The neural systems that mediate human perceptual decision making

Impaired visual decision-making in individuals with amblyopia

This study examined the effects of amblyopia on perceptual decision-making processes to determine the consequences of visual deprivation on the development of higher level cortical networks outside of the visual cortex. A variant of the Eriksen flanker task was used to measure response time and accuracy for decisions made in the presence of response-selection conflict. Performance of adults with amblyopia was compared to that of neurotypical participants of the same age. Additionally, simple and choice reaction time tasks presented in the visual and the auditory modality were used to control for factors such as feature visibility, crowding, and motor execution speed. A selective deficit in response time for visual decisions was found when individuals with amblyopia used either the amblyopic or non-amblyopic (dominant) eye, and this deficit was independent of visual acuity, motor time, and performance accuracy. In trial conditions that provoked response-selection conflict, responses were significantly delayed in amblyopic relative to neurotypical participants and were not subject to standard trial sequence effects. Our results indicate that, beyond the known effects of abnormal visual experience on visual cortex, suboptimal binocular input during a developmental critical period may also impact cortical connections to downstream areas of the brain, including parietal and frontal cortices, that are believed to underlie decision and response-selection processes.

Electrophysiological responses of rat olfactory tubercle neurons to biologically relevant odours

Biologically relevant odours were used to stimulate olfactory tubercle neurons in anaesthetized male rats. Among 120 recorded neurons, 118 showed spontaneous activity (mean firing rate, 15.0 ± 1.4 spikes/s). Ninety-eight neurons were exposed to at least one of the four following odour sources: an empty vial, or a vial containing food pellets (familiar odour), a sample of oestrous rat faeces (conspecific sexual odour), or a sample of male fox faeces (predator odour). The proportion of neurons responding with a change in activity was significantly linked to the odour applied. Repetition of the stimulation with the same odour elicited the same activity change. Between 50 and 70% of neuronal activity changes were not accompanied by respiration changes. Fifty-six neurons were exposed successively to all four odours, and 38 of them showed an activity change in response to at least one. The response of a neuron to an odour was not affected by its response to the previous one, and no neuron responded in the same manner to all odours. Conversely, no odour elicited a unique response in this population of neurons. However, the proportions of excited, inhibited and insensitive neurons depended significantly on the odour applied, suggesting that the recruitment of olfactory tubercle neurons is directly dependent on the biological significance of the odour.

The human likeness dimension of the "uncanny valley hypothesis": behavioral and functional MRI findings

The uncanny valley hypothesis (Mori, 1970) predicts differential experience of negative and positive affect as a function of human likeness. Affective experience of humanlike robots and computer-generated characters (avatars) dominates "uncanny" research, but findings are inconsistent. Importantly, it is unknown how objects are actually perceived along the hypothesis' dimension of human likeness (DOH), defined in terms of human physical similarity. To examine whether the DOH can also be defined in terms of effects of categorical perception (CP), stimuli from morph continua with controlled differences in physical human likeness between avatar and human faces as endpoints were presented. Two behavioral studies found a sharp category boundary along the DOH and enhanced visual discrimination (i.e., CP) of fine-grained differences between pairs of faces at the category boundary. Discrimination was better for face pairs presenting category change in the human-to-avatar than avatar-to-human direction along the DOH. To investigate brain representation of physical change and category change along the DOH, an event-related functional magnetic resonance imaging study used the same stimuli in a pair-repetition priming paradigm. Bilateral mid-fusiform areas and a different right mid-fusiform area were sensitive to physical change within the human and avatar categories, respectively, whereas entirely different regions were sensitive to the human-to-avatar (caudate head, putamen, thalamus, red nucleus) and avatar-to-human (hippocampus, amygdala, mid-insula) direction of category change. These findings show that Mori's DOH definition does not reflect subjective perception of human likeness and suggest that future "uncanny" studies consider CP and the DOH's category structure in guiding experience of non-human objects.

How awareness changes the relative weights of evidence during human decision-making

A combined behavioral and brain imaging study shows how sensory awareness and stimulus visibility can influence the dynamics of decision-making in humans.

Human decisions are based on accumulating evidence over time for different options. Here we ask a simple question: How is the accumulation of evidence affected by the level of awareness of the information? We examined the influence of awareness on decision-making using combined behavioral methods and magneto-encephalography (MEG). Participants were required to make decisions by accumulating evidence over a series of visually presented arrow stimuli whose visibility was modulated by masking. Behavioral results showed that participants could accumulate evidence under both high and low visibility. However, a top-down strategic modulation of the flow of incoming evidence was only present for stimuli with high visibility: once enough evidence had been accrued, participants strategically reduced the impact of new incoming stimuli. Also, decision-making speed and confidence were strongly modulated by the strength of the evidence for high-visible but not low-visible evidence, even though direct priming effects were identical for both types of stimuli. Neural recordings revealed that, while initial perceptual processing was independent of visibility, there was stronger top-down amplification for stimuli with high visibility than low visibility. Furthermore, neural markers of evidence accumulation over occipito-parietal cortex showed a strategic bias only for highly visible sensory information, speeding up processing and reducing neural computations related to the decision process. Our results indicate that the level of awareness of information changes decision-making: while accumulation of evidence already exists under low visibility conditions, high visibility allows evidence to be accumulated up to a higher level, leading to important strategical top-down changes in decision-making. Our results therefore suggest a potential role of awareness in deploying flexible strategies for biasing information acquisition in line with one's expectations and goals.

When making a decision, we gather evidence for the different options and ultimately choose on the basis of the accumulated evidence. A fundamental question is whether and how conscious awareness of the evidence changes this decision-making process. Here, we examined the influence of sensory awareness on decision-making using behavioral studies and magneto-encephalographic recordings in human participants. In our task, participants had to indicate the prevailing direction of five arrows presented on a screen that each pointed either left or right, and in different trials these arrows were either easy to see (high visibility) or difficult to see (low visibility). Behavioral and neural recordings show that evidence accumulation changed from a linear to a non-linear integration strategy with increasing stimulus visibility. In particular, the impact of later evidence was reduced when more evidence had been accrued, but only for highly visible information. By contrast, barely perceptible arrows contributed equally to a decision because participants needed to continue to accumulate evidence in order to make an accurate decision. These results suggest that consciousness may play a role in decision-making by biasing the accumulation of new evidence.

