Neural responses to visual stimuli exhibit complex temporal dynamics, including sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic (ECoG) recordings from patients presented with stimuli that varied in contrast, duration, and inter-stimulus interval (ISI). Aggregating data across patients yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several non-linear features: peak response amplitude saturates with high contrast and longer stimulus durations; the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs; response latency decreases with increasing contrast. These features are accurately captured by a computational model comprised of a small set of canonical neuronal operations: linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast-and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex, and demonstrate that a simple model captures these dynamics at millisecond resolution.2

Neural responses to visual stimuli exhibit complex temporal dynamics, including sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic (ECoG) recordings from patients presented with stimuli that varied in contrast, duration, and inter-stimulus interval (ISI). Aggregating data across patients yielded 88 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several non-linear features: peak response amplitude saturates with high contrast and longer stimulus durations; the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs; response latency decreases with increasing contrast. These features are accurately captured by a computational model comprised of a small set of canonical neuronal operations: linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex, and demonstrate that a simple model captures these dynamics at millisecond resolution.

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across large regions of occipital cortex, reflecting general cognitive states such as attention, arousal, and alertness. However, there is also evidence that modulation of alpha oscillations in visual cortex can be spatially specific. Here, we used intracranial electrodes in human patients to measure alpha oscillations in multiple visual areas in response to visual stimuli whose location varied systematically across the visual field. We used a model-based approach to separate the alpha oscillation from broadband power changes. Using a population receptive field (pRF) model to explain the pattern of the alpha signal, we find that the alpha pRF centers are similar to those estimated from broadband (70–180 Hz) time series, but the sizes are several times larger. The results demonstrate that alpha suppression in human visual cortex can be precisely tuned. Finally, we show how the pattern of alpha responses can explain several features of exogenous visual attention.

Prosaccades are saccadic eye movements made reflexively in response to the sudden appearance of visual stimuli, whereas antisaccades are saccades that are directed to a location opposite a stimulus. Bibi and Edelman (Bibi R, Edelman JA. J Neurophysiol 102: 3101–3110, 2009) demonstrated that decreases in reaction time resulting from training prosaccades along one spatial axis (horizontal or vertical) could transfer to prosaccades made along the other axis. To help determine whether visual or motor-related processes underlie this facilitation, in the present study we trained participants to make prosaccades and probed their performance (reaction time, error rate) on antisaccade trials and vice versa. Subjects were probed for the effects of training on saccade performance before, during, and after 12 sessions of training. Training on prosaccades improved performance on both pro- and antisaccade tasks. Antisaccade training, with either a classic step task or a gap task, improved performance on gap prosaccades, though by less than it improved antisaccade performance, but had limited effect on an overlap prosaccade task. Across all subjects, training on one task only rarely had an adverse impact on an untrained task. These findings suggest that the predominant effect of saccade training is to facilitate fixation disengagement and motor preparation processes while having little impact on visual input to the saccadic system. NEW & NOTEWORTHY This is the first systematic examination of whether training of prosaccades and antisaccades is task specific or instead transfers to the other saccade type. It finds that training tends to improve performance of all saccade types tested. These behavioral results provide insight into saccade neurophysiology, suggesting that saccade training enhances processes related to motor excitation and inhibition.