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Purpose The study aims to explore the relationship between orbitofrontal cortex (OFC) and thalamus volumes and metacognition in patients with obsessive‐compulsive disorder (OCD). By analyzing structural MRI data and metacognitive measures, it investigates how brain volume variations correlate with dysfunctional beliefs and OCD symptoms. Method The study consisted of 20 patients with OCD and 20 healthy controls. Yale‐Brown Obsession Compulsion Scale (Y‐BOCS), Metacognition Questionnaire‐30 (MCQ‐30), Hamilton Depression Scale (HAM‐D), and Hamilton Anxiety Scale (HAM‐A) were administered to OCD patients and healthy controls. They then underwent structural MRI scans to measure the volume of the OFC and thalamus. Finding On both sides, OCD patients had smaller volumes of OFC than healthy control individuals, and their thalamic volumes were similar to those of the control participants. Furthermore, MCQ‐30 scores showed a substantial negative correlation with left OFC volume. Conclusion In conclusion, we suggest that dysfunctional metacognitive beliefs might be related to the occurrence of OCD, and these beliefs might be associated with the left side of OFC neuroanatomically. This study investigates the interplay between metacognitive processes and the neuroanatomical characteristics of the orbitofrontal cortex (OFC) and thalamus in obsessive‐compulsive disorder (OCD). Findings suggest that reduced OFC volumes and specific metacognitive dysfunctions are closely linked to OCD symptoms, highlighting the critical role of these brain regions in understanding and potentially addressing the cognitive mechanisms underlying OCD.

Food choices constitute a classic self-control dilemma involving the trade-off between immediate eating enjoyment and the long term goal of being slim and healthy, especially for weight-concerned women. For them, decision-making concerning high (HE) and low energy (LE) snacks differs when it comes to the need for self-control. In line, our first study aim was to investigate which brain regions are activated during food choices during HE compared to LE energy snacks in weight-concerned women. Since it is particularly difficult to resist HE snacks when they are very tasty, our second aim was to investigate in which brain regions choice-related activation varies with the food's tastiness. Our third aim was to assess in which brain regions choice-related activation varies with individual differences in self-regulatory success. To this end, 20 weight-concerned women indicated for 100 HE or LE snacks whether they wanted to eat them or not, while their brains were scanned using fMRI. HE snacks were refused more often than equally-liked LE snacks. HE snack choice elicited stronger activation in reward-related brain regions [medial to middle orbitofrontal cortex (OFC), caudate]. Highly tasty HE snacks were more difficult to resist and, accordingly, activation in inhibitory areas (inferior frontal gyrus, lateral OFC) was negatively associated with tastiness. More successful self-controllers showed increased activation in the supplementary motor area during HE food choices. In sum, the results suggest that HE snacks constitute a higher reward for weight-concerned women compared to (equally-liked) LE snacks, and that activation during food choice in brain regions involved in response inhibition varied with tastiness and individual differences in self-regulatory success. These findings advance our understanding of the neural correlates of food choice and point to new avenues for investigating explanations for self-regulatory failure.

Following a first version AAL of the automated anatomical labeling atlas (Tzourio-Mazoyer et al., 2002), a second version (AAL2) (Rolls et al., 2015) was developed that provided an alternative parcellation of the orbitofrontal cortex following the description provided by Chiavaras, Petrides, and colleagues. We now provide a third version, AAL3, which adds a number of brain areas not previously defined, but of interest in many neuroimaging investigations. The 26 new areas in the third version are subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts; subdivision of the thalamus into 15 parts; the nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus, locus coeruleus, and raphe nuclei. The new atlas is available as a toolbox for SPM, and can be used with MRIcron. •The automated anatomical atlas 3 (AAL3) is described. The following new areas are added.•Subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts.•Thalamus, nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus.•Locus coeruleus, and raphe nuclei.•AAL3 is available as a toolbox for SPM at www.oxcns.org.

The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, depending on whether the probability distributions of outcomes are known or unknown. Behavioural neurophysiological studies on dopamine neurons revealed a risk signal, which covaried with the standard deviation or variance of the magnitude of juice rewards and occurred separately from reward value coding. Human imaging studies identified similarly distinct risk signals for monetary rewards in the striatum and orbitofrontal cortex (OFC), thus fulfilling a requirement for the mean variance approach of economic decision theory. The orbitofrontal risk signal covaried with individual risk attitudes, possibly explaining individual differences in risk perception and risky decision making. Ambiguous gambles with incomplete probabilistic information induced stronger brain signals than risky gambles in OFC and amygdala, suggesting that the brain's reward system signals the partial lack of information. The brain can use the uncertainty signals to assess the uncertainty of rewards, influence learning, modulate the value of uncertain rewards and make appropriate behavioural choices between only partly known options.

