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 Demo & 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)

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