Neural dynamics of the anesthetized brain and the control of conscious states

General anesthesia (GA) reversibly induces unconsciousness. It is arguably the most powerful brain state manipulation that clinicians and researchers can reliably perform. However, the mechanisms underlying GA at the neural systems level are underexplored and largely not understood. To link neural dynamics to the loss of consciousness, we measured spiking activity and local field potentials (LFPs) from multiple cortical and thalamic regions while monkeys were pharmacologically rendered unconscious. In Chapter 2, we examine effects of the GABAergic anesthetic propofol across prefrontal cortices (PFC), parietal cortex, temporal cortex, and the mediodorsal and intralaminar thalamic nuclei. Propofol decreased brain-wide spiking and high-frequency LFPs (e.g. gamma, 30- 80Hz) while producing prominent slow cortical oscillations (0-4 Hz). These slow rhythms were incoherent across PFC yet synchronized in frontoparietal networks. Electrical stimulation of the central thalamus immediately and continuously reversed the neurophysiological effects of propofol and awakened the anesthetized monkeys. Thus, we interpret GABAergic anesthetics to produce unconsciousness via fragmented network dynamics facilitated by subcortical arousal pathway inhibition. In Chapter 3, we explore an alternative unconscious state mediated by the anti-glutamatergic anesthetic ketamine. Ketamine substantially increased spiking and gamma rhythms while eliminating beta (13- 25 Hz) power and coherence across the cortical areas studied in Chapter 2. In anesthesia, slow waves interrupted high-frequency activity globally and PFC uniquely entrained central thalamic LFPs. Seemingly, ketamine harnesses an excitatory mechanism to disrupt conscious processing, overwhelming cortex with disordered spiking activity and binding thalamo-prefrontal flexibility. In Chapter 4, we describe our model for closed-loop control of GA in monkeys. We established and implemented a pharmacokinetic-pharmacodynamic paradigm within an optimal control framework that automatically titrated propofol using an LFP-derived GA biomarker. Together, this collection of work demonstrates the distinct network mechanisms that can drive GA and the systems-level approach to enhanced control of conscious states.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Donoghue, Jacob A. (Jacob Alexander)

Advisor dc:contributor.advisor

• Earl K. Miller.

• Brain and Cognitive Sciences.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/132745

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/132745