<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; color: rgb(0, 0, 0); font-size: 14px; font-family: Calibri, sans-serif; "><div><br></div><span id="OLK_SRC_BODY_SECTION"><div xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><div lang="EN-US" link="blue" vlink="purple"><div class="WordSection1"><p class="MsoNormal"><o:p> </o:p></p><p class="MsoNormal"><o:p> </o:p></p><p class="MsoNormal" align="center" style="text-align:center"><span style="color:#1F497D"><o:p> </o:p></span></p><p class="MsoNormal" align="center" style="text-align:center"><span style="font-size:10.5pt;color:black"><img width="497" height="62" id="Picture_x0020_2" src="cid:image001.jpg@01D209EC.0DCC2460" alt="cid:image001.jpg@01D209E8.CE3A36F0"></span><span style="font-size:10.5pt;color:black"><o:p></o:p></span></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size: 11.5pt; font-family: Times, serif; color: black; "> </span></b><span style="font-size:10.5pt;color:black"><o:p></o:p></span></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:12.0pt;color:black">Seminar<br></span></b><b><span style="font-size:14.0pt">NON-INVASIVE EEG+FNIRS AS A PORTABLE IMAGING PLATFORM<o:p></o:p></span></b></p><p class="MsoNormal" align="center" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;text-align:center"><b><span style="font-size:11.5pt;color:red">Friday, September 9, 2016<br>
SEC 204: 12-1PM<o:p></o:p></span></b></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:11.5pt">Speaker: Dr. Ahmet Omurtag<o:p></o:p></span></b></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:12.0pt"><o:p> </o:p></span></b></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:12.0pt"><img width="223" height="278" id="Picture_x0020_1" src="cid:image002.png@01D209EC.0DCC2460" alt="cid:image004.png@01D209EB.9C162FF0"></span></b><b><span style="font-size:12.0pt"><o:p></o:p></span></b></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:12.0pt"><o:p> </o:p></span></b></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:11.5pt">Ahmet Omurtag, PhD<br>
Associate Professor<br>
Department of Biomedical Engineering<o:p></o:p></span></b></p><p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:11.5pt">University of Houston<o:p></o:p></span></b></p><p class="MsoNormal"><b><span style="font-size:11.5pt"><o:p> </o:p></span></b></p><p class="MsoNormal"><b><span style="font-size:11.5pt">Abstract:</span></b><span style="font-size:11.5pt"> Functional near-infrared spectroscopy (fNIRS) is similar to EEG in cost and portability, and provides a complementary set of information about the functional
status of the brain. We will describe the concurrent use of these modalities, EEG+fNIRS, in healthy adult volunteers and its potential applications in disease monitoring. First the development of the FDA approved medical device microEEG and its testing in
emergency departments will be described. Then the recent results from Dr. Omurtag's team will be shown about the detection of neural activity driven hemodynamics using EEG+fNIRS. Machine learning techniques show that hybrid functional neuroimaging data during
task performance is more accurate than from individual modalities alone.<o:p></o:p></span></p><p class="MsoNormal"><span style="font-size:11.5pt"><o:p> </o:p></span></p><p class="MsoNormal"><b><span style="font-size:11.5pt;color:black">Bio: </span></b><span style="font-size:10.5pt;color:black"></span><b><span style="font-size:11.5pt;color:black">Dr. Omurtag </span></b><span style="font-size:11.5pt;color:black">is an Associate Professor in Biomedical Engineering at the University of Houston. He holds a Ph.D. in Mechanical Engineering from Columbia
University. His post-doctoral training was at the Mount Sinai School of Medicine in computational neuroscience. His research focus is on the diagnostic utility of portable functional neuroimaging devices. He works on applications of simultaneous EEG and functional
near-infrared spectroscopy (fNIRS).<o:p></o:p></span></p></div></div></div></span><style><!--
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