Large-scale spatiotemporal cortical dynamics in visual short-term memory: from spiking activity to oscillations

Abstract

Cognitive processes occur through coordinated activity via disparate cortical and subcortical brain structures. Although these structures may be widely separated, evolutionary pressures dictate that cognition must occur rapidly and efficiently. In order to capture these brain-wide activity patterns the tools for measuring them need to be similarly capable of measurements of both high spatial coverage, and high temporal resolution. Additionally, the measurements would ideally be of the activity of the fundamental units involved in cognition, that is the neurons, rather than an extrapolation of their activity via a different signal source. However, outside of the work presented here, current technologies are rare that allow both the requisite coverage and spatiotemporal resolution to achieve these measurements. The results of the studies presented in Chapters 2-4 provide both the tools for making such measurements, and the initial analyses of the neuronal dynamics during short-term memory. In Chapter 2 we present the technological and methodological process for recording neural activity (both action potentials and local field potentials) from across roughly a hemisphere of cortex in the macaque monkey performing a visual short-term memory task. In visual short-term memory a visual percept must be maintained then recalled when it is no longer present. This cognitive process is one we use nearly incessantly in every-day life. In Chapter 3 we found task dependent spiking activity during short-term memory is wide-spread, and that most areas display a balanced state of both increases and decreases in firing rate. Within these areas we found a hierarchically organized subset of cortical areas that also showed stimulus specific activity during the memory period of the task. In Chapter 4 we used spectral analysis to investigate the oscillatory make-up of neural activity across the recorded areas. We found within specific frequency bands there are different gradients of amplitude of spectral power across cortex. Additionally, we found that we could use a small number of spectrally derived variables in order to decode the brain area origin of the signal. This shows that areas have a characteristic spectral composition, that varies systematically across the cortical mantle.