Figure 1: Behavioral task, recording sites, receptive fields, and schematic of hypotheses.

A: Schematic of the motion direction change detection task. The monkeys were cued in blocks of trials to expect changes in motion direction at one of two spatial locations (cue was 80% valid). The monkey started the trial by fixating a central spot. Two small Gabor stimuli synchronously flashed on for 200ms and off for a randomized period of 200–400ms. One of the stimuli was positioned inside the joint receptive fields of the MT and SC neurons, and the other was placed in the opposite hemifield. Both stimuli moved in a direction that was chosen to drive the MT population well. After a randomized number of stimulus presentations (between 2 and 13), the direction of one of the stimuli changed. The monkeys were rewarded for making a saccade to the direction change in either location. We analyzed neuronal responses to all identical stimulus presentations except the first to minimize the effect of adaptation.

B: Illustration of recording locations. Populations of MT and SC neurons were recorded with linear 24-channel moveable probes from the right hemisphere of two monkeys as they were doing the behavioral task described in (A).

C: Receptive field locations of recorded units from an example recording session. The dots represent the receptive field centers of 28 MT (red) and 26 SC (blue) units. The circles represent the size and location of the median receptive field from each area.

D: Schematics describing the hypotheses about attention-related changes in information flow between two areas. Each icon depicts the response space of the source area (the responses of the first n neurons or principal components, for instance), and orange and blue surfaces that represent two subspaces for the private or shared fluctuations in neural activity respectively. The two rows of icons represent the attended and unattended conditions (when attention was directed toward or away from the receptive fields of the recorded neurons), and each column describes the expected result of each of the following hypothesis. (left) Attention could alter the dimensionality of the private, shared, or both subspaces. If attention only modified local representations, then the number of private dimensions that explain the local neural fluctuations would change. (middle) Alternatively, attention could modulate information flow by enhancing or diminishing the extent to which neural activity in a target population tracks the neural activity of its source. If attention acted via this mechanism locally, then prediction would improve in private dimensions. (right) If attention modulated functional communication by modulating information flow across areas, then prediction would improve in shared dimensions.