UC San Diego

In a complex visual environment—such as a crowed street in Bangkok— driving would be impossible if drivers do not have an intact attentional system. They have to monitor cars and trucks surrounding their vehicles, and at the same time they have to also attend to traffic lights and street signs and watch out for pedestrians and motorbikes that could cross the street unexpectedly at any given time. In this type of scenarios, drivers need to divide their attention into multiple spotlights and flexibly change the size of their attention field (zoom-in and zoom-out) such that relevant information is most efficiently encoded at the expense of irrelevant information. The first two experiments in my dissertation examined neural mechanisms underlying these two natures of our attentonal system, and the last experiment officially evaluated the relative contributions of alternative neural mechanisms that may account for attention-related improvement in perceptual performance. In the first experiment (Chapter 2), we provided neural evidence showing that attention could be divided into multiple spotlights across non-contiguous locations in the visual scene, even when visual objects were in close proximity (i.e., in a single quadrant). Using a stimulus- frequency-tagging technique where we flashed two visual targets and a distractor at the intermediate location at different frequencies, we were able to monitor changes of steady state visually evoked potentials (SSVEPs) that oscillated at the same frequencies as the target and distractor stimuli. We found the significant divergence of the target-related and distractor-related SSVEPs ~150-350ms before human participants correctly discriminated the orientations of the two targets. In the second experiment (Chapter 3), we examined the neural basis underlying changes of the spatial scope of attention and studied how such changes may alter the way sensory information is encoded in the visual cortex. By manipulating the spatial extent of visual target in a stream of flickering non-target stimuli, we observed changes in the spread of cortical activity in the contralateral visual cortex measured using functional magnetic resonance imaging (fMRI). As attention became more distributed due to the uncertainty of target locations, we observed a larger spread of cortical activity compared to when attention was more focused to a single target location. Importantly, we found that this spread of the spatial attention modulated the magnitude of attentional modulations of sensory signals measured via SSVEPs in the way that was consistent with predictions from computational models based on divisive normalization. Lastly, in the third experiment (Chapter 4), we made a further step to formally examine the quantitative relationship between attentional gain modulations of neural signals and attention-related improvement in behavioral performance, and evaluated the relative contributions of attentional gain mechanisms and other alternative mechanisms, including noise reduction and efficient read-out mechanisms. We found that in a relatively simple attention task, attentional gain modulations of early visually evoked responses measured via electroencephalography (EEG) could sufficiently predict attention-related improvement in perceptual performance, without the need to invoke the other alternative mechanisms. Taken together, the results from these three experiments suggest that selective attention enhances sensory information processing via changes in gain modulations of early sensory signals and these attentional gain modulations play a critical role in supporting attention-related improvement in perceptual performance.