The last issue of Nature Neuroscience features 4 great papers on the neuroscience of decision-making:
A few papers worth reading:
A study on meta-ethics beleifs (how people see ethical claims):
Important for anyone interested in neuroscience: to a non-expert public, seeing a picture of a brain biases people to give more credibility to a piece of information:
Social cognition: it begins with goal recognition
Jesse Prinz's new book (in a nutshell: morality is emotional and relative to a culture)
Forthcoming in the new journal Neuroethics:
A study on Chimpanzee barter behavior:
Valerie Gray Hardcastle, a philosopher of mind and neuroscience, reviews Carl F. Craver's Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience (Oxford University Press, 2007). It seems like a great book for people interested in neuroscience, not just philosophers.
Collective Agency: From Intuitions to Mechanisms (pdf)
Benoît Dubreuil & Benoît Hardy-Vallée
Abstract:
This chapter analyzes and discusses one of the most important uses of information in the biological world: decision-making. I will first present a fundamental principle introduced by Darwin, the idea of an “economy of nature,” by which decision-making can be understood. Following this principle, I then argue that biological decision-making should be construed as goal-oriented, value-based information processing. I propose a value-based account of neural information, where information is primarily economic and relative to goal achievement. If living beings (I focus here on animals) are biological decision-makers, we may expect that their behavior would be coherent with the pursuit of certain goals (either ultimate or instrumental) and that their behavioral control mechanisms would be endowed with goal-directed and valuation mechanisms. These expectations, I argue, are supported by behavioral ecology and decision neuroscience. Together, they provide a rich, biological account of decision-making that should be integrated in a wider concept of ‘natural rationality’.
Decision-making is usually a secondary topic in psychology, relegated to the last chapters of textbooks. It pictures decision-making mostly as a deliberative task and rationality as a matter of idealization. This conception also suggests that psychology should either document human failures to comply with rational-choice standards (bounded rationality) or detail how mental mechanisms are ecologically rational (ecological rationality). This conception, I argue, runs into many problems: descriptive (section 2), conceptual (section 3) and normative (section 4). I suggest that psychology and philosophy need another—wider—conception of rationality, that goes beyond bounded and ecological rationality (section 5).
From http://lawandneuroscienceproject.org/resources via Neuroethics and Law Blog.
Readings on Law and Neuroscience
Bibliography on Law and Biology
Blog on Neuroethics and Law
Liberals tend to be: against, skeptical of, or cynical about familiar and traditional ideology; open to new experiences; individualistic and uncompromising, pursuing a place in the world on personal terms; private; disobedient, even rebellious rulebreakers; sensation seekers and pleasure seekers, including in the frequency and diversity of sexual experiences; socially and economically egalitarian; and risk prone; furthermore, they value diversity, imagination, intellectualism, logic, and scientific progress. Conservatives exhibit the reverse in all these domains. Moreover, the felt need for order, structure, closure, family and national security, salvation, sexual restraint, and self-control, in general, as well as the effort devoted to avoidance of change, novelty, unpredictability, ambiguity, and complexity, is a well-established characteristic of conservatives. (Thornhill & Fincher, 2007).In their paper, Thornhill & Fincher presents an evolutionary hypothesis for explaining the liberalism/conservatism ideologies: both originate from innate adaptation to attachement, parametrized by early childhood experiences. In another but related domain Lakoff (2002) argued that liberals and conservatives differs in their methaphors: both view the nation or the State as a child, but they hold different perspectives on how to raise her: the Strict Father model (conservatives) or the Nurturant Parent model (liberals); see an extensive description here). The first one
posits a traditional nuclear family, with the father having primary responsibility for supporting and protecting the family as well as the authority to set overall policy, to set strict rules for the behavior of children, and to enforce the rules [where] [s]elf-discipline, self-reliance, and respect for legitimate authority are the crucial things that children must learn.
