Neural substrates of norm compliance in perceptual decisions.

Societal norms exert a powerful influence on our decisions. Behaviours motivated by norms, however, do not always concur with the responses mandated by decision relevant information potentially generating a conflict. To probe the interplay between normative and informational influences, we examined how prosocial norms impact on perceptual decisions subjects made in the context of a simultaneous presentation of social information. Participants displayed a bias in their perceptual decisions towards that mandated by social information. However, normative prescriptions modulated this bias bi-directionally depending on whether norms mandated a decision in accord or contrary to the contextual social information. At a neural level, the addition of a norms increased activity in prefrontal cortex and modulated functional connectivity between prefrontal and parietal areas. The bi-directional effect of our norms was captured by differential activations when participants decided against the social information. When norms indicated a decision in line with social information, non-compliance modulated lateral prefrontal cortex activity. By contrast, when norms mandated a decision against social information norm compliance increased activity in the anterior cingulate cortex. Hence, social norms changed the balance between a reliance on perceptual and social information by modulating brain activity in regions associated with response inhibition and conflict monitoring.

The impact of traumatic stress on Pavlovian biases.

BACKGROUND: Disturbances in Pavlovian valuation systems are reported to follow traumatic stress exposure. However, motivated decisions are also guided by instrumental mechanisms, but to date the effect of traumatic stress on these instrumental systems remain poorly investigated. Here, we examine whether a single episode of severe traumatic stress influences flexible instrumental decisions through an impact on a Pavlovian system. METHODS: Twenty-six survivors of the 2011 Norwegian terror attack and 30 matched control subjects performed an instrumental learning task in which Pavlovian and instrumental associations promoted congruent or conflicting responses. We used reinforcement learning models to infer how traumatic stress affected learning and decision-making. Based on the importance of dorsal anterior cingulate cortex (dACC) for cognitive control, we also investigated if individual concentrations of Glx (=glutamate + glutamine) in dACC predicted the Pavlovian bias of choice. RESULTS: Survivors of traumatic stress expressed a greater Pavlovian interference with instrumental action selection and had significantly lower levels of Glx in the dACC. Across subjects, the degree of Pavlovian interference was negatively associated with dACC Glx concentrations. CONCLUSIONS: Experiencing traumatic stress appears to render instrumental decisions less flexible by increasing the susceptibility to Pavlovian influences. An observed association between prefrontal glutamatergic levels and this Pavlovian bias provides novel insight into the neurochemical basis of decision-making, and suggests a mechanism by which traumatic stress can impair flexible instrumental behaviours.

Increased fronto-striatal reward prediction errors moderate decision making in obsessive-compulsive disorder.

BACKGROUND: Obsessive-compulsive disorder (OCD) has been linked to functional abnormalities in fronto-striatal networks as well as impairments in decision making and learning. Little is known about the neurocognitive mechanisms causing these decision-making and learning deficits in OCD, and how they relate to dysfunction in fronto-striatal networks. METHOD: We investigated neural mechanisms of decision making in OCD patients, including early and late onset of disorder, in terms of reward prediction errors (RPEs) using functional magnetic resonance imaging. RPEs index a mismatch between expected and received outcomes, encoded by the dopaminergic system, and are known to drive learning and decision making in humans and animals. We used reinforcement learning models and RPE signals to infer the learning mechanisms and to compare behavioural parameters and neural RPE responses of the OCD patients with those of healthy matched controls. RESULTS: Patients with OCD showed significantly increased RPE responses in the anterior cingulate cortex (ACC) and the putamen compared with controls. OCD patients also had a significantly lower perseveration parameter than controls. CONCLUSIONS: Enhanced RPE signals in the ACC and putamen extend previous findings of fronto-striatal deficits in OCD. These abnormally strong RPEs suggest a hyper-responsive learning network in patients with OCD, which might explain their indecisiveness and intolerance of uncertainty.

Computational neuroimaging strategies for single patient predictions.

Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve clinically relevant single-subject predictions. An alternative to machine learning, which tries to establish predictive links between features of the observed data and clinical variables, is the deployment of computational models for inferring on the (patho)physiological and cognitive mechanisms that generate behavioural and neuroimaging responses. This paper discusses the rationale behind a computational approach to neuroimaging-based single-subject inference, focusing on its potential for characterising disease mechanisms in individual subjects and mapping these characterisations to clinical predictions. Following an overview of two main approaches - Bayesian model selection and generative embedding - which can link computational models to individual predictions, we review how these methods accommodate heterogeneity in psychiatric and neurological spectrum disorders, help avoid erroneous interpretations of neuroimaging data, and establish a link between a mechanistic, model-based approach and the statistical perspectives afforded by machine learning.

Unmasking Latent Inhibitory Connections in Human Cortex to Reveal Dormant Cortical Memories.

Balance of cortical excitation and inhibition (EI) is thought to be disrupted in several neuropsychiatric conditions, yet it is not clear how it is maintained in the healthy human brain. When EI balance is disturbed during learning and memory in animal models, it can be restabilized via formation of inhibitory replicas of newly formed excitatory connections. Here we assess evidence for such selective inhibitory rebalancing in humans. Using fMRI repetition suppression we measure newly formed cortical associations in the human brain. We show that expression of these associations reduces over time despite persistence in behavior, consistent with inhibitory rebalancing. To test this, we modulated excitation/inhibition balance with transcranial direct current stimulation (tDCS). Using ultra-high-field (7T) MRI and spectroscopy, we show that reducing GABA allows cortical associations to be re-expressed. This suggests that in humans associative memories are stored in balanced excitatory-inhibitory ensembles that lie dormant unless latent inhibitory connections are unmasked.

The specificity of Pavlovian regulation is associated with recovery from depression.

BACKGROUND: Changes in reflexive emotional responses are hallmarks of depression, but how emotional reflexes make an impact on adaptive decision-making in depression has not been examined formally. Using a Pavlovian-instrumental transfer (PIT) task, we compared the influence of affectively valenced stimuli on decision-making in depression and generalized anxiety disorder compared with healthy controls; and related this to the longitudinal course of the illness. METHOD: A total of 40 subjects with a current DSM-IV-TR diagnosis of major depressive disorder, dysthymia, generalized anxiety disorder, or a combination thereof, and 40 matched healthy controls performed a PIT task that assesses how instrumental approach and withdrawal behaviours are influenced by appetitive and aversive Pavlovian conditioned stimuli (CSs). Patients were followed up after 4-6 months. Analyses focused on patients with depression alone (n = 25). RESULTS: In healthy controls, Pavlovian CSs exerted action-specific effects, with appetitive CSs boosting active approach and aversive CSs active withdrawal. This action-specificity was absent in currently depressed subjects. Greater action-specificity in patients was associated with better recovery over the follow-up period. CONCLUSIONS: Depression is associated with an abnormal influence of emotional reactions on decision-making in a way that may predict recovery.

The computational psychiatry of reward: broken brains or misguided minds?

Research into the biological basis of emotional and motivational disorders is in danger of riding roughshod over a patient-centered psychiatry and falling into the dualist errors of the past, i.e., by treating mind and brain as conceptually distinct. We argue that a psychiatry informed by computational neuroscience, computational psychiatry, can obviate this danger. Through a focus on the reasoning processes by which humans attempt to maximize reward (and minimize punishment), and how such reasoning is expressed neurally, computational psychiatry can render obsolete the polarity between biological and psychosocial conceptions of illness. Here, the term 'psychological' comes to refer to information processing performed by biological agents, seen in light of underlying goals. We reflect on the implications of this perspective for a definition of mental disorder, including what is entailed in asserting that a particular disorder is 'biological' or 'psychological' in origin. We propose that a computational approach assists in understanding the topography of mental disorder, while cautioning that the point at which eccentric reasoning constitutes disorder often remains a matter of cultural judgment.

Arbitration between controlled and impulsive choices.

The impulse to act for immediate reward often conflicts with more deliberate evaluations that support long-term benefit. The neural architecture that negotiates this conflict remains unclear. One account proposes a single neural circuit that evaluates both immediate and delayed outcomes, while another outlines separate impulsive and patient systems that compete for behavioral control. Here we designed a task in which a complex payout structure divorces the immediate value of acting from the overall long-term value, within the same outcome modality. Using model-based fMRI in humans, we demonstrate separate neural representations of immediate and long-term values, with the former tracked in the anterior caudate (AC) and the latter in the ventromedial prefrontal cortex (vmPFC). Crucially, when subjects' choices were compatible with long-run consequences, value signals in AC were down-weighted and those in vmPFC were enhanced, while the opposite occurred when choice was impulsive. Thus, our data implicate a trade-off in value representation between AC and vmPFC as underlying controlled versus impulsive choice.

