Visual Hallucinations Are Characterized by Impaired Sensory Evidence Accumulation: Insights From Hierarchical Drift Diffusion Modeling in Parkinson’s Disease

O’Callaghan, Claire; Jm, Hall; Tomassini, Alessandro; Muller, Alana J.; Walpola, Ishan C.; Moustafa, Ahmed A.; Shine, James M.; Lewis, Simon J.G.

doi:10.1016/j.bpsc.2017.04.007

Cited by 60 publications

(82 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is possible that by modulating the decision threshold, STN-DBS could alter the bound for evidence accumulation and thus uncertainty in the representation of the reward environment (Herz et al, 2018;Pote et al, 2016). Further work employing drift diffusion modelling to quantify rates of evidence accumulation and decision boundaries after STN-DBS may be illuminating, having previously helped to elucidate the mechanisms underlying hallucinations in Parkinson's disease (O'Callaghan et al, 2017). Further work is also required to determine if the site of stimulation affects the magnitude of changes in uncertainty estimation observed here and specifically if cognitive-associative or sensorimotor regions of the STN are most implicated in these shifts.…”

Section: Discussionmentioning

confidence: 99%

Subjective estimates of uncertainty during gambling and impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

Paliwal

Mosley

Breakspear

et al. 2018

Preprint

View full text Add to dashboard Cite

Subthalamic deep brain stimulation (STN-DBS) for Parkinson's disease may modulate chronometric and instrumental aspects of choice behaviour, including motor inhibition, decisional slowing, and value sensitivity. However, it is not well known whether STN-DBS affects more complex aspects of decision-making, such as the influence of subjective estimates of uncertainty on choices. In this study, thirty-eight participants with Parkinson's disease played a virtual casino prior to subthalamic DBS (whilst 'on' medication) and again, threemonths postoperatively (whilst 'on' stimulation). At the group level, there was a small but statistically significant postoperative decrease in impulsivity, as quantified by the Barratt Impulsiveness Scale (BIS). The gambling behaviour of participants (bet increases, slot machine switches and double or nothing gambles) was associated with this self-reported measure of impulsivity. However, there was a large variance in outcome amongst participants, and we were interested in whether individual differences in subjective estimates of uncertainty (specifically, volatility) were related to differences in pre-and postoperative impulsivity. To examine these individual differences, we fit a computational model (the Hierarchical Gaussian Filter, HGF), to choices made during slot machine game play as well as a simpler reinforcement learning model based on the Rescorla-Wagner formalism. The HGF was superior in accounting for the behaviour of our participants, suggesting that participants incorporated beliefs about environmental uncertainty when updating their beliefs about gambling outcome and translating these beliefs into action. A specific aspect of subjective uncertainty, the participant's estimate of the tendency of the slot machine's winning probability to change (volatility), increased subsequent to DBS. Additionally, the decision temperature of the response model decreased post-operatively, implying greater stochasticity in the belief-to-choice mapping of participants.Model parameter estimates were significantly associated with impulsivity; specifically, increased uncertainty was related to increased postoperative impulsivity. Moreover, changes in these parameter estimates were significantly associated with the maximum post-operative change in impulsivity over a six month follow up period. Our findings suggest that impulsivity in persons with Parkinson's disease may be influenced by subjective estimates of uncertainty (environmental volatility) and implicate a role for the subthalamic nucleus in the modulation of outcome certainty. Furthermore, our work outlines a possible approach to characterising those persons who become more impulsive after subthalamic DBS, an intervention in which non-motor outcomes can be highly variable.3 2014). For example, consider deciding how to invest a sum of money in order to maximise profit. In a dependable economic setting with a reliable government, low unemployment, steadily rising house prices and a stable stock market, one might be confident that...

show abstract

Section: Discussionmentioning

confidence: 99%

Subjective estimates of uncertainty during gambling and impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

Paliwal

Mosley

Breakspear

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Behavioural performance on the Go/NoGo task was calculated by summing scores for the task conditions, and by modelling latent task variables using the hBayesDM package (hierarchical Bayesian modeling of Decision Making tasks) for R (version 0.5.0 on MacOS High Sierra version 10.13.1) developed by Ahn et al (2017). We used this approach to generate posterior distributions of the parameters characterising task performance to improve the balance of within-subject and between-subject random effects, whilst also taking into account within-subject variability and group-level similarities (O'Callaghan et al, 2017). Full information on the details of the modelling parameters and model fitting and comparison can be found in the Supplementary Material.…”

