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...

There is growing evidence that a specific region in the posterior frontolateral cortex is involved intimately in cognitive control processes. This region, located in the vicinity of the junction of the inferior frontal sulcus and the inferior precentral sulcus, was termed the inferior frontal junction (IFJ). The IFJ was shown to be involved in the updating of task representations and to be activated commonly in a within-subject investigation of a task-switching paradigm, the Stroop task, and a verbal n-back task. Here, we investigate the involvement of the IFJ in cognitive control by employing a meta-analytic approach. Two quantitative meta-analyses of functional magnetic resonance imaging (fMRI) studies were conducted. One meta-analysis included frontal activations from task-switching, set-shifting, and stimulus-response (S-R) reversal studies, the other included frontal activations from color-word Stroop studies. Results showed highly significant clustering of activations in the IFJ in both analyses. These results provide strong evidence for the consistent involvement of the IFJ in both switching and Stroop paradigms. Furthermore, they support our concept of areal specialization in the frontolateral cortex, which posits that it is not only the middorsolateral part that plays an important role in cognitive control, but also the IFJ. Finally, our results demonstrate how quantitative meta-analyses can be used to test hypotheses about the involvement of specific brain regions in cognitive control.

Language processing in context requires more than merely comprehending words and sentences. Important subprocesses are inferences for bridging successive utterances, the use of background knowledge and discourse context, and pragmatic interpretations. The functional neuroanatomy of these text comprehension processes has only recently been investigated. Although there is evidence for right-hemisphere contributions, reviews have implicated the left lateral prefrontal cortex, left temporal regions beyond Wernicke's area, and the left dorso-medial prefrontal cortex (dmPFC) for text comprehension. To objectively confirm this extended language network and to evaluate the respective contribution of right hemisphere regions, meta-analyses of 23 neuroimaging studies are reported here. The analyses used replicator dynamics based on activation likelihood estimates. Independent of the baseline, the anterior temporal lobes (aTL) were active bilaterally. In addition, processing of coherent compared with incoherent text engaged the dmPFC and the posterior cingulate cortex. Right hemisphere activations were seen most notably in the analysis of contrasts testing specific subprocesses, such as metaphor comprehension. These results suggest task dependent contributions for the lateral PFC and the right hemisphere. Most importantly, they confirm the role of the aTL and the fronto-medial cortex for language processing in context.

The role of dopamine in monitoring negative action outcomes and feedback-based learning was tested in a neuroimaging study in humans grouped according to the dopamine D2 receptor gene polymorphism DRD2-TAQ-IA. In a probabilistic learning task, A1-allele carriers with reduced dopamine D2 receptor densities learned to avoid actions with negative consequences less efficiently. Their posterior medial frontal cortex (pMFC), involved in feedback monitoring, responded less to negative feedback than others' did. Dynamically changing interactions between pMFC and hippocampus found to underlie feedback-based learning were reduced in A1-allele carriers. This demonstrates that learning from errors requires dopaminergic signaling. Dopamine D2 receptor reduction seems to decrease sensitivity to negative action consequences, which may explain an increased risk of developing addictive behaviors in A1-allele carriers.

