Influence of the sensory information ambiguity on the brain state during the decision-making task

2019 ◽  
Author(s):  
Alexander Kuc ◽  
Vladimir Nedaivozov
Keyword(s):  
Decision Making ◽  
Sensory Information ◽  
Brain State ◽  
Information Ambiguity ◽  
The Brain

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.

Decision making by urgency gating: theory and experimental support

2012 ◽  
Vol 108 (11) ◽  
pp. 2912-2930 ◽  
Author(s):  
David Thura ◽  
Julie Beauregard-Racine ◽  
Charles-William Fradet ◽  
Paul Cisek
Keyword(s):  
Decision Making ◽  
Neural Activity ◽  
Time Window ◽  
Sensory Information ◽  
Natural Conditions ◽  
Accuracy Criterion ◽  
Sensory Evidence ◽  
Dot Motion ◽  
The Brain ◽  
Random Dot Motion

It is often suggested that decisions are made when accumulated sensory information reaches a fixed accuracy criterion. This is supported by many studies showing a gradual build up of neural activity to a threshold. However, the proposal that this build up is caused by sensory accumulation is challenged by findings that decisions are based on information from a time window much shorter than the build-up process. Here, we propose that in natural conditions where the environment can suddenly change, the policy that maximizes reward rate is to estimate evidence by accumulating only novel information and then compare the result to a decreasing accuracy criterion. We suggest that the brain approximates this policy by multiplying an estimate of sensory evidence with a motor-related urgency signal and that the latter is primarily responsible for neural activity build up. We support this hypothesis using human behavioral data from a modified random-dot motion task in which motion coherence changes during each trial.

Credo for optimality

2018 ◽  
Vol 41 ◽  
Author(s):  
Alan A. Stocker
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Sensory Information ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Sensory Information Processing ◽  
The Brain ◽  
Additional Constraints

AbstractOptimal or suboptimal, Rahnev & Denison (R&D) rightly argue that this ill-defined distinction is not useful when comparing models of perceptual decision making. However, what they miss is how valuable the focus on optimality has been in deriving these models in the first place. Rather than prematurely abandon the optimality assumption, we should refine this successful normative hypothesis with additional constraints that capture specific limitations of (sensory) information processing in the brain.

scholarly journals Auditory Decisions in the Supplementary Motor Area

2020 ◽  
Author(s):  
Isaac Morán ◽  
Javier Perez-Orive ◽  
Jonathan Melchor ◽  
Tonatiuh Figueroa ◽  
Luis Lemus
Keyword(s):  
Decision Making ◽  
Rhesus Monkeys ◽  
Supplementary Motor Area ◽  
Sensory Information ◽  
Motor Area ◽  
Neural Population ◽  
Auditory Stimuli ◽  
Motor Programs ◽  
The Brain ◽  
Selection Of

AbstractIn human speech and communication across various species, recognizing and categorizing sounds is fundamental for the selection of appropriate behaviors. But how does the brain decide which action to perform based on sounds? We explored whether the premotor supplementary motor area (SMA), responsible for linking sensory information to motor programs, also accounts for auditory-driven decision making. To this end, we trained two rhesus monkeys to discriminate between numerous naturalistic sounds and words learned as target (T) or non-target (nT) categories. We demonstrated that the neural population is organized differently during the auditory and the movement periods of the task, implying that it is performing different computations in each period. We found that SMA neurons perform acoustic-decision-related computations that transition from auditory to movement representations in this task. Our results suggest that the SMA integrates sensory information while listening to auditory stimuli in order to form categorical signals that drive behavior.

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.

Relation Between Level of Prefrontal Activity and Subject's Performance

1999 ◽  
Vol 13 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Laurence Casini ◽  
Françoise Macar ◽  
Marie-Hélène Giard
Keyword(s):  
Brain Activity ◽  
Sensory Information ◽  
Practice Phase ◽  
Trained Subjects ◽  
Anagram Task ◽  
Economic Information ◽  
Long Duration ◽  
Level Of Activity ◽  
The Brain ◽  
Processing Mechanism

Abstract The experiment reported here was aimed at determining whether the level of brain activity can be related to performance in trained subjects. Two tasks were compared: a temporal and a linguistic task. An array of four letters appeared on a screen. In the temporal task, subjects had to decide whether the letters remained on the screen for a short or a long duration as learned in a practice phase. In the linguistic task, they had to determine whether the four letters could form a word or not (anagram task). These tasks allowed us to compare the level of brain activity obtained in correct and incorrect responses. The current density measures recorded over prefrontal areas showed a relationship between the performance and the level of activity in the temporal task only. The level of activity obtained with correct responses was lower than that obtained with incorrect responses. This suggests that a good temporal performance could be the result of an efficacious, but economic, information-processing mechanism in the brain. In addition, the absence of this relation in the anagram task results in the question of whether this relation is specific to the processing of sensory information only.

Measuring the World

2018 ◽  
Author(s):  
Ann-Sophie Barwich
Keyword(s):  
Sensory Information ◽  
Network Models ◽  
Model System ◽  
Stimulus Input ◽  
Expectancy Effects ◽  
Neural Network Models ◽  
Perceptual Object ◽  
External Objects ◽  
The Common ◽  
The Brain

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes.

Neuroscience: The New English Major?

2021 ◽  
pp. 107385842110039
Author(s):  
Kristin F. Phillips ◽  
Harald Sontheimer
Keyword(s):  
Decision Making ◽  
Graduate Education ◽  
Human Behavior ◽  
Undergraduate Curriculum ◽  
Virginia Tech ◽  
Bachelor's Degree ◽  
State University ◽  
Human Interactions ◽  
English Major ◽  
The Brain

Once strictly the domain of medical and graduate education, neuroscience has made its way into the undergraduate curriculum with over 230 colleges and universities now offering a bachelor’s degree in neuroscience. The disciplinary focus on the brain teaches students to apply science to the understanding of human behavior, human interactions, sensation, emotions, and decision making. In this article, we encourage new and existing undergraduate neuroscience programs to envision neuroscience as a broad discipline with the potential to develop competencies suitable for a variety of careers that reach well beyond research and medicine. This article describes our philosophy and illustrates a broad-based undergraduate degree in neuroscience implemented at a major state university, Virginia Tech. We highlight the fact that the research-centered Experimental Neuroscience major is least popular of our four distinct majors, which underscores our philosophy that undergraduate neuroscience can cater to a different audience than traditionally thought.

scholarly journals Failure of the Brain Glucagon-Like Peptide-1-Mediated Control of Intestinal Redox Homeostasis in a Rat Model of Sporadic Alzheimer’s Disease

Antioxidants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1118
Author(s):  
Jan Homolak ◽  
Ana Babic Perhoc ◽  
Ana Knezovic ◽  
Jelena Osmanovic Barilar ◽  
Melita Salkovic-Petrisic
Keyword(s):  
Oxidative Stress ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Rat Model ◽  
Redox Homeostasis ◽  
Brain State ◽  
Gastrointestinal Hormone ◽  
Glucagon Like Peptide ◽  
Glucagon Like Peptide 1 ◽  
The Brain

The gastrointestinal system may be involved in the etiopathogenesis of the insulin-resistant brain state (IRBS) and Alzheimer’s disease (AD). Gastrointestinal hormone glucagon-like peptide-1 (GLP-1) is being explored as a potential therapy as activation of brain GLP-1 receptors (GLP-1R) exerts neuroprotection and controls peripheral metabolism. Intracerebroventricular administration of streptozotocin (STZ-icv) is used to model IRBS and GLP-1 dyshomeostasis seems to be involved in the development of neuropathological changes. The aim was to explore (i) gastrointestinal homeostasis in the STZ-icv model (ii) assess whether the brain GLP-1 is involved in the regulation of gastrointestinal redox homeostasis and (iii) analyze whether brain-gut GLP-1 axis is functional in the STZ-icv animals. Acute intracerebroventricular treatment with exendin-3(9-39)amide was used for pharmacological inhibition of brain GLP-1R in the control and STZ-icv rats, and oxidative stress was assessed in plasma, duodenum and ileum. Acute inhibition of brain GLP-1R increased plasma oxidative stress. TBARS were increased, and low molecular weight thiols (LMWT), protein sulfhydryls (SH), and superoxide dismutase (SOD) were decreased in the duodenum, but not in the ileum of the controls. In the STZ-icv, TBARS and CAT were increased, LMWT and SH were decreased at baseline, and no further increment of oxidative stress was observed upon central GLP-1R inhibition. The presented results indicate that (i) oxidative stress is increased in the duodenum of the STZ-icv rat model of AD, (ii) brain GLP-1R signaling is involved in systemic redox regulation, (iii) brain-gut GLP-1 axis regulates duodenal, but not ileal redox homeostasis, and iv) brain-gut GLP-1 axis is dysfunctional in the STZ-icv model.

scholarly journals Consciousness, decision making, and volition: freedom beyond chance and necessity

2021 ◽  
Author(s):  
Hans Liljenström
Keyword(s):  
Decision Making ◽  
Free Will ◽  
Brain Activity ◽  
Brain Structures ◽  
Complex Process ◽  
Neural Information ◽  
Neural Information Processing ◽  
Stochastic Population Model ◽  
The Brain

AbstractWhat is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what “you” decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world.

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