Category Archives: cognitive map

Multiple Cognitive Maps: how they are kept distinct

Readers of this blog will remember a study that had shown that there were three dissociable systems in the human hippocampal regions as relevant to declarative memory. These were the anterior hippocampus (dentate gyrus) for detecting novelty; the Posterior hippocampus (CA3 )for recollecting (or using contextual cues for recall) and the posterior hippocamal gyrus for familiarity detection. Extending these to spatial memory , one can conjecture that dentate gyrus would be involved in detecting a novel cognitive map or spatial arrangement from the older stored cognitive maps; the CA3 region will actually store these cognitive maps that provide the context using which the mice (or men ) can orient oneself; while the posterior hippocampal gyrus might be involved in detecting familiarity or whether the spatial place has been visited earlier and is familiar.

Research has indicated that indeed the CA3 region contains ‘ place cells ‘ or cells that fire when a mice is near a spatial location. Multiple such cognitive maps of the environment that the mice encounters can be stored in the hippocampus.

However, as Madam Fathom has excellently elaborated, there persisted a mystery as to how widely similar, but subtly distinct cognitive maps , were distinguished within the hippocampus. As per the above model, dentate gyrus should have a prominent role to play here detecting if a new spatial location is a novel spatial location, despite it being similar in many ways to an earlier encountered spatial location.

This is exactly what has been experimentally observed. When mice which had NMDA receptors knocked off in the dentate gyrus were put in a novel environment or context, they were unable to distinguish it from the previously learned context. Thus, these mice though capable of learning could not distinguish between contexts, as presumably their ability to detect a novel context were hampered.

To me this bodes as further evidence for the cognitive map theory and I would stick my neck and say that the mechanisms and circuits involved in spatial navigation, episodic and declarative memory are same and serve a similar function. Thus, the dentate gyrus not only detects novel words in a word list (declarative memory) , but also detects novel spatial locations (cognitive maps) and novel autobiographical events (episodic memory). Similarly the CA3 region of hippocampus codes for distinct spatial maps and distinct words an facts and also distinct autobiographical memories. Similarly posterior hippocampul gyrus may detect familiarity for both facts, episodic memories (and trouble with this may lead to Deja Vu like feelings) and spatial locations.

These multiplexed use of the same brain regions, for different types of memories, may also explain why mnemonic methods like the method of loci work excellently- as the brain regions for declarative memory are the same as for discerning one’s spatial location in an environment- hence it might be computationally easy to remember lists if a associated with spatial locations or a prominent cognitive map.

Depression, Neurogenesis and Spatial navigation

We all know that hippocampus is the seat of both memory as well as spatial abilities (cognitive map theory). We also know that most of the neurogeneisis in adult humans happens in hippocmapus. We also know that depression is caused by stress and both stress and depression lead to or are correlated with reduced neurogeneisis in the hippocmapus (my learning helplessness theory of depression) .

Now a new study has found that depressed people have impaired spatial navigation abilities. Putting 2 and 2 together it is highly plausible that this relationship between depression and impaired spatial navigation is mediated by the reduced neurogeneies or atrophy in hippocampus.

Relatedly, a good article (pdf) regarding how new anti-depressants are targeting neurogenesis in hippocampus as a mechanism to alleviate depression.

Three cheers to the cognitive map theory- the focus with which this blog started!!

Hat Tip: BPS Research Digest

The courage of a mouse to say ‘No’: A case of metacognition or risk-aversion?

A recent article in Current Biology by Foote et al (courtsey Ars Technica) posits that rats have metacognition abilities. till now only Humans and primates were assumed to have metacognitive abilities. One feature or defining characteristic of metacognition is knowing what you know and also knowing what you don’t know. It means one can think about one’s own mental states and determine what knowledge one already has and what knowledge one has not yet learned. So a related ability would be the ability to decline a test of knowledge if one thinks that one has not learned enough to ace the test. For those who gave GRE/ any other exam recently and maybe postponed that exam, they would have no difficulty appreciating this that postponing/declining a test involves metacognition.

Taking this line of reasoning further, Foote et al surmise that if a rat could decline a test, under conditions when the rat was not sure of its learned knowledge regarding the test and doubted its ability to successfully complete the test, then such a declining behavior would indicate that the rat has metacognitive abilities. I find no flaws in this reasoning, but have a few quips about their particular experimental setup, which may have confounded the results by not factoring in the risk aversion.

First regarding their hypothesis of the experiment:

Here, we demonstrate for the first time that rats are capable of metacognition—i.e., they know when they do not know the answer in a duration-discrimination test. Before taking the duration test, rats were given the opportunity to decline the test. On other trials, they were not given the option to decline the test. Accurate performance on the duration test yielded a large reward, whereas inaccurate performance resulted in no reward. Declining a test yielded a small but guaranteed reward. If rats possess knowledge regarding whether they know the answer to the test, they would be expected to decline most frequently on difficult tests and show lowest accuracy on difficult tests that cannot be declined [4]. Our data provide evidence for both predictions and suggest that a nonprimate has knowledge of its own cognitive state.

