Monday, 7 June
| Time (EDT) | Session | Speaker(s) | Title | Links |
|---|---|---|---|---|
| 13:00 - 13:15 | Opening remarks | YouTube | ||
| 13:15 - 14:15 | Keynote talk | Pim Haselager |
Unifying AI & Neuroscience: A great idea! But to what purpose?The combination of Artificial Intelligence (AI) and Neuroscience (NS) has great promise. It can lead to various practical applications in a wide variety of fields, ranging from micro-targeted marketing to clinical therapy and law. At the same time, the combined power of AI and NS leads to serious questions about what it is that we would like to achieve and why. It also leads to questions about how we can exert meaningful human control over the ensuing technologies. This is especially urgent given the many challenges humanity is facing this century, from inequity to ecology. It seems fair to say that our current ways to address these challenges have not been, to put it mildly, particularly successful. AI and NS enable us to see our human strengths and weaknesses with greater clarity, and build more effective technology accordingly. But the potentially exploitative power of this combination of sciences does present us with the challenge to apply it wisely. I will suggest that we are in need of a more profound reflection on what our sciences show us about ourselves, what our technology enables us to do with that, and what, apparently, we aim to do with those insights and applications. |
YouTube |
| 14:20 - 14:50 | Lightning talks | Selection of presentations by participants | YouTube | |
| 14:50 - 15:10 | Lightning talks Q&A + Social | |||
| 15:05 - 15:10 | Active break | Caelan Taylor | ||
| 15:10 - 15:15 | Go to Crowdcast | |||
| 15:15 - 16:15 | Keynote talk | Megan Peters |
Linking metacognition and consciousness with computational modelsFew people tackle the neural or computational basis of qualitative experience (Frith, 2019). Why? One major reason is that science and philosophy have both struggled to propose how we might even begin to start studying it. Here I propose that metacognitive computations, and the subjective feelings that go along with them, give us a solid starting point. Specifically, perceptual metacognition possesses unique properties that provide a powerful and unique opportunity for studying the neural and computational correlates of subjective experience. I will describe these properties, and discuss how computational models of metacognition can be used to an empirically-tractable early step in identifying the generative process that constructs qualitative experience, drawing on empirical data. By applying decades of developments in computational cognitive science and formal computational model comparisons to the specific properties of perceptual metacognition, we may reveal new and exciting insights about how the brain constructs subjective conscious experiences and the nature of those experiences themselves. |
YouTube |
| 16:15 - 16:25 | Social break | |||
| 16:20 - 16:25 | Active break | Caelan Taylor | ||
| 16:25 - 16:30 | Go to Crowdcast | |||
| 16:30 - 17:15 | Panel discussion | Stefanie Blain-Moraes , Megan Peters , Pim Haselager , Irina Rish | YouTube | |
| 17:15 - 17:30 | Closing remarks | YouTube |
Tuesday, 8 June
| Time (EDT) | Session | Mentor(s) | Title | Links |
|---|---|---|---|---|
| 13:00 - 13:15 | Opening remarks | |||
| 13:15 - 14:00 | Round table | Aislinn Sandre , Robin Renault , Marie-Ève Vautrin-Nadeau | Round table on mental health | |
| 13:15 - 14:00 | Focused discussion | Guillaume Lajoie |
Machine learning and NeuroscienceA panel discussion with Dr. Pouya Bashinvan, Dr. Irina Rish and Dr. Danilo Bzdok about (1) deep network models of neural circuits (2) ML for large data analysis and (3) ANN to explore neuroscience ideas unattainable by experiments. |
|
| 14:00 - 14:15 | Social break | |||
| 14:15 - 15:00 | Workshop | Andréanne Proulx , Samuel Guay |
First steps into Open Science [Slides]This workshop aims to introduce the broad concept that is open science from a global perspective. We will touch on three core aspects that open science is based on, namely processes (e.g., collaboration, reproducibility), Products (e.g., Open Data, Open Materials), and Values (e.g., freedom, equity). We will then showcase some tools and state-of-the-art examples of openness from the Neuro-AI field. If time permits, we will end the workshop by collaboratively (yes, all of us!) creating a Neuro-AI open science student guide. |
|
| 14:15 - 15:00 | Focused discussion | Thomas R. Shultz | Memory and Learning | |
| 15:00 - 15:05 | Social break | |||
| 15:05 - 15:10 | Active break | Caelan Taylor | ||
| 15:10 - 15:15 | Go to the next session | |||
| 15:15 - 16:00 | Workshop | Madeleine Elise Nadler |
Developing, Disseminating, and Diversifying Knowledge: An Introduction to Equity, Diversity, and Inclusion (EDI) in Academia [Slides]This workshop is designed for new students as well as those with no background in Equity, Diversity, and Inclusion (EDI). The workshop aims to help develop awareness of EDI concepts and issues in Academia. Participants will be introduced to basics of EDI in both theory and reality with relation to data-driven research as well as current events. |
|
| 15:15 - 16:00 | Focused discussion | Paul Cisek | Decision Making | |
| 16:00 - 16:15 | Closing remarks | |||
| 16:15 - 16:45 | Social + Talent Show |