CuttingGarden2023: LA Garden Program

WEDNESDAY 18th

5:30 – [Global] Reproductible processing pipelines and multiverses

8:30 – Registration & Continental Breakfast

9:15 – Richard Leahy (University of Southern California):

Opening of the LA Garden

9:30 – David Shattuck (University of California, Los Angeles):

• Introduction and Overview of Brainsuite

10:15 Coffee Break

10:30 – Anand Joshi (University of Southern California):

• Brainsuite Tools & Discussion

11:00 – Richard Leahy (University of Southern California):

• Introduction to EEG/MEG Analysis

11:45 – Cameron Sacks (Wearable Sensing):

• EEG Live Demo & Discussion

12:00 – Lunch Break

12:30–17:30 – Tutorial – Hands-On Brainstorm

• Raymundo Cassani (McGill University) & Takfarinas Medani (University of Southern California)

12:30–13:00 Onsite assistance in installing the material for the training session

13:00–13:30 Introduction to Brainstorm (lecture) - Youtub Video -

13:30–14:35 Loading anatomy and recordings

• Set anatomy
• Review Raw recordings
• Import events

14:35–15:35 Pre-processing

• Frequency filters
• Artefact detections
• Artifact correction with SSP

15:30–15:45 Coffee Break

15:45–16:20 Analysis sensor level

• Import recording

• Review trials

• Trial averages

16:20–16:55 Source estimation

• Forward Model (aka Head model)

• Noise covariance matrix

• Source estimation (from EEG and MEG recording)

16:55–17:15 Analysis source level

• Cortex parcellations: Atlases and scouts

• Noise covariance matrix

• Source estimation (from EEG and MEG recording)

THURSDAY 19th

5:30 – [Global] Deep Neural Network (DNN) analysis for MEEG data

8:30 – Continental Breakfast

9:00 – 17:30 – [Local] Machine Learning and EEG

Session 1: Computational Tools and Pipelines for ML analysis; session chair: Richard Leahy.

• 9:00–9:25- Arnaud Delorme (University of California, San Diego): “Machine learning and the BIDS EEG data format”

• 9:25–9:50- Tim Mullen (Intheon Labs):

• “Creating Deployable Workflows for EEG Signal Processing and ML/DL Using NeuroPype”

• 9:50–10:15– Ivan Tashev (Microsoft Research):

• “Workload estimation using brain- and bio- signals for adaptive training system”

• 10:15–10:40– Bin He (Carnegie Mellon University):

• “AI/ML Enhances Dynamic Brain Imaging from EEG/MEG”

• Coffee Break (10:40–11:00)

Session 2: Self Supervised Leaning; session chair: Takfarinas Medani

• 11:00–11:25– Dominique Duncan (University of Southern California):

• “Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG”

• 11:25–11:50– Wenhui Cui (University of Southern California):

• “Neuro-GPT: A Foundation Model Pretrained on Large-Scale EEG Data”

Lunch Break (12:00–13:00)

Session 3: Machine Learning for brain computer interfaces; session chair: Shrikanth Narayanan

• 13:00–13:30- Alexander Silva (University of California, San Francisco):

• “A high performance neuroprosthesis for speech decoding and avatar control“

• 13:30–14:00– Maryam Shanechi (University of Southern California):

• “AI-powered next-generation neurotechnologies”

• 14:00–14:30– Ludovic Bellier '(University of California, Berkeley) :

• “Reconstructing Pink Floyd from human auditory cortex”

Panel Discussion

• 14:40–15:10– Moderator: Shrikanth Narayanan and Kristina Lerman (University of Southern California):

• “The Role of Foundational Models in Spontaneous and Event-Related EEG“

Coffee Break(15:10–15:40)

Session 4: Machine Learning for neurological disorders; session chair: Kristina Lerman

• 15:40–16:05– Srikantan Nagarajan '(University of California, San Francisco):

• “Machine learning algorithms for electromagnetic brain imaging in dementia”

• 16:05–16:30– Dimitrios Pantazis (Massachusetts Institute of Technology):

• “Graph representation learning of MEG signals opens a window to aging trajectories and Alzheimer’s disease”

• 16:30–16:55– Jason da Silva Castanheira (McGill University):

• “Inter-individual differences in neurophysiology vary with age and disease”

Closing and final remarks