Now on to the actual experimental setup:

Each trial consisted of three phases: study, choice, and test phases (Figure 1). In the study phase, a brief noise was presented for the subject to classify as short (2–3.62 s) or long (4.42–8 s). Stimuli with intermediate durations (e.g., 3.62 and 4.42 s) are most difficult to classify as short or long [11, 12]. By contrast, more widely spaced intervals (e.g., 2 and 8 s) are easiest to classify. In the choice phase, the rat was sometimes presented with two response options, signaled by the illumination of two nose-poke apertures. On these choice-test trials, a response in one of these apertures (referred to as a take-the-test response) led to the insertion of two response levers in the subsequent test phase; one lever was designated as the correct response after a short noise, and the other lever was designated as the correct response after a long noise. The other aperture (referred to as the decline-the-test response) led to the omission of the duration test. On other trials in the choice phase, the rat was presented with only one response option; on these forced-test trials, the rat was required to select the aperture that led to the duration test (i.e., the option to decline the test was not available), and this was followed by the duration test. In the test phase, a correct lever press with respect to the duration discrimination produced a large reward of six pellets; an incorrect lever press produced no reward. A decline response (provided that this option was, indeed, available) led to a guaranteed but smaller reward of three pellets.

The test they have used is a stimulus discrimination test. Their results indicated that indeed the rats declined more often on difficult trials (trials in which the stimulus were closely spaced around the men of 4s) as compared to easy trial (in which they had to discriminate widely spaced stimulus (say 2s and 8s). This neatly demonstrates that the rats were internally calculating what their odds of passing the test were, and in case of the difficult test they took the better option of choosing the decline-the-test condition. However I would like to see more of their data and factor out the effcets of risk aversion.

We all know that humans are prone to risk aversion. That is if I present to you an option of choosing a sure amount of 100 rs or a 50% chance of winning 200rs , you would normally choose the fist option, though if one compares the utility function it is the same. In first case you have and expected value of 100 and in the second case too you have an expected value of 100 (0.5*0 +0.5*200). Thus it doesnt make much sense why one would use one over the other. This becomes more interseting when we increase the amount of the risky option. suppose we now have 100 rs assured vis-avis a 50 % chance of 300 rs still , most of us end up choosing the assured sum.

In this setup the utility of declining the test is 3 pellets; while if we assume that the rats have not learned how to discriminate the stimuli; then assuming that they press the levers at random and thus each option of the test condition is equally probable we have the utility as 0.5 *0 +0.5 *6 = 3 pellets. so we have the same situations as with humans. Now taking risk aversion into account, one would find that the rats would decline the test more often in the difficult stimulus conditions as that is a safe and assured option as compared to the take-the-test condition. As a matter of fact I am surprised that there were some rats who did choose the take-the-test condition. I guess men are more meek than mice!!

So the best thing to do would be to take risk-aversion into account and then after factoring it out decide on whether the rats knew (in a conscious sense) that the test is difficult. Risk aversion is mostly sub-conscious and would not involve metacognition. However, the trend of rising declining behaviors with test difficulty does point to the fact that the rats did have some metacognition.

I would love to have this study replicated using a maze (mouse trap sort of) task. In a amze the cognitive map of the maze provides a good indicataor of how much the mice know about the test/ test difficulty and measuring the declining in this case may be directly related to their meta-cognitive abilities.

Encephalon #10: A treat for your mind!

The latest edition of encephalon, the brain carnival, has just been published by Bora at A Blog Around The Clock.

It is a truly outstanding issue highlighting some of the best cognitive posts on the web.

My favorite picks are Gene Expression’s excellent summary of the current view of Hippocampal formation as a memory consolidator and also as representing spatio-temporal information in the form of Cognitive Maps.

The readers of this blog will remember that this blog started with a cognitive map focus and it is heartening to see how the place and grid cell systems discovered in Hippcoampus may contribute to the different dissociated memory areas hypothesized in the hippocampus regarding novelty and similarity (recollection) memory retrieval. Incidentally, the novelty related area, found using fMRI, was the rhinal cortices and the grid cells are also found there! I would write a detailed mail linking everything up, but for now you may want to savor the other great articles in the Encephalon- another favorite being the exploration of peripersonal space in neglect patients by Michael.

Causal learning: how different is it from normal learning?

I was browsing a write-up on Causal reasoning by Mixing Memory, and came across this article by Lagnado et al, regarding the Causal Structure underlying causal reasoning.

In brief , Causal reasoning refers to that ability of the humans by which they can classify some events as causes and some events as effects and also determine either deterministically or probabilistically as to which effects are caused by which causes. In simple words, the ability to assign causes to effects.

Historically, Causal reasoning has focused on the statistical methods of covariance or correlation between two events and used the strength of the correlation to calculate and predict the causal relation between the two events. This suffers from several drawbacks like inability to determine the direction of causation or the inability to rule out a third common cause of which the two observed events are the effects.