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When people make decisions they often face opposing demands for response speed and response accuracy, a process likely mediated by response thresholds. According to the striatal hypothesis, people decrease response thresholds by increasing activation from cortex to striatum, releasing the brain from inhibition. According to the STN hypothesis, people decrease response thresholds by decreasing activation from cortex to subthalamic nucleus (STN); a decrease in STN activity is likewise thought to release the brain from inhibition and result in responses that are fast but error-prone. To test these hypotheses-both of which may be true-we conducted two experiments on perceptual decision making in which we used cues to vary the demands for speed vs. accuracy. In both experiments, behavioral data and mathematical model analyses confirmed that instruction from the cue selectively affected the setting of response thresholds. In the first experiment we used ultra-high-resolution 7T structural MRI to locate the STN precisely. We then used 3T structural MRI and probabilistic tractography to quantify the connectivity between the relevant brain areas. The results showed that participants who flexibly change response thresholds (as quantified by the mathematical model) have strong structural connections between presupplementary motor area and striatum. This result was confirmed in an independent second experiment. In general, these findings show that individual differences in elementary cognitive tasks are partly driven by structural differences in brain connectivity. Specifically, these findings support a cortico-striatal control account of how the brain implements adaptive switches between cautious and risky behavior.basal ganglia | response time model | speed-accuracy tradeoff | structural connectivity | subthalamic nucleus F or many everyday life decisions, people and animals face the dilemma that fast decisions tend to be error-prone, whereas accurate decisions tend to be relatively slow. In other words, the temporal benefits of responding quickly come at a cost of increased error rates, a phenomenon known as the speed-accuracy tradeoff (SAT) (1-6).Even though the SAT is ubiquitous in many areas of decision making, relatively little is known about its neurobiological underpinnings. Currently available empirical data (2, 7, 8) and neurocomputational models both suggest several brain mechanisms that could be responsible for how people switch from cautious behavior that is accurate but slow to risky behavior that is fast but errorprone (1). The work presented here is relevant for two hypotheses about how the brain controls the SAT (Fig. 1). First, the striatal hypothesis posits that an emphasis on speed promotes excitatory input from cortex to striatum; the increased baseline activation of the striatum acts to decrease the inhibitory control that the output nuclei of the basal ganglia exert over the brain, thereby facilitating faster but possibly premature responses (2). Second, the STN hypothesis posits that an emphasis on ...

Alzheimer's disease is the most common form of dementia. Its prodromal stage amnestic mild cognitive impairment is characterized by deficits of anterograde episodic memory. The development of standardized imaging inclusion criteria has to be regarded as a prerequisite for future diagnostic systems. Moreover, successful treatment requires isolating imaging markers predicting the disease. Accordingly, we conducted a systematic and quantitative meta-analysis to reveal the prototypical neural correlates of Alzheimer's disease and its prodromal stage. To prevent any a priori assumptions and enable a data-driven approach only studies applying quantitative automated whole brain analysis were included. Finally, 40 studies were identified involving 1,351 patients and 1,097 healthy control subjects reporting either atrophy or decreases in glucose utilization and perfusion. The currently most sophisticated and best-validated of coordinate-based voxel-wise meta-analyses was applied (anatomical likelihood estimates). The meta-analysis reveals that early Alzheimer's disease affects structurally the (trans-)entorhinal and hippocampal region, functionally the inferior parietal lobules and precuneus. Results further may suggest that atrophy in the (trans-)entorhinal area/hippocampus and hypometabolism/hypoperfusion in the inferior parietal lobules predict most reliably the progression from amnestic mild cognitive impairment to Alzheimer's disease, whereas changes in the posterior cingulate cortex and precuneus are unspecific. Fully developed Alzheimer's disease involved additionally a frontomedian-thalamic network. In conclusion, the meta-analysis characterizes the prototypical neural substrates of Alzheimer's disease and its prodromal stage amnestic mild cognitive impairment. By isolating predictive markers it enables successful treatment strategies in the future and contributes to standardized imaging inclusion criteria for Alzheimer's disease as suggested for future diagnostic systems.

The Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994) is often used to assess decision-making deficits in clinical populations. The interpretation of the results hinges on 3 key assumptions: (a) healthy participants learn to prefer the good options over the bad options; (b) healthy participants show homogeneous choice behavior; and (c) healthy participants first explore the different options and then exploit the most profitable ones. Here we test these assumptions using 2 extensive literature reviews and analysis of 8 data sets. The results show that all 3 assumptions may be invalid; that is, (a) healthy participants often prefer decks with infrequent losses; (b) healthy participants show idiosyncratic choice behavior; and (c) healthy participants do not show a systematic decrease in the number of switches across trials. Our findings question the prevailing interpretation of IGT data and suggest that, in future applications of the IGT, key assumptions about performance of healthy participants warrant close scrutiny.