Near-real-time feature-selective modulations in human cortex

For neural activity to be linked with cognitive function, information is needed about both the temporal dynamics and the content of neural codes. Traditionally, recording of single neurons in animals has been the primary means of obtaining high temporal resolution and precise information about neural tuning properties such as selectivity for different sensory features. Recent functional magnetic resonance imaging (fMRI) studies in humans have been able to measure feature selectivity within specific subregions of sensory cortex (e.g., orientation selectivity in primary visual cortex, or V1) [1, 2]. However, investigating the neural mechanisms that support cognitive processing-which often occurs rapidly on a subsecond scale-with a temporally insensitive method such as fMRI severely limits the types of inferences that can be drawn. Here, we describe a new method for tracking the rapid temporal evolution of feature-selective information processing with scalp recordings of electroencephalography (EEG). We generate orientation-selective response profiles based on the spatially distributed pattern of steady-state visual evoked potential (SSVEP) responses to flickering visual stimuli. Using this approach, we report a multiplicative attentional modulation of these feature-selective response profiles with a temporal resolution of 24-120 ms, which is far faster than that achieved with fMRI. Finally, we show that behavioral performance on a discrimination task can be predicted based on the amplitude of these temporally precise feature-selective response profiles. This method thus provides a high-temporal-resolution metric that can be used to track the influence of cognitive manipulations on feature-selective information processing in human cortex.