A combination of experimental and modeling approaches was used to study cellular-molecular mechanisms underlying the expression of short-term potentiation (STP) and long-term potentiation (LTP) of glutamatergic synaptic transmission in the hippocampal slice. Electrophysiological recordings from dentate granule cells revealed that highfrequency stimulation of perforant path afferents induced a robust STP and LTP of both (؎)-␣-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) and N-methyl-Daspartic acid (NMDA) receptor-mediated synaptic responses. However, the decay time constant for STP of the AMPA receptor-mediated excitatory postsynaptic potential was approximately 6 min, whereas the decay time constant for STP of the NMDA receptor-mediated excitatory postsynaptic potential was only 1 min. In addition, focal application of agonists during the expression of STP revealed that the magnitude of conductance change elicited by NMDA application was significantly enhanced, whereas the magnitude of conductance change elicited by application of AMPA remained constant. These findings are most consistent with a postsynaptic mechanism of STP and LTP. Different putative mechanisms were evaluated formally using a computational model that included diffusion of glutamate within the synaptic cleft, different kinetic properties of AMPA and NMDA receptor͞channels, and geometric relations between presynaptic release sites and postsynaptic receptor͞channels. Simulation results revealed that the only hypothesis consistent with experimental data is that STP and LTP ref lect a relocation of AMPA receptor͞channels in the postsynaptic membrane such that they become more closely ''aligned'' with presynaptic release sites. The same mechanism cannot account for STP or LTP of NMDA receptor-mediated responses; instead, potentiation of the NMDA receptor subtype is most consistent with an increase in receptor sensitivity or number.Long-term potentiation (LTP) is a widely studied form of use-dependent synaptic plasticity expressed robustly by glutamatergic synapses of the hippocampus. The initial stage of LTP expression, typically identified as short-term potentiation (STP), is characterized by a rapid decay in the magnitude of potentiation to an asymptotic, steady-state level. Although there is a convergence of evidence concerning the cellular͞ molecular mechanisms mediating the induction of N-methyl-D-aspartic acid (NMDA) receptor-dependent STP and LTP (1), there remains substantial debate as to whether the expression of potentiation reflects change in presynaptic release mechanisms or postsynaptic receptor-channel function. Because of the synaptic coexistence of (Ϯ)-␣-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) and NMDA glutamatergic receptor subtypes (2), substantial differences in the magnitude of LTP expressed by AMPA and NMDA receptors would favor a mechanism that is postsynaptic in origin. Several studies have reported a more substantial induction of AMPA receptor-mediated LTP compared with NMDA receptormedi...

An interdisciplinary multilaboratory effort to develop an implantable neural prosthetic that can coexist and bidirectionally communicate with living brain tissue is described. Although the final achievement of such a goal is many years in the future, it is proposed that the path to an implantable prosthetic is now definable, allowing the problem to be solved in a rational, incremental manner. Outlined in this report is our collective progress in developing the underlying science and technology that will enable the functions of specific brain damaged regions to be replaced by multichip modules consisting of novel hybrid analog/digital microchips. The component microchips are "neurocomputational" incorporating experimentally based mathematical models of the nonlinear dynamic and adaptive properties of biological neurons and neural networks. The hardware developed to date, although limited in capacity, can perform computations supporting cognitive functions such as pattern recognition, but more generally will support any brain function for which there is sufficient experimental information. To allow the "neurocomputational" multichip module to communicate with existing brain tissue, another novel microcircuitry element

Presynaptic mechanisms influencing the probability of neurotransmitter release from an axon terminal, such as facilitation, augmentation, and presynaptic feedback inhibition, are fundamental features of biological neurons and are cardinal physiological properties of synaptic connections in the hippocampus. The consequence of these presynaptic mechanisms is that the probability of release becomes a function of the temporal pattern of action potential occurrence, and hence, the strength of a given synapse varies upon the arrival of each action potential invading the terminal region. From the perspective of neural information processing, the capability of dynamically tuning the synaptic strength as a function of the level of neuronal activation gives rise to a significant representational and processing power of temporal spike patterns at the synaptic level. Furthermore, there is an exponential growth in such computational power when the specific dynamics of presynaptic mechanisms varies quantitatively across axon terminals of a single neuron, a recently established characteristic of hippocampal synapses. During learning, alterations in the presynaptic mechanisms lead to different pattern transformation functions, whereas changes in the postsynaptic mechanisms determine how the synaptic signals are to be combined. We demonstrate the computational capability of dynamic synapses by performing speech recognition from unprocessed, noisy raw waveforms of words spoken by multiple speakers with a simple neural network consisting of a small number of neurons connected with synapses incorporating dynamically determined probability of release. The dynamics included in the model are consistent with available experimental data on hippocampal neurons in that parameter values were chosen so as to be consistent with time constants of facilitative and inhibitory processes governing the dynamics of hippocampal synaptic transmission studied using nonlinear systems analytic procedures.

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