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Ontario: The 8 Ibid. Folk psychology routinely identifies mental states through their veridicality-conditions. For example, we might identify a belief as the belief that Obama is president , thereby specifying a condition that must obtain for the belief to be true. Or we might identify a desire as a desire to eat chocolate , thereby specifying a condition that must obtain for the desire to be fulfilled. Taking inspiration from folk psychology, cognitive science offers numerous intentional explanations.
For example, perceptual psychology studies how the perceptual system transits from proximal sensory stimulations e. A perceptual state is veridical only if perceived objects have the estimated shapes, sizes, colors, locations, and other such properties. The science identifies perceptual states through representational properties that contribute to veridicality-conditions — e.
Intentional explanations of perception have proved enormously fruitful, illuminating a wide range of perceptual phenomena. Does cognitive science offer successful intentional explanations of animal navigation? While there is room for healthy debate here, my own view is that intentional discourse contributes serious explanatory value at least when applied to mammalian map-based navigation. Scientific research into mammalian navigation hinges upon a straightforward thought: mammalian cognitive maps are estimates.
They estimate geometric aspects of the environment, including the spatial layout of landmarks. An estimate is evaluable as veridical or non-veridical. Cognitive science identifies mammalian cognitive maps at least partly through their veridicality-conditions, i. By identifying cognitive maps in this way, the science delineates systematic patterns of interaction between allocentric cognitive maps, egocentric perceptual states, and actions.
To illustrate, consider coordinate transformations between allocentric and egocentric representations. As we have seen, these coordinate transformations underwrite mammalian localization and mapping.
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They also underwrite the interface between cognitive maps and action: to travel towards a goal, the animal often converts its allocentric representation of the goal into an egocentric representation with immediate consequences for action Gallistel Overall, coordinate transformations figure pivotally in scientific theorizing about mammalian navigation Madl et al. A coordinate transformation preserves veridicality when it carries veridical representations into veridical representations.
Virtually all scientific treatments presume that mammalian coordinate transformations typically preserve veridicality, at least approximately. Given a veridical allocentric cognitive map, the relevant coordinate transformations typically yield veridical or approximately veridical egocentric representations of landmark positions. Approximate veridicality-preservation is a core presupposition of scientific research into mammalian navigation, including the aforementioned computational models.
This core presupposition, although not often made explicit, guides the construction of detailed theories describing how cognitive maps interact with perception and action. It also helps us explain the extraordinary success with which mammals navigate. Veridical allocentric cognitive maps tend to cause veridical egocentric representations, which in turn tend to cause successful actions. Researchers have developed this explanatory strategy with increasing experimental and theoretical sophistication over ensuing decades.
The strategy presupposes that cognitive maps have veridicality-conditions. After all, a coordinate transformation can only preserve veridicality if the representations over which it operates have veridicality-conditions. I favor a broadly scientific realist viewpoint: explanatory success is a prima facie guide to truth. From a scientific realist viewpoint, successful intentional explanation provides reason to attribute veridicality-conditions. For example, the explanatory success of perceptual psychology provides reason to attribute veridicality-conditions to perceptual states Burge ; Rescorla Likewise, successful intentional explanations of mammalian navigation provide reason to attribute veridicality-conditions to mammalian cognitive maps.
I conclude that 2 applies to mammalian cognitive maps. Bayesian models of mammalian navigation provide further evidence for this conclusion. The basic idea behind Bayesian models is that the navigational system maintains a probability distribution over a hypothesis space. Each hypothesis represents some aspect of the spatial environment.
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One such hypothesis might represent that a certain landmark has a certain allocentric location. Another hypothesis might represent that the animal itself has a certain allocentric location. Hypotheses of this kind are incorporated into cognitive maps, which estimate overall spatial layout.
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The probability assigned to a cognitive map is determined by the probabilities assigned to component hypotheses. The navigational system regularly updates its probabilities in light of perceptual input and self-motion cues. In this manner, localization and mapping become exercises in statistical inference.
Current Bayesian models identify the hypotheses through representational properties that contribute to veridicality-conditions. For example, when we identify a hypothesis as representing that a landmark has a certain allocentric location, we cite a condition that must be satisfied for the overall cognitive map to be veridical: that the landmark has the hypothesized location. We thereby identify the hypothesis in intentional terms. Bayesian models describe how probabilities over hypotheses as identified in intentional terms change in light of perceptual input and self-motion cues.
Hence, the science presuppose that 2 applies to mammalian cognitive maps. The success of the Bayesian research program provides further reason to attribute veridicality-conditions to mammalian cognitive maps.