Dopamine, Salience, and Response Set Shifting in Prefrontal Cortex.

Dopamine is implicated in multiple functions, including motor execution, action learning for hedonically salient outcomes, maintenance, and switching of behavioral response set. Here, we used a novel within-subject psychopharmacological and combined functional neuroimaging paradigm, investigating the interaction between hedonic salience, dopamine, and response set shifting, distinct from effects on action learning or motor execution. We asked whether behavioral performance in response set shifting depends on the hedonic salience of reversal cues, by presenting these as null (neutral) or salient (monetary loss) outcomes. We observed marked effects of reversal cue salience on set-switching, with more efficient reversals following salient loss outcomes. L-Dopa degraded this discrimination, leading to inappropriate perseveration. Generic activation in thalamus, insula, and striatum preceded response set switches, with an opposite pattern in ventromedial prefrontal cortex (vmPFC). However, the behavioral effect of hedonic salience was reflected in differential vmPFC deactivation following salient relative to null reversal cues. l-Dopa reversed this pattern in vmPFC, suggesting that its behavioral effects are due to disruption of the stability and switching of firing patterns in prefrontal cortex. Our findings provide a potential neurobiological explanation for paradoxical phenomena, including maintenance of behavioral set despite negative outcomes, seen in impulse control disorders in Parkinson's disease.

Optimistic update bias increases in older age.

BACKGROUND: Healthy older adults report greater well-being and life satisfaction than their younger counterparts. One potential explanation for this is enhanced optimism. We tested the influence of age on optimistic and pessimistic beliefs about the future and the associated structural neural correlates. METHOD: Eighteen young and 18 healthy older adults performed a belief updating paradigm, measuring differences in updating beliefs for desirable and undesirable information about future negative events. These measures were related to regional brain volume, focusing on the anterior cingulate cortex (ACC) because this region is strongly linked to a positivity bias in older age. RESULTS: We demonstrate an age-related reduction in updating beliefs when older adults are faced with undesirable, but not desirable, information about negative events. This greater 'update bias' in older age persisted even after controlling for a variety of variables including subjective rating scales and poorer overall memory. A structural brain correlate of this greater 'update bias' was evident in greater grey matter volume in the dorsal ACC in older but not in young adults. CONCLUSIONS: We show a greater update bias in healthy older age. The link between this bias and relative volume of the ACC suggests a shared mechanism with an age-related positivity bias. Older adults frequently have to make important decisions relating to personal, health and financial issues. Our findings have wider behavioural implications in these contexts because an enhanced optimistic update bias may skew such real-world decision making.

Depression is related to an absence of optimistically biased belief updating about future life events.

BACKGROUND: When challenged with information about the future, healthy participants show an optimistically biased updating pattern, taking desirable information more into account than undesirable information. However, it is unknown how patients suffering from major depressive disorder (MDD), who express pervasive pessimistic beliefs, update their beliefs when receiving information about their future. Here we tested whether an optimistically biased information processing pattern found in healthy individuals is absent in MDD patients. METHOD: MDD patients (n = 18; 13 medicated; eight with co-morbid anxiety disorder) and healthy controls (n = 19) estimated their personal probability of experiencing 70 adverse life events. After each estimate participants were presented with the average probability of the event occurring to a person living in the same sociocultural environment. This information could be desirable (i.e. average probability better than expected) or undesirable (i.e. average probability worse than expected). To assess how desirable versus undesirable information influenced beliefs, participants estimated their personal probability of experiencing the 70 events a second time. RESULTS: Healthy controls showed an optimistic bias in updating, that is they changed their beliefs more toward desirable versus undesirable information. Overall, this optimistic bias was absent in MDD patients. Symptom severity correlated with biased updating: more severely depressed individuals showed a more pessimistic updating pattern. Furthermore, MDD patients estimated the probability of experiencing adverse life events as higher than healthy controls. CONCLUSIONS: Our findings raise the intriguing possibility that optimistically biased updating of expectations about one's personal future is associated with mental health.

Learning and generalization under ambiguity: an fMRI study.