Different roles of the posterior inferior frontal gyrus in Chinese character form judgment differences between literate and illiterate individuals

In the present study, we used event-related functional magnetic resonance imaging (fMRI) to explore the different roles of the posterior inferior frontal gyrus (pIFG) in Chinese character form judgment between literate and illiterate subjects. Using event-related fMRI, 24 healthy right-handed Chinese subjects (12 literates and 12 illiterates) were asked to perform Chinese character and figure form judgment tasks. The blood oxygen level-dependent (BOLD) differences in pIFG were examined with general linear modeling (GLM). We found differences in reaction times and accuracy between subjects as they performed these tasks. These behavioral differences reflect the different cognitive demands of character form judgment for literate and illiterate individuals. The results showed differences in the BOLD response patterns in the pIFG between the two discrimination tasks and the two subject groups. A comparison of the character and figure tasks showed that literate and illiterate subjects had similar BOLD responses in the inferior frontal gyrus. However, differences in behavioral performance suggest that the pIFG plays a different role in Chinese character form judgment for each subject group. In literate subjects, the left pIFG mediated access to phonology in achieving Chinese character form judgment, whereas the right pIFG participated in the processing of the orthography of Chinese characters. In illiterate subjects, the bilateral frontal gyrus participated in the visual-spatial processing of Chinese characters to achieve form judgment.

Relative blindsight arises from a criterion confound in metacontrast masking: implications for theories of consciousness

Relative blindsight is said to occur when different levels of subjective awareness are obtained at equality of objective performance. Using metacontrast masking, Lau and Passingham (2006) reported relative blindsight in normal observers at the shorter of two stimulus-onset asynchronies (SOAs) between target and mask. Experiment 1 replicated the critical asymmetry in subjective awareness at equality of objective performance. We argue that this asymmetry cannot be regarded as evidence for relative blindsight because the observers' responses were based on different attributes of the stimuli (criterion contents) at the two SOAs. With an invariant criterion content (Experiment 2), there was no asymmetry in subjective awareness across the two SOAs even though objective performance was the same. Experiment 3 examined the effect of criterion level on estimates of relative blindsight. Collectively, the present results question whether metacontrast masking is a suitable paradigm for establishing relative blindsight. Implications for theories of consciousness are discussed.

Differential BOLD activity associated with subjective and objective reports during "blindsight" in normal observers

The study of conscious visual perception invariably necessitates some means of report. Report can be either subjective, i.e., an introspective evaluation of conscious experience, or objective, i.e., a forced-choice discrimination regarding different stimulus states. However, the link between report type and fMRI-BOLD signals has remained unknown. Here we used continuous flash suppression to render target images invisible, and observed a long-lasting dissociation between subjective report of visibility and human subjects' forced-choice localization of targets ("blindsight"). Our results show a robust dissociation between brain regions and type of report. We find subjective visibility effects in high-order visual areas even under equal objective performance. No significant BOLD difference was found between correct and incorrect trials in these areas when subjective report was constant. On the other hand, objective performance was linked to the accuracy of multivariate pattern classification mainly in early visual areas. Together, our data support the notion that subjective and objective reports tap cortical signals of different location and amplitude within the visual cortex.

Transformation of stimulus value signals into motor commands during simple choice

Decision-making can be broken down into several component processes: assigning values to stimuli under consideration, selecting an option by comparing those values, and initiating motor responses to obtain the reward. Although much is known about the neural encoding of stimulus values and motor commands, little is known about the mechanisms through which stimulus values are compared, and the resulting decision is transmitted to motor systems. We investigated this process using human fMRI in a task where choices were indicated using the left or right hand. We found evidence consistent with the hypothesis that value signals are computed in the ventral medial prefrontal cortex, they are passed to regions of dorsomedial prefrontal cortex and intraparietal sulcus, implementing a comparison process, and the output of the comparator regions modulates activity in motor cortex to implement the choice. These results describe the network through which stimulus values are transformed into actions during a simple choice task.

The neurocognitive connection between physical activity and eating behaviour

As obesity rates increase worldwide, healthcare providers require methods to instill the lifestyle behaviours necessary for sustainable weight loss. Designing effective weight-loss interventions requires an understanding of how these behaviours are elicited, how they relate to each other and whether they are supported by common neurocognitive mechanisms. This may provide valuable insights to optimize existing interventions and develop novel approaches to weight control. Researchers have begun to investigate the neurocognitive underpinnings of eating behaviour and the impact of physical activity on cognition and the brain. This review attempts to bring these somewhat disparate, yet interrelated lines of literature together in order to examine a hypothesis that eating behaviour and physical activity share a common neurocognitive link. The link pertains to executive functions, which rely on brain circuits located in the prefrontal cortex. These advanced cognitive processes are of limited capacity and undergo relentless strain in the current obesogenic environment. The increased demand on these neurocognitive resources as well as their overuse and/or impairment may facilitate impulses to over-eat, contributing to weight gain and obesity. This impulsive eating drive may be counteracted by physical activity due to its enhancement of neurocognitive resources for executive functions and goal-oriented behaviour. By enhancing the resources that facilitate 'top-down' inhibitory control, increased physical activity may help compensate and suppress the hedonic drive to over-eat. Understanding how physical activity and eating behaviours interact on a neurocognitive level may help to maintain a healthy lifestyle in an obesogenic environment.

The neural encoding of guesses in the human brain

Human perception depends heavily on the quality of sensory information. When objects are hard to see we often believe ourselves to be purely guessing. Here we investigated whether such guesses use brain networks involved in perceptual decision making or independent networks. We used a combination of fMRI and pattern classification to test how visibility affects the signals, which determine choices. We found that decisions regarding clearly visible objects are predicted by signals in sensory brain regions, whereas different regions in parietal cortex became predictive when subjects were shown invisible objects and believed themselves to be purely guessing. This parietal network was highly overlapping with regions, which have previously been shown to encode free decisions. Thus, the brain might use a dedicated network for determining choices when insufficient sensory information is available.

Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

How do we make decisions when confronted with several alternatives (e.g., on a supermarket shelf)? Previous work has shown that accumulator models, such as the drift-diffusion model, can provide accurate descriptions of the psychometric data for binary value-based choices, and that the choice process is guided by visual attention. However, the computational processes used to make choices in more complicated situations involving three or more options are unknown. We propose a model of trinary value-based choice that generalizes what is known about binary choice, and test it using an eye-tracking experiment. We find that the model provides a quantitatively accurate description of the relationship between choice, reaction time, and visual fixation data using the same parameters that were estimated in previous work on binary choice. Our findings suggest that the brain uses similar computational processes to make binary and trinary choices.

Prior expectation modulates the interaction between sensory and prefrontal regions in the human brain

How do expectations about the identity of a forthcoming visual stimulus influence the neural mechanisms of perceptual decision making in the human brain? Previous investigations into this issue have mostly involved changing the subjects' attentional focus or the behavioral relevance of certain targets but rarely manipulated subjects' prior expectation about the likely identity of the stimulus. Also, because perceptual decisions were often paired with specific motor responses, it has been difficult to dissociate neural activity that reflects perceptual decisions from motor preparatory activity. Here we designed a task in which we induced prior expectations about the direction of a moving-dot pattern and withheld the stimulus-response mapping until the subjects were prompted to respond. In line with current models of perceptual decision making, we found that subjects' performance was influenced by their expectation about upcoming motion direction. The integration of such information into the decision process was reflected by heightened activity in the dorsolateral prefrontal cortex. Activity in this area reflected the degree to which subjects adjusted their decisions based on the prior expectation cue. Furthermore, there was increased effective connectivity between sensory regions (motion-sensitive medial temporal area MT+) and dorsolateral prefrontal cortex when subjects had a prior expectation about the upcoming motion direction. Dynamic causal modeling suggested that stimulus expectation modulated both the feedforward and feedback connectivity between MT+ and prefrontal cortex. These results provide a mechanism of how prior expectations may affect perceptual decision making, namely by changing neural activity in, and sensory drive to, prefrontal areas.

Neural decoding of collective wisdom with multi-brain computing

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states.

Perceptual learning and decision-making in human medial frontal cortex

The dominant view that perceptual learning is accompanied by changes in early sensory representations has recently been challenged. Here we tested the idea that perceptual learning can be accounted for by reinforcement learning involving changes in higher decision-making areas. We trained subjects on an orientation discrimination task involving feedback over 4 days, acquiring fMRI data on the first and last day. Behavioral improvements were well explained by a reinforcement learning model in which learning leads to enhanced readout of sensory information, thereby establishing noise-robust representations of decision variables. We find stimulus orientation encoded in early visual and higher cortical regions such as lateral parietal cortex and anterior cingulate cortex (ACC). However, only activity patterns in the ACC tracked changes in decision variables during learning. These results provide strong evidence for perceptual learning-related changes in higher order areas and suggest that perceptual and reward learning are based on a common neurobiological mechanism.

Empirical support for higher-order theories of conscious awareness

Higher-order theories of consciousness argue that conscious awareness crucially depends on higher-order mental representations that represent oneself as being in particular mental states. These theories have featured prominently in recent debates on conscious awareness. We provide new leverage on these debates by reviewing the empirical evidence in support of the higher-order view. We focus on evidence that distinguishes the higher-order view from its alternatives, such as the first-order, global workspace and recurrent visual processing theories. We defend the higher-order view against several major criticisms, such as prefrontal activity reflects attention but not awareness, and prefrontal lesion does not abolish awareness. Although the higher-order approach originated in philosophical discussions, we show that it is testable and has received substantial empirical support.

Estimating the growth of internal evidence guiding perceptual decisions

Perceptual decision-making is thought to involve a gradual accrual of noisy evidence. Temporal integration of the evidence reduces the relative contribution of dynamic internal noise to the decision variable, thereby boosting its signal-to-noise ratio. We aimed to estimate the internal evidence guiding perceptual decisions over time, using a novel combination of external noise and the response signal methods. Observers performed orientation discrimination of patterns presented in external noise. We varied the contrast of the patterns and the delay at which observers were forced to signal their decision. Each test stimulus (patterns and noise sample) was presented twice. Across two experiments we varied the availability of the visual stimulus for processing. Observer model analyses of discrimination accuracy and response consistency to two passes of the same stimulus, suggested that there was very little growth in the internal evidence. The improvement in accuracy over time characterised by the speed-accuracy trade-off function predominantly reflected a decreasing proportion of non-visual decisions, or pure guesses. There was no advantage to having the visual patterns visible for longer than 80 ms, indicating that only the visual information in a short window after display onset was used to drive the decisions. The remarkable constancy of the internal evidence over time suggests that temporal integration of the sensory information was very limited. Alternatively, more extended integration of the evidence from memory could have taken place, provided that the dominant source of internal noise limiting performance occurs between-trials, which cannot be reduced by prolonged evidence integration.

Decoding representations of scenes in the medial temporal lobes

Recent theoretical perspectives have suggested that the function of the human hippocampus, like its rodent counterpart, may be best characterized in terms of its information processing capacities. In this study, we use a combination of high-resolution functional magnetic resonance imaging, multivariate pattern analysis, and a simple decision making task, to test specific hypotheses concerning the role of the medial temporal lobe (MTL) in scene processing. We observed that while information that enabled two highly similar scenes to be distinguished was widely distributed throughout the MTL, more distinct scene representations were present in the hippocampus, consistent with its role in performing pattern separation. As well as viewing the two similar scenes, during scanning participants also viewed morphed scenes that spanned a continuum between the original two scenes. We found that patterns of hippocampal activity during morph trials, even when perceptual inputs were held entirely constant (i.e., in 50% morph trials), showed a robust relationship with participants' choices in the decision task. Our findings provide evidence for a specific computational role for the hippocampus in sustaining detailed representations of complex scenes, and shed new light on how the information processing capacities of the hippocampus may influence the decision making process. © 2011 Wiley Periodicals, Inc.

