===== WEDNESDAY 18th =====
5:30   – [''Global''] Reproductible processing pipelines and multiverses8:30   – Registration & Continental Breakfast9:15   – Richard Leahy (University of Southern California): Opening of the LA Garden9:30   – David Shattuck (University of California, Los Angeles): Introduction and Overview of Brainsuite10:15    ''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  –   [[https://neuroimage.usc.edu/brainstorm/WorkshopLA2023|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

<<BR>>Set anatomy

<<BR>>Review Raw recordings

<<BR>>Import events

14:35–15:35    Pre-processing

<<BR>>Frequency filters

<<BR>>Artefact detections

<<BR>>Artifact correction with SSP

15:30–15:45     Coffee Break

15:45–16:20    Analysis sensor level

<<BR>>''Import recording''

<<BR>>Review trials

<<BR>>Trial averages

16:20–16:55    Source estimation

<<BR>>Forward Model (aka Head model)

<<BR>>Noise covariance matrix

<<BR>>Source estimation (from EEG and MEG recording)

16:55–17:15    Analysis source level

<<BR>>Cortex parcellations: Atlases and scouts

<<BR>>Noise covariance matrix

<<BR>>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''' ''