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<div id="breadcrumb" class="row-full-width"><div class="inside"><h2 class="element-invisible">You are here</h2><div class="breadcrumb"><a href="/">Home</a> > <span class="breadcrumb-page-title">Research</span></div></div></div> <h1 class="title" id="page-title">Research</h1> <div class="content-top"> <div class="region region-content-top"> <div id="block-fieldblock-node-page-default-field-paragraph-sliders" class="block block-fieldblock"> <div class="content"> <div class="paragraphs-items paragraphs-items-field-paragraph-sliders paragraphs-items-field-paragraph-sliders-full paragraphs-items-full"> <div class="field field-name-field-paragraph-sliders field-type-paragraphs field-label-hidden"><div class="field-items"><div class="field-item even"><div class="entity entity-paragraphs-item paragraphs-item-slider"> <div class="content"> <div class="field field-name-field-pg-slider-image field-type-image field-label-hidden"><div class="field-items"><div class="field-item even"><div class="bg-slider-image" style="background-image:url('https://alab.ucsf.edu/sites/g/files/tkssra6046/f/styles/slider_secondary/public/EEG_MRI_arrest_smallv2.png?itok=UghM7VTk')"></div></div></div></div><div class="group-slider-content field-group-div"><div class="group-slider-inside field-group-div"><div class="field field-name-field-pg-slider-title field-type-text field-label-hidden"><div class="field-items"><div class="field-item even">New Methods and Insights About Neurological Emergencies</div></div></div><div class="field field-name-field-pg-slider-body field-type-text-long field-label-hidden"><div class="field-items"><div class="field-item even">We are uncovering actionable insights for some of the most severe types of acute brain injury by integrating physiology, neuroimaging, and electronic health records data streams.</div></div></div><div class="field field-name-field-pg-slider-link field-type-link-field field-label-hidden"><div class="field-items"><div class="field-item even"><a href="https://alab.ucsf.edu/publications">PUBLICATIONS</a></div></div></div></div></div> </div> </div> </div></div></div></div> </div> </div> </div> </div> <div id="main-wrapper"> <div id="main" class="clearfix"> <div id="content" class="column"> <div class="inside"> <a id="main-content"></a> <div class="tabs"></div> <div class="region region-content"> <div id="block-system-main" class="block block-system"> <div class="content"> <div id="node-6" class="node node-page slider-secondary clearfix" about="/research" typeof="sioc:Item foaf:Document"> <span property="dc:title" content="Research" class="rdf-meta element-hidden"></span><span property="sioc:num_replies" content="0" datatype="xsd:integer" class="rdf-meta element-hidden"></span> <div class="content"> <div class="field field-name-field-body field-type-text-long field-label-hidden"><div class="field-items"><div class="field-item even"><p>聽</p> <div class="collapse-item"> <div aria-expanded="true" class="header-text" role="button" tabindex="0"> <h2>Machine Learning Applied to Coma Neuroscience聽</h2> </div> <div aria-hidden="false" class="content-text" role="region" tabindex="-1"> <p>We use state-of-the-art machine learning methods leveraging multimodal healthcare data with the goal to improve prediction,聽diagnosis, and prognostication in acute neurological emergencies. We are developing聽methods that can integrate time-series data (EEG, EKG, blood pressure, intracranial physiology) with electronic health record data and neuroimaging studies to uncover new insights about the mechanisms of neurological recovery after acute brain injury that can聽support clinical聽decision-making.</p> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="347" src="/sites/g/files/tkssra6046/f/wysiwyg/LSTM_EEG.png" width="600" /> <figcaption>Convolutional neural networks can help decode which features from individual EEG snapshots are most relevant for predictions. We string together the CNN data using long short-term neural networks to capture the longitudinal evolution of EEG data during consciousness recovery from coma after acute brain injury with the goal of providing real-time brain injury severity predictions (MRI: purple indicates more severe injury).</figcaption> </figure> </div> <p>聽</p> </div> </div> <div class="collapse-item"> <div aria-expanded="true" class="header-text" role="button" tabindex="0"> <h2>Quantitative Brain Imaging Models</h2> </div> <div aria-hidden="false" class="content-text" role="region" tabindex="-1"> <p>We utilize quantitative structural brain MR imaging techniques to identify patients more likely to recover consciousness from traumatic or non-traumatic coma as well as聽post-traumatic epilepsy.