Dynamic circuit motifs underlying multimodal interactions in primate auditory cortex - ABSTRACT
There is a strong movement within the neuroscience community towards studying the brain under
naturalistic conditions, in rich multisensory paradigms and in the context of behaviors observed in natural
environments, such as free viewing. This requires transforming our traditional data collection and analysis
pipelines, and their underlying theoretical frameworks. Instead of focusing on one specific system supporting a
particular brain function, we must conduct multisite recordings targeting multiple, reciprocally connected
circuits, which is the main motivation for our project. Fortunately, this is now technically feasible in both human
and nonhuman primates.
The overarching goal of our project is to define information transmitting (“driving”) vs. “modulatory”
circuits of the auditory system. The rationale for this goal is that if only driving circuits existed in the brain, we
would not have the ability to focus on behaviorally relevant aspects of our environment. From this perspective,
modulatory circuits play as an important role in brain operations as information transmitting ones.
Specifically, our project will explore the interaction of four domains of brain function and the distinctive,
dynamic circuit motifs (circuits and their spectrotemporal neuronal activity patterns) that underlie them. These
brain functions are auditory perception, multisensory interactions within the auditory system, motor sampling of
the environment (eye movements), and memory recall.
We will utilize electrophysiological recordings during behavioral experiments in non-human and human
primates, with computational modeling to bridge the gap between different recording scales (single unit to
EEG), and species (non-human primate vs. human). Computational models will also be used to suggest
specific target nodes and patterns of the distinct circuits for neuromodulation. Using the spectrotemporal
neuronal activity (a key feature of a dynamic circuit motif) and model prediction based intracranial electrical
brain stimulation, we will verify each identified circuit’s causal role in producing its unique circuit motifs and in
supporting different aspects of behavior.
