(Bartlett, Broadbent, Tulving, Damasio, Lenneberg, Wittgenstein, Rosch, Lakoff, Fauconnier, Keil, Piaget, Karmiloff-Smith, Hobson, Jouvet, Winson)

Memories are Made of This

The mind’s cognitive faculties depend to a great extent on memory. The mind would not truly be a mind is we couldn’t learn and remember at all. The process of thinking depends on the process of categorizing: the mind deals with concepts, and concepts exist because memory is capable of organizing experience into concepts. The mind looks like, ultimately, as a processor of concepts. The mind's functioning is driven by memory, which is capable of organizing knowledge into concepts. So much so that, inevitably, a theory of memory becomes a theory of concepts, and a theory of concepts becomes a theory of thought.

Cognition revolves around memory. All cognitive faculties use memory and would not be possible without memory. They are, in fact, but side effects of the process of remembering. There is a fundamental unity of cognition, organized around the ability to categorize, to create concepts out of experience.

Memory's task is easily summarized: to remember past experience. But, unlike the memory of a computer, which is structured and works in a fairly intuitive way, human memory does in many ways a weird and poor job at remembering.

First of all, it rarely remembers things exactly the way they happened. Memory of something is almost always approximate. Many details are forgotten right away. If we want to remember a poem by heart, we have to repeat it to ourselves countless times. And sometimes memory is also very slow: sometimes it takes a long time to retrieve a detail of a scene, sometimes it will take days before the name of a person comes back to mind. Rather than accessing memories by calendar day or person's name, we seem to access them by associations, which is a much more complicated way to navigate in the past.

Anomalies abound. For example, we cannot count very easily. Do you know how your home looks like? Of course. How many windows does it have? You have looked at your home thousands of times, but you cannot say for sure how many windows it has. If you see a flock of birds in the sky, you can tell the shape, the direction, the approximate speed... but not how many birds are in the flock, even if there are only six or seven.

Human memory is a bizarre device that differs in a fundamental way from the memory of machines: a camera or a computer can replicate a scene in every minute detail; our memory was just not designed to do that.

What was our memory designed to do?

The Reconstructive Memory

The most startling feature of our memory is that it does not remember things the way we perceived them. Something happens between the time we see or hear a scene and the time that scene gets stored in memory.

In the 1930's, the British psychologist Frederic Charles Bartlett developed one of the earliest models of memory. Bartlett studied how memory "reconstructs" the essence of a scene. We can easily relate the plot of a movie, and even discuss the main characters, analyze the cinematography, and so forth, but we cannot cite verbatim a single line of the movie. We stored enough information about the movie that we can tell what it was about and perform all sorts of reasoning about it, but we cannot simply quote what a character said at one point or another.

What Bartlett discovered is that events are not stored faithfully in memory: they are somehow summarized into a different form, a "schema". Individuals do not passively record stories verbatim, but rather actively code them in terms of schemas, and then can recount the stories by retranslating the schemas into words.

Each new memory is categorized in a schema which depends on the already existing schemas. In practice, only what is strictly necessary is added. When a memory must be retrieved, the corresponding schema provides the instructions to reconstruct it. That is the reason why recognizing an object is much easier in its typical context than in an unusual context.

The advantage of the "reconstructive" memory is that it can fit a lot of information in a relatively narrow space. Any memory that tried to store all the scenes, text and sound of a movie would require an immense amount of space. But our memory stores only what is indispensable for reconstructing the plot and other essential features of the movie, thereby losing lots of details but at the same time saving a lot of space.

Several Types of Memory

The standard model that became popular in the late 1950's, due to the work of psychologists such as Donald Broadbent and George Miller, was based on the existence of two types of memory: a "short-term memory", limited to few pieces of information, capable of retrieving them very quickly and subject to decaying also very quickly; and a "long-term memory", capable of large storage and much slower in both retrieving and decaying. The idea was already implicit in William James’ writings, but Broadbent hypothesized that short-term memory may be just a set of pointers to blocks of information located in the long-term memory.

Broadbent also stated the principle of "limited capacity" to explain how the brain can focus on one specific object out of the thousands perceived by the retina at the same time. The selective character of attention is due to the limited capacity of processing by the brain. In other words, the brain can only be conscious of so many events at the same time. What actually gets the attention is complicated to establish, because Broadbent found out that attention originates from a multitude of attentional functions in different subsystems of the brain.

