The ease and sureness of a decision: evidence accumulation of conflict and uncertainty.

The likelihood of an outcome (uncertainty or sureness) and the similarity between choices (conflict or ease of a decision) are often critical to decision-making. We often ask ourselves: how likely are we to win or lose? And how different is this option's likelihood from the other? Uncertainty is a characteristic of the stimulus and conflict between stimuli, but these dissociable processes are often confounded. Here, applying a novel hierarchical drift diffusion approach, we study their interaction using a sequential learning task in healthy volunteers and pathological groups characterized by compulsive behaviours, by posing it as an evidence accumulation problem. The variables, Conflict (difficult or easy; difference between reward probabilities of the stimuli) and Uncertainty (low, medium or high; inverse U-shaped probability-uncertainty function) were then used to extract threshold ('a', amount of evidence accumulated before making a decision) and drift rate ('v', information processing speed) parameters. Critically, when a decision was both difficult (high conflict) and uncertain, relative to other conditions, healthy volunteers unexpectedly accumulated less evidence with lower decision thresholds and accuracy rates at chance levels. In contrast, patients with obsessive-compulsive disorder had slower processing speeds during these difficult uncertain decisions; yet, despite this more cautious approach, performed suboptimally with poorer accuracy relative to healthy volunteers below that of chance level. Thus, faced with a difficult uncertain decision, healthy controls are capable of rapid possibly random decisions, displaying almost a willingness to 'walk away', whereas those with obsessive compulsive disorder become more deliberative and cautious but despite appearing to learn the differential contingencies, still perform poorly. These observations might underlie disordered behaviours characterized by pathological uncertainty or doubt despite compulsive checking with impaired performance. In contrast, alcohol-dependent subjects show a different pattern relative to healthy controls with difficulties in adjusting their behavioural patterns with slower drift rates or processing speed despite decisions being easy or low conflict. We emphasize the multidimensional nature of compulsive behaviours and the utility of computational models in detecting subtle underlying processes relative to behavioural measures. These observations have implications for targeted behavioural interventions for specific cognitive impairments across psychiatric disorders

Electrode Position and Current Amplitude Modulate Impulsivity after Subthalamic Stimulation in Parkinsons Disease—A Computational Study

Background: Subthalamic Nucleus Deep Brain Stimulation (STN-DBS) is highly effective in alleviating motor symptoms of Parkinson’s disease (PD) which are not optimally controlled by dopamine replacement therapy. Clinical studies and reports suggest that STN-DBS may result in increased impulsivity and de novo impulse control disorders (ICD)Objective/Hypothesis: We aimed to compare performance on a decision making task, the Iowa Gambling Task (IGT), in healthy conditions (HC), untreated and medically-treated PD conditions with and without STN stimulation. We hypothesized that the position of electrode and stimulation current modulate impulsivity after STN-DBS.Methods: We built a computational spiking network model of basal ganglia (BG) and compared the model’s STN output with STN activity in PD. Reinforcement learning methodology was applied to simulate IGT performance under various conditions of dopaminergic and STN stimulation where IGT total and bin scores were compared among various conditions.Results: The computational model reproduced neural activity observed in normal and PD conditions. Untreated and medically-treated PD conditions had lower total IGT scores (higher impulsivity) compared to HC (P<0.0001). The electrode position that happens to selectively stimulate the part of the STN corresponding to an advantageous panel on IGT resulted in de-selection of that panel and worsening of performance (P<0.0001). Supratherapeutic stimulation amplitudes also worsened IGT performance (P<0.001). Conclusion(s): In our computational model, STN stimulation led to impulsive decision making in IGT in PD condition. Electrode position and stimulation current influenced impulsivity which may explain the variable effects of STN-DBS reported in patients

Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder.

