Effect of Stimulus Normalization and Visual Attention at multiple scales of Neural Integration
The effect of visual attention on neural signals has been extensively studied using various techniques such as macaque neurophysiology and human electro/magneto encephalogram (EEG/MEG). Depending on the technique, different neural measures are typically used for studying attention. For example, in neurophysiology experiments involving macaques, many studies have focused on the modulation in spiking activity or the change in oscillatory power at different frequency bands such as alpha (8-12 Hz) or gamma (30-80 Hz) with attention, or the change in the relationship of spikes with these oscillations. In contrast, human EEG studies, in addition to studying alpha and gamma modulation, often use flickering stimuli that produce a specific neural response called steady-state visually evoked potential (SSVEP), which is also modulated by attention. However, due to the differences in stimuli and task paradigms in such studies, it is difficult to determine the effectiveness of these various neural measures for capturing attentional modulation. To address this, we designed a task paradigm which included both static and counterphase flickering stimuli to generate all the relevant neural measures (alpha/gamma power as well as SSVEPs) under identical recording conditions, which allowed us to compare their effectiveness in studying attention. Since several reports suggest that attention modulates these neural measures through a canonical neural mechanism called normalization, in the first study of this thesis, we varied the normalization strength parametrically as a proxy for attentional modulation and tested its effect on various neural measures. We manipulated normalization strength by presenting static as well as flickering orthogonal superimposed gratings (plaids) at varying contrasts to two female monkeys while recording multiunit activity (MUA) and LFP from the primary visual cortex (area V1). We quantified the modulation in MUA, gamma (32-80 Hz), high-gamma (104-248 Hz) power, and SSVEP. Even under similar conditions, normalization strength was different for the four measures; and increased as: spikes, high-gamma, SSVEP, and gamma. However, these results could be explained using a normalization model, modified for population responses by varying the tuned normalization parameter and semi-saturation constant. In the second part of the thesis, we tested the predictions of the gamma phase coding hypothesis in the context of stimulus contrast and visual attention. The gamma phase coding hypothesis posits that the intensity of the incoming stimulus is encoded in the position of the spike relative to the gamma rhythm. Using chronically implanted microelectrode arrays in the primary visual cortex of macaques engaged in an attention task while presenting stimuli of varying contrasts, we tested whether the phase of the gamma rhythm relative to spikes varied as a function of stimulus contrast and attentional state. We analyzed spikes and LFP from different electrodes and found a weak but significant effect of attention, but not stimulus contrast, on the gamma phase relative to spikes. Although we found a significant effect of attention, we argue that a small magnitude of phase shift as well as the dependence of phase angles on gamma power and center frequency, limits the potential role of gamma in phase coding in area V1. In the third part of the thesis, we recorded EEG signals from 26 human participants while they were engaged in an attention task and analyzed alpha and gamma band powers for both static and flickering stimuli and SSVEP power for flickering stimuli. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, we found that non-foveal stimuli produced weak gamma despite various stimulus optimizations and therefore showed a negligible effect of attention although the same participants showed robust gamma activity for full-screen gratings. Thus, alpha and SSVEP won over gamma in capturing attentional modulation in human EEG. This result was in contrast to the findings of a comparable study in monkeys, where gamma and alpha won over SSVEPs. This study highlights the effectiveness of various neural measures in studying visual spatial attention and further implicates their usefulness in decoding behavior and attentional state in humans.