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https://www.readbyqxmd.com/read/28334960/neural-mechanisms-of-reinforcement-learning-in-unmedicated-patients-with-major-depressive-disorder
#1
Marcus Rothkirch, Jonas Tonn, Stephan Köhler, Philipp Sterzer
According to current concepts, major depressive disorder is strongly related to dysfunctional neural processing of motivational information, entailing impairments in reinforcement learning. While computational modelling can reveal the precise nature of neural learning signals, it has not been used to study learning-related neural dysfunctions in unmedicated patients with major depressive disorder so far. We thus aimed at comparing the neural coding of reward and punishment prediction errors, representing indicators of neural learning-related processes, between unmedicated patients with major depressive disorder and healthy participants...
February 20, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28324169/roles-of-centromedian-parafascicular-nuclei-of-thalamus-and-cholinergic-interneurons-in-the-dorsal-striatum-in-associative-learning-of-environmental-events
#2
REVIEW
Ko Yamanaka, Yukiko Hori, Takafumi Minamimoto, Hiroshi Yamada, Naoyuki Matsumoto, Kazuki Enomoto, Toshihiko Aosaki, Ann M Graybiel, Minoru Kimura
The thalamus provides a massive input to the striatum, but despite accumulating evidence, the functions of this system remain unclear. It is known, however, that the centromedian (CM) and parafascicular (Pf) nuclei of the thalamus can strongly influence particular striatal neuron subtypes, notably including the cholinergic interneurons of the striatum (CINs), key regulators of striatal function. Here, we highlight the thalamostriatal system through the CM-Pf to striatal CINs. We consider how, by virtue of the direct synaptic connections of the CM and PF, their neural activity contributes to the activity of CINs and striatal projection neurons (SPNs)...
March 21, 2017: Journal of Neural Transmission
https://www.readbyqxmd.com/read/28320846/working-memory-load-strengthens-reward-prediction-errors
#3
Anne G E Collins, Brittany Ciullo, Michael J Frank, David Badre
Reinforcement learning in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we asked how working memory and incremental reinforcement learning processes interact to guide human learning. Working memory load was manipulated by varying the number of stimuli to be learned across blocks...
March 20, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28301764/reward-processing-neuroeconomics-and-psychopathology
#4
David H Zald, Michael T Treadway
Abnormal reward processing is a prominent transdiagnostic feature of psychopathology. The present review provides a framework for considering the different aspects of reward processing and their assessment, and highlights recent insights from the field of neuroeconomics that may aid in understanding these processes. Although altered reward processing in psychopathology has often been treated as a general hypo- or hyperresponsivity to reward, increasing data indicate that a comprehensive understanding of reward dysfunction requires characterization within more specific reward-processing domains, including subjective valuation, discounting, hedonics, reward anticipation and facilitation, and reinforcement learning...
March 15, 2017: Annual Review of Clinical Psychology
https://www.readbyqxmd.com/read/28301188/effects-of-inference-on-dopaminergic-prediction-errors-depend-on-orbitofrontal-processing
#5
Yuji K Takahashi, Thomas A Stalnaker, Matthew R Roesch, Geoffrey Schoenbaum
Dopaminergic reward prediction errors in monkeys reflect inferential reward predictions that well-trained animals can make when associative rules change. Here, in a new analysis of previously described data, we test whether dopaminergic error signals in rats are influenced by inferential predictions and whether such effects depend on the orbitofrontal cortex (OFC). Dopamine neurons were recorded from controls or rats with ipsilateral OFC lesions during performance of a choice task in which odor cues signaled the availability of sucrose reward in 2 wells...
April 2017: Behavioral Neuroscience
https://www.readbyqxmd.com/read/28295339/annual-research-review-childhood-maltreatment-latent-vulnerability-and-the-shift-to-preventative-psychiatry-the-contribution-of-functional-brain-imaging
#6
REVIEW
Eamon J McCrory, Mattia I Gerin, Essi Viding
BACKGROUND: Childhood maltreatment is a potent predictor of poor mental health across the life span. We argue that there is a need to improve the understanding of the mechanisms that confer psychiatric vulnerability following maltreatment, if we are to progress from simply treating those with a manifest disorder, to developing effective preventative approaches that can help offset the likelihood that such disorders will emerge in the first place. METHODS: We review extant functional neuroimaging studies of children and adolescents exposed to early neglect and/or maltreatment, including physical, sexual and emotional abuse across four neurocognitive domains: threat processing, reward processing, emotion regulation and executive control...
