Some Principles in the Brain Analysis of Important Signals: Mapping and Stimulus Recognition

Abstract

This essay addresses two questions: (1) What are the meanings of different kinds of brain maps? (2) Can the recognition of important communicative signals and other stimuli known to the system be adequately explained by an ensemble code? Several kinds and grades of brain maps are distinguished. Before we can properly state the meaning, especially of the higher forms of multiple and multifactor maps, we need to learn where they project. At the higher levels this is a labor-intensive task, requiring also ingenuity and ethological thinking to devise stimuli. The neuronal basis of recognition in those cases where behavior or perception is triggered in an either-or manner has chiefly been attributed to one or the other of two classes of models: (a) a large spatiotemporal configuration of many kinds of cells in which there is little convergence of input, and (b) a small set of nearly equivalent cells after successive convergences. The latter is known to exist but it is not clear how far it goes or for what classes of stimuli. The former is a more popular view but carries several burdens in required assumptions and is essentially not demonstrable or disprovable. I believe both exist and operate in sequence: specific ensembles are inputs to small sets of equivalent recognition units and specific arrays of different recognition units at higher and higher levels of abstraction may constitute the specific configurations for the most sophisticated recognitions. Our information base is pitifully small, especially in comparative physiology of higher integrative functions of the brain and in comparative behaviour.

Long-term temporal integration in the anuran auditory system

“…In the sensory periphery, these signals are represented by unique spatiotemporal patterns of activity. It is still unclear to what extent these spatiotemporal patterns are read by higher-order 'detectors' of temporal features 6 .…”

The role of broadband inhibition in the rate representation of spectral cues for sound localization in the inferior colliculus

“…This initial Fourier-like analysis is largely linear and a great deal may be learned about the information content of the neural response by parametric manipulations of simple auditory stimuli (Le Prell et al, 1996;May and Huang, 1997;Sachs and Young, 1980). When the distributed representation of the sound's physical characteristics reaches higher levels of processing, unique patterns of convergence establish neural receptive fields that are tuned to discrete acoustic features (Bullock, 1986;Kolomiets et al, 2001;Majorossy and Kiss, 1994;Oliver, 1987). For example, bilateral projections from the ventral cochlear nuclei merge in the superior olive to endow local neurons with a sensitivity for interaural level or time disparities (ILDs and ITDs) (Glendenning et al, 1985;Oliver et al, 2003;Tsuchitani, 1988).…”