Adaptive behavior often exploits generalizations from past experience by applying them judiciously in new situations. This requires a means of quantifying the relative importance of prior experience and current information, so they can be balanced optimally. In this study, we ask whether the brain generalizes in an optimal way. Specifically, we used Bayesian learning theory and fMRI to test whether neuronal responses reflect context-sensitive changes in ambiguity or uncertainty about experience-dependent beliefs. We found that the hippocampus expresses clear ambiguity-dependent responses that are associated with an augmented rate of learning. These findings suggest candidate neuronal systems that may be involved in aberrations of generalization, such as over-confidence.

Optimistic biases in observational learning of value.

Action-outcome contingencies can be learnt either by active trial-and-error, or vicariously, by observing the outcomes of actions performed by others. The extant literature is ambiguous as to which of these modes of learning is more effective, as controlled comparisons of operant and observational learning are rare. Here, we contrasted human operant and observational value learning, assessing implicit and explicit measures of learning from positive and negative reinforcement. Compared to direct operant learning, we show observational learning is associated with an optimistic over-valuation of low-value options, a pattern apparent both in participants' choice preferences and their explicit post-hoc estimates of value. Learning of higher value options showed no such bias. We suggest that such a bias can be explained as a tendency for optimistic underestimation of the chance of experiencing negative events, an optimism repressed when information is gathered through direct operant learning.

Rewarding feedback after correct visual discriminations has both general and specific influences on visual cortex.

Reward can influence visual performance, but the neural basis of this effect remains poorly understood. Here we used functional magnetic resonance imaging to investigate how rewarding feedback affected activity in distinct areas of human visual cortex, separating rewarding feedback events after correct performance from preceding visual events. Participants discriminated oriented gratings in either hemifield, receiving auditory feedback at trial end that signaled financial reward after correct performance. Greater rewards improved performance for all but the most difficult trials. Rewarding feedback increased blood-oxygen-level-dependent (BOLD) signals in striatum and orbitofrontal cortex. It also increased BOLD signals in visual areas beyond retinotopic cortex, but not in primary visual cortex representing the judged stimuli. These modulations were seen at a time point in which no visual stimuli were presented or expected, demonstrating a novel type of activity change in visual cortex that cannot reflect modulation of response to incoming or anticipated visual stimuli. Rewarded trials led on the next trial to improved performance and enhanced visual activity contralateral to the judged stimulus, for retinotopic representations of the judged visual stimuli in V1. Our findings distinguish general effects in nonretinotopic visual cortex when receiving rewarding feedback after correct performance from consequences of reward for spatially specific responses in V1.

Choosing to make an effort: the role of striatum in signaling physical effort of a chosen action.

The possibility that we will have to invest effort influences our future choice behavior. Indeed deciding whether an action is actually worth taking is a key element in the expression of human apathy or inertia. There is a well developed literature on brain activity related to the anticipation of effort, but how effort affects actual choice is less well understood. Furthermore, prior work is largely restricted to mental as opposed to physical effort or has confounded temporal with effortful costs. Here we investigated choice behavior and brain activity, using functional magnetic resonance imaging, in a study where healthy participants are required to make decisions between effortful gripping, where the factors of force (high and low) and reward (high and low) were varied, and a choice of merely holding a grip device for minimal monetary reward. Behaviorally, we show that force level influences the likelihood of choosing an effortful grip. We observed greater activity in the putamen when participants opt to grip an option with low effort compared with when they opt to grip an option with high effort. The results suggest that, over and above a nonspecific role in movement anticipation and salience, the putamen plays a crucial role in computations for choice that involves effort costs.

Pain relativity in motor control.

Motivational theories of pain highlight its role in people's choices of actions that avoid bodily damage. By contrast, little is known regarding how pain influences action implementation. To explore this less-understood area, we conducted a study in which participants had to rapidly point to a target area to win money while avoiding an overlapping penalty area that would cause pain in their contralateral hand. We found that pain intensity and target-penalty proximity repelled participants' movement away from pain and that motor execution was influenced not by absolute pain magnitudes but by relative pain differences. Our results indicate that the magnitude and probability of pain have a precise role in guiding motor control and that representations of pain that guide action are, at least in part, relative rather than absolute. Additionally, our study shows that the implicit monetary valuation of pain, like many explicit valuations (e.g., patients' use of rating scales in medical contexts), is unstable, a finding that has implications for pain treatment in clinical contexts.

