Audition, Memory, and Consciousness

Audition, Memory, and Consciousness

Andrew Francl and Josh McDermott train a deep neural network enhanced with human ears, to understand how sounds are localized in a complex acoustic environment.

Overview

This unit explores models of the neural mechanisms underlying three kinds of intelligent processes: (1) auditory processing, including the spatial localization of sounds and recognition of speech and music; (2) the representation of episodic and spatial memory in the hippocampus; and (3) conscious experience of objects and events in the world.

Videos

Josh McDermott first introduces the main components of the auditory system and early models of auditory processing in the brain. He then asks three fundamental questions: can we build better models of auditory perception and its underlying neural mechanisms, what can we learn from new models about auditory behavior and human auditory cortex, and can new models be exploited to help people hear better?
The hippocampus is involved in episodic memory, which is the linkage of events, as well as the spatial memory used in navigation, which is the linkage of spatial locations. Both may depend critically on temporal sequence encoding. Matthew Wilson describes key research on the role of the hippocampus in these two kinds of memory, and the neural mechanisms of sequence encoding.
Christof Koch reflects on the history of research on what is consciousness, what is currently known about the nature of conscious experience, and what are possible neural correlates of consciousness. He then introduces the Integrated Information Theory of Consciousness that can explain a range of clinical and laboratory findings, and makes key predictions for future research on consciousness.

Further Study

Online Resources

Additional information about the speakers’ research and publications can be found at these websites:

Readings

Francl, A., McDermott, J. H. (2020) Deep neural network models of sound localization reveal how perception is adapted to real-world environments, bioRxiv, pp. 2020.07.21.214486

Jones M. W., Wilson, M. A. (2005) Theta rhythms coordinate hippocampal-prefrontal interactions in a spatial memory task, PLoS Biology, 3, 2187-2199

Kell, A., Yamins, D., Shook, E., Norman-Haignere, S., McDermott, J. (2018)  A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy, Neuron, 98, 630-644

Koch, C. (2019) The feeling of life itself: Why consciousness is widespread but can’t be computed, The MIT Press, Cambridge

Koch, C. (2004) The quest for consciousness: A neurobiological approach, Roberts and Company Publishers, Englewood, CO

Penagos, H., Varela, C., Wilson, M. A. (2017) Oscillations, neural computations and learning during wake and sleep, Current Opinion in Neurobiology, 44, 193-201

Saddler, M. R., Gonzalez, R., McDermott, J. H. (2020) Deep neural network models reveal interplay of peripheral coding and stimulus statistics in pitch perception, bioRxiv, pp. 2020.11.19.389999

Sanders, H., Ji, D., Sasaki, T., Leutgeb, J. K., Wilson, M. A., Lisman, J. E. (2019) Temporal coding and rate remapping: Representation of nonspatial information in the hippocampus Hippocampus, 29, 111-127

Tononi, G., Koch, C. (2015) Consciousness: Here, there and everywhere, Philosophical Transactions of the Royal Society B, 370: 20140167