We offer an ecological (Gibsonian) alternative to cognitive (im)penetrability. Whereas Pylyshyn explains cognitive (im)penetrability by focusing solely on computations carried out by the nervous system, according to the ecological approach the perceiver as a knowing agent influences the entire animal-environmental system: in the determination of what constitutes the environment (affordances), what constitutes information, what information is detected and, thus, what is perceived.

Leech et al. present a connectionist algorithm as a model of (the development) of analogizing, but they do not specify the algorithm's associated computational-level theory, nor its computational complexity. We argue that doing so may be essential for connectionist cognitive models to have full explanatory power and transparency, as well as for assessing their scalability to real-world input domains.

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance theTractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational‐level theories of cognition. To utilize this constraint, a precise and workable definition of “computational tractability” is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial‐time computability, leading to theP‐Cognition thesis. This article (...) explains how and why the P‐Cognition thesis may be overly restrictive, risking the exclusion of veridical computational‐level theories from scientific investigation. An argument is made to replace the P‐Cognition thesis by theFPT‐Cognition thesisas an alternative formalization of the Tractable Cognition thesis (here, FPT stands for fixed‐parameter tractable). Possible objections to the Tractable Cognition thesis, and its proposed formalization, are discussed, and existing misconceptions are clarified. (shrink)

Theory of mind refers to the human capacity for reasoning about others’ mental states based on observations of their actions and unfolding events. This type of reasoning is notorious in the cognitive science literature for its presumed computational intractability. A possible reason could be that it may involve higher-order thinking. To investigate this we formalize theory of mind reasoning as updating of beliefs about beliefs using dynamic epistemic logic, as this formalism allows to parameterize ‘order of thinking.’ We prove that (...) theory of mind reasoning, so formalized, indeed is intractable. Using parameterized complexity we prove, however, that the ‘order parameter’ is not a source of intractability. We furthermore consider a set of alternative parameters and investigate which of them are sources of intractability. We discuss the implications of these results for the understanding of theory of mind. (shrink)

Posner & Raichle (1994) is a nice addition to the Scientific American Library and the average reader will both enjoy the book and learn a great deal. As an activeresearcher, however, I find the book disappointing in many respects. My two major disappointments are in the illusion of computation that is created throughout the volume and in the inadequate perspective of the presentation on visual attention.

We examine the verification of simple quantifiers in natural language from a computational model perspective. We refer to previous neuropsychological investigations of the same problem and suggest extending their experimental setting. Moreover, we give some direct empirical evidence linking computational complexity predictions with cognitive reality.<br>In the empirical study we compare time needed for understanding different types of quantifiers. We show that the computational distinction between quantifiers recognized by finite-automata and push-down automata is psychologically relevant. Our research improves upon hypothesis and (...) explanatory power of recent neuroimaging studies as well as provides<br>evidence. (shrink)

The authors ofImages of the Mindhave made a significant contribution to our understanding of the brain through imaging technology. The book is well written, timely, beautifully illustrated and conveys a sense of history. It will appeal to alay audience as well as a professional audience.

There are methodological problems with the new techniques reviewed by Posner & Raichle. Some brain mechanisms are not detected by the temporal and spatial resolution. Questions are also raised by the stimulation paradigms.

Images of mindsuperbly summarizes work on cognitive neuroscienee using PET scanning. Some of the data emphasized suggests that parietal cortex is involved in the disengagement of attention. We have discovered neurons in awake monkeys which could perform this function. Another point of emphasis is the concept of neutral cues. Although an appealing concept, it is extremely difficult to define what is actually neutral.

This volume explores how functional brain imaging techniques like positron emission tomography have influenced cognitive studies. The first chapter outlines efforts to relate human thought and cognition in terms of great books from the late 1800s through the present. Chapter 2 describes mental operations as they are measured in cognitive science studies. It develops a framework for relating mental operations to activity in nerve cells. In Chapter 3, the PET method is reviewed and studies are presented that use PET to (...) map the striate cortex and to activate extrastriate motion, color, and form areas. Chapter 4 shows how top down processes involving attention can lead to activation of these same areas in the detection of targets, visual search, and visual imagery. This chapter reveals complex networks of activations. Chapters 5 and 6 deal with the presentation of words. Chapter 5 illustrates PET studies of the anatomy of visual word processing and shows how the circuitry used for generating novel uses of words changes as the task becomes automated. Chapter 6 applies high density electrical recording to explore these activations in real time and to show how a constant anatomy can be reprogrammed by task instructions to produce and perform different cognitive tasks. Chapter 7 shows how studies of brain lesions and PET converge on common networks underlying attentional functions such as visual orienting, target detection, and maintenance of the alert state. Chapters 8 and 9 apply the network approach to examine normal development of attention in infants and pathological conditions resulting from brain damage, and psychiatric pathologies of depression, schizophrenia, and attention deficit disorder. In Chapter 10, new developments such as functional MRI are discussed in terms of future developments and integration of cognitive neuroscience. (shrink)

We divided the many diverse comments on our book into categories. These are: theory, scope and goals of our project, methods, comments on specific anatomical areas, the concept of attention, consciousness and cognitive control, and finally other issues. Although many of the points of the critics are certainly well taken, we believe studies that have emerged since our book provide strong evidence that the general approach taken in our book is now yielding important new data on the relation of cognitive (...) processes to underlying brain activity. (shrink)

PET studies in domains like vision and attention have been successful because the experiments are the product of highly articulated theories. In contrast, the results of PET studies investigating language processing are difficult to interpret. We suggest that this difficulty is due to the more tentative connection of these experiments with the insights of psycholinguistics and linguistic theory.