Broadbent's model of memory reflected at least two well-known features of memory: information about stimuli is temporarily retained but it will fade unless attention is turned quickly to it; the unattended information is "filtered out" without being analyzed. He drew a distinction between a sensory store of virtually unlimited capacity and a categorical short-term store of limited capacity. This is the way that a limited-capacity system such as human memory can cope with the overwhelming amount of information available in the world.

At the same time, George Miller’s experiments proved that the short-term memory can hold only up to seven "chunks" of information and therefore provided an order of magnitude for it. It wasn’t clear, though, the "size" of a chunk: is the entire car a chunk of information, or is each wheel a chunk, or...? In Broadbent’s model, a chunk is a pointer to something that already exists. Therefore a chunk can be even very "big", as long as it is already in memory. Its "size" is not important (in short-term memory, it is only a pointer). This is consistent with experiments in which short-term memory proves to be capable of holding familiar images, but not of images never seen before.

Today, it appears that neurons in the prefrontal cortex (the newest part of the brain, from an evolutionary standpoint) can draw data from other regions of the brain and hold them for as long as needed. The prefrontal cortex is unique in having a huge number of connections with the sensory system and with lower brain centers. The prefrontal cortex could be the locus of a "working memory", in which decisions, planning and behavior take place.

Experiments conducted in the 1970's by the Canadian psychologist Endel Tulving proved that "intension" (such as concepts) and "extension" (such as episodes) are dealt with by two different types of memory: episodic memory contains specific episodes of the history of the individual, while semantic memory contains general knowledge applicable to different situations. Episodic memory, which receives and stores information about temporally dated episodes and spacetemporal relations among them, is a faithful record of a person's experience. Semantic memory, instead, is organized knowledge about the world. In episodic memory, accessibility of a piece of information depends on the conditions ("cues") under which that piece of information has been learned.

Tulving also devised a scheme by which memory can associate a new perception or thought to an old memory: the remembering of events always depends on the interaction between encoding and retrieval conditions (or compatibility between the "engram" and the "cue").

Things are more complicated than Broadbent’s generation thought, but the standard model is still a good approximation of what we know.

Categories

Arguably the most important function of memory is categorization. The rings of a tree or the scratches on a stone can be said to "remember" the past, but human memory can do more: it is capable of using the literal past to build abstractions that are useful to predict the future. It is able to build generalizations. Actually, categorization is the main way that humans make sense of their world. For example, if we analyze the grammar of our language, the basic mechanisms of meaning-bearing are processes of categorization.

One can even wonder whether all living beings, or at least many of them, need to do some level of categorization in order to deal with the world.

Eric Lenneberg has argued that all animals organize the sensory world through a process of categorization. They exhibit propensities for responding to categories of stimuli. In humans this process of categorization becomes "naming", the ability to assign a name to a category. But even in humans the process of categorization is still a process whose function is to enable a similar response to different stimuli.

Traditionally, categories were conceived as being closed by clear boundaries and defined by common properties of their members. The psychologist Jerome Bruner was influential in conceiving categories as sets of features: a category is defined by the set of features that are individually necessary and jointly sufficient for an object to belong to it. This seems to be the case for nominal types (the one invented by us, such as "mother" or "triangle"), but not for natural types.

As the great Austrian philosopher Ludwig Wittgenstein pointed out (in 1953), a category like "game" does not fit the classical idea (both cards and chess and football are sports, but they have very little in common). A dog that does not bark or a dog with three legs or a vegetarian dog would probably still be considered a dog, even if it violates the set of features we usually associate with the concept of a dog. What unites a category is "family resemblance", plus sets of positive and negative examples. Its boundaries are not important: they can be extended at any time.

Prototype Theory

The traditional view that categories are defined by common properties of their members was quickly replaced by Rosch's theory of prototypes. As we all know, the best way to teach a concept is to show an example of it.

Eleanor Rosch noted that some members of a category seem to be better examples of the category than others. Not all members are alike, even if they share all the same features of the category. This implies that the features by themselves are not enough to determine the category. It also implies that there may be a "best" example of the category, what she called the "prototype" of the category.

In the 1970's, she founded her early theory on two basic principles of categorization: 1. the task of category systems is to provide maximum information with the least cognitive effort; and 2. the perceived world comes as structured information. In other words, we do categorization because it helps save a lot of space in memory and because the world lends itself to categorization. Concepts promote a cognitive economy by partitioning the world into classes, and therefore allow the mind to substantially reduce the amount of information to be remembered and processed.

