1. Technological evolution of BCI
1970s: research algorithms to reconstruct movements from motor cortex neurons
1980s: Johns Hopkins researchers found a mathematical relationship between electrical responses of single motor-cortex neurons in rhesus macaque monkeys and the direction that monkeys moved their arms (based on a cosine function).
1990s: Several groups able to capture complex brain motor centre signals using recordings from neurons and use these to control external devices
The common thread throughout the research is the remarkable cortical plasticity of the brain, which often adapts to BCIs

2. Practical Elements
Signal acquisition: the BCI system's recorded + digitised brain signal input.
Signal processing: conversion of raw information into device command
Feature extraction = the determination of a meaningful change in signal Feature translation = the conversion of that signal alteration to a device command.
Statistical analysis on the basis of the probability function that an electrophysiological event correlates with a given cognitive or motor task.
Device output: the overt command or control functions produced.
word processing, communication, wheel chair, prosthetic limb.
new output channel, therefore must have feedback to improve how they alter their electro physiological signal.
Operating protocol: the manner in which the system is turned on/off.

3. Neurosurgical issues Safety
Durability/Reliability: scar, removal and re-implantation
Consistency, Useful complexity (DOF)
Suitability
Speed and accuracy
Efficacy: Technical vs. Practical

4. EEG-based BCI P300 evoked potentials Sensorimotor Cortex Rhythms
brain's response to infrequent or significant stimuli from its response to routine stimuli.
Sensorimotor Cortex Rhythms
Movement or preparation for movement is typically accompanied by a decrease in µ (8–12 Hz) and beta (18–26 Hz) activity over sensorimotor cortex
People, including those with ALS or SCI have learned to control µ or beta amplitudes in the absence of movement or sensation
susceptible to external forces (i.e., electrode movement) and contamination
less fidelity and spatial specificity and a limited frequency detection (<40Hz), resulting in prolonged user training for higher levels of control.
Spatial and frequency limitations prohibits complexity of movements supported by EEG

5. Single unit-based BCI
Best signal for BCI control has been achieved with multiple, single-unit action potentials recorded in parallel directly from cerebral cortex, in terms of accuracy, speed and DOF than single unit data.
Obtaining long-term stability of single unit recordings has proven difficult - Only provide a year of BCI control
Require insertion of a recording electrode into the brain parenchyma
Prone to scarring, implanted in eloquent regions of cortex

6. Simultaneously recorded intracellular and extracellular signals

7. Spatial dependence of spike waveform

8. Chronic recording electronics

9. How do you know you have a single unit?
Spike train autocorrelation
Always verify refractory period relative to long-time asymptote of autocorrelation function
Latency Variability Analysis

10. Antidromic Spike Collision

11. Multiple neural signals
Time (sec)
Voltage (A/D Levels)
Time (sec)
Voltage (A/D Levels)
3 msec

12. Spike sorting Raw Data Spike Detector Region from previous slide
Neuron #1 Spikes
Neuron #2 Spikes
Time (sec)

13. The ‘graduate student’ algorithm
Time (sec)
Voltage (A/D Levels)
Raw Data
Threshold detector at 32
Time (msec)
Voltage (A/D Levels)
Candidate Waveforms
# of Intervals
Time (msec)
Interspike Interval Histogram
Spike Height vs. Width Plot
Width (msec)
Height (A/D Levels)

14. General framework Locate Spikes Preprocess Waveforms
Density Estimation
Spike Classification
Quality Measures

15. Principal Component Analysis
Create “feature vector” for each spike
“Feature space”

16. Post-Stimulus Time Histogram (PSTH)
40 µV
200 ms

17. Semi-automatic Clustering

18. Electrocorticogram-based system
Electrocorticogram (EcoG) measures electrical activity of the brain taken from beneath the skull (subdural or epidural)
Gamma rhythms as well as µ and beta rhythms are prominent in ECoG during movements
higher spatial resolution, better signal-to-noise ratio, wider frequency range, and lesser training requirements than scalp-recorded EEG

21. Electric current dipole fields

22. Power spectrum handling & auto correlation function

23. Artifact detection in EEG
EOG
EMG

24. Stimulation mapping to locate cortical areas

25. Electromyography Indicator for muscle activation/deactivation
Electrode Categories
Inserted
Fine-wire (Intra-muscular)
Needle
Surface

26. Fine wire electrode vs. surface electrode
Pros
Extremely sensitive
Record single muscle activity
Access to deep musculature
Little cross-talk concern
Cons
Requires medical personnel, certification
Repositioning nearly impossible
Detection area may not be representative of entire muscle
Pros
Quick, easy to apply
No medical supervision, required certification
Minimal discomfort
Cons
Generally used only for superficial muscles
Cross-talk concerns
No standard electrode placement
May affect movement patterns of subject
Limitations with recording dynamic muscle activity

27. Characteristics of EMG signal and noise
Amplitude range: 0–10 mV (+5 to -5) prior to amplification
Usable energy: Range of Hz
Dominant energy: 50 – 150 Hz
Noise
Inherent noise in electronics equipment: 0 – thousands Hz
Cannot be eliminated
Reduced by using high quality components
Ambient noise: e.g. 60Hz
Radio transmission, electrical wires, fluorescent lights
Essentially impossible to avoid
Amplitude: 1 – 3x EMG signal
Motion artifact: 0 – 20 Hz
Electrode/skin interface, electrode cable
Reducible by proper circuitry and set-up
Inherent instability of signal
Amplitude is somewhat random in nature
Frequency range of 0 – 20 Hz is especially unstable > removal

28. Maximizing quality of EMG signal
Signal-to-noise ratio
Highest amount of information from EMG signal as possible
Minimum amount of noise contamination
As minimal distortion of EMG signal as possible
No unnecessary filtering
No distortion of signal peaks
No notch filters recommended, e.g. 60 Hz
Differential amplification
Reduces electromagnetic radiation noise
Dual electrodes
Electrode stability
Time for chemical reaction to stabilize
Important factors: electrode movement, perspiration, humidity changes
Improved quality of electrodes
Less need for skin abrasion, hair removal

30. Nerve conduction measurement
motor nerve conduction study, MNCS)
sensory nerve conduction study, SNCS)