Distinct patterns of functional and effective connectivity between perirhinal cortex and other cortical regions in recognition memory and perceptual discrimination

Traditionally, the medial temporal lobe (MTL) is thought to be dedicated to declarative memory. Recent evidence challenges this view, suggesting that perirhinal cortex (PrC), which interfaces the MTL with the ventral visual pathway, supports highly integrated object representations in recognition memory and perceptual discrimination. Even with comparable representational demands, perceptual and memory tasks differ in numerous task demands and the subjective experience they evoke. Here, we tested whether such differences are reflected in distinct patterns of connectivity between PrC and other cortical regions, including differential involvement of prefrontal control processes. We examined functional magnetic resonance imaging data for closely matched perceptual and recognition memory tasks for faces that engaged right PrC equivalently. Multivariate seed analyses revealed distinct patterns of interactions: Right ventrolateral prefrontal and posterior cingulate cortices exhibited stronger functional connectivity with PrC in recognition memory; fusiform regions were part of the pattern that displayed stronger functional connectivity with PrC in perceptual discrimination. Structural equation modeling revealed distinct patterns of effective connectivity that allowed us to constrain interpretation of these findings. Overall, they demonstrate that, even when MTL structures show similar involvement in recognition memory and perceptual discrimination, differential neural mechanisms are reflected in the interplay between the MTL and other cortical regions.

High quality but limited quantity perceptual evidence produces neural accumulation in frontal and parietal cortex

Goal-directed perceptual decisions involve the analysis of sensory inputs, the extraction and accumulation of evidence, and the commitment to a choice. Previous neuroimaging studies of perceptual decision making have identified activity related to accumulation in parietal, inferior temporal, and frontal regions. However, such effects may be related to factors other than the integration of evidence over time, such as changes in the quantity of stimulus input and in attentional demands leading up to a decision. The current study tested an accumulation account using 2 manipulations. First, to test whether patterns of accumulation can be explained by changes in the quantity of sensory information, objects were revealed with a high quality but consistent quantity of evidence throughout the trial. Imaging analysis revealed patterns of accumulation in frontal and parietal regions but not in inferior temporal regions. This result supports a framework in which evidence is processed in sensory cortex and integrated over time in higher order cortical areas. Second, to test whether accumulation signals are driven by attentional demands, task difficulty was increased on some trials. This manipulation did not affect the nature of accumulating functional magnetic resonance imaging signals, indicating that accumulating signals are not necessarily driven by changes in attentional demand.

Dissociating the effect of noise on sensory processing and overall decision difficulty

It has been proposed that perceptual decision making involves a task-difficulty component, which detects perceptual uncertainty and guides allocation of attentional resources. It is thought to take place immediately after the early extraction of sensory information and is specifically reflected in a positive component of the event related potentials, peaking at ∼ 220 ms after stimulus onset. However, in the previous research, neural processes associated with the monitoring of overall task difficulty were confounded by those associated with the increased sensory processing demands as a result of adding noise to the stimuli. Here we dissociated the effect of phase noise on sensory processing and overall decision difficulty using a face gender categorization task. Task difficulty was manipulated either by adding noise to the stimuli or by adjusting the female/male characteristics of the face images. We found that it is the presence of noise and not the increased overall task difficulty that affects the electrophysiological responses in the first 300 ms following stimulus onset in humans. Furthermore, we also showed that processing of phase-randomized as compared to intact faces is associated with increased fMRI responses in the lateral occipital cortex. These results revealed that noise-induced modulation of the early electrophysiological responses reflects increased visual cortical processing demands and thus failed to provide support for a task-difficulty component taking place between the early sensory processing and the later sensory accumulation stages of perceptual decision making.

Neural characterization of the speed-accuracy tradeoff in a perceptual decision-making task

Decisions often necessitate a tradeoff between speed and accuracy (SAT), that is, fast decisions are more error prone while careful decisions take longer. Sequential sampling models assume that evidence for different response alternatives is accumulated over time and suggest that SAT modulates the decision system by setting a lower threshold (boundary) on required accumulated evidence to commit a response under time pressure. We investigated how such a speed accuracy tradeoff is implemented neurally under different levels of sensory evidence. Using magnetoencephalography (MEG) and a face-house categorization task, we show that the later decision- and motor-related systems rather than the early sensory system are modulated by SAT. Source analysis revealed that the bilateral supplementary motor areas (SMAs) and the medial precuneus were more activated under the speed instruction and correlated negatively (right SMA) with the boundary parameter, whereas the left dorsolateral prefrontal cortex (DLPFC) was more activated under the accuracy instruction and showed a positive correlation with the boundary. The findings are interpreted in the sense that SMA activity dynamically facilitates fast responses during stimulus processing, potentially by disinhibiting thalamo-striatal loops, whereas DLPFC reflects accumulated evidence before response execution.

An integrated perspective on the relation between response speed and intelligence

Research in the field of mental chronometry and individual differences has revealed several robust regularities (Jensen, 2006). These include right-skewed response time (RT) distributions, the worst performance rule, correlations with general intelligence (g) that are more pronounced for RT standard deviations (RTSD) than they are for RT means (RTm), an almost perfect linear relation between individual differences in RTSD and RTm, linear Brinley plots, and stronger correlations between g and inspection time (IT) than between g and RTm. Here we show how all these regularities are manifestations of a single underlying relationship, when viewed through the lens of Ratcliff's diffusion model (Ratcliff, 1978; Ratcliff, Schmiedek, & McKoon, 2008). The single underlying relationship is between individual differences in general intelligence and individual differences in "drift rate", which is just the speed of information processing in Ratcliff's model. We also test and confirm a strong prediction of the diffusion model, namely that the worst performance rule generalizes to phenomena outside of the field of intelligence. Our approach provides an integrative perspective on intelligence findings.

Prediction of collision events: an EEG coherence analysis

OBJECTIVE

A common daily-life task is the interaction with moving objects for which prediction of collision events is required. To evaluate the sources of information used in this process, this EEG study required participants to judge whether two moving objects would collide with one another or not. In addition, the effect of a distractor object is evaluated.

METHODS

The measurements included the behavioural decision time and accuracy, eye movement fixation times, and the neural dynamics which was determined by means of EEG coherence, expressing functional connectivity between brain areas.

RESULTS

Collision judgment involved widespread information processing across both hemispheres. When a distractor object was present, task-related activity was increased whereas distractor activity induced modulation of local sensory processing. Also relevant were the parietal regions communicating with bilateral occipital and midline areas and a left-sided sensorimotor circuit.

CONCLUSIONS

Besides visual cues, cognitive and strategic strategies are used to establish a decision of events in time. When distracting information is introduced into the collision judgment process, it is managed at different processing levels and supported by distinct neural correlates.

SIGNIFICANCE

These data shed light on the processing mechanisms that support judgment of collision events; an ability that implicates higher-order decision-making.

