Striatum and pre-SMA facilitate decision-making under time pressure

Abstract

Human decision-making almost always takes place under time pressure. When people are engaged in activities such as shopping, driving, or playing chess, they have to continually balance the demands for fast decisions against the demands for accurate decisions. In the cognitive sciences, this balance is thought to be modulated by a response threshold, the neural substrate of which is currently subject to speculation. In a speed decision-making experiment, we presented participants with cues that indicated different requirements for response speed. Application of a mathematical model for the behavioral data confirmed that cueing for speed lowered the response threshold. Functional neuroimaging showed that cueing for speed activates the striatum and the pre-supplementary motor area (pre-SMA), brain structures that are part of a closed-loop motor circuit involved in the preparation of voluntary action plans. Moreover, activation in the striatum is known to release the motor system from global inhibition, thereby facilitating faster but possibly premature actions. Finally, the data show that individual variation in the activation of striatum and pre-SMA is selectively associated with individual variation in the amplitude of the adjustments in the response threshold estimated by the mathematical model. These results demonstrate that when people have to make decisions under time pressure their striatum and pre-SMA show increased levels of activation.basal ganglia ͉ fMRI ͉ linear ballistic accumulator model ͉ speed-accuracy tradeoff W hether buying new shoes, participating in traffic, playing chess, or shooting basketball, one invariably faces the dilemma of when to stop deliberating and make a decision. In many situations, it is maladaptive to ponder over alternative courses of action for a very long time. In basketball, for instance, one has to shoot the ball before a defender can block the shot. However, decisions taken without sufficient thought may lead to poor results; a shot that is taken too hastily may not go in.The foregoing example shows that decision-making involves a delicate balance between the competing demands of response speed and choice accuracy, a balance that is usually referred to as the speed-accuracy tradeoff (1). In the cognitive sciences, this tradeoff is thought to be modulated by a response threshold that determines the amount of diagnostic information that is required to make a decision and initiate an action (2, 3). Because the accumulation of diagnostic information takes time, high response thresholds lead to accurate, yet slow, decisions, and low response thresholds lead to fast yet error-prone decisions.The behavioral consequences of the speed-accuracy tradeoff are both profound and predictable, and the tradeoff therefore constitutes one of the most important benchmark findings for formal models of decision-making (4, 5). In light of its ubiquity and impact, it is surprising that relatively little is known about the neural underpinnings of the speed-accuracy tradeoff (but see refs. 6 and 7...

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration

“…This shift to striatum-mediated learning has also been found when participants performed the weather prediction task under cognitive load (Foerde et al, 2006). In studies of the speed-accuracy tradeoff, increased activation was found in the striatum during trials with speed emphasis compared to trials with accuracy emphasis (Forstmann et al, 2008;van Veen et al, 2008), suggesting that enhanced striatal activity may be critical in reducing inhibitory control and facilitating speeded responses (Bogacz et al, 2010). Here, we significantly expand these findings by directly demonstrating that increased time pressure decreases the involvement of frontal and parietal regions and shifts probabilistic multi-cue decision-making to the striatum, even after the completion of initial cue learning.…”

“…Specifically, learning the weather prediction task under stress induced by the cold pressor test has been associated with increased use of implicit, striatum-mediated strategies (Schwabe and Wolf, 2012). Similarly, time pressure on perceptual decision-making has been associated with a deterioration in information processing in early sensory areas (Ho et al, 2012) and increased activity in the striatum (Bogacz et al, 2010;Forstmann et al, 2008), indicating that the striatum may promote faster but possibly premature or sub-optimal decisions.…”

The acute brain response to levodopa heralds dyskinesias in Parkinson disease

“…The connectivity of this region to motor regions is abnormal in PD38 and modulated by dopamine 39. Furthermore, preSMA is involved in decreasing motor threshold during the speed–accuracy tradeoff 40. The observed overactivity of preSMA might therefore constitute an aberrant striatal feedback signal that causes an abnormal induction of internally generated movements and hereby contributes to the emergence of dyskinesias.…”

Time pressure affects the efficiency of perceptual processing in decisions under conflict

“…This speed-accuracy tradeoff can be straightforwardly implemented in sequential sampling models, which not only account for performance in a wide range of perceptual tasks (Brown & Heathcote, 2005;Ratcliff & McKoon, 2008) but can also be plausibly linked to neurophysiological correlates of decision making (Bogacz, Wagenmakers, Forstmann, & Nieuwenhuis, 2010;Forstmann et al, 2008Forstmann et al, , 2010Forstmann et al, , 2011Ho et al, 2012;Ivanoff, Branning, & Marois, 2008;Philiastides, Ratcliff, & Sajda, 2006;van Veen, Krug, & Carter, 2008). In general, decision making in sequential sampling models is based on the accumulation of evidence over time until a boundary (or criterion) is reached and an associated response is initiated (Brown & Heathcote, 2005Busemeyer & Townsend, 1993;Diederich & Busemeyer, 2006;Hübner, Steinhauser, & Lehle, 2010;Ratcliff & Smith, 2004;Ratcliff, 1978;Usher & McClelland, 2001;White, Ratcliff, & Starns, 2011).…”