In Posner & Raichle's (1994) book, two essential and strictly related limitations of cognitive neurophysiology are not sufficiently enhanced: (1) The problem of “coding,” namely the capability of a natural brain to redefine its own “basic symbols” as a function of a changing environment; (2) the inadequacy of a Hebbian rule to reckon with complex computational problems such as those solved by real brains.

In computational complexity theory, decision problems are divided into complexity classes based on the amount of computational resources it takes for algorithms to solve them. In theoretical computer science, it is commonly accepted that only functions for solving problems in the complexity class P, solvable by a deterministic Turing machine in polynomial time, are considered to be tractable. In cognitive science and philosophy, this tractability result has been used to argue that only functions in P can feasibly work as computational (...) models of human cognitive capacities. One interesting area of computational complexity theory is descriptive complexity, which connects the expressive strength of systems of logic with the computational complexity classes. In descriptive complexity theory, it is established that only first-order systems are connected to P, or one of its subclasses. Consequently, second-order systems of logic are considered to be computationally intractable, and may therefore seem to be unfit to model human cognitive capacities. This would be problematic when we think of the role of logic as the foundations of mathematics. In order to express many important mathematical concepts and systematically prove theorems involving them, we need to have a system of logic stronger than classical first-order logic. But if such a system is considered to be intractable, it means that the logical foundation of mathematics can be prohibitively complex for human cognition. In this paper I will argue, however, that this problem is the result of an unjustified direct use of computational complexity classes in cognitive modelling. Placing my account in the recent literature on the topic, I argue that the problem can be solved by considering computational complexity for humanly relevant problem solving algorithms and input sizes. (shrink)

Pictures of normal brain activity during human thought can be worth a great deal. Electrophysiology and functional neuroimaging together allow both temporal and spatial dimensions of neurocognitive functions to be explored. Although these techniqueshave their limitations, the Cognitive Neuroscience approach is well-suited to pursuing questions about how words are perceived, understood, and remembered.

Posner & Raichle's book is a superbly presented and wellwritten overview of a fast-developing and important field in contemporary neuroscience. It suffers from being an overview, however, because it does not go into sufficient detail or depth in many of the issues that it raises. It also neglects many other important areas of current research, for example, technical advances in other areas, learning and memory, and lesion analysis of brain function.

Posner & Raichle's (1994) book is a fascinating and readable account of the studies the authors have conducted on the localization of cognitive functions in the brain mainly using PET and EEC evoked potential methods. Our criticism concerns the underrepresentation of some imaging techniques (magnetoencephalography) and some forms of brain activity (spontaneous activity). Furthermore, the book leaves the reader with the impression that the brain only responds to external events.

This is an excellent book but it lacks a detailed presentation and formulation of images of memory. Positron emission tomography (PET) findings sometimes raise more enigmatic questions than they answer, with differences between studies and differences with established lesion evidence. Perhaps the book could have been more critical in its analysis of these enigmas, covering more of the basic issues and assumptions underlying PET research.

Posner & Raichle illustrate how neuroimaging blends profitably with neuropsychology and electrophysiology to advance cognitive theory. Recognizing that there are limitations to each of these techniques, we nonetheless argue that their confluence has fundamentally changed the way cognitive psychologists think about problems of the mind.

It is argued that current neuroimaging studies can provide useful constraints for the construction of models of cognition, and that these studies should be guided by cognitive models. A numberof challenges for a successful cross-fertilization between “mind mappers” and cognitive modelers are discussed in the light of current research on word recognition.

Posner & Raichle'sImages of mindis an excellent educational book and very well written. Some flaws as a scientific publication are: (a) the accuracy of the linear subtraction method used in PET is subject to scrutiny by further research at finer spatial-temporal resolutions; (b) lack of accuracy of the experimental paradigm used for EEG complementary studies.

The subtraction and covariance paradigms are two analytic techniques used with functional neuroimaging data. The first assumes that a brain region participating in a task should show altered neural activity (relative to a control task). The second assumes that tasks are mediated by networks of interacting regions.Images of mindattempts to link results from the subtraction paradigm with a network interpretation that could have been more explicitly done using the covariance paradigm.

The authors ofImages of mindhave been highly successful in unravelling the neural basis of complex brain functions. Their emphasis on top-down processingin experimental neuroscience is especially important and, it is hoped, influential. Tracking brain activation accurately botli in space and in time would benefit from studiesofindividual subjects without relying on grand average data.

PET detects changes in metabolism between task periods and is thus insensitive to areas that are activated during all or most of cognition. Depth-recorded, evokedpotentials indicate that many multimodal and limbic cortical areas may be activated during most cognitive tasks. Thus, PET may be insensitive to some core processes of awareness that are difficult to eliminate from the control periods.

On the basis of neuroiinaging studies, Posner & Raichle summarily report that the prefrontal cortex is involved in executive functioning and attention. In contrast to that superficial view, we briefly describe a testable model of the kinds of representations that are stored in prefrontal cortex, which, when activated, are expressed via plans, actions, thematic knowledge, and schemas.

Research reported by Posner & Raichle may be usefully applied to the rehabilitation of persons with brain damage. Their findings are related to the “dual premotorsystems hypothesis” that reciprocally interactive medial and lateral brain systems are involved in attention and learning. Recent studies show that “brain healing” occurs through dynamic reorganization involving attentional networks postulated by Posner & Raichle.

Images of mindis an exciting book, well-written and wellorganized, but many of the connections the authors draw between PET scan results and more general psychological issues are somewhat strained.