In Rosch's theory of prototypes, a concept is represented through a prototype which expresses its most significant properties. Membership of an individual in a category is then determined by the perceived distance of resemblance of the individual to the prototype of the category.

Next, Rosch unified a number of experimental findings and proposed that thought in general is organized around a privileged level of categorization. In the Fifties, the psychologist Roger Brown had noted that children tend to learn concepts at a level which is not the most general and not the most specific (say, "chair", rather than "furniture" or "armchair"); and, in The Sixties, the anthropologist Brent Berlin, in his studies on colors and on plants and animals naming, had reached a similar conclusion that applies on categories used by adults. The point was that we can name objects in many different ways: a cat is also a feline, a mammal, an animal, and it is also a specific variety of cat, but we normally call it "a cat". The level at which we naturally name objects is the level of what Brown termed "distinctive action". The actions we perform on flowers are pretty much all the same, and certainly different from the actions that we perform on a cat (e.g., one we smell and one we pat). But the actions we perform on two different varieties of cats or two different types of flowers are the same (we pat both the same way, we smell both the same way). Our actions tell us that a cat is a cat and a flower is a flower, but they can’t tell us that a rose is not a lily. "Cat" and "flower" represent a "natural" level of categorization.

Rosch postulated a level of abstraction at which the most basic category cuts are made (i.e., where "cue validity" is maximized), which she called the "basic" level. Categories are not merely organized in a hierarchy, from more specific to more general. There is one level of the hierarchy that is somewhat privileged when it comes to perception of form, movement of body parts, organization of knowledge, etc. "Chair" and "car" are examples of basic categories. We can form a mental picture of them. We have a motor program for dealing with them. They are the first ones learned by children. The category of "furniture", for example, is different: I cannot visualize it, I do not have a motor program to deal with it, and it takes some time for a child to learn it.

Generalization tends to proceed upwards from this level, and specialization proceeds downward from this level. Superordinate categories are more abstract and more comprehensive. Subordinate categories are less abstract and less comprehensive. The most fundamental perception and description of the world occurs at the level of basic (or natural) categories.

Rosch also realized that categories occur in systems, and they depend on the existence of contrasting categories within the same system. Each contrasting category limits a category (e.g., if a category for birds did not exist, the category for mammals would probably be bigger). At the basic level, categories are maximally distinct, i.e. they maximize perceived similarity among category members and minimize perceived similarities across contrasting categories. Technically, one can use the notion of "cue validity": the conditional probability that an object falls in a particular category given a specific feature. Category cue validity is the sum of all the individual cue validities of the features associated with a category. The highest cue validity occurs at the basic level. The lowest cue validities occur for superordinate categories.

This model of categorization, albeit extremely popular for a while, turned out to be another gross approximation. But the basic model remains a reference point for most researchers: categories are organized in a taxonomic hierarchy, categories in the middle are the most basic, and knowledge is mainly organized at the basic level.

Fuzzy Concepts

Later, Rosch recognized that categories are not mutually exclusive (an object can belong to more than one category to different degrees), i.e. that they are fundamentally ambigous. This led to the use of fuzzy logic in studying categorization.

For example, the American linguist George Lakoff borrowed ideas from Wittgenstein's family-resemblance theory, Rosch's prototype theory and Lotfi Zadeh's theory of fuzzy quantities.

Lakoff started off by demolishing the traditional view of categories: that categories are defined by common features of their members; that thought is the disembodied manipulation of abstract symbols; that concepts are internal representations of external reality; that symbols have meaning by virtue of their correspondence to real objects.

Through a number of experiments, Lakoff first proved that categories depend on two more factors: the bodily experience of the categorizer and what Lakoff calls the "imaginative processes" (metaphor, metonymy, mental imagery) of the categorizer.

His close associate, Mark Johnson, had shown that experience is structured in a meaningful way prior to any concepts: some schemata are inherently meaningful to people by virtue of their bodily experience (e.g., the "container" schema, the "part-whole" schema, the "link" schema, the "center-periphery" schema). We "know" these schemata even before we acquire the related concepts because such "kinesthetic" schemata come with a basic logic that is used to directly "understand" them.

Thus Lakoff argued that thought makes use of symbolic structures which are meaningful to begin with (they are directly understood in terms of our physical experience): basic-level concepts (which are meaningful because they reflect our sensorimotor life) and kinesthetic image schemas (which are meaningful because they reflect our spatial life). Other meaningful symbolic structures are built up from these elementary ones through imaginative processes such as metaphor.

