Microstimulation of macaque area LIP affects decision-making in a motion discrimination task

Abstract

A central goal of cognitive neuroscience is to elucidate the neural mechanisms underlying decision-making. Recent physiological studies suggest that neurons in association areas may be involved in this process. To test this, we measured the effects of electrical microstimulation in the lateral intraparietal area (LIP) while monkeys performed a reaction-time motion discrimination task with a saccadic response. In each experiment, we identified a cluster of LIP cells with overlapping response fields (RFs) and sustained activity during memory-guided saccades. Microstimulation of this cluster caused an increase in the proportion of choices toward the RF of the stimulated neurons. Choices toward the stimulated RF were faster with microstimulation, while choices in the opposite direction were slower. Microstimulation never directly evoked saccades, nor did it change reaction times in a simple saccade task. These results demonstrate that the discharge of LIP neurons is causally related to decision formation in the discrimination task.

Fig. 1

Experimental Design. A recording/stimulating microelectrode was advanced into the ventral portion of area LIP to identify a cluster of neurons with similar RFs. The monkey performed a direction discrimination task with several levels of task difficulty randomly interleaved. The monkey could respond at any time after onset of the random dot motion and it indicated its decision with a saccadic eye movement. One of the two choice targets was placed in the RF of the LIP neurons. We applied microstimulation as shown from the onset of the motion stimulus until the initiation of the saccade on a random half of the trials.

Fig. 2

Microstimulation in LIP affects both decisions and reaction times. (a, b) Effect of motion strength and LIP microstimulation on monkeys’ choices. The probability of a T_in choice is plotted as a function of motion strength. Positive and negative motion strengths correspond to motion toward T_in and T_out, respectively. The sigmoid curves are fit using equation 1, which characterizes the microstimulation effect as a horizontal shift of the psychometric function. Data are pooled from 12 stimulation sites in monkey B and 12 sites in monkey S. (c, d) Effect of motion strength and LIP microstimulation on reaction time. Average RTs (± SEM) are plotted as a function of motion strength for all correct trials. The lines are fit using equation 2 (Methods). Data are not shown for the highest motion strength (± 51.2% coh) because the effects are similar to those seen at the next highest motion strength (± 25.6% coh).

Fig. 3

Effects of LIP microstimulation are evident during individual experiments. (a) Effect of microstimulation on choices at different electrode sites for two monkeys. The equivalent motion strength, calculated using equation 1, is the horizontal shift in the psychometric function with microstimulation at each site. (b) Effect of microstimulation on T_in RTs at different electrode sites for two monkeys. The equivalent motion strength is calculated using equation 2a. (c) Effect of microstimulation on T_out RTs at different electrode sites for two monkeys. The equivalent motion strength is calculated using equation 2b.

Fig. 4

Microstimulation in MT and LIP have different effects on decisions and RTs. Each point represents the effect of microstimulation on choices and RTs in one experiment. This is characterized by the equivalent motion strength that would have been needed to produce the observed choice bias or RT shift (equations 1 and 2; α₂ and α₅ constrained to be equal). Open symbols show LIP stimulation sites (○, monkey B;□, monkey S), and filled symbols show MT stimulation sites (black, monkey B; gray, monkey N). Error bars show the standard error of the parameter estimates (see Methods). The line is fit to the MT sites (weighted type II regression50). All LIP sites lie above this line, indicating that LIP stimulation has larger effects than MT stimulation on RT for a given effect on choices. One MT data point from monkey N lies outside the boundaries of this figure at (62, 60). The gray box highlights all sites in LIP and those in MT with similarly sized RT effects.

Fig. 5

Microstimulation of LIP and MT affect the decision process at different points. (a) Diffusion-to-bound model of the decision process. Momentary evidence in favor of the T_in direction and against the T_out direction is accumulated as a function of time. The accumulation is termed the decision variable. The process terminates with a T_in or T_out choice when the decision variable reaches the upper or lower bound, respectively, at +A or −B. The momentary evidence is distributed as a unit-variance Gaussian whose mean, μ, is proportional to motion strength. On a single trial, the decision variable follows a random “diffusion” path, like the one shown. Both decision time and the proportion of T_in choices are governed by A, B, and μ. (b) Diffusion model fit to psychometric and chronometric functions for monkey B with and without LIP microstimulation. Data are the same as in Figs. 2a and c. LIP stimulation mainly affects the decision process by adding a constant to the decision variable. The faster RTs associated with T_in choices are explained by less nondecision time for leftward choices, which was always the direction of T_in for this monkey. (A = 13.4, k = 0.0056, T_out nondecision time = 511 ms, T_in nondecision time = 465 ms). (c) Diffusion model fit to psychometric and chronometric functions for monkey B with and without MT microstimulation. Data are from a previously published experiment using this monkey. Although the average effects on RT were similar for MT and LIP stimulation, MT stimulation caused a stronger choice bias: 13.1% more choices in favor of the preferred direction of the stimulated neurons compared to 3.5% more T_in choices with LIP stimulation. MT stimulation mainly affects the decision process by adding to the momentary evidence. Less nondecision time for leftward choices was also frequently present in individual MT experiments, but it is not apparent in the averages because the preferred direction of individual MT sites corresponded to different saccade directions. (A = 16.7, k = 0.0023, Null nondecision time = 398 ms, Pref nondecision time = 372 ms).

Fig. 6

Predicted magnitude of LIP microstimulation effects on choice and RT. Predicted psychometric and chronometric functions for the two monkeys. Microstimulation was assumed to change the spike rates of LIP neurons that represent the decision variable by 5 sp/s. The size of the change was estimated by analyzing MT microstimulation experiments in monkey B. It is the change in firing rates of MT neurons that would be required to produce the observed effects on choice and RT, equivalent to a change in motion strength of 10% coh. See text for details. The data points are the same as Fig. 2. Dashed and solid lines are predictions for non-stimulated and stimulated conditions, respectively. (a) Predictions for monkey B. Solid curve shows the diffusion model fit to the non-stimulation trials (A = 13.4, k = 0.0056, T_out nondecision time = 511 ms, T_in nondecision time = 465 ms). Dashed curve shows predicted change in the choices and RTs if the decision variable were offset by 2.48 units (18.5%) toward A. (b) Predictions for monkey S. Same conventions as in a (model fit to non-stimulation trials: A = 23.6, k = 0.0032, T_out nondecision time = 385 ms, T_in nondecision time = 385 ms). The prediction is based on the same offset of 2.48 units toward A, which constitutes a smaller fraction of the bound height for this monkey (10.5%).