Evidence affirms that aesthetic engagement patterns our movements, often with us barely aware. This invites an examination of pre-reflective engagement within cities and also aesthetic experience as a form of the pre-reflective. The invitation is amplified because design has political implications. For instance, it can draw people in or exclude them by establishing implicitly recognized public-private boundaries. The Value Sensitive Design school, which holds that artifacts embody ethical and political values, stresses some of this. But while emphasizing that design embodies (...) implicit values, research in this field lacks sustained attention to largely unconscious background biases or values, rooted in cultural attitudes and personal interests, that lead theorists and planners—often too narrowly—to promote design organized around specific values such as defensibility. In examining these points, I draw on J. J. Gibson, a central figure for some writing on aesthetics and cities, and whom pragmatists and phenomenologists in turn influenced. Taking a cue from pragmatists in particular, I argue Gibson’s perceptual theory of affordances entails a theory of values, meaning our perception and therewith movements are inherently value-based. I advocate design that accounts for relatively constantly held values such as safety, while also handling the vast pluralism that exists and not crushing the aesthetic vibrancy of city life. (shrink)

Empirical evidence is reviewed indicating that the extraordinary aspects of the human mind are due to our species’ ability to go beyond simple “dyadic associations” and to process the relations among three items of information simultaneously. Classic explanations of the “triadic” nature of human skills have been advocated by various scholars in the context of the evolution of human cognition. Here I summarize the core processes as found in (i) the syntax of language, (ii) tool-usage, and (iii) joint attention. I (...) then review the triadic foundations of two perceptual phenomena of great importance in human aesthetics: (iv) harmony perception and (v) pictorial depth perception. In all five subfields of human psychology, most previous work has emphasized the recursive, hierarchical complexity of such “higher cognition”, but a reductionist approach indicates that the core mechanisms are triadic. It is concluded that the cognitive skills traditionally considered to be “uniquely” human require three-way associational processing that most non-Primate animal species find difficult or impossible, but all members of Homo sapiens – regardless of small individual and cultural differences – find easy and inherently intriguing. (shrink)

Although our subjective impression is of a richly detailed visual world, numerous empirical results suggest that the amount of visual information observers can perceive and remember at any given moment is limited. How can our subjective impressions be reconciled with these objective observations? Here, we answer this question by arguing that, although we see more than the handful of objects, claimed by prominent models of visual attention and working memory, we still see far less than we think we do. Taken (...) together, we argue that these considerations resolve the apparent conflict between our subjective impressions and empirical data on visual capacity, while also illuminating the nature of the representations underlying perceptual experience. (shrink)

(2013). Two facets of cognitive control in analogical mapping: The role of semantic interference resolution andgoal-driven structure selection. Thinking & Reasoning. ???aop.label???

Spearman’s Law of Diminishing Returns holds that correlation between general /fluid intelligence factor and other cognitive abilities weakens with increasing ability level. Thus, cognitive processing in low ability people is most strongly saturated by g/gf, whereas processing in high ability people depends less on g/gf. Numerous studies demonstrated that low g is more strongly correlated with crystallized intelligence/creativity/processing speed than is high g, however no study tested an analogous effect in the case of working memory. Our aim was to investigate (...) SLODR for the relationship between Gf and WM capacity, using a large data set from our own previous studies. We tested alternative regression models separately for three types of WM tasks that tapped short-term memory storage, attention control, and relational integration, respectively. No significant SLODR effect was found for any of these tasks. Each task shared with Gf virtually the same amount of variance in the case of low- and high-ability people. This result suggests that Gf and WM rely on one and the same cognitive mechanism. (shrink)

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the brain deal successfully with the continual deluge of linguistic input? We argue that, to deal with this “Now-or-Never” bottleneck, the brain must compress and recode linguistic input as rapidly as possible. This observation has strong implications for the nature of language processing: (1) the language system must “eagerly” recode and compress linguistic input; (2) as the bottleneck recurs at each new representational level, the language system must build (...) a multilevel linguistic representation; and (3) the language system must deploy all available information predictively to ensure that local linguistic ambiguities are dealt with “Right-First-Time”; once the original input is lost, there is no way for the language system to recover. This is “Chunk-and-Pass” processing. Similarly, language learning must also occur in the here and now, which implies that language acquisition is learning to process, rather than inducing, a grammar. Moreover, this perspective provides a cognitive foundation for grammaticalization and other aspects of language change. Chunk-and-Pass processing also helps explain a variety of core properties of language, including its multilevel representational structure and duality of patterning. This approach promises to create a direct relationship between psycholinguistics and linguistic theory. More generally, we outline a framework within which to integrate often disconnected inquiries into language processing, language acquisition, and language change and evolution. (shrink)

