Neural correlates of weighted reward prediction error during reinforcement learning classify response to cognitive behavioral therapy in depression

While cognitive behavioral therapy (CBT) is an effective treatment for major depressive disorder, only up to 45% of depressed patients will respond to it. At present, there is no clinically viable neuroimaging predictor of CBT response. Notably, the lack of a mechanistic understanding of treatment response has hindered identification of predictive biomarkers. To obtain mechanistically meaningful fMRI predictors of CBT response, we capitalize on pretreatment neural activity encoding a weighted reward prediction error (RPE), which is implicated in the acquisition and processing of feedback information during probabilistic learning. Using a conventional mass-univariate fMRI analysis, we demonstrate that, at the group level, responders exhibit greater pretreatment neural activity encoding a weighted RPE in the right striatum and right amygdala. Crucially, using multivariate methods, we show that this activity offers significant out-of-sample classification of treatment response. Our findings support the feasibility and validity of neurocomputational approaches to treatment prediction in psychiatry

Timing along the cardiac cycle modulates neural signals of reward-based learning.

Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations - absolute and signed prediction errors. We combined machine learning techniques with electroencephalography with both simple, direct indices of task performance and computational model-derived indices of learning. Our results demonstrate that just as people are more sensitive to low magnitude, near-threshold sensory stimuli in certain cardiac phases, so are they more sensitive to low magnitude absolute prediction errors in the same cycles. However, this occurs even when the low magnitude prediction errors are associated with clearly suprathreshold sensory events. In addition, participants exhibiting stronger differences in their prediction error representations between cardiac cycles exhibited higher learning rates and greater task accuracy

Transcranial focused ultrasound-mediated neurochemical and functional connectivity changes in deep cortical regions in humans

Low-intensity transcranial ultrasound stimulation (TUS) is an emerging non-invasive technique for focally modulating human brain function. The mechanisms and neurochemical substrates underlying TUS neuromodulation in humans and how these relate to excitation and inhibition are still poorly understood. In 24 healthy controls, we separately stimulated two deep cortical regions and investigated the effects of theta-burst TUS, a protocol shown to increase corticospinal excitability, on the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and functional connectivity. We show that theta-burst TUS in humans selectively reduces GABA levels in the posterior cingulate, but not the dorsal anterior cingulate cortex. Functional connectivity increased following TUS in both regions. Our findings suggest that TUS changes overall excitability by reducing GABAergic inhibition and that changes in TUS-mediated neuroplasticity last at least 50 mins after stimulation. The difference in TUS effects on the posterior and anterior cingulate could suggest state- or location-dependency of the TUS effect—both mechanisms increasingly recognized to influence the brain’s response to neuromodulation

Transcranial focused ultrasound-mediated neurochemical and functional connectivity changes in deep cortical regions in humans

Low-intensity transcranial ultrasound stimulation (TUS) is an emerging non-invasive technique for focally modulating human brain function. The mechanisms and neurochemical substrates underlying TUS neuromodulation in humans and how these relate to excitation and inhibition are still poorly understood. In 24 healthy controls, we separately stimulated two deep cortical regions and investigated the effects of theta-burst TUS, a protocol shown to increase corticospinal excitability, on the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and functional connectivity. We show that theta-burst TUS in humans selectively reduces GABA levels in the posterior cingulate, but not the dorsal anterior cingulate cortex. Functional connectivity increased following TUS in both regions. Our findings suggest that TUS changes overall excitability by reducing GABAergic inhibition and that changes in TUS-mediated neuroplasticity last at least 50 mins after stimulation. The difference in TUS effects on the posterior and anterior cingulate could suggest state- or location-dependency of the TUS effect—both mechanisms increasingly recognized to influence the brain’s response to neuromodulation

Manipulation of subcortical and deep cortical activity in the primate brain using transcranial focused ultrasound stimulation

