Dynamics of Neural Population Responses in Prefrontal Cortex Indicate Changes of Mind on Single Trials

Abstract

Summary Decision-making is a complex process in which different sources of information are combined into a decision variable (DV) that guides action [1, 2]. Neurophysiological studies have typically sought insight into the dynamics of the decision-making process and its neural mechanisms through statistical analysis of large numbers of trials from sequentially recorded single neurons or small groups of neurons [3-6]. However, detecting and analyzing the DV on individual trials has been challenging [7]. Here we show that by recording simultaneously from hundreds of units in pre-arcuate gyrus of macaque monkeys performing a direction discrimination task, we can predict the monkey’s choices with high accuracy and decode DV dynamically as the decision unfolds on individual trials. This advance enabled us to study changes-of-mind (CoM’s) that occasionally happen before the final commitment to a decision [8-10]. On individual trials, the decoded DV varied significantly over time and occasionally changed its sign, identifying a potential CoM. Interrogating the system by random stopping of the decision-making process during the delay period after stimulus presentation confirmed the validity of identified CoM’s. Importantly, the properties of the candidate CoM’s also conformed to expectations based on prior theoretical and behavioral studies [8]: they were more likely to go from an incorrect to a correct choice; they were more likely for weak and intermediate stimuli than for strong stimuli; and they were more likely earlier in the trial. We suggest that simultaneous recording of large neural populations provides a good estimate of DV and explains idiosyncratic aspects of the decision-making process that were inaccessible before.

Choice Certainty Is Informed by Both Evidence and Decision Time

“…Further, we expect that a serial report of choice and confidence would significantly reduce the utility of error trials for inferring the mechanism of confidence (Fig. 4) simply because subjects could use the period between the choice and confidence report to recalibrate their confidence or even change their minds (Caspi et al, 2004; Kiani et al, 2014; Resulaj et al, 2009). For example, serial reporting of choice and certainty might weaken or even reverse the trend in Figure 4.…”

Decisions reduce sensitivity to subsequent information

“…While a decision-induced gain-reduction may appear disadvantageous for situations in which the decision is reversible, some degree of inertia on decisions may help to reduce indecisiveness that could lead to multiple changes of mind when faced with ambiguous evidence and to avoid time wasting [42,43]. Recent work within the framework of embodied decisions have shown that decision models in which the motor action has a stabilizing feedback input into the decision process can improve task performance, when the cost of action-changes are factored in [51].…”

Reach target selection in humans using ambiguous decision cues containing variable amounts of conflicting sensory evidence supporting each target choice

“…The changes of reach direction are an overt physical expression of that vacillation, which might also occur during evidence accumulation without crossing one or the other decision bounds for the two reach options. Evidence of covert subthreshold mental vacillations has been reported in neurophysiological studies Kiani et al 2014). The models can only explain such events on the basis of the parameters available to them, and so might erroneously attribute any tendency of these mental vacillations to prolong RTs to an increase in the duration and variability of the non-decision time and changes in other parameters, rather than to transient fluctuations in the evidence accumulation process itself.…”