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Hi everyone, </div>
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Please join us a week from today (Tuesday Dec 6 at 2:30) <span style="background-color:rgb(255, 255, 255);display:inline !important" class="ContentPasted3">
for the final CTN seminar of the term</span>. Professor Leyla Isik will join us remotely from the Department of Cognitive Science at Johns Hopkins.</div>
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Meeting link: <a href="https://uwaterloo.zoom.us/j/94597018322?pwd=ekpzNklNUHRuSlJ2LzlvTkx0T3NtQT09" id="LPlnk268616">https://uwaterloo.zoom.us/j/94597018322?pwd=ekpzNklNUHRuSlJ2LzlvTkx0T3NtQT09</a> </div>
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The title and abstract follow. </div>
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Regards,
<div>Bryan</div>
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<b>The neural computations underlying real-world social interaction perception</b></div>
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Humans perceive the world in rich social detail. We effortlessly recognize not only objects and people in our environment, but also social interactions between people. The ability to perceive and understand social interactions is critical for functioning in
our social world. We recently identified a brain region that selectively represents others’ social interactions in the posterior superior temporal sulcus (pSTS) in a manner that is distinct from other visual and social processes, like face recognition and
theory of mind. However, it is unclear how social interactions are processed in the real world where they co-vary with many other sensory and social features. In the first part of my talk, I will discuss new work using naturalistic movie fMRI paradigms and
novel machine learning analyses to understand how humans process social interactions in real-world settings. We find that social interactions guide behavioral judgements and are selectively processed in the pSTS, even after controlling for the effects of other
co-varying perceptual and social information, including faces, voices, and theory of mind. In the second part of my talk, I will discuss the computational implications of social interaction selectivity and present a novel graph neural network model, SocialGNN,
that instantiates these insights. SocialGNN reproduces human social interaction judgements in both controlled and natural videos using only visual information, but requires relational, graph structure and processing to do so. Together, this work suggests that
social interaction recognition is a core human ability that relies on specialized, structured visual representations. <br>
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Bryan Tripp, PhD </div>
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<span style="color: rgb(0, 0, 0); font-family: Calibri, Arial, Helvetica, sans-serif; font-size: 12pt;">Associate Professor, Department of Systems Design Engineering</span><br>
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Core Member, Centre for Theoretical Neuroscience</div>
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University of Waterloo</div>
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