Cortical network dynamics of perceptual decision-making in the human brain

Goal-directed behavior requires the flexible transformation of sensory evidence about our environment into motor actions. Studies of perceptual decision-making have shown that this transformation is distributed across several widely separated brain regions. Yet, little is known about how decision-making emerges from the dynamic interactions among these regions. Here, we review a series of studies, in which we characterized the cortical network interactions underlying a perceptual decision process in the human brain. We used magnetoencephalography to measure the large-scale cortical population dynamics underlying each of the sub-processes involved in this decision: the encoding of sensory evidence and action plan, the mapping between the two, and the attentional selection of task-relevant evidence. We found that these sub-processes are mediated by neuronal oscillations within specific frequency ranges. Localized gamma-band oscillations in sensory and motor cortices reflect the encoding of the sensory evidence and motor plan. Large-scale oscillations across widespread cortical networks mediate the integrative processes connecting these local networks: Gamma- and beta-band oscillations across frontal, parietal, and sensory cortices serve the selection of relevant sensory evidence and its flexible mapping onto action plans. In sum, our results suggest that perceptual decisions are mediated by oscillatory interactions within overlapping local and large-scale cortical networks.

Delayed perceptual awareness in rapid perceptual decisions

The flourishing of studies on the neural correlates of decision-making calls for an appraisal of the relation between perceptual decisions and conscious perception. By exploiting the long integration time of noisy motion stimuli, and by forcing human observers to make difficult speeded decisions – sometimes a blind guess – about stimulus direction, we traced the temporal buildup of motion discrimination capability and perceptual awareness, as assessed trial by trial through direct rating. We found that both increased gradually with motion coherence and viewing time, but discrimination was systematically leading awareness, reaching a plateau much earlier. Sensitivity and criterion changes contributed jointly to the slow buildup of perceptual awareness. It made no difference whether motion discrimination was accomplished by saccades or verbal responses. These findings suggest that perceptual awareness emerges on the top of a developing or even mature perceptual decision. We argue that the middle temporal (MT) cortical region does not confer us the full phenomenic depth of motion perception, although it may represent a precursor stage in building our subjective sense of visual motion.

How does neuroscience affect our conception of volition?

Although there is no clear concept of volition or the will, we do have intuitive ideas that characterize the will, agency, and voluntary behavior. Here I review results from a number of strands of neuroscientific research that bear upon our intuitive notions of the will. These neuroscientific results provide some insight into the neural circuits mediating behaviors that we identify as related to will and volition. Although some researchers contend that neuroscience will undermine our views about free will, to date no results have succeeded in fundamentally disrupting our common sense beliefs. Still, the picture emerging from neuroscience does raise new questions, and ultimately may put pressure on some intuitive notions about what is necessary for free will.

Brain dynamics of upstream perceptual processes leading to visual object recognition: a high density ERP topographic mapping study

Recent studies suggest that visual object recognition is a proactive process through which perceptual evidence accumulates over time before a decision can be made about the object. However, the exact electrophysiological correlates and time-course of this complex process remain unclear. In addition, the potential influence of emotion on this process has not been investigated yet. We recorded high density EEG in healthy adult participants performing a novel perceptual recognition task. For each trial, an initial blurred visual scene was first shown, before the actual content of the stimulus was gradually revealed by progressively adding diagnostic high spatial frequency information. Participants were asked to stop this stimulus sequence as soon as they could correctly perform an animacy judgment task. Behavioral results showed that participants reliably gathered perceptual evidence before recognition. Furthermore, prolonged exploration times were observed for pleasant, relative to either neutral or unpleasant scenes. ERP results showed distinct effects starting at 280 ms post-stimulus onset in distant brain regions during stimulus processing, mainly characterized by: (i) a monotonic accumulation of evidence, involving regions of the posterior cingulate cortex/parahippocampal gyrus, and (ii) true categorical recognition effects in medial frontal regions, including the dorsal anterior cingulate cortex. These findings provide evidence for the early involvement, following stimulus onset, of non-overlapping brain networks during proactive processes eventually leading to visual object recognition.

Effects of parametrical and trial-to-trial variation in prior probability processing revealed by simultaneous electroencephalogram/functional magnetic resonance imaging

Prior knowledge of the probabilities concerning decision alternatives facilitates the selection of more likely alternatives to the disadvantage of others. The neural basis of prior probability (PP) integration into the decision-making process and associated preparatory processes is, however, still essentially unknown. Furthermore, trial-to-trial fluctuations in PP processing have not been considered thus far. In a previous study, we found that the amplitude of the contingent negative variation (CNV) in a precueing task is sensitive to PP information (Scheibe et al., 2009). We investigated brain regions with a parametric relationship between neural activity and PP and those regions involved in PP processing on a trial-to-trial basis in simultaneously recorded electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data. Conventional fMRI analysis focusing on the information content of the probability precue revealed increasing activation of the posterior medial frontal cortex with increasing PP, supporting its putative role in updating action values. EEG-informed fMRI analysis relating single-trial CNV amplitudes to the hemodynamic signal addressed trial-to-trial fluctuations in PP processing. We identified a set of regions mainly consisting of frontal, parietal, and striatal regions that represents unspecific response preparation on a trial-to-trial basis. A subset of these regions, namely, the dorsolateral prefrontal cortex, the inferior frontal gyrus, and the inferior parietal lobule, showed activations that exclusively represented the contributions of PP to the trial-to-trial fluctuations of the CNV.

Value, pleasure and choice in the ventral prefrontal cortex

Rapid advances have recently been made in understanding how value-based decision-making processes are implemented in the brain. We integrate neuroeconomic and computational approaches with evidence on the neural correlates of value and experienced pleasure to describe how systems for valuation and decision-making are organized in the prefrontal cortex of humans and other primates. We show that the orbitofrontal and ventromedial prefrontal (VMPFC) cortices compute expected value, reward outcome and experienced pleasure for different stimuli on a common value scale. Attractor networks in VMPFC area 10 then implement categorical decision processes that transform value signals into a choice between the values, thereby guiding action. This synthesis of findings across fields provides a unifying perspective for the study of decision-making processes in the brain.

