Oscillations in many regions of the cortex have common temporal characteristics with dominant frequencies centered around the 40 Hz (gamma) frequency range and the 5–10 Hz (theta) frequency range. Experimental results also reveal spatially synchronous oscillations, which are stimulus dependent (Gray&Singer, 1987;Gray, König, Engel, & Singer, 1989; Engel, König, Kreiter, Schillen, & Singer, 1992). This rhythmic activity suggests that the coherence of neural populations is a crucial feature of cortical dynamics (Gray, 1994). Using both simulations and a theoretical coupled oscillator approach, we demonstrate that the spike frequency adaptation seen in many pyramidal cells plays a subtle but important role in the dynamics of cortical networks. Without adaptation, excitatory connections among model pyramidal cells are desynchronizing. However, the slow processes associated with adaptation encourage stable synchronous behavior.

We have examined a model by Holmes and Levy (1990) of the induction of associative long-term potentiation (LTP) by a rise in the free Ca 2+ concentration ([Ca 2+ ]) after synaptic activation of dendritic spines. The previously reported amplification of the change in [Ca 2+ ] caused by coactivation of several synapses was found to be quite sensitive to changes in the permeability of the N -methyl-D-aspartate (NMDA) receptor channels to Ca 2+ . Varying this parameter indicated that maximum amplification is obtained at values that are close to Ca 2+ permeabilities reported in the literature. However, amplification failed if permeability is reduced by more than 50%. We also found that the maximum free [Ca 2+ ] reached in an individual spine during synaptic coactivation of several spines depended on the location of that spine on the dendritic tree. Distal spines attained a higher [Ca 2+ ] than proximal ones, with differences of up to 80%. The implications of this result for the uniformity of induction of associative LTP in spines in different regions of the dendrite are discussed.

Periodic variations in correlated cellular activity have been observed in many regions of the cerebral cortex. The recent discovery of stimulus-dependent, spatially-coherent oscillations in primary visual cortex of the cat has led to suggestions of neural information encoding schemes based on phase and/or frequency variation. To explore the mechanisms underlying this behavior and their possible functional consequences, we have developed a realistic neural model, based on structural features of visual cortex, which replicates observed oscillatory phenomena. In the model, this oscillatory behavior emerges directly from the structure of the cortical network and the properties of its intrinsic neurons; however, phase coherence is shown to be an average phenomenon seen only when measurements are made over multiple trials. Because average coherence does not ensure synchrony of firing over the course of single stimuli, oscillatory phase may not be a robust strategy for directly encoding stimulus-specific information. Instead, the phase and frequency of cortical oscillations may reflect the coordination of general computational processes within and between cortical areas. Under this interpretation, coherence emerges as a result of horizontal interactions that could be involved in the formation of receptive field properties.