Low Latent Inhibition, high faith in intuition and psychosis/creativity

Well, the cluster goes together. Previous research has found that Low LI and psychosis (schizophrenia) and creativity are related; previous research has also found that psychotic /some types of creative people have more faith in intuition; and this research ties things by showing that Low LI and high faith in intuition are correlated.

The research under question is by Kaufman and in it he explores the dual-process theories of cognition- the popular slow high road of deliberate conscious reasoning and the fast low road of unconscious processing. I would rather have the high road consist of both cognitive and affective factors and similarly the unconscious low road consist of both cognitive and affective factors. Kaufman focuses on the unconscious low road and his factor analysis reveal three factors: Faith in intuition: a meta cognition about ones tendency to use intuition; Holistic intuition: the cognitive factor; and affective intuition: the affective factor. with this in mind let us see what Kaufman's thesis is:

He first introduces the low road and the high road:

In recent years, dual-process theories of cognition have become increasingly popular in explaining cognitive, personality, and social processes (Evans & Frankish, 2009). Although individual differences in the controlled, deliberate, reflective processes that underlay System 2 are strongly related to psychometric intelligence (Spearman, 1904) and working memory (Conway, Jarrold, Kane, Miyake, & Towse, 2007), few research studies have investigated individual differences in the automatic, associative, nonconscious processes that underlay System 1. Creativity and intelligence researchers might benefit from taking into account dual-process theories of cognition in their models and research, especially when exploring individual differences in nonconscious cognitive processes.

Then he explain LI:

Here I present new data, using a measure of implicit processing called latent inhibition (LI; Lubow, Ingberg-Sachs, Zalstein-Orda, & Gewirtz, 1992). LI reflects the brain’s capacity to screen from current attentional focus stimuli previously tagged as irrelevant (Lubow, 1989). LI is often characterized as a preconscious gating mechanism that automatically inhibits stimuli that have been previously experienced as irrelevant from entering awareness, and those with increased LI show higher levels of this form of inhibition (Peterson, Smith, & Carson, 2002). Variation in LI has been documented across a variety of mammalian species and, at least in other animals, has a known biological basis (Lubow & Gerwirtz, 1995). LI is surely important in people’s everyday lives—if people had to consciously decide at all times what stimuli to ignore, they would quickly become overstimulated.
Indeed, prior research has documented an association between decreased LI and acute-phase schizophrenia (Baruch, Hemsley, & Gray, 1988a, 1988b; Lubow et al., 1992). It is known, however, that schizophrenia is also associated with low executive functioning (Barch, 2005). Recent research has suggested that in highfunctioning individuals (in this case, Harvard students) with high IQs, decreased LI is associated with increased creative achievement (Carson et al., 2003). Therefore, decreased LI may make an individual more likely to perceive and make connections that others do not see and, in combination with high executive functioning, may lead to the highest levels of creative achievement. Indeed, the link between low LI and creativity is part of Eysenck’s (1995) model of creative potential, and Martindale (1999) has argued that a major contributor to creative thought is cognitive disinhibition.

He then relates this to intuition and presents his thesis:

A concept related to LI is intuition. Jung’s (1923/1971, p. 538) original conception of intuition is “perception via the unconscious.” Two of the most widely used measures of individual differences in the tendency to rely on an intuitive information-processing style are Epstein’s Rational- Experiential Inventory (REI; Pacini & Epstein, 1999) and the Myers-Briggs Type Indicator (MBTI) Intuition/Sensation subscale (Myers, McCaulley, Quenk, & Hammer, 1998). Both of these measures have demonstrated correlations with openness to experience (Keller, Bohner, & Erb, 2000; McCrae, 1994; Pacini & Epstein, 1999), a construct that has in turn shown associations with a reduced LI (Peterson & Carson, 2000; Peterson et al., 2002), as well as with divergent thinking (McCrae, 1987) and creative achievement.
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The main hypothesis was that intuitive cognitive style is associated with decreased latent inhibition.

He found support for the hypothesis from his data. It seemed people with low LI were high in faith in intuition factor. Here is what he discusses:

The results of the current study suggest that faith in intuition, as assessed by the REI and the MBTI Thinking/Feeling subscale, is associated with decreased LI. Furthermore, a factor consisting of abstract, conceptual, holistic thought is not related to LI. Consistent with Pretz and Totz (2007), exploratory factor analysis revealed a distinction between a factor consisting of REI Experiential and MBTI Thinking/Feeling and a factor consisting of MBTI Intuition/Sensation and REI Rational Favorability. This further supports Epstein’s (1994) theory that the experiential system is directly tied to affect. The finding that MBTI Intuition/Sensation and REI Rational Favorability loaded on the same factor supports the idea that the type of intuition that is being measured by these tasks is affect neutral and more related to abstract, conceptual, holistic thought than to the gut feelings that are part of the Faith in Intuition factor.

Here are the broader implications:

The current study adds to a growing literature on the potential benefits of a decreased LI for creative cognition. Hopefully, with further research on the biological basis of LI, as well as its associated behaviors, including interactions with IQ and working memory, we can develop a more nuanced understanding of creative cognition. There is already promising theoretical progress in this direction.

Peterson et al. (2002) and Peterson and Carson (2000) found a significant relationship between low LI and three personality measures relating to an approach-oriented response and sensation-seeking behavior: openness to experience, psychoticism, and extraversion. Peterson et al. found that a combined measure of openness and extraversion (which was referred to as plasticity) provided a more differentiated prediction of decreased LI.

Peterson et al. (2002) argued that individual differences in a tendency toward exploratory behavior and cognition may be related to the activity of the mesolimbic dopamine system and predispose an individual to perceive even preexposed stimuli as interesting and novel, resulting in low LI. Moreover, under stressful or novel conditions, the dopamine system in these individuals will become more activated and the individual will instigate exploratory behavior. Under such conditions, decreased LI could help the individual by allowing him or her more options for reconsideration and thereby more ways to resolve the incongruity. It could also be disadvantageous in that the stressed individual risks becoming overwhelmed with possibilities. Research has shown that the combination of high IQ and reduced LI predicts creative achievement (Carson et al., 2003). Therefore, the individual predisposed to schizophrenia may suffer from an influx of experiential sensations and possess insufficient executive functioning to cope with the influx, whereas the healthy individual low in LI and open to experience (particularly an openness and faith in his or her gut feelings) may be better able to use the information effectively while not becoming overwhelmed or stressed out by the incongruity of the situation. Clearly, further research will need to investigate these ideas, but an understanding of the biological basis of individual differences in different forms of implicit processing and their relationship to openness to experience and intuition will surely increase our understanding of how certain individuals attain the highest levels of creative accomplishment.

To me this is exciting, the triad of creative/psychotic cognitive style, intuition and Latent Inhibition seem to gel together. the only grip eI have is that the author could also have measured intuition directly by using some insight problems requiring 'aha' solutions; maybe that is a project for future!

Kaufman, S. (2009). Faith in intuition is associated with decreased latent inhibition in a sample of high-achieving adolescents. Psychology of Aesthetics, Creativity, and the Arts, 3 (1), 28-34 DOI: 10.1037/a0014822

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Science 2.0 : what is and what needs to be

Chris Patil , of Ouroboros , and Vivian Siegel have an interesting and thought-provoking op-ed in DMM, on the issue of the promise and the not-so-promising actuality of science 2.0.

