be traced from the seeding point to some other point in the brain. Using this diffusion tensor imaging (DTI) approach and specific hypotheses concerning the connectivity of language networks, Catani and colleagues identified white matter tracts that extend not only between Broca's area and Wernicke's area (the arcuate fasciculus of classic aphasiology) but also between Wernicke's area and the inferior parietal lobule and between the inferior parietal lobule and Broca's area. They point out that this arrangement allows Broca's and Wernicke's areas to communicate directly and also through the mediation of the inferior parietal lobule, an arrangement that supports the more flexible architecture of parallel processing. This arrangement also helps to explain why conduction aphasia, based on a disconnection between Broca's and Wernicke's areas, can have different substrates and therefore different clinical manifestations. Exciting and plausible as these results are, however, it is necessary to keep in mind that DTI is not perfect either. There is no proof that the fascicles it reveals have neurons of origin or terminal synaptic fields in the areas used for seeding. At the present, the validity of DTI in humans as well as animals has been established most convincingly for the cortico-spinal and geniculo-calcarine pathways where robust projections are known to form macroscopically identifiable bundles of homogeneous connectivity16-18. It remains to be seen if DTI is equally successful for tracing sparse association pathways. The ability of DTI to demonstrate a documented connection in the association cortex of the monkey brain would greatly enhance the face validity of results obtained in analogous neural systems of the human brain. As spectacular advances in fMRI are yielding unprecedented amounts of new information on the functional specialization of cortical areas, the need to understand the interconnectivity among these areas is becoming increasingly more pressing. A number of post-mortem or in vivo approaches are potentially available for this purpose, each subject to a specific set of limitations (Table 1). Among available in vivo methods, the DTI approach remains particularly promising. The method can potentially be used in conjunction with fMRI so that areas activated by a given cognitive function can be used to seed the fiber reconstruction algorithms, providing a selective tracing of connectivity within a behaviorally characterized network. An even more exciting but still speculative possibility is the use of fMRI to detect activations not only in cortical areas but also in corresponding white matter pathways so that the axons of activated cortical areas could be visualized selectively19. The revolution triggered by functional imaging has lost none of its momentum. However, the value of this rich information cannot be fully realized until equally rich information concerning the underlying connectivity of the relevant areas can be obtained. Unfortunately, the connectivity of the cerebral cortex is immensely complex. Despite the powerful methods based on tracers, immunolabeling, and electrical recordings, we still have a lot more to learn about the intricate local and inter-areal circuitry of the cerebral cortex, even in the monkey. The resolving power of the methods listed in Table 1 pale in comparison to those that have been applied to animals, a fact that could trigger considerable despair about the prospects for understanding the real connectivity of the human brain. But this is a not an age for despair. As recently as twenty years ago, who could have predicted the current achievements of fMRI? If imagers and neuroanatomists were to forge a targeted alliance for addressing this question, the next twenty years could well witness equally impressive advances in understanding the connectivity of the human cerebral cortex and its relevance to human cognition." @default.
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• W2031694025 date "2004-12-27" @default.
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• W2031694025 title "Imaging connectivity in the human cerebral cortex: The next frontier?" @default.
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• W2031694025 doi "https://doi.org/10.1002/ana.20368" @default.
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