Reward and Punishment Learning as Predictors of Cognitive Behavioral Therapy Response in Parkinson's Disease Comorbid with Clinical Depression.

Depression is highly comorbid among individuals with Parkinson's Disease (PD), who often experience unique challenges to accessing and benefitting from empirically supported interventions like Cognitive Behavioral Therapy (CBT). Given the role of reward processing in both depression and PD, this study analyzed a subset (N = 25) of participants who participated in a pilot telemedicine intervention of PD-informed CBT, and also completed a Reward- and Punishment-Learning Task (RPLT) at baseline. At the conclusion of CBT, participants were categorized into treatment responders (n = 14) and non-responders (n = 11). Responders learned more optimally from negative rather than positive feedback on the RPLT, while this pattern was reversed in non-responders. Computational modeling suggested group differences in learning rate to negative feedback may drive the observed differences. Overall, the results suggest that a within-subject bias for punishment-based learning might help to predict response to CBT intervention for depression in those with PD.Plain Language Summary Performance on a Computerized Task may predict which Parkinson's Disease Patients benefit from Cognitive Behavioral Treatment of Clinical DepressionWhy was the study done? Clinical depression regularly arises in individuals with Parkinson's Disease (PD) due to the neurobiological changes with the onset and progression of the disease as well as the unique psychosocial difficulties associated with living with a chronic condition. Nonetheless, psychiatric disorders among individuals with PD are often underdiagnosed and likewise undertreated for a variety of reasons. The results of our study have implications about how to improve the accuracy and specificity of mental health treatment recommendations in the future to maximize benefits for individuals with PD, who often face additional barriers to accessing quality mental health treatment.What did the researchers do? We explored whether performance on a computerized task called the Reward- and Punishment-Learning Task (RPLT) helped to predict response to Cognitive Behavioral Therapy (CBT) for depression better than other predictors identified in previous studies. Twenty-five individuals with PD and clinical depression that completed a 10-week telehealth CBT program were assessed for: Demographics (Age, gender, etc.); Clinical information (PD duration, mental health diagnoses, levels of anxiety/depression, etc.); Neurocognitive performance (Memory, processing speed, impulse control, etc.); and RPLT performance.What did the researchers find? A total of 14 participants significantly benefitted from CBT treatment while 11 did not significantly benefit from treatment.There were no differences before treatment in the demographics, clinical information, and neurocognitive performance of those participants who ended up benefitting from the treatment versus those who did not.There were, however, differences before treatment in RPLT performance so that those individuals that benefitted from CBT seemed to learn better from negative feedback.What do the findings mean? Our results suggest that the CBT program benefitted those PD patients with clinical depression that seemed to overall learn best from avoiding punishment rather than obtaining reward which was targeted in CBT by focusing on increasing engagement in rewarding activities. The Reward- and Punishment-Learning Task hence may be a useful tool to help predict treatment response and provide more individualized recommendations on how to best maximize the benefits of psychotherapy for individuals with PD that may struggle to connect to mental health care. Caution is recommended about interpretating these results beyond this study as the overall number of participants was small and the data for this study were collected as part of a previous study so there was no opportunity to include additional measurements of interest.

Prefrontal transcranial magnetic stimulation boosts response vigour during reinforcement learning in healthy adults.

A 10-Hz repetitive transcranial magnetic stimulation to the left dorsal lateral prefrontal cortex has been shown to increase dopaminergic activity in the dorsal striatum, a region strongly implicated in reinforcement learning. However, the behavioural influence of this effect remains largely unknown. We tested the causal effects of 10-Hz stimulation on behavioural and computational characteristics of reinforcement learning. A total of 40 healthy individuals were randomized into active and sham (placebo) stimulation groups. Each participant underwent one stimulation session (1500 pulses) in which stimulation was applied over the left dorsal lateral prefrontal cortex using a robotic arm. Participants then completed a reinforcement learning task sensitive to striatal dopamine functioning. Participants' choices were modelled using a reinforcement learning model (Q-learning) that calculates separate learning rates associated with positive and negative reward prediction errors. Subjects receiving active stimulation exhibited increased reward rate (number of correct responses per second of task activity) compared with those in sham. Computationally, although no group differences were observed, the active group displayed a higher learning rate for correct trials (αG) compared with incorrect trials (αL). Finally, when tested with novel pairs of stimuli, the active group displayed extremely fast reaction times, and a trend towards a higher reward rate. This study provided specific behavioural and computational accounts of altered striatal-mediated behaviour, particularly response vigour, induced by a proposed increase of dopamine activity by 10-Hz stimulation to the left dorsal lateral prefrontal cortex. Together, these findings bolster the use of repetitive transcranial magnetic stimulation to target neurocognitive disturbances attributed to the dysregulation of dopaminergic-striatal circuits.

