This summary includes a concise but still very detailed summary of all the mandatory literature of the course. It is written in full sentences to make everything understandable for you. Each paper is divided into aim of the paper, the task, the results and the overall conclusion and interpretation....
Sensorimotor Processing
Task 1: the cortical control of movement
How are movements represented in the motor cortex? There are three interrelated
hypotheses on cortical movement control:
1. Primary motor cortex (M1), located on the precentral gyrus, contains a topographic
map of the body arranged systematically from a representation of the contralateral
foot at the top of the hemisphere to a representation of the mouth at the bottom.
2. Each point in the map specifies simple parameters of simple joint movements
controlled by a small number of muscles.
3. The cortical motor areas are organized in a hierarchical fashion. This is suggested
because higher-order motor areas project to M1, which in turn projects to and
controls the spinal cord. The higher-order areas control more complex movements.
Book Chapter (2013): Voluntary Movement: The Primary Motor Cortex (M1)
What exactly is represented in M1 is still under debate: The book chapter discusses
evidence regarding the different hypotheses.
The motor cortex:
• Was first divided into premotor and motor cortex (cytoarchitecture)
• Then later divided into subdivisions
→ PMC: supplementary motor area (medial) and lateral premotor cortex (lateral)
• In monkeys the motor areas have been divided into even smaller subdivisions
Hypothesis 1: there is a topographic map in primary cortex
• electrical stimulation of surface of limited cortex area of anesthetised animals evoked
movements of parts of contralateral body, this topography is crude
→ cortical magnification: not a point-to-point representation of body: instead, most
finely controlled body parts (e.g. fingers, face, mouth) are represented by
disproportionately large areas, reflecting the larger number of neurons needed for fine
motor control (more nerves in the skin in these areas, more neurons in the brain)
• However: Microstimulation of several sites in the arm motor map can produce rotations
of the same joint: one neuron involved in contractions of different muscles, and multiple
neurons can activate the same muscle
→ neurons that control wrist movements are
concentrated in the core and for the shoulder
around the core, and there is a lot of overlap
→ the higher the peak, the less stimulation
was needed to evoke a response
,Hypothesis 2: Many researchers have tried to elucidate the nature of the motor
representation expressed by the discharge of M1 neurons - Force vs. direction:
1. Concluding that M1 activity correlates with direction and amplitude of muscle forces:
• Study 1: Single cell recordings: found that a patch of cortex is specific to particular body
part and particular movement of the body part: The monkey was instructed to extend or
flex his wrist
→ when recording from M1, there was neural response just before extending the wrist,
and no response when flexing the wrist: spiking starts before movement
→ this suggests that there is the causal relationship that you first need neural activity in
M1 and then see the consequential movement
• Study 2: Monkey had to rotate a rod to one direction or the other (flexion/extension)
while the arm was restraint, in three conditions:
A When no load is applied to the wrist, the neuron fires before and during flexion
B When a load opposing flexion is applied, the monkey has to apply more force to do
the movement: the activity of the flexor muscles and also the neuron increases
C When a load assisting wrist flexion is applied, the flexor muscles and neuron show no
activity
2. However the previous experiments just focused on distal muscles and to simple
movement:
• the task is restricted to one dimension: just opposing directions of a single joint
• focused on distal joints (the wrist): normally, when we use our arm, that is a mainly
multicompartment action where muscles and joints have to work in synergy
In order to look at this a little more closely, they used a center-out reaching task: monkeys
start with a central position. hold a lever and are instructed (cue) to move it to one of the
indicated peripheral target points
• showed that some M1 neurons are direction selective, single neurons had clear
preference to a single direction of movement (figure A), (tuning curve manner)
• however, this data is still ambiguous: with one neuron only the direction at the peak of
the tuning curve can be estimated, as for all other amplitudes two movement
directions are possible (on the left and right of the tuning curve), thus, with one tuning
curve the movement direction is ambiguous, how does the brain know which direction
of movement is coded?
,→ The idea is that motor commands are population codes:
• activity of each neuron can be represented in a vector:
→ Direction = aligned to neuron’s preferred direction (PD)
→ Length = varies as a function of neurons spiking rate during each movement
• With use of these vectors the movement the monkey makes can be estimated:
→ by combining the tuning curves of multiple neurons, the vector of the actual
movement can be estimated
→ the actual movement is at 135 degrees (preferred direction of red neuron N1):
(1) only the tuning curve of N1 is ambiguous – when also using tuning curve of N2
(preferred direction at 45 degree) and getting the sum of both vectors, this gives a
close but not completely correct estimate of the movement.
(2) When now adding the tuning curve of N3, we have enough information, and the
sum of the vectors will give us the correct movement
→ This is a mechanism of how the motor cortex might code movement!
• The motor command for a movement is generated by a widely distributed population
of cells throughout motor map, each of which fires at a different intensity for
movement in a particular direction, eliciting a directional bias
• Thus: The overall directional bias of the activity within the population of neurons shifts
with movement direction so that the vectorial sum of the activity of all cells is a
population vector that closely matches that of the direction of movement
So far, we looked at the average firing rate of a specific movement: You can also do a
temporally resolved version of this by binning the activity each 25ms
• The monkey did a continuous spiraling finger movement (A)
• When estimating the vector of the population we are recording from (B), we can see
that it is nicely predicting the movement the monkey is doing also in a temporal
manner (C): pattern of activity signals moment-to-moment details
• Was also possible to be shown in the 3D movement domain
, The overall conclusion of those studies is that M1 activity correlates with the direction
(both 2D and 3D) of multi-joint reaching movements
→ not just limited to M1, also in other motor areas
3. However, it is still unclear whether the activity patterns signal changes in the direction
of movement per se, the direction and level of forces, or some combination
→ Still need to generate particular patterns of muscle activity; question whether neurons
encode kinematics (extrinsic, spatiotemporal form of movement) or kinetics (intrinsic, forces
and muscle activity required to generate movement)
Study: To tease those parameters apart, a mix of previous design was used: again, a center-
out reaching task and a poly system with weights that can work either with or against you
• The results show again that a single neuron has a preferred direction, but now you
can see what different load does to this activity:
→ when more force is needed, there is still the preference for the particular
direction, but the firing rate increases, when load assists movement it decreases
→ thus, the cell’s firing rate is related to the amount of force required to maintain
an arm trajectory in a given direction, not just the direction itself
• Again, we can make a population code:
→ In the pot below the monkey always does a leftward reach (or right): the
individual subplots indicate in which direction the weight was pulling the monkeys
arm: If the weight is assisting the monkey the population vector becomes rather
small, and if it’s counteracting the monkey the population vector becomes longer as
more force is used, and the population vectors are slightly tilted as the movement
has to be corrected a little bit
→ the overall directional bias of activity of a neural population varies with direction
of external load (to counteract its effect), even though the trajectory of the
movement does not change
→ only in M1, not in Parietal area 5: there the external load does not alter the
population vector, higher level area do not take required muscle force into account
Hypothesis 3: hierarchical processing does not seem to be correct! Motor areas are involved
in a variety of tasks, not just movement.
• Cortical level: cortical connections between motor areas and other areas are not
only feedforward but also feedback: highly connected and communicative
• Connectivity to the spinal cord: both premotor cortex and primary cortex have
direct connections to the spinal cord, not only M1
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