In this review article, Christiansen provides a historical perspective on the two research traditions, implicit learning and statistical learning, thus nicely setting the scene for this special issue of Topics in Cognitive Science. In this “tale of two literatures”, he first traces the history of both literatures before sketching a framework that provides a basis for understanding implicit learning and statistical learning as a unified phenomenon.

A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the (...) network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall. (shrink)

Individual differences in the strategies that control sequential behavior were investigated in an experiment in which participants memorized sentences and then wrote them by hand, in a non‐cursive style. Thirty‐two participants each wrote eight sentences, which had hierarchical structures with five levels. The dataset included over 31,000 letters. Despite the deliberately constrained nature of the task and stimuli, 23 patterns of behavior were identified from the durations of pauses that occurred before the inscription of letters at four chunk levels, spanning (...) letters, words, phrases, and sentences. A critical path task analytic model, Graphical Production of Memorized Sentences (GPoMS), shows that the control of writing relies on cues that continuously switch between motor actions and chunk retrievals in a just‐in‐time fashion at the level of letter information. GPoMS explains the individual differences in terms of variants of a motor production mechanism and variants of a chunk retrieval mechanism, which involve varying degrees of parallelism between cognitive actions and motor actions. A graphical technique for constructing GPoMS models was developed that enabled the estimation of ongoing working memory demands during production. (shrink)

Working memory has been shown to be strongly related to fluid intelligence; however, our goal is to shed further light on the process of information compression in working memory as a determining factor of fluid intelligence. Our main hypothesis was that compression in working memory is an excellent indicator for studying the relationship between working-memory capacity and fluid intelligence because both depend on the optimization of storage capacity. Compressibility of memoranda was estimated using an algorithmic complexity metric. The results showed (...) that compressibility can be used to predict working-memory performance and that fluid intelligence is well predicted by the ability to compress information. We conclude that the ability to compress information in working memory is the reason why both manipulation and retention of information are linked to intelligence. This result offers a new concept of intelligence based on the idea that compression and intelligence are equivalent problems. (shrink)

If human language must be squeezed through a narrow cognitive bottleneck, what are the implications for language processing, acquisition, change, and structure? In our target article, we suggested that the implications are far-reaching and form the basis of an integrated account of many apparently unconnected aspects of language and language processing, as well as suggesting revision of many existing theoretical accounts. With some exceptions, commentators were generally supportive both of the existence of the bottleneck and its potential implications. Many commentators (...) suggested additional theoretical and linguistic nuances and extensions, links with prior work, and relevant computational and neuroscientific considerations; some argued for related but distinct viewpoints; a few, though, felt traditional perspectives were being abandoned too readily. Our response attempts to build on the many suggestions raised by the commentators and to engage constructively with challenges to our approach. (shrink)

This article challenges Block's ‘overflow argument’ for the conclusion that phenomenal consciousness and access-consciousness are distinct. It shows that the data can be explained just as well in terms of a distinction between contents that are made globally accessible through bottom–up sensory stimulation and those that are sustained and made available in working memory through top-down attention.

In the 1980s and 1990s, there was a major theoretical debate in the memory domain regarding the multiple memory systems and processing modes frameworks. The components of processing framework argued for a middle ground: Instead of neatly divided memory systems or processing modes, this framework proposed the existence of numerous processing components that are recruited in different combinations by memory tasks and yield complex patterns of associations and dissociations. Because behavioral evidence was not sufficient to decide among these three frameworks, (...) the debate was largely abandoned. However, functional neuroimaging evidence accumulated during the last two decades resolves the stalemate, because this evidence is more consistent with the components framework than with the other two frameworks. For example, functional neuroimaging evidence shows that brain regions attributed to one memory system can contribute to tasks associated with other memory systems and that brain regions attributed to the same processing mode (perceptual or conceptual) can be dissociated from each other. Functional neuroimaging evidence suggests that memory processes are supported by transient interactions between a few regions called process-specific alliances. These conceptual developments are an example of how functional neuroimaging can contribute to theoretical debates in cognitive psychology. (shrink)

