scholarly journals Sensory and decisional components of endogenous attention are dissociable

2017 ◽  
Author(s):  
Sanjna Banerjee ◽  
Shrey Grover ◽  
Suhas Ganesh ◽  
Devarajan Sridharan
Keyword(s):  
Sensory Processing ◽  
Reaction Times ◽  
Optimal Decision ◽  
Endogenous Attention ◽  
Attention Task ◽  
Detection Model ◽  
Multidimensional Signal ◽  
Choice Bias ◽  
Sensitivity Changes ◽  
Optimal Decision Making

AbstractEndogenous attention acts by enhancing sensory processing (perceptual sensitivity) and prioritizing gating of attended information for decisions (choice bias). It is unknown if the sensitivity and bias components of attention are under the control of common or distinct mechanisms. We tested human observers on a multialternative visuospatial attention task with probabilistic cues, whose predictive validity varied across locations. Analysis of behavior with a multidimensional signal detection model revealed striking dissociations between sensitivity and bias changes induced by cueing. While bias varied in a graded manner, reflecting cue validities, across locations, sensitivity varied in an ‘all-or-none’ fashion, being highest at the cued location. Cue-induced modulations of sensitivity and bias were uncorrelated within and across observers. Moreover, bias changes, rather than sensitivity changes, covaried robustly with key metrics of reaction times and optimal decision-making. Our results demonstrate that endogenous attention engages not a unitary process, but dissociable sensory and decisional processes.

scholarly journals Sensory and decisional components of endogenous attention are dissociable

2019 ◽  
Vol 122 (4) ◽  
pp. 1538-1554 ◽  
Author(s):  
Sanjna Banerjee ◽  
Shrey Grover ◽  
Suhas Ganesh ◽  
Devarajan Sridharan
Keyword(s):  
Decision Making ◽  
Spatial Attention ◽  
Behavioral Model ◽  
Neural Correlates ◽  
Endogenous Attention ◽  
Perceptual Sensitivity ◽  
Spatial Choice ◽  
Attention Task ◽  
Choice Bias ◽  
Differential Risk

Endogenous cueing of attention enhances sensory processing of the attended stimulus (perceptual sensitivity) and prioritizes information from the attended location for guiding behavioral decisions (spatial choice bias). Here, we test whether sensitivity and bias effects of endogenous spatial attention are under the control of common or distinct mechanisms. Human observers performed a multialternative visuospatial attention task with probabilistic spatial cues. Observers’ behavioral choices were analyzed with a recently developed multidimensional signal detection model (the m-ADC model). The model effectively decoupled the effects of spatial cueing on sensitivity from those on spatial bias and revealed striking dissociations between them. Sensitivity was highest at the cued location and not significantly different among uncued locations, suggesting a spotlight-like allocation of sensory resources at the cued location. On the other hand, bias varied systematically with cue validity, suggesting a graded allocation of decisional priority across locations. Cueing-induced modulations of sensitivity and bias were uncorrelated within and across subjects. Bias, but not sensitivity, correlated with key metrics of prioritized decision-making, including reaction times and decision optimality indices. In addition, we developed a novel metric, differential risk curvature, for distinguishing bias effects of attention from those of signal expectation. Differential risk curvature correlated selectively with m-ADC model estimates of bias but not with estimates of sensitivity. Our results reveal dissociable effects of endogenous attention on perceptual sensitivity and choice bias in a multialternative choice task and motivate the search for the distinct neural correlates of each. NEW & NOTEWORTHY Attention is often studied as a unitary phenomenon. Yet, attention can both enhance the perception of important stimuli (sensitivity) and prioritize such stimuli for decision-making (bias). Employing a multialternative spatial attention task with probabilistic cueing, we show that attention affects sensitivity and bias through dissociable mechanisms. Specifically, the effects on sensitivity alone match the notion of an attentional “spotlight.” Our behavioral model enables quantifying component processes of attention, and identifying their respective neural correlates.

scholarly journals Exogenous attention facilitates performance through dissociable sensitivity and bias mechanisms