Improving the prospective prediction of a near-term suicide attempt in veterans at risk for suicide, using a go/no-go task.

BACKGROUND: Neurocognitive testing may advance the goal of predicting near-term suicide risk. The current study examined whether performance on a Go/No-go (GNG) task, and computational modeling to extract latent cognitive variables, could enhance prediction of suicide attempts within next 90 days, among individuals at high-risk for suicide. METHOD: 136 Veterans at high-risk for suicide previously completed a computer-based GNG task requiring rapid responding (Go) to target stimuli, while withholding responses (No-go) to infrequent foil stimuli; behavioral variables included false alarms to foils (failure to inhibit) and missed responses to targets. We conducted a secondary analysis of these data, with outcomes defined as actual suicide attempt (ASA), other suicide-related event (OtherSE) such as interrupted/aborted attempt or preparatory behavior, or neither (noSE), within 90-days after GNG testing, to examine whether GNG variables could improve ASA prediction over standard clinical variables. A computational model (linear ballistic accumulator, LBA) was also applied, to elucidate cognitive mechanisms underlying group differences. RESULTS: On GNG, increased miss rate selectively predicted ASA, while increased false alarm rate predicted OtherSE (without ASA) within the 90-day follow-up window. In LBA modeling, ASA (but not OtherSE) was associated with decreases in decisional efficiency to targets, suggesting differences in the evidence accumulation process were specifically associated with upcoming ASA. CONCLUSIONS: These findings suggest that GNG may improve prediction of near-term suicide risk, with distinct behavioral patterns in those who will attempt suicide within the next 90 days. Computational modeling suggests qualitative differences in cognition in individuals at near-term risk of suicide attempt.

Pyridostigmine bromide, chlorpyrifos, and DEET combined Gulf War exposure insult depresses mitochondrial function in neuroblastoma cells.

Gulf War Illness (GWI) is defined by the Centers for Disease Control and Prevention (CDC) as a multi-symptom illness having at least one symptom from two of three factors, which include: fatigue, mood-cognition problems, and musculoskeletal disorders. The cluster of long-term symptoms is unique to military personnel from coalition countries including United States, Australia, and the United Kingdom that served in Operation Desert Storm from 1990 to 1991. Reporting of these symptoms is much lower among soldiers deployed in other parts of the world like Bosnia during the same time period. The exact cause of GWI is unknown, but combined exposure to N,N-diethyl-m-toluamide (DEET), organophosphates like chlorpyrifos (CPF), and pyridostigmine bromide (PB), has been hypothesized as a potential mechanism. Mitochondrial dysfunction is known to occur in most neurodegenerative diseases that share symptoms with GWI and has therefore been implicated in GWI. Although exposure to these and other toxicants continues to be investigated as potential causes of GWI, their combined impact on mitochondrial physiology remains unknown. In this study, the effects of combined GWI toxicant exposure on mitochondrial function were determined in a commonly used and readily available immortalized cell line (N2a), whose higher rate of oxygen consumption resembles that of highly metabolic neurons in vivo. We report that combined exposure containing pesticide CPF 71 µM, insect repellants DEET 78 µM, and antitoxins PB 19 µM, causes profound mitochondrial dysfunction after a 4-h incubation resulting in decreased mitochondrial respiratory states in the absence of proapoptotic signaling, proton leak, or significant increase in reactive oxygen species production.

ABCA7 risk variant in healthy older African Americans is associated with a functionally isolated entorhinal cortex mediating deficient generalization of prior discrimination training.

