My brain has a politics of its own: neuropolitic musing on values and signal detection

Political psychology (just as politicians and voters) identifies two species of political values: left/right, or liberalism/conservatism. Reviewing many studies, Thornhill & Fincher (2007) summarizes the cognitive style of both ideologies:

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.

while in the second:

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-regulation

Thus 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."

What this study--together with other data on conservatives and liberal--might justify is the following hypothesis: what if conservatives and liberals are natural kinds? That is, "homeostatic property clusters", (see Boyd 1991, 1999), categories of "things" formed by nature (like water, mammals, etc.), not by definition? (like supralunar objects, non-cat, grue emerald, etc.) Things that share surface properties (political beliefs and behavior) whose co-occurence can be explained by underlying mechanims (neural processing of conflict monitoring)? Maybe our evolution, as social animals, required the interplay of tradition-oriented and novelty-oriented individuals, risk-prone and risk-averse agents. But why, in the first place, evolution did not select one type over another? Here is another completely armchair hypothesis: in order to distribute, in the social body, the signal detection problem.

What kind of errors would you rather do: a false positive (you identify a signal but it's only noise) or a false negative (you think it's noise but it's a signal)? A miss or a false alarm? That is the kind of problems modeled by signal detection theory (SDT): since there is always some noise and you try to detect signal, you cannot know in advance, under radical uncertainty, what kind of policy you should stick to (risk-averse or risk-prone. "Signal" and "noise" are generic information-theoretic terms that may be related to any situation where an agent tries to find if a stimuli is present:

Is is rather ironic that signal detection theorists employ the term liberal* and conservative* (the "*" means that I am talking of SDT, not politics) to refer to different biases or criterions in signal detection. A liberal* bias is more likely to set off a positive response ( increasing the probability of false positive), whereas a conservative* bias is more likely to set off a negative response (increasing the probability of false negative). The big problem in life is that in certain domains conservatism* pay, while in others it's liberalism* who does (see Proust 2006): when identifying danger, a false negative is more expensive (better safe than sorry) whereas in looking for food a false positive can be more expensive better (better satiated than exhausted). So a robust criterion is not adaptive; but how to adjust the criterion properly? If you are an individual agent, you must altern between liberal* and conservative* criterion based on your knowledge. But if you are part of a group, liberal* and conservative* biases may be distributed: certains individuals might be more liberals* (let's send them to stand and keep watch) and other more conservatives* (let's send them foraging). Collectively, it could be a good solution (if it is enforced by norms of cooperation) to perpetual uncertainty and danger. So if our species evolved with a distribution of signal detection criterions, then we should have evolved different cognitive styles and personality traits that deal differently with uncertainty: those who favor habits, traditions, security, and the others. If liberal* and conservative* criterions are applied to other domains such as family (an institution that existed before the State), you may end up with the Strict Father model and the Nurturant Parent model; when these models are applied to political decision-making, you may end up with liberals/conservatives (no "*"). That would give a new meaning to the idea that we are, by nature, political animals.


Related posts

• A Neuropolitic Look at Political Psychology
• The Political Brain
• A Neuroecomic Picture of Valuation
  

Links

• A clear discussion of the study at The Cognitive Daily.
• Political Psychology (Blackwell Publishing Journal)
• See their special issue: Political Psychology and Social Neuroscience: Strange Bedfellows or Comrades in Arms?, especially this review paper.
• Neuropolitics.org (Ezine)
• Neuropolitics mailing list.
• A presentation of Darren Schreiber research (not professor at UCSD in the Political Science Department) on neural studies of differences between political novices and sophisticates : "When asked political questions, political novices show higher activation in the prefrontal lobes, where deliberative thinking takes place. Political sophisticates show higher levels of temporal lobe activity, which suggests they 'have more meaning attached to these questions' "

References

• Amodio, D. M., Jost, J. T., Master, S. L., & Yee, C. M. (2007). Neurocognitive correlates of liberalism and conservatism. Nature Neuroscience, 10(10), 1246-1247
• Boyd, R. (1991). Realism, Anti-Foundationalism and the Enthusiasm for Natural Kinds. Philosophical Studies, 61(1 - 2), 127.
• Boyd, R. (1999). Kinds, Complexity and Multiple Realization. Philosophical Studies, 95(1 - 2), 67.
• Lakoff, G. (2002). Moral Politics: How Liberals and Conservatives Think. Chicago: University of Chicago Press (read chapter 2 here)
• Proust, J. (2006 ). Metacognition and Animal Rationality. In S. Hurley & M. Nudds (Eds.), Rational Animals. Oxford: Oxford University Press.
  
• Thornhill, R., & Fincher, C. L. (2007). What is the relevance of attachment and life history to political values? Evolution and Human Behavior, 28(4), 215-222.
• Thorisdottir, H., Jost, J. T., Liviatan, I., & Shrout, P. E. (2007). Psychological Needs and Values Underlying Left-Right Political Orientation: Cross-National Evidence from Eastern and Western Europe. Public Opin Q, nfm008.

