A Neural Index of Inefficient Evidence Accumulation in Dyslexia Underlying Slow Perceptual Decision Making

Cortex ◽  
2021 ◽  
Author(s):  
Nicole R. Stefanac ◽  
Shou-Han Zhou ◽  
Megan M. Spencer-Smith ◽  
Redmond O’Connell ◽  
Mark A. Bellgrove
2021 ◽  
Vol 32 (9) ◽  
pp. 1494-1509
Author(s):  
Yuan Chang Leong ◽  
Roma Dziembaj ◽  
Mark D’Esposito

People’s perceptual reports are biased toward percepts they are motivated to see. The arousal system coordinates the body’s response to motivationally significant events and is well positioned to regulate motivational effects on perceptual judgments. However, it remains unclear whether arousal would enhance or reduce motivational biases. Here, we measured pupil dilation as a measure of arousal while participants ( N = 38) performed a visual categorization task. We used monetary bonuses to motivate participants to perceive one category over another. Even though the reward-maximizing strategy was to perform the task accurately, participants were more likely to report seeing the desirable category. Furthermore, higher arousal levels were associated with making motivationally biased responses. Analyses using computational models suggested that arousal enhanced motivational effects by biasing evidence accumulation in favor of desirable percepts. These results suggest that heightened arousal biases people toward what they want to see and away from an objective representation of the environment.


2019 ◽  
Vol 31 (7) ◽  
pp. 1044-1053 ◽  
Author(s):  
Gerard M. Loughnane ◽  
Méadhbh B. Brosnan ◽  
Jessica J. M. Barnes ◽  
Angela Dean ◽  
Sanjay L. Nandam ◽  
...  

Recent behavioral modeling and pupillometry studies suggest that neuromodulatory arousal systems play a role in regulating decision formation but neurophysiological support for these observations is lacking. We employed a randomized, double-blinded, placebo-controlled, crossover design to probe the impact of pharmacological enhancement of catecholamine levels on perceptual decision-making. Catecholamine levels were manipulated using the clinically relevant drugs methylphenidate and atomoxetine, and their effects were compared with those of citalopram and placebo. Participants performed a classic EEG oddball paradigm that elicits the P3b, a centro-parietal potential that has been shown to trace evidence accumulation, under each of the four drug conditions. We found that methylphenidate and atomoxetine administration shortened RTs to the oddball targets. The neural basis of this behavioral effect was an earlier P3b peak latency, driven specifically by an increase in its buildup rate without any change in its time of onset or peak amplitude. This study provides neurophysiological evidence for the catecholaminergic enhancement of a discrete aspect of human decision-making, that is, evidence accumulation. Our results also support theoretical accounts suggesting that catecholamines may enhance cognition via increases in neural gain.


2017 ◽  
Author(s):  
Onno van der Groen ◽  
Matthew F. Tang ◽  
Nicole Wenderoth ◽  
Jason B. Mattingley

Summary:Perceptual decision-making relies on the gradual accumulation of noisy sensory evidence until a specified boundary is reached and an appropriate response is made. It might be assumed that adding noise to a stimulus, or to the neural systems involved in its processing, would interfere with the decision process. But it has been suggested that adding an optimal amount of noise can, under appropriate conditions, enhance the quality of subthreshold signals in nonlinear systems, a phenomenon known as stochastic resonance. Here we asked whether perceptual decisions obey these stochastic resonance principles by adding noise directly to the visual cortex using transcranial random noise stimulation (tRNS) while participants judged the direction of motion in foveally presented random-dot motion arrays. Consistent with the stochastic resonance account, we found that adding tRNS bilaterally to visual cortex enhanced decision-making when stimuli were just below, but not well below or above, perceptual threshold. We modelled the data under a drift diffusion framework to isolate the specific components of the multi-stage decision process that were influenced by the addition of neural noise. This modelling showed that tRNS increased drift rate, which indexes the rate of evidence accumulation, but had no effect on bound separation or non-decision time. These results were specific to bilateral stimulation of visual cortex; control experiments involving unilateral stimulation of left and right visual areas showed no influence of random noise stimulation. Our study is the first to provide causal evidence that perceptual decision-making is susceptible to a stochastic resonance effect induced by tRNS, and that this effect arises from selective enhancement of the rate of evidence accumulation for sub-threshold sensory events.


Author(s):  
Loughnane Gerard ◽  
Newman Daniel ◽  
Bellgrove Mark ◽  
Lalor Edmund ◽  
Kelly Simon ◽  
...  

2017 ◽  
Author(s):  
Paul G. Middlebrooks ◽  
Bram B. Zandbelt ◽  
Gordon D. Logan ◽  
Thomas J. Palmeri ◽  
Jeffrey D. Schall

Perceptual decision-making, studied using two-alternative forced-choice tasks, is explained by sequential sampling models of evidence accumulation, which correspond to the dynamics of neurons in sensorimotor structures of the brain1 2. Response inhibition, studied using stop-signal (countermanding) tasks, is explained by a race model of the initiation or canceling of a response, which correspond to the dynamics of neurons in sensorimotor structures3 4. Neither standard model accounts for performance of the other task. Sequential sampling models incorporate response initiation as an uninterrupted non-decision time parameter independent of task-related variables. The countermanding race model does not account for the choice process. Here we show with new behavioral, neural and computational results that perceptual decision making of varying difficulty can be countermanded with invariant efficiency, that single prefrontal neurons instantiate both evidence accumulation and response inhibition, and that an interactive race between two GO and one STOP stochastic accumulator fits countermanding choice behavior. Thus, perceptual decision-making and response control, previously regarded as distinct mechanisms, are actually aspects of more flexible behavior supported by a common neural and computational mechanism. The identification of this aspect of decision-making with response production clarifies the component processes of decision-making.


