Internal and external influences on the rate of sensory evidence accumulation in the human brain

Abstract

We frequently need to make timely decisions based on sensory evidence that is weak, ambiguous, or noisy resulting from conditions in the external environment (e.g., a cluttered visual scene) or within the brain itself (e.g., inattention, neural noise). Here we examine how externally and internally driven variations in the quality of sensory evidence affect the build-to-threshold dynamics of a supramodal "decision variable" signal and, hence, the timing and accuracy of decision reports in humans. Observers performed a continuous-monitoring version of the prototypical two-alternative dot-motion discrimination task, which is known to strongly benefit from sequential sampling and temporal accumulation of evidence. A centroparietal positive potential (CPP), which we previously established as a supramodal decision signal based on its invariance to motor or sensory parameters, exhibited two key identifying properties associated with the "decision variable" long described in sequential sampling models: (1) its buildup rate systematically scaled with sensory evidence strength across four levels of motion coherence, consistent with temporal integration; and (2) its amplitude reached a stereotyped level at the moment of perceptual report executions, consistent with a boundary-crossing stopping criterion. The buildup rate of the CPP also strongly predicted reaction time within coherence levels (i.e., independent of physical evidence strength), and this endogenous variation was linked with attentional fluctuations indexed by the level of parieto-occipital α-band activity preceding target onset. In tandem with the CPP, build-to-threshold dynamics were also observed in an effector-selective motor preparation signal; however, the buildup of this motor-specific process significantly lagged that of the supramodal process.

Figure 1.

Integration-to-threshold dynamics during motion discrimination in the human brain. A, Schematic of the continuous RDM task. Participants monitored a centrally presented dot kinetogram for step transitions from random to coherent motion. B, RT (left) and miss rate (right) decreased as a function of coherence across the 13 subjects. Error bars indicate SEM. C, CPP waveforms aligned to stimulus onset (left) and response execution (middle) and signal scalp topography (right, color bar represents signal amplitude). D, LRP waveforms aligned to stimulus onset (left) and response execution (middle) measured as the contralateral minus ipsilateral potential difference over frontocentral sites, and the scalp topography of the difference between left motion and right motion trials at the time of response execution (right). Both signals exhibit a gradual buildup whose rate is proportional to the strength of coherent motion and which terminates at a stereotyped potential. Markers running along the bottom of plot C and D indicate the center of 100 ms time windows in which a linear contrast of signal slope as a function of coherence reached significance (one-tailed based on prediction of faster signal buildup with increasing coherence, p < 0.05), and arrows indicate the point at which each signal reaches half of its peak voltage (averaging across coherences), highlighting that the evidence-dependent buildup of the supramodal CPP precedes that of the effector-selective LRP.

Figure 2.

Internal influences on decision speed. A, For each participant, single trials within each coherence level were sorted as a function of RT and divided into equal-sized fast and slow bins based on a median split. Faster RTs were preceded by decreased activity in the 8–13 Hz α band over parieto-occipital electrodes (left). CPP waveforms aligned to stimulus onset (middle) and response (right) show that faster buildup rates led to faster RTs. Markers running along the bottom of each plot indicate the center of 100 ms time windows in which signal buildup rate significantly differed as a function of RT (one-tailed based on prediction of faster RTs with increasing buildup rate, p < 0.05). B, Within each coherence level, single trials were pooled across subjects and sorted as a function of RT and divided into six equal-sized bins. Trials in the corresponding bins were then averaged across coherence levels for the plots in this figure. In keeping with the results of the within-subject analysis in A, faster RTs were preceded by decreased activity in the 8–13 Hz α band over parieto-occipital electrodes (see topography inset). Again, RT clearly decreases with CPP buildup rate.

Figure 3.

Variability in timing of perceptual reports explained by trial-to-trial changes in decision signal buildup rate. A, Faster CPP buildup rates were preceded by decreased activity in the 8–13 Hz α band over parieto-occipital electrodes. B, Faster CPP buildup rates were followed by faster RTs.

Figure 4.

A distinct slow negative potential over frontocentral scalp. A, Without applying a CSD transformation, the peak amplitude of the CPP appeared to increase as a function of coherence. This scatter plot of centroparietal amplitude at RT against RT itself indicates that this arises from a trend of decreasing amplitude with RT, not with coherence. Colored lines indicate the linear fit for the relationship between RT and amplitude at each coherence level, which appear colinear. B, Topography of the mean difference in CPP amplitude across consecutive pairs of coherence levels, revealing that the decrease in amplitude with RT is driven by a distinct negative-going frontocentral scalp potential, which spatially spreads to centroparietal electrodes in the absence of CSD transformation.