As a corollary, everything we use in language, even the smallest unit, has meaning. And it has meaning not because it refers to something, but because it is either related to our bodily experience or because it is built on top of other meaning-bearing elements.

Thought is embodiment of concepts via direct and indirect experience. Concepts grow out of bodily experience and are understood in terms of it. The core of our conceptual system is directly grounded in bodily experience. This explains why Rosch’s basic level is what it is: the one that reflects our bodily nature. Meaning is based on experience. With Putnam, "meaning is not in the mind". But, at the same time, thought is imaginative: those concepts that are not directly grounded in bodily experience are created by imaginative processes such as metaphor.

In summary, knowledge is organized into categories by what Lakoff calls "idealized cognitive models". Each model employs four kinds of categorizing processes: propositional (which specifies elements, their properties and relations among them in a manner similar to frames); image-schematic (which specifies spatial images in a manner similar to Ronald Langacker’s image schemata); metaphoric (which maps a propositional or image-schematic model in one domain to a model in another domain); and metonymic (which maps an element of a model to another element of the same model). Some models are classical (in that they yield categories that have rigid boundaries and are defined by necessary and sufficient conditions), some models are scalar (they yield categories whose members have only degrees of membership). All models are embodied, i.e. they are linked with bodily experience.

Models build what the French linguist Gilles Fauconnier calls "mental spaces", interconnected domains that consist of elements, roles, strategies and relations between them. Mental spaces allow for alternative views of the world. The mind needs to create multiple cognitive spaces in order to engage in creative thought.

Lakoff argues that the conceptual system of a mind, far from being one gigantic theory of the world, is normally not consistent. In the late Seventies, it appeared apparent that we have available in our minds many different ways of making sense of situations. We constantly keep alternative conceptualizations of the world.

Conceptual Holism

Inspired by Willard Quine's holism, Frank Keil argues that concepts are always related to other concepts. No concept can be understood in isolation from all other concepts. Concepts are not simple sets of features. Concepts embody "systematic sets of causal beliefs" about the world and contain implicit explanations about the world. Concepts are embedded in theories about the world, and they can only be understood in the context of such theories.

In particular, natural kinds (such as "gold") are not defined by a set of features or by a prototype: they derive their concept from the causal structure that underlies them and explains their superficial features. They are defined by a "causal homeostatic system", which tends to stability over time in order to maximize categorizing. Nominal kinds (e.g., "odd numbers") and artifacts (e.g., "cars") are similarly defined by the theories they are embedded in, although such theories are qualitatively different. There is a continuum between pure nominal kinds and pure natural kinds with increasing well-definedness as we move towards natural kinds. What develops over time is the awareness of the network of causal relations and mechanisms that are responsible for the essential properties of a natural kind. The theory explaining a natural kind gets refined over the years.

Convergence Zones

A truly new paradigm has been introduced in the 1980's by the Portuguese biologist Antonio Damasio, with his model based on the idea of "convergence zones".

When an image enters the brain via the visual cortex, it is channelled through "convergence zones" in the brain until it is identified. Each convergence zone handles a category of objects (faces, animals, trees, etc.): a convergence zone does not store permanent memories of words and concepts but helps reconstructing them. Once the image has been identified, an acoustic pattern corresponding to the image is constructed by another area of the brain. Finally an articulatory pattern is constructed so that the word that the image represents can be spoken. There are about twenty known categories that the brain uses to organize knowledge: fruits/vegetables, plants, animals, body parts, colors, numbers, letters, nouns, verbs, proper names, faces, facial expressions, emotions, sounds.

In practice, convergence zones behave like indexes that draw information from other areas of the brain. The memory of something is stored in bits at the back of the brain (near the gateways of the senses): features are recognized and combined and an index of these features is formed and stored. When the brain needs to bring back the memory of something, it will follow the instructions in that index, recover all the features and link them to other associated categories. As information is processed, moving from station to station through the brain, each station creates new connections reaching back to the earlier levels of processing. These connections enable the brain to work in reverse at any time.

The Mind’s Growth

The fundamental feature of the mind is that it is not always the same. Just like every other organ in the body, it undergoes growth. It is not only a matter of memory getting "bigger": the "quality" of the thought system changes in a significant way. What we are capable of doing with our minds changes dramatically during the growth of the mind from childhood to adulthood. It is more than just learning about the environment: the mind literally "grows" into something else, capable of new types of actions. The brain, as well as the rest of the body, undergoes a massive change in shape and volume. Somehow, in the brain's case, this also results in significant new skills.