2018 ◽  
Author(s):  
Jochem van Kempen ◽  
Gerard M. Loughnane ◽  
Daniel P. Newman ◽  
Simon P. Kelly ◽  
Alexander Thiele ◽  
...  

AbstractThe timing and accuracy of perceptual decision making is exquisitely sensitive to fluctuations in arousal. Although extensive research has highlighted the role of neural evidence accumulation in forming decisions, our understanding of how arousal impacts these processes remains limited. Here we isolated electrophysiological signatures of evidence accumulation alongside signals reflecting target selection, attentional engagement and motor output and examined their modulation as a function of both tonic and phasic arousal, indexed by baseline and task-evoked pupil diameter, respectively. For both pupillometric measures, the relationship with reaction time was best described by a second-order, U-shaped, polynomial. Additionally, the two pupil measures were predictive of a unique set of EEG signatures that together represent multiple information processing steps of perceptual decision-making, including evidence accumulation. Finally, we found that behavioural variability associated with fluctuations in both tonic and phasic arousal was largely mediated by variability in evidence accumulation.


2018 ◽  
Author(s):  
Fredrik Allenmark ◽  
Hermann J. Müller ◽  
Zhuanghua Shi

AbstractMany previous studies on visual search have reported inter-trial effects, that is, observers respond faster when some target property, such as a defining feature or dimension, or the response associated with the target repeats versus changes across consecutive trial episodes. However, what processes drive these inter-trial effects is still controversial. Here, we investigated this question using a combination of Bayesian modeling of belief updating and evidence accumulation modeling in perceptual decision-making. In three visual singleton (‘pop-out’) search experiments, we explored how the probability of the response-critical states of the search display (e.g., target presence/absence) and the repetition/switch of the target-defining dimension (color/ orientation) affect reaction time distributions. The results replicated the mean reaction time (RT) inter-trial and dimension repetition/switch effects that have been reported in previous studies. Going beyond this, to uncover the underlying mechanisms, we used the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model to explain the RT distributions in terms of decision bias (starting point) and information processing speed (evidence accumulation rate). We further investigated how these different aspects of the decision-making process are affected by different properties of stimulus history, giving rise to dissociable inter-trial effects. We approached this question by (i) combining each perceptual decision making model (DDM or LATER) with different updating models, each specifying a plausible rule for updating of either the starting point or the rate, based on stimulus history, and (ii) comparing every possible combination of trial-wise updating mechanism and perceptual decision model in a factorial model comparison. Consistently across experiments, we found that the (recent) history of the response-critical property influences the initial decision bias, while repetition/switch of the target-defining dimension affects the accumulation rate, likely reflecting an implicit ‘top-down’ modulation process. This provides strong evidence of a disassociation between response- and dimension-based inter-trial effects.


2020 ◽  
Author(s):  
Daniel Feuerriegel ◽  
Tessel Blom ◽  
Hinze Hogendoorn

Our brains can represent expected future states of our sensory environment. Recent work has shown that, when we expect a specific stimulus to appear at a specific time, we can predictively generate neural representations of that stimulus even before it is physically presented. These observations raise two exciting questions: Are pre-activated sensory representations used for perceptual decision-making? And, are there instances in which we transiently perceive an expected stimulus that does not actually appear? To address these questions, we propose that pre-activated neural representations provide sensory evidence that is used for perceptual decision-making. This can be understood within the framework of the Diffusion Decision Model as an early accumulation of decision evidence in favour of the expected percept. Our proposal makes novel predictions relating to expectation effects on neural markers of decision evidence accumulation, and also provides an explanation for why we do not typically perceive stimuli that are expected, but do not appear.


2011 ◽  
Vol 106 (5) ◽  
pp. 2383-2398 ◽  
Author(s):  
Taosheng Liu ◽  
Timothy J. Pleskac

Sequential sampling models provide a useful framework for understanding human decision making. A key component of these models is an evidence accumulation process in which information is accrued over time to a threshold, at which point a choice is made. Previous neurophysiological studies on perceptual decision making have suggested accumulation occurs only in sensorimotor areas involved in making the action for the choice. Here we investigated the neural correlates of evidence accumulation in the human brain using functional magnetic resonance imaging (fMRI) while manipulating the quality of sensory evidence, the response modality, and the foreknowledge of the response modality. We trained subjects to perform a random dot motion direction discrimination task by either moving their eyes or pressing buttons to make their responses. In addition, they were cued about the response modality either in advance of the stimulus or after a delay. We isolated fMRI responses for perceptual decisions in both independently defined sensorimotor areas and task-defined nonsensorimotor areas. We found neural signatures of evidence accumulation, a higher fMRI response on low coherence trials than high coherence trials, primarily in saccade-related sensorimotor areas (frontal eye field and intraparietal sulcus) and nonsensorimotor areas in anterior insula and inferior frontal sulcus. Critically, such neural signatures did not depend on response modality or foreknowledge. These results help establish human brain areas involved in evidence accumulation and suggest that the neural mechanism for evidence accumulation is not specific to effectors. Instead, the neural system might accumulate evidence for particular stimulus features relevant to a perceptual task.


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