They are right when they say that they doubt if science 2.0 wold attract more scientists than the currently active science bloggers and the likes; and I share their skepticism. However, while they believe that all the tools for online collaboration are already in place, I on the other hand think we need a more formalized one-stop system for scientists, where all their sharing, networking and collaborating needs are met. It doesn't really attract me that much if I have to collaborate using FrinedFeed, share using twitter , learn using google reader, disseminate using blogger, or network using acaedmia.org etc. I am sure a scientific virtual water-cooler will soon emerge , but till that time I am skeptical of actual practicing scientists using science 2.0 in their day-to-day life; of course how the current breed of science bloggers use these tools and the kind of successful collaborations they can demonstrate would easily and likely define the way science 2.0 shapes up. Needless to say I am excited to be part of the early adopters and while twitter/ FF have not lived to their promise, the relatively older sibling of blogging , has managed to land me virtual collaborations, where I am discussing research ideas with persons who actually perform experiments (I am by circumstances an armchair scientist). For an example see comments by Kim on my last post on action selection, which has also led to some offline discussion and a possible future collaboration. For me science 2.0 works perfectly because I am not in the competitive business of being the first to publish a paper or to secure tenure etc and thus can put my 'ideas to the world' as freely as they come. At the same time, I am more than aware that the apprehensions scientists have over being stolen from are genuine and need more thought and care while designing the science 2.0 tools.

I will now like to quote some passages from the op-ed that I liked the most.

Suppose that your unique combination of training and expertise leads you to ask a novel question that you are not currently able to address. You advertise your idea to the world, seeking others who might be able to help. You find that Miranda has an idle machine, built for another purpose, that could be modified just so to help answer your question, if only she had a few samples from an appropriate patient. Hugo, busy with clinical responsibilities, has no time, but has a freezer full of biopsy tissues from such patients. Steve has the time and inclination to modify Miranda’s machine and to write the scripts to drive the analysis. Polly watches the whole process to make sure that the study has sufficient statistical power. Correspondence among the interested parties could be recorded in a publicly available forum, along with data and analysis as they emerge – allowing the entire scientific world to look on and to offer advice on the framing of the question, the design of the machine, the processing of the samples and the interpretation of the results.

In other words, what if you could think a thought at the world and have the world think back? What if everyone in the world were in your lab – a ‘hive mind’ of sorts, but composed of countless creative intellects rather than mindless worker ants, and one in which resources, reagents and effort could be shared, along with ideas, in a manner not dictated by institutional and geographical constraints?

What if, in the process, you could do actual scientific research? Granted, it would be research for which no one person (or group) could take credit, but research all the same. Progress might even occur more rapidly than it does in our world, where new knowledge is shared in the form of highly refined distillates of years of work.

I fit perfectly the person who can ask novel questions, experimental suggestions, but lacks expertise / time/ resources/ sanctity to run them. to me this hive mind would be god-send. If only, it could take off!! But then they provide a reality check:

Beyond raising concerns about the philosophy of communication, our utopian fantasy ignores important aspects of human nature. In any real world, finding collaborators would require a great deal more than shooting questions into the void and cocking an ear for the echo. In particular, in order to find a colleague with exactly the right complement of skills, interest and dependability, we need not only openness but trust. Within a laboratory group (at least, in a functional one), trust is part and parcel of lab citizenship; we and our colleagues voluntarily suspend our competitive urges in order to create a cooperative (and mutually beneficial) environment. In the wider world, however, the presumption is reversed: we tend to be cagey and suspicious in our interactions with other scientists. When we step outside the laboratory door, we transform from Musketeers (‘All for one…!’) to Mulder and Scully (‘Trust no one.’).

Oh , how I hate them to have burst my fantasy bubble by providing this reality check!! But thankfully not being bound to any laboratory I am at least immune form this cooperate or compete dilemma. I just hope there are more people like me (or enuff foolish scientists not really bothered about plagiarism) to reach a critical mass and snowball science 2.0. and then they touch on some subtle aspects of the above:

Another clash between utopia and human nature occurs at the level of publicly sharing preliminary data. In particular, during the period of transition between the status quo and the glorious future, openness may be provably irrational from a game-theoretical standpoint. If I share my data but my competitors do not, I’ve laid all of my cards out on the table, whereas others play theirs close to the vest – a bad bet under any circumstances. At best, my openness allows my adversaries to strategize; at worst, it allows them to steal my ideas. Perhaps the term ‘stealing’ is too harsh: in the words of our estimable thesis advisor, Peter Walter, ‘you can’t unthink a thought.’ Once an idea is in the field, can anyone be blamed for reacting to it in a way that is personally optimal? We already live with this moral conundrum every time we agree to review papers and need to balance the expectation of confidentiality with our own desire to shape our own future plans on the basis of the best and most current information. Radical sharing will require ways for individuals to protect themselves from the occasionally deleterious consequences of rational self-interest.

Perhaps most importantly from a practical perspective: information doesn’t share itself. From establishing an open record of preliminary discussions to freely disseminating experimental results, each step in the process requires an infrastructure. A framework, composed of software and web tools, is necessary in order to empower individual scientists to share information without each of them having to write the enabling code from scratch.

The weakest part of the article in my opinion, is when they argue that the tools are already available. I beleive we are still in the early stages of experimenting; new concepts and sites like biomedexperts need to be experimented with and I am sure we will soon be there. The authors suggest several sites where scientists in science 2.0 purportedly hang and then they point to reasons why that model has not succeeded yet:

Social networking tools also suffer from a variant of the ‘no one will go there until everyone goes there’ problem – the ‘me too’ dilution factor. Just as in the social/job space (Facebook, LinkedIn, MySpace, Bebo), there are myriad networks to choose from and many are too similar to distinguish. To a new user with limited time, it’s not obvious whether to try and join multiple networks, arbitrarily choose one, or wait for a clear winner to emerge.

Here's praying that a clear victor emerges soon!


Patil, C., & Siegel, V. (2009). This revolution will be digitized: online tools for radical collaboration Disease Models and Mechanisms, 2 (5-6), 201-205 DOI: 10.1242/dmm.003285

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Action-selection and Attention-allocation: a common problem and a common solution?

I have recently blogged a bit about action-selection and operant learning, emphasizing that the action one chooses, out of many possible, is driven by maximizing the utility function associated with the set of possible actions, so perhaps a quick read of last few posts would help appreciate where I come from .

To recap, whenever an organism makes a decision to indulge in an act (an operant behavior), there are many possible actions from which it has to choose the most appropriate one. Each action leads to a possibly different Outcome and the organism may value the outcomes differentially. this valuation may be both objective (how the organism actually 'likes' the outcome once it happens, or it may be subjective and based on how keenly the organism 'wants' the outcome to happen independent on whether the outcome is pleasurable or not. Also, it is never guaranteed that the action would produce the desired/expected outcome. There is always some probability associated that the act may or may not result in the expected outcome. Also, on a macro level the organism may lack sufficient energy required to indulge in the act or to carry it out successfully to completion. Mathematically, with each action one can associate a utility U= E x V (where U is utility of act; E is expectancy as to whether one would be able to carry the act and if so whether the act would result in desired outcome; and V is the Value (both subjective and objective0 that one has assigned to the outcome. The problem of action-selection then is simply to maximize the utility given different acts n and to choose the action with maximum utility.

Today I had an epiphany; doesn't the same logic apply to allocating attention to the various stimuli that bombard us. Assuming a spotlight view of attention, and assuming that there are limited attentional resources, one is constantly faced with the problem of finding which stimuli in the world are salient and need to be attended to. Now, the leap I am making is that attention-allocation just like choosing to act volitionally is an operant and not a reactive, but pro-active process. It may be unconscious, but still it involves volition and 'choosing'. Remember, that even acts can be reactive and thus there is room for reactive attention; but what I am proposing is that the majority of attention is pro-active- actively choosing between stimuli and focusing on one to try and better predict the world. We are basically prediction machines that want to predict beforehand the state of the world that is most relevant to us and this we do by classical or pavlovian conditioning. We try to associate stimuli (CS) with stimuli(UCS) or response (UCR) and thus try to ascertain what state of world at time T would be given that stimulus (CS) has happened. Apart from prediction machines we are also Agents that try to maximize rewards and minimize punishments by acting on this knowledge and acting and interacting with the world. There are thousands of actions we can indulge in- but we choose wisely; there are thousands of stimuli in the external world, but we attend to salient features wisely.

