A POSSIBLE BASIC CORTICAL MICROCIRCUIT CALLED CASCADED INHIBITION - RESULTS FROM CORTICAL NETWORK MODELS AND RECORDING EXPERIMENTS FROM STRIATE SIMPLE CELLS

The robust behavior, the degree of response linearity, and the aspect of contrast gain control in visual cortical simple cells are (amongst others) the result of the interplay between excitatory and inhibitory afferent and intracortical connections. The goal nf this study was to suggest a simple intracortical connection pattern, which could also pl ay a role in other cortical substructures, in order to generically obt ain these desired effects within large physiological parameter ranges. To this end we explored the degree of linearity of spatial summation in visual simple cells experimentally and in different models based on half-wave rectifying cells (''push-pull models''). Visual cortical pu sh-pull connection schemes originated from antagonistic motor-control models. Thus, this model class is widely applicable but normally requi res a rather specific design. On the other hand we showed that a more generic version of a push-pull model, the so-called cascaded inhibitor y intracortical connection scheme, which we implemented in a biologica lly realistic simulation, naturally explains much of the experimental data. We investigated the influence of the afferent and intracortical connection structure on the measured linearity of spatial summation in simple cells. The analysis made use of the relative modulation measur e, which is easy to apply but is limited to moving sinusoidal grating stimuli. We introduced two basic push;pull models, where the order of threshold nonlinearity and linear summation is reversed. Very little d ifference is observed with the relative modulation measure for these m odels. Alterative models, like half-wave squaring models, were also br iefly discussed. Of all model parameters, the ratio of excitation to i nhibition in the simple cell exerts the most crucial influence on the relative modulation. Linearity deteriorates as soon as excitatory and inhibitory inputs are imbalanced and the relative modulation drops. Th is prediction was tested experimentally by extracellular recordings fr om cat area 17 simple cells and we found that about 62% showed a signi ficant deviation from linear behavior. The problem that individual bas ic push-pull models are hard to distinguish experimentally led us to s uggest a different solution. In order to generically account for the o bserved behavior (e.g., imbalance of excitation versus inhibition), we suggested a rather generic version of a push-pull model where it no l onger mattered about (the hard-to-distinguish) fine differences in con nectivity. Thus, we introduced a new class of biophysically realistic models (''cascaded inhibition''). This model class requires very littl e connection specificity and is therefore highly robust against parame ter variations. Up to 25 cells are connected to each target cell. Ther eby a highly interconnected network is generated, which also leads to disinhibition at some parts of an individual receptive field. We showe d that the performance of these models simulates the degree of lineari ty and its variability in recal simple cells with comparatively high a ccuracy. This behavior can be explained by the self-regulating propert ies of a cascaded inhibitory connection scheme by which the balance be tween excitation and inhibition at a given cell is improved by the joi nt network effects. The virtues and the generic design of this connect ion pattern, therefore, allow to speculate that it is used also in oth er parts of the cortex.