Using high-resolution resting state functional magnetic resonance imaging (fMRI), the present study tested the hypothesis that ABCA7 genetic risk differentially affects intra-medial temporal lobe (MTL) functional connectivity between MTL subfields, versus internetwork connectivity of the MTL with the medial prefrontal cortex (mPFC), in nondemented older African Americans. Although the association of ABCA7 risk variants with Alzheimer's disease (AD) has been confirmed worldwide, its effect size on the relative odds of being diagnosed with AD is significantly higher in African Americans. However, little is known about the neural correlates of cognitive function in older African Americans and how they relate to AD risk conferred by ABCA7. In a case-control fMRI study of 36 healthy African Americans, we observed ABCA7 related impairments in behavioral generalization that was mediated by dissociation in entorhinal cortex (EC) resting state functional connectivity. Specifically, ABCA7 risk variant was associated with EC-hippocampus hyper-synchronization and EC-mPFC hypo-synchronization. Carriers of the risk genotype also had a significantly smaller anterolateral EC, despite our finding no group differences on standardized neuropsychological tests. Our findings suggest a model where impaired cortical connectivity leads to a more functionally isolated EC at rest, which translates into aberrant EC-hippocampus hyper-synchronization resulting in generalization deficits. While we cannot identify the exact mechanism underlying the observed alterations in EC structure and network function, considering the relevance of Aß in ABCA7 related AD pathogenesis, the results of our study may reflect the synergistic reinforcement between amyloid and tau pathology in the EC, which significantly increases tau-induced neuronal loss and accelerates synaptic alterations. Finally, our results add to a growing literature suggesting that generalization of learning may be a useful tool for assessing the mild cognitive deficits seen in the earliest phases of prodromal AD, even before the more commonly reported deficits in episodic memory arise.

Greater avoidance behavior in individuals with posttraumatic stress disorder symptoms.

While avoidance is a core symptom of PTSD, little is known about whether individuals with PTSD show a general cognitive bias to acquire and express avoidance, in situations not related to trauma or fear. Here, we used a computer-based task to examine operant acquisition and extinction of avoidance in participants with and without severe self-reported PTSD symptoms. A total of 119 participants (77 male, 42 female; 74 veteran, 45 civilian) with symptoms (PTSS; n = 63) or with few/no symptoms (noPTSS; n = 56) performed a task, in which they controlled a spaceship and could shoot a target to gain points or hide in "safe areas" to escape or avoid on-screen aversive events. Results show that participants with PTSS exhibited more avoidance across trials than noPTSS participants, particularly due to more avoidance behavior in PTSS females compared to noPTSS females. Avoidance behavior decreased across extinction trials but interactions with PTSS and gender fell short of significance. Overall, PTSD symptoms were associated with propensity to acquire and express avoidance behavior, in both civilians and veterans, and even in a cognitive task that does not explicitly involve trauma or fear. This effect was more pronounced in females, highlighting the role of gender differences in PTSD symptomatology. Importantly, this study also demonstrates the potential of an objective assessment of avoidance behavior, which could be used to supplement the common but limited self-report tools.

Reward and punishment-based compound cue learning and generalization in opiate dependency.

Substance dependence is thought to be mediated by abnormalities in cognitive abilities, but how this impacts decision-making remains unclear. This study aimed to test whether people who are opiate dependent differed from never-dependent controls in learning from reward and punishment or in the generalization of learning to novel conditions. Participants with opiate dependency consisted of 21 people who were outpatients in a methadone maintenance program; the control group consisted of 21 healthy participants with no histories of substance abuse. Subjects completed a computer-based task that involved two phases: the training phase involved participants being presented with compound stimulus (a shape and color) in each trial, with the goal of learning which compounds to 'pick' for rewards or 'skip' to avoid punishment. The test phase involved a transfer test, where stimuli from the first phase were combined together to form novel compounds without feedback. The control group demonstrated fewer errors compared to opiate-dependent individuals during the training phase. In the test phase, controls used prior knowledge of both shapes and colors in responding; however, opiate-dependent individuals used shapes but did not use their knowledge of color to modulate responding. When performance during training was equated in the groups using a learning threshold, this difference between groups on the generalization test remained. A deficit in learning generalization might be indicative of group differences in learning strategies in operation during training; however, future work is necessary to uncover the specific neural substrates in action during transfer tasks, and to determine the effects of acute methadone dosage on decision-making.

Deficits in hippocampal-dependent transfer generalization learning accompany synaptic dysfunction in a mouse model of amyloidosis.