Let me elaborate on the analogy. While selecting an action we maximize reward and minimize punishment, basically we choose the maximal utility function; while choosing which stimuli to attend to we maximize our foreknowledge of the world and minimize surprises, basically we choose the maximal predictability function; we can even write an equivalent mathematical formula: Predictability P = E x R where P is the increase in predictability due to attending to stimulus 1 ; E is probability that stimulus 1 correctly leads to prediction of stimulus 2; and R is the Relevance of stimulus 2(information) to us. Thus the stimulus one would attend, is the one that leads to maximum gain in predictability. Also, similar to the general energy level of organism that would bias as to whether, and how much, the organism acts or not; there is a general arousal level of the organism that biases whether and how much it would attend to stimuli.

So, what new insights do we gain from this formulation? First insight we may gain is by elaborating the analogy further. We know that basal ganglia in particular and dopamine in general is involved in action-selection. Dopamine is also heavily involved in operant learning. We can predict that dopamine systems , and the same underlying mechanisms, may also be used for attention-allocation. Dopamine may also be heavily involved in classical learning as well. Moreover, the basic computations and circuitry involved in allocating attention should be similar to the one involved in action-selection. Both disciplines can learn from each other and utilize methods developed in one field for understanding and elaborating phenomenon in the other filed. For eg; we know that dopamine while coding for reward-error/ incentive salience also codes for novelty and is heavily involved in novelty detection. Is the novelty detection driven by the need to avoid surprises, especially while allocating attention to a novel stimulus.

What are some of the prediction we can make form this model: just like the abundant literature on U= E x V in decision making and action selection literature, we should be able to show the independent and interacting effects of Expectancy and Relevance on attention-grabbing properties of stimulus. The relevance of different stimuli can be manipulated by pairing them with UCR/UCS that has different degrees of relevance. The expectancy can be differentially manipulated by the strength of conditioning; more trials would mean that the association between the CS and UCS is strong; also the level of arousal may bias the ability to attend to stimuli. I am sure that there is much to learn in attention research from the research on decision-making and action-selection and the reverse would also be true. It may even be that attention-allocation is actually conceptualized in the above terms; if so I plead ignorance of knowledge of this sub-field and would love to get a few pointers so that I can refine my thinking and framework.

Also consider the fact that there is already some literature implicating dopamine in attention and the fact that dopamine dysfunction in schizophrenia, ADHD etc has cognitive and attentional implications is an indication in itself. Also, the contextual salience of drug-related cues may be a powerful effect of dapomine based classical conditioning  and attention allocation hijacking the normal dopamine pathways in addicted individuals. 

Lastly, I got set on this direction while reading an article on chaining of actions to get desired outcomes and how two different brain systems ( a cognitive (Prefrontal) high road one based on model-based reinforcement learning and a unconscious low road one (dorsolateral striatal) based on model-free reinforcement learning)may be involved in deciding which action to choose and select. I believe that the same conundrum would present itself when one turns attention to the attention allocation problem, where stimuli are chained together and predict each other in succession); I would predict that there would be two roads involved here too! but that is matter for a future post. for now, would love some honest feedback on what value, if any, this new conceptualization adds to what we already know about attention allocation.

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Low Mood and Risk Aversion: a poor State outcome?

Daniel Nettle, writes an article in Journal Of Theoretical Biology about the evolution of low mood states. Before I get to his central thesis, let us review what he reviews:

Low mood describes a temporary emotional and physiological state in humans, typically characterised by fatigue, loss of motivation and interest, anhedonia (loss of pleasure in previously pleasurable activities), pessimism about future actions, locomotor retardation, and other symptoms such as crying.
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This paper focuses on a central triad of symptoms which are common across many types of low mood, namely anhedonia, fatigue and pessimism. Theorists have argued that, whereas their opposites facilitate novel and risky behavioural projects. These symptoms function to reduce risk-taking. They do this, proximately, by making the potential payoffs seem insufficiently rewarding (anhedonia), the energy required seem too great (fatigue), or the probability of success seem insufficiently high (pessimism). An evolutionary hypothesis for why low mood has these features, then, is that is adaptive to avoid risky behaviours when one is in a relatively poor current state, since one would not be able to bear the costs of unsuccessful risky endeavors at such times .

I would like to pause here and note how he has beautifully summed up the low mood symptoms and key features; taking liberty to define using my own framework of Value X Expectancy and distinction between cognitive('wanting') and behavioral ('liking') side of things :

• Anhedonia: behavioral inability to feel rewarded by previously pleasurable activities. Loss of 'liking' following the act. Less behavioral Value assigned.
• Loss of motivation and interest: cognitive inability to look forward to or value previously desired activities. Loss of 'wanting' prior to the act. Less cognitive Value assigned.
• Fatigue: behavioral inability to feel that one can achieve the desired outcome due to feelings that one does not have sufficient energy to carry the act to success. Less behavioral Expectancy assigned.
• Pessimism: cognitive inability to look forward to or expect good things about the future or that good outcomes are possible. Less cognitive Expectancy assigned.

The reverse conglomeration is found in high mood- High wanting and liking, high energy and outlook. Thus, I agree with Nettle fully that low mood and high mood are defined by these opposed features and also that these features of low and high mood are powerful proximate mechanisms that determine the risk proneness of the individual: by subjectively manipulating the Value and Expectancy associated with an outcome, the high and low mood mediate the risk proneness that an organism would display while assigning a utility to the action. Thus, it is fairly settled: if ultimate goal is to increase risk-prone behavior than the organism should use the proximate mechanism of high mood; if the ultimate goal is to avoid risky behavior, then the organism should display low mood which would proximately help it avoid risky behavior.

Now let me talk about Nettle's central thesis. It has been previously proposed in literature that low mood (and thus risk-aversion) is due to being in a poor state wherein one can avoid energy expenditure (and thus worsening of situation) by assuming a low profile. Nettle plays the devil's advocate and argues that an exactly opposite argument can be made that the organism in a poor state needs to indulge in high risk (and high energy) activities to get out of the poor state. Thus, there is no a prior reason as to why one explanation may be more sound than the other. To find out when exactly high risk behavior pay off and when exactly low risk behaviors are more optimal, he develops a model and uses some elementary mathematics to derive some conclusions. He, of course , bases his model on a Preventive focus, whereby the organism tries to minimize getting in a state R , which is sub-threshold. He allows the S(t) to be maximized under the constraint that one does not lose sight of R. I'll not go into the mathematics, but the results are simple. When there is a lot of difference between R (dreaded state) and S (current state), then the organism adopts a risky behavioral profile. when the R and S are close, he maintains low risk behavior, however when he is in dire circumstances (R and S are very close) then risk proneness again rises to dramatic levels. To quote:

The model predicts that individuals in a good state will be prepared to take relatively large risks, but as their state deteriorates, the maximum riskiness of behaviour that they will choose declines until they become highly risk-averse. However, when their state becomes dire, there is a predicted abrupt shift towards being totally risk-prone. The switch to risk-proneness at the dire end of the state continuum is akin to that found near the point of starvation in the original optimal foraging model from which the current one is derived (Stephens, 1981). The graded shift towards greater preferred risk with improving state is novel to this model, and stems from the stipulation that if the probability of falling into the danger zone in the next time step is minimal, then the potential gain in S at the next time step should be maximised. However, a somewhat similar pattern of risk proneness in a very poor state, risk aversion in an intermediate state, and some risk proneness in a better state, is seen in an optimal-foraging model where the organism has not just to avoid the threshold of starvation, but also to try to attain the threshold of reproduction (McNamara et al., 1991). Thus, the qualitative pattern of results may emerge quite generally from models using different assumptions.

