scholarly journals Any way the brain blows? The nature of decision noise in random exploration

2018 ◽  
Author(s):  
Siyu Wang ◽  
Robert C Wilson
Keyword(s):  
Decision Making ◽  
Cognitive Control ◽  
Recent Work ◽  
Human Behavior ◽  
External Noise ◽  
Behavioral Variability ◽  
The World ◽  
Human Decision ◽  
Adaptive Noise ◽  
The Brain

Human decision making is inherently variable. While this variability is often seen as a sign of suboptimality in human behavior, recent work suggests that randomness can actually be adaptive. An example arises when we must choose between exploring unknown options or exploiting options we know well. A little randomness in these `explore-exploit' decisions is remarkably effective as it encourages us to explore options we might otherwise ignore. Moreover, people actually use such `random exploration' in practice, increasing their behavioral variability when it is more valuable to explore. Despite this progress, the nature of adaptive `decision noise' for exploration is unknown -- specifically whether it is generated internally, from stochastic processes in the brain, or externally, from stochastic stimuli in the world. Here we show that, while both internal and external noise drive variability in behavior, the noise driving random exploration is predominantly internal. This suggests that random exploration depends on adaptive noise processes in the brain which are subject to cognitive control.

scholarly journals Deep exploration as a unifying account of explore-exploit behavior

2020 ◽  
Author(s):  
Robert C Wilson ◽  
Siyu Wang ◽  
Hashem Sadeghiyeh ◽  
Jonathan D. Cohen
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Human Behavior ◽  
Information Seeking ◽  
The Other ◽  
Behavioral Variability ◽  
Simple Task ◽  
Stochastic Planning ◽  
Human Decision ◽  
Deep Exploration

Many decisions involve a choice between exploring unknown opportunities and exploiting well-known options. Work across a variety of domains, from animal foraging to human decision making, has suggested that animals solve such ``explore-exploit dilemmas'' with a mixture of two strategies: one driven by information seeking (directed exploration) and the other by behavioral variability (random exploration). Here we propose a unifying account in which these two strategies emerge from a kind of stochastic planning, known in the machine learning literature as Deep Exploration. In this model, the explore-exploit decision is made by stochastic simulation of plausible futures that are deep, in that they extend far into the future, and narrow, in that the number of possible futures they consider is small. By applying Deep Exploration to a simple explore-exploit task we show theoretically how directed and random exploration can emerge in these settings. Moreover, we show that Deep Exploration implies a tradeoff between directed and random exploration that is mediated by the number of simulations, or samples --- with more samples leading to increased directed exploration and decreased random exploration at the expense of greater time taken to respond. By measuring human behavior on the same simple task, we show that this reaction-time-mediated tradeoff exists in human behavior both between and within participants. We therefore suggest that Deep Exploration is a unifying account of explore-exploit behavior in humans.

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.

Networks of Photos, Landmarks, and People

Leonardo ◽  
2011 ◽  
Vol 44 (3) ◽  
pp. 240-243 ◽  
Author(s):  
David Crandall ◽  
Noah Snavely
Keyword(s):  
Recent Work ◽  
Human Behavior ◽  
Visual Representations ◽  
3D Models ◽  
Global Scale ◽  
Local Scale ◽  
Photo Sharing ◽  
The World ◽  
Vantage Points ◽  
Combining Information

Social photo-sharing sites like Flickr contain vast amounts of latent information about the world and human behavior. The authors describe their recent work in building automatic algorithms that analyze large collections of imagery in order to extract some of this information. At a global scale, geo-tagged photographs can be used to identify the most photographed places on Earth, as well as to infer the names and visual representations of these places. At a local scale, the authors build detailed 3D models of a scene by combining information from thousands of 2D photographs taken by different people and from different vantage points.

The Study of Human Decision-Making: A Cautionary Tale from the World of Experimental Gaming

1981 ◽  
Vol 32 (3) ◽  
pp. 173 ◽  
Author(s):  
C. S. Huxham ◽  
P. G. Bennett ◽  
M. V. Lozowski ◽  
M. R. Dando
Keyword(s):  
Decision Making ◽  
Cautionary Tale ◽  
The World ◽  
Human Decision

scholarly journals Prehistory of the Concept of ‘Neuroreductionism’: The Sorrowful Path of the Soul

2021 ◽  
pp. 77-87
Author(s):  
Дамиан Воронов
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Human Spirit ◽  
Brain Science ◽  
Long Period ◽  
Natural Scientists ◽  
The Brain ◽  
Neuroimaging Techniques

Современная нейронаука описывает человека как биологическую машину, в которой вера, любовь, надежда, страхи, воспоминания, мечты и свобода предстают как убедительная иллюзия. Перспективные методы нейровизуализации позволяют естествоиспытателям заглянуть внутрь мозга и измерить его деятельность, соответствующую ощущениям от переживания боли, цвета и звуков. Редукционизм и нейроцентризм умаляют сферу человеческого духа, сжимая её до выражения «я - это мой мозг». Позиция современной науки о мозге, постулирующей его ключевую роль в генерации мыслей, принятии решений и поведения человека, утверждалась постепенно, ей предшествовал длительный период оживлённых споров и удивительных открытий, о чём и повествуется в данной статье. Modern neuroscience describes humans as a biological machine in which faith, love, hope, fears, memories, dreams and freedom appear as a compelling illusion. Advanced neuroimaging techniques allow natural scientists to look inside the brain and measure its activity corresponding to the sensations of pain, color and sound. Reductionism and neurocentrism detract from the sphere of the human spirit, shrinking it to the expression «I am my brain». The position of modern brain science, postulating its key role in the generation of thoughts, decision-making and human behavior, was established gradually, it was preceded by a long period of debate and amazing discoveries, which is described in this article.

scholarly journals Revisiting the Neural Architecture of Decision-Making: Univariate and Multivariate Evidence for System-Based Models in Adolescence

2020 ◽  
Author(s):  
João F. Guassi Moreira ◽  
Adriana S. Méndez Leal ◽  
Yael H. Waizman ◽  
Natalie Saragosa-Harris ◽  
Emilia Ninova ◽  
...  
Keyword(s):  
Decision Making ◽  
Cognitive Control ◽  
Risk Taking ◽  
Neural Activity ◽  
Brain Activity ◽  
Empirical Support ◽  
Risky Decision ◽  
Human Decision ◽  
Within Subjects ◽  
Multivariate Pattern

AbstractSystem-based theories are a popular approach to explaining the psychology of human decision making. Such theories posit that decision-making is governed by interactions between different psychological processes that arbitrate amongst each other for control over behavior. To date, system-based theories have received inconsistent support at the neural level, leading some to question their veracity. Here we examine the possibility that prior attempts to evaluate system-based theories have been limited by their reliance on predicting brain activity from behavior, and seek to advance evaluations of system-based models through modeling approaches that predict behavior from brain activity. Using within-subject decision-level modeling of fMRI data from a risk-taking task in a sample of over 2000 decisions across 51 adolescents—a population in which decision-making processes are particularly dynamic and consequential—we find support for system-based theories of decision-making. In particular, neural activity in lateral prefrontal cortex and a multivariate pattern of cognitive control both predicted a reduced likelihood of making a risky decision, whereas increased activity in the ventral striatum—a region typically associated with valuation processes—predicted a greater likelihood of engaging in risk-taking. These results comprise the first formalized within-subjects neuroimaging test of system-based theories, garnering support for the notion that competing systems drive decision behaviors.Significance StatementDecision making is central to adaptive behavior. While dominant psychological theories of decision-making behavior have found empirical support, their neuroscientific implementations have received inconsistent support. This may in part be due to statistical approaches employed by prior neuroimaging studies of system-based theories. Here we use brain modeling—an approach that predicts behavior from brain activity—of univariate and multivariate neural activity metrics to better understand how neural components of psychological systems guide decision behavior. We found broad support for system-based theories such that that neural systems involved in cognitive control predicted a reduced likelihood to make risky decisions, whereas value-based systems predicted greater risk-taking propensity.

How the Brain Makes Decisions

2020 ◽  
Author(s):  
Thomas Boraud
Keyword(s):  
Decision Making ◽  
General Framework ◽  
Fundamental Question ◽  
Decision Making Process ◽  
Brain Functions ◽  
It Impacts ◽  
Combining Data ◽  
Neural Substrate ◽  
Human Decision ◽  
The Brain

The human decision-making process is tainted with irrationality. To address this issue, this book proposes a ‘bottom-up’ approach of the neural substrate of decision-making, starting from the fundamental question: What are the basic properties that a neural network of decision-making needs to possess? Combining data drawn from phylogeny and physiology, this book provides a general framework of the neurobiology of decision-making in vertebrates and explains how it evolved from the lamprey to the apes. It also addresses the consequences, examining how it impacts our capacity of reasoning and some aspects of the pathophysiology of high brain functions. To conclude, the text opens discussion to more philosophical concepts such as the question of free will.

Decision-Making Cognitive Process

2018 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Thais Spiegel ◽  
Ana Carolina P V Silva
Keyword(s):  
Decision Making ◽  
Cognitive Process ◽  
Decision Makers ◽  
Time Constraints ◽  
Decision Making Process ◽  
Cognitive Limitations ◽  
The World ◽  
Human Decision ◽  
Per Se ◽  
Rationality Theory

In the study of decision-making, the classical view of behavioral appropriateness or rationality was challenged by neuro and psychological reasons. The “bounded rationality” theory proposed that cognitive limitations lead decision-makers to construct simplified models for dealing with the world. Doctors' decisions, for example, are made under uncertain conditions, as without knowing precisely whether a diagnosis is correct or whether a treatment will actually cure a patient, and often under time constraints. Using cognitive heuristics are neither good nor bad per se, if applied in situations to which they have been adapted to be helpful. Therefore, this text contextualizes the human decision-making perspective to find descriptions that adhere more closely to the human decision-making process. Then, based on a literature review of cognition during decision-making, particularly in healthcare context, it addresses a model that identifies the roles of attention, categorization, memory, emotion, and their inter-relations, during the decision-making process.

The Role of Executive Function in Shaping Reinforcement Learning

2020 ◽  
Author(s):  
Milena Rmus ◽  
Samuel McDougle ◽  
Anne Collins
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Instrumental Behavior ◽  
Complex Environments ◽  
Neural Computations ◽  
Human Decision ◽  
Brain And Behavior ◽  
And Behavior ◽  
The Brain

Reinforcement learning (RL) models have advanced our understanding of how animals learn and make decisions, and how the brain supports some aspects of learning. However, the neural computations that are explained by RL algorithms fall short of explaining many sophisticated aspects of human decision making, including the generalization of learned information, one-shot learning, and the synthesis of task information in complex environments. Instead, these aspects of instrumental behavior are assumed to be supported by the brain’s executive functions (EF). We review recent findings that highlight the importance of EF in learning. Specifically, we advance the theory that EF sets the stage for canonical RL computations in the brain, providing inputs that broaden their flexibility and applicability. Our theory has important implications for how to interpret RL computations in the brain and behavior.

Relational Dynamics

2017 ◽  
pp. 128-151
Author(s):  
David Stefan Bathory
Keyword(s):  
Decision Making ◽  
World Wide ◽  
Rural Tourism ◽  
Intergenerational Effects ◽  
Relational Dynamics ◽  
Mass Trauma ◽  
Functional Changes ◽  
The World ◽  
South Eastern Europe ◽  
The Brain

The effects of global warming are becoming apparent through- out the world. Europe has begun to experience more severe winters and increased rain (Steffen, 2011). Massive flooding in South Eastern Europe has devastated communities and repeatedly strains the economy of these regions resulting in mass trauma to the residents of multiple countries (Sito-Sucic & Djurica, 2014). Intergenerational effects of trauma (Bathory & Celik, 2014; Kaitz, Levy, Ebstein, Faraone, & Mankuta, 2009) have been noted to be an increasing world-wide concern. These traumatic effects are not only psychologically based but result in structural and functional changes within the brain and body (D. Bathory, 2012; D. S. Bathory, 2013a, 2013b; van der Kolk, Roth, Pelcovitz, Sunday, & Spinazzola, 2005). This chapter explores the application of decision making and Relational Dynamics to mass victims of floods by creating healing sites of sustainable energy and rural tourism to assist mass victims of natural disaster flooding.

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