According to the "genetic epistemology" advanced by the Swiss psychologist Jean Piaget in the 1930's, the development of children's intellect proceeds from simple mental arrangements to progressively more complex ones not by gradual evolution but by sudden rearrangements of mental operations that produce qualitatively new forms of thought.

Cognitive faculties are not fixed at birth but evolve during the lifetime of the individual and Piaget identified four stages of cognitive development: first a child lives a purely sensorimotor life, in which knowledge of the world is only due to her actions in it; then the child begins to deal with internal symbols and introspection; then the child learns to perform internal manipulations on symbols that represent real objects, i.e. internal action on top of external action; finally, the mental life extends to abstract objects, besides real objects. This four-step transition leads from a stage in which the dominant factor is perception, which is irreversible, to a stage in which the dominant is thought, which is reversible.

Also, the mind’s growth seems to follow the need to maintain a balance between the mind and its knowledge of the world. Rationality can then be defined, in general, as the overall way in which an organism adapts to its environment. Rationality occurs when the organism needs to solve a problem, i.e. when the organism needs to reach a new form of balance with its environment. Once that balance has been achieved, the organism proceeds by instinct. Rationality will be needed only when the equilibrium is broken again. The organism develops according to "orthogenesis", evolution directed towards a constant increase in equilibrium.

The British psychologist Annette Karmiloff-Smith has proposed a model of child development that bridges Piaget's constructivism and Fodor's nativism by prescribing for the human mind both some innate capacities and a sequence of subsequent changes.

She has found that children display from the very beginning a whole array of cognitive skills, albeit still unrelated and specific (for example, identifying sounds, imitating other people's movements, recognizing the shapes of faces). The child is therefore born with a set of pre-wired modules that account for these cognitive skills. She contends, in a somewhat Chomskyan fashion, that the mind is structured in separate cognitive categories, each with its own innate structure; and development of the mind proceeds along the same sequential steps for all mental faculties. Somehow, during development the modules start interacting and working together and adult life takes shape. Initially, children learn by instinct, or at least implicitly; then their thinking develops, by redescribing the world from an implicit form to more and more explicit forms, to more and more verbal knowledge.

Naturally, the environment that drives the mind's growth also includes the other individuals. Education and playing are forms of influencing the evolution of the thought system of a child.

Dreams Are Made of This

The bizarre, irrational nature of dreams, where reality gets warped and laws of nature are turned upside down, and why we remember them at all, are some of the most puzzling mysteries of the mind. Dreaming is a process that absorbs a lot of energy; therefore, it must serve a purpose, possible an important one.

Since 1953, when Nathaniel Kleitman and Eugene Aserinsky discovered that dreaming only occurs during one particular phase of sleep, the one characterized by rapid eye movement (R.E.M.), considerable scientific progress has been achieved over the subscientific theories of Sigmund Freud and Carl Jung.

Anthony Stevens has provided an explanation for why some animals started dreaming: dreaming emerged when oviparous animals evolved into viviparous animals. By dreaming, the brain could augment its performance with some "off-line" processing. This made possible to limit the size of the brain while leaving brain activity free to grow. Brains, and thus heads, would remain small enough to pass through the maternal pelvis.

We know that the dreaming brain employs the same systems and processes of the awake brain, except that those processes are not activated by stimuli from the outside world; that the outcome of those processes does not result in (significant) body movements; and that self-awareness and memory are dormant. Basically, as the American psychiatrist Allan Hobson summarizes it, the input, the output, the processor and the working space of the awake brain are replaced by something else.

What differs between wake and sleep is very little, but enough to alter dramatically the outcome: during sleep the brain is bombarded by erratic pulses from the brain stem and flooded with nervous system chemicals. Technically speaking, the awake brain is dominated by "adrenergic" chemicals while the sleeping brain is dominated by "cholinergic" chemicals. Cholinergic chemicals free the system used for cognition and behavior. They paralyze the body by sending pulses to the spinal chord, even if motor neurons are always in motion. The emotional neurons are at the center of dreams' neural activity. They react to the stories that are being pasted together by the brain, based on the inputs produced by the cholinergic processes. These stories are often incongruous, uncertain, approximate, incoherent.