Nettle, then extrapolates the clinical significance from this by proposing that 'agitated' / 'excited' depression can be explained as when the organism is in dire straits and has thus become risk-prone. He also uses a similar logic for dysphoric mania although I don't buy that. However, I agree that euphoric mania may just be the other extreme of high mood and more risk proneness and goal achievements; while depression the normal extreme of low mood and adverse circumstances and risk aversion. To me this model ties up certain things we know about life circumstances and the risk profile and mood tone of people and contributes to deepening our understanding.

Nettle, D. (2009). An evolutionary model of low mood states Journal of Theoretical Biology, 257 (1), 100-103 DOI: 10.1016/j.jtbi.2008.10.033

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The bipolar phenotype: Excessive self-regulatory focus?

In my last post I had hinted that bipolar mania and depression may both be characterized by an excessive and overactive self-regulatory focus: with promotion focus being related to Mania and prevention focus being related to depression. It is important to pause and note that the bipolar propensity is towards more self-referential goal-directed activity resulting in excessive use of self-regulatory focus. To clarify, I am sticking my neck out and claiming that depression is marked by an excessive obsession with self-oriented goal directed activities- but with a preventive focus thus focusing more on self's responsibilities and duties , obligations etc with respect to other near and dear ones. Mania on the other hand, also has excessive self-oriented goal-directed focus, but the focus is promotional with obsession with hopes, aspirations etc, which are relatively more inward-focused and not too much dependent on significant others.

Thus, my characterization of depression as a state where regulatory reference is negative (one is focused on avoiding landing up in a negative end-state like being a burden on others), the regulatory anticipation is negative ( one anticipates pain as a result of almost any act one may perform and thus dreads day-to-day- activity) and the regulatory focus is negative (preventive focus whereby one is more concerned with duties and obligations to perform and security is a paramount need). The entire depressive syndrome can be summed up as an over activity of avoidance based mechanisms. However, please note that still there is an excess of self-referential/self-focused thinking and one is greatly motivated (although might be lacking energy) to bridge the differences between the real self and the 'ought' self. One can say that one's whole life revolves around trying to become the 'ought' self, or rather one conceptualizes oneself in terms of the 'ought' self.

Contrast this with Mania, where the regulatory reference is positive (one is focused on achieving something grandiose ) , regulatory anticipation is positive (one feels in control and believes that only good things can happen to the self) and regulatory focus is positive (promotional focus whereby one is more concerned with hopes, aspirations etc and growth / actualization needs). Still, juts like in depression there is an excess of focus on self and one is greatly motivated (and also has the energy) to bridge the difference between the real and the 'ideal' self. One can say that one's whole life revolves around trying to become the 'ideal' self , or rather one conceptualizes oneslef in terms of an 'ideal' self.

What can we predict from above: we know that brain's default network is involved in self-focused thoughts and ruminations. We can predict, and know for a fact, that the default network is overactive in schizophrenics (and thus by extension in bipolars who I believe have the same underlying pathology, at least as far as psychotic spectrum is concerned)and thus we can say with confidence that indeed the regulatory focus should be high for bipolars and this should be correlated with default network activity. We can also predict that during the Manic phase, the promotion focus related neural network should be more active and in depressive phase the prevention-related areas of the brain should be more active. this last hypothesis still needs experimentation, but lets backtrack a bit and first look at the neural correlates of the promotion and preventive regulatory self-focus.

For this, I refer the readers to an , in my view, important study that tried to dissociate the medial PFC and PCC activity (both of which belong to the default network) while people engaged in self-reflection. Here is the abstract of the study:

Motivationally significant agendas guide perception, thought and behaviour, helping one to define a ‘self’ and to regulate interactions with the environment. To investigate neural correlates of thinking about such agendas, we asked participants to think about their hopes and aspirations (promotion focus) or their duties and obligations (prevention focus) during functional magnetic resonance imaging and compared these self-reflection conditions with a distraction condition in which participants thought about non-self-relevant items. Self-reflection resulted in greater activity than distraction in dorsomedial frontal/anterior cingulate cortex and posterior cingulate cortex/precuneus, consistent with previous findings of activity in these areas during self-relevant thought. For additional medial areas, we report new evidence of a double dissociation of function between medial prefrontal/anterior cingulate cortex, which showed relatively greater activity to thinking about hopes and aspirations, and posterior cingulate cortex/precuneus, which showed relatively greater activity to thinking about duties and obligations. One possibility is that activity in medial prefrontal cortex is associated with instrumental or agentic self-reflection, whereas posterior medial cortex is associated with experiential self-reflection. Another, not necessarily mutually exclusive, possibility is that medial prefrontal cortex is associated with a more inward-directed focus, while posterior cingulate is associated with a more outward-directed, social or contextual focus.

The authors then touch upon something similar to what I have said above, that one can be too much planful or goal-directed (bipolar propensity) , but it would still make sense to find whether the focus is promotional or preventive. To quote:

The idea of variation in individuals’ regulatory focus highlights the difference between agendas and traits; two people could both be described by the trait ‘planful’, but planful about what? A person with a predominantly promotion focus would be more likely to be planful about attaining positive rewards or outcomes, while a person with a predominantly prevention focus would be more likely to be planful about avoiding negative events or outcomes. Although a promotion or prevention focus may dominate, the aspects of the self that are active change dynamically across situations (e.g. Markus and Wurf, 1987), thus most individuals have both promotion and prevention agendas. For example, the same person can hold both the hope of becoming rich (a promotion agenda) and the duty to support an aging parent (a prevention agenda), or the aspiration to be a good citizen and the obligation to be a well-informed voter. As individuals, hopes and aspirations and duties and obligations make up a large part of our mental life and constitute the motivational scaffolding for much of our behaviour.

Now comes the study design:

The present studies investigated neural activity when participants were asked to think about self-relevant agendas related to either a promotion (think about your hopes and aspirations) or prevention (think about your duties and obligations) focus. We compared neural activity associated with thinking about these two different types of self-relevant agendas and with thinking about non-self-relevant topics (distraction). We expected greater activity in anterior and/or posterior medial regions associated with these two self-reflection conditions compared with the distraction control condition because thinking about one's agendas, like thinking about one's traits, is self-referential. Such a finding would also be consistent, for example, with Luu and Tucker's (2004) proposal that both anterior cingulate and posterior cingulate cortex contribute to action regulation by representing goals and expectancies.

