Orbitofrontal cortex volume and brain reward response in obesity.

Background/objectivesWhat drives overconsumption of food is poorly understood. Alterations in brain structure and function could contribute to increased food seeking. Recently, brain orbitofrontal cortex (OFC) volume has been implicated in dysregulated eating but little is known how brain structure relates to function.Subjects/methodsWe examined obese (n=18, age=28.7±8.3 years) and healthy control women (n=24, age=27.4±6.3 years) using a multimodal brain imaging approach. We applied magnetic resonance and diffusion tensor imaging to study brain gray and white matter volume as well as white matter (WM) integrity, and tested whether orbitofrontal cortex volume predicts brain reward circuitry activation in a taste reinforcement-learning paradigm that has been associated with dopamine function.ResultsObese individuals displayed lower gray and associated white matter volumes (P<0.05 family-wise error (FWE)- small volume corrected) compared with controls in the orbitofrontal cortex, striatum and insula. White matter integrity was reduced in obese individuals in fiber tracts including the external capsule, corona radiata, sagittal stratum, and the uncinate, inferior fronto-occipital, and inferior longitudinal fasciculi. Gray matter volume of the gyrus rectus at the medial edge of the orbitofrontal cortex predicted functional taste reward-learning response in frontal cortex, insula, basal ganglia, amygdala, hypothalamus and anterior cingulate cortex in control but not obese individuals.ConclusionsThis study indicates a strong association between medial orbitofrontal cortex volume and taste reinforcement-learning activation in the brain in control but not in obese women. Lower brain volumes in the orbitofrontal cortex and other brain regions associated with taste reward function as well as lower integrity of connecting pathways in obesity (OB) may support a more widespread disruption of reward pathways. The medial orbitofrontal cortex is an important structure in the termination of food intake and disturbances in this and related structures could contribute to overconsumption of food in obesity

Attention-dependent modulation of cortical taste circuits revealed by granger causality with signal-dependent noise

We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention

Functional connectivity of the human amygdala in health and in depression

To analyze the functioning of the amygdala in depression, we performed the first voxel-level resting state functional-connectivity neuroimaging analysis of depression of voxels in the amygdala with all other voxels in the brain, with 336 patients with major depressive disorder and 350 controls. Amygdala voxels had decreased functional connectivity with the orbitofrontal cortex, temporal lobe areas, including the temporal pole, inferior temporal gyrus, and the parahippocampal gyrus. The reductions in the strengths of the functional connectivity of the amygdala voxels with the medial orbitofrontal cortex and temporal lobe voxels were correlated with increases in the Beck Depression Inventory score and in the duration of illness measures of depression. Parcellation analysis in 350 healthy controls based on voxel-level functional connectivity showed that the basal division of the amygdala has high functional connectivity with medial orbitofrontal cortex areas, and the dorsolateral amygdala has strong functional connectivity with the lateral orbitofrontal cortex and related ventral parts of the inferior frontal gyrus. In depression, the basal amygdala division had especially reduced functional connectivity with the medial orbitofrontal cortex which is involved in reward; and the dorsolateral amygdala subdivision had relatively reduced functional connectivity with the lateral orbitofrontal cortex which is involved in non-reward

How the brain represents the reward value of fat in the mouth.

The palatability and pleasantness of the sensory properties of foods drive food selection and intake and may contribute to overeating and obesity. Oral fat texture can make food palatable and pleasant. To analyze its neural basis, we correlated humans’ subjective reports of the pleasantness of the texture and flavor of a high- and low-fat food with a vanilla or strawberry flavor, with neural activations measured with functional magnetic resonance imaging. Activity in the midorbitofrontal and anterior cingulate cortex was correlated with the pleasantness of oral fat texture and in nearby locations with the pleasantness of flavor. The pregenual cingulate cortex showed a supralinear response to the combination of high fat and pleasant, sweet flavor, implicating it in the convergence of fat texture and flavor to produce a representation of highly pleasant stimuli. The subjective reports of oral fattiness were correlated with activations in the midorbitofrontal cortex and ventral striatum. The lateral hypothalamus and amygdala were more strongly activated by high- versus low-fat stimuli. This discovery of which brain regions track the subjective hedonic experience of fat texture will help to unravel possible differences in the neural responses in obese versus lean people to oral fat, a driver of food intake

Neural correlates of processing valence and arousal in affective words

Psychological frameworks conceptualize emotion along 2 dimensions, "valence" and "arousal." Arousal invokes a single axis of intensity increasing from neutral to maximally arousing. Valence can be described variously as a bipolar continuum, as independent positive and negative dimensions, or as hedonic value (distance from neutral). In this study, we used functional magnetic resonance imaging to characterize neural activity correlating with arousal and with distinct models of valence during presentation of affective word stimuli. Our results extend observations in the chemosensory domain suggesting a double dissociation in which subregions of orbitofrontal cortex process valence, whereas amygdala preferentially processes arousal. In addition, our data support the physiological validity of descriptions of valence along independent axes or as absolute distance from neutral but fail to support the validity of descriptions of valence along a bipolar continuum

