Neuronal Population Coding of Movement Direction

Abstract

Although individual neurons in the arm area of the primate motor cortex are only broadly tuned to a particular direction in three-dimensional space, the animal can very precisely control the movement of its arm. The direction of movement was found to be uniquely predicted by the action of a population of motor cortical neurons. When individual cells were represented as vectors that make weighted contributions along the axis of their preferred direction (according to changes in their activity during the movement under consideration) the resulting vector sum of all cell vectors (population vector) was in a direction congruent with the direction of movement. This population vector can be monitored during various tasks, and similar measures in other neuronal populations could be of heuristic value where there is a neural representation of variables with vectorial attributes.

A Continuous Attractor Network Model Without Recurrent Excitation: Maintenance and Integration in the Head Direction Cell System

“…In order to reconstruct the current head direction θ (t) in bins [t, t + t], a population vector scheme (Georgopoulos et al, 1986) is employed to decode the ensemble HD cell activity:…”

The complementary brain: unifying brain dynamics and modularity

“…For example, it helps to explain how motor expectations (pattern) interact with volitional speed signals (energy) to generate goaldirected arm movements [89][90][91] , as during the computation of the Desired Velocity Vector in the cortical area 4 circuit of Figure 6. As noted in the discussion of 'where' and 'how' processing, a motor expectation represents where we want to move, such as to the position where our hand can grasp a desired object.…”

“…As noted in the discussion of 'where' and 'how' processing, a motor expectation represents where we want to move, such as to the position where our hand can grasp a desired object. Such a motor representation, or Target Position Vector (TPV), can prime a movement, or get us ready to make a movement, but by itself, it cannot release the movement 55,89 . First the TPV needs to be converted into a Difference Vector (DV), which triggers an overt action only when a volitional signal 90 that multiplicatively gates action read-out.…”

Cerebellar learning of accurate predictive control for fast-reaching movements

“…Following Georgopoulos et al (1986), variables are coded in the activity of a population of neurons with each neuron tuned to a speci®c value and its output de®ned as a cosine function of the di erence between the value of the variable and the neuron's preferred value. We model a total of 680 MFs; after preliminary simulations, we found that if 340 conveyed desired kinematic variables (position, velocity and acceleration for each joint), 280 target and movement distance information and 60 ®bers are Ia a erents from the six muscles, good performance could be obtained.…”