And this is what they found:

A double dissociation was found when participants were cued to think about promotion and prevention agendas on different trials for the first time during scanning (Experiment 2) and when they spent several minutes thinking about either promotion or prevention agendas before scanning (Experiment 1), indicating that it results from what participants are thinking about during the scan and not from some general effect (e.g. mood) carried over from the pre-scan period of self-reflection,

Here is what they discuss:

In short, the double dissociation between medial PFC and anterior/inferior medial posterior areas and our two self-reflection conditions indicates that these brain areas serve somewhat different functions during self-focus. There are a number of interesting possibilities that remain to be sorted out. Differential activity in these anterior medial and posterior medial regions as a function of the types of agendas participants were asked to think about could reflect: (i) differences in the representational content in the specific features of agendas, schemas, possible selves and so forth that constitute hopes and aspirations on the one hand and duties and obligations on the other (cf. Luu and Tucker, 2004); (ii) differences in the type(s) of component processes these agendas are likely to engage and/or the representational content they are likely to activate, for example, discovering new possibilities (hopes) vs retrieving episodic memories (e.g. Maddock et al., 2001) of past commitments (duties); (iii) differences in affective significance of hopes and aspirations (attaining the positive) and duties and obligations (avoiding the negative, Higgins, 1997; 1998); (iv) different aspects of the subjective experience of self, such as the subjective experience of control (an instrumental self) vs the subjective experience of awareness (an experiential self; Johnson, 1991; Johnson and Reeder, 1997; compare, e.g. Searle, 1992 and Weiskrantz, 1997, vs Shallice, 1978 and Umilta, 1988); (v) differences in the social significance of hopes and aspirations (more individual) and duties and obligations (involving others). This last possibility is suggested by findings linking the posterior cingulate with taking the perspective of another (Jackson et al., 2006). It may be that thinking about duties and obligations (a more outward focus) tends to involve more perspective-taking than does thinking about hopes and aspirations (a more inward focus). The greater number of mental/emotional references from the promotion group on the pre-scan essay and the tendency for a greater number of references to others from the prevention group are consistent with the hypothesis that medial PFC activity is associated with a more inward focus whereas posterior cingulate/precuneus activity is associated with a more outward, social focus. Clarifying the basis of the similarities and differences between neural activation associated with thinking about hopes and aspirations vs duties and obligations would begin to help differentiate the relative roles of brain regions in different types of self-reflective processing.

They do discuss clinical significance of their studies , but not in terms I would have loved to. I would like to see, whether there is state/trait hyperactivity and dissociation between the mPFC and PCC activation when the variable of depressive episode or manic episode subject is introduced. I'll place my bets that there would be an interaction between the type of episode and the over activity in the corresponding default-brain regions; but would like to see that data collected.

So my thesis is that the self-reflective and focused default network is overactive in biploar/psychotic spectrum people, but a bias or tilt towards promotion or preventive focus leads to their recurring and periodic episdoes of mania and depression.

Lastly let me touch upon affect in these state and what Higgins had to say about this in his paper covered yesterday. Higgins proposed that bipolar is due to a promotional focus, with mania induced when there is not much mismatch (or awareness of mismatch) between the ideal and real self; while depression or sadness and melancholia induced when one becomes aware of the discrepancy between the ideal and the real self. He proposes that 'ought' and real self discrepancy leads to anxiety and nervousness/ agitation; while a preventive focus and congruency between 'ought' and real leads to calmness/quiescence.

I disagree with his formulations, in as much as I differentiate between a regulatory focus and the corresponding awareness of discrepancies in that direction. To Higgins they are the same; if someone has a promotional focus , he would also be more aware of the discrepancies between his ideal and real self and thus be saddened. I disagree. I believe that if one has a promotional focus one is driven by goals to make the resl self as close to the ideal self as possible and if one is not able to do so, one would use defense mechanisms to delude oneself , but will not admit to its reality, as the reality of incongruence along the focused dimension is too painful. However, because on is consciously focused on promotions, one would be aware of trade-offs and will acknowledge to himself that his 'ought' self, which anyway is not too important for his self-concept, is not congruent to the real self. Thus, one wit a predominant promotion focus may be painfully aware of the discrepancy between his 'ought' and real self and thus might be nervous, agitated/ irritable- all symptoms of Mania.

A depressive person on the other hand has a predominant preventive focus and all actions/ ruminations are driven by responsibilities and obligations. Here acknowledging to oneself that one has failed in meeting obligations may be catastrophic so one will try to delude oneself that one is closer to the 'ought' self than is the case. However, one may not require any defense mechanisms when judging the discrepancy between the 'ideal' and real self as that 'ideal' self is no longer a matter of life and death! One would be aware that one is not focusing too much on hopes and aspirations and thus feel despondent/ sad/ melancholic - again classical symptoms of depression. Yet, despite the affect of sadness, all rumination would be focused on 'ought' self and thus the content be of guilt, duties, burden, responsibilities, etc.

I'm sure there is some grain of truth in my formulation, but wont be able to state emphatically unless the above proposed dissociation study involving default region and bipolar people is done. If one of you decide to do that, do let me know the results, even if they contradict the thesis.


Johnson, M. (2006). Dissociating medial frontal and posterior cingulate activity during self-reflection Social Cognitive and Affective Neuroscience, 1 (1), 56-64 DOI: 10.1093/scan/nsl004
Higgins, E. T. (1997). Beyond pleasure and pain American Psychologist (52), 1280-1300

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Children not mini-adults, at least in cognitive control

A predominant, but unstated, thinking that biases many research paradigms is the assumption that children are just mini-adults with less well developed mechanisms than adults, but fundamentally using and relying on the same unitary cognitive mechanisms as the adults use. this has proven time and again wrong, and better psychologists now agree that children view the world in a fundamentally different manner from adults. I have covered some research in the past that showed for example that while differentiating between two color hues (categorical color perception), children show a more right hemisphere domination (non-verbal); while adults rely on Left hemisphere (verbal knowledge). Over development the RH processes are shadowed by the maturing LH verbal process, as far as it relates to Categorical Perception.

This recent PNAS article , by none other than the famed Chris Catham of the Developing Intelligence fame, is an effort in the same direction, showing that children use a different mechanism than adults when it comes to using cognitive control. while Adults use a more proactive cognitive control, the children rely on a reactive cognitive control. The authors do a good job of describing the proactive and reactive cognitive control so over to them:

Although sometimes derided as ‘‘creatures of habit,’’ humans develop an unparalleled ability to adaptively control thought and behavior in accordance with current goals and plans. Dominant theories of cognitive control suggest that this flexibility is enabled by the proactive regulation of behavior through sustained inhibition of inappropriate thoughts and actions , the active biasing of task-relevant thoughts, or construction of rule-like representations. Theories of the developmental origins of cognitive control converge in positing that children engage these same proactive processes, but in a weaker form, with less strength or stability , less resistance toward habitual responses, or degraded complexity.
...
However, children can be notoriously constrained to the present, raising the possibility that the temporal dynamics of immature cognitive control are fundamentally different from that of adults. Specifically, we hypothesized that young children may show ‘‘reactive’’ as opposed to ‘‘proactive’’ context processing , characterized by a failure to proactively prepare for even the predictable future and a tendency to react to events only as they occur, retrieving information from memory as needed in the moment. For lack of age-appropriate methods, the possibility of this qualitative developmental shift has not been directly tested.

They also describe the paradigm used beautifully so again quoting from the article:

In the AX-CPT, subjects provide a target response to a particular probe (‘‘X’’) if it follows a specific contextual cue (‘‘A’’). Nontarget responses are provided to other cue–probe sequences (‘‘A’’ then ‘‘Y,’’ ‘‘B’’ then ‘‘X,’’ or ‘‘B’’ then ‘‘Y’’), each occurring with lower probability than the target pair. This asymmetry in trial type frequency is critical for revealing distinct behavioral profiles for proactive versus reactive control. Proactive control supports good BX trial performance at the expense of AY trials. Maintenance of the ‘‘B’’ cue supports a nontarget response to the subsequent ‘‘X’’ probe; however, maintenance of the ‘‘A’’ cue leads to anticipation of an X and thus a target response (due to the expectancy effect cultivated by the asymmetry in trial type frequencies), which can lead to false alarms in AY trials . Reactive control leads to the opposite pattern. The preceding cue is retrieved when needed, that is, in response to ‘‘X’’ probes but not to ‘‘Y’’ probes. Such retrieval renders BX trials vulnerable to retrieval-based interference; the lack of such retrieval on AY trials means that false alarms are less likely in this case. Similarly, proactive control should lead to increased delay-period effort, whereas reactive control should lead to increased effort to probes.

