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| Describe CuttingGarden2023_SymposiumLA here. | ===== – [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 – [[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 '' 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'''' <<BR>>'' '' 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''' '' |
– [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