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| 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'' |
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'' |
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| Raymundo Cassani (McGill University) | . Raymundo Cassani (McGill University) Takfarinas Medani (University of Southern California) 12:30–13:00 Onsite assistance in installing the material for the training session |
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| Takfarinas Medani (University of Southern California) | 13:00–13:30 Introduction to Brainstorm (lecture) |
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| ''12:30–13:00 '' Onsite assistance in installing the material for the training session | 13:30–14:35 Loading anatomy and recordings |
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| '' 13:00–13:30 ''Introduction to Brainstorm (lecture) | <<BR>>Set anatomy |
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| '' 13:30–14:35 ''Loading anatomy and recordings | <<BR>>Review Raw recordings |
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| '' Set anatomy '' |
<<BR>>Import events |
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| '' Review Raw recordings'' | 14:35–15:35 Pre-processing |
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| '' Import events'' | <<BR>>Frequency filters |
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| '' 14:35–15:35 ''Pre-processing | <<BR>>Artefact detections |
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| '' Frequency filters '' |
<<BR>>Artifact correction with SSP |
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| '' Artefact detections'' | 15:30–15:45 Coffee Break |
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| '' Artifact correction with SSP'' | 15:45–16:20 Analysis sensor level |
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| '' 15:30–15:45 Coffee Break'' | <<BR>>''Import recording'' |
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| '' 15:45–16:20 Analysis sensor level'' | <<BR>>Review trials |
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| '' Import recording'''' <<BR>>'' | <<BR>>Trial averages |
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| '' Review trials'' | 16:20–16:55 Source estimation |
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| '' Trial averages'' | <<BR>>Forward Model (aka Head model) |
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| '' 16:20–16:55 Source estimation'' | <<BR>>Noise covariance matrix |
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| '' Forward Model (aka Head model)'''''' | <<BR>>Source estimation (from EEG and MEG recording) |
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| '' Noise covariance matrix'' | 16:55–17:15 Analysis source level |
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| '' Source estimation (from EEG and MEG recording)'' | <<BR>>Cortex parcellations: Atlases and scouts |
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| '' 16:55–17:15 Analysis source level'' | <<BR>>Noise covariance matrix |
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| '' Cortex parcellations: Atlases and scouts'''''' '' Noise covariance matrix'' '' Source estimation (from EEG and MEG recording)'''' '' |
<<BR>>Source estimation (from EEG and MEG recording) |
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| '' '' | '' '' |
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| 5:30 – [''Global''] Deep Neural Network (DNN) analysis for MEEG data | ''5:30 – [''Global''] Deep Neural Network (DNN) analysis for MEEG data '' |
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| 8:30 – ''' Continental Breakfast''' | ''8:30 – ''' Continental Breakfast''' '' |
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| 9:00 – 17:30 – [''Local''] Machine Learning and EEG | ''9:00 – 17:30 – [''Local''] Machine Learning and EEG '' |
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| Session 1: Computational Tools and Pipelines for ML analysis; session chair: Richard Leahy | . ''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”'' '' |
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| 9:00–9:25- Arnaud Delorme (University of California, San Diego): “''Machine learning and the BIDS EEG data format”'' | ''''' Lunch ''''''Break (12:00–13:00)''' '' |
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| 9:25–9:50- Tim Mullen (Intheon Labs):'' “Creating Deployable Workflows for EEG Signal Processing and ML/DL Using NeuroPype”'' | ''''' Session 3: Machine Learning for brain computer interfaces; session chair: Shrikanth Narayanan''' '' |
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| 9:50–10:15''– ''Ivan Tashev (Microsoft Research)'': “Workload estimation using brain- and bio- signals for adaptive training system”'' | . ''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”'' '' |
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| 10:15–10:40''– ''Bin He (Carnegie Mellon University)'': “AI/ML Enhances Dynamic Brain Imaging from EEG/MEG”'' | ''''' Panel Discussion''' '' |
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| '''Coffee ''''''Break (10:40–11:00)''' | . ''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“'' '' |
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| Session 2: Self Supervised Leaning; session chair: Takfarinas Medani | ''''' Coffee ''''''Break(15:10–15:40)''' '' |
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| 11:00–11:25''– ''Dominique Duncan (University of Southern California)'': “Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG”'' | ''''' Session 4: Machine Learning for neurological disorders; session chair: Kristina Lerman''' '' |
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| 11:25–11:50''– ''Wenhui Cui (University of Southern California)'': “Neuro-GPT: A Foundation Model Pretrained on Large-Scale EEG Data”'' | . ''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”'' '' |
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| ''' 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''' |
''''' Closing and final remarks''' '' |
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 – 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