What they found was consistent with their hypothesis. The reaction time data, the effort data gauged from puppilometry, the speed-accuracy trade off data all pointed to the fact that children used a reactive cognitive control mechanism while adults used a proactive cognitive control mechanism. This what they conclude:

By dissociating proactive and reactive control mechanisms in children, our findings call into question a previously untested assumption of developmental theories of cognitive control, that is, relative to young adults, weaker but qualitatively similar control processes guide the task performance of children. Of course, children and even infants may be capable of sustaining context representations over shorter delays than the 1.2 s used here, but such limited proactive mechanisms would seem unlikely to strongly influence most behaviors.

Further research is needed to determine the processes that drive the developmental transition from reactive to proactive control. This qualitative shift could reflect genuinely qualitative changes, for example, in metacognitive strategies that allow children to engage proactive control. Alternatively (or additionally), the underlying mechanisms for this qualitative shift could be continuous. For example, the gradual strengthening of task-relevant representations could allow proactive control to become effective, thus supporting a shift in the temporal dynamics of control. In any case, the developmental progression to be addressed is a shift from reactive to proactive control rather than merely positing incremental improvements with development.

I think these are steps in the right direction; I lean towards a stage theory account of development so am supportive of a dramatic developmental stage whereby reactive cognitive control mechanisms are replaced by proactive ones, although both strategies may be available to the critical age children equally. However, it may be the case that the neural architecture for proactive CC develops late (just like linguistic CP) and overrides the default reactive CC circuit. that dominance of Proactive CC over reactive CC to me should mark an important developmental stage.

Thanks Chris, for your wonderful blog posts and this paper!



Chatham, C., Frank, M., & Munakata, Y. (2009). Pupillometric and behavioral markers of a developmental shift in the temporal dynamics of cognitive control Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0810002106

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Beyond pleasure and pain: promotion, prevention, desire and dread.

The hedonic principle says that we are motivated to approach pleasure and avoid pain. This, as per Higgins is too simplistic a formulation. He supplants this with his concepts of regulatory focus, regulatory anticipation and regulatory reference. That is too much of jargon for a single post, but let us see if we can make sense.

First, let us conceptualize a desired end-state that an organism wants to be in- say eating food and satisfying hunger. This desired end-state becomes the current goal of the organism and leads to gold-directed behavior. Now, it is proposed that given this desired end-state, the organism has two ways to go about achieving or moving towards the end-state. If the organism has promotion or achievement self-regulation focus, then it will be more sensitive to whether the positive outcome is achieved or not and will thus have an approach orientation whereby it would try to match his next state to the desired state or try approaching the desired end-sate as close as possible. On the other hand, if the organism has a prevention or safety self-regulation focus, then it will be more sensitive to the negative outcome as to whether it becomes worse off after the behavior and will have an avoidance orientation whereby it would try to minimize the mismatch between his next state and the desired state. Thus given n next states with different food availability , the person with promotion focus will choose a next state that is as close, say within a particular threshold, to the desired state of satiety ; while the person with the prevention focus will be driven by avoiding all the sates that have a sub-threshold food availability and are thus mis-matched with the end-goal of satiety. thus, the number and actual states which are available for choosing form are different for the two groups: the first set is derived from whether the states are within a particular range of the end-state; the second set is derived from excluding all the states that are not within a particular range of the end-state. Put this way it is easy to see, that these strategies of promotion or prevention focus, place different cognitive and computational demands: the former requires explortation/ maximizing, the other may be satisfied by satisficing. (see my earlier post on exploration/ exploitation and satisficers / maximisers where I believe I was slightly mistaken).

Now, that I have explained in simple terms (hopefully) the concepts of self-regulatory focus, let me quote from the article and show how Higgins arrives at the same.

The theory of self-regulatory focus begins by assuming that the hedonic principle should operate differently when serving fundamentally different needs, such as the distinct survival needs of nurturance (e.g., nourishment) and security (e.g., protection). Human survival requires adaptation to the surrounding environment, especially the social environment (see Buss, 1996). To obtain the nurturance and security that children need to survive, children must establish and maintain relationships with caretakers who provide them with nurturance and security by supporting, encouraging, protecting, and defending them (see Bowlby, 1969, 1973). To make these relationships work, children must learn how their appearance and behaviors influence caretakers' responses to them (see Bowlby, 1969; Cooley, 1902/1964; Mead, 1934; Sullivan, 1953). As the hedonic principle suggests,children must learn how to behave in order to approach pleasure and avoid pain. But what is learned about regulating pleasure and pain can be different for nurturance and security needs. Regulatory-focus theory proposes that nurturance-related regulation and security-related regulation differ in regulatory focus. Nurturance-related regulation involves a promotion focus, whereas security related regulation involves a prevention focus.
.....
People are motivated to approach desired end-states, which could be either promotion-focus aspirations and accomplishments or prevention-focus responsibilities and safety. But within this general approach toward desired end-states, regulatory focus can induce either approach or avoidance strategic inclinations. Because a promotion focus involves a sensitivity to positive outcomes (their presence and absence), an inclination to approach matches to desired end-states is the natural strategy for promotion self-regulation. In contrast, because a prevention focus involves a sensitivity to negative outcomes (their absence and presence), an inclination to avoid mismatches to desired end-states is the natural strategy for prevention self-regulation (see Higgins, Roney, Crowe, & Hymes, 1994).

Figure 1 (not shown here, go read the article for the figure) summarizes the different sets of psychological variables discussed thus far that have distinct relations to promotion focus and prevention focus (as well as some variables to be discussed later). On the input side (the left side of Figure 1), nurturance needs, strong ideals, and situations involving gain-nongain induce a promotion focus, whereas security needs, strong oughts, and situations involving nonloss-loss induce a prevention focus. On the output side (the right side of Figure 1), a promotion focus yields sensitivity to the presence or absence of positive outcomes and approach as strategic means, whereas a prevention focus yields sensitivity to the absence or presence of negative outcomes and avoidance
as strategic means.

Higgins then goes on describing many experiments that support this differential regulations focus and how that is different from pleasure-pain valence based approaches. He also discusses the regulatory focus in terms of signal detection theory and here it is important to note that promotion focus leads to leaning towards (being biased towards) increasing Hits and reducing Misses ; while prevention focus means leaning more towards increasing correct rejections and reducing or minimizing false alarms. Thus,a promotion focus individual is driven by finding correct answers and minimizing errors of omission; while a preventive focused person is driven by avoiding incorrect answers and minimizing errors of commission. In Higgin's words:

Individuals in a promotion focus, who are strategically inclined to approach matches to desired end-states, should be eager to attain advancement and gains. In contrast, individuals in a prevention focus, who are strategically inclined to avoid mismatches to desired end-states, should be vigilant to insure safety and nonlosses. One would expect this difference in self-regulatory state to be related to differences in strategic tendencies. In signal detection terms (e.g., Tanner & Swets, 1954; see also Trope & Liberman, 1996), individuals in a state of eagerness from a promotion focus should want, especially, to accomplish hits and to avoid errors of omission or misses (i.e., a loss of accomplishment). In contrast, individuals in a state of vigilance from a prevention focus should want, especially, to attain correct rejections and to avoid errors of commission or false alarms (i.e., making a mistake). Therefore, the strategic tendencies in a promotion focus should be to insure hits and insure against errors of omission, whereas in a prevention focus, they should be to insure correct rejections and insure against errors of commission .

