scholarly journals Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

2019 ◽  
Author(s):  
Dragan Rangelov ◽  
Jason B. Mattingley
Keyword(s):  
Decision Making ◽  
Brain Activity ◽  
Sensory Information ◽  
Neural Correlates ◽  
Attentional Selection ◽  
Adaptive Behaviour ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Sensory Inputs

AbstractThe ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize stimuli that are task-relevant and to attenuate potentially distracting sources of sensory information. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel ‘integrated’ decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used linear regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.

scholarly journals Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions

2020 ◽  
Vol 30 (10) ◽  
pp. 5471-5483
Author(s):  
Y Yau ◽  
M Dadar ◽  
M Taylor ◽  
Y Zeighami ◽  
L K Fellows ◽  
...  
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Sensory Information ◽  
Neural Correlates ◽  
Primate Research ◽  
Perceptual Decision Making ◽  
Emotional Information ◽  
Perceptual Decision ◽  
The Face ◽  
The Brain

Abstract Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

scholarly journals Neural correlates of evidence and urgency during human perceptual decision-making in dynamically changing conditions

2019 ◽  
Author(s):  
Y. Yau ◽  
M. Dadar ◽  
M. Taylor ◽  
Y. Zeighami ◽  
L.K. Fellows ◽  
...  
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Sensory Information ◽  
Neural Correlates ◽  
Primate Research ◽  
Perceptual Decision Making ◽  
Emotional Information ◽  
Perceptual Decision ◽  
The Face ◽  
The Brain

AbstractCurrent models of decision-making assume that the brain gradually accumulates evidence and drifts towards a threshold which, once crossed, results in a choice selection. These models have been especially successful in primate research, however transposing them to human fMRI paradigms has proved challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

scholarly journals Sensor-Level Wavelet Analysis Reveals EEG Biomarkers of Perceptual Decision-Making

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2461
Author(s):  
Alexander Kuc ◽  
Vadim V. Grubov ◽  
Vladimir A. Maksimenko ◽  
Natalia Shusharina ◽  
Alexander N. Pisarchik ◽  
...  
Keyword(s):  
Decision Making ◽  
Sensory Information ◽  
Stimulus Onset ◽  
Perceptual Process ◽  
Perceptual Decision Making ◽  
Beta Band ◽  
Perceptual Decision ◽  
Time Frequency ◽  
Band Power ◽  
Sensory Features

Perceptual decision-making requires transforming sensory information into decisions. An ambiguity of sensory input affects perceptual decisions inducing specific time-frequency patterns on EEG (electroencephalogram) signals. This paper uses a wavelet-based method to analyze how ambiguity affects EEG features during a perceptual decision-making task. We observe that parietal and temporal beta-band wavelet power monotonically increases throughout the perceptual process. Ambiguity induces high frontal beta-band power at 0.3–0.6 s post-stimulus onset. It may reflect the increasing reliance on the top-down mechanisms to facilitate accumulating decision-relevant sensory features. Finally, this study analyzes the perceptual process using mixed within-trial and within-subject design. First, we found significant percept-related changes in each subject and then test their significance at the group level. Thus, observed beta-band biomarkers are pronounced in single EEG trials and may serve as control commands for brain-computer interface (BCI).

scholarly journals P2-16: Dual-Bound Model and the Role of Time Bound in Perceptual Decision Making

i-Perception ◽  
10.1068/if676 ◽  
2012 ◽  
Vol 3 (9) ◽  
pp. 676-676
Author(s):  
Daeseob Lim ◽  
Hansem Sohn ◽  
Sang-Hun Lee
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Dual Bound

scholarly journals Performance-optimized hierarchical models only partially predict neural responses during perceptual decision making

2017 ◽  
Author(s):  
Laura Gwilliams ◽  
Jean-Rémi King
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Brain Activity ◽  
Hand Movement ◽  
Temporal Organization ◽  
Natural Image ◽  
Neural Responses ◽  
Perceptual Decision Making ◽  
Healthy Human ◽  
Perceptual Decision

AbstractModels of perceptual decision making have historically been designed to maximally explain behaviour and brain activity independently of their ability to actually perform tasks. More recently, performance-optimized models have been shown to correlate with brain responses to images and thus present a complementary approach to understand perceptual processes. In the present study, we compare how these approaches comparatively account for the spatio-temporal organization of neural responses elicited by ambiguous visual stimuli. Forty-six healthy human subjects performed perceptual decisions on briefly flashed stimuli constructed from ambiguous characters. The stimuli were designed to have 7 orthogonal properties, ranging from low-sensory levels (e.g. spatial location of the stimulus) to conceptual (whether stimulus is a letter or a digit) and task levels (i.e. required hand movement). Magneto-encephalography source and decoding analyses revealed that these 7 levels of representations are sequentially encoded by the cortical hierarchy, and actively maintained until the subject responds. This hierarchy appeared poorly correlated to normative, drift-diffusion, and 5-layer convolutional neural networks (CNN) optimized to accurately categorize alpha-numeric characters, but partially matched the sequence of activations of 3/6 state-of-the-art CNNs trained for natural image labeling (VGG-16, VGG-19, MobileNet). Additionally, we identify several systematic discrepancies between these CNNs and brain activity, revealing the importance of single-trial learning and recurrent processing. Overall, our results strengthen the notion that performance-optimized algorithms can converge towards the computational solution implemented by the human visual system, and open possible avenues to improve artificial perceptual decision making.

