Morphological content (MC) is content that is implicit in the standing structure of the cognitive system. Henderson and Horgan claim that MC plays a distinctive epistemological role unrecognized by traditional epistemic theories. I consider the possibilities that MC plays this role either in central cognition or in peripheral modules. I argue that the peripheral MC does not play an interesting epistemological role and that the central MC is already recognized by traditional theories.

The paper offers a solution to the generality problem for a reliabilist epistemology, by developing an “algorithm and parameters” scheme for type-individuating cognitive processes. Algorithms are detailed procedures for mapping inputs to outputs. Parameters are psychological variables that systematically affect processing. The relevant process type for a given token is given by the complete algorithmic characterization of the token, along with the values of all the causally relevant parameters. The typing that results is far removed from the typings of folk (...) psychology, and from much of the epistemology literature. But it is principled and empirically grounded, and shows good prospects for yielding the desired epistemological verdicts. The paper articulates and elaborates the theory, drawing out some of its consequences. Toward the end, the fleshed-out theory is applied to two important case studies: hallucination and cognitive penetration of perception. (shrink)

To avoid teleological interpretations, it is important to make a distinction between functions and uses of consciousness, and to address questions concerning the consequences of consciousness. Assumptions about the phylogenetic distribution of consciousness are examined. It is concluded that there is some value in identifying consciousness an exclusively human attribute.

Gray's integration of the different levels of description and explanation in his theory is problematic: The introduction of consciousness into his theorising consists of the mind-brain identity assumption, which tells us nothing new. There need not be correlations between levels of description. Gray's account does not extend beyond “brute” correlation. Integration must be achieved in a principled, mutually constraining way.

There is ample evidence that humans (and other primates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision-making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge expansion and heuristic simplification. One region (...) implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort minimization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and routine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to address unresolved issues. (shrink)

Abstract.There is ample evidence that humans (and other primates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision‐making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge expansion and heuristic simplification. One region (...) implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort minimization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and routine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to address unresolved issues. (shrink)

We describe a set of two computer‐implemented models that solve physics problems in ways characteristic of more and less competent human solvers. The main features accounting for different competences are differences in strategy for selecting physics principles, and differences in the degree of automation in the process of applying a single principle. The models provide a good account of the order in which principles are applied by human solvers working problems in kinematics and dynamics. They also are sufficiently flexible to (...) allow easy extension to several related domains of physics problems. (shrink)

The dual concepts of mindfulness and mindlessness are described. Mindfulness is a state of conscious awareness in which the individual is implicitly aware of the context and content of information. It is a state of openness to novelty in which the individual actively constructs categories and distinctions. In contrast, mindlessness is a state of mind characterized by an over reliance on categories and distinctions drawn in the past and in which the individual is context-dependent and, as such, is oblivious to (...) novel aspects of the situation. Mindlessness is compared to more familiar concepts such as habit, functional fixedness, overlearning, and automatic processing. Like mindlessness, these concepts concern rigid invariant behavior that occurs with little or no conscious awareness. The primary difference is that mindlessness may result from a single exposure to information. When information is given in absolute language, is given by an authority, or initially appears irrelevant, there is little manifest reason to critically examine the information and thereby recognize the ways it may be context-dependent. Instead, the individual mindlessly forms a cognitive commitment to the information and freezes its potential meaning. Alternative meanings or uses of the information become unavailable for active cognitive use. Automatic vs controlled processing, while seemingly most similar to mindlessness/mindfulness, are orthogonal to them. One can process information in a controlled but mindless manner, or automatic but mindful. Related concepts like scripts, set, expectancy, labels, and roles direct behavior, but these too may be enacted mindlessly or mindfully. The major consequences of mindlessness/mindfulness are discussed with respect to their relevance for overt behavior , memory, and health. Finally, the relationship between traditional notions of consciousness and mindfulness is briefly examined. (shrink)

Despite the accumulation of substantial cognitive science research relevant to education, there remains confusion and controversy in the application of research to educational practice. In support of a more systematic approach, we describe the Knowledge-Learning-Instruction (KLI) framework. KLI promotes the emergence of instructional principles of high potential for generality, while explicitly identifying constraints of and opportunities for detailed analysis of the knowledge students may acquire in courses. Drawing on research across domains of science, math, and language learning, we illustrate the (...) analyses of knowledge, learning, and instructional events that the KLI framework affords. We present a set of three coordinated taxonomies of knowledge, learning, and instruction. For example, we identify three broad classes of learning events (LEs): (a) memory and fluency processes, (b) induction and refinement processes, and (c) understanding and sense-making processes, and we show how these can lead to different knowledge changes and constraints on optimal instructional choices. (shrink)

The model proposed by Redish et al. considers vulnerabilities within decision systems based on expectancy-value assumptions. Further understanding of processes leading to addiction can be gained by considering other inputs to decision-making, particularly affective associations with behaviors. This consideration suggests additional decision-making vulnerabilities that might explain addictive behaviors.

In this paper I consider the relation between Descartes' psychology of vision and the cognitive science approach to psychology (henceforth CS). In particular, I examine Descartes' the Optics (1637) in the light of David Marr's (1982) position in CS. My general claim is that CS can be seen as a rediscovery of Descartes' psychology of vision. In the first section, I point to a parallel between Descartes' epistemological revolution, which created the modem version of the problem of perception, and the (...) cognitive revolution. These fundamental revolutions in theoretical psychology were both inspired and legitimated by a revolution in mathematics. They took place in accordance with one of Marr's maxims: “To the desirable via the possible”. In the second section, I demonstrate that in the Optics, Descartes explains perception of metrical properties in a way that — on a detailed level — is in accordance with how Man argues that complex information processing systems have to be explained: both Descartes and Man emphasize the co-ordination of logical and physical analysis. In the third section, I claim that Descartes' arguments for a sharp distinction between mechanical transmission of sense data (sensation) and non-mechanical inferences on those sense data (thinking) are sound arguments seen from Man's position in CS. Descartes' arguments are based on his logical and physical analysis. Malebranche's radicalized version of Cartesian dualism turns Descartes' empirically-based assumption that mechanisms cannot realize inferences into a metaphysical assumption. In the final section, I argue that this metaphysical assumption contributes to an understanding of perception as a non-symbolic, non-inferential bottom-up process in mainstream monistic and mechanistic scientific psychology until the cognitive revolution. (shrink)

As Gray insists, his comparator model proposes a brute correlation only – of consciousness with septohippocampal output. I suggest that the comparator straddles a feedback loop that boosts the activation ofnovelrepresentations, thus helping them feature in present or recollected experience. Such a role in organizing conscious contents would transcend correlation and help explain how consciousness emerges from brain function.

Visual masking of primes lowers prime visibility but spares processing of primes as reflected in prime–target congruence and prime–response compatibility effects. However, the question is how to appropriately measure prime visibility. Here, we tested the influence of three procedural variables on prime visibility measures: prime–target similarity, prime–response similarity, and the variability of prime–response mappings. Our results show that a low prime–target similarity is a favorable condition for a prime visibility measure because it increases the sensitivity of this measure in comparison (...) to a high prime–target similarity. (shrink)