Publisher’s embargo period: Embargo set on 04.03.2019 by SR (TIS).The causal role of an area within a neural network can be determined by interfering with its activity and measuring the impact. Many current reversible manipulation techniques have limitations preventing their application, particularly in deep areas of the primate brain. Here, we demonstrate that a focused transcranial ultrasound stimulation (TUS) protocol impacts activity even in deep brain areas: a subcortical brain structure, the amygdala (experiment 1), and a deep cortical region, the anterior cingulate cortex (ACC, experiment 2), in macaques. TUS neuromodulatory effects were measured by examining relationships between activity in each area and the rest of the brain using functional magnetic resonance imaging (fMRI). In control conditions without sonication, activity in a given area is related to activity in interconnected regions, but such relationships are reduced after sonication, specifically for the targeted areas. Dissociable and focal effects on neural activity could not be explained by auditory confounds

Preference for Safe Over Risky Options in Binge Eating.

Binge eating has been usually viewed as a loss of control and an impulsive behavior. But, little is known about the actual behavior of binging patients (prevalently women) in terms of basic decision-making under risk or under uncertainty. In healthy women, stressful cues bias behavior for safer options, raising the question of whether food cues that are perceived as threatening by binging patients may modulate patients' behaviors towards safer options. A cross-sectional study was conducted with binging patients (20 bulimia nervosa (BN) and 23 anorexia nervosa binging (ANB) patients) and two control groups (22 non-binging restrictive (ANR) anorexia nervosa patients and 20 healthy participants), without any concomitant impulsive disorder. We assessed decisions under risk with a gambling task with known probabilities and decisions under uncertainty with the balloon analog risk taking task (BART) with unknown probabilities of winning, in three cued-conditions including neutral, binge food and stressful cues. In the gambling task, binging and ANR patients adopted similar safer attitudes and coherently elicited a higher aversion to losses when primed by food as compared to neutral cues. This held true for BN and ANR patients in the BART. After controlling for anxiety level, these safer attitudes in the food condition were similar to the ones under stress. In the BART, ANB patients exhibited a higher variability in their choices in the food compared to neutral condition. This higher variability was associated with higher difficulties to discard irrelevant information. All these results suggest that decision-making under risk and under uncertainty is not fundamentally altered in all these patients

The Neural Computation of Trust and Reputation

Humans learn to trust new partners by evaluating the outcomes of repeated interpersonal interactions. However, available prior information concerning the reputation of these partners may alter the way in which outcomes affect learning. This thesis combines for the first time behavioral, computational, psychophysiological and neural models in a direct comparison of interaction-based and prior-based decision-to-trust mechanisms. Three studies are presented, in which participants played repeated and single trust games with anonymous counterparts. We manipulated several conditions: whether or not reputational priors were provided, the probability of reciprocation (trustworthiness) of each counterpart, and the time-horizon of the relationships. The thesis addresses several challenges involved in understanding the complex behavior of people in social contexts, by investigating whether and how they integrate reputation into decisions to trust unfamiliar others, by designing ways to combine reputation information and observed trustworthiness into unified models, and by providing insight into information on the brain processes underlying social cognition. Numerous models, algorithms, game theoretical and neuroscientific methods are used to examine these questions. The thesis presents several new reinforcement learning (RL) models and explores how well these models explain the behavioral and neural interactions between trust and reputation. The performance of the new models was tested using experiments of varying complexity. These experiments showed that model-based algorithms correlate better with behavioral and neural responses than model-free RL algorithms. More specifically, when no prior information was available our results were consistent with previous studies in reporting the neural detection of parametric estimates of RL models within the bilateral caudate nuclei. However, our work additionally showed that this correlation was modified when reputational priors on counterparts are provided. Indeed participants continued to rely on priors even when experience shed doubt on their accuracy. Notably, violations of trust from counterparts with high pro-social reputations elicited both stronger electrodermal responses and caudate deactivations when priors were available than when they were not. However, tolerance to such violations appeared to be mediated by priors-enhanced connectivity between the caudate nucleus and ventrolateral prefrontal cortex, which was anti-correlated with retaliation rates. Moreover, in addition to affecting learning mechanisms, violation of trust clearly influenced emotional arousal and increased subsequent recognition of partners who had betrayed trust