Langrado et al, in their paper, present a refreshing new perspective on causal reasoning by differentiating between the qualitative Causal Structure between two or more events and the quantitative Causal Strength of that relationship. For example, a causal structure may causally relate the presence of fever with bacterial infection thus identifying bacterial infection as a cause of fever; but the causal strength between bacterial infection and fever would determine what probability we assign to a particular case of fever to have been caused due to bacterial infection (diagnostic learning) or the probability that given bacterial infection a person would develop fever (predictive learning).

The authors contend that the issues involved in causal strength learning and causal structure learning are different and should be addressed differently. Further, they contend that most of the historical research has been limited to causal strength learning, ignoring the prior and more fundamental stage of causal structure learning; as in their theory, the causal strength of any relation can only be learned once one has some a priori qualitative assumptions about the underlying causal relationships. Their paper thus focuses what cues/mechanisms are involved in the formation of the causal structure.

Causal-model theory was a relatively early, qualitative attempt to capture the distinction between structure and strength. According to this proposal causal induction is guided by top-down assumptions about the structure of causal models. These hypothetical causal models guide the processing of the learning input. The basic idea behind this approach is that we rarely encounter a causal learning situation in which we do not have some intuitions about basic causal features, such as whether an event is a potential cause or effect. If, for example, the task is to press a button and observe a light, we may not know whether these events are causally related or not, but we assume that the button is a potential cause and the light is a potential effect. Once a hypothetical causal model is in place, we can start estimating causal strength by observing covariation information. The way covariation estimates are computed and interpreted is dependent on the assumed causal model.

They list the cues that humans use to form their Causal structures as

  • Statistical relations
  • Temporal order
  • Intervention
  • Prior knowledge

Before discussing, in depth, each of these cues and how they may affect causal reasoning, it is instructive to note that the concept of a Causal Structure underlying a given set of phenomena is quite close to the idea of a Cognitive Map underlying a given environment (say the maze or the mouse trap). While the latter is a spatial mental map of the objects in the surrounding 3-D space, the former may be conceived as a causal mental map of events in the temporal dimension. The reason I am using this analogy is to contrast the cues used in formulating a Causal structure with the different learning mechanisms used by mice to form a cognitive map of the mouse trap. The contention is that the same cognitive mechanisms are involved and also that these mechanisms are structured and unfold in a developmentally guided and staged manner.

The first cue to form a Causal structure or link two or more events is that of statistical relations. Here, correlation information between the events, as well as their conditional independences are used to arrive at a set of Markov equivalent causal models. Much of the learning is associative, probabilistic and maybe latent. It may not be accessible to consciousness and the learning of causal structure is more implicit, than explicit. For example, the regularities in the data may give rise to a fuzzy causal structure, where tentative causal relations are posited. Suppose from the data, it is determined that A and B are perfectly correlated. The person will have a strong sense of causation between A and B, but would be unable to determine the direction of causation. similarly if 3 events A,B and C are correlated, we would not be able to determine the directions of causation. This mechanism is very much similar to the latent learning mechanism exhibited by the mice in the mouse trap.

The second cue to form a causal structure that we consider here is that of Intervention. Here, human intervention takes place by affecting one of the events (potential cause) and by basis of that intervention or exercised choice, experiment to find out what effect that variable has on the outcome (effect). To more rigorously define Interventions, let me quote from the paper.

Informally, an intervention involves imposing a change on a variable in a causal system from outside the system. A strong intervention is one that sets the variable in question to a particular value, and thus overrides the effects of any other causes of that variable. It does this without directly changing anything else in the system, although of course other variables in the system can change indirectly as a result of changes to the intervened-on variable. What is important for the purposes of causal learning is that an intervention can act as a quasi-experiment, one that eliminates (or reduces) confounds and helps establish the existence of a causal relation between the intervened-on variable and its effects.

Suppose A and B have been found to be correlated. Further suppose that the happening of event A and B is under the control of the human subject. Then one can intervene to cause A and observe whether B occurred. If so the direction of causation is from A -> B. On the other hand if by intervening the human subject caused B to happen and did not observe A, then one could conclude that B does not cause A. To make the example concrete, consider event A as ‘Fire’ and event B as ‘Smoke’. We find that Fire and Smoke are correlated. By intervening and conducting experiments whereby we can control the occurrence of ‘fire’ or ‘smoke’ we can come up with correct causal relation that ‘fire’ -> ‘smoke’

Consider again, a 3 event situation whereby the relation between two causal events (A and B) and an outcome (C) has to be ascertained. Specifically, by intervening and causing A sometimes and B other times, and observing the happening of C we could ascertain the causal structure as to whether A->c or B-> C. The situation is not too different than the vicarious trail and error learning exhibited by a mouse when at a choice point. There, the mice has to, by trail-and error choosing of either right/left black /white turnings, learn which stimulus is associated with food (outcome). Thus, intervention mechanism is nothing but the refined vicarious trial-and-error learning.

The third, and perhaps the most important, mechanism that is used to form the Causal structure is Temporal ordering. This is a very simple mechanism whereby events that are occurring prior to some other event can be the cause of that event, but not vice versa.