Determining a Role for Ventromedial Prefrontal Cortex in Encoding Action-Based Value Signals During Reward-Related Decision Making

Considerable evidence has emerged to implicate ventromedial prefrontal cortex in encoding expectations of future reward during value-based decision making. However, the nature of the learned associations upon which such representations depend is much less clear. Here, we aimed to determine whether expected reward representations in this region could be driven by action–outcome associations, rather than being dependent on the associative value assigned to particular discriminative stimuli. Subjects were scanned with functional magnetic resonance imaging while performing 2 variants of a simple reward-related decision task. In one version, subjects made choices between 2 different physical motor responses in the absence of discriminative stimuli, whereas in the other version, subjects chose between 2 different stimuli that were randomly assigned to different responses on a trial-by-trial basis. Using an extension of a reinforcement learning algorithm, we found activity in ventromedial prefrontal cortex tracked expected future reward during the action-based task as well as during the stimulus-based task, indicating that value representations in this region can be driven by action–outcome associations. These findings suggest that ventromedial prefrontal cortex may play a role in encoding the value of chosen actions irrespective of whether those actions denote physical motor responses or more abstract decision options

Dopaminergic and Non-Dopaminergic Value Systems in Conditioning and Outcome-Specific Revaluation

Animals are motivated to choose environmental options that can best satisfy current needs. To explain such choices, this paper introduces the MOTIVATOR (Matching Objects To Internal Values Triggers Option Revaluations) neural model. MOTIVATOR describes cognitiveemotional interactions between higher-order sensory cortices and an evaluative neuraxis composed of the hypothalamus, amygdala, and orbitofrontal cortex. Given a conditioned stimulus (CS), the model amygdala and lateral hypothalamus interact to calculate the expected current value of the subjective outcome that the CS predicts, constrained by the current state of deprivation or satiation. The amygdala relays the expected value information to orbitofrontal cells that receive inputs from anterior inferotemporal cells, and medial orbitofrontal cells that receive inputs from rhinal cortex. The activations of these orbitofrontal cells code the subjective values of objects. These values guide behavioral choices. The model basal ganglia detect errors in CS-specific predictions of the value and timing of rewards. Excitatory inputs from the pedunculopontine nucleus interact with timed inhibitory inputs from model striosomes in the ventral striatum to regulate dopamine burst and dip responses from cells in the substantia nigra pars compacta and ventral tegmental area. Learning in cortical and striatal regions is strongly modulated by dopamine. The model is used to address tasks that examine food-specific satiety, Pavlovian conditioning, reinforcer devaluation, and simultaneous visual discrimination. Model simulations successfully reproduce discharge dynamics of known cell types, including signals that predict saccadic reaction times and CS-dependent changes in systolic blood pressure.Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Institutes of Health (R29-DC02952, R01-DC007683); National Science Foundation (IIS-97-20333, SBE-0354378); Office of Naval Research (N00014-01-1-0624

Autism spectrum traits in normal individuals : a preliminary VBM analysis

In light of the new DSM-5 autism spectrum disorders diagnosis in which the autism spectrum reflects a group of neurodevelopmental disorders existing on a continuum from mild to severe expression of autistic traits, and recent empirical findings showing a continuous distribution of autistic traits in the general population, our voxel based morphometry study compares normal individuals with high autistic traits to normal individuals with low autistic traits. We hypothesize that normal individuals with high autistic traits in terms of empathizing and systemizing [high systemizing (HS)/low empathizing (LE)] share brain irregularities with individuals that fall within the clinical autism spectrum disorder. We find differences in several social brain network areas between our groups. Specifically, we find increased gray matter (GM) volume in the orbitofrontal cortex, the cuneus, the hippocampus and parahippocampus and reduced GM volume in the inferior temporal cortex, the insula, and the amygdala in our HS/LE individuals relative to our HE/LS (low autistic traits in terms of empathizing and systemizing) individuals

Dissociating the Role of the Orbitofrontal Cortex and the Striatum in the Computation of Goal Values and Prediction Errors

To make sound economic decisions, the brain needs to compute several different value-related signals. These include goal values that measure the predicted reward that results from the outcome generated by each of the actions under consideration, decision values that measure the net value of taking the different actions, and prediction errors that measure deviations from individuals' previous reward expectations. We used functional magnetic resonance imaging and a novel decision-making paradigm to dissociate the neural basis of these three computations. Our results show that they are supported by different neural substrates: goal values are correlated with activity in the medial orbitofrontal cortex, decision values are correlated with activity in the central orbitofrontal cortex, and prediction errors are correlated with activity in the ventral striatum