<div dir="ltr">FYI<br><div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <b class="gmail_sendername" dir="auto">QLS Coordinator</b> <span dir="auto"><<a href="mailto:coordinator.qls@mcgill.ca">coordinator.qls@mcgill.ca</a>></span><br>Date: Mon, Jan 20, 2020 at 9:55 AM<br>Subject: Brownbag which might interest QLS members<br>To: <br></div><br><br>




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<b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">McGill Quantitative Psychology Brownbag Series</span></b></div>
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<b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Title: Task-state functional brain networks detectable by fMRI using constrained principal component analysis: More than just a pretty picture</span></b></p>
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<b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Speaker</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">: Dr. Todd Woodward (Psychiatry, University of British Columbia)</span></p>
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<b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Time</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">: 10:00 – 11:00 am, Thursday January 23
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<b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Place</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">: 2001 McGill College, Room 464</span></p>
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<b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif">Abstract:</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif"> Characterization of brain networks using functional magnetic resonance imaging (fMRI) has primarily been
 advanced by resting-state research; however, using task-based research, functional characterizations can be more robustly determined by observing how the timing of network-level evoked hemodynamic responses (HDRs) differ between task conditions. To this end,
 our laboratory has developed a novel approach which integrates the following principles: (1) as opposed to voxel-by-voxel univariate analyses, use multivariate/multidimensional analysis methods computing networks based on the dominant pattern of intercorrelations
 between voxels; (2) as opposed to mixing task-related and task-unrelated variance in brain activity, extract the task-related variance prior to network extraction; (3) as opposed to selecting brain regions of interest (ROIs), compute networks that allow every
 voxel to participate in every brain network; (4) as opposed to assuming HDR shapes, use data-driven explorations of HDR shapes, allowing separate HDR shapes for every subject, network and task condition separately (Finite Impulse Response [FIR] model). Principles
 (1) and (2) can be achieved by applying constrained principal component analysis (CPCA) to fMRI data (fMRI-CPCA). Principles (3) and (4) are achieved by decisions about the content of the matrices submitted to fMRI-CPCA. This line of research has led to the
 identification of a set of 10 core task-based fMRI networks, a subset of which are retrieved from all task-based fMRI data, regardless of the specific task. Based on the experimental conditions to which they respond, we have assigned a preliminary cognitive
 function to each of these interacting networks. Some of them are already familiar to the field from resting state studies (e.g., default mode network, response network), but others are novel and specific to the task state (e.g., cognitive evaluation, volitional
 attention to internal representations). Extended applications of CPCA models to fMRI, MEG, and EEG data are also discussed.</span></p>
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif">McGill Quant Psych Brownbag: <a href="https://sites.google.com/view/hwanglab/quant-psych-seminar" target="_blank">https://sites.google.com/view/hwanglab/quant-psych-seminar</a></span></p>
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:black">==================================================<br>
Heungsun Hwang, Ph.D.</span></p>
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:black">Professor, Department of Psychology, McGill University</span></p>
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:black">2001 McGill College Avenue, Room 710
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<span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:black">Montreal, QC H3A 1G1, Canada<br>
Tel: 514-398-8021       Fax: 514-398-4896<br>
Lab: </span><a href="https://sites.google.com/view/hwanglab" target="_blank"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:#0563c1">sites.google.com/view/hwanglab</span></a><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:black"><br>
==================================================</span></p>
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