scholarly journals Hidden temporal structure of the ongoing task impacts detection strategy and is reflected in pupillary dynamics

2021 ◽  
Author(s):  
Jennifer Lawlor ◽  
Agnes Zagala ◽  
Sara Jamali ◽  
Yves Boubenec
Keyword(s):  
Decision Model ◽  
Temporal Structure ◽  
Decision Variable ◽  
Noisy Environments ◽  
Ongoing Task ◽  
Optimal Decisions ◽  
Pupillary Responses ◽  
Block Based ◽  
Auditory Change Detection

Estimating temporal regularities in incoming sensory inputs supports optimal decisions in noisy environments. In particular, inferred temporal structure can ease the detection of likely target events. Here we postulated that timely urgency signals can adapt subjects' decision-making to the ongoing task temporal structure, possibly through neuromodulatory tone. To test this hypothesis, we used an auditory change detection task in which targets followed a block-based temporal contingency, unbeknownst to participants. False alarm occurrences were driven by the distribution of target timings, indicating that participants adapted their behavior to the ongoing temporal structure. Task-evoked pupillary responses were larger for blocks with earliest target timings, and correlated with individual subjects' behavioral adaptation. Individual pupil responses matched an urgency signal extracted from a decision model fitted to behavior. This work demonstrates that internal temporal expectation can be tracked through pupillary dynamics, suggesting a role of neuromodulatory systems in context-dependent modulation of decision variable dynamics.

scholarly journals Collicular Vision Guides Nonconscious Behavior

2010 ◽  
Vol 22 (5) ◽  
pp. 888-902 ◽  
Author(s):  
Marco Tamietto ◽  
Franco Cauda ◽  
Luca Latini Corazzini ◽  
Silvia Savazzi ◽  
Carlo A. Marzi ◽  
...  
Keyword(s):  
Visual Experience ◽  
Striate Cortex ◽  
Visual Signals ◽  
Visually Guided ◽  
Visuomotor Integration ◽  
Motor Processing ◽  
Pupillary Responses ◽  
Cortex Area ◽  
Extrastriate Areas

Following destruction or deafferentation of primary visual cortex (area V1, striate cortex), clinical blindness ensues, but residual visual functions may, nevertheless, persist without perceptual consciousness (a condition termed blindsight). The study of patients with such lesions thus offers a unique opportunity to investigate what visual capacities are mediated by the extrastriate pathways that bypass V1. Here we provide evidence for a crucial role of the collicular–extrastriate pathway in nonconscious visuomotor integration by showing that, in the absence of V1, the superior colliculus (SC) is essential to translate visual signals that cannot be consciously perceived into motor outputs. We found that a gray stimulus presented in the blind field of a patient with unilateral V1 loss, although not consciously seen, can influence his behavioral and pupillary responses to consciously perceived stimuli in the intact field (implicit bilateral summation). Notably, this effect was accompanied by selective activations in the SC and in occipito-temporal extrastriate areas. However, when instead of gray stimuli we presented purple stimuli, which predominantly draw on S-cones and are thus invisible to the SC, any evidence of implicit visuomotor integration disappeared and activations in the SC dropped significantly. The present findings show that the SC acts as an interface between sensory and motor processing in the human brain, thereby providing a contribution to visually guided behavior that may remain functionally and anatomically segregated from the geniculo-striate pathway and entirely outside conscious visual experience.

