Effects of synaptic noise and filtering on the frequency response of spiking neurons.

Noise can have a significant impact on the response dynamics of a nonlinear system. For neurons, the primary source of noise comes from background synaptic input activity. If this is approximated as white noise, the amplitude of the modulation of the firing rate in response to an input current oscillating at frequency omega decreases as 1/square root[omega] and lags the input by 45 degrees in phase. However, if filtering due to realistic synaptic dynamics is included, the firing rate is modulated by a finite amount even in the limit omega-->infinity and the phase lag is eliminated. Thus, through its effect on noise inputs, realistic synaptic dynamics can ensure unlagged neuronal responses to high-frequency inputs.

Divisive inhibition in recurrent networks.

Models of visual cortex suggest that response selectivity can arise from recurrent networks operating at high gain. However, such networks have a number of problematic features: (i) they operate perilously close to a point of instability, (ii) small changes in synaptic strength can dramatically modify the degree of amplification, and (iii) they respond slowly to rapidly changing stimuli. Divisive inhibition, acting through interneurons that are themselves divisively inhibited, can solve these problems without degrading the selectivity of a recurrent network.

Complex cells as cortically amplified simple cells.

The majority of synapses in primary visual cortex mediate excitation between nearby neurons, yet the role of local recurrent connections in visual processing remains unclear. We propose that these connections are responsible for the spatial-phase invariance of complex-cell responses. In a network model with selective cortical amplification, neurons exhibit simple-cell responses when recurrent connections are weak and complex-cell responses when they are strong, suggesting that simple and complex cells are the low- and high-gain limits of the same basic cortical circuit. Given the ubiquity of invariant responses in cognitive processing, the recurrent mechanism we propose for complex cells may be widely applicable.

Synaptic depression and the temporal response characteristics of V1 cells.

We explore the effects of short-term synaptic depression on the temporal dynamics of V1 responses to visual images by constructing a model simple cell. Synaptic depression is modeled on the basis of previous detailed fits to experimental data. A component of synaptic depression operating in the range of hundreds of milliseconds can account for a number of the unique temporal characteristics of cortical neurons, including the bandpass nature of frequency-response curves, increases in response amplitude and in cutoff frequency for transient stimuli, nonlinear temporal summation, and contrast-dependent shifts in response phase. Synaptic depression also provides a mechanism for generating the temporal phase shifts needed to produce direction selectivity, and a model constructed along these lines matches both extracellular and intracellular data. A slower component of depression can reproduce the effects of contrast adaptation.