Background We assessed whether evidence accumulation could be observed in the BOLD signal during perceptual decision making. This presents a challenge since the hemodynamic response is slow, while perceptual decisions are typically fast. New method Guided by theoretical predictions of the drift diffusion model, we slowed down decisions by penalizing participants for incorrect responses. Second, we distinguished BOLD activity related to stimulus detection (modeled using a boxcar) from activity related to integration (modeled using a ramp) by minimizing the collinearity of GLM regressors. This was achieved by dissecting a boxcar into its two most orthogonal components: an “up-ramp” and a “down-ramp.” Third, we used a control condition in which stimuli and responses were similar to the experimental condition, but that did not engage evidence accumulation of the stimuli. Results The results revealed an absence of areas in parietal cortex that have been proposed to drive perceptual decision making but have recently come into question; and newly identified regions that are candidates for involvement in evidence accumulation. Comparison with existing methods Previous fMRI studies have either used fast perceptual decision making, which precludes the measurement of evidence accumulation, or slowed down responses by gradually revealing stimuli. The latter approach confounds perceptual detection with evidence accumulation because accumulation is constrained by perceptual input. Conclusions We slowed down the decision making process itself while leaving perceptual information intact. This provided a more sensitive and selective observation of brain regions associated with the evidence accumulation processes underlying perceptual decision making than previous methods.

Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.

Many perceptual decision making models posit that participants accumulate noisy evidence over time to improve the accuracy of their decisions, and that in free response tasks, participants respond when the accumulated evidence reaches a decision threshold. Research on the neural correlates of these models components focuses primarily on evidence accumulation. Far less attention has been paid to the neural correlates of decision thresholds, reflecting the final commitment to a decision. Inspired by a model of bistable neural activity that implements a decision threshold, we reinterpret human lateralized readiness potentials (LRPs) as reflecting the crossing of a decision threshold. Interestingly, this threshold crossing preserves signatures of a drift-diffusion process of evidence accumulation that feeds in to the threshold mechanism. We show that, as our model predicts, LRP amplitudes and growth rates recorded while participants performed a motion discrimination task correlate with individual differences in behaviorally-estimated prior beliefs, decision thresholds and evidence accumulation rates. As such LRPs provide a useful measure to test dynamical models of both evidence accumulation and decision commitment processes non-invasively.

We examined whether older adults differ from younger adults in how they learn from rewarding and aversive outcomes. Human participants were asked to either learn to choose actions that lead to monetary reward or learn to avoid actions that lead to monetary losses. To examine age differences in the neurophysiological mechanisms of learning, we applied a combination of computational modeling and fMRI. Behavioral results showed age-related impairments in learning from reward but not in learning from monetary losses. Consistent with these results, we observed age-related reductions in BOLD activity during learning from reward in the ventromedial PFC. Furthermore, the model-based fMRI analysis revealed a reduced responsivity of the ventral striatum to reward prediction errors during learning in older than younger adults. This age-related reduction in striatal sensitivity to reward prediction errors may result from a decline in phasic dopaminergic learning signals in the elderly.

Multivariate pattern analysis (MVPA) is a relatively recent innovation in functional magnetic resonance imaging (fMRI) methods. MVPA is increasingly widely used, as it is apparently more effective than classical general linear model analysis (GLMA) for detecting response patterns or representations that are distributed at a fine spatial scale. However, we demonstrate that widely used approaches to MVPA can systematically admit certain confounds that are appropriately eliminated by GLMA. Thus confounds rather than distributed representations may explain some cases in which MVPA produced positive results but GLMA did not. The issue is that it is common practice in MVPA to conduct group tests on single-subject summary statistics that discard the sign or direction of underlying effects, whereas GLMA group tests are conducted directly on single-subject effects themselves. We describe how this common MVPA practice undermines standard experiment design logic that is intended to control at the group level for certain types of confounds, such as time on task and individual differences. Furthermore, we note that a simple application of linear regression can restore experimental control when using MVPA in many situations. Finally, we present a case study with novel fMRI data in the domain of rule representations, or flexible stimulus–response mappings, which has seen several recent MVPA publications. In our new dataset, as with recent reports, standard MVPA appears to reveal rule representations in prefrontal cortex regions, whereas GLMA produces null results. However, controlling for a variable that is confounded with rule at the individual-subject level but not the group level (reaction time differences across rules) eliminates the MVPA results. This raises the question of whether recently reported results truly reflect rule representations, or rather the effects of confounds such as reaction time, difficulty, or other variables of no interest.