2018 ◽  
Author(s):  
Vishak Sagar ◽  
Ranit Sengupta ◽  
Devarajan Sridharan
Keyword(s):  
Reaction Times ◽  
Neural Correlates ◽  
Exogenous Attention ◽  
High Contrast ◽  
Perceptual Sensitivity ◽  
Detection Model ◽  
Exogenous Cueing ◽  
Multiple Alternative ◽  
Choice Bias ◽  
Spatial Locations

AbstractSelective attention enables prioritizing the most important information for differential sensory processing and decision-making. Here, we address an active debate regarding whether attention reflects a unitary phenomenon or involves the operation of dissociable sensory enhancement (perceptual sensitivity) and decisional gating (choice bias) processes. We developed a multialternative task in which participants detected and localized orientation changes in gratings at one of four spatial locations. Exogenous attention cues (high contrast flashes) preceded or followed the change events in close temporal proximity. Analysis of participants’ behavior with a multidimensional signal detection model revealed markedly distinct effects of exogenous cueing on perceptual sensitivity and choice bias. Whereas sensitivity enhancement was localized to the stimulus proximal to the exogenous cue, bias enhancement occurred even for distal stimuli in the cued hemifield. Modulations of sensitivity and bias were uncorrelated at both cued and uncued locations. Finally, exogenous cueing produced reaction time benefits only at the cued location and costs only at locations contralateral to the cue. These disparate effects of exogenous cueing on sensitivity, bias and reaction times could be parsimoniously explained within the framework of a diffusion-decision model, in which the drift rate was determined by a linear combination of sensitivity and bias at each location. Exogenous cueing effects on sensitivity and bias differed systematically from previously reported effects of endogenous cueing. We propose that the search for shared neural substrates of exogenous and endogenous attention would benefit from investigating neural correlates of their component sensory and decisional mechanisms.Significance statementWhen we voluntarily direct attention “endogenously”, we are able to better perceive stimuli at the attended location (sensitivity), and to prioritize information from that location for guiding behavioral decisions (bias). But when a salient stimulus, such as a flash of lightning, captures our attention “exogenously”, does it also produce these same effects? To answer this question, we designed a multiple alternative task in which task events occurred in close conjunction with salient exogenous cues (high contrast flashes). We discovered that exogenous attention enhanced both sensitivity and bias for cued stimuli, but each of these changes followed distinct spatial patterns across locations. Our results provide novel insights into component processes of exogenous attention and motivate the search for their neural correlates.

Integration of Reinforcement Learning and Optimal Decision-Making Theories of the Basal Ganglia

2011 ◽  
Vol 23 (4) ◽  
pp. 817-851 ◽  
Author(s):  
Rafal Bogacz ◽  
Tobias Larsen
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Basal Ganglia ◽  
Reaction Times ◽  
Learning Theories ◽  
Optimal Decision ◽  
Neural Responses ◽  
Sensory Evidence ◽  
Optimal Decision Making ◽  
Reinforcement Learning Models

This article seeks to integrate two sets of theories describing action selection in the basal ganglia: reinforcement learning theories describing learning which actions to select to maximize reward and decision-making theories proposing that the basal ganglia selects actions on the basis of sensory evidence accumulated in the cortex. In particular, we present a model that integrates the actor-critic model of reinforcement learning and a model assuming that the cortico-basal-ganglia circuit implements a statistically optimal decision-making procedure. The values of corico-striatal weights required for optimal decision making in our model differ from those provided by standard reinforcement learning models. Nevertheless, we show that an actor-critic model converges to the weights required for optimal decision making when biologically realistic limits on synaptic weights are introduced. We also describe the model's predictions concerning reaction times and neural responses during learning, and we discuss directions required for further integration of reinforcement learning and optimal decision-making theories.

scholarly journals GEAR: On Optimal Decision Making with Auxiliary Data

Stat ◽  
2021 ◽  
Author(s):  
Hengrui Cai ◽  
Rui Song ◽  
Wenbin Lu
Keyword(s):  
Decision Making ◽  
Optimal Decision ◽  
Auxiliary Data ◽  
Optimal Decision Making
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