Cognitive Control and Dopamine: A Very Brief Intro

In certain situations, learned routines are not enough. When situations are too uncommon, dangerous and difficult or when they require the overcoming of a habitual response, decisions must be guided by representations. Acting upon an internal representation is referred to, in cognitive science, as cognitive control or executive function[1]. The agent is lead by a representation of a goal and will robustly readjust its behavior in order to maintain the pursuit of a goal. The behavior is then controlled ‘top-down’, not ‘bottom-up’. In the Stroop task, for instance, subject must identify the color of written words such as ‘red’, ‘blue' or ‘yellow’ printed in different colors (the word and the ink color do not match). The written word, however, primes the subject to focus on the meaning of the word instead of focusing on the ink’s color. If, for instance, the word “red” is written in yellow ink, subjects will utter “red” more readily than they say “yellow”. There is a cognitive conflict between the semantic priming induced by the word and the imperative to focus on the ink’s color. In this task, cognitive control mechanisms ought to give priority to goals in working memory (naming ink color) over external affordances (semantic priming). An extreme lack of cognitive control is exemplified in subjects who suffer from “environmental dependency syndrome”[2]: they will spontaneously do what their environment indicates of affords them: for instance, they will sit on a chair whenever they see one, or undress and get into a bed whenever they are in presence of a bed (even if it’s not in a bedroom).

Cognitive control is thought to happen mostly in the prefrontal cortex (PFC),[3] an area strongly innervated by midbrain dopaminergic fibers. Prefrontal areas activity is associated with maintenance and updating of cognitive representations of goals. Moreover, impairment of these areas results in executive control deficits (such as the environmental dependency syndrome). Since working memory is limited, however, agents cannot hold everything in their prefrontal areas. Thus the brain faces a tradeoff between attending to environmental stimuli (that may reveal rewards or danger, for instance) and maintaining representation of goals, viz. the tradeoff between rapid updating and active maintenance [4]. Efficiency requires brains to focus on relevant information and again, dopaminergic systems are involved in this process. According to many researches[5], dopaminergic activity implements a ‘gating’ mechanism, by which the PFC alternates between rapid updating and active maintenance. A higher level of dopamine in prefrontal area signals the need to rapidly update goals in working memory (rapid updating: ‘opening the gate’), while a lower level induces resistance to afferent signals and thus a focus on represented goals (active maintenance: ‘shutting the gate’). Hence dopaminergic neurons select which information (goal representation or external environment) is worth paying attention to. This mechanisms is thought to be implemented by different dopamine receptors, the D1 and D2 being responsive to different dopamine concentration (D1-low, D2-high):

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.

Here is a neurobiological description of the phenomena, with neuroanatomical details:

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.

Hence it is interesting to note that dopaminergic neurons are involved in basic motivation and reinforcement, and in more abstract operations such as cognitive control.



Notes and references

1. (Norman & Shallice, 1980; Shallice, 1988)
2. (Lhermitte, 1986)
3. (Duncan, 1986; Koechlin, Ody, & Kouneiher, 2003; Miller & Cohen, 2001; O’Reilly, 2006)
4. (O’Reilly, 2006)
5. (Montague, Hyman, & Cohen, 2004; O'Donnell, 2003; O’Reilly, 2006)

• Durstewitz, D., Seamans, J. K., & Sejnowski, T. J. (2000). Dopamine-Mediated Stabilization of Delay-Period Activity in a Network Model of Prefrontal Cortex. Journal of Neurophysiology, 83(3), 1733-1750.
• Duncan, J. (1986). Disorganization of behavior after frontal lobe damage. Cognitive Neuropsychology, 3(3), 271-290.
• Koechlin, E., Ody, C., & Kouneiher, F. (2003). The Architecture of Cognitive Control in the Human Prefrontal Cortex. Science, 302(5648), 1181-1185.
• Lhermitte, F. (1986). Human autonomy and the frontal lobes. Part 11: Patient behavior in complex and social situations: The “environmental dependency syndrome.” Annals of Neurology, 19(4), 335–343.
• Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24(1), 167-202.
• Montague, P. R., Hyman, S. E., & Cohen, J. D. (2004). Computational roles for dopamine in behavioural control. Nature, 431(7010), 760.
• Norman, D. A., & Shallice, T. (1980). Attention to Action: Willed and Automatic Control of Behavior: Center for Human Information Processing, University of California, San Diego.
• O'Donnell, P. (2003). Dopamine gating of forebrain neural ensembles. European Journal of Neuroscience, 17(3), 429-435.
• O’Reilly, R. C. (2006). Biologically Based Computational Models of High-Level Cognition Science, 314, 91-94.
• Shallice, T. (1988). From neuropsychology to mental structure. Cambridge [England] ; New York: Cambridge University Press.