聽We collaborate very closely with UCSF radiology, neurology, and neurosurgery teams at ZSFG and UCSF Medical Center in聽developing protocols and performing quantitative analysis of high-resolution data.聽</p> <div class="responsive-video align--center size--half"><iframe data-align="center" data-original-input="https://www.youtube.com/watch?v=BncpDu5wI8g&ab_channel=AmorimLab" data-size="half" data-video-image="http://img.youtube.com/vi/BncpDu5wI8g/0.jpg" src="https://www.youtube.com/embed/BncpDu5wI8g?autohide=1&controls=1&showinfo=0" style="position: absolute; top: 0px; left: 0px; width: 100%; height: 100%;"></iframe></div> <p>MRI representing聽the brain regions most commonly injured after cardiac arrest. Areas colored in yellow indicate more severely injured areas聽(data from 50 patients undergoing MRI - diffusion-weighted imaging). Collaboration with J. Talbott, MD, Ph.D., Shital Gandhi, MD, and Evan Calabrese, MD, Ph.D. (UCSF Radiology).</p> <div class="wysiwyg_twocols layout--50-50"> <div class="wysiwyg_twocols--first bg--transparent"> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="231" src="/sites/g/files/tkssra6046/f/wysiwyg/Screen%20Shot%202020-08-12%20at%206.23.38%20PM.png" width="400" /> <figcaption>Automated parcellation of brain structures allows for rapid and unbiased quantification of brain injury.</figcaption> </figure> </div> <p>聽</p> </div> <div class="wysiwyg_twocols--second bg--transparent"> <figure class="image" style="float:right"><img alt="" height="229" src="/sites/g/files/tkssra6046/f/wysiwyg/calabrese_brain_23.png" width="360" /> <figcaption>Brain Injury pattern after cardiac arrest for patients with poor (A) and good (B) outcome聽</figcaption> </figure> </div> </div> </div> </div> <div class="collapse-item"> <div aria-expanded="true" class="header-text" role="button" tabindex="0"> <h2>Coma & Critical Care Neurophysiology (Arrest, TBI, and Stroke)</h2> </div> <div aria-hidden="false" class="content-text" role="region" tabindex="-1"> <p>We employ invasive and non-invasive brain monitoring for critically ill patients with聽coma, cardiac arrest, traumatic brain injury, stroke,聽epilepsy, or those at risk for neurological deterioration. We聽focus on continuous EEG monitoring modeling as well as combining聽scalp EEG data analysis with intracranial EEG (ECoG), cerebral blood flow, brain oxygenation, and intracranial pressure trends. Our group also has聽experience delivering聽auditory task聽experiments in comatose subjects in the critical care environment to identify if neural responses to these tasks predict the likelihood of聽consciousness recovery.</p> <h5 style="text-align: center;"><strong>Neural State Dynamics Predict Acute Coma Recovery</strong></h5> <p>聽</p> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="314" src="/sites/g/files/tkssra6046/f/wysiwyg/tsne_MRI_EEG_1.png" width="600" /> <figcaption>t-SNE map of more than 50,000 hours of EEG data for 1,038 comatose cardiac arrest patients: different EEG signatures are associated with various degrees of brain edema severity on MRI. Each dot represents 6h of EEG data and the distance between dots indicates how different the EEG data within every 6 hours are from each other. The limited overlap between clusters indicates that there are well-defined EEG phenotypes (each color represents an EEG phenotype). Coma recovery likelihood varies across phenotypes and patient transitions between phenotypes are predictive of coma recovery.</figcaption> </figure> </div> <p>聽</p> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="319" src="/sites/g/files/tkssra6046/f/wysiwyg/chord_diagram_coma_spectrogram_notitle.png" width="400" /> <figcaption>Chord diagrams demonstrating longitudinal neural state transitions for 1,038 acutely comatose cardiac arrest patients (EEG based). Transition dynamics in the first 84h after cardiac arrest varies between patients recovering from a coma (left) and those with poor neurological outcomes (right). Patients who recover from coma are primarily stationary on higher entropy states, but the transition to and from seizure (green and orange) and burst suppression (blue) states can be observed in specific time windows. The raw EEG and spectrogram shown are representative of a high entropy state (left) and burst suppression and seizure state (right).