March 13, 2017: Journal of Child Psychology and Psychiatry, and Allied Disciplines
https://www.readbyqxmd.com/read/28285994/midbrain-dopamine-neurons-signal-belief-in-choice-accuracy-during-a-perceptual-decision
#7
Armin Lak, Kensaku Nomoto, Mehdi Keramati, Masamichi Sakagami, Adam Kepecs
Central to the organization of behavior is the ability to predict the values of outcomes to guide choices. The accuracy of such predictions is honed by a teaching signal that indicates how incorrect a prediction was ("reward prediction error," RPE). In several reinforcement learning contexts, such as Pavlovian conditioning and decisions guided by reward history, this RPE signal is provided by midbrain dopamine neurons. In many situations, however, the stimuli predictive of outcomes are perceptually ambiguous...
March 20, 2017: Current Biology: CB
https://www.readbyqxmd.com/read/28285820/dynamic-nigrostriatal-dopamine-biases-action-selection
#8
Christopher D Howard, Hao Li, Claire E Geddes, Xin Jin
Dopamine is thought to play a critical role in reinforcement learning and goal-directed behavior, but its function in action selection remains largely unknown. Here we demonstrate that nigrostriatal dopamine biases ongoing action selection. When mice were trained to dynamically switch the action selected at different time points, changes in firing rate of nigrostriatal dopamine neurons, as well as dopamine signaling in the dorsal striatum, were found to be associated with action selection. This dopamine profile is specific to behavioral choice, scalable with interval duration, and doesn't reflect reward prediction error, timing, or value as single factors alone...
March 22, 2017: Neuron
https://www.readbyqxmd.com/read/28275359/the-dopamine-prediction-error-contributions-to-associative-models-of-reward-learning
#9
REVIEW
Helen M Nasser, Donna J Calu, Geoffrey Schoenbaum, Melissa J Sharpe
Phasic activity of midbrain dopamine neurons is currently thought to encapsulate the prediction-error signal described in Sutton and Barto's (1981) model-free reinforcement learning algorithm. This phasic signal is thought to contain information about the quantitative value of reward, which transfers to the reward-predictive cue after learning. This is argued to endow the reward-predictive cue with the value inherent in the reward, motivating behavior toward cues signaling the presence of reward. Yet theoretical and empirical research has implicated prediction-error signaling in learning that extends far beyond a transfer of quantitative value to a reward-predictive cue...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28263301/dopamine-reward-prediction-errors-reflect-hidden-state-inference-across-time
#10
Clara Kwon Starkweather, Benedicte M Babayan, Naoshige Uchida, Samuel J Gershman
Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a 'belief state')...
March 6, 2017: Nature Neuroscience
https://www.readbyqxmd.com/read/28261071/trial-by-trial-modulation-of-associative-memory-formation-by-reward-prediction-error-and-reward-anticipation-as-revealed-by-a-biologically-plausible-computational-model
#11
Kristoffer C Aberg, Julia Müller, Sophie Schwartz
Anticipation and delivery of rewards improves memory formation, but little effort has been made to disentangle their respective contributions to memory enhancement. Moreover, it has been suggested that the effects of reward on memory are mediated by dopaminergic influences on hippocampal plasticity. Yet, evidence linking memory improvements to actual reward computations reflected in the activity of the dopaminergic system, i.e., prediction errors and expected values, is scarce and inconclusive. For example, different previous studies reported that the magnitude of prediction errors during a reinforcement learning task was a positive, negative, or non-significant predictor of successfully encoding simultaneously presented images...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28257849/viral-vector-strategies-for-investigating-midbrain-dopamine-circuits-underlying-motivated-behaviors
#12
REVIEW
Daniel F Cardozo Pinto, Stephan Lammel
Midbrain dopamine (DA) neurons have received significant attention in brain research because of their central role in reward processing and their dysfunction in neuropsychiatric disorders such as Parkinson's disease, drug addiction, depression and schizophrenia. Until recently, it has been thought that DA neurons form a homogeneous population whose primary function is the computation of reward prediction errors. However, through the implementation of viral vector strategies, an unexpected complexity and diversity has been revealed at the anatomical, molecular and functional level...
February 28, 2017: Pharmacology, Biochemistry, and Behavior
https://www.readbyqxmd.com/read/28239676/intact-ventral-striatal-prediction-error-signaling-in-medicated-schizophrenia-patients
#13
Adam J Culbreth, Andrew Westbrook, Ziye Xu, Deanna M Barch, James A Waltz
BACKGROUND: Midbrain dopaminergic neurons code a computational quantity, reward prediction error (RPE), which has been causally related to learning. Recently, this insight has been leveraged to link phenomenological and biological levels of understanding in psychiatric disorders, such as schizophrenia. However, results have been mixed, possibly due to small sample sizes. Here we present results from two studies with relatively large Ns to assess VS RPE in schizophrenia. METHODS: In the current study we analyzed data from two independent studies, involving a total of 87 chronic medicated schizophrenia patients and 61 controls...
