Cog sci review for test 1
1 Behaviorism is no longer the dominant paradigm in psychology
60s:Behaviorism is no longer the dominant paradigm: Eliza, turing, hypothesis, 80s-after, artificial science, magnetic reasoning, new tools and tech for simulation of brain Behaviorism is no longer dominant
The following support seeing the study of the brain as an integral part of cognitive science
A The development of new techniques for studying the brain. B The development of powerful tools for simulating brain processes. C The two visual systems hypothesis. D Information processing in artificial neural networks.
What is an algorithm?
A finite set of rules that can be applied systematically to transform objects in circumscribed ways.
Consider the following statement: "A Turing machine is highly idealized and does not actually exist". Is this true?
A. Turing machines are highly idealized and do not in fact exist, because they require an infinitely long string of information. However, computers are, in a certain sense, Turing machines—just finite Turing machines.
Suppose you want to explain to your friend how olfaction (the sense of smell) works and you say "Olfaction takes information from sensory systems about odors and transforms it into a representation of discrete smells. But I'm not sure how the odors are transformed into discrete smells or what representations are involved in the process." What level of explanation do you need to answer these latter questions, according to Marr?
Algorithmic
Why are artificial neural networks so useful for cognitive science?
Because they provide a bridge between algorithm and implementation.
Chomsky was interested in gaining a theoretical understanding of why languages work as they do. How does the theory of transformational grammar contribute to this project?
Chomsky computers to transform to another sentence = in meaning Info processing: model , how it effected cognitive science
Behaviorists thought that even complex behaviors like language could be explained as a series of conditioned responses.
true
Chomsky's theory of syntax illustrates the hierarchical nature of language.
true
Fodor thought that the easiest way to understand how the brain works was to think of the brain as a type of computer.
true
Navigation examples (such as finding a new route when a road is closed, or driving to a new restaurant in a familiar part of town) are everyday examples of tasks that require us to use cognitive maps.
true
2 Shepard and Metlzer's experimental paradigm Is it significant that it seems to participants as if they are rotating one image to compare it with the other?
Experiment by shepard nd Metlerz- representing in brain different from pixels in computers Yes, introspection is absolutely a valid method in psychology. While the reports that people give when they are being studied may not always be accurate to what is really going on in the mind, itdoes give researchers clues to how the mind is processing material. With respect to Shepard and Metlzer's experiment paradigm, it is indeed significant that the participants map the turning of one figure out to see if it will match the other. While judging space, distance, and proximity is something that all people do in navigating their way through their days, this revelation hints at much more complex mechanisms at work
None of the functions of the human body are multiply realizable.
False
Tolman
In classic experiments, Tolman convincingly demonstrated that you need some notion of mental representation — like a mental map — to explain rat behavior. This idea challenged behaviorist dogma and paved the way for cognitive science.
1 Is it important that SHRDLU only deals with a micro-world and a restricted language? Winograd's idea: "All language use can be thought of as a way of activating procedures within the hearer."
It is important that SHRDLU only deals with a micro-world and restricted language, in order for the program to grasp the situation and be able to respond, it must have a strict parameter that it is working from. Without the constraint of the set programming SHRDLU would not be able to decipher the instructions given to it and then act upon them. The whole idea behind the program is to process information and respond. Much like the way that the mind processes information, SHRDLU breaks sentences down using the programming rules and searches for directions automatically. While SHRDLU is impressive as a tool to study cognitive workings, it is only a very simple representation of what the brain is capable of
3 Is neural network modeling a useful endeavor in cognitive science? Why or why not?
Neural networks are part of the associationist tradition that goes back to Aristotle There are similarities with behaviorist, S-R theories: The notion that all complex behavior can be explained in terms of simple associations A cognitive version of S-R theories?
Theory of computation, Turing machines, and algorithms. Is computation what minds do, as many cognitive scientists believe?
Theory of computation: how efficiently problems can be solved on a model of computation, using an algorithm. algorithm: * precise set of steps Turing machines : how machines could be specified mathematically TURINING TEST :Evaluate machines ability to exhibit intelligent behavior indistinguishable from that of a human Turing described the machine, did not build machine
Explain the connection between Shepard and Metzler's mental imagery study and Kosslyn's (1973) experiment. They both uncovered mental imagery processes.
They both uncovered mental imagery processes. They also both caused problems for the idea of digital representation of information in the brain.
What type of analysis is illustrated by Marr's three levels of explanation?
Top-down
A machine's ability to exhibit intelligent behavior indistinguishable from that of a human may be evaluated by
Turing tests.
Which of the following are examples of cognitive systems that can be understood "hierarchically"?
Vision, smell. hearing
1 Can we understand the mind without investigating the brain? (HW2)
We can learn much about the mind without knowing a neuron from an astrocyte. As I often repeat to myself and occasionally to others, "If you want to understand human performance, study human performance." But brain data provide information about the mind that cannot be gleaned from even the most careful studies of behavior. In short, brain data provide a physical grounding that constrains the myriad otherwise-plausible models of cognition. They give us a direct window into which mental processes involve similar and different neurobiological processes, allowing us to use biology to 'carve nature at its joints' and understand the structure of mental processes (Kosslyn, 1994). Brain function also provides a common language for directly comparing and contrasting processes that are otherwise 'apples and oranges,' such as attention and emotion. This common language is a basis for the integration of knowledge across different types of research—basic and clinical, human and nonhuman.