As the research program accrues more explanatory success, the case for an intentional analysis of mammalian navigation should grow commensurately stronger. I now consider the representational format of cognitive maps. Do they have representationally significant geometric structure? More precisely, do they share properties 3 and 4 with ordinary concrete maps? Even if we grant that an animal mentally represents geometric structure, why should we hold that the animal uses geometrically structured mental representations?
What would it even mean to ascribe geometric structure to a mental representation? Pylyshyn : 80—81 warns against the intentional fallacy — the fallacy of confusing properties of a representation with properties of what it represents. Mental representations of color are not colored. Mental representations of loudness are not loud. Why should mental representations of geometric structure be geometrically structured? Note furthermore that cognitive maps do not seem to have literal spatial structure in the brain. In particular, nearby place cells do not correspond to nearby locations in physical space.
In this connection, it is helpful to recall the highly abstract character of modern mathematical geometry. The standard modern procedure is to isolate axioms of geometric structure, such as metric or topological structure. In principle, then, it makes sense to talk about geometric structure over the mental coordinates that appear on a cognitive map. Indeed, if C is a set of mental coordinates, then there are infinitely many metric spaces C , d. If so, does the resulting geometric structure contribute to veridicality-conditions as 4 dictates?
Several authors have explored how something like properties 3 and 4 might be true of cognitive maps e. Brecht et al. The basic idea behind most treatments is that functionally significant neural or psychological relations among mental coordinates induce geometric structure over the cognitive map, where this structure represents geometric relations in physical space. For example, Shea suggests that place cells may have a co-activation structure that represents proximity relations in physical space. An important task for future scientific and philosophical research is to investigate suggestions along these lines.
Doing so should illuminate whether, and in what sense, cognitive maps have representationally significant geometric structure. Cognitive maps figure pivotally in navigation across a range of species. Numerous navigational phenomena are difficult or impossible to explain unless we posit cognitive maps in the loose sense. Animal navigation therefore provides strong evidence for a broadly representationalist approach to psychology.
A vast interdisciplinary literature spanning many decades provides great insight into the nature of cognitive maps, their neurophysiological underpinnings, and the psychological processes in which they participate. We understand quite a bit about cognitive maps, as compared with most other mental representations posited by philosophers and scientists. Nevertheless, numerous questions remain about their format, content, psychological role, and neural basis. This entry will have served its purpose if you feel moved to investigate further.
Honeybees can perceptually estimate the egocentric distances and directions of landmarks. As Burge : emphasizes, the resulting perceptual estimates do not appear to exert much impact upon honeybee localization. Honeybee localization seems to operate primarily through dead reckoning, with periodic resets of the odometer when the bee encounters a familiar landmark Srinivasan Do coordinate transformations between egocentric and allocentric representations play a significant role in honeybee navigation?
The answer is unclear. By comparison with scientific theorizing about mammalian navigation, scientific theorizing about honeybee navigation assigns relatively little weight to coordinate transformations. For example, as mentioned in note 1, honeybees do not seem to localize based upon egocentric perceptually-based representations of landmark distances and directions. Thus, my argument in the main text does not readily generalize from mammals to honeybees. In general, it is unclear whether attribution of veridicality-conditions adds explanatory value to the scientific study of honeybee navigation Burge : —; Rescorla Philosophers sometimes suggest that non-intentional discourse can reproduce any explanatory benefits afforded by intentional explanation Field ; Stich They claim that we can eliminate intentional locutions from cognitive science, without explanatory loss.
In Rescorla , I argue that such claims are implausible when applied to intentional explanations of human perception. I think they are also implausible when applied to intentional explanations of mammalian map-based navigation. For present purposes, I must leave my assessment undefended.
Metrics Views In This Chapter Maps in the Head? Map-based navigation Evidence for cognitive maps in the loose sense Localization and mapping Neurophysiological underpinnings Cartographic representation The explanatory role of veridicality-conditions Geometrically structured mental representations? Conclusion Notes Further reading References.
Maps in the Head? Abstract Any creature that travels through space needs some ability to navigate.
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Map-based navigation Scientists standardly distinguish four main animal navigation strategies. Evidence for cognitive maps in the loose sense To defend the existence of cognitive maps, scientists usually cite evidence that animals take novel detours and shortcuts. Localization and mapping How do animals construct and update cognitive maps? Neurophysiological underpinnings How are cognitive maps realized in the brain?
The explanatory role of veridicality-conditions Intentional explanation is explanation that cites veridicality-conditions or representational properties that contribute to veridicality-conditions. Geometrically structured mental representations? A metric space may be composed of any entities whatsoever. Moral: any entities may be enveloped within a metric structure. Conclusion Cognitive maps figure pivotally in navigation across a range of species. Madl et al. Bennett, A. Bingman, V.
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