September 2016: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
https://www.readbyqxmd.com/read/28228422/elevated-reward-response-to-receipt-of-palatable-food-predicts-future-weight-variability-in-healthy-weight-adolescents
#14
Samantha R Winter, Sonja Yokum, Eric Stice, Karol Osipowicz, Michael R Lowe
Background: Both an elevated brain-reward-region response to palatable food and elevated weight variability have been shown to predict future weight gain.Objective: We examined whether the brain-reward response to food is related to future weight variability.Design: A total of 162 healthy-weight adolescents, who were aged 14-18 y at baseline, were enrolled in the study and were assessed annually over a 3-y follow-up period with 127 participants completing the final 3-y follow-up assessment. With the use of functional magnetic resonance imaging, we tested whether the neural responses to a cue that signaled an impending milkshake receipt and the receipt of the milkshake predicted weight variability over the follow-up period...
February 22, 2017: American Journal of Clinical Nutrition
https://www.readbyqxmd.com/read/28223097/the-roles-of-the-orbitofrontal-cortex-via-the-habenula-in-non-reward-and-depression-and-in-the-responses-of-serotonin-and-dopamine-neurons
#15
Edmund T Rolls
Cortical regions such as the orbitofrontal cortex involved in reward and in non-reward and which are implicated in depression, and the amygdala, are connected to the habenula via the striatum and pallidum, and via subcortical limbic structures. The habenula in turn projects to the raphe nuclei, the source of the serotonin-containing neurons that project to the forebrain. It is proposed that this provides a route for cortical signals related to reward, and to not obtaining expected rewards, to influence the serotonin-containing neuronal system that is influenced by many antidepressant treatments...
February 14, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/28202786/dopamine-modulates-adaptive-prediction-error-coding-in-the-human-midbrain-and-striatum
#16
Kelly M J Diederen, Hisham Ziauddeen, Martin D Vestergaard, Tom Spencer, Wolfram Schultz, Paul C Fletcher
Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride)...
February 15, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28191489/an-efficiency-framework-for-valence-processing-systems-inspired-by-soft-cross-wiring
#17
P Read Montague, Kenneth T Kishida, Rosalyn J Moran, Terry M Lohrenz
Recent experiments suggest that subsecond dopamine delivery to human striatum encodes a combination of reward prediction errors and counterfactual errors thus composing the actual with the possible into one neurochemical signal. Here, we present a model where the counterfactual part of these striatal dopamine fluctuations originates in another valuation system that shadows the dopamine system by acting as its near-antipode in terms of spike-rate encoding yet co-releases dopamine alongside its own native neurotransmitter...
October 2016: Current Opinion in Behavioral Sciences
https://www.readbyqxmd.com/read/28176352/learning-processes-underlying-avoidance-of-negative-outcomes
#18
Marta Andreatta, Sebastian Michelmann, Paul Pauli, Johannes Hewig
Successful avoidance of a threatening event may negatively reinforce the behavior due to activation of brain structures involved in reward processing. Here, we further investigated the learning-related properties of avoidance using feedback-related negativity (FRN). The FRN is modulated by violations of an intended outcome (prediction error, PE), that is, the bigger the difference between intended and actual outcome, the larger the FRN amplitude is. Twenty-eight participants underwent an operant conditioning paradigm, in which a behavior (button press) allowed them to avoid a painful electric shock...
February 8, 2017: Psychophysiology
https://www.readbyqxmd.com/read/28111829/no-association-of-goal-directed-and-habitual-control-with-alcohol-consumption-in-young-adults
#19
Stephan Nebe, Nils B Kroemer, Daniel J Schad, Nadine Bernhardt, Miriam Sebold, Dirk K Müller, Lucie Scholl, Sören Kuitunen-Paul, Andreas Heinz, Michael A Rapp, Quentin J M Huys, Michael N Smolka
Alcohol dependence is a mental disorder that has been associated with an imbalance in behavioral control favoring model-free habitual over model-based goal-directed strategies. It is as yet unknown, however, whether such an imbalance reflects a predisposing vulnerability or results as a consequence of repeated and/or excessive alcohol exposure. We, therefore, examined the association of alcohol consumption with model-based goal-directed and model-free habitual control in 188 18-year-old social drinkers in a two-step sequential decision-making task while undergoing functional magnetic resonance imaging before prolonged alcohol misuse could have led to severe neurobiological adaptations...
January 23, 2017: Addiction Biology
https://www.readbyqxmd.com/read/28103483/dynamic-interaction-between-reinforcement-learning-and-attention-in-multidimensional-environments
#20
Yuan Chang Leong, Angela Radulescu, Reka Daniel, Vivian DeWoskin, Yael Niv
Little is known about the relationship between attention and learning during decision making. Using eye tracking and multivariate pattern analysis of fMRI data, we measured participants' dimensional attention as they performed a trial-and-error learning task in which only one of three stimulus dimensions was relevant for reward at any given time. Analysis of participants' choices revealed that attention biased both value computation during choice and value update during learning. Value signals in the ventromedial prefrontal cortex and prediction errors in the striatum were similarly biased by attention...
January 18, 2017: Neuron
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