The temporal order in which events occur provides a fundamental cue to causal structure. Causes occur before (or possibly simultaneously with) their effects, so if one knows that event A occurs after event B, one can be sure that A is not a cause of B. However, while the temporal order of events can be used to rule out potential causes, it does not provide a sufficient cue to rule them in. Just because events of type B reliably follow events of type A, it does not follow that A causes B. Their regular succession may be explained by a common cause C (e.g., heavy drinking first causes euphoria and only later causes sickness). Thus the temporal order of events is an imperfect cue to causal structure.

This mechanism is the same as the one used by mice in searching for stimulus. When two events follow each other than an active search mechanism is used to identify the salient stimulus which may have been the cause of the event. The concept of temporal ordering implying causation is inherent in this learning mechanism as are concepts of spatial and temporal contiguity and proximity. This is the normal avoidance learning mechanism in mice and in human causal structure learning may be more engaged in and relevant to identifying the causes of events that are undesirable.

The fourth cue used for identifying causal structure, that the authors do not touch on, but do hint in terms of highlighting the importance of causal mechanisms; but that I propose nonetheless, is that of causal chains construction and elaboration. This basically involves breaking the simple A-> B with intermediate and competing C, D, E etc and intervening and conducting experiments to come up with the correct causal chain. Thus, A->B may be refined as A->C->D->B or A-> E->B and experimentation done to narrow down on a particular causal chain.

This is similar to the hypothesis learning involved in mice and depends on a cognitive capacity to sequence events . Also this is normally exhibited in approach behavior and this elaboration of causal chain may be more relevant to the desirable outcomes that human subjects want to happen and all the small intermediate steps of they need to cause to make the final outcome happen.

The fifth, and for now final, cue that is used in the formation of causal structure is prior knowledge. The authors define it as follows:

Regardless of when we observe fever in a patient, our world knowledge tells us that fever is not a cause but rather an effect of an underlying disease. Prior knowledge may be very specific when we have already learned about a causal relation, but prior knowledge can also be abstract and hypothetical. We know that switches can turn on devices even when we do not know about the specific function of a switch in a novel device. Similarly we know that diseases can cause a wide range of symptoms prior to finding out which symptom is caused by which disease. In contrast, rarely do we consider symptoms as possible causes of a disease.

My take on prior knowledge is something close to that, but slightly different. The subject forms a general idea of which events are causes and which effects and also the general relationship between a primary cause and a desired/undesired later final outcome. Though, the intervening small steps of the causal chain may not be present, and thus no formal corroborating data based proof may be there, yet one can deduce the causal relationship between the primal cause and the later final outcome, ignoring the intermediate minor events down the line. A case in point would be food aversion learning, whereby one single vomit following consumption of say a spoiled food that was taken hours ago, may result in a strong automatic association and learning of that food as the cause of vomit and lead to avoidance of (or escape from) that food.

To me this mechanism is the same as that exhibited by the mice when they learn the spatial orientation in the mouse trap and are able to exhibit novel escape learning.

This summarizes the analogy between the causal learning and normal learning as of now. Will touch on the qualitatively different next 3 (causal) learning mechanisms later.

Unification of psychology in either direction

There is an interesting endeavor going on at PsyBlog to document the unity of psychology journey and current issues.

I got hooked to the same as I am also currently reading Consillience by E. O. Wilson and thus on the lookout for unified theories. Thanks to Mind Hacks via which I discovered this thread.

As per the Tree of Knowledge of Henriques, Psychology (on the mind plane) sits between Biology (on the life plane) and social Sciences (on the culture plane). He bridges the efforts of Skinner (towards the biological end of the spectrum) with Freud (towards the sociological end) as under the umbrella of psychological domain.

What interests me, is my own obsession at the two ends of the spectrum. While the Cognitive Map and research of Tolman seems to me a marking phase in psychology where behaviorism led way to the more cognitive approaches belonging to psychology proper; I am also intrigued by Conceptual Metaphors and linguistics which sits at the intersection of psychological phenomenon like thoughts and cultural phenomenon like language and its effects (the sapir-whorf hypothesis).

Hopefully my idiosyncratic tastes in Psychology would help the readers onwards on their own journey of unifying the Psychological stream of inquiry.

Cognitive Development: The different perceptual systems while undertaking point-of-view tasks

Jean Piaget had initially proposed that something akin to theory-of-mind develops in the children quite late and they have difficulty seeing things from another person’s perspective. The 2 most comment methods used to study this are false-belief tests and the sight-of-view-from-another-person’s-perspective tests.

A recent insightful article on Cognitive Daily elaborate on the recent work that has been done on the second theory-of-mind test viz. the-sight-of-view tests. Please do read the article for details and some pictures used in the actual experimental setup

To quote the end conclusion of the article (emphasis added):
Michelon and Zacks argue that these experiments offer substantial evidence that we use at least two different methods to understand the perspective of others. When we are trying to decide whether someone else can see what we can see, these experiments suggest that we use the line-tracing method, but when we’re trying to understand the relative positions of objects, we use the more cognitively demanding perspective-taking approach.