The orbitofrontal cortex and amygdala are involved in emotion and in motivation, but the relationship between these functions performed by these brain structures is not clear. To address this, a unified theory of emotion and motivation is described in which motivational states are states in which instrumental goal-directed actions are performed to obtain rewards or avoid punishers, and emotional states are states that are elicited when the reward or punisher is or is not received. This greatly simplifies our understanding of emotion and motivation, for the same set of genes and associated brain systems can define the primary or unlearned rewards and punishers such as sweet taste or pain. Recent evidence on the connectivity of human brain systems involved in emotion and motivation indicates that the orbitofrontal cortex is involved in reward value and experienced emotion with outputs to cortical regions including those involved in language, and is a key brain region involved in depression and the associated changes in motivation. The amygdala has weak effective connectivity back to the cortex in humans, and is implicated in brainstem-mediated responses to stimuli such as freezing and autonomic activity, rather than in declarative emotion. The anterior cingulate cortex is involved in learning actions to obtain rewards, and with the orbitofrontal cortex and ventromedial prefrontal cortex in providing the goals for navigation and in reward-related effects on memory consolidation mediated partly via the cholinergic system.

Evidence is provided for a new conceptualization of the connectivity and functions of the cingulate cortex in emotion, action, and memory. The anterior cingulate cortex receives information from the orbitofrontal cortex about reward and non-reward outcomes. The posterior cingulate cortex receives spatial and action-related information from parietal cortical areas. It is argued that these inputs allow the cingulate cortex to perform action–outcome learning, with outputs from the midcingulate motor area to premotor areas. In addition, because the anterior cingulate cortex connects rewards to actions, it is involved in emotion; and because the posterior cingulate cortex has outputs to the hippocampal system, it is involved in memory. These apparently multiple different functions of the cingulate cortex are related to the place of this proisocortical limbic region in brain connectivity.

Corticosteroid hormones, released after stress, are known to influence neuronal activity and produce a wide range of effects upon the brain. They affect cognitive tasks including decision-making. Recently it was shown that systemic injections of corticosterone (CORT) disrupt reward-based decision-making in rats when tested in a rat model of the Iowa Gambling Task (rIGT), i.e., rats do not learn across trial blocks to avoid the long-term disadvantageous option. This effect was associated with a change in neuronal activity in prefrontal brain areas, i.e., the infralimbic (IL), lateral orbitofrontal (lOFC) and insular cortex, as assessed by changes in c-Fos expression. Here, we studied whether injections of CORT directly into the IL and lOFC lead to similar changes in decision-making. As in our earlier study, CORT was injected during the final 3 days of the behavioral paradigm, 25 min prior to behavioral testing. Infusions of vehicle into the IL led to a decreased number of visits to the disadvantageous arm across trial blocks, while infusion with CORT did not. Infusions into the lOFC did not lead to differences in the number of visits to the disadvantageous arm between vehicle treated and CORT treated rats. However, compared to vehicle treated rats of the IL group, performance of vehicle treated rats of the lOFC group was impaired, possibly due to cannulation/infusion-related damage of the lOFC affecting decision-making. Overall, these results show that infusions with CORT into the IL are sufficient to disrupt decision-making performance, pointing to a critical role of the IL in corticosteroid effects on reward-based decision-making. The data do not directly support that the same holds true for infusions into the lOFC.

Reward-guided decision-making depends on a network of brain regions. Among these are the orbitofrontal and the anterior cingulate cortex. However, it is difficult to ascertain if these areas constitute anatomical and functional unities, and how these areas correspond between monkeys and humans. To address these questions we looked at connectivity profiles of these areas using resting-state functional MRI in 38 humans and 25 macaque monkeys. We sought brain regions in the macaque that resembled 10 human areas identified with decision making and brain regions in the human that resembled six macaque areas identified with decision making. We also used diffusion-weighted MRI to delineate key human orbital and medial frontal brain regions. We identified 21 different regions, many of which could be linked to particular aspects of reward-guided learning, valuation, and decision making, and in many cases we identified areas in the macaque with similar coupling profiles. Significance Because of the interest in reward-guided learning and decision making, these neural mechanisms have been studied in both humans and monkeys. But whether and how key brain areas correspond between the two species has been uncertain. Areas in the two species can be compared as a function of the brain circuits in which they participate, which can be estimated from patterns of correlation in brain activity measured with functional MRI. Taking such measurements in 38 humans and 25 macaques, we identified fundamental similarities between the species and one human frontal area with no monkey counterpart. Altogether these findings suggest that everyday human decision-making capitalizes on a neural apparatus similar to the one that supports monkeys when foraging in the wild.

Hedonic hotspots are brain sites where particular neurochemical stimulations causally amplify the hedonic impact of sensory rewards, such as “liking” for sweetness. Here, we report the mapping of two hedonic hotspots in cortex, where mu opioid or orexin stimulations enhance the hedonic impact of sucrose taste. One hedonic hotspot was found in anterior orbitofrontal cortex (OFC), and another was found in posterior insula. A suppressive hedonic coldspot was also found in the formof an intervening strip stretching from the posterior OFC through the anterior and middle insula, bracketed by the two cortical hotspots. Opioid/orexin stimulations in either cortical hotspot activated Fos throughout a distributed “hedonic circuit” involving cortical and subcortical structures. Conversely, cortical coldspot stimulation activated circuitry for “hedonic suppression.” Finally, food intake was increased by stimulations at several prefrontal cortical sites, indicating that the anatomical substrates in cortex for enhancing the motivation to eat are discriminable from those for hedonic impact.

Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity. This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores). Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged. Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.