Imaging connectivity in the human cerebral cortex: The next frontier?

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 pathways. The connectivity of the human cerebral cortex became a favorite area of research in the second half of the 19 century. Charcot, Wernicke, Lichtheim and Freud, among others, published elaborate diagrams depicting cortical association pathways implicated in aphasias and kindred disorders. 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 patients. 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 another. 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 1, 2, and 3 order unimodal association areas and then to multimodal convergence zones in heteromodal, paralimbic, and limbic cortices. 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 knowledge. 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 constraints. 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 monkeys, but daunting for domains such as language where homologies were not apparent. EDITORIAL