Now this conclusion when seen in the light of my earlier mails regarding Cognitive Maps and different models for Space like 3-D linear system, or R,theta,phi angular system induces one to stretch boundaries of analogies further and speculate that when one uses the Cartesian 3-D space metaphor, one may not necessarily need to put oneself in the place of another (as the origin in such systems are arbitrary) and one can trace the line from the other person to the target object and use trace-line mechanism to answer; but when one is forced to answer about left-right distinctions (that necessitate that if angular geometry is used then we have to distinguish between clockwise and anti-clockwise motion…and this may be with reference to origin…in most cases by ourselves as the origin), then the nature of task (making left-right distinctions) literally necessitate that one puts oneself in the place of the other person, and use angular geometry concepts to answer and this may take more time-to-respond as one has to literally rotate one’s frames of reference to align at the new origin (that of the other person).

Interesting line of thought and more evidence regarding the validity of Cognitive Map approach and conclusions derived from it.

Endgame: To give a linguistic twist (and include the determining sets concepts), would the distinction between right-wrong actions of a person require us to literally put in the other person’s shoe…and use angular geometry concepts?

Time Space Metaphors: Do we have different metaphors based on different cultures( mouse traps)

Reading about “conceptual metaphor theory” may be useful for understanding the rest of this mail.

There are 2 great articles regarding space time metaphors on Mixing Memories. Yet the research seems to be focussed only on linear representations of time as Space is automatically assumed to be the Cartesian space of X,Y and Z co-ordinates and the metaphorical mapping of time to space is thus limited in this regard. Also, in the article time perception is regarded as based on either-or of future-movement or ego-movement.

Even when linear metaphors of time are concerned, one can have both future-movement or ego-movement simultaneously. I remember when I was giving IIT-JEE, and the date of exam was approaching, I used to sing a lot a hindi song “Tu hai meri kiran” from Baazigar and liked one of the lines of the stanza the most ” faasle aur kam ho rahe hain, door se pass hum ho rahe hain” which means “The distance is becoming lesser and we are approaching each other from distance to closeness”. This metaphor that I had used was more of event-based whereby both I (ego) as well as future(the test) were moving towards each other to meet at a particular instance/ event.

With reference to the second post on this blog describing how mice may get concepts of Space and develop representations that are either close to Cartesian geometry or alternately of Angular Geometry, it is reasonable to assume that the Time concept/ representation that such mice may develop would also follow the way they represent space.

Of particular interest to us is the metaphorical representation of time for those mice who have developed the concepts of Space as being in r, theta format of angular geometry (some critics may thrash this as regressing back to heliocentric view of the universe with Sun denoting the origin/ centre of universe…..but the representation of time is more Anthropomorphic or Ratothromorphic view, with the origin conceptualized as not the rat or human himself but something close by (preferably a light source) that can be used as reference) and would thus naturally map time to one of the dimensions in r, theta, phi…in this case view time as circular or repetitive or in rhythm. An article that traces internal clock mechanisms like circadian rhythms may be instructive.

Thus, considering the numerous mythical elements in Indian Culture regarding the circular nature of time ( reincarnation, repetitive Eng or ages, no distinction between word ‘kal’ representing either today or tomorrow based on context), i is reasonable to assume that it is possible that some humans/ cultures may have a circular, or at the least, rhythmic representation of time.

Thus while Amyara present a paradox in terms of viewing time backwards, the oriental cultures (esp. Indian) may represent another paradox in terms of viewing time circular or rhythmic. Also to venture into area that I’m ignorant of, this may explain the popularity of films like the ground hog day, explain deja vus and when eventually we would be able to ‘see’ the 4D time-space continuum, may require utilization of both 3-D Cartesian space representations and the angular (or curvature) time perception.

Also, while we are at the topic of time perception, please check this excellent article summing up the major approaches in studying time perception phenomenon.

Cognitive Map continued :The importance of color and other irrelevant facts as to my journey towards color vision

There is an article on EurekaAlert regarding the necessity of colors for identifying say members of your favorite football teams when engaged in a match with an adversary team. The contiguity provided by colors of uniforms worn by players ensures we are able to keep track of which member belongs to which team. As per the article in the absence of colors , we cannot track more than 3 objects at the same time.

