Invasive Brain Computer Interface

Characterization of BMI control signals

The search for the optimal control signal(s) is one of the most urgent questions in current BMI research. The characterization of potential BMI control signals is a subject of our research. We focus on intracranial EEG signals from motor cortex and other brain regions involved in the control of behavior. An example of single trial decoding results obtained from ECoG signals is shown in the following figures:

(Left) Position of the grid electrode over the left cerebral hemisphere, covering part of the prefrontal, premotor, primary motor, parietal, and temporal cortex.  (Middle) Intraoperatively taken photograph of subdural grid electrode implantation. (Right) Map of decoding power (DP, in % of correctly inferred trials) in respect to right vs. left finger movement based on the low frequency component of ECoG signals. The map corresponds to the area covered by the grid electrode. Black symbols: electrodes with motor responses upon electrical stimulation (■ arm, □ finger with 1 = thumb, 2 = index finger, 5 = little finger, Δ oro-facial, * eye), white symbols: sensory responses. Maximal DP of 100% was found at an electrode within M1 where electrical stimulation elicited index finger movement. All Figures from Ball et al., BMT Berlin Suppl, 2004.

Publications:

• Ball T, Schulze-Bonhage A, Aertsen A, Mehring C (2009),
  Differential representation of arm movement direction in relation to cortical anatomy and function,
  Journal of Neural Engineering 6(1):016006
• Pistohl T, Ball T, Schulze-Bonhage A, Aertsen A, Mehring C (2008),
  Prediction of Arm Movement Trajectories  from ECoG-Recordings in Humans.,
  J Neurosci Methods, 167/1 pp. 105-115
• Mehring C, Nawrot MP, Cardoso de Oliveira S, Vaadia E, Schulze-Bonhage A, Aertsen A, Ball T (2005),
  Comparing information about arm movement direction in single channels of local and epicortical field potentials from monkey and human motor cortex.,
  J.Physiol. (Paris) 98:498-506
• Ball T, Nawrot MP, Pistohl T, Aertsen A, Schulze-Bonhage A, Mehring C (2004),
  Towards a brain-machine interface based on epicortical field potentials.,
  Biomed. Eng. (Berlin), 49 (Suppl. 2), 756-759