Love, empathy, and nurturance are primary, and children become responsible, self-disciplined and self-reliant through being cared for, respected, and caring for others, both in their family and in their community.In the October issue of Nature Neuroscience, a new research paper by Amodio et al. study the "neurocognitive correlates of liberalism and conservatism". The study is more modest than the title suggests. Subject were submitted to the same test, a Go/No Go task (click when you see a "W" don't click when it's a "M"). The experimenters then trained the subjects to be used to the Go stimuli; on a few occasions, they were presented with the No Go stimuli. Since they got used to the Go stimuli, the presentation of a No Go creates a cognitive conflict: balancing the fast/automatic/ vs. the slow/deliberative processing. You have to inhibit an habit in order to focus on the goal when the habit goes in the wrong direction. The idea was to study the correlation between political values and conflict monitoring. The latter is partly mediated by the anterior cingulate cortex, a brain area widely studied in neuroeconomics and decision neuroscience (see this post). EEG recording indicated that liberals' neural response to conflict were stronger when response inhibition was required. Hence liberalism is associated to a greater sensibility to response conflict, while conservatism is associated with a greater persistence in the habitual pattern. These results, say the authors, are
consistent with the view that political orientation, in part, reflects individual differences in the functioning of a general mechanism related to cognitive control and self-regulationThus valuing tradition vs. novelty, security vs. novelty might have sensorimotor counterpart, or symptoms. Of course, it does not mean that the neural basis of conservatism is identified, or the "liberal area", etc, but this study suggest how micro-tasks may help to elucidate, as the authors say in the closing sentence, "how abstract, seemingly ineffable constructs, such as ideology, are reflected in the human brain."
An essential component of every economic transaction is a willingness-to-pay (WTP) computation in which buyers calculate the maximum amount of financial resources that they are willing to give up in exchange for the object being sold. Despite its pervasiveness, little is known about how the brain makes this computation. We investigated the neural basis of the WTP computation by scanning hungry subjects' brains using functional magnetic resonance imaging while they placed real bids for the right to eat different foods. We found that activity in the medial orbitofrontal cortex and in the dorsolateral prefrontal cortex encodes subjects' WTP for the items. Our results support the hypothesis that the medial orbitofrontal cortex encodes the value of goals in decision making.
The massive redeployment hypothesis (MRH) is a theory about the functional topography of the human brain, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components—originally developed to serve some specific purpose—were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs. If the evolution of cognition was indeed driven by such exaptation, then we should be able to make some specific empirical predictions regarding the resulting functional topography of the brain. This essay discusses three such predictions, and some of the evidence supporting them. Then, using this account as a background, the essay considers the implications of these findings for an account of the functional integration of cognitive operations. For instance, MRH suggests that in order to determine the functional role of a given brain area it is necessary to consider its participation across multiple task categories, and not just focus on one, as has been the typical practice in cognitive neuroscience. This change of methodology will motivate (even perhaps necessitate) the development of a new, domain-neutral vocabulary for characterizing the contribution of individual brain areas to larger functional complexes, and direct particular attention to the question of how these various area roles are integrated and coordinated to result in the observed cognitive effect. Finally, the details of the mix of cognitive functions a given area supports should tell us something interesting not just about the likely computational role of that area, but about the nature of and relations between the cognitive functions themselves. For instance, growing evidence of the role of “motor” areas like M1, SMA and PMC in language processing, and of “language” areas like Broca’s area in motor control, offers the possibility for significantly reconceptualizing the nature both of language and of motor control.
