It also enabled us to make direct comparisons between our results from area 5d and earlier data from PRR and PMd (Pesaran et al., 2006, 2010). The data were aligned at movement onset (0 ms) and

the delay period was defined as −500 to −100 ms. For each neuron, mean firing rates during the delay period were converted into twelve firing rate response matrices, four for each of the three possible combinations of variables (TH, TG, HG; see Figure S1 available online). For example, a single 4-by-4 target-hand (TH) matrix represents the firing rates for all 16 different arrangements of target location and starting hand position, but with gaze position constant at, say, −20 degrees in all trials. The other three TH matrices have the same target and hand structure, but TSA HDAC in vivo are composed of trials in which gaze was located at −10, 0, or 10 degrees, respectively. Each element within a matrix therefore Adriamycin purchase represents the mean firing rate for a single trial type. The TG matrices, in which H was held constant, and the HG matrices, in which T was held constant, were formed similarly. The main analysis was conducted on the subset of matrices in which the third variable was held constant at the response field peak (e.g.,

gaze at −10 degrees for a TH matrix). This results in a set of three matrices per neuron, one for each variable pair (see Figure 3B and Figure S1). Figures 2A and 2B (left panels) illustrate how a matrix would appear for an idealized cell with a purely gain field relationship between a given pair of variables (T and H in this example). The peak of the

tuning curve for T remains located at the same extrinsic position (−10 degrees) for all values of H, with the effect of H being to scale the magnitude of the response. In other words, changes in H and T produce multiplicatively separable changes in the response of the cell. Etomidate Figure 2C shows the quite distinct “diagonal” pattern for an idealized cell that codes the extrinsic reach vector T-H: the peak of the tuning curve for T shifts as H is varied. The influence of the two variables cannot be separated from each other in this hand-centered reference frame for target position. Such a vector relationship need not involve full shifts (Figure 2D). Furthermore, cells may simultaneously represent both a vector and a postural gain field (Figure 2E). A population of cells of this type could contain a distributed code for the location of the target in head/body-centered space (Andersen et al., 1990; Zipser and Andersen, 1988). We used singular value decomposition (SVD) to determine whether each variable-pair matrix was separable or inseparable, and hence whether the defining relationship between a pair of variables for a cell was better described as a gain field or as a vector (Peña and Konishi, 2001; Pesaran et al.