Elevated ß-amyloid and impaired synaptic function in hippocampus are among the earliest manifestations of Alzheimer's disease (AD). Most cognitive assessments employed in both humans and animal models, however, are insensitive to this early disease pathology. One critical aspect of hippocampal function is its role in episodic memory, which involves the binding of temporally coincident sensory information (e.g., sights, smells, and sounds) to create a representation of a specific learning epoch. Flexible associations can be formed among these distinct sensory stimuli that enable the "transfer" of new learning across a wide variety of contexts. The current studies employed a mouse analog of an associative "transfer learning" task that has previously been used to identify risk for prodromal AD in humans. The rodent version of the task assesses the transfer of learning about stimulus features relevant to a food reward across a series of compound discrimination problems. The relevant feature that predicts the food reward is unchanged across problems, but an irrelevant feature (i.e., the context) is altered. Experiment 1 demonstrated that C57BL6/J mice with bilateral ibotenic acid lesions of hippocampus were able to discriminate between two stimuli on par with control mice; however, lesioned mice were unable to transfer or apply this learning to new problem configurations. Experiment 2 used the APPswe PS1 mouse model of amyloidosis to show that robust impairments in transfer learning are evident in mice with subtle ß-amyloid-induced synaptic deficits in the hippocampus. Finally, Experiment 3 confirmed that the same transfer learning impairments observed in APPswePS1 mice were also evident in the Tg-SwDI mouse, a second model of amyloidosis. Together, these data show that the ability to generalize learned associations to new contexts is disrupted even in the presence of subtle hippocampal dysfunction and suggest that, across species, this aspect of hippocampal-dependent learning may be useful for early identification of AD-like pathology.

Corruption of the dentate gyrus by "dominant" granule cells: Implications for dentate gyrus function in health and disease.

The dentate gyrus (DG) and area CA3 of the hippocampus are highly organized lamellar structures which have been implicated in specific cognitive functions such as pattern separation and pattern completion. Here we describe how the anatomical organization and physiology of the DG and CA3 are consistent with structures that perform pattern separation and completion. We then raise a new idea related to the complex circuitry of the DG and CA3 where CA3 pyramidal cell 'backprojections' play a potentially important role in the sparse firing of granule cells (GCs), considered important in pattern separation. We also propose that GC axons, the mossy fibers, already known for their highly specialized structure, have a dynamic function that imparts variance--'mossy fiber variance'--which is important to pattern separation and completion. Computational modeling is used to show that when a subset of GCs become 'dominant,' one consequence is loss of variance in the activity of mossy fiber axons and a reduction in pattern separation and completion in the model. Empirical data are then provided using an example of 'dominant' GCs--subsets of GCs that develop abnormally and have increased excitability. Notably, these abnormal GCs have been identified in animal models of disease where DG-dependent behaviors are impaired. Together these data provide insight into pattern separation and completion, and suggest that behavioral impairment could arise from dominance of a subset of GCs in the DG-CA3 network.

Beyond symptom self-report: use of a computer "avatar" to assess post-traumatic stress disorder (PTSD) symptoms.

Post-traumatic stress disorder (PTSD) can occur in the wake of exposure to a traumatic event. Currently, PTSD symptoms are assessed mainly through self-report in the form of questionnaire or clinical interview. Self-report has inherent limitations, particularly in psychiatric populations who may have limited awareness of deficit, reduced attention span, or poor vocabulary and/or literacy skills. Diagnosis and evaluation of treatment efficacy would be aided by behavioral measures. A viable alternative may be virtual environments, in which the participant guides an on-screen "avatar" through a series of onscreen events meant to simulate real-world situations. Here, a sample of 82 veterans, self-assessed for PTSD symptoms was administered such a task, in which the avatar was confronted with situations that might evoke avoidant behavior, a core feature of PTSD. Results showed a strong correlation between PTSD symptom burden and task performance; in fact, the ability to predict PTSD symptom burden based on simple demographic variables (age, sex, combat exposure) was significantly improved by adding task score as a predictor variable. The results therefore suggest that virtual environments may provide a new way to assess PTSD symptoms, while avoiding at least some of the limitations associated with symptom self-report, and thus might be a useful complement to questionnaire or clinical interview, potentially facilitating both diagnosis and evaluation of treatment efficacy.

Increased generalization of learned associations is related to re-experiencing symptoms in veterans with symptoms of post-traumatic stress.