Prior Beliefs and Ambiguity Attitudes in Decision from Experience

2021 ◽  
Author(s):  
Ilke Aydogan
Keyword(s):  
Decision Analysis ◽  
Crucial Role ◽  
Decision Model ◽  
Data Sets ◽  
Subjective Probabilities ◽  
Prior Beliefs ◽  
Decisions From Experience ◽  
Ambiguity Attitudes ◽  
Existing Data

Prior beliefs and their updating play a crucial role in decisions under uncertainty, and theories about them have been well established in classical Bayesianism. Yet, they are almost absent for ambiguous decisions from experience. This paper proposes a new decision model that incorporates the role of prior beliefs, beyond the role of ambiguity attitudes, into the analysis of such decisions. Hence, it connects ambiguity theories, popular in economics, with decision from experience, popular (mostly) in psychology, to the benefit of both. A reanalysis of some existing data sets from the literature on decisions from experience shows that the model that incorporates prior beliefs into the estimation of subjective probabilities outperforms the commonly used model that approximates subjective probabilities with observed relative frequencies. Controlling for subjective priors, we obtain more accurate measurements of ambiguity attitudes, and thus a new explanation of the gap between decision from description and decision from experience. This paper was accepted by Manel Baucells, decision analysis.

Bounds and good policies in stationary finite–stage Markovian decision problems

1980 ◽  
Vol 12 (1) ◽  
pp. 154-173 ◽  
Author(s):  
Gerhard Hübner
Keyword(s):  
Decision Model ◽  
Transition Probabilities ◽  
Planning Horizon ◽  
Decision Problems ◽  
Optimal Decisions ◽  
Optimal Value ◽  
Action Spaces ◽  
Stationary Problems ◽  
Markovian Decision Problems

A stationary Markovian decision model is considered with general state and action spaces where the transition probabilities are weakened to be bounded transition measures (this is useful for many applications). New and improved bounds are given for the optimal value of stationary problems with a large planning horizon if either only a few steps of iteration are carried out or, in addition, a solution of the infinite-stage problem is known. Similar estimates are obtained for the quality of policies which are composed of nearly optimal decisions from the first few steps or from the infinite-stage solution.

The role of temporal structure in envelope processing

2005 ◽  
pp. 220-228 ◽  
Author(s):  
Neal F. Viemeister ◽  
Mark A. Stellmack ◽  
Andrew J. Byrne
Keyword(s):  
Temporal Structure ◽  
Envelope Processing

Transmission of high-frequency vocalizations from hummingbirds living in diverse habitats

2020 ◽  
Vol 132 (1) ◽  
pp. 148-160
Author(s):  
F G Duque ◽  
C A Rodriguez-Saltos ◽  
M F Monteros ◽  
W Wilczynski
Keyword(s):  
High Frequency ◽  
Habitat Structure ◽  
Cloud Forest ◽  
Temporal Structure ◽  
High Frequencies ◽  
Complex Song ◽  
Vocal Signals ◽  
Narrow Frequency Range ◽  
High Altitude Grasslands

Abstract Some species of Andean hummingbirds produce high-frequency vocalizations which exceed the vocal range of most birds. They also challenge our understanding of the role of habitat structure in the evolution of vocal signals because these hummingbirds live in strikingly different habitats, ranging from cloud forest to high-altitude grasslands. Although these vocalizations are produced at high frequencies, they exhibit considerable variation in frequency content and temporal structure. The calls of the hummingbirds from the cloud forest are simpler and have a narrow frequency range compared to the complex song of the grasslands hummingbird. We hypothesized that each of the three high-frequency vocalizations is adapted for transmission in their habitat. We characterized the transmission of high-frequency vocal signals in the cloud forest and in the grasslands. All vocalizations attenuated and degraded substantially at short distances, suggesting that they are adapted for short-range communication. The simple vocalizations of the cloud-forest species transmitted better in both environments compared to the complex song of the grasslands hummingbird, probably due to relaxed constraints for high-frequency sounds in open habitats.

The Role of Arthroscopy in the Management of Glenohumeral Osteoarthritis: A Markov Decision Model

2014 ◽  
Vol 30 (11) ◽  
pp. 1392-1399 ◽  
Author(s):  
Ulrich J. Spiegl ◽  
Scott C. Faucett ◽  
Marilee P. Horan ◽  
Ryan J. Warth ◽  
Peter J. Millett
Keyword(s):  
Decision Model ◽  
Markov Decision ◽  
Glenohumeral Osteoarthritis ◽  
Markov Decision Model
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