There is more visual information in the environment than we can process at one time, and selective attention abilities allow us to select only the information that is relevant to our current goals. Theories of visual attention typically propose that this goal-directed selection relies on the maintenance of immediate task priorities in working memory, with the attention system using this information to determine what information is attended or ignored in a given situation. As a result, studies examining the cognitive and neural mechanisms of goal-directed attentional control have focused almost exclusively on the role of working memory systems in this process. At the same time, given the limited capacity of working memory and the complexity of most tasks (and associated goals) it is unlikely that the active maintenance of information in working memory is solely responsible for goal-directed attention. Instead, experience with regularities in a given environmental context can lead to the formation of long-term memory representations that can automatically drive the allocation of attention upon future encounters with that context. In this way, learning-induced plasticity within the attentional system can increase the efficiency of goal-directed attention while simultaneously decreasing demands on limited-capacity working memory processes. A better understanding of how long-term contextual information changes neural processing within the attentional system is not only important from a basic science standpoint, but can also be used to inform behavioral and pharmacological interventions designed to improve selective attention abilities in both the normal and disordered brain. However, it is currently unknown precisely how contextual learning influences selective attention at the neural level. To this end, the primary research goal of this training proposal is to understand how contextual learning influences attention at both the neuronal and systems level, by employing a comparative electrophysiological approach in humans and non-human primates. Specifically, the aims are to 1) elucidate electrophysiological markers of context-dependent attentional learning in humans and non-human primates using scalp-recorded EEG, and 2) use single-unit neurophysiological techniques to determine how these changes are instantiated at the level of individual neurons. Through this work, my goal is to develop expertise in both, human and non- human primate electrophysiology, complementing my expertise in behavioral and neuropsychological approaches to the study of memory and attention function. This will provide me the ability to directly bridge human and animal models of cognition, as well as allowing more direct and rapid translation of my basic research to clinically relevant applications.
The broad research goal of the current proposal is to better understand how learning-induced plasticity in attentional networks influences the ability to selectively attend goal-relevant information in the environment. The hope is to inform research into both behavioral and pharmacological interventions that have the ability to remediate attentional impairments due to aging, brain injury, or neuropathological conditions. The training goal of the current proposal is to gain proficiency in neurophysiological recording techniques across species, complementing my existing behavioral and clinical expertise and expediting the speed with which I can translate my basic research findings to clinically relevant programs of research.
|Cosman, Joshua D; Arita, Jason T; Ianni, Julianna D et al. (2016) Electrophysiological measurement of information flow during visual search. Psychophysiology 53:535-43|
|Hecht, Lauren N; Cosman, Joshua D; Vecera, Shaun P (2016) Enhanced spatial resolution on figures versus grounds. Atten Percept Psychophys 78:1444-52|
|Cosman, Joshua D; Atreya, Priyanka V; Woodman, Geoffrey F (2015) Transient reduction of visual distraction following electrical stimulation of the prefrontal cortex. Cognition 145:73-6|
|Cosman, Joshua D; Vecera, Shaun P (2014) Establishment of an attentional set via statistical learning. J Exp Psychol Hum Percept Perform 40:1-6|