One interpretation of re-experiencing symptoms in post-traumatic stress disorder (PTSD) is that memories related to emotional information are stored strongly, but with insufficient specificity, so that stimuli which are minimally related to the traumatic event are sufficient to trigger recall. If so, re-experiencing symptoms may reflect a general bias against encoding background information during a learning experience, and this tendency might not be limited to learning about traumatic or even autobiographical events. To test this possibility, we administered a discrimination-and-transfer task to 60 Veterans (11.2% female, mean age 54.0 years) self-assessed for PTSD symptoms in order to examine whether re-experiencing symptoms were associated with increased generalization following associative learning. The discrimination task involved learning to choose the rewarded object from each of six object pairs; each pair differed in color or shape but not both. In the transfer phase, the irrelevant feature in each pair was altered. Regression analysis revealed no relationships between re-experiencing symptoms and initial discrimination learning. However, re-experiencing symptom scores contributed to the prediction of transfer performance. Other PTSD symptom clusters (avoidance/numbing, hyperarousal) did not account for significant additional variance. The results are consistent with an emerging interpretation of re-experiencing symptoms as reflecting a learning bias that favors generalization at the expense of specificity. Future studies will be needed to determine whether this learning bias may pre-date and confer risk for, re-experiencing symptoms in individuals subsequently exposed to trauma, or emerges only in the wake of trauma exposure and PTSD symptom development.

Hippocampal BOLD response during category learning predicts subsequent performance on transfer generalization.

To test a prediction of our previous computational model of cortico-hippocampal interaction (Gluck and Myers [1993, 2001]) for characterizing individual differences in category learning, we studied young healthy subjects using an fMRI-adapted category-learning task that has two phases, an initial phase in which associations are learned through trial-and-error feedback followed by a generalization phase in which previously learned rules can be applied to novel associations (Myers et al. [2003]). As expected by our model, we found a negative correlation between learning-related hippocampal responses and accuracy during transfer, demonstrating that hippocampal adaptation during learning is associated with better behavioral scores during transfer generalization. In addition, we found an inverse relationship between Blood Oxygenation Level Dependent (BOLD) activity in the striatum and that in the hippocampal formation and the orbitofrontal cortex during the initial learning phase. Conversely, activity in the dorsolateral prefrontal cortex, orbitofrontal cortex and parietal lobes dominated over that of the hippocampal formation during the generalization phase. These findings provide evidence in support of theories of the neural substrates of category learning which argue that the hippocampal region plays a critical role during learning for appropriately encoding and representing newly learned information so that that this learning can be successfully applied and generalized to subsequent novel task demands.

Acquired equivalence in U.S. veterans with symptoms of posttraumatic stress: reexperiencing symptoms are associated with greater generalization.

The severity and number of reexperiencing symptoms (e.g., flashbacks) show considerable variability across individuals with posttraumatic stress disorder (PTSD). One interpretation of reexperiencing symptoms invokes generalization: Specifically, the traumatic memory may be stored in such a way that neutral stimuli that only vaguely resemble some feature of the traumatic event are sufficient to trigger the memory. If this is the case, then individuals with higher levels of reexperiencing symptoms might show greater generalization, even in contexts unrelated to trauma. In the current study, an acquired equivalence test was used to assess associative learning and generalization in 114 U.S. veterans who were also given a test of declarative memory. PTSD symptoms were rated by the veteran. After adjusting for demographic variables, psychoactive medication use, and initial learning, regression analyses showed that the number of PTSD reexperiencing symptoms significantly improved the model for generalization (ß = -.23, R(2) = .34) but not associative learning or declarative memory. The results support the idea that generalization is linked to reexperiencing symptoms, is not limited to learning about traumatic events, and can emerge even in a relatively innocuous computer-based learning task.

Impairment in recognition memory may be associated with near-term risk for suicide attempt in a high-risk sample.

INTRODUCTION: Prior work has implicated several neurocognitive domains, including memory, in patients with a history of prior suicide attempt. The current study evaluated whether a delayed recognition test could enhance prospective prediction of near-term suicide outcomes in a sample of patients at high-risk for suicide. METHODS: 132 Veterans at high-risk for suicide completed a computer-based recognition memory test including semantically-related and -unrelated words. Outcomes were coded as actual suicide attempt (ASA), other suicide-related event (OtherSE) such as aborted/interrupted attempt or preparatory behavior, or neither (noSE), within 90 days after testing. RESULTS: Reduced performance was a significant predictor of upcoming ASA, but not OtherSE, after controlling for standard clinical variables such as current suicidal ideation and history of prior suicide attempt. However, compared to the noSE reference group, the OtherSE group showed a reduction in the expected benefit of semantic relatedness in recognizing familiar words. A computational model, the drift diffusion model (DDM), to explore latent cognitive processes, revealed the OtherSE group had decreased decisional efficiency for semantically-related compared to semantically-unrelated familiar words. LIMITATIONS: This study was a secondary analysis of an existing dataset, involving participants in a treatment trial, and requires replication; ~10 % of the sample was excluded from analysis due to failure to master the practice tasks and/or apparent noncompliance. CONCLUSION: Impairments in recognition memory may be associated with near-term risk for suicide attempt, and may provide a tool to improve prediction of when at-risk individuals may be transitioning into a period of heightened risk for suicide attempt.