The application of this to the cognitive map is evident. In the absence of colors, we may view the world in Black, White and Gray and would be forced to make arbitrary decisions of clubbing everything in one category or the other. This will limit us to make sense of the world in TriColor (if color can be used in this B&W context) (say of satve, rajas and Tamas gunas) by joining some isolated regions together to bi-or-trifurcate the world in some 2 or 3 arbitrary qualities/regions. Thus the world as located on our cognitive map would be made up of 2 or 3 qualia and different colors used to represent different but interconnected and hence same regions. One is reminded of the shloka from Gita ” tri-state is all of creation, be non-tri-state O Arjun”

With even 3(RGB) or 4 (CYMK) or 6 colors (??) at our disposal (and in the language of cognitive maps the ‘colors’ may be equivalent to the ’emotions’ and thus reflect how we feel about that part (region) of the Map), we can have infinite combinations of colors to code the Map and thus either have a kaleidoscopic view of the world (in which there are more colors then can fit our working memory (limited by size constraints of 6 +-2 ); or we can stick to the 4 or 6 colors that are primary and see all the different regions of the cognitive map having the same color(out of the 4 or 6 primary colors) as one particular quality /qualia of the world. Thus all the red regions on our cognitive map may signify all the parts of our life (time-space event) that are felt by us as colored Red or arousing angry feelings (If Red is associated with Anger. Here is a link to V S Ramchnadran’s site that carries many research on synesthasia, though association of color with emotions is not discussed.)

Thus with the correct color coding (either MCYN or yet to be discovered 6 primary color schema….And that color mapped to ‘color’ as applicable in cognitive Maps) and the correct cognitive MAP nature ( a Rotating Sphere or a klien bottle ) with some other type of ‘spin’ one may be better adapted to understand reality and act accordingly knowing which parts of Cognitive map are more or less the same and which Cognitive Map is to be used for which season.

The article contains a quote from the original article viz

. “We found that humans are unable to store information from more than three sets at once,” Halberda said. “This places an important constraint on how humans think about and interact with sets in the world.”

As per this quote even when we have extended sets (say many regions on an Atlas covered in Cyan only- and thus forming one set), we can keep in memory no greater than 3 such sets. Thus we may be able to keep Cyan sets, Magneta sets and Yellow sets in the cognitive Map, but would miss on the Key (or Black set). This seems to be a limitation that has been observed experimentally and needs some thinking. Maybe later experiments (say done on Tibetan Lamas) could verify that more than 3- maybe upto 6 sets can be distinguished.

Before venturing forth and elaborating more on the Cognitive Map theme, I would like to backtrack a bit and again indicate from where I come: I believe that the personality traits from the Five-Factor Model can be mapped to successful or unsuccessful completion of the 5 development tasks that a child need to undergo before becoming an adult (or has an ego, or becomes a hero with a thousand faces!). After the first five developmental task are the 3 qualitatively different tasks that require him/her to reach out to others and thus develop traits that would not be captured by factor analysis that has as its reference an individual; but might possibly be revealed when one talks (or does a factor analysis) about say a pair. Are the pair intimate? are they a case of ‘sleeping with the enemy”? are they sacrificial etc? Broadly the first task and Factor would have to be intimacy and sharing and has to be attained not by an individual but by the pair. Intimacy with married partner may be one task that literally expands your horizons or lets you see issues from both sides of the coin, or with different spins applied to it!

The second (or sixth if the first 5 are also counted) task is related to group performance and solidarity. One could be instrumental and active in competitive groups, co-operating groups, creative/synergetic groups, or even destructive groups. How group dynamism is achieved, how synergy is created, how one submits one’s freedom to the greater good , how one starts understanding when to be competitive, when co-operative and when to go with the flow ( and when to stand up against the tide), all these would be tasks that need to be completed before achieving the feeling of efficacy.

The third (or last or eighth ) task would be to broaden your group identity and start extending it to others – say to whole of live creation. The end result of this would be peaceful death or passage to next life with no guilt feelings. Otherwise feeling of despair may occur instead of feelings of integrity with the world.

Much of the background for above is the ashtang yoga having 5 physical aspects – yam, niyam, asan, pranayam, pratyaharare and after these 3 mental aspects – Dhyan, Dharna and Samadhi.

Also, the analogy with the traditional 4 varna-ashrams that one should observe: Brahmacharya (in which ego identity is achieved while learning- and five personality factors deepened and come to terms with: this has to be completed by 25th B’day and till that time pure celibacy maintained), then Grahastha (next 25 years of your life devoted to marriage so that pure intimacy and union could be achieved), then Vanprastha ( next 25 years of life spent wandering in the forests with like minded people and planting seeds in the form of upnishads etc), Sanyas (the last 25 years of age being at peace with the world and oneself, relaxing and not felling bitter about old age/ physical conditions etc, reflecting on life). Thus the theory predicts to 3 more traits or factors , but these would be applicable to pairs, groups and universe respectively.

On another note, much of insights I have got regarding the 6th and 7th developmental tasks is from studying vision and Eye. After an eye is formed, then one needs a pair for binocular/depth vision. This is the 6th developmental task for eye (to pair up with another). after that one could have different movements of eye leading to different visual capacity: Smooth pursuit (involuntary), Saccadic (voluntary) and Nystagmus (sort of involuntary rhythmic movement).

Another parallel is formed in the physical motion subsystem with 6th step being the contraction and relaxation of muscle to produce desired motion and 7th step being differentiated muscle groups to serve different functions: Smooth muscles (involuntary for ex in stomach), striated/skeleton (voluntary used for locomotion) and cardiac (involuntary rhythmic with some randomness thrown in in the form of pacemaker cells).