scholarly journals Evidence against perfect integration of sensory information during perceptual decision making

2016 ◽  
Vol 115 (2) ◽  
pp. 915-930 ◽  
Author(s):  
Matthew A. Carland ◽  
Encarni Marcos ◽  
David Thura ◽  
Paul Cisek
Keyword(s):  
Decision Making ◽  
Neural Activity ◽  
Temporal Integration ◽  
Sensory Information ◽  
Reaction Times ◽  
Perceptual Decision Making ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Perceptual Decision ◽  
Low Pass

Perceptual decision making is often modeled as perfect integration of sequential sensory samples until the accumulated total reaches a fixed decision bound. In that view, the buildup of neural activity during perceptual decision making is attributed to temporal integration. However, an alternative explanation is that sensory estimates are computed quickly with a low-pass filter and combined with a growing signal reflecting the urgency to respond and it is the latter that is primarily responsible for neural activity buildup. These models are difficult to distinguish empirically because they make similar predictions for tasks in which sensory information is constant within a trial, as in most previous studies. Here we presented subjects with a variant of the classic constant-coherence motion discrimination (CMD) task in which we inserted brief motion pulses. We examined the effect of these pulses on reaction times (RTs) in two conditions: 1) when the CMD trials were blocked and subjects responded quickly and 2) when the same CMD trials were interleaved among trials of a variable-motion coherence task that motivated slower decisions. In the blocked condition, early pulses had a strong effect on RTs but late pulses did not, consistent with both models. However, when subjects slowed their decision policy in the interleaved condition, later pulses now became effective while early pulses lost their efficacy. This last result contradicts models based on perfect integration of sensory evidence and implies that motion signals are processed with a strong leak, equivalent to a low-pass filter with a short time constant.

scholarly journals Subject- and task-independent neural correlates and prediction of decision confidence in perceptual decision making

2021 ◽  
Author(s):  
Jacobo Fernandez-Vargas ◽  
Christoph Tremmel ◽  
Davide Valeriani ◽  
Saugat Bhattacharyya ◽  
Caterina Cinel ◽  
...  
Keyword(s):  
Decision Making ◽  
Neural Correlates ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Decision Confidence ◽  
And Task

scholarly journals Re-thinking the fixed-criterion model of perceptual decision-making

2021 ◽  
Author(s):  
Jennifer Laura Lee ◽  
Rachel N. Denison ◽  
Wei Ji Ma
Keyword(s):  
Decision Making ◽  
Probabilistic Reasoning ◽  
Sensory Information ◽  
Feature Space ◽  
Decision Criterion ◽  
Decision Variable ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Response Variance ◽  
Sensory Uncertainty

Perceptual decision-making is often conceptualized as the process of comparing an internal decision variable to a categorical boundary, or criterion. How the mind sets such a criterion has been studied from at least two perspectives. First, researchers interested in consciousness have proposed that criterion-crossing determines whether a stimulus is consciously perceived. Second, researchers interested in decision-making have studied how the criterion depends on a range of stimulus and task variables. Both communities have considered the question of how the criterion behaves when sensory information is weak or uncertain. Interestingly, however, they have arrived at different conclusions. Consciousness researchers investigating a phenomenon called "subjective inflation" – a form of metacognitive mismatch in which observers overestimate the quality of their sensory representations in the periphery or at an unattended location – have proposed that the criterion governing subjective visibility is fixed. That is, it does not adjust to changes in sensory uncertainty. Decision-making researchers, on the other hand, have concluded that the criterion does adjust to account for sensory uncertainty, including under inattention. Here, we mathematically demonstrate that previous empirical findings supporting subjective inflation are consistent with either a fixed or a flexible decision criterion. We further show that specific experimental task requirements are necessary to make inferences about the flexibility of the criterion: 1) a clear mapping from decision variable space to stimulus feature space, and 2) a task incentive for observers to adjust their decision criterion as response variance increases. We conclude that the fixed-criterion model of subjective inflation requires re-thinking in light of new evidence from the probabilistic reasoning literature that decision criteria flexibly adjust according to response variance.

scholarly journals Robust spatial ventriloquism effect and aftereffect under memory interference

2020 ◽  
Author(s):  
Hame Park ◽  
Christoph Kayser
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Perceptual Decision Making ◽  
Sequential Effects ◽  
Perceptual Decision ◽  
Sensory Inputs ◽  
Memory Interference ◽  
Sensory Motor ◽  
Ventriloquism Aftereffect ◽  
With Memory

ABSTRACTOur brain adapts to discrepancies in the sensory inputs. One example is provided by the ventriloquism effect, experienced when the sight and sound of an object are displaced. Here the discrepant multisensory stimuli not only result in a biased localization of the sound, but also recalibrate the perception of subsequent unisensory acoustic information in the so-called ventriloquism aftereffect. This aftereffect has been linked to memory-related processes based on its parallels to general sequential effects in perceptual decision making experiments and insights obtained in neuroimaging studies. For example, we have recently implied memory-related medial parietal regions in the trial-by-trial ventriloquism aftereffect. Here, we tested the hypothesis that the ventriloquism aftereffect is indeed susceptible to manipulations interfering with working memory. Across three experiments we systematically manipulated the temporal delays between stimuli and response for either the ventriloquism or the aftereffect trials, or added a sensory-motor masking trial in between. Our data reveal no significant impact of either of these manipulations on the aftereffect, suggesting that the recalibration reflected by the ventriloquism aftereffect is surprisingly resilient to manipulations interfering with memory-related processes.

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