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.In an introductive book tocognitive science, oddly enough, kitchen recipes are used as metaphors to describehow the brain operates.Readers who have never written a computer program but have used cookbooks canconsider another analogy.A recipe usually has two parts: a list of ingredients and aset of instructions to the ingredients, just as a running program results from applyingalgorithms to data structures such as numbers and lists, and just as thinking results fromapplying computational procedures to mental representations.The recipe analogy forthinking is weak, since ingredients are not representations and cooking instructionsrequire someone to interpret them.(Thagard 2005: 12)As this example demonstrates, one of the main tenets of cognitive psychology is thatinformation functions according to patterns and rules constituting a formal logic thatis totally independent from the actual medium that carries it out (LeDoux 1998: 27).As psychologist Jerry Fodor elaborated in 1983, brain operations would be basedon modules, each focusing on a specific function, e.g.face recognition, speech, andnumbers (Fodor 1983).These modules would constitute a sort of architecture of themind, another metaphor that suggests stability, if not a static condition.The medium within which these modules can operate can be indifferently abrain or a machine.As a matter of fact, terms that are widely used in informationstudies, such as code, signal, processing, transformation, processor, areemployed in other fields connected with the human mind, such as neuroscience,semiotics, and psychology.The relevance of the research on Artificial Intelligence(AI) can be attributed to the spectacular advance of this discipline and to the fact thatmodern computers and robots are symbol-using entities, based on formal systems.Furthermore, AI reinforces the choice of cognitive psychologists to concentrateon the software of the mind rather than on its hardware (Flanagan 1984: 222).To 24 " Bite Mea certain extent, humans and computers are different manifestations of the samephenomenon: they are thinking engines, based on systems organized like computers,which function using signals (Haugeland 1981: 31).According to these theories, the long-lasting mind vs.brain opposition becomesirrelevant, since the mind is virtually disembodied, for all research purposes.Furthermore, the logical and rational aspects of the mind take over its emotionalside since emotions are closely connected with the body and its responses to externalstimuli, even if under brain control.Nonetheless, with the enormous development ofneuroscience in the last 20 years, many scientists have turned their attention back tobrain structures, trying to come to terms with the new discoveries about the relevanceof their physical functions and dynamics (Thagard 2005: 170).Joseph LeDoux notedin his seminal work The Emotional Brain (1998) that it is not possible to separatecognition from the emotional elements of the mind.Furthermore, LeDoux argues,the hardware, the actual structure of the brain, is non-secondary in understanding themind, especially when it comes to emotions (LeDoux 1998: 41: LeDoux 2002).It isnot an easy task.As biologist Steven Rose points out, the brain is full of paradoxes.It is simultaneously a fixed structure and a set of dynamic, partly coherent and partlyindependent processes (Rose 2005: 4).At the same time, the mind is wider than thebrain (Rose 2005: 88).That is to say, we cannot approach the brain s hardware andits functioning in the same way we would dissect the internal wiring of a computer.One of the most influential voices in this field is the Nobel Prize recipient GeraldEdelman.In his book A Universe of Consciousness (2000), written with GiulioTononi, he underlines the features of the brain that point to fundamental differenceswith computers.Since no two brains are identical, the overall pattern of connectionsin a brain can be defined in general terms, but the microscopic variability of theseconnections in different individuals is enormous because of their developmentalhistory and their past experiences.For instance, when it comes to food, althoughchildren of the same family might be genetically similar and are likely to beexposed to the same dishes, they all show their own likes and dislikes, differenttastes, sometimes even diverging memories concerning the same events.Synapticconnections change, die, are created every day, and vary in each individual, affectingthe way things and events are remembered (Edelman and Tononi 2000: 47).Of course, computer simulations of neural networks reveal that a man-madesystem can develop exceptional complexity in a short time if it is programmed todevelop patterns that are beneficial to the goal it is created to carry out.Nevertheless,the inputs the brain receives from the external world are not an unambiguous seriesof signals, as in the case of computers.The brain has developed functions aimedand filtering and organizing perceptions into categories, which are instrumental toour interaction with the world.Furthermore, our perceptions and the categories weuse to give them order are not neutral, impassionate, and impartial.In fact, the brainhas developed several mechanisms called value systems, that is to say, dynamicsaimed to evaluate the relevance (also called salience, meaning to stick out ) of all Hungry Memories " 25sensory inputs.These dynamics are regulated by organs sometimes defined as thelimbic system located outside the cortical areas in charge of rational thinking.Theevaluation of relevance is also determined by substances (e.g.neurotransmitters,hormones and even peptides, a specific kind of protein) that respond to emotionalstimulation and that travel through our body through all kinds of fluids, includingblood.These facts all indicate that neural impulses cannot be compared to computerinformation in that they travel following many alternate routes and that their flowis not linear, going from A to B, bur rather parallel, recursive, feedforward, andfeedback (Cytowic 2003: 156).All these elements influence the strength of synapses (i.e.the contact pointsbetween neurons) because neurons that fire together, wire together, using theexpression modeled after Canadian psychologist Donald Hebb s theory (Hebb1949).In other words, repeated neural activity involving two or more neuronsstrengthens the connection between them, under the influence of value systems (LeDoux 1998: 214).These dynamics have a great impact on learning, categorizingabilities and adaptive behaviors.Because of these factors, human memory differsfrom a computer s in that it is selective.Not every item is retained in the same way,or always retrieved in the same way.As biologist Steven Rose pointedly noted, Dynamism is all.The brain, like allfeatures of living systems, is both being and becoming, its apparent stability a stab-ility of process, not of fixed architecture.Today s brain is not yesterday s, and willnot be tomorrow s (Rose 2005: 147)
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