To have a fully integrated understanding of neurobiological systems, we must address two fundamental questions: 1. What do brains do (what is their function)? and 2. How do brains do whatever it is that they do (how is that function implemented)? I begin by arguing that these questions are necessarily inter-related. Thus, addressing one without consideration of an answer to the other, as is often done, is a mistake. I then describe what I take to be the best available approach to addressing both questions. Specifically, to address 2, I adopt the Neural Engineering Framework (NEF) of Eliasmith & Anderson [Neural engineering: Computation representation and dynamics in neurobiological systems. Cambridge, MA: MIT Press, 2003] which identifies implementational principles for neural models. To address 1, I suggest that adopting statistical modeling methods for perception and action will be functionally sufficient for capturing biological behavior. I show how these two answers will be mutually constraining, since the process of model selection for the statistical method in this approach can be informed by known anatomical and physiological properties of the brain, captured by the NEF. Similarly, the application of the NEF must be informed by functional hypotheses, captured by the statistical modeling approach.
Fig. 1 (From O'Reilly, 2006). Dopamine-based gating mechanism that emerges from the detailed biological model of Durstewitz, Seamans, and colleagues. The opening of the gate occurs in the dopamine D2-receptor–dominated state (State 1), in which any existing active maintenance is destabilized and the system is more responsive to inputs. The closing of the gate occurs in the D1-receptor–dominated state (State 2), which stabilizes the strongest activation pattern for robust active maintenance. D2 receptors are located synaptically and require high concentrations of dopamine and are therefore activated only during phasic dopamine bursts, which thus trigger rapid updating. D1 receptors are extrasynaptic and respond to lower concentrations, so robust maintenance is the default state of the system with normal tonic levels of dopamine firing.
Fig. 2. (From O'Reilly, 2006). Dynamic gating produced by disinhibitory circuits through the basal ganglia and frontal cortex/PFC (one of multiple parallel circuits shown). (A) In the base state (no striatum activity) and when NoGo (indirect pathway) striatum neurons are firing more than Go, the SNr (substantia nigra pars reticulata) is tonically active and inhibits excitatory loops through the basal ganglia and PFC through the thalamus. This corresponds to the gate being closed, and PFC continues to robustly maintain ongoing activity (which does not match the activity pattern in the posterior cortex, as indicated). (B) When direct pathway Go neurons in striatum fire, they inhibit the SNr and thus disinhibit the excitatory loops through the thalamus and the frontal cortex, producing a gating-like modulation that triggers the update of working memory representations in prefrontal cortex. This corresponds to the gate being open.
(...) explores the adaptive advantages of group life and the accompanying development of social skills. News articles examine clues from our primate cousins about the evolution of sophisticated social behavior and explorations of human behavior made possible by computer-generated realities. Review articles dissect the human capacity for prospection and the links between sociality and brain evolution and fitness. And related podcast segments highlight research on the social abilities of children and chimps and the value of virtual worlds to studies of social science
Four papers you don't want to miss:
All animals can predict the hedonic consequences of events they've experienced before. But humans can predict the hedonic consequences of events they've never experienced by simulating those events in their minds. Scientists are beginning to understand how the brain simulates future events, how it uses those simulations to predict an event's hedonic consequences, and why these predictions so often go awry.
A book review in the NYT of Drew Westen's new book, "The Political Brain".
Stop Making Sense Between 2000 and 2006, a specter haunted the community of fundamentalist Democrats. Members of this community looked around and observed their moral and intellectual superiority. They observed that their policies were better for the middle classes. And yet the middle classes did not support Democrats. They tended to vote, in large numbers, for the morally and intellectually inferior party, the one, moreover, that catered to the interests of the rich.
How could this be?