In contrast to Constructivist Views, which construe perceptual cognition as an essentially reconstructive process, this article recommends the Deictic View, which grounds perception in perceptual-demonstrative reference and the use of deictic tracking strategies for acquiring and updating knowledge about individuals. The view raises the problem of how sensory-motor tracking connects to epistemic and integrated forms of tracking. To study the strategies used to solve this problem, we report a study of the ability to track distal individuals when only their directions (...) can be perceived and not their locations. We introduce a new experimental paradigm named the 'Modified Traveling Salesman Problem' (MTSP), which requires subjects to visit n invisible targets in a 2D display once each. Surprisingly, subjects are competent at this task for up to 10 targets. We consider two types of tracking strategies that subjects might use: 'location-based' strategies and 'deictic direction-based' strategies. A number of observations suggest that subjects used the latter, at least for larger numbers of targets. We hypothesize that subjects used perceptual-demonstrative reference and deictic strategies (i) to perform the sensory-motor tracking of directional segments, (ii) to bind the segments with their updated status in the task, and (iii) to perform the epistemic tracking of invisible targets by means of perception-based inferences. (shrink)

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting (...) brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data. (shrink)

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN–human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in (...) the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN–human correspondences in vision and other domains of cognition. We explore all these issues in this response. (shrink)

How can we disentangle the neural basis of phenomenal consciousness from the neural machinery of the cognitive access that underlies reports of phenomenal consciousness? We can see the problem in stark form if we ask how we could tell whether representations inside a Fodorian module are phenomenally conscious. The methodology would seem straightforward: find the neural natural kinds that are the basis of phenomenal consciousness in clear cases when subjects are completely confident and we have no reason to doubt their (...) authority, and look to see whether those neural natural kinds exist within Fodorian modules. But a puzzle arises: do we include the machinery underlying reportability within the neural natural kinds of the clear cases? If the answer is ‘Yes’, then there can be no phenomenally conscious representations in Fodorian modules. But how can we know if the answer is ‘Yes’? The suggested methodology requires an answer to the question it was supposed to answer! The paper argues for an abstract solution to the problem and exhibits a source of empirical data that is relevant, data that show that in a certain sense phenomenal consciousness overflows cognitive accessibility. The paper argues that we can find a neural realizer of this overflow if assume that the neural basis of phenomenal consciousness does not include the neural basis of cognitive accessibility and that this assumption is justified by the explanations it allows. (shrink)

This article concerns the interplay between two issues that involve both philosophy and neuroscience: whether the content of phenomenal consciousness is 'rich' or 'sparse', whether phenomenal consciousness goes beyond cognitive access, and how it would be possible for there to be evidence one way or the other.

A novel explanation of belief bias in relational reasoning is presented based on the role of working memory and retrieval in deductive reasoning, and the influence of prior knowledge on this process. It is proposed that belief bias is caused by the believability of a conclusion in working memory which influences its activation level, determining its likelihood of retrieval and therefore its effect on the reasoning process. This theory explores two main influences of belief on the activation levels of these (...) conclusions. First, believable conclusions have higher activation levels and so are more likely to be recalled during the evaluation of reasoning problems than unbelievable conclusions, and therefore, they have a greater influence on the reasoning process. Secondly, prior beliefs about the conclusion have a base level of activation and may be retrieved when logically irrelevant, influencing the evaluation of the problem. The theory of activation and memory is derived from the Atomic Components of Thought-Rational (ACT-R) cognitive architecture and so this account is formalized in an ACT-R cognitive model. Two experiments were conducted to test predictions of this model. Experiment 1 tested strength of belief and Experiment 2 tested the impact of a concurrent working memory load. Both of these manipulations increased the main effect of belief overall and in particular raised belief-based responding in indeterminately invalid problems. These effects support the idea that the activation level of conclusions formed during reasoning influences belief bias. This theory adds to current explanations of belief bias by providing a detailed specification of the role of working memory and how it is influenced by prior knowledge. (shrink)