Neural representations of relevant and irrelevant features in perceptual decision making

Although perceptual decision making activates a network of brain areas involved in sensory, integrative, and motor functions, circuit activity can clearly be modulated by factors beyond the stimulus. Of particular interest is to understand how the network is modulated by top-down factors such as attention. Here, we demonstrate in a motion coherence task that selective attention produces marked changes in the blood oxygen level-dependent (BOLD) response in a subset of regions within a human perceptual decision-making circuit. Specifically, when motion is attended, the BOLD response decreases with increasing motion coherence in many regions, including the motion-sensitive area MT+, the intraparietal sulcus, and the inferior frontal sulcus. However, when motion is ignored, the negative parametric response in a subset of this circuit becomes positive. Through both modeling and connectivity analyses, we demonstrate that this inversion both reflects a top-down influence and segregates attentional from accumulation regions, thereby permitting us to further delineate the contributions of different regions to the perceptual decision.

Decision processes in human performance monitoring

The ability to detect and compensate for errors is crucial in producing effective, goal-directed behavior. Human error processing is reflected in two event-related brain potential components, the error-related negativity (Ne/ERN) and error positivity (Pe), but the functional significance of both components remains unclear. Our approach was to consider error detection as a decision process involving an evaluation of available evidence that an error has occurred against an internal criterion. This framework distinguishes two fundamental stages of error detection--accumulating evidence (input), and reaching a decision (output)--that should be differentially affected by changes in internal criterion. Predictions from this model were tested in a brightness discrimination task that required human participants to signal their errors, with incentives varied to encourage participants to adopt a high or low criterion for signaling their errors. Whereas the Ne/ERN was unaffected by this manipulation, the Pe varied consistently with criterion: A higher criterion was associated with larger Pe amplitude for signaled errors, suggesting that the Pe reflects the strength of accumulated evidence. Across participants, Pe amplitude was predictive of changes in behavioral criterion as estimated through signal detection theory analysis. Within participants, Pe amplitude could be estimated robustly with multivariate machine learning techniques and used to predict error signaling behavior both at the level of error signaling frequencies and at the level of individual signaling responses. These results suggest that the Pe, rather than the Ne/ERN, is closely related to error detection, and specifically reflects the accumulated evidence that an error has been committed.

Deficits in visual sustained attention differentiate genetic liability and disease expression for schizophrenia from Bipolar Disorder

BACKGROUND

There is mounting evidence for shared genetic liability to psychoses, particularly with respect to Schizophrenia (SZ) and Bipolar Disorder (BD), which may also involve aspects of cognitive dysfunction. Impaired sustained attention is considered a cardinal feature of psychoses but its association with genetic liability and disease expression in BD remains to be clarified.

METHODS

Visual sustained attention was assessed using the Degraded Symbol Continuous Performance Test (DS-CPT) in a sample of 397 individuals consisting of 50 remitted SZ patients, 119 of their first degree relatives, 47 euthymic BD patients, 88 of their first degree relatives and 93 healthy controls. Relatives with a personal history of schizophrenia or bipolar spectrum disorders were excluded. Performance on the DS-CPT was evaluated based on the response criterion (the amount of perceptual evidence required to designate a stimulus as a target) and sensitivity (a signal-detection theory measure of signal/noise discrimination).

RESULTS

We found no effect of genetic risk or diagnosis for either disorder on response criterion. In contrast, impaired sensitivity was seen in SZ patients and to a lesser degree in their relatives but not in BD patients and their relatives. These findings were not attributable to IQ, medication, age of onset or duration of illness.

CONCLUSIONS

Our results argue for the specificity of visual sustained attention impairment in differentiating SZ from BD. They also suggest that compromised visual information processing is a significant contributor to these deficits in SZ.

How the brain integrates costs and benefits during decision making

When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost-benefit computations. Using functional magnetic resonance imaging and choice modeling, we show that decision making based on cost-benefit comparison can be explained as a stochastic accumulation of cost-benefit difference. Model-driven functional MRI shows that ventromedial and left dorsolateral prefrontal cortex compare costs and benefits by computing the difference between neural signatures of anticipated benefits and costs from the ventral striatum and amygdala, respectively. Moreover, changes in blood oxygen level dependent (BOLD) signal in the bilateral middle intraparietal sulcus reflect the accumulation of the difference signal from ventromedial prefrontal cortex. In sum, we show that a neurophysiological mechanism previously established for perceptual decision making, that is, the difference-based accumulation of evidence, is fundamental also in value-based decisions. The brain, thus, weighs costs against benefits by combining neural benefit and cost signals into a single, difference-based neural representation of net value, which is accumulated over time until the individual decides to accept or reject an option.

Complementary roles of systems representing sensory evidence and systems detecting task difficulty during perceptual decision making

Perceptual decision making is a multi-stage process where incoming sensory information is used to select one option from several alternatives. Researchers typically have adopted one of two conceptual frameworks to define the criteria for determining whether a brain region is involved in decision computations. One framework, building on single-unit recordings in monkeys, posits that activity in a region involved in decision making reflects the accumulation of evidence toward a decision threshold, thus showing the lowest level of BOLD signal during the hardest decisions. The other framework instead posits that activity in a decision-making region reflects the difficulty of a decision, thus showing the highest level of BOLD signal during the hardest decisions. We had subjects perform a face detection task on degraded face images while we simultaneously recorded BOLD activity. We searched for brain regions where changes in BOLD activity during this task supported either of these frameworks by calculating the correlation of BOLD activity with reaction time - a measure of task difficulty. We found that the right supplementary eye field, right frontal eye field, and right inferior frontal gyrus had increased activity relative to baseline that positively correlated with reaction time, while the left superior frontal sulcus and left middle temporal gyrus had decreased activity relative to baseline that negatively correlated with reaction time. We propose that a simple mechanism that scales a region's activity based on task demands can explain our results.

The Drift Diffusion Model can account for the accuracy and reaction time of value-based choices under high and low time pressure

An important open problem is how values are compared to make simple choices. A natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the Drift Diffusion Model (DDM), since this model has been able to account for a large amount of data in other domains. We investigated the ability of four different versions of the DDM to explain the data in a real binary food choice task under conditions of high and low time pressure. We found that a seven-parameter version of the DDM can account for the choice and reaction time data with high-accuracy, in both the high and low time pressure conditions. The changes associated with the introduction of time pressure could be traced to changes in two key model parameters: the barrier height and the noise in the slope of the drift process.

