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| '''9:15 – '''Richard Leahy (University of Southern California):'''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/WelcomeCuttingEEGLAGarden__intro_leahy.pdf|Opening of the LA Garden]]''' | '''9:15 – ''' Richard Leahy (University of Southern California):'''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/WelcomeCuttingEEGLAGarden__intro_leahy.pdf|Opening of the LA Garden]]''' |
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| '''9:30 – '''David Shattuck (University of California, Los Angeles): Introduction and Overview of Brainsuite | '''9:30 – ''' David Shattuck (University of California, Los Angeles): Introduction and Overview of Brainsuite |
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| Set anatomy | . Set anatomy |
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| Review Raw recordings | . Review Raw recordings |
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| Import events | . Import events |
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| Frequency filters | . Frequency filters |
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| Forward Model (aka Head model) | . Forward Model (aka Head model) |
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CuttingGarden2023 Symposium: 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)
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