Hobson has built a detailed model which specifies which brain cells and molecules trigger REM sleep and dreaming and the dynamics of their interaction. There's a periodic activation of the brain by the brain stem and a synthesis provided by the forebrain.

The bottom line is that dreams are meaningful: the mind makes a synthetic effort to provide meaning to the signals that are generated internally (during a dream, memory is even "hypermnesic", i.e. is intensified). Wishes are not the cause of the dreaming process, although, once dreaming has been started by the brain stem, wishes may be incorporated in the dream. Therefore, Hobson thinks that dreams need not be interpreted: their meaning is transparent. Or, equivalently, dreams must be interpreted in the realm of neurophysiology, not psychology.

The interplay between the aminergic and the cholinergic systems may be responsible for all conscious phenomena (for Hobson, dreams are as conscious as thinking) and ultimately for consciousness itself. After all, conscious states fluctuate continuously between waking and dreaming.

The Subconscious as a Genetic Program

Hobson’s biological model is supplemented by other models that, while not as far fetched as Freud’s, assign dreams a specific role in the cognitive growth of the mind.

The French physiologist Michel Jouvet, who first localized the trigger zone for REM sleep and dreaming in the brain stem, was also a pioneer of the theory that dreams have a function: to derive crucial action patterns from the genetic program of the individual.

According to his findings, a dream is the vehicle employed by an organism to cancel or archive the day's experiences on the basis of a genetic program. This explanation would also reconcile the dualism between hereditary and acquired features: how much of what we know is innate and how much is acquired by experience? In Jouvet’s scenario, an hereditary component is activated daily to decide how new data must be acquired.

Jonathan Winson expresses this concept in a more general way: dreams represent "practice sessions" in which animals (not only humans) refine their survival skills.

Winson believes in a connection between the neurophysiological processes of the brain (specifically, of the hippocampus) and the unconscious, which lends Freud's psychoanalytical theories some biological plausibility. Dreams are the bridge between the conscious and the unconscious. There is a biologically relevant reason to dream: a dream is an ordered processing of memory which interprets experience that is precious for survival. Dreaming is a sort of off-line processing essential to learning. The Freudian "subconscious" becomes the phylogenetically ancient mechanism involving REM sleep, in which memories and strategies are formed in the prefrontal cortex. In other words, dreams helped us survive a long time before our mind was capable of providing any help at all. And dreams, unlike higher consciousness, are likely to be common to many species.

The mind could well be an evolution of dreaming, which happened in humans and not in other species. First the brain started dreaming, then dreams took over the brain and became the mind, which could be viewed as a continuous dream of the universe.

Incidentally, this history of the mind does not differ too much from the one in which the mind was created by memes. The relationship between memes and dreams is intuitive, and psychologist Joseph Campbell indirectly summarized it with his celebrated aphorism that "a myth is a public dream, a dream is a private myth".

Hobson agrees that the ultimate purpose of dreams is to help us learn. We dream hypothetical situations so that we will be prepared to face real situations of the same kind. When a waking situation occurs, it has probably already been played at least once in our dreams, and we know what to expect. By dreaming, we train our brain: dreams are mental gymnastics. It's like saying that, in order to see something, we must first create the vision of that something in our mind.

Dreaming works in a fashion similar to the immune system: dreams are created all the time for all possible situations, but only some will be useful in real life. An implication of the theory is that dreams may be universal ("impersonal necessities forced on brain by nature"). REM sleep provides a means to combine genetic instructions with experience. Sleep and dreaming are a survival strategy.

Emotion is a way of orienting in the world abd dreams contains the three basic states of emotion: fear of danger, aggressiveness towards competitors and sexual arousal.

Whether driven by the genetic program or not, what the brain does during sleep is consolidating memories that have been acquired during the day. Dreaming, far from being an eccentric manifestation of irrationality, is at the core of human cognition.

Joking

What have joking and dreaming in common? Apparently nothing, but they both belong to the category of acts that do not seem to have a useful funtion. Like dreaming, joking seems to be a pointless waste of energies. Like dreaming, joking is some kind of playing with our experience. Like dreaming, joking is process of rearranging our experience in a somewhat irrational way. Like dreams, jokes do not necessarily require linguistic skills, but normally occur in a linguistic context. More than dreams, actually, jokes tend to rely on language. More than dreams, jokes seem to have developed in humans to a level far more sophisticated than in any other species. We see animals play and laugh, but the gap between a comedian and two lion cubs wrestling in the grass is enormous.