Transcranial magnetic stimulation of posterior parietal cortex affects decisions of hand choice

Deciding which hand to use for an action is one of the most frequent decisions people make in everyday behavior. Using a speeded reaching task, we provide evidence that hand choice entails a competitive decision process between simultaneously activated action plans for each hand. We then show that single-pulse transcranial magnetic stimulation to the left posterior parietal cortex biases this competitive process, leading to an increase in ipsilateral, left hand reaches. Stimulation of the right posterior parietal cortex did not alter hand choice, suggesting a hemispheric asymmetry in the representations of reach plans. These results are unique in providing causal evidence that the posterior parietal cortex is involved in decisions of hand choice.

Decision-making, errors, and confidence in the brain

To provide a fundamental basis for understanding decision-making and decision confidence, we analyze a neuronal spiking attractor-based model of decision-making. The model predicts probabilistic decision-making with larger neuronal responses and larger functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent (BOLD) responses on correct than on error trials because the spiking noise-influenced decision attractor state of the network is consistent with the external evidence. Moreover, the model predicts that the neuronal activity and the BOLD response will become larger on correct trials as the discriminability ΔI increases and confidence increases and will become smaller as confidence decreases on error trials as ΔI increases. Confidence is thus an emergent property of the model. In an fMRI study of an olfactory decision-making task, we confirm these predictions for cortical areas including medial prefrontal cortex and the cingulate cortex implicated in choice decision-making, showing a linear increase in the BOLD signal with ΔI on correct trials, and a linear decrease on error trials. These effects were not found in a control area, the orbitofrontal cortex, where reward value useful for the choice is represented on a continuous scale but that is not implicated in the choice itself. This provides a unifying approach to decision-making and decision confidence and to how spiking-related noise affects choice, confidence, synaptic and neuronal activity, and fMRI signals.

Brain areas consistently linked to individual differences in perceptual decision-making in younger as well as older adults before and after training

Perceptual decision-making performance depends on several cognitive and neural processes. Here, we fit Ratcliff's diffusion model to accuracy data and reaction-time distributions from one numerical and one verbal two-choice perceptual-decision task to deconstruct these performance measures into the rate of evidence accumulation (i.e., drift rate), response criterion setting (i.e., boundary separation), and peripheral aspects of performance (i.e., nondecision time). These theoretical processes are then related to individual differences in brain activation by means of multiple regression. The sample consisted of 24 younger and 15 older adults performing the task in fMRI before and after 100 daily 1-hr behavioral training sessions in a multitude of cognitive tasks. Results showed that individual differences in boundary separation were related to striatal activity, whereas differences in drift rate were related to activity in the inferior parietal lobe. These associations were not significantly modified by adult age or perceptual expertise. We conclude that the striatum is involved in regulating response thresholds, whereas the inferior parietal lobe might represent decision-making evidence related to letters and numbers.

Active and passive touch differentially activate somatosensory cortex in texture perception

The neural mechanisms behind active and passive touch are not yet fully understood. Using fMRI we investigated the brain correlates of these exploratory procedures using a roughness categorization task. Participants either actively explored a surface (active touch) or the surface was moved under the participant's stationary finger (passive touch). The stimuli consisted of three different grades of sandpaper which participants were required to categorize as either coarse, medium, or fine. Exploratory procedure did not affect performance although the coarse and fine surfaces were more easily categorized than the medium surface. An initial whole brain analysis revealed activation of sensory and cognitive areas, including post-central gyrus and prefrontal cortical areas, in line with areas reported in previous studies. Our main analysis revealed greater activation during active than passive touch in the contralateral primary somatosensory region but no effect of stimulus roughness. In contrast, activation in the parietal operculum (OP) was significantly affected by stimulus roughness but not by exploration procedure. Active touch also elicited greater and more distributed brain activity compared with passive touch in areas outside the somatosensory region, possibly due to the motor component of the task. Our results reveal that different cortical areas may be involved in the processing of surface exploration and surface texture, with exploration procedures affecting activations in the primary somatosensory cortex and stimulus properties affecting relatively higher cortical areas within the somatosensory system.

Assessing the neural basis of uncertainty in perceptual category learning through varying levels of distortion

The formation of new perceptual categories involves learning to extract that information from a wide range of often noisy sensory inputs, which is critical for selecting between a limited number of responses. To identify brain regions involved in visual classification learning under noisy conditions, we developed a task on the basis of the classical dot pattern prototype distortion task [M. I. Posner, Journal of Experimental Psychology, 68, 113-118, 1964]. Twenty-seven healthy young adults were required to assign distorted patterns of dots into one of two categories, each defined by its prototype. Categorization uncertainty was modulated parametrically by means of Shannon's entropy formula and set to the levels of 3, 7, and 8.5 bits/dot within subsets of the stimuli. Feedback was presented after each trial, and two parallel versions of the task were developed to contrast practiced and unpracticed performance within a single session. Using event-related fMRI, areas showing increasing activation with categorization uncertainty and decreasing activation with training were identified. Both networks largely overlapped and included areas involved in visuospatial processing (inferior temporal and posterior parietal areas), areas involved in cognitive processes requiring a high amount of cognitive control (posterior medial wall), and a cortico-striatal-thalamic loop through the body of the caudate nucleus. Activity in the medial prefrontal wall was increased when subjects received negative as compared with positive feedback, providing further evidence for its important role in mediating the error signal. This study characterizes the cortico-striatal network underlying the classification of distorted visual patterns that is directly related to decision uncertainty.

Neural processing of risk

In our everyday life, we often have to make decisions with risky consequences, such as choosing a restaurant for dinner or choosing a form of retirement saving. To date, however, little is known about how the brain processes risk. Recent conceptualizations of risky decision making highlight that it is generally associated with emotions but do not specify how emotions are implicated in risk processing. Moreover, little is known about risk processing in non-choice situations and how potential losses influence risk processing. Here we used quantitative meta-analyses of functional magnetic resonance imaging experiments on risk processing in the brain to investigate (1) how risk processing is influenced by emotions, (2) how it differs between choice and non-choice situations, and (3) how it changes when losses are possible. By showing that, over a range of experiments and paradigms, risk is consistently represented in the anterior insula, a brain region known to process aversive emotions such as anxiety, disappointment, or regret, we provide evidence that risk processing is influenced by emotions. Furthermore, our results show risk-related activity in the dorsolateral prefrontal cortex and the parietal cortex in choice situations but not in situations in which no choice is involved or a choice has already been made. The anterior insula was predominantly active in the presence of potential losses, indicating that potential losses modulate risk processing.