Risk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift-diffusion model to extract parameters such as threshold ('a'-amount of evidence accumulated before making a decision), drift rate ('v'-information processing speed) and response bias ('z' apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population.Wellcome Trust Intermediate Fellowship (093881/Z/10/Z) to Dr. Harrison, Brighton and Sussex Medical School and the Dr. Mortimer and Dame Theresa Sackler Foundation. Dr. Voon is supported by a Medical Research Council Senior Clinical Fellowship (MR/P008747/1)

A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity

Parkinson's disease (PD) is a neurodegenerative disease associated with progressive and inexorable loss of dopaminergic cells in Substantia Nigra pars compacta (SNc). Although many mechanisms have been suggested, a decisive root cause of this cell loss is unknown. A couple of the proposed mechanisms, however, show potential for the development of a novel line of PD therapeutics. One of these mechanisms is the peculiar metabolic vulnerability of SNc cells compared to other dopaminergic clusters; the other is the SubThalamic Nucleus (STN)-induced excitotoxicity in SNc. To investigate the latter hypothesis computationally, we developed a spiking neuron network-model of SNc-STN-GPe system. In the model, prolonged stimulation of SNc cells by an overactive STN leads to an increase in ‘stress' variable; when the stress in a SNc neuron exceeds a stress threshold, the neuron dies. The model shows that the interaction between SNc and STN involves a positive-feedback due to which, an initial loss of SNc cells that crosses a threshold causes a runaway-effect, leading to an inexorable loss of SNc cells, strongly resembling the process of neurodegeneration. The model further suggests a link between the two aforementioned mechanisms of SNc cell loss. Our simulation results show that the excitotoxic cause of SNc cell loss might initiate by weak-excitotoxicity mediated by energy deficit, followed by strong-excitotoxicity, mediated by a disinhibited STN. A variety of conventional therapies were simulated to test their efficacy in slowing down SNc cell loss. Among them, glutamate inhibition, dopamine restoration, subthalamotomy and deep brain stimulation showed superior neuroprotective-effects in the proposed model

A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity.

Parkinson's disease (PD) is a neurodegenerative disease associated with progressive and inexorable loss of dopaminergic cells in Substantia Nigra pars compacta (SNc). Although many mechanisms have been suggested, a decisive root cause of this cell loss is unknown. A couple of the proposed mechanisms, however, show potential for the development of a novel line of PD therapeutics. One of these mechanisms is the peculiar metabolic vulnerability of SNc cells compared to other dopaminergic clusters; the other is the SubThalamic Nucleus (STN)-induced excitotoxicity in SNc. To investigate the latter hypothesis computationally, we developed a spiking neuron network-model of SNc-STN-GPe system. In the model, prolonged stimulation of SNc cells by an overactive STN leads to an increase in 'stress' variable; when the stress in a SNc neuron exceeds a stress threshold, the neuron dies. The model shows that the interaction between SNc and STN involves a positive-feedback due to which, an initial loss of SNc cells that crosses a threshold causes a runaway-effect, leading to an inexorable loss of SNc cells, strongly resembling the process of neurodegeneration. The model further suggests a link between the two aforementioned mechanisms of SNc cell loss. Our simulation results show that the excitotoxic cause of SNc cell loss might initiate by weak-excitotoxicity mediated by energy deficit, followed by strong-excitotoxicity, mediated by a disinhibited STN. A variety of conventional therapies were simulated to test their efficacy in slowing down SNc cell loss. Among them, glutamate inhibition, dopamine restoration, subthalamotomy and deep brain stimulation showed superior neuroprotective-effects in the proposed model

Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder

Abstract: Risk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift–diffusion model to extract parameters such as threshold (‘a’—amount of evidence accumulated before making a decision), drift rate (‘v’—information processing speed) and response bias (‘z’ apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population

Impulsivity and craving in subjects with opioid use disorder on methadone maintenance treatment.