Serious thinkers set to work, and produced a long shelf of books answering this question. Their answers tended to rely on similar themes. First, Democrats lose because they are too intelligent. Their arguments are too complicated for American voters. Second, Democrats lose because they are too tolerant. They refuse to cater to racism and hatred. Finally, Democrats lose because they are not good at the dark art of politics. Republicans, though they are knuckle-dragging simpletons when it comes to policy, are devilishly clever when it comes to electioneering. They have brilliant political consultants like Lee Atwater and Karl Rove, who frame issues so fiendishly, they can fool the American people into voting against their own best interests. (READ MORE)
ReferencesCognitive models of inhibition have focused on inhibition of prepotent responses to external stimuli (Logan et al., 1984; Cohen et al., 1990). An important distinction is made between "lateral" competitive interaction between alternative representations at a single level (Rumelhart and McClelland, 1986) and inhibitory top-down control signals from hierarchically higher brain areas (Norman and Shallice, 1986). The first idea would be consistent with a general decision process being involved. If the dFMC decides between action and inhibition by a competitive interaction process, then representations corresponding to the possibilities of action and to non-action should initially both be active, leading to activation in both action trials and inhibition trials. Our finding of minimal dFMC activation in action trials (...) argues against a view of endogenous inhibition based on competitive interaction between alternatives and thus is also not consistent with the idea of the dFMC being involved in a general decision process. In contrast, our result is consistent with a specific top-down control signal gating the neural pathways linking intention to action. This view is supported by the negative correlation between dFMC activation and primary motor cortex activation.
But first, what is a blog carnival?
A blog carnival is a type of blog event. It is similar to a magazine, in that it is dedicated to a particular topic, and is published on a regular schedule, often weekly or monthly. Each edition of a blog carnival is in the form of a blog article that contains permalinks links to other blog articles on the particular topic.Two Blog carnival may be of interest for the readers of this blog:
There are many variations, but typically, someone who wants to organize a carnival posts details of the theme or topic to their blog, and asks readers to submit relevant articles for inclusion in an upcoming edition. The host then collects links to these submissions, edits and annotates them (often in very creative ways), and publishes the resulting round-up to his or her blog. (From Wikiepdia)
Many carnivals have a home page or principal organizer, who lines up guest bloggers to host each edition. This means that the carnival travels, appearing on a different blog each time.
Encephalon , a neuroscience blog carnival; the 28the edition is hosted by the Bohemian Scientist; the next issue will be published (August 13) at Memoirs of a PostgradThe new edition of The Journal of Neuroscience features six (!!) Mini-Reviews papers (max 5 pages) on decision-making,:
(From the paper:) A schematic model of implementation of reinforcement learning in the cortico-basal ganglia circuit (Doya, 1999, 2000). Based on the state representation in the cortex, the striatum learns state and action value functions. The state value coding striatal neurons project to dopamine neurons, which sends the TD signal back to the striatum. The outputs of action value coding striatal neurons channel through the pallidum and the thalamus, where stochastic action selection may be realized
a theory of bounded rationality cannot avoid this basic mode of behavior (Selten, 2001, p. 16)
The may issue of the Annals of the New York Academy of Sciences is devoted to Reward and Decision Making in Corticobasal Ganglia Networks. Many big names in decision neuroscience (Berns, Knutson, Delgado, etc.) contributed.
Introduction. Current Trends in Decision Making
Bernard W Balleine, Kenji Doya, John O'Doherty, Masamichi Sakagami
Learning about Multiple Attributes of Reward in Pavlovian Conditioning
ANDREW R DELAMATER, STEPHEN OAKESHOTT
Should I Stay or Should I Go?. Transformation of Time-Discounted Rewards in Orbitofrontal Cortex and Associated Brain Circuits
MATTHEW R ROESCH, DONNA J CALU, KATHRYN A BURKE, GEOFFREY SCHOENBAUM
Model-Based fMRI and Its Application to Reward Learning and Decision Making
JOHN P O'DOHERTY, ALAN HAMPTON, HACKJIN KIM
Splitting the Difference. How Does the Brain Code Reward Episodes?