Thus, to me the 6th stage of development/evolution normally corresponds to pairing with similar type (but different in some aspect) and then utilizing the pairing to achieve something qualitatively different. The 7th evolution/development stage is normally related either ‘colors or ‘movements’ or ‘group dynamics’ and again leads to new qualities and abilities. Finally the 8th stage is delegating control to someone higher up (say Eye delegating control to brain…Except for some control still retained over the Nystagmus or the muscles of entire body delegating control to brain (CNS) except for some pacemaker cells in the heart.

Pointers to other who would like to build:
1) start thinking about 5 ‘normal’ senses and then the other neglected senses like vestibular, kinesthetic etc.
2) revisit Howard Gardner’s 8 intelligences or EQ’s
3)revisit quarks their properties and dynamics etc

Why the number 8?

reason is Maths: Fibonacci series. Evolution works by building on what is. So assuming initially we have 1, the series of evolution, development becomes 1, 2, 3, 5, 8, 13, 21 and so on.

Assuming somehow that one unit of something gets created. Then any complex system can be theoretically reduced to that one unit. Next come dualist system who can differentiate between the qualities that came into existence when a pair was formed. After that 2+1 units merge to form a new unit with 3 qualities. After that 5 qualities are possible, then eight is possible and then 13 or 21 is possible. I’ll stop here because the Tarot that I used to decipher the Fibonacci (and DA vinci code) has only 21 cards in Major Arcana if one discount the 0 card representing the fool). More about that in later mail. (Some caution, I don’t much believe in Tarot etc, but believe in the archetypal strength of such concepts as they have stood test of time).

So we in 21st century may start with 0 or may move further to 45

Another teaser: Tolman in his other article hints behavior-cues, behavior-object and behavior act as the next 3 steps in his behavioristic cognitive map theory. This makes for the eight fold development stage complete. Interestingly he continues beyond that on problems of Motive and hints at the next 5 spiritual/mental qualities that may be involved ” Finally, the problem of the relation of behavior-act to behavior-object is the extremely important problem of motive. It is the problem of desire, emotion, instinct, habit, determining set.” .

also we should always remember that world and reality is more like Mandelbrot set and each components of one puzzle may end up making an equivalent puzzle to us.

Endgame: is it top down or bottom up: what about say hands (2 of which would come together on 6th stage, and which would individually contain 5 fingers/thumb specialists for different tasks- the result of earlier 5 developmental/evolutionary tasks; what about the seventh task? Also can we just like analyzing from bottom down, start with universe and come down to quantum equations and come to closer approximations in terms of determining sets etc that Tolman was hinting in his other article.

The Cognitive Map continued: Its nature and implications: Is my Map different from Yours?

Would like to elaborate a bit more on the theme of the Cognitive Map especially as applicable to Humans and focusing more on the last 3 learning mechanisms relevant to ensuring that your Map reflects Reality as well as possible and is in accordance with the Reality Principle instead of some other principle (like the Pleasure Principle if it exists!)

In the forthcoming discussion, when I’ll refer to Map, I would start with assuming it to refer to a literal spatial map as outlined on a sphere. ( say a globe representing earth in which all the countries are mapped). The Map is thus 2 dimensional in nature, though outlawed on a 3-D object (Sphere or Oval of the earth shape)

6) Which Map to use for Which Season ( Regression as a pathology?) :

The assumption is that successive Cognitive Maps are placed on a sphere and the globe keeps rotating ensuring that we have the arrest cognitive Map in front of us. If one doesn’t stick to the globe analogy, one can also see the Cognitive Maps as being placed on a tape and when rewinded, they may appear as a movie.

A number of earlier Cognitive Maps not relevant to today’s’ experiment are still with Mice as they had earlier learned or internalized those Maps: Once the Mice or men have formed a Cognitive Map reflecting say the actual spatial location and 2-D nature of the table surface and objects that was used in mice experiments and are able to understand the concepts of either R, theta angular geometry or X,Y Cartesian Geometry , then it may happen that over time they realize that different experiment situation require them to use different cognitive maps (say in one situation they would be required to use the cognitive map using angular geometry concepts and then in other X,Y geometry concepts, then they may come to a logical conclusion that at times it is necessary to use earlier Cognitive Maps that were relevant in some earlier situation and may Regress to an earlier Map when their current Map (more in touch with Reality) does not help in the latest experimental setup. This is the first of the Many problems that they have to overcome before ensuring that they can use a broadly consistent Cognitive Map and become immune from the problem of regression. Imagine a Mice, who has just formed a spatial cognitive Map that has given him insight as to the nature of 2-D space and the location of food object/light in it. Imagine suddenly that he finds that these concepts although valid across many previous situations are no longer valid in the present situation, but force him to change his cognitive map. Then the Rat in an attempt to use an appropriate cognitive Map may start using an earlier map (may regress)

Another Analogy is that of Spinning. You might store your Map in a right-spinning globe, while another rat may overlay the cognitive Map on a left-spinning globe. Thus though the maps are identical, but due to different spins the subjective perception may be different. This may be analogous to the fact that though most groups (tribes/clans) of humans have past in back and future in front, some tribes (eg.. Aymara) actually have past in front and future in back. A word of caution though, here too the past and future are so to say linearly spoken of. In Indian languages, the word for day-after as for day-before is same and may suggest a spherical or repetitive nature of Cognitive Maps/ Reality.