We examined whether older adults differ from younger adults in the degree to which they favor immediate over delayed rewards during decision-making. To examine the neural correlates of age-related differences in delay discounting we acquired functional MR images while participants made decisions between smaller but sooner and larger but later monetary rewards. The behavioral results show age-related reductions in delay discounting. Less impulsive decision-making in older adults was associated with lower ventral striatal activations to immediate reward. Furthermore, older adults showed an overall higher percentage of delayed choices and reduced activity in the dorsal striatum than younger adults. This points to a reduced reward sensitivity of the dorsal striatum in older adults. Taken together, our findings indicate that less impulsive decision-making in older adults is due to a reduced sensitivity of striatal areas to reward. These age-related changes in reward sensitivity may result from transformations in dopaminergic neuromodulation with age.

Recent studies have begun to elucidate the neural correlates of evidence accumulation in perceptual decision making, but few of them have used a combined modeling-electrophysiological approach to studying evidence accumulation. We introduce a multivariate approach to EEG analysis with which we can perform a comprehensive search for the neural correlate of dynamics predicted by accumulator models. We show that the dynamics of evidence accumulation are most strongly correlated with ramping of oscillatory power in the 4–9 Hz theta band over the course of a trial, although it also correlates with oscillatory power in other frequency bands. The rate of power decrease in the theta band correlates with individual differences in the parameters of drift diffusion models fitted to individuals’ behavioral data.

Humans are adept at switching between goal-directed behaviors quickly and effectively. The prefrontal cortex (PFC) is thought to play a critical role by encoding, updating, and maintaining internal representations of task context in working memory. It has also been hypothesized that the encoding of context representations in PFC is regulated by phasic dopamine gating signals. Here we use multimodal methods to test these hypotheses. First we used functional MRI (fMRI) to identify regions of PFC associated with the representation of context in a working memory task. Next we used single-pulse transcranial magnetic stimulation (TMS), guided spatially by our fMRI findings and temporally by previous event-related EEG recordings, to disrupt context encoding while participants performed the same working memory task. We found that TMS pulses to the right dorsolateral PFC (DLPFC) immediately after context presentation, and well in advance of the response, adversely impacted context-dependent relative to context-independent responses. This finding causally implicates right DLPFC function in context encoding. Finally, using the same paradigm, we conducted high-resolution fMRI measurements in brainstem dopaminergic nuclei (ventral tegmental area and substantia nigra) and found phasic responses after presentation of context stimuli relative to other stimuli, consistent with the timing of a gating signal that regulates the encoding of representations in PFC. Furthermore, these responses were positively correlated with behavior, as well as with responses in the same region of right DLPFC targeted in the TMS experiment, lending support to the hypothesis that dopamine phasic signals regulate encoding, and thereby the updating, of context representations in PFC.

In some cases people judge it morally acceptable to sacrifice one person’s life in order to save several other lives, while in other similar cases they make the opposite judgment. Researchers have identified two general factors that may explain this phenomenon at the stimulus level: (1) the agent’s intention (i.e. whether the harmful event is intended as a means or merely foreseen as a side-effect) and (2) whether the agent harms the victim in a manner that is relatively “direct” or “personal”. Here we integrate these two classes of findings. Two experiments examine a novel personalness/directness factor that we call personal force, present when the force that directly impacts the victim is generated by the agent’s muscles (e.g., in pushing). Experiments 1a and b demonstrate the influence of personal force on moral judgment, distinguishing it from physical contact and spatial proximity. Experiments 2a and b demonstrate an interaction between personal force and intention, whereby the effect of personal force depends entirely on intention. These studies also introduce a method for controlling for people’s real-world expectations in decisions involving potentially unrealistic hypothetical dilemmas.

