BCI papers

21 Feb 2020

FES paper by Prof Miller

• FES = implanted electrode in muscles.
• Use intracortical recordings from M1 to predict muscle contractions in three groups of muscles.
• During experiment, block muscle groups.
  • Grasping dysfunctional when muscle contractions blocked.
  • Grasping restored by FES stimulation predicted from M1 recordings.

2 Feb 2020

LFP paper by Rosa

• Use mean power of LFP between 200Hz – 400Hz band. For each channel compute mean power.
• decoded into 4 class (wheel chair task)
• uses LDA for decoding
• Adaptive
  • method 1: update dataset used to train LDA
    • there is a fix set of training data used to compute LDA model. The training dataset is a fixed size. Update training dataset when you have good data.
    • criteria
      • predict probability > 99%
      • same output in previous 5 timesteps
  • method 2: adaptive channel selection

 

 

LFP paper by Marc Slutzky

19 Jan 2020

[Brain-computer interfaces for dissecting cognitive processes underlying sensorimotor control]
(https://web.stanford.edu/~mgolub/publications/GolubCONeur2016.pdf)

 

 

29th Nov 2019

Rajesh Rao: Brain-computer interfacing: an introduction

20 nov 2019

Approaches to large scale neural recording by chronic implants for mobile BCIs

15 nov 2019

several papers by Zhang Yin and Steven Chase

talk to public by Jose Carmena

 

6 nov 2019

blog post about rao’s paper

rao’s paper about bidirectional neural interfaces

5 nov 2019

• Ten-dimensional anthropomorphic arm control in a human brain−machine interface: difficulties, solutions, and limitations
• Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array
• Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex
• Control of a brain–computer interface without spike sorting
• Self-recalibrating classifiers for intracortical brain–computer interfaces
• Intra-day signal instabilities affect decoding performance in an intracortical neural interface system

 

Intracortical recording stability in human brain–computer interface users

 

Current Challenges Facing the Translation of Brain Computer Interfaces from Preclinical Trials to Use in Human Patients (2016)

 

[Silicon Valley new focus on brain computer interface: hype or hope for new applications? (2016)](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343225/)

 

invasive vs non invasive signals for BCI. Will one prevail (2016)

 

 

3 nov 2019

• a new frontier: the convergence of nanotechnology, brain machine interface and artificial intelligence
• Computational neuroscience and neuroinformatics: Recent progress and resources.
• Arto Nurmikko – BCI PI from brown

 

konrad kording interview

 

konrad kording podcast neuralink

physical principles for scalable neural recording

neurallink live coverage by andrew hires

flexible electrodes (2017)

 

rethinking BCIs ted talk

 

direct neural interface – justin sanchez