Origins: Brain and Self Organization

By Karl Pribram | Go to book overview
msec (7D), the pattern has again shifted, and frontal sites J and L are involved with visual sites. In summary, dynamic self-organization in the brain during execution of this visuomotor pattern discrimination task may be characterized by patterns of significant between-sites coherence, which change on a fraction-of-a-second basis.
DYNAMIC SELF-ORGANIZATION AND CORTICAL INFORMATION PROCESSING
These results do not afford an exact description of the spatial patterning of task-related coherence in the cortex in terms of the functionality of the participating sites. However, they are suggestive of a general functional scheme for cortical information processing at the systems level. Every cognitive task may be considered as a complex set of micro-steps, each with its own processing contingencies [21]. The cerebral cortex may then be viewed as a self- organizing network of high dimensionality which processes these cognitive micro-steps. The wide range of possible processing requirements mandates the need for a flexible system that is capable of spontaneous and rapid reorganization. The processing demands of each micro-step may be viewed as imposing a unique set of constraints on the system, restricting it to a particular network configuration, and thereby reducing its degrees of freedom.If integration of the participating network nodes occurs by temporal correlation, then the spatial pattern of coherence among cortical sites may represent the particular network configuration imposed by the immediate processing contingencies. The changing spatial pattern of coherence may then reflect the underlying change in network configuration that corresponds to the evolution of the cognitive micro-steps necessary for task execution.One way to test these ideas would be with more specific task manipulations and more functionally localized electrode placements. Thus, for example, electrodes could be placed in visual areas that are functionally identified as corresponding to particular aspects of visual function. e.g. color, shape, or movement. Then, tasks which specifically manipulate a given visual dimension would be expected to engage processing networks selectively involving the sites corresponding to that dimension. As another example, a recently identified area in frontal cortex that specifically subserves feature identification, and another that subserves spatial localization [22], would be expected to selectively participate in processing networks when tasks differentially require one or the other function.It has been shown elsewhere [2] that transient elevated cortical coherence is indicative of intermittent synchronization in single-trial LFP waveforms, and it has been suggested that synchronization may be a neural mechanism for cortical binding. Binding has been proposed by Damasio [23] as a general mechanism for the integration of processing components in distributed cortical regions during perception, recall, and behavior. According to Damasio, posterior cortical areas require communication with anterior areas in order to "guide the pattern of multiregional activations necessary to reconstitute an event". The spatial patterns of coherence in Figure 7 are certainly consistent with this view. In this framework, then, dynamic self-organization in the brain, reflected in spatial patterns of transient cortical coherence, may actually represent a fundamental neurocognitive operation that gives each individual a coherent sense of reality.
Acknowledgments
Supported by NIMH grants MH43370 to the EEG Systems Laboratory, San Francisco, and MH42900 to the Center for Complex Systems.
References
[1] M. P. Stryker et al., "Principles of cortical self-organization", in Neurobiology of Neocortex, P. Rakic and W. Singer (Eds.), New York: Wiley, 1988, pp. 115-136.
[2] S. L. Bressler, R. Coppola, and R. Nakamura, "Episodic multi-regional cortical coherence at multiple frequencies during visual task performance by the macaque monkey", Nature, In press.
[3] A. S. Gevins and S. L. Bressler, "Functional topography of the human brain", in Functional Brain Imaging, G.. Pfurtscheller and F. Lopes da Silva (Eds.), Bern: Hans Huber, 1988, pp. 99-116.

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