</figcaption> </figure> </div> <p style="text-align: center;">聽</p> <p style="text-align: center;"><strong>Spreading Depolarizations in Traumatic Brain Injury</strong></p> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="208" src="/sites/g/files/tkssra6046/f/wysiwyg/CSD_rainbow.png" width="600" /> <figcaption>Traumatic brain injury can trigger spreading depolarizations (three spreading depression events are shown above traveling across five intracranial electrodes). This is a massive neurophysiology phenomenon with ultra-slow brain waves that are associated with worse outcomes and are likely a source of secondary injury to the brain. These waveforms can only be recorded with invasive brain monitors and special amplifiers.</figcaption> </figure> </div> <p>聽</p> <p style="text-align: center;"><strong>Detecting Responses to Sound and Music聽In Comatose聽Patients</strong></p> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="240" src="/sites/g/files/tkssra6046/f/wysiwyg/auditory_evoked_ecog.png" width="600" /> <figcaption><strong>Neural processing of auditory responses to novel stimuli </strong>(red) versus deviant (blue) and standard (gray) sounds in an epilepsy patient with multiple intracranial depth electrodes placed. The data shown represent electrodes targeting the left superior temporal gyrus (LAT). The brain tends to have a more pronounced response, i.e. higher amplitude, to salient complex sounds (e.g. telephone ringing) than low complexity tones (e.g. white noise). These higher-order neural responses can also be identified in non-invasive surface EEG for patients in a coma who recover consciousness.</figcaption> </figure> </div> <p>聽</p> </div> </div> <div class="collapse-item"> <div aria-expanded="false" class="header-text" role="button" tabindex="0"> <h2>Tackling Disparities in Neurological Care</h2> </div> <div aria-hidden="true" class="content-text" role="region" tabindex="-1"> <p>Severe acute brain injury often affects the most vulnerable populations in our society. We strive to design and implement equity-relevant and inclusive research that will聽advance the care of all patients we serve. We are specifically evaluating the effects of cardiac arrest related to substance use related overdose聽with the goal of identifying best practices for accelerating neurological recovery after cardiac arrest.</p> </div> </div> <div style="text-align:center"> <figure class="image" style="display:inline-block"><img alt="" height="275" src="/sites/g/files/tkssra6046/f/wysiwyg/calabrese_substance_use_MRI_formatted.png" width="700" /> <figcaption>The opioid crisis and fentanyl use have caused an increase in deaths and cardiac arrests associated with overdose. We have shown that cardiac arrest in the setting of opioid and fentanyl use is associated with more severe brain injury and that this injury might affect different brain regions compared to cardiac arrests not associated with substance use.</figcaption> </figure> </div> <p style="text-align: center;">聽</p> <p style="text-align:center"><a href="https://alab.ucsf.edu/publications"><img alt="" height="113" src="/sites/g/files/tkssra6046/f/wysiwyg/amorim_rubik_neuro_logo_short_no_ucsf_logo.png" width="100" /></a></p> <p style="text-align: center;"><a class="btn--large btn--more--reverse" href="https://alab.ucsf.edu/publications">OUR PUBLICATIONS</a></p> </div></div></div> </div> </div> </div> </div> </div> </div> </div> <div id="sidebar" class="column"> </div> </div></div> <div id="footer"> <div class="section"> <div class="footer-bottom"> <nav aria-label="Footer Navigation" class="footer--navigation"> <ul> <li><a href="/cdn-cgi/l/email-protection#8eefe3e1fce7e3cefbedfde8a0ebeafb">Contact Us</a></li> <li><a href="https://www.ucsf.edu/accessibility-resources">Accessibility</a></li> <li><a href="https://www.ucsf.edu/website-privacy-policy">Privacy Policy</a></li> <li><a href="https://websites.ucsf.edu/website-terms-use">Terms of Use </a></li> <li><a href="https://websites.ucsf.edu/azlist">A-Z Website List</a></li> </ul> </nav> <div class="footer--copyright"> <p>© 2024 The Regents of the University of California</p> </div> </div> </div> </div> </div> </div> <script data-cfasync="false" src="/cdn-cgi/scripts/5c5dd728/cloudflare-static/email-decode.min.js"></script><script type="text/javascript"> /*<![CDATA[*/ (function() { var sz = document.createElement('script'); sz.type = 'text/javascript'; sz.async = true; sz.src = '//siteimproveanalytics.com/js/siteanalyze_8343.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(sz, s); })(); /*]]>*/ </script> </body> </html>