Which of the following most accurately describes the two visual systems, as proposed by Ungerleider & Mishkin?
Which of the following most accurately describes the two visual systems, as proposed by Ungerleider & Mishkin?
3 Marr's computational analysis of the visual system Marr's approach: a top-down approach to cognitive science
computational analysis of the visual system: computational investigation into the human representation and processing of visual info, analyze cognitive systems: 1) translate gen description fo cog systems into a specific account of particular info processing identify the constraints that hold upon any solution to info processing task. Top-down analysis: specific info processing, thinking about human vision, visual system strongly influenced by research. Damage to the left and right parietal cortex- areas of the brain tend to produce problem perceptual recognition. Right partial lesions are able to recognize and verbally identify familiar objects provided they can see them from familiar or conventional perspectives. The left parietal lesions diametrically opposed pattern of behavior =, language problem. info about the shape of an object processed sseparatelyfrom info about object and what its called , the visual system can deliver a specificaion of shaope on an object even when the object is not in any sense recognized.
What is one major theme in the work of Chomsky, Miller, and Broadbent?
information
3 Is Searle's Chinese room thought experiment a convincing argument? In general, what do you think of the use of thought experiments?
One of the most commonly raised objection is that even though the person in the Chinese Room does not understand Chinese, the system as whole does - the room with all its constituents, including the person. This objection is often called the Systems Reply and there are various versions of it. For example, artificial intelligence researcher, entrepreneur and author Ray Kurzweil says in [5] that the person is only an executive unit and that its properties are not to be confused with the properties of the system. If one looks at the room as an overall system, the fact that the person does not understand Chinese doesn't entail that this also holds for the room. Cognitive scientist Margaret Boden argues in [1] that the human brain is not the carrier of intelligence, but rather that it causes intelligence. Analogously, the person in the room causes an understanding of Chinese to arise, even though it does not understand Chinese itself. Searle responds to the Systems Reply with the semantic argument: Even the system as a whole couldn't go from syntax to semantics and, hence, couldn't understand the meaning of the Chinese symbols. In [9], he adds that the person in the room could theoretically memorize all the formal rules and perform all the computations in its head. Then, he argues, the person is the entire system, could answer Chinese questions without help and perhaps even lead Chinese conversations, but still wouldn't understand Chinese since it only carries out formal rules and can't associate a meaning with the formal symbols.
4 What role should functional neuroimaging play in cognitive science? Are there any criticisms of using it?
Pictures have a powerful effect on people Sometimes too powerful! Diane Beck (2010): People find brain images and neuroscience language more convincing Greene's work on moral judgments shows how careful research can clarify the theoretical issues Think of neuroimaging as just another dependent variable Compare, say, PET results with reaction time data: Both work best if (a) we have models that make explicit predictions and (b) the predictions imply a double dissociation with some independent variable
2 Is intentional realism the correct approach to thinking about propositional attitudes?:
Propositional attituedIs intentional realism the correct approach to thinking about propositional attitudes? Intentional realism, as articulated by Fodor, is the commitment to states which. are (1) semantically evaluable, (2) causally efficacious in producing behavior, and (3) truly described by the generalizations of commonsense psychology. Thus, any theory.
What is one way to understand sentences in the language of thought?
Purely semantically, in terms of how they represent the world.
What reasons suggested that cognitive tasks involve ways of encoding information very differently from how information is encoded in a digital computer?
Shepard & Metzler's experiments.
1 Is the physical symbol system hypothesis correct? Does problem solving lie at the heart of intelligence, as Newell and Simon suggest?
we have already seen how a physical symbol system can contain processes for generating complex symbol structure from the basic building blocks provided by the system's alphabet but what really matters is what the system does with those complex symbol structures—just as what really matters in propositional logic are the rules that allow one complex formula to be derived from another the physical symbol system hypothesis is a hypothesis about intelligence and intelligent action this means that it has to explain what thinking consists in—whether in human beings or in machines and here we have the distinctive claim of the physical symbol system hypothesis this is that thinking is simply the transformation of symbol structures according to rules any system that can transform symbol structures in a sophisticated enough way will qualify as intelligent and when we fully understand what is going in agents that we uncontroversially take to be intelligent (such as human beings), what we will ultimately find is simply the rule-governed transformation of symbol structures this hypothesis about thinking is simple (and in many ways compelling) there are many different things that count as thinking but not all of them really count as manifestations of intelligence after all, even daydreaming is a type of thinking Newell and Simon's fundamental claim is that the essence of intelligent thinking is the ability to solve problems intelligence consists in the ability to work out, when confronted with a range of options, which of those options best matches certain requirements and constraints intelligence only comes into the picture when there is what might abstractly be called search-space the notion of a search-space is very general one example might be the position of one of the players halfway through a chess game—as in the situation being analyzed by Newell and Simon in Figure 6.1 each chess player has a large number of possible moves and a clearly defined aim—to checkmate her opponent the possible moves define the search-space and the problem is deciding which of the possible moves will move her closest to her goal another example (much studied by computer scientists and mathematicians) is a traveling salesman who starts in a particular city (say, Boston) and has to visit twenty other cities as quickly and efficiently as possible before eventually returning to Boston here we can think about the search-space in terms of all the possible routes that start and end in Boston and go through the twenty cities (perhaps visiting some more than once) the diagram at the top in Figure 6.2 illustrates a simpler traveling salesman problem with only five cities
