|
Size: 5433
Comment:
|
Size: 4865
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 2: | Line 2: |
| 5:30 – [''Global''] Reproductible processing pipelines and multiverses | '''5:30 –''' [''Global''] Reproductible processing pipelines and multiverses |
| Line 4: | Line 4: |
| 8:30 – '''Registration & Continental Breakfast ''' | '''8:30 – '''Registration & Continental Breakfast |
| Line 6: | Line 6: |
| 9:15 – Richard Leahy (University of Southern California): 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]]''' |
| Line 8: | Line 8: |
| 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 |
| Line 12: | Line 12: |
| 10:30 – Anand Joshi (University of Southern California): Brainsuite Demo & Discussion | '''10:30 – '''Anand Joshi (University of Southern California): Brainsuite Demo & Discussion |
| Line 14: | Line 14: |
| 11:00 – Richard Leahy (University of Southern California): Introduction to EEG/MEG Analysis | '''11:00 – '''Richard Leahy (University of Southern California): Introduction to EEG/MEG Analysis |
| Line 16: | Line 16: |
| 11:45 – Cameron Sacks (Wearable Sensing): EEG Live Demo & Discussion | '''11:45 –''' Cameron Sacks (Wearable Sensing): EEG Live Demo & Discussion |
| Line 18: | Line 18: |
| 12:00 – ''Lunch Break'' | '''12:00 – ''Lunch Break'' ''' |
| Line 20: | Line 20: |
| 12:30–17:30 – [[https://neuroimage.usc.edu/brainstorm/WorkshopLA2023|Tutorial – Hands-On Brainstorm]] | '''12:30–17:30 ''' – [[https://neuroimage.usc.edu/brainstorm/WorkshopLA2023|Tutorial – Hands-On Brainstorm]] |
| Line 22: | Line 22: |
| Raymundo Cassani (McGill University) | . Raymundo Cassani (McGill University) Takfarinas Medani (University of Southern California) . |
| Line 24: | Line 25: |
| Takfarinas Medani (University of Southern California) | '''12:30–13:00''' Onsite assistance in installing the material for the training session |
| Line 26: | Line 27: |
| ''12:30–13:00 '' Onsite assistance in installing the material for the training session | '''13:00–13:30 '''Introduction to Brainstorm (lecture) |
| Line 28: | Line 29: |
| '' 13:00–13:30 ''Introduction to Brainstorm (lecture) | '''13:30–14:35 Loading anatomy and recordings ''' |
| Line 30: | Line 31: |
| '' 13:30–14:35 ''Loading anatomy and recordings | Set anatomy |
| Line 32: | Line 33: |
| '' Set anatomy '' |
Review Raw recordings |
| Line 35: | Line 35: |
| '' Review Raw recordings'' | Import events |
| Line 37: | Line 37: |
| '' Import events'' | '''14:35–15:35 Pre-processing ''' |
| Line 39: | Line 39: |
| '' 14:35–15:35 ''Pre-processing | Frequency filters |
| Line 41: | Line 41: |
| '' Frequency filters '' |
Artefact detections |
| Line 44: | Line 43: |
| '' Artefact detections'' | Artifact correction with SSP |
| Line 46: | Line 45: |
| '' Artifact correction with SSP'' | '''15:30–15:45 Coffee Break ''' |
| Line 48: | Line 47: |
| '' 15:30–15:45 Coffee Break'' | '''15:45–16:20 Analysis sensor level ''' |
| Line 50: | Line 49: |
| '' 15:45–16:20 Analysis sensor level'' | ''Import recording'' |
| Line 52: | Line 51: |
| '' Import recording'''' <<BR>>'' | Review trials |
| Line 54: | Line 53: |
| '' Review trials'' | Trial averages |
| Line 56: | Line 55: |
| '' Trial averages'' | '''16:20–16:55 Source estimation ''' |
| Line 58: | Line 57: |
| '' 16:20–16:55 Source estimation'' | Forward Model (aka Head model) |
| Line 60: | Line 59: |
| '' Forward Model (aka Head model)'''''' | Noise covariance matrix |
| Line 62: | Line 61: |
| '' Noise covariance matrix'' | Source estimation (from EEG and MEG recording) |
| Line 64: | Line 63: |
| '' Source estimation (from EEG and MEG recording)'' | '''16:55–17:15 Analysis source level ''' |
| Line 66: | Line 65: |
| '' 16:55–17:15 Analysis source level'' | Cortex parcellations: Atlases and scouts |
| Line 68: | Line 67: |
| '' Cortex parcellations: Atlases and scouts'''''' | Noise covariance matrix |
| Line 70: | Line 69: |
| '' Noise covariance matrix'' '' Source estimation (from EEG and MEG recording)'''' '' |
Source estimation (from EEG and MEG recording) |
| Line 77: | Line 72: |
| '' '' | '' '' |
| Line 79: | Line 74: |
| 5:30 – [''Global''] Deep Neural Network (DNN) analysis for MEEG data | ''5:30 – [''Global''] Deep Neural Network (DNN) analysis for MEEG data '' |
| Line 81: | Line 76: |
| 8:30 – ''' Continental Breakfast''' | ''8:30 – ''' Continental Breakfast''' '' |
| Line 83: | Line 78: |
| 9:00 – 17:30 – [''Local''] Machine Learning and EEG | ''9:00 – 17:30 – [''Local''] Machine Learning and EEG '' |
| Line 85: | Line 80: |
| 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”'' '' |
| Line 87: | Line 89: |
| 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)''' '' |
| Line 89: | Line 91: |
| 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''' '' |
| Line 91: | Line 93: |
| 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”'' '' |
| Line 93: | Line 97: |
| 10:15–10:40''– ''Bin He (Carnegie Mellon University)'': “AI/ML Enhances Dynamic Brain Imaging from EEG/MEG”'' | ''''' Panel Discussion''' '' |
| Line 95: | Line 99: |
| '''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“'' '' |
| Line 97: | Line 101: |
| Session 2: Self Supervised Leaning; session chair: Takfarinas Medani | ''''' Coffee ''''''Break(15:10–15:40)''' '' |
| Line 99: | Line 103: |
| 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''' '' |
| Line 101: | Line 105: |
| 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”'' '' |
| Line 103: | Line 109: |
| ''' 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 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