Section: Computational Modelling: Hbayesdmmentioning

confidence: 99%

Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population

Montagnese

Knolle

Haarsma

et al. 2019

Preprint

View full text Add to dashboard Cite

AbstractBackgroundSchizophrenia is a complex disorder in which the causal relations between risk genes and observed clinical symptoms are not well understood and the explanatory gap is too wide to be clarified without considering an intermediary level. Thus, we aimed to test the hypothesis of a pathway from molecular polygenic influence to clinical presentation occurring via deficits in reinforcement learning.MethodsWe administered a reinforcement learning task (Go/NoGo) that measures reinforcement learning and the effect of Pavlovian bias on decision making. We modelled the behavioural data with a hierarchical Bayesian approach (hBayesDM) to decompose task performance into its underlying learning mechanisms. Study 1 included controls (n= 29, F|M=0.81), At Risk Mental State for psychosis (ARMS, n= 23, F|M=0.35) and FEP (First-episode psychosis, n= 26, F|M=0.18). Study 2 included healthy adolescents (n= 735, F|M= 1.06), 390 of whom had their polygenic risk scores for schizophrenia (PRSs) calculated.ResultsPatients with FEP showed significant impairments in overriding Pavlovian conflict, a lower learning rate and a lower sensitivity to both reward and punishment. Less widespread deficits were observed in ARMS. PRSs did not significantly predict performance on the task in the general population, which only partially correlated with measures of psychopathology.ConclusionsReinforcement learning deficits are observed in first episode psychosis and, to some extent, in those at clinical risk for psychosis, and were not predicted by molecular genetic risk for schizophrenia in healthy individuals. The study does not support the role of reinforcement learning as an intermediate phenotype in psychosis.

show abstract

“…The orbitofrontal cortex (OFC) process coarse information projected from the visual cortex and provides an "initial guess" of an object's identity (21). Previous work in PD patients with VHs has shown that the accumulation of sensory evidence is slow and inefficient, which may result in an over-reliance on these top-down predictions (22). Importantly, top-down visual processing regions can modulate neural activity in early visual regions, with expected stimuli leading to reduced activity (23).Additionally, activity within the default mode network (DMN), a network involved in mediating endogenous perception, has shown to be increased during a misperception in this patient population (24).…”

mentioning

confidence: 99%

“…Importantly, top-down visual processing regions can modulate neural activity in early visual regions, with expected stimuli leading to reduced activity (23).Additionally, activity within the default mode network (DMN), a network involved in mediating endogenous perception, has shown to be increased during a misperception in this patient population (24). Therefore, VHs may arise when perceptual input is not properly integrated and internally generated images interfere with the perceptual process (22,(25)(26)(27).While functional neuroimaging studies have made significant contributions to our understanding (24,(28)(29)(30)(31), less is known about the involvement of white matter changes in the manifestation of VHs in PD. Experiments using diffusion tensor imaging (DTI) have reported altered white matter integrity in the optic nerve and optic radiation (32) as well as ascending tracts from the cholinergic nucleus basalis of Meynert to parietal and occipital cortical regions (33).…”

mentioning

confidence: 99%

See 1 more Smart Citation

Changes in structural network topology correlate with severity of hallucinatory behaviour in Parkinson’s disease

Hall

O’Callaghan

Muller

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

An inefficient integration between bottom-up visual input and higher-order visual processing regions is implicated in the manifestation of visual hallucinations (VH) inParkinson's disease (PD). Using graph theory, the current study aimed to investigate white matter contributions to this perceptual imbalance hypothesis. Twenty-nine PD patients reported their hallucinatory behaviour on a questionnaire and performed a behavioural test that has been shown to elicit misperceptions. A composite score derived from these measures was used as a proxy for hallucinations severity and was correlated to connectivity strength of the network using the Network Based Statistic approach. The results showed that the severity of VH was associated with reduced connectivity within a large sub-network. This network included the majority of the diverse club and showed overall greater between-and within-module scores, compared to nodes not associated with hallucination severity. Furthermore, a reduction in between-module connectivity in the lateral occipital cortex, insula and pars orbitalis, as well as decreased within-module connectivity in the prefrontal, somatosensory and primary visual cortices were associated with VH severity. In contrast, the severity of VH was associated with an increase in between-and withinmodule connectivity in the orbitofrontal and temporal cortex, as well as regions comprising the dorsal attentional and DMN. These results suggest that the severity of VHs is associated with marked alterations in structural network topology, highlighted by a reduction in connectivity strength across a large sub-network, as well as changes in participation across top-down visual processing centres, visual and attentional networks. Therefore, impaired integration across the perceptual hierarchy may result in the inefficient transfer of information that gives rise to VHs in PD.

show abstract

Visual Hallucinations Are Characterized by Impaired Sensory Evidence Accumulation: Insights From Hierarchical Drift Diffusion Modeling in Parkinson’s Disease

Cited by 60 publications

References 71 publications

Subjective estimates of uncertainty during gambling and impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

Subjective estimates of uncertainty during gambling and impulsivity after subthalamic deep brain stimulation for Parkinson’s disease

Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population

Changes in structural network topology correlate with severity of hallucinatory behaviour in Parkinson’s disease

Contact Info

Product

Resources

About