The goal of perceptual systems is to allow organisms to adaptively respond to ecologically relevant stimuli. Because all perceptual inputs are ambiguous, perception needs to rely on prior knowledge accumulated over evolutionary and developmental time to turn sensory energy into information useful for guiding behavior. It remains controversial whether the guidance of perception extends to cognitive states or is locked up in a “cognitively impenetrable” part of perception. I argue that expectations, knowledge, and task demands can shape perception at multiple (...) levels, leaving no part untouched. The position advocated here is broadly consistent with the notion that perceptual systems strive to minimize prediction error en route to globally optimal solutions :181–204, 2013). On this view, penetrability should be expected whenever constraining lower-level processes by higher level knowledge is minimizes global prediction error. Just as Fodor feared cognitive penetration of perception threatens theory-neutral observation and the distinction between observation and inference. However, because theories themselves are constrained by the task of minimizing prediction error, theory-laden observation turns out to be superior to theory-free observation in turning sensory energy into useful information. (shrink)

Can what we know change what we see? Does language affect cognition and perception? The last few years have seen increased attention to these seemingly disparate questions, but with little theoretical advance. We argue that substantial clarity can be gained by considering these questions through the lens of predictive processing, a framework in which mental representations—from the perceptual to the cognitive—reflect an interplay between downward-flowing predictions and upward-flowing sensory signals. This framework provides a parsimonious account of how what we know (...) ought to change what we see and helps us understand how a putatively high-level trait such as language can impact putatively low-level processes such as perception. Within this framework, language begins to take on a surprisingly central role in cognition by providing a uniquely focused and flexible means of constructing predictions against which sensory signals can be evaluated. Predictive processing thus provides a plausible mechanism for many of the reported effects of language on perception, thought, and action, and new insights on how and when speakers of different languages construct the same “reality” in alternate ways. (shrink)

It is often assumed that how we talk about the world matters a great deal. This is one reason why conceptual engineers seek to improve our linguistic practices by advocating novel uses of our words, or by inventing new ones altogether. A core idea shared by conceptual engineers is that by changing our language in this way, we can reap all sorts of cognitive and practical benefits, such as improving our theorizing, combating hermeneutical injustice, or promoting social emancipation. But how (...) do changes at the linguistic level translate into any of these worthwhile benefits? In this paper, we propose the nameability account as a novel answer to this question. More specifically, we argue that what linguistic resources are readily available to us directly affects our cognitive performance on various categorization‐related tasks. Consequently, our performance on such tasks can be improved by making controlled changes to our linguistic resources. We argue that this account supports and extends recent motivations for conceptual engineering, as categorization plays an important role in both theoretical and practical contexts. (shrink)

Many animals can be trained to perform novel tasks. People, too, can be trained, but sometime in early childhood people transition from being trainable to something qualitatively more powerful—being programmable. We argue that such programmability constitutes a leap in the way that organisms learn, interact, and transmit knowledge, and that what facilitates or enables this programmability is the learning and use of language. We then examine how language programs the mind and argue that it does so through the manipulation of (...) embodied, sensorimotor representations. The role language plays in controlling mental representations offers important insights for understanding its origin and evolution. (shrink)

In addition to the many easily observable differences between people, there are also differences in people's subjective experiences that are harder to observe, and which, as a consequence, remain hidden. For example, people vary widely in how much visual imagery they experience. But those who cannot see in their mind's eye, tend to assume everyone is like them. Those who can, assume everyone else can as well. We argue that a study of such hidden phenomenal differences has much to teach (...) cognitive science. Uncovering and describing this variation (a search for unknown unknowns) may help predict otherwise puzzling differences in human behavior. The very existence of certain differences can also act as a stress test for some cognitive theories. Finally, studying hidden phenomenal differences is the first step toward understanding what kinds of environments may mask or unmask links between phenomenal experience and observable behavior. (shrink)

The very expertise with which psychologists wield their tools for achieving laboratory control may have had the unwelcome effect of blinding psychologists to the possibilities of discovering principles of behavior without conducting experiments. When creatively interrogated, a diverse range of large, real-world data sets provides powerful diagnostic tools for revealing principles of human judgment, perception, categorization, decision-making, language use, inference, problem solving, and representation. Examples of these data sets include patterns of website links, dictionaries, logs of group interactions, collections of (...) images and image tags, text corpora, history of financial transactions, trends in twitter tag usage and propagation, patents, consumer product sales, performance in high-stakes sporting events, dialect maps, and scientific citations. The goal of this issue is to present some exemplary case studies of mining naturally existing data sets to reveal important principles and phenomena in cognitive science, and to discuss some of the underlying issues involved with conducting traditional experiments, analyses of naturally occurring data, computational modeling, and the synthesis of all three methods. (shrink)

Some spoken words are iconic, exhibiting a resemblance between form and meaning. We used native speaker ratings to assess the iconicity of 3001 English words, analyzing their iconicity in relation to part-of-speech differences and differences between the sensory domain they relate to. First, we replicated previous findings showing that onomatopoeia and interjections were highest in iconicity, followed by verbs and adjectives, and then nouns and grammatical words. We further show that words with meanings related to the senses are more iconic (...) than words with abstract meanings. Moreover, iconicity is not distributed equally across sensory modalities: Auditory and tactile