5433
Comment:
|
8000
|
Deletions are marked like this. | Additions are marked like this. |
Line 1: | Line 1: |
===== WEDNESDAY 18th ===== 5:30 – [''Global''] Reproductible processing pipelines and multiverses |
= Cutting Garden 2023: Los Angeles Garden! = <<HTML(<img align="right" alt="cutting_lax_logo.png" class="attachment" src="/brainstorm/WorkshopLA2023?action=AttachFile&do=get&target=cutting_lax_logo.png" title="cutting_lax_logo.png" style="width: 35%;">)>> |
Line 4: | Line 4: |
8:30 – '''Registration & Continental Breakfast ''' | As part of the [[https://cuttinggardens2023.org/|CuttingGardens2023 conference]]. <<BR>> |
Line 6: | Line 6: |
9:15 – Richard Leahy (University of Southern California): Opening of the LA Garden | The Los Angeles (LA) Garden will be held at the Ming Hsieh Department of Electrical and Computer Engineering (EEB) at the University of Southern California (USC). This event is scheduled to be an in-person gathering, but there will also be an option to broadcast it to all Gardens. |
Line 8: | Line 8: |
9:30 – David Shattuck (University of California, Los Angeles): Introduction and Overview of Brainsuite | The LA Garden will span across two days. On the first day, we have scheduled a Brainstorm workshop and a Brainsuite Demo. The second day will feature local speakers presenting cutting-edge methods on Deep Neural Networks and Machine learning techniques applied to EEG data. |
Line 10: | Line 10: |
10:15 ''Coffee Break'' | Furthermore, we are arranging a live stream of the Global Program, allowing anyone interested to join remotely. External attendees are more than welcome to participate, but prior registration will be required for attendance. |
Line 12: | Line 12: |
10:30 – Anand Joshi (University of Southern California): Brainsuite Demo & Discussion | == WEDNESDAY 18th == '''5:30 –''' [''Global''] Reproductible processing pipelines and multiverses |
Line 14: | Line 15: |
11:00 – Richard Leahy (University of Southern California): Introduction to EEG/MEG Analysis | '''8:30 – '''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/Local-Program_LA.pdf|Registration & Continental Breakfast]] |
Line 16: | Line 17: |
11:45 – Cameron Sacks (Wearable Sensing): EEG Live Demo & Discussion | '''9:15 – Richard Leahy''' (University of Southern California): |
Line 18: | Line 19: |
12:00 – ''Lunch Break'' | ''' [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/WelcomeCuttingEEGLAGarden__intro_leahy.pdf|Opening of the LA Garden]]''' |
Line 20: | Line 21: |
12:30–17:30 – [[https://neuroimage.usc.edu/brainstorm/WorkshopLA2023|Tutorial – Hands-On Brainstorm]] | '''9:30 – David Shattuck '''(University of California, Los Angeles): |
Line 22: | Line 23: |
Raymundo Cassani (McGill University) | . Introduction and Overview of Brainsuite |
Line 24: | Line 25: |
Takfarinas Medani (University of Southern California) | '''10:15''' ''Coffee Break'' |
Line 26: | Line 27: |
''12:30–13:00 '' Onsite assistance in installing the material for the training session | '''10:30 – Anand Joshi''' (University of Southern California): |
Line 28: | Line 29: |
'' 13:00–13:30 ''Introduction to Brainstorm (lecture) | . [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/BrainSuiteToolsGardens_joshi.pdf|Brainsuite Tools & Discussion]] |
Line 30: | Line 31: |
'' 13:30–14:35 ''Loading anatomy and recordings | '''11:00 – Richard Leahy''' (University of Southern California): |
Line 32: | Line 33: |
'' Set anatomy '' |
. [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/BrainstormEEGOverviewCuttingGardens2023_leahy.pdf|Introduction to EEG/MEG Analysis]] |
Line 35: | Line 35: |
'' Review Raw recordings'' | '''11:45 –''' '''Cameron Sacks''' (Wearable Sensing): |
Line 37: | Line 37: |
'' Import events'' | . [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/wearableSensig_Cameron_compressed.pdf|EEG Live Demo & Discussion]] |
Line 39: | Line 39: |
'' 14:35–15:35 ''Pre-processing | '''12:00 – ''Lunch Break'' ''' |
Line 41: | Line 41: |
'' Frequency filters '' |
'''12:30–17:30 ''' – [[https://neuroimage.usc.edu/brainstorm/WorkshopLA2023|Tutorial – Hands-On Brainstorm]] |
Line 44: | Line 43: |
'' Artefact detections'' | . '''Raymundo Cassani '''(McGill University) &''' Takfarinas Medani '''(University of Southern California) . |
Line 46: | Line 46: |
'' Artifact correction with SSP'' | '''12:30–13:00''' Onsite assistance in installing the material for the training session |
Line 48: | Line 48: |
'' 15:30–15:45 Coffee Break'' | '''13:00–13:30 '''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/2023_lax_tm_bst.pdf|Introduction to Brainstorm (lecture)]] - [[https://www.youtube.com/watch?v=_h-X6GfxmpE|Youtube Video]] - |
Line 50: | Line 50: |
'' 15:45–16:20 Analysis sensor level'' | '''13:30–14:35 Loading anatomy and recordings ''' |
Line 52: | Line 52: |
'' Import recording'''' <<BR>>'' | . Set anatomy |
Line 54: | Line 54: |
'' Review trials'' | . Review Raw recordings |
Line 56: | Line 56: |
'' Trial averages'' | . Import events |
Line 58: | Line 58: |
'' 16:20–16:55 Source estimation'' | '''14:35–15:35 Pre-processing ''' |
Line 60: | Line 60: |
'' Forward Model (aka Head model)'''''' | . Frequency filters |
Line 62: | Line 62: |
'' Noise covariance matrix'' | . Artefact detections |
Line 64: | Line 64: |
'' Source estimation (from EEG and MEG recording)'' | . Artifact correction with SSP |
Line 66: | Line 66: |
'' 16:55–17:15 Analysis source level'' | '''15:30–15:45 Coffee Break ''' |
Line 68: | Line 68: |
'' Cortex parcellations: Atlases and scouts'''''' | '''15:45–16:20 Analysis sensor level ''' |
Line 70: | Line 70: |
'' Noise covariance matrix'' | . Import recording'' '' |
Line 72: | Line 72: |
'' Source estimation (from EEG and MEG recording)'''' '' | . ''Review trials '' |
Line 74: | Line 74: |
. ''Trial averages '' | |
Line 75: | Line 76: |
'''''16:20–16:55 Source estimation ''' '' | |
Line 76: | Line 78: |
===== THURSDAY 19th ===== '' '' |
. ''Forward Model (aka Head model) '' |
Line 79: | Line 80: |
5:30 – [''Global''] Deep Neural Network (DNN) analysis for MEEG data | . ''Noise covariance matrix '' |
Line 81: | Line 82: |
8:30 – ''' Continental Breakfast''' | . ''Source estimation (from EEG and MEG recording) '' |
Line 83: | Line 84: |
9:00 – 17:30 – [''Local''] Machine Learning and EEG | '''''16:55–17:15 Analysis source level ''' '' |
Line 85: | Line 86: |
Session 1: Computational Tools and Pipelines for ML analysis; session chair: Richard Leahy | . ''Cortex parcellations: Atlases and scouts '' |
Line 87: | Line 88: |
9:00–9:25- Arnaud Delorme (University of California, San Diego): “''Machine learning and the BIDS EEG data format”'' | . ''Noise covariance matrix '' |
Line 89: | Line 90: |
9:25–9:50- Tim Mullen (Intheon Labs):'' “Creating Deployable Workflows for EEG Signal Processing and ML/DL Using NeuroPype”'' | . ''Source estimation (from EEG and MEG recording) '' |
Line 91: | Line 92: |
9:50–10:15''– ''Ivan Tashev (Microsoft Research)'': “Workload estimation using brain- and bio- signals for adaptive training system”'' | == THURSDAY 19th == '''5:30 –''' [''Global''] Deep Neural Network (DNN) analysis for MEEG data '' '' |
Line 93: | Line 95: |
10:15–10:40''– ''Bin He (Carnegie Mellon University)'': “AI/ML Enhances Dynamic Brain Imaging from EEG/MEG”'' | '''8:30 –''' ''' Continental Breakfast''' '' '' |
Line 95: | Line 97: |
'''Coffee ''''''Break (10:40–11:00)''' | '''9:00 – 17:30 –''' [''Local''] Machine Learning and EEG '' '' |
Line 97: | Line 99: |
Session 2: Self Supervised Leaning; session chair: Takfarinas Medani | '''Session 1: Computational Tools and Pipelines for ML analysis; session chair: Richard Leahy.'' '' ''' |
Line 99: | Line 101: |
11:00–11:25''– ''Dominique Duncan (University of Southern California)'': “Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG”'' | . '''9:00–9:25- Arnaud Delorme '''(University of California, San Diego): “''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/BIDS_ml_usc_delorme.pdf|Machine learning and the BIDS EEG data format]]”'' . '''9:25–9:50- Tim Mullen''' (Intheon Labs):'' '' |
Line 101: | Line 104: |
11:25–11:50''– ''Wenhui Cui (University of Southern California)'': “Neuro-GPT: A Foundation Model Pretrained on Large-Scale EEG Data”'' | . ''“Creating Deployable Workflows for EEG Signal Processing and ML/DL Using NeuroPype”'' '' '' . '''9:50–10:15''– ''Ivan Tashev''' (Microsoft Research)'':'' . '' [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/2023_Garden_WorkloadEstimation_IvanTashev_final.pdf|“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”'' |
Line 103: | Line 110: |
''' Lunch ''''''Break (12:00–13:00)''' | '''Coffee ''''''Break (10:40–11:00)'''''' ''' |
Line 105: | Line 112: |
''' Session 3: Machine Learning for brain computer interfaces; session chair: Shrikanth Narayanan''' | '''Session 2: Self Supervised Leaning; session chair: Takfarinas Medani '' '' ''' |
Line 107: | Line 114: |
13:00–13:30- Alexander Silva (University of California, San Francisco): “A high performance neuroprosthesis for speech decoding and avatar control''“'' | . '''11:00–11:25''– ''Dominique Duncan''' (University of Southern California)'':'' . '' [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/Cutting_EEG_2023_Duncan.pdf|“Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG”]]'' '' '' . '''11:25–11:50''– ''Wenhui Cui '''(University of Southern California)'':'' . '' [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/eeg_foundation_model_talk_Cui.pdf|“Neuro-GPT: A Foundation Model Pretrained on Large-Scale EEG Data”]]'' |
Line 109: | Line 119: |
13:30–14:00''– ''Maryam Shanechi (University of Southern California)'': “AI-powered next-generation neurotechnologies”'' | '''Lunch Break (12:00–13:00) '' '' ''' |
Line 111: | Line 121: |
14:00–14:30''– ''Ludovic Bellier (University of California, Berkeley) '': “Reconstructing Pink Floyd from human auditory cortex”'' | '''Session 3: Machine Learning for brain computer interfaces; session chair: Shrikanth Narayanan '' '' ''' |
Line 113: | Line 123: |
''' Panel Discussion''' | . '''13:00–13:30- Alexander Silva '''(University of California, San Francisco): . [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/USCsymposium_Alex_Silva.pdf|“A high performance neuroprosthesis for speech decoding and avatar control]]''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/USCsymposium_Alex_Silva.pdf|“]] '' . '''''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) '': '' '' ''''' . [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/CuttingEEG20231029_LBellier.pdf|“Reconstructing Pink Floyd from human auditory cortex”]] |
Line 115: | Line 130: |
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“'' | '''Panel Discussion'' ''''' |
Line 117: | Line 132: |
''' Coffee ''''''Break(15:10–15:40)''' | . '''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 119: | Line 135: |
''' Session 4: Machine Learning for neurological disorders; session chair: Kristina Lerman''' | '''Coffee Break(15:10–15:40) ''' |
Line 121: | Line 137: |
15:40–16:05''– ''Srikantan Nagarajan (University of California, San Francisco)'': “Machine learning algorithms for electromagnetic brain imaging in dementia”'' | '''Session 4: Machine Learning for neurological disorders; session chair: Kristina Lerman''''' '' |
Line 123: | Line 139: |
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”'' | . 15:40–16:05''– ''Srikantan Nagarajan '(University of California, San Francisco)'':'' '' '' . ''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/USCTalk_Oct2023_v3_Sri.pdf|“Machine learning algorithms for electromagnetic brain imaging in dementia”]]'' '' '' '' '' . '''16:05–16:30''''''''– ''Dimitrios Pantazis''''' (Massachusetts Institute of Technology)'':'' '' ''' ''' . [[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/CuttingEEG_GardenLA2023_Pantazis.pdf|“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)'':''''' '' ''' ''' . ''[[https://neuroimage.usc.edu/resources/CuttingEEG2023finalSlides/Cutting_Gardens_daSilvaCastanheira_short.pdf|“Inter-individual differences in neurophysiology vary with age and disease”]] '' ''' ''' |
Line 125: | Line 146: |
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''' |
Cutting Garden 2023: Los Angeles Garden!
As part of the CuttingGardens2023 conference.
The Los Angeles (LA) Garden will be held at the Ming Hsieh Department of Electrical and Computer Engineering (EEB) at the University of Southern California (USC). This event is scheduled to be an in-person gathering, but there will also be an option to broadcast it to all Gardens.
The LA Garden will span across two days. On the first day, we have scheduled a Brainstorm workshop and a Brainsuite Demo. The second day will feature local speakers presenting cutting-edge methods on Deep Neural Networks and Machine learning techniques applied to EEG data.
Furthermore, we are arranging a live stream of the Global Program, allowing anyone interested to join remotely. External attendees are more than welcome to participate, but prior registration will be required for attendance.
WEDNESDAY 18th
5:30 – [Global] Reproductible processing pipelines and multiverses
8:30 – Registration & Continental Breakfast
9:15 – Richard Leahy (University of Southern California):
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):
11:00 – Richard Leahy (University of Southern California):
11:45 – Cameron Sacks (Wearable Sensing):
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) - Youtube Video -
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) :
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):
16:30–16:55– Jason da Silva Castanheira (McGill University):
“Inter-individual differences in neurophysiology vary with age and disease”
Closing and final remarks