He next discusses Expectancy x Value effects in utility research. Basically , whenever one tries to decide between two or more alternative actions/ outcomes, one tries to find the utility of a particular decision/ behavioral act based on both the value and expectance of the outcome. Value means how desirable or undesirable (i.e what value is attached) that outcome is to that person. Expectancy means how probable it is that the contemplated action (that one is deciding to do) would lead to the outcome. By way of an example: If I am hungry, I want to eat food. Lets say there are two actions or decisions that have different utility that can lead to my hunger reduction. The first involves begging for food from the shopkeeper; the second involves stealing the food from the shopkeeper. The first may be having positive value (begging might not be that embarrassing) , but low expectancy (the shopkeeper is miserly and unsympathetic) ; while the second act may have negative value (I believe that stealing is wrong and would like to avoid that act) but high expectancy (I am sure I'll be able to steal the food and fulfill my hunger). the utility I impart to the two acts may determine what act I eventually decide to indulge in.

Higgins touches on research that showed that Expectancy X value have a multiplicative effect i.e as expectancy increases, and value increases the motivation to take that decision/ course of action increases non-linearly. He clarifies that this interaction effect is seen in promotion focus , but not in preventive focus:

Expectancy-value models of motivation assume not only that expectancy and value have an impact on goal commitment as independent variables but also that they combine multiplicatively (Lewin, Dembo, Festinger, & Sears, 1944; Tolman, 1955; Vroom, 1964; for a review, see Feather, 1982). The multiplicative assumption is that as either expectancy or value increases, the impact of the other variable on commitment increases. For example, it is assumed that the effect on goal commitment of higher likelihood of goal attainment is greater for goals of higher value. This assumption reflects the notion that the goal commitment involves a motivation to maximize the product of value and expectancy, as is evident in a positive interactive effect of value and expectancy. This maximization prediction is compatible with the hedonic or pleasure principle because it suggests that people are motivated to attain as much pleasure as possible.
Despite the almost universal belief in the positive interactive effect of value and expectancy, not all studies have found this effect empirically (see Shah & Higgins, 1997b). Shah and Higgins proposed that differences in the regulatory focus of decision makers might underlie the inconsistent findings in the literature. They suggested that making a decision with a promotion focus is more likely to involve the motivation to maximize the product of value and expectancy. A promotion focus on goals as accomplishments should induce an approach-matches strategic inclination to pursue highly valued goals with the highest expected utility, which maximizes Value × Expectancy. Thus, the positive interactive effect of value and expectancy assumed by classic expectancy-value models should increase as promotion focus increases.
But what about a prevention focus? A prevention focus on goals as security or safety should induce an avoid-mismatches strategic inclination to avoid all unnecessary risks by striving to meet only responsibilities that are clearly necessary. This strategic inclination creates a different interactive relation between value and expectancy. As the value of a prevention goal increases, the goal becomes a necessity, like the moral duties of the Ten Commandments or the safety of one's child. When a goal becomes a necessity, one must do whatever one can to attain it, regardless of the ease or likelihood of goal attainment. That is, expectancy information becomes less relevant as a prevention goal becomes more like a necessity. With prevention goals, motivation would still generally increase when the likelihood of goal attainment is higher, but this increase would be smaller for high-value goals (i.e., necessities) than low-value goals. Thus, the second prediction was that the positive interactive effect of value and expectancy assumed by classic expectancy value models would not be found as prevention focus increased. Specifically, as prevention focus increases, the interactive effect of value and expectancy should be negative.

And that is exactly what they found! the paper touches on many other corroborating readers and the interested reader can go to the source for more. Here I will now focus on his concepts of regulatory expectancy and regulatory reference.

Regulatory Reference is the tendency to be either driven by positive and desired end-states as a reference end-point and a goal; or to be driven by negative and undesired end-states as goals that are most prominent. For example, eating food is a desirable end-state; while being eaten by others is a undesired end-sate. now an organism may be driven by the end-sate of 'getting food' and thus would be regulating approach behavior of how to go about getting food. It is important to contrast this with regulatory focus; while searching for food, it may have promotion orientation focusing on matching the end state; or may have prevention focus i.e avoiding states that don't contain food; but it is still driven by a 'positive' or desired end-state. On the other hand, when the regulatory reference is a negative or undesirable end-state like 'becoming food', then avoidance behavior is regulated i.e. behavior is driven by avoiding the end-state. Thus, any state that keeps one away from 'being eaten' is the one that is desired; this may involve promotion focus as in approaching states that are opposite of the undesired state and provide safety from predator; or it may have a prevention focus as in avoiding states that can lead one closer to the undesired end-state. In words of Higgins:

Inspired by these latter models in particular, Carver and Scheier (1981, 1990) drew an especially clear distinction between self-regulatory systems that have positive versus negative reference values. A self-regulatory system with a positive reference value has a desired end state as the reference point. The system is discrepancy reducing and involves attempts to move one's (represented) current self-state as close as possible to the desired end-state. In contrast, a self-regulatory system with a negative reference value has an undesired end-state as the reference point. This system is discrepancy-amplifying and involves attempts to move the current self-state as far away as possible from the undesired end-state.

To me Regulatory Reference is similar to Value associated with a utility decision and determines whether when we are choosing between different actions/ goals , the end-states or goals have a positive connotation or a negative connotation.

That brings us to Regulatory anticipation: that is the now well-known Desire/ dread functionality of dopamine mediated brain regions that are involved in anticipation of pleasure and pain and drive behavior. This anticipation of pleasure or pain is driven by our Expectancies of how our actions will yield the desired/undesired outcomes and can be treated as the equivalent to Expectancy in the Utility decisions. The combination of independent factors of regulatory reference and regulatory anticipation will drive what end-state or goal is activated to be the next target for the organism. Once activated, its tendencies towards promotion focus or prevention focus would determine how it strategically uses approach/ avoidance mechanisms to archive that goal or move towards the end-state. Let us also look at regulatory anticipation as described by higgins:

Freud (1920/1950) described motivation as a "hedonism of the future." In Beyond the Pleasure Principle (Freud, 1920/1950), he postulated that people go beyond total control of the "id" that wants to maximize pleasure with immediate gratification to regulating as well in terms of the "ego" or reality principle that avoids punishments from norm violations. For Freud, then, behavior and other psychical activities were driven by anticipations of pleasure to be approached (wishes) and anticipations of pain to be avoided (fears). Lewin (1935) described how the "prospect" of reward or punishment is involved in children learning to produce or suppress, respectively, certain specific behaviors (see also Rotter, 1954). In the area of animal learning, Mowrer (1960) proposed that the fundamental principle underlying motivated learning was regulatory anticipation, specifically, approaching hoped-for desired end-states and avoiding feared undesired endstates. Atkinson's (1964) personality model of achievement motivation also proposed a basic distinction between self-regulation in relation to "hope of success" versus "fear of failure." Wicker, Wiehe, Hagen, and Brown (1994) extended this notion by suggesting that approaching a goal because one anticipates positive affect from attaining it should be distinguished from approaching a goal because one anticipates negative affect from not attaining it. In cognitive psychology, Kahneman and Tversky's (1979) "prospect theory" distinguishes between mentally considering the possibility of experiencing pleasure (gains) versus the possibility of experiencing pain (losses).

Why I have been dwelling on this and how this fits into the larger framework: Wait for the next post, but the hint is that I believe that bipolar mania as well as depression is driven by too much goal-oriented activity- in mania the focus being promotion; while in depression the focus being preventive; Higgins does discuss mania and depression in his article, but my views differ and would require a new and separate blog post. Stay tuned!


Higgins, E. T. (1997). Beyond pleasure and pain American Psychologist (52), 1280-1300

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The first 30 seconds: Trustworthiness, Dominance and their neural correlates

A lot has already been written in the blogosphre regarding this study that found the brain regions that are involved in first impression formation. I view the study from a slightly different angle , but first let me introduce the study and its main findings.