Modulation of perception and brain activity by predictable trajectories of facial expressions.

People track facial expression dynamics with ease to accurately perceive distinct emotions. Although the superior temporal sulcus (STS) appears to possess mechanisms for perceiving changeable facial attributes such as expressions, the nature of the underlying neural computations is not known. Motivated by novel theoretical accounts, we hypothesized that visual and motor areas represent expressions as anticipated motion trajectories. Using magnetoencephalography, we show predictable transitions between fearful and neutral expressions (compared with scrambled and static presentations) heighten activity in visual cortex as quickly as 165 ms poststimulus onset and later (237 ms) engage fusiform gyrus, STS and premotor areas. Consistent with proposed models of biological motion representation, we suggest that visual areas predictively represent coherent facial trajectories. We show that such representations bias emotion perception of subsequent static faces, suggesting that facial movements elicit predictions that bias perception. Our findings reveal critical processes evoked in the perception of dynamic stimuli such as facial expressions, which can endow perception with temporal continuity.

Modulation of fusiform cortex activity by cholinesterase inhibition predicts effects on subsequent memory.

Cholinergic influences on memory are likely to be expressed at several processing stages, including via well-recognized effects of acetylcholine on stimulus processing during encoding. Since previous studies have shown that cholinesterase inhibition enhances visual extrastriate cortex activity during stimulus encoding, especially under attention-demanding tasks, we tested whether this effect correlates with improved subsequent memory. In a within-subject physostigmine versus placebo design, we measured brain activity with functional magnetic resonance imaging while healthy and mild Alzheimer's disease subjects performed superficial and deep encoding tasks on face (and building) visual stimuli. We explored regions in which physostigmine modulation of face-selective neural responses correlated with physostigmine effects on subsequent recognition performance. In healthy subjects physostigmine led to enhanced later recognition for deep- versus superficially-encoded faces, which correlated across subjects with a physostigmine-induced enhancement of face-selective responses in right fusiform cortex during deep- versus superficial-encoding tasks. In contrast, the Alzheimer's disease group showed neither a depth of processing effect nor restoration of this with physostigmine. Instead, patients showed a task-independent improvement in confident memory with physostigmine, an effect that correlated with enhancements in face-selective (but task-independent) responses in bilateral fusiform cortices. Our results indicate that one mechanism by which cholinesterase inhibitors can improve memory is by enhancing extrastriate cortex stimulus selectivity at encoding, in a manner that for healthy people but not in Alzheimer's disease is dependent upon depth of processing.

Dynamic causal models of steady-state responses.

In this paper, we describe a dynamic causal model (DCM) of steady-state responses in electrophysiological data that are summarised in terms of their cross-spectral density. These spectral data-features are generated by a biologically plausible, neural-mass model of coupled electromagnetic sources; where each source comprises three sub-populations. Under linearity and stationarity assumptions, the model's biophysical parameters (e.g., post-synaptic receptor density and time constants) prescribe the cross-spectral density of responses measured directly (e.g., local field potentials) or indirectly through some lead-field (e.g., electroencephalographic and magnetoencephalographic data). Inversion of the ensuing DCM provides conditional probabilities on the synaptic parameters of intrinsic and extrinsic connections in the underlying neuronal network. This means we can make inferences about synaptic physiology, as well as changes induced by pharmacological or behavioural manipulations, using the cross-spectral density of invasive or non-invasive electrophysiological recordings. In this paper, we focus on the form of the model, its inversion and validation using synthetic and real data. We conclude with an illustrative application to multi-channel local field potential data acquired during a learning experiment in mice.

Neuroimaging of cognition: past, present, and future.

Neuroimaging, particularly that based upon functional magnetic resonance (fMRI), has become a dominant tool in cognitive neuroscience. This review provides a personal and selective perspective on its past, present, and future. Two trends currently characterize the field that broadly reflect a pursuit of "where"- and "how"-type questions. The latter addresses basic mechanisms related to the expression of task-induced neural activity and is likely to be an increasingly important theme in the future. This trend entails an enhanced symbiosis among investigators pursuing similar questions in fields such as computational and theoretical neuroscience as well as through the detailed analysis of microcircuitry.