Traditional theories of moral development emphasize the role of controlled cognition in mature moral judgment, while a more recent trend emphasizes intuitive and emotional processes. Here we test a dual-process theory synthesizing these perspectives. More specifically, our theory associates utilitarian moral judgment (approving of harmful actions that maximize good consequences) with controlled cognitive processes and associates non-utilitarian moral judgment with automatic emotional responses. Consistent with this theory, we find that a cognitive load manipulation selectively interferes with utilitarian judgment. This interference effect provides direct evidence for the influence of controlled cognitive processes in moral judgment, and utilitarian moral judgment more specifically.

In an effort to clarify how deductive reasoning is accomplished, an fMRI study was performed to observe the neural substrates of logical reasoning and mathematical calculation. Participants viewed a problem statement and three premises, and then either a conclusion or a mathematical formula. They had to indicate whether the conclusion followed from the premises, or to solve the mathematical formula. Language areas of the brain (Broca s and Wernicke s area) responded as the premises and the conclusion were read, but solution of the problems was then carried out by non-language areas. Regions in right prefrontal cortex and inferior parietal lobe were more active for reasoning than for calculation, whereas regions in left prefrontal cortex and superior parietal lobe were more active for calculation than for reasoning. In reasoning, only those problems calling for a search for counterexamples to conclusions recruited right frontal pole. These results have important implications for understanding how higher cognition, including deduction, is implemented in the brain. Different sorts of thinking recruit separate neural substrates, and logical reasoning goes beyond linguistic regions of the brain.

Decision conflict occurs when people feel uncertain as to which option to choose from a set of similarly attractive (or unattractive) options, with many studies demonstrating that this conflict can lead to suboptimal decision making. In this article, we investigate the neurobiological underpinnings of decision conflict, in particular, the involvement of the anterior cingulate cortex (ACC). Previous studies have implicated the ACC in conflict monitoring during perceptual tasks, but there is considerable controversy as to whether the ACC actually indexes conflict related to choice, or merely conflict related to selection of competing motor responses. In a functional magnetic resonance imaging study, we dissociate the decision and response phases of a decision task, and show that the ACC does indeed index conflict at the decision stage. Furthermore, we show that it does so for a complex decision task, one that requires the integration of beliefs and preferences and not just perceptual judgments.

Cognitive control is required to regulate interactions between brain regions to produce effective, purposeful behavior. We used functional magnetic resonance imaging to investigate the nature of these interactions and the role of prefrontal cortex (PFC) in cognitive control as subjects switched between simple face and word categorization tasks. Face and word stimuli were used because previous research has shown them to activate distinguishable cortical regions, allowing us to measure levels of activity in task-selective brain regions during task switching. We found that activity in brain regions selective for the currently irrelevant task predicted the behavioral cost associated with switching tasks. This finding supports the theory that between-task competition is a critical determinant of behavior. Task switching was also associated with increased activity in a network of regions implicated in cognitive control, including lateral PFC and parietal cortex. Within this network of regions, we observed dissociations between task-selective and general purpose mechanisms. These findings provide support for theories that propose a control hierarchy comprising regions responsible for maintaining task-specific information about rules or goals, and regions involved in the coordination of these goals.

Tasks that engage a theory of mind seem to activate a consistent set of brain areas. In this study, we sought to determine whether two different interactive tasks, both of which involve receiving consequential feedback from social partners that can be used to infer intent, similarly engaged the putative theory of mind neural network. Participants were scanned using fMRI as they played the Ultimatum Game (UG) and the Prisoner s Dilemma Game (PDG) with both alleged human and computer partners who were outside the scanner. We observed a remarkable degree of overlap in brain areas that activated to partner decisions in the two games, including commonly observed theory of mind areas, as well as several brain areas that have not been reported previously and may relate to immersion of participants in real social interactions that have personally meaningful consequences. Although computer partners elicited activation in some of the same areas activated by human partners, most of these activations were stronger for human partners.