Initial evaluation of a personalized advantage index to determine which individuals may benefit from mindfulness-based cognitive therapy for suicide prevention.

OBJECTIVE: Develop and evaluate a treatment matching algorithm to predict differential treatment response to Mindfulness-Based Cognitive Therapy for suicide prevention (MBCT-S) versus enhanced treatment-as-usual (eTAU). METHODS: Analyses used data from Veterans at high-risk for suicide assigned to either MBCT-S (n = 71) or eTAU (n = 69) in a randomized clinical trial. Potential predictors (n = 55) included available demographic, clinical, and neurocognitive variables. Random forest models were used to predict risk of suicidal event (suicidal behaviors, or ideation resulting in hospitalization or emergency department visit) within 12 months following randomization, characterize the prediction, and develop a Personalized Advantage Index (PAI). RESULTS: A slightly better prediction model emerged for MBCT-S (AUC = 0.70) than eTAU (AUC = 0.63). Important outcome predictors for participants in the MBCT-S arm included PTSD diagnosis, decisional efficiency on a neurocognitive task (Go/No-Go), prior-year mental health residential treatment, and non-suicidal self-injury. Significant predictors for participants in the eTAU arm included past-year acute psychiatric hospitalizations, past-year outpatient psychotherapy visits, past-year suicidal ideation severity, and attentional control (indexed by Stroop task). A moderation analysis showed that fewer suicidal events occurred among those randomized to their PAI-indicated optimal treatment. CONCLUSIONS: PAI-guided treatment assignment may enhance suicide prevention outcomes. However, prior to real-world application, additional research is required to improve model accuracy and evaluate model generalization.

Multi-modal risk factors differentiate suicide attempters from ideators in military veterans with major depressive disorder.

BACKGROUND: The suicide rate for United States military veterans is 1.5× higher than that of non-veterans. To meaningfully advance suicide prevention efforts, research is needed to delineate factors that differentiate veterans with suicide attempt/s, particularly in high-risk groups, e.g., major depressive disorder (MDD), from those with suicidal ideation (no history of attempt/s). The current study aimed to identify clinical, neurocognitive, and neuroimaging variables that differentiate suicide-severity groups in veterans with MDD. METHODS: Sixty-eight veterans with a DSM-5 diagnosis of MDD, including those with no ideation or suicide attempt (N = 21; MDD-SI/SA), ideation-only (N = 17; MDD + SI), and one-or-more suicide attempts (N = 30; MDD + SA; aborted, interrupted, actual attempts), participated in this study. Participants underwent a structured diagnostic interview, neurocognitive assessment, and 3 T-structural/diffusion tensor magnetic-resonance-imaging (MRI). Multinomial logistic regression models were conducted to identify variables that differentiated groups with respect to the severity of suicidal behavior. RESULTS: Relative to veterans with MDD-SI/SA, those with MDD + SA had significantly higher left cingulum fractional anisotropy, decreased attentional control on emotional-Stroop, and faster response time with intact accuracy on Go/No-Go. Relative to MDD + SI, MDD + SA had higher left cingulum fractional anisotropy and faster response time with intact accuracy on Go/No-Go. LIMITATIONS: Findings are based on retrospective, cross-sectional data and cannot identify causal relationships. Also, a healthy control group was not included given the study's focus on differentiating suicide profiles in MDD. CONCLUSIONS: This study suggests that MRI and neurocognition differentiate veterans with MDD along the suicide-risk spectrum and could inform suicide-risk stratification and prevention efforts in veterans and other vulnerable populations.

Enhanced avoidance learning in behaviorally inhibited young men and women.