Thus, even when your Map is Correct, it is not a single Map but one that is overlaid on a sphere and thus needs to be revolved in a particular direction to update with most accurate cognitive Map. Even when you have done this, if you don’t want to regress, you may have to take help of another mice to ‘see the map from a different angle’/ Assuming that you pair with a mice of different spin orientation, you would then be able to is any Map for any situation. Interesting to note that recent experiments have revealed that people take help of their spouses in storing memories. This may also explain why loss of spouse may be the most triggering factor for regression.

7) How many Colors do you need to paint your Map (which color is your umbrella):

After the Cognitive Maps have been developed and the trick of spinning there globe in clockwise or anti-clockwise direction to get an appropriate Cognitive Map is learned, the difficult question of how to distinguish the cognitive Map appropriate for the situation arises. Before deciding appropriateness, one must first face the problem of how to distinguish the different Maps. (Here I take Map as referring to a contiguous region on a globe- like a country). The answer is simple; a -priori- we need four colors as per four-color theorem. This would be true if the cognitive Maps were indeed mapped on a sphere. In this case one can use CMYK system as used in color printers (a subtractive system). We want pure colors for Mapping- we do not want to mix colors as that may lead to confusion as to us remembering a lot of different colors due to different shaded maps.) Also by using these 4 colors we can still print on our mental map the different shades of all hues. Thus this can give us an opportunity for identifying regions/Maps in ‘pure’ colors as well as identifying regions/Maps in their ‘actual/mixed’ colors. Point to note that in CMYK, the K stands for Key which is usually represented by Black ink. Thus, in CMYK system some regions would be marked as black.

Some notes though:- There are other strong contenders for how we may color our maps.

1. One is the HSV model, whereby one would assign a different Hue to every region(and this is done in terms of an angle), and a saturation (how ‘pure’ and non-grey is the color) and a brightness (how bright or high energy the region/map is). This model would be learned most easily by this rats who learned the R.Theta angular geometry. HSL is also similar.

2. The second is RGB model. Here every region is given a Cartesian co-ordinate corresponding to R, G and B values which start form 0 at origin and move towards infinity as we move away from origin.

3. The third is YUV model. Hereby there is one luminance components (Y) and 2 chromonence componenets (u,v). The primary advantage of this model is that it is compatible with black and white (or grayish) view and coloring of Maps. Thus with this system, one can choose to see the Maps in color or in grey at whim!

Before closing on the color theory of maps, would like to throw one more gauntlet. It seems a Klien bottle (which is a surface that has no inside and outside ( and in this respect is similar to mobius strip) is the only surface that does not follow a rule in mathematic for calculating the number of colors needed to paint regions on that surface. The klien bottle requires 6 colors . My personal view is that our reality as well as the cognitive Maps we make follow more the Kline bottle surface and hence would need 6 colors to fully color them. These may be 6 colors or 6 factors related to color/luminance etc). I am pursuing thus path because of analogous 6 types of flavors in quarks (up,bottom, top, strange, charm, down). Also the previous discussion of spins is partly influenced by the isospin of quarks.

A dysfunctional (or incorrectly colored cognitive map) map would lead to problems like fixation. If the map is painted all Red and no other colors are used(and if red is associated with anger in that person’s internal language), then we have a case whereby the person who uses excessive red in his map is fixating his energy on anger (or a previous map that was excessively red)

Parting note on this: the colored cognitive map theory may explain the charm of Picasso or stained glass windows.

8) Who shares your map and who doesn’t :

Ultimately, when a mice or (wo)man acts, it has to determine not only what cognitive map is relevant for the situation, but also who else would share that cognitive map . This info is necessary irrespective of whether the motive is to compete or co-operate. Slowly over the different experiments the mice learn that not only they themselves know a bit about the maze, but that other mice (as well as the experimenter 🙂 ) knows about the Maze. In such insight situations, if the mice feels frustrated it may either seek help from conspecifics or direct his anger towards non-conspecifics (like the experimenter). Thus, after this last set of experiments he may start co-operating and sharing his Cognitive Map with others or retreat and exhibit “displacement of aggression”. This would work even in case of husband-wife agression displacement, if the spouse does not understand the map of the other.

An instructive way of looking at these Cognitive Maps an be form the other end of the spectrum (i.e instead of analogies with quarks/particles look at the analogies with light/waves) . tolman seems to have taken a similar approach in his another landmark article. Here he discusses behavior tendencies, behavior acts et and they seem more like quantum Fields and collapse of the quantum wave. More on that in a later post.

For now a parting link to a recent article that grants more intelligence to mice than was customary till now.