EP Cognitive and Behavioural Neuroscience Seminar: Theta-rhythmic neuronal activity: a sampling mechanism for perception and attention?
Dr Michael Schmid (University of Newcastle)
Tuesday, 31 October 2017, 1pm to 2pm
Schlich Lecture Theatre, Plant Sciences, S. Parks Road, Oxford OX1 3RB
Hosted by Professor Mark Buckley
Neuronal rhythms are an important aspect of brain function. Increasing evidence suggests a relationship between neuronal oscillations and rhythmic behavioural exploration. In vision this can be observed in theta-rhythmic saccadic exploration of visual scenes. Similar rhythmic sampling phenomena have also been discovered in investigations on covert spatial attention, i.e. in the absence of overt eye movements. Several EEG/MEG studies confirmed that theta-alpha (4-10 Hz) range oscillations measured over visual cortex influence the detectability of target stimuli during covert attention and perceptual illusion paradigms. But the mechanisms contributing to the emergence of oscillations at a neuronal level remain not well understood. Here I will present data from multi-electrode array recordings in primate visual cortex during different perceptual conditions. We initially observed theta rhythmic neuronal spiking during the Kanizsa illusion when the neuron’s receptive field covered the illusion center. More extensive tests revealed that theta spiking emerged from competitive receptive field interactions between neighbouring neuronal populations. Kanizsa-related theta spiking was observed in areas V1 and V4 of visual cortex, but vanished in V4 when V1 was lesioned resulting in Blindsight. Similar theta spiking was also observed when primates engaged in attentional sampling to detect targets occurring with spatio-temporal uncertainty. The phase of the neuronal rhythm was predictive of the primate’s reaction time and the frequency of the rhythm was influenced by the size of the attentional focus. Taken together, our findings confirm the presence of rhythmic sampling strategies during active visual perception and indicate its root in the local network dynamics of neurons in visual cortex.