Neural Circuits and Computations for Attentional Selection
Assistant Professor,Psychological & Brain Sciences, and Neuroscience, Johns Hopkins University
Time: March 18, 2019 @ 11:15 AM to 12:05 PM
Location: 204 Evans Hall
Attention, the ability to selectively process the most important subset of information in the environment (at the expense of all others) is a fundamental component of adaptive behavior. Much is known about the consequences of attention to behavior and neural representations, about the shaping of attention by neuromodulators, and about genetic factors associated with attentional dysfunction. However, the neural basis of the control of attention has remained largely elusive. Specifically, how do neural circuits select the next target of (spatial) attention, and what canonical neural computations underlie this function? I will share recent findings from our work in barn owls that addresses one such computation underlying stimulus selection for spatial attention, namely, location-invariance. We discovered that specialized inhibitory neurons in the barn owl midbrain, which are conserved across all vertebrates, employ a novel form of population coding, namely, combinatorially-optimized coding, through the use of unusual representations of space. We showed that this results in a combinatorial strategy for solving selection at all possible pairs of stimulus locations, a strategy that also minimizes the net costs of building and operating the neural circuitry. I will then switch gears and share briefly our recent work in developing primate-like behavioral paradigms for visuospatial attention in freely behaving mice. These paradigms are designed to allow the (ongoing) dissection of mammalian neural circuitry underlying spatial attention control. We anticipate that such efforts will help not only to advance our understanding of attention control at a circuit-level, but also to lay a foundation for the ‘neurotype’ of attentional impairments.