First, we may want to ponder whether human dreams too are so much more complex than other species’ dreams. Second, we may want to ascribe this complexity to the acquisition of language.

Third, we may want to use what we know about dreams to explain why we make jokes at all. While there is no biological evidence to support the idea that jokes have a specific function for our learning and survival, one wonders why we enjoy so much making them. Woody Allen once said that comedy is tragedy plus time: when something tragic occurs, it is inappropriate to make fun of it, but months or years later it may be perfectly appropriate. If I trip on something and break my leg, I am in no mood to hear a joke about it, but it is more than likely that years later somebody will mock me on this subject. Jokes refer to past experience, and usually refer to tragic experience. If not tragic, then significant in some way. The point is that, indirectly, jokes help us learn and remember.

The Evolution of Memories

Memory is not a storage, because it cannot recall events exactly the way they were. Memories change all the time, therefore memory is not a static system, it is a dynamic system.

Memory is pivotal for the entire thought system of the individual. Therefore, memory is about thought, it is not limited to remembering. Memory stores and retrieves thoughts.

Memory can be viewed as an evolving population of thoughts. Thoughts that survive and reproduce are variations of original thoughts, and somehow "contain" those original thoughts, but adapted to the new circumstances. Memories are descendents of thoughts that occurred in the past. Thoughts are continuously generated from previous one, just like the immune system generates antibodies all the time and just like species are created from previous ones.

Memory, far from being a static storage, is changing continuously. It's not a location, it is the collective process of thinking. Every thought contains memories.

Further Reading

Baddeley Alan: YOUR MEMORY (MacMillan, 1982)

Baddeley Alan: WORKING MEMORY (Clarendon Press, 1986)

Baddeley Alan: HUMAN MEMORY (Simon & Schuster, 1990)

Barsalou Lawrence: COGNITIVE PSYCHOLOGY (Lawrence Erlbaum, 1992)

Bartlett Frederic Charles: REMEMBERING (Cambridge Univ Press, 1967)

Broadbent Donald: PERCEPTION AND COMMUNICATION (Pergamon, 1958)

Broadbent Donald: DECISION AND STRESS (Academic Press, 1971)

Bruner Jerome: A STUDY OF THINKING (Wiley, 1956)

Collins Alan: THEORIES OF MEMORY (Lawrence Erlbaum, 1993)

Crowder Robert: PRINCIPLES OF LEARNING AND MEMORY (Erlbaum, 1976)

Damasio Antonio: DESCARTES' ERROR (G.P. Putnam's Sons, 1995)

Estes William: CLASSIFICATION AND COGNITION (Oxford University Press, 1994)

Fauconnier Gilles: MENTAL SPACES (MIT Press, 1994)

Greene Robert: HUMAN MEMORY (Lawrence Erlbaum, 1992)

Hobson J. Allan: THE DREAMING BRAIN (Basic, 1989)

Hobson Allan: THE CHEMISTRY OF CONSCIOUS STATES (Little & Brown, 1994)

Jouvet Michel: LE SOMMEIL ET LE REVE (Jacob, 1992)

Karmiloff-Smith Annette: BEYOND MODULARITY (MIT Press, 1992)

Keil Frank: CONCEPTS, KINDS AND COGNITIVE DEVELOPMENT (Cambridge University Press, 1989)

Lakoff George: WOMEN, FIRE AND DANGEROUS THINGS (Univ of Chicago Press, 1987)

Lenneberg Eric: BIOLOGICAL FOUNDATIONS OF LANGUAGE (Wiley, 1967)

Piaget Jean: EQUILIBRATION OF COGNITIVE STRUCTURES (University of Chicago Press, 1985)

Roediger Henry: VARIETIES OF MEMORY AND CONSCIOUSNESS (Lawrence Erlbaum, 1989)

Rosch Eleanor: COGNITION AND CATEGORIZATION (Erlbaum, 1978)

Schacter Daniel & Tulving Endel: MEMORY SYSTEMS (MIT Press, 1994)

Tulving Endel: ORGANIZATION OF MEMORY (Academic Press, 1972)

Tulving Endel: ELEMENTS OF EPISODIC MEMORY (Oxford Univ Press, 1983)

Winson Jonathan: BRAIN AND PSYCHE (Anchor Press, 1985)

Wittgenstein Ludwig: PHILOSOPHICAL INVESTIGATIONS (Macmillan, 1953)