BACKGROUND: Methadone maintenance treatment (MMT) is effective in decreasing opioid use or facilitating abstinence. Previous studies using small opioid use disorder samples suggest that cognitive impairments including impulsivity and executive functions may partially improve on MMT, but a range of deficits may persist. However, systematic assessments with larger samples are needed to confirm the profile of cognitive functions on MMT. METHODS: We assessed four types of impulsivity (delay discounting, reflection impulsivity, risk taking and motoric impulsivity), executive functioning (spatial working memory, paired associative learning and strategic planning) and drug cue-induced craving in a relatively large population (115 MMT patients, 115 healthy controls). The relationships between impulsivity, drug cue-induced craving and addiction-related variables were also assessed. RESULTS: Delay discounting, as well as drug cue-induced craving was increased in patients, while motoric impulsivity was lower than in controls. Paired associative learning was additionally impaired, which was explained by increased depression and anxiety levels in patients. Within the MMT group, the delay discounting and drug-cue induced craving scores were positively correlated with self-reported urgency, but unrelated to methadone dosage, duration on methadone, withdrawal symptoms, or presence of nicotine dependence. CONCLUSIONS: Our findings highlight increased delay discounting and cue-induced craving in MMT patients suggesting a potential role for trait effects in delay discounting. Although previous smaller studies have shown impaired executive function, in our large sample size on chronic MMT we only observed impaired associative learning related to depressive and anxiety symptoms highlighting a role for managing comorbid symptoms to further optimize cognitive function

Addictions NeuroImaging Assessment (ANIA): Towards an integrative framework for alcohol use disorder.

Alcohol misuse and addiction are major international public health issues. Addiction can be characterized as a disorder of aberrant neurocircuitry interacting with environmental, genetic and social factors. Neuroimaging in alcohol misuse can thus provide a critical window into underlying neural mechanisms, highlighting possible treatment targets and acting as clinical biomarkers for predicting risk and treatment outcomes. This neuroimaging review on alcohol misuse in humans follows the Addictions Neuroclinical Assessment (ANA) that proposes incorporating three functional neuroscience domains integral to the neurocircuitry of addiction: incentive salience and habits, negative emotional states, and executive function within the context of the addiction cycle. Here we review and integrate multiple imaging modalities focusing on underlying cognitive processes such as reward anticipation, negative emotionality, cue reactivity, impulsivity, compulsivity and executive function. We highlight limitations in the literature and propose a model forward in the use of neuroimaging as a tool to understanding underlying mechanisms and potential clinical applicability for phenotyping of heterogeneity and predicting risk and treatment outcomes

The molecular, cellular, and systems-level structure of the basal ganglia

This chapter provides a brief overview of the systems, cellular, and molecular structure of the various nuclei of basal ganglia (BG) such as striatum, STN, GPe, GPi, and the SNr including the various neurotransmitters impacting its function. We start with the system-level connection between cortex and BG and then cover the various cell types, receptors (such as dopaminergic, acetylcholine) present on each of the BG nuclei. The effect of Parkinson’s disease on their dynamics especially the STN-GPe oscillatory network is then discussed. The dopaminergic systems SNc and VTA are also covered in terms of their architecture and input-output synaptic projection patterns. Finally, a short intro to the multiple cortico-BG loops and their functional relevance is discussed. This brief overview helps provide background on BG structure, which is the basis of several models we present in this book

Replicable effect of cortical-paired associative stimulation on response inhibition as a function of age

How quickly we stop at a traffic light determines our survival. Similarly, how efficiently one can dodge a craving thought for a pint of beer could define one's relapse probability. Response inhibition, a form of impulsivity, measures one's ability to interrupt an ongoing action, and is central to neuropsychiatric disorders[1, 2]. Using cortico-cortical paired associative stimulation (cc-PAS) with transcranial magnetic (TMS) pulses, we targeted the right pre-supplementary motor area (preSMA) and right-inferior frontal cortex (rIFC). We previously showed an improvement in response inhibition as a function of age[3] using the stop-signal task[1]. Repeated pairs of pulses over two cortical regions induce changes in excitability and functional interaction due to spike time-dependent plasticity mechanisms[4]. Specifically, response inhibition improved in older individuals when the rIFC pulse preceded the preSMA pulse by 4milliseconds[3]. Here, we address the problem of reproducibility, a significant issue in TMS studies, by assessing the 4ms cc-PAS protocol in a different, larger group of healthy volunteers with a broader age range