Advent of general anesthetics over a century ago revolutionized the practice of medicine by allowing humane care for surgical patients. Yet despite routine clinical use, there is no detailed understanding of the neurophysiological basis of action of anesthetics. Anesthetics act on a variety of molecular targets distributed among many brain regions. Understanding how these molecular-level actions lead to reversible loss of consciousness requires a systems neuroscience analysis - defining the actions of anesthetics within the context of highly interconnected brain circuits. I analyzed electrocorticography recordings from human subjects and non-human primates during induction of general anesthesia. Stability analysis of these dynamics revealed that in the awake brain, cortical activity is tuned precisely to the critical regime between damping and growing oscillations. Dynamical criticality renders the brain responsive to external stimuli. I show that dynamical criticality is lost during induction of anesthesia with mechanistically distinct anesthetic agents. Thus, dynamical criticality is a novel systems-level property of cortical activity disrupted by general anesthetics. I propose to investigate how circuit level dynamical criticality arises out of plasticity of the interactions among different cortical areas and how it is disrupted during natura sleep and general anesthesia. Cortical recordings do not address the contribution of deeper brain structures such as thalamus and the reticular activating system. Thus, I developed an animal preparation for simultaneous multi-site recordings from the cortex, thalamus, and brain stem during emergence from anesthesia. Using this technique, I demonstrate that under steady state anesthetic concentration the brain exhibits fluctuations among several distinct activity states and that the dynamics of these fluctuations change depending on the concentration of anesthetic. I hypothesize that the dynamics of these fluctuations mediate the processes through which the brain recovers the complexity of function required for emergence of consciousness and propose to investigate the neurophysiological basis of these fluctuations by recording and manipulating activity of specific neuronal populations within the brain arousal circuitry during emergence from anesthesia.
The specific Aims are:
Specific Aim 1 : Characterization of dynamical criticality of neuronal activity in human subjects during natural sleep and general anesthesia (years 1-5).
Specific Aim 2 : Characterization of neuronal mechanisms that lead to the emergence of consciousness after anesthesia (years 1-5). The applicant, Dr. Alexander Proekt, is an anesthesiologist specializing in caring for patients undergoing neurosurgical procedures. He has outlined a 5 year research plan that builds upon his background in neurophysiology and biophysics. Under the leadership of Dr. Donald Pfaff, an internationally renowned neuroscientist, he seeks to utilize a combination of cutting edge experimental techniques and novel theoretical approaches to study the neurophysiological basis of general anesthesia. Dr. Proekt will be mentored by an Advisory Committee comprised of internationally recognized experts with diverse and complementary areas of expertise. The research will be conducted in an academically rich collaborative environment of Tri-Institutional conglomerate that includes the Rockefeller University, Weill Cornell Medical College, and Memorial Sloan Kettering. This is an ideal environment for the applicant's carrier development. With support provided by K08, the proposed research plan will likely lead to transformative insights into the neurophysiological basis of action of anesthetics and will help establish the applicant as an independently funded investigator and clinician- scientist.
Despite significant breakthroughs in the understanding of molecular mechanisms of action of anesthetic agents there is no detailed understanding of how these molecular-level effects lead to changes in activity of highly interconnected neuronal circuits that result in the reversible loss of consciousness. This lack of understanding leads to high prevalence of anesthesia-related complications such as intraoperative awareness and post-operative cognitive dysfunction and delirium. To get at the systems-level mechanisms of anesthetic action we will characterize stability of cortical dynamics during natural sleep and anesthesia in human subjects and investigate how changes in the pattern of interactions among different cortical regions lead to changes in neuronal dynamics. To address the role of subcortical networks mediating brain arousal, we will perform simultaneous multisite recordings from the cortex, thalamus and brain stem in animal models during emergence from anesthesia using mechanistically distinct anesthetic agents to define the mechanisms which allow the brain to recover complexity of function essential for consciousness. The information gained from these studies will deepen our understanding of systems level properties essential for loss and recovery of consciousness and may guide improvements in administering anesthesia.
|Proekt, A; Hudson, A E (2018) A stochastic basis for neural inertia in emergence from general anaesthesia. Br J Anaesth 121:86-94|
|Solovey, Guillermo; Alonso, Leandro M; Yanagawa, Toru et al. (2015) Loss of Consciousness Is Associated with Stabilization of Cortical Activity. J Neurosci 35:10866-77|
|Hudson, A E; Proekt, A (2015) Some heightened sensitivity. Br J Anaesth 115 Suppl 1:i5-i8|
|Svensson, Erik; Proekt, Alex; Jing, Jian et al. (2014) PKC-mediated GABAergic enhancement of dopaminergic responses: implication for short-term potentiation at a dual-transmitter synapse. J Neurophysiol 112:22-9|
|Hudson, Andrew E; Calderon, Diany Paola; Pfaff, Donald W et al. (2014) Recovery of consciousness is mediated by a network of discrete metastable activity states. Proc Natl Acad Sci U S A 111:9283-8|
|Alonso, Leandro M; Proekt, Alex; Schwartz, Theodore H et al. (2014) Dynamical criticality during induction of anesthesia in human ECoG recordings. Front Neural Circuits 8:20|