Behavioral inhibition (BI) is a temperamental tendency to avoid or withdraw from novel social and nonsocial situations, and has been shown to predispose individuals to anxiety disorders. However, adequate means to assess individual differences in avoidance learning in humans are presently limited. Here, we tested whether individuals with high self-reported BI show faster associative learning on a purely cognitive task and whether such inhibited individuals are more prone to avoid aversive outcomes. In Experiment 1, we tested 74 healthy undergraduate students (mean age 19.5 years; 55.4% female) on a computer-based probabilistic classification task, where participants were asked to classify four distinct visual stimuli into two categories. Two stimuli were associated with reward (point gain) and two were associated with punishment (point loss). In Experiment 2, 79 participants from the same population (mean age 19.8 years; 62% female) were tested on a novel modification of the same task, where they also had the option to opt out of responding on each trial, thus avoiding any chance of being punished (or rewarded) on that trial. Results show that inhibited participants demonstrated better associative learning in Experiment 1, while exhibiting a greater tendency to opt out in Experiment 2 (repeated-measures analysis of variance, main effects of BI, both p < 0.05). These results indicate that the facilitated classically conditioned learning previously observed in inhibited individuals can be extended to a cognitive task, and also highlight a specific preference in inhibited individuals for withdrawal ("opting out") as a response strategy, when multiple strategies are available to avoid punishment.

A model of amygdala-hippocampal-prefrontal interaction in fear conditioning and extinction in animals.

Empirical research has shown that the amygdala, hippocampus, and ventromedial prefrontal cortex (vmPFC) are involved in fear conditioning. However, the functional contribution of each brain area and the nature of their interactions are not clearly understood. Here, we extend existing neural network models of the functional roles of the hippocampus in classical conditioning to include interactions with the amygdala and prefrontal cortex. We apply the model to fear conditioning, in which animals learn physiological (e.g. heart rate) and behavioral (e.g. freezing) responses to stimuli that have been paired with a highly aversive event (e.g. electrical shock). The key feature of our model is that learning of these conditioned responses in the central nucleus of the amygdala is modulated by two separate processes, one from basolateral amygdala and signaling a positive prediction error, and one from the vmPFC, via the intercalated cells of the amygdala, and signaling a negative prediction error. In addition, we propose that hippocampal input to both vmPFC and basolateral amygdala is essential for contextual modulation of fear acquisition and extinction. The model is sufficient to account for a body of data from various animal fear conditioning paradigms, including acquisition, extinction, reacquisition, and context specificity effects. Consistent with studies on lesioned animals, our model shows that damage to the vmPFC impairs extinction, while damage to the hippocampus impairs extinction in a different context (e.g., a different conditioning chamber from that used in initial training in animal experiments). We also discuss model limitations and predictions, including the effects of number of training trials on fear conditioning.

{alpha}-Synuclein gene duplication impairs reward learning.

alpha-Synuclein (SNCA) plays an important role in the regulation of dopaminergic neurotransmission and neurodegeneration in Parkinson disease. We investigated reward and punishment learning in asymptomatic carriers of a rare SNCA gene duplication who were healthy siblings of patients with Parkinson disease. Results revealed that healthy SNCA duplication carriers displayed impaired reward and intact punishment learning compared with noncarriers. These results demonstrate that a copy number variation of the SNCA gene is associated with selective impairments on reinforcement learning in asymptomatic carriers without the motor symptoms of Parkinson disease.

Altered learning and transfer abilities in Korsakoff's syndrome depending on task complexity.

Korsakoff's syndrome (KS) is characterized by episodic memory impairment due to damage to the medial diencephalic structures. Although commonly associated with chronic alcoholism, starvation due to the hunger strike is one of its nonalcoholic causes. Learning the stimulus-response associations and transferring the just-learned associations to novel combinations were previously tested by specific tasks in memory-impaired patients with hippocampal, basal forebrain, and basal ganglia damage. To add to this previous research, we aimed to use the same tasks in a group of patients with hunger strike-related KS presenting a stable isolated amnestic profile. Twelve patients with hunger strike-related KS and matched healthy controls were tested in two tasks varying in task complexity. Each task included two phases: the initial phase is feedback-based learning of (simple vs. complex) stimulus-response associations, and the following phase is transfer generalization (in the presence vs. absence of feedback). On a task involving simple associations, five patients with KS failed to learn the associations, while the other seven patients showed intact learning and transfer. On the other task involving more complex associations, seven patients showed slower learning and failed at transfer generalization, whereas the other five patients failed even at the acquisition phase. These findings of a task-complexity-related impairment on associative learning and transfer represent a distinct pattern from the spared learning but impaired transfer previously observed on these tasks in patients with medial temporal lobe amnesia.