<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T19:48:40Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/79187" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/79187</identifier><datestamp>2022-01-13T07:53:56Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Emery N. Brown and Patrick L. Purdon.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Weiner, Veronica Sara</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2013-06-17T19:46:04Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2013-06-17T19:46:04Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2013</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/79187</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">844347952</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2013.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis. Vita.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">General anesthesia is a drug-induced, reversible behavioral state characterized by hypnosis (loss of consciousness), amnesia (loss of memory), analgesia (loss of pain perception), akinesia (loss of movement), and hemodynamic stability (stability and control of the cardiovascular, respiratory, and autonomic nervous systems). Each year, more than 25 million patients receive general anesthesia in the United States. Anesthesia-related morbidity is a significant medical problem, including nausea, vomiting, respiratory distress, post-operative cognitive dysfunction, and post-operative recall. To eliminate anesthesia-related morbidity, the brain systems involved in producing general anesthesia must be identified and characterized, and methods must be devised to monitor those brain systems and guide drug administration. A priority for anesthesia research is to identify the brain networks responsible for the characteristic electroencephalography (EEG) signals of anesthesia in relation to sensory, cognitive, memory, and pain systems. In this thesis, we recorded simultaneous intracranial and surface EEG, and single unit data in patients with intractable epilepsy who had been previously implanted with clinical and/or research electrodes. The aims of this research were to characterize the neural signals of anesthesia in a regionally and temporally precise way that is relevant to clinical anesthesia, and to identify dynamic neuronal networks that underlie these signals. We demonstrated region-specific, frequency-band-specific changes in neural recordings at loss of consciousness. We related these findings to theories of how anesthetic drugs may impart their behavioral effects.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Veronica Sara Weiner.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">94 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by 
copyright. They may be viewed from this source for any purpose, but 
reproduction or distribution in any format is prohibited without written 
permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Brain and Cognitive Sciences.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Intracranial electroencephalography signatures of the induction of general anesthesia with Propofol</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Neural dynamics during induction of general anesthesia with Propofol</dim:field>
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   	&lt;Title>Intracranial electroencephalography signatures of the induction of general anesthesia with Propofol&lt;/Title>
   	&lt;Subtitle>Neural dynamics during induction of general anesthesia with Propofol&lt;/Subtitle>
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   	&lt;PublicationDate>2013&lt;/PublicationDate>
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        	&lt;DisplayName>Weiner, Veronica Sara&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;License>http://dspace.mit.edu/handle/1721.1/7582&lt;/License>
    &lt;Keyword>Brain and Cognitive Sciences.&lt;/Keyword>
   	&lt;Abstract>General anesthesia is a drug-induced, reversible behavioral state characterized by hypnosis (loss of consciousness), amnesia (loss of memory), analgesia (loss of pain perception), akinesia (loss of movement), and hemodynamic stability (stability and control of the cardiovascular, respiratory, and autonomic nervous systems). Each year, more than 25 million patients receive general anesthesia in the United States. Anesthesia-related morbidity is a significant medical problem, including nausea, vomiting, respiratory distress, post-operative cognitive dysfunction, and post-operative recall. To eliminate anesthesia-related morbidity, the brain systems involved in producing general anesthesia must be identified and characterized, and methods must be devised to monitor those brain systems and guide drug administration. A priority for anesthesia research is to identify the brain networks responsible for the characteristic electroencephalography (EEG) signals of anesthesia in relation to sensory, cognitive, memory, and pain systems. In this thesis, we recorded simultaneous intracranial and surface EEG, and single unit data in patients with intractable epilepsy who had been previously implanted with clinical and/or research electrodes. The aims of this research were to characterize the neural signals of anesthesia in a regionally and temporally precise way that is relevant to clinical anesthesia, and to identify dynamic neuronal networks that underlie these signals. We demonstrated region-specific, frequency-band-specific changes in neural recordings at loss of consciousness. We related these findings to theories of how anesthetic drugs may impart their behavioral effects.&lt;/Abstract>
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