The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI. functional Magnetic Resonance Imaging) to the underpinning neural networks. Models tied to human brain imaging data often focus on a few "boxes" based on brain regions associated with exceptionally high blood flow, rather than analyzing the cooperative computation of multiple brain regions. For analysis directly at the level of such data, a schema-based model may be most appropriate. To further address neurophysiological data, the Synthetic PET imaging method uses computational models of biological neural circuitry based on animal data to predict and analyze the results of human PET studies. This technique makes use of the hypothesis that rCBF (regional cerebral blood flow) is correlated with the integrated synaptic activity in a localized brain region. We also describe the possible extension of the Synthetic PET method to fMRI. The second half of the paper then exemplifies this general research program with two case studies, one on visuo-motor processing for control of grasping (Section 3 in which the focus is on Synthetic PET) and the imitation of motor skills (Sections 4 and 5, with a focus on Synthetic fMRI). Our discussion of imitation pays particular attention to data on the mirror system in monkey (neural circuitry which allows the brain to recognize actions as well as execute them). Finally, Section 6 outlines the immense challenges in integrating models of different portions of the nervous system which address detailed neurophysiological data from studies of primates and other species; summarizes key issues for developing the methodology of Synthetic Brain Imaging; and shows how comparative neuroscience and evolutionary arguments will allow us to extend Synthetic Brain Imaging even to language and other cognitive functions for which few or no animal data are available.

Animals↗

PubMedDate not supplied

A cortico-subcortical model for generation of spatially accurate sequential saccades.

This article provides a systems framework for the analysis of cortical and subcortical interactions in the control of saccadic eye movements, A major thesis of this model is that a topography of saccade direction and amplitude is preserved through multiple projections between brain regions until they are finally transformed into a temporal pattern of activity that drives the eyes to the target. The control of voluntary saccades to visual and remembered targets is modeled in terms of interactions between posterior parietal cortex, frontal eye fields, the basal ganglia (caudate and substantia nigra), superior colliculus, mediodorsal thalamus, and the saccade generator of the brainstem. Interactions include the modulation of eye movement motor error maps by topographic inhibitory projections, dynamic remapping of spatial target representations in saccade motor error maps, and sustained neural activity that embodies spatial memory. Models of these mechanisms implemented in our Neural Simulation Language simulate behavior and neural activity described in the literature, and suggest new experiments.

Animals↗

PubMedDate not supplied

Functional anatomy of pointing and grasping in humans.

The functional anatomy of reaching and grasping simple objects was determined in nine healthy subjects with positron emission tomography imaging of regional cerebral blood flow (rCBF). In a prehension (grasping) task, subjects reached and grasped illuminated cylindrical objects with their right hand. In a pointing task, subjects reached and pointed over the same targets. In a control condition subjects looked at the targets. Both movement tasks increased activity in a distributed set of cortical and subcortical sites: contralateral motor, premotor, ventral supplementary motor area (SMA), cingulate, superior parietal, and dorsal occipital cortex. Cortical areas including cuneate and dorsal occipital cortex were more extensively activated than ventral occipital or temporal pathways. The left parietal operculum (putative SII) was recruited during grasping but not pointing. Blood flow changes were individually localized with respect to local cortical anatomy using sulcal landmarks. Consistent anatomic landmarks from MRI scans could be identified to locate sensorimotor, ventral SMA, and SII blood flow increases. The time required to complete individual movements and the amount of movement made during imaging correlated positively with the magnitude of rCBF increases during grasping in the contralateral inferior sensorimotor, cingulate, and ipsilateral inferior temporal cortex, and bilateral anterior cerebellum. This functional-anatomic study defines a cortical system for "pragmatic' manipulation of simple neutral objects.

Adult↗

PubMedDate not supplied

A model of cerebellar metaplasticity.

The term "learning rule" in neural network theory usually refers to a rule for the plasticity of a given synapse, whereas metaplasticity involves a "metalearning algorithm" describing higher level control mechanisms for apportioning plasticity across a population of synapses. We propose here that the cerebellar cortex may use metaplasticity, and we demonstrate this by introducing the Cerebellar Adaptive Rate Learning (CARL) algorithm that concentrates learning on those Purkinje cell synapses whose adaptation is most relevant to learning an overall pattern. Our results show that this biologically plausible metalearning algorithm not only improves significantly the learning capability of the cerebellum but is very robust. Finally, we identify several putative neurochemicals that could be involved in a cascade of events leading to adaptive learning rates in Purkinje cell synapses.

Adaptation, Physiological↗