The study was focused on finding the brain regions that are involved in the impression formation of a new social entity. We all know that we form automatic and consistent first impressions of strangers we meet based on things like their face to the social information that is available about them. The authors theorized that to know which regions of the brain are involved in evaluating a person for the first time, it would be sufficient to know which regions of the brain were engaged more while the evaluation-consistent information was being processed. To understand this logic, consider the brain regions involved in memory and how they are discovered. Typically, a series of words/images to be remembered are presented to the subjects, while simultaneously their brain are imaged. Later a memory recall/recognition test is administered. It is found that some brain regions are consistently more active during encoding of the original stimuli which are later recalled/ recognized correctly. This effect is know as Difference in Memory effect (DM effect). the fact that these areas are differentially engaged during encoding of remembered stimuli as opposed to forgotten stimuli is taken as evidence for the fact that these brain regions are involved in encoding of memory. Similar to this effect, it is found that evaluations that are consistent with the later overall evaluation of the person engage some brain regions more than when the evaluation is inconsistent with the later overall evaluation. This difference in evaluation effect (DE ) can be used to locate the regions that are involved in social evaluation or formation of first impressions.

Previous studies had indicated that dmPFC was engaged in social evaluation; however many cognitive factors other than purely evaluative factors might be in action here.

It has also been indicated that amygdala is involved in both social evaluation and valence based evaluations and might be involved in these first impression formation. So the authors hypothesized that they would find differential activity in amygdala in consistent as opposed to inconsistent evaluations and this is what they actually observed. They also found that PCC was also differentially engaged while forming first impressions and thus was another brain region involved in evaluating others.

Here is the study design:

To test these hypotheses, we developed the difference in evaluation procedure (see Figure), allowing us to sort social information encoding trials by subsequent evaluations. More specifically, we measured blood oxygenation level–dependent (BOLD) signals using whole brain fMRI during exposure to different person profiles. Each profile consisted of 6 person-descriptive sentences implying different personality traits. The sentences varied gradually in their positive to negative valence (or vice versa) but evoked equivalent levels of arousal. A 12-s interval with the face alone separated the positive and the negative segments. Subsequently, an evaluation slide instructed subjects to form their impression on an 8-point scale. On the basis of these evaluations, we determined which of the presented descriptive sentences guided evaluations (evaluation relevant) and which did not (evaluation irrelevant). For example, if a subject's evaluation was positive, we assigned the positive segment of the profile to the evaluation-relevant category and the negative segment to the evaluation-irrelevant category. We then identified the brain regions dissociating items from each category (that is, difference in evaluation effect). Notably, we correlated subjects' BOLD signal with their own individual evaluations. This allowed us to identify brain regions that were consistent across subjects in processing evaluation-relevant information regardless of the particular stimuli that they considered. Immediately after the scanning session, subjects underwent a memory-recognition task.

The results were clear and found that while dmPFC was involved in social evaluations it was not differentially engaged: thus it had a general role to play, perhaps holding the representation of evaluation after it had already been formed; in contrast both amygdala and PCC were differentially recruited and thus underlie the first time evaluations. In the words of the authors:

Understanding the neural substrates of social cognition has been one of the core motivations driving the burgeoning field of social neuroscience. A number of studies have highlighted the dmPFC in the processing of social information. Our results provide further evidence that the dmPFC is recruited to process person-descriptive information during impression formation. However, BOLD responses in this region do not dissociate evaluation-relevant from evaluation-irrelevant information, suggesting that the dmPFC is not essential for the evaluative component of impression formation. In fact, social evaluation recruits brain regions that are not socially specialized but are more generally involved in valuation and emotional processes.

Valuation and emotional processes, as a substantial amount of research has shown, are characteristic of the amygdala. In particular, the amygdala is considered to be a crucial region in learning about motivationally important stimuli. It is also implicated in social inferences that are based on facial and bodily expressions, in inferences of trustworthiness and in the capacity to infer social attributes. Moreover, the involvement of amygdala in social inferences might be independent of awareness or explicit memory. For example, increased amygdala responses were correlated with implicit, but not explicit, measures of the race bias, as well as with presentation of faces previously presented in an emotional, but not neutral, context, regardless of whether subjects could explicitly retrieve this information. Here we provide evidence linking the two domains of affective learning and social processing by showing that the amygdala is engaged in the formation of subjective value assigned to another person in a social encounter.

Although the amygdala is typically implicated in the processing of negative affect and negative stimuli have been shown to modulate it more than positive stimuli, we found that the amygdala processed both positive and negative evaluation-relevant information, suggesting that amygdala activity is driven by factors other than mere valence, such as the motivational importance or salience of the stimuli. This result is consistent with recent findings showing enhanced amygdala responses for both positive and negative stimuli as a function of motivational importance.

Evidence related to the PCC has been more diverse. There have been reports in the social domain, such as involvement in theory of mind and self-referential outward-focused thought33, in memory related processes such as autobiographical memory of family and friends34, and in emotional modulation of memory and attention. More recently, the PCC has been linked with economic decision making, the assignment of subjective value to rewards under risk and uncertainty, and credit assignment in a social exchange. A common denominator of these studies might be that all involved either a social or an outward-directed valuation component. Our task also encompasses these features, extending the role of the PCC to value assignment to social information guiding our first impressions of others.

The amygdala and the PCC are both interconnected with the thalamus as part of a larger circuitry that is implicated in emotion, arousal and learning. Beyond the known role of the amygdala and the PCC in social-information processing and value representation, our results suggest a neural mechanism underlying the online formation of first impressions. When encoding everyday social information during a social encounter, these regions sort information on the basis of its personal and subjective importance and summarize it into an ultimate score, a first impression. Other regions, such as the ventromedial PFC, the striatum and the insula, have also been implicated in valuation processes. However, these regions did not emerge in our difference in evaluation effect analysis. This might suggest a possible dissociation in the valuation network between regions engaged in the formation of value and its subsequent representation and updating. The latter regions would not be engaged during encoding and therefore would not show a difference in evaluation effect but would instead have an effect once the evaluation is formed. The amygdala and the PCC probably participate in both value formation and its representation. The difference in evaluation procedure may provide a useful tool for disentangling the different components of the valuation system and their specific contributions to social versus nonsocial evaluations.

Now I would like to link all this new research with an earlier research on face attributes that found that there were two orthogonal factors that characterize a face- trustworthiness (valence) and dominance. It is important to note that faces are an important mechanism by which we make snap judgments and if it has been found that there are two orthogonal dimensions (found using factor analysis) on which we judge faces and form rifts impressions, there is no reason to suppose that those same two orthogonal factors would not come into play when we form first impressions based on social information and not the face. What I am trying to say is that the non-face social information driven social evaluation would still be structured around the factors of whether the social information pointed to the person as Trustworthy or as Dominant. I would expect that there would be different brain regions specialized for these two functions: We all know too clearly that amygdala is specialized for trustworthiness judgments and that fits in with one of the areas that has been identified for snap judgments. thta leaves us with the PCC, which has normally been implicated in self-referential thinking with an outward and evaluative (as opposed to inward and executive) focus and also a preventive focus. It seems likely that this region would be used to evaluate a social other and judge as to whether he has the ability to execute, harm and dominate oneself. So, what I would like to see is a study that dissociates the scoial information provided to subjects in terms of trustworthiness and dominance factors and sees if there is a dissociation in the evaluative regions of amygdala and PCC; or maybe one can juts factor analyze the results of the original study and see if the same two factors emerge! I am excited,and would love to see these studies being preformed!!

Schiller, D., Freeman, J., Mitchell, J., Uleman, J., & Phelps, E. (2009). A neural mechanism of first impressions Nature Neuroscience DOI: 10.1038/nn.2278
Oosterhof, N., & Todorov, A. (2008). The functional basis of face evaluation Proceedings of the National Academy of Sciences, 105 (32), 11087-11092 DOI: 10.1073/pnas.0805664105

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