03 Brain-Computer Interfaces Flashcards
1
Q
What are the premotor cortices? (position, input, involvement)
A
- lateral part (including Broca’s area in the dominant hemisphere) and medial part (supplementary motor area and pre-SMA)
- receive input from prefrontal areas on motivation and intention (action goals) and from parietal lobe (information on circumstance)
- lateral premotor areas more involved in responses to the environment, medial premotor areas more involved in self initiated movements
2
Q
Relation premotor cortices - movement
A
- in a conditioned task, premotor neurons begin firing with the cue (intention), primary motor neurons fire at movement execution (action)
- premotor cortices assemble the movements necessary to achieve those goals and instruct the motor cortex, where simple movement patterns are stored
- premotor influence motor behavior both indirectly (via projections to primary motor cortex) and directly (>30 % of corticospinal neurons arise in premotor areas)
3
Q
Primary motor cortex (M1) anatomy
A
- anterior rim of the central sulcus and minor part of precentral gyrus
- topographical map of motor cortex comparable to sensory homunculus (yet less clear cut)
- lateral to medial: face (corticobulbar), upper extremity, trunk, lower extremity (all corticospinal)
- layer V giant pyramidal cells (Betz cells) contact contralateral (“second”) motor neurons in spinal chord
- stimulation of a single motor neuron elicits activity in 2-3 muscles (“muscle field” of neuron)
- M1 codes for simple movements, not single muscle
4
Q
What are upper and lower motor neurons? Which other structures are important for motor control?
A
- upper motor neurons: neurons from descending systems (motor cortex, brainstem centers)
- lower motor neurons: send axons out of the brainstem or spinal chord (ventral horn), innervate single muscle (grouped together into rod shaped clusters)
- other important structures for motor control: basal ganglia, cerebellum
5
Q
How are neurons in the ventral horn of spinal chord organised?
A
- lower motor neurons enter/exit spinal chord here
- neurons innervating proximal extremities are more medial, more distal extremities are more lateral
6
Q
Corticospinal and corticobulbar tract together
A
- Betz cells in layer V of M1 only account for 5% of the axons projected from motor cortex to the spinal cord
- Non Betz pyramidal neurons found in the V layer of M1 descend in the corticobulbar and corticospinal tracts
- they pass through the internal capsule, enter the cerebral peduncle at the base of the midbrain, pass through the base of the pons and coalesce to form the medullary pyramids
- corticobulbar tract terminates in the brainstem
7
Q
corticospinal tract
A
- near the caudal end of the medulla most fibers in the medullary pyramids are corticospinal axons
- About 90% of these axons decussate on the height of the caudal medulla and form the lateral corticospinal tract
- other 10% of such axons do not change sides and form the ventral corticospinal tract
- lateral corticospinal tract forms direct pathways from the cortex to the spinal cord and terminates primarily in lateral part of the ventral horn
- Some of these axons synapse directly onto α motor neurons that directly govern distal extremities (mostly hand and forearm muscles)
- Most of these axons however will terminate in pools of local circuit neurons that coordinate activities in lateral cell columns of the ventral horn
8
Q
definition Brain-Computer interface
A
- system measuring CNS activity
- converting it into artificial output
- output replaces, restores, enhances, supplements or improves natural CNS output
- -> changing/modifying ongoing interaction between CNS and its external or internal environment
- based on sensorimotor hypothesis
- BCI gives CNS additional artificial output (not neuromuscular or hormonal)
9
Q
sensorimotor hypothesis
A
entire function of CNS is to translate sensory inputs into motor outputs
10
Q
elements of BCI
A
- signal acquisition
- feature extraction
- feature translation
- device output
- (feedback)
- interactive functioning between CNS and BCI determined by operating protocol
11
Q
BCI - signal acquisition
A
- measurement of neurophysiological state of the brain
- recording interface gathers neural information reflecting intent embedded within brain activity
- acquired through particular sensory modality, e.g. scalp or intracranial electrodes, fMRI for metabolic activity
12
Q
BCI - feature extraction
A
- process of analysing digital signals and distinguishing pertinent signal characteristics (features) from irrelevant signals
- features should have strong correlations with users intent
- typical features: amplitudes or latencies of ERPs (e.g. P300), frequency power spectra (e.g., sensorimotor rhythms), firing rates of individual cortical neurons
13
Q
BCI - feature translation
A
- conversion of pertinent feature into device command using translation algorithm
- core = model (set of mathematical equations) describing relationship between intent and feature
- description can be employed in order to convert future observations to appropriate output (generalization)
- not all BCIs require separate feature extraction and translation (e.g. artificial neural networks)
14
Q
BCI - device output
A
- translated features allow for an output to operate a task-specific device
- various examples of different output devices: letter selection, cursor control, robotic arm operation
- output then again produces feedback
15
Q
Restoration of Hand Use in temporarily paralyzed monkeys
A
- Multi electrode recordings from the primary motor cortex M1 can be deployed to predict kinematic features of movement
- Neurons in M1 carry information related to the dynamics of movement as well as kinematics
- Such information can be employed to predict muscle activity (EMG) underlying complex reaching tasks
- In this study Pohlmeyer and colleagues use real time EMG predictions to control the focal electrical stimulation (FES) of multiple forearm muscles in temporarily paralyzed monkeys
