Brain and Values: Is a Biological Science of Values Possible

By Karl H. Pribram | Go to book overview

Introduction
Recent neurophysiologic, neuroanatomic, psychophysical, and computational modeling studies have begun to clarify the cortical organization and neuronal pathways through which an image on the retina is transformed into recognition of a face. Although many questions remain, the mechanisms involved in the transformation of the retinotopic image by the retina ( Miller, 1976 a,b, c), LGN ( Hubel, 1961), and striate cortex ( Hubel 1959, 1962) which have received the longest and most intense scrutiny, are beginning to be understood. Experimental evidence and models of the organization, development, structure, and function of simple cells, complex cells, and the orientation columns, are rapidly accumulating ( Rose, 1985; Obermeyer, 1993; Miller, 1994; Gilbert, 1996a,b). Early visual processing (up to and including the striate cortex) extracts a variety of features (referred to here as microfeatures) from the retinal image ( Van Essen, 1992), including edges and ends of contrast boundaries ( Von der Heydt, 1989), local color ( Zeki, 1983), texture, and energy in the spatial frequency bands ( De Valois, 1982; Movshon, 1978).Further along the processing pathways ( Baizer, 1991; McIntosh, 1994; Mishkin, 1982), cells in the inferior temporal (IT) cortex have been shown to respond selectively to highly complex stimuli ( Baylis, 1987; Desimone, 1984; Tanaka, 1993, 1996; Sary, 1995; Ito, 1995) including facial expressions and faces ( Baylis, 1985; Desimone, 1991; Rolls, 1994). However, the information processing paradigm in the intermediate stages between striate and IT cortex are largely unknown and it is the paradigm and its neurobiological plausibility, rather than the details of the cellular and subcellular mechanisms that support it, that is the primary subject of this paper.Accumulated observations, surveyed below, suggest that learning extends through multiple neuronal layers linking striate to IT cortex and can produce the observed responses of IT cortical cells. Learning rules followed within these layers can be derived from neuroanatomic and biophysical observations that implicate clusters of dendritic spines as fundamental architectural loci of information processing and memory storage. These loci are distributed throughout large arrays of neurons comprising multiple layers of brain structure. Taken together, these results suggest the formulation of three principles used to construct a unifying conceptual framework of information processing between striate and IT cortex:
1. Each axon makes multiple synaptic connections on a neuron ( Deuchars, 1994, Kaneko, 1994), providing a one-to-many connectivity between axons and synaptic spines that are located along a well-elaborated dendritic tree ( Larkman, 1991; Chicurel, 1992; Trommald, 1995),suggesting a rich spectrum of afferent combinations that enervate the dendritic spine clusters (DSCs).
2. A cluster of interacting synaptic spines, co-located on dendritic branches responds maximally to specific patterns of inputs ( Alkon, 1987; Harris, 1995; Liu, 1995; Eilers, 1995) and form a basic information processing unit of the CNS.
3. The signals corresponding to the micro-features generated by the striate cortex are not all independent; subsets of these signals are subject to functional constraints imposed by the properties of the external world. Membership in these subsets can be determined from the signals ( Saffran, 1996; Becker, 1996; Ghose, 1997).

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