5433
Comment:
|
5391
|
Deletions are marked like this. | Additions are marked like this. |
Line 2: | Line 2: |
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 |
. 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 |
Line 22: | Line 17: |
Raymundo Cassani (McGill University) Takfarinas Medani (University of Southern California) ''12:30–13:00 '' Onsite assistance in installing the material for the training session |
. Raymundo Cassani (McGill University) Takfarinas Medani (University of Southern California) ''12:30–13:00 '' Onsite assistance in installing the material for the training session |
Line 32: | Line 24: |
'' Set anatomy '' |
'' Set anatomy '' |
Line 41: | Line 32: |
'' Frequency filters '' |
'' Frequency filters '' |
Line 52: | Line 42: |
'' Import recording'''' <<BR>>'' | '' Import recording'''' <<BR>>'''''''' ''' |
Line 54: | Line 44: |
'' Review trials'' | ''''' Review trials'' ''' |
Line 56: | Line 46: |
'' Trial averages'' | ''''' Trial averages'' ''' |
Line 58: | Line 48: |
'' 16:20–16:55 Source estimation'' | ''''' 16:20–16:55 Source estimation'' ''' |
Line 60: | Line 50: |
'' Forward Model (aka Head model)'''''' | ''''' Forward Model (aka Head model)'''''''''' ''''' |
Line 62: | Line 52: |
'' Noise covariance matrix'' | ''' Noise covariance matrix'' ''''' |
Line 64: | Line 54: |
'' Source estimation (from EEG and MEG recording)'' | ''' Source estimation (from EEG and MEG recording)'' ''''' |
Line 66: | Line 56: |
'' 16:55–17:15 Analysis source level'' | ''' 16:55–17:15 Analysis source level'' ''''' |
Line 68: | Line 58: |
'' Cortex parcellations: Atlases and scouts'''''' | ''' Cortex parcellations: Atlases and scouts'''''' ''' |
Line 70: | Line 60: |
'' Noise covariance matrix'' | ''''' Noise covariance matrix'' ''' |
Line 72: | Line 62: |
'' Source estimation (from EEG and MEG recording)'''' '' |
''''' Source estimation (from EEG and MEG recording)'''''''' '' |
Line 85: | Line 73: |
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”'' |
. 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”'' |
Line 107: | Line 87: |
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”'' |
. 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”'' |
Line 115: | Line 93: |
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“'' | . 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“'' |
Line 121: | Line 99: |
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”'' |
. 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”'' |
Line 128: | Line 104: |
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)
5:30 – [ 8:30 – Continental Breakfast 9:00 – 17:30 – [ 9:00–9:25- Arnaud Delorme (University of California, San Diego): “ 11:00–11:25 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 Panel Discussion 14:40–15:10 Coffee Break(15:10–15:40) Session 4: Machine Learning for neurological disorders; session chair: Kristina Lerman 15:40–16:05 Closing and final remarks THURSDAY 19th
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
– 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”
“ 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”
– Moderator: Shrikanth Narayanan and Kristina Lerman (University of Southern California): “The Role of Foundational Models in Spontaneous and Event Related EEG“
– 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”