Effects of category-specific costs on neural systems for perceptual decision-making

Perceptual judgments are often biased by prospective losses, leading to changes in decision criteria. Little is known about how and where sensory evidence and cost information interact in the brain to influence perceptual categorization. Here we show that prospective losses systematically bias the perception of noisy face-house images. Asymmetries in category-specific cost were associated with enhanced blood-oxygen-level-dependent signal in a frontoparietal network. We observed selective activation of parahippocampal gyrus for changes in category-specific cost in keeping with the hypothesis that loss functions enact a particular task set that is communicated to visual regions. Across subjects, greater shifts in decision criteria were associated with greater activation of the anterior cingulate cortex (ACC). Our results support a hypothesis that costs bias an intermediate representation between perception and action, expressed via general effects on frontal cortex, and selective effects on extrastriate cortex. These findings indicate that asymmetric costs may affect a neural implementation of perceptual decision making in a similar manner to changes in category expectation, constituting a step toward accounting for how prospective losses are flexibly integrated with sensory evidence in the brain.

Anterior insula activations in perceptual paradigms: often observed but barely understood

Anterior insular cortex is among the non-sensory brain regions most commonly found activated in functional brain imaging studies on visual and auditory perception. However, most of these studies do not explicitly address the functional role of this specific brain region in perception, but rather report its activation as a by-product. Here, we attempt to characterize the involvement of anterior insular cortex in various perceptual paradigms, including studies of visual awareness, perceptual decision making, cross-modal sensory processes and the role of spontaneous neural activity fluctuations in perception. We conclude that anterior insular cortex may be associated with perception in that it underpins heightened alertness of either stimulus- or task-driven origin, or both. Such a mechanism could integrate endogenous and exogenous functional demands under the joint criterion of whether they challenge an individual's homeostasis.

Prior Information biases stimulus representations during vibrotactile decision making

Neurophysiological data suggest that the integration of prior information and incoming sensory evidence represents the neural basis of the decision-making process. Here, we aimed to identify the brain structures involved in the integration of prior information about the average magnitude of a stimulus set and current sensory evidence. Specifically, we investigated whether prior average information already biases vibrotactile decision making during stimulus perception and maintenance before the comparison process. For this purpose, we used a vibrotactile delayed discrimination task and fMRI. At the behavioral level, participants showed the time-order effect. This psychophysical phenomenon has been shown to result from the influence of prior information on the perception of and the memory for currently presented stimuli. Similarly, the fMRI signal reflected the integration of prior information about the average vibration frequency and the currently presented vibration frequency. During stimulus encoding, the fMRI signal in primary and secondary somatosensory (S2) cortex, thalamus, and ventral premotor cortex mirrored an integration process. During stimulus maintenance, only a region in the intraparietal sulcus showed this modulation by prior average information. Importantly, the fMRI signal in S2 and intraparietal sulcus correlated with individual differences in the degree to which participants integrated prior average information. This strongly suggests that these two regions play a pivotal role in the integration process. Taken together, these results support the notion that the integration of current sensory and prior average information is a major feature of how the human brain perceives, remembers, and judges magnitude stimuli.

Decoding different roles for vmPFC and dlPFC in multi-attribute decision making

In everyday life, successful decision making requires precise representations of expected values. However, for most behavioral options more than one attribute can be relevant in order to predict the expected reward. Thus, to make good or even optimal choices the reward predictions of multiple attributes need to be integrated into a combined expected value. Importantly, the individual attributes of such multi-attribute objects can agree or disagree in their reward prediction. Here we address where the brain encodes the combined reward prediction (averaged across attributes) and where it encodes the variability of the value predictions of the individual attributes. We acquired fMRI data while subjects performed a task in which they had to integrate reward predictions from multiple attributes into a combined value. Using time-resolved pattern recognition techniques (support vector regression) we find that (1) the combined value is encoded in distributed fMRI patterns in the ventromedial prefrontal cortex (vmPFC) and that (2) the variability of value predictions of the individual attributes is encoded in the dorsolateral prefrontal cortex (dlPFC). The combined value could be used to guide choices, whereas the variability of the value predictions of individual attributes indicates an ambiguity that results in an increased difficulty of the value-integration. These results demonstrate that the different features defining multi-attribute objects are encoded in non-overlapping brain regions and therefore suggest different roles for vmPFC and dlPFC in multi-attribute decision making.

The neural substrate of prior information in perceptual decision making: a model-based analysis

PRIOR INFORMATION BIASES THE DECISION PROCESS: actions consistent with prior information are executed swiftly, whereas actions inconsistent with prior information are executed slowly. How is this bias implemented in the brain? To address this question we conducted an experiment in which people had to decide quickly whether a cloud of dots moved coherently to the left or to the right. Cues provided probabilistic information about the upcoming stimulus. Behavioral data were analyzed with the linear ballistic accumulator (LBA) model, confirming that people used the cue to bias their decisions. The functional magnetic resonance imaging (fMRI) data showed that presentation of the cue differentially activated orbitofrontal cortex, hippocampus, and the putamen. Directional cues selectively activated the contralateral putamen. The fMRI analysis yielded results only when the LBA bias parameter was included as a covariate, highlighting the practical benefits of formal modeling. Our results suggest that the human brain uses prior information by increasing cortico-striatal activation to selectively disinhibit preferred responses.

A mechanistic account of value computation in the human brain

To make decisions based on the value of different options, we often have to combine different sources of probabilistic evidence. For example, when shopping for strawberries on a fruit stand, one uses their color and size to infer-with some uncertainty-which strawberries taste best. Despite much progress in understanding the neural underpinnings of value-based decision making in humans, it remains unclear how the brain represents different sources of probabilistic evidence and how they are used to compute value signals needed to drive the decision. Here, we use a visual probabilistic categorization task to show that regions in ventral temporal cortex encode probabilistic evidence for different decision alternatives, while ventromedial prefrontal cortex integrates information from these regions into a value signal using a difference-based comparator operation.