RESUMEN
Although great progress in neuroanatomy and physiology has occurred lately, we still cannot go directly to those levels to discover the neural mechanisms of higher cognition and consciousness. But we can use neurocomputational methods based on these details to push this project forward. Here we describe vector subtraction as an operation that computes sequential paths through high-dimensional vector spaces. Vector-space interpretations of network activity patterns are a fruitful resource in recent computational neuroscience. Vector subtraction also appears to be implemented neurally in primate frontal eye field activity, which computes dimensions of saccadic eye movements. We use this apparent neural implementation as a model and construct from it a general neurocomputational account of an important type of sequential cognitive and conscious process. We defend the biological plausibility of all components of the general model and show that it yields testable anatomical and physiological predictions. We close by suggesting some interesting consequences for consciousness if our model characterizes correctly the neural mechanisms producing a common type of episode in our conscious streams.
Asunto(s)
Cognición/fisiología , Estado de Conciencia/fisiología , Memoria , Red Nerviosa , Humanos , Modelos Teóricos , Percepción VisualRESUMEN
We employ computer simulation to investigate the function of neural circuitries between thalamic sensory relay nuclei, primary sensory cortices, and the thalamic reticular nucleus (TRN). Computational similarities exist between these circuits and the architecture of a simple artificial neural network. We impose processing parameters on this network architecture in keeping with anatomical and physiological details of the mammalian geniculo-cortical visual pathway, and then run the simulation on a task involving multiple simultaneous inputs from the simulated visual field. After two to three loops through the simulation, activity in cortical and thalamic units whose receptive fields include the stronger stimulus remains constant, while activity in other cortical and thalamic units activated by weaker stimuli declines toward resting values. These results suggest that the modeled neural circuitry functions to "prime" selective attentional mechanisms further up the visual streams toward specific portions of the total visual stimulus. Besides extending existing models and evidence about the function of these neural circuits, our results also provide physiologists with predicted activity profiles of thalamic and cortical elements of the modeled neural system for a task not yet studied experimentally.