Knowledge Vault 3/75 - G.TEC BCI & Neurotechnology Spring School 2024 - Day 8
recoveriX study with different control groups
Jack Zhang, The Hong Kong Polytechnic University (HK)
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Concept Graph & Resume using Claude 3 Opus | Chat GPT4 | Llama 3:

Jack Zhang
HK Polytechnic Univ research. 1
Lab: brain stimulation, behavior,
neurophysiology. 2
BCI: assistive devices,
therapeutic tools. 3
Motor BCI: motor imagery,
induce neuroplasticity. 4
EEG in BCI:
temporal resolution, portability. 5
ERD: cortical activation,
key BCI feature. 6
BCI meta-analysis:
improved outcomes post-intervention. 7
Pilot RCT: BCI with
FES+VR, FES, VR. 8
All BCI interventions
improved function. 9
Motor imagery accuracy
correlated with gains. 10
BCI training effects
specific to movements. 11
Resting EEG detects
abnormal post-stroke patterns. 12
Reduced ERD over
ipsilesional motor cortex. 13
Mirror feedback rebalances
hemispheric activity. 14
Interhemispheric asymmetry in
delta/theta and beta. 15
Beta power, delta networks
reflect reorganization. 16
Greater beta ERD during
mirrored movement. 17
Beta ERD correlated with
function in mirror conditions. 18
RCT: TBS before
robotic training. 19
Real TBS improved function,
ERD, reduced delta. 20
Baseline mirror ERD predicted
brain stimulation gains. 21
Future: fNIRS-BCI, robotic outputs,
closed-loop TMS. 22-24
Sham BCI control
considerations needed. 25
Increasing BCI sessions
could enhance efficacy. 26
TMS timing with
oscillations affects excitability. 27
Collaborations: cardiopulmonary rehab,
heart-brain BCI. 28
Topics: BCI, neurophysiology,
brain stimulation for stroke. 29
Themes: neuroplasticity, asymmetry,
personalized neuromodulation. 30

Resume:

1.- Jack Zhang from Hong Kong Polytechnic University presented recent research using the GTAC Recovery X device and neurophysiological studies in stroke rehabilitation.

2.- Their lab has 3 components: non-invasive brain stimulation, behavior tracking, and neural modulation/neurophysiology. They use the Recovery X for BCI research.

3.- Brain-computer interfaces can be used as both assistive devices to control external machines and as therapeutic tools to improve recovery after neurological injury.

4.- In motor BCI, the user regulates brain activity related to motor execution via motor imagery to control an external device, inducing neuroplasticity.

5.- EEG is commonly used in BCI for its excellent temporal resolution, portability, and ability to assess sensorimotor rhythms related to motor imagery.

6.- Event-related desynchronization (ERD) during motor imagery represents cortical activation and is used as a key feature in many motor BCI systems.

7.- A meta-analysis found BCI-based interventions significantly improved upper limb motor outcomes compared to sham immediately post-intervention, but not at follow-up.

8.- Their pilot RCT compared BCI with FES+VR feedback, just FES, and just VR in 27 chronic stroke patients over 10 sessions.

9.- All 3 BCI interventions significantly improved upper limb function, but combining FES+VR was not superior to FES or VR alone.

10.- Motor imagery accuracy in the first BCI session correlated with motor gains, suggesting precise motor imagery is key to BCI efficacy.

11.- The capacity for motor imagery did not significantly improve, indicating the BCI training effects were specific to the trained movements.

12.- Resting-state EEG can detect abnormal brain activity patterns after stroke, such as increased low-frequency and decreased high-frequency oscillations.

13.- Movement-related ERD over the ipsilesional primary motor cortex is reduced after stroke and correlates with upper limb motor function.

14.- Mirror visual feedback during unaffected hand movement can rebalance hemispheric activity and increase contralesional ERD in stroke patients.

15.- Their cross-sectional resting-state EEG study found interhemispheric asymmetry in delta/theta (higher ipsilesionally) and beta (lower ipsilesionally) power in chronic stroke.

16.- Beta power bilaterally and delta band network properties correlated with upper limb motor function, reflecting regional and network-level reorganization post-stroke.

17.- Their task-based EEG study found greater high beta ERD over contralateral sensorimotor areas during actual and mirrored hand movement in stroke patients.

18.- Beta ERD correlated with upper limb function only in the mirror and action observation conditions, supporting mirror training relevance in stroke rehabilitation.

19.- An RCT applied excitatory theta-burst stimulation (TBS) to the ipsilesional motor cortex before robotic upper limb training in stroke patients.

20.- Real TBS improved motor function more than sham. Only the primed TBS group showed increased ERD and reduced pathological delta activity post-intervention.

21.- Baseline mirror-induced ERD predicted motor gains from the intervention, suggesting ERD could be a biomarker of brain stimulation responsiveness in stroke.

22.- Future directions include using fNIRS-based BCI to target abnormal cerebrovascular perfusion in stroke and provide neurofeedback to normalize the pathological signals.

23.- They are connecting BCI with robotic devices as an alternative output to FES and piloting this setup in stroke patients.

24.- Closed-loop integration of TMS with BCI based on individual brain states could improve the precision and efficacy of brain stimulation.

25.- Careful consideration is needed for sham BCI control conditions, as completely random feedback can be confusing and potentially train maladaptive patterns.

26.- Increasing BCI training session numbers could enhance efficacy, though an optimal dose is still unclear and shorter protocols can demonstrate proof-of-concept.

27.- Synchronizing TMS with peak negativity of the alpha oscillation may enhance cortical excitability, while stimulating at peak positivity could be inhibitory.

28.- Their lab focuses on stroke, but collaborates with physical therapy researchers investigating cardiopulmonary rehabilitation, with potential for heart-brain integrated BCI applications.

29.- The presentation covered a range of topics integrating BCI, neurophysiology, and brain stimulation to advance the mechanistic understanding and treatment of stroke.

30.- Key themes included leveraging neuroplasticity, re-balancing aberrant hemispheric asymmetries, and personalizing neuromodulation based on individual brain dynamics to optimize rehabilitation outcomes.

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