BRIAN KNUTSON, G. ELLIOTT WIMMER
Reward-Related Responses in the Human Striatum
MAURICIO R DELGADO
Integration of Cognitive and Motivational Information in the Primate Lateral Prefrontal Cortex
MASAMICHI SAKAGAMI, MASATAKA WATANABE
Mechanisms of Reinforcement Learning and Decision Making in the Primate Dorsolateral Prefrontal Cortex
DAEYEOL LEE, HYOJUNG SEO
Resisting the Power of Temptations. The Right Prefrontal Cortex and Self-Control
DARIA KNOCH, ERNST FEHR
Adding Prediction Risk to the Theory of Reward Learning
KERSTIN PREUSCHOFF, PETER BOSSAERTS
Still at the Choice-Point. Action Selection and Initiation in Instrumental Conditioning
BERNARD W BALLEINE, SEAN B OSTLUND
Plastic Corticostriatal Circuits for Action Learning. What's Dopamine Got to Do with It?
RUI M COSTA
Striatal Contributions to Reward and Decision Making. Making Sense of Regional Variations in a Reiterated Processing Matrix
JEFFERY R WICKENS, CHRISTOPHER S BUDD, BRIAN I HYLAND, GORDON W ARBUTHNOTT
Multiple Representations of Belief States and Action Values in Corticobasal Ganglia Loops
KAZUYUKI SAMEJIMA, KENJI DOYA
Basal Ganglia Mechanisms of Reward-Oriented Eye Movement
OKIHIDE HIKOSAKA
Contextual Control of Choice Performance. Behavioral, Neurobiological, and Neurochemical Influences
JOSEPHINE E HADDON, SIMON KILLCROSS
A "Good Parent" Function of Dopamine. Transient Modulation of Learning and Performance during Early Stages of Training
JON C HORVITZ, WON YUNG CHOI, CECILE MORVAN, YANIV EYNY, PETER D BALSAM
Serotonin and the Evaluation of Future Rewards. Theory, Experiments, and Possible Neural Mechanisms
NICOLAS SCHWEIGHOFER, SAORI C TANAKA, KENJI DOYA
Receptor Theory and Biological Constraints on Value
GREGORY S BERNS, C. MONICA CAPRA, CHARLES NOUSSAIR
Reward Prediction Error Computation in the Pedunculopontine Tegmental Nucleus Neurons
YASUSHI KOBAYASHI, KEN-ICHI OKADA
A Computational Model of Craving and Obsession
A. DAVID REDISH, ADAM JOHNSON
Calculating the Cost of Acting in Frontal Cortex
MARK E WALTON, PETER H RUDEBECK, DAVID M BANNERMAN, MATTHEW F. S RUSHWORTH
Cost, Benefit, Tonic, Phasic. What Do Response Rates Tell Us about Dopamine and Motivation?
YAEL NIV
It was known since a couple of years that oxytocin (OT) increases trust (Kosfeld, et al., 2005): in the Trust game, players transfered more money once they inhale OT. Now recent research also suggest that it increases generosity. In a paper presented at the ESA (Economic Science Association, an empirically-oriented economics society) meeting, Stanton, Ahmadi, and Zak, (from the Center for Neuroeconomics studies) showed that Ultimatum players in the OT group offered more money (21% more) than in the placebo group--$4.86 (OT) vs. $4.03 (placebo).
They defined generosity as "an offer that exceeds the average of the MinAccept" (p.9), i.e., the minimum acceptable offer by the "responder" in the Ultimatum. In this case, offers over $2.97 were categorized as generous. Again, OT subjects displayed more generosity: the OT group offered $1.86 (80% more) over the minimum acceptable offer, while placebo subjects offered $1.03.
Found yesterday, in a paper by Sanfey (nice review paper, by the way):
"Fig. 2. Map of brain areas commonly found to be activated in decision-making studies. The sagittal section (A) shows the location of the anterior cingulate cortex (ACC), medial prefrontal cortex (MPFC), orbitofrontal cortex (OFC), nucleus accumbens (NA), and substantia nigra (SN). The lateral view (B) shows the location of the dorsolateral prefrontal cortex (DLPFC) and lateral intraparietal area (LIP). The axial section (C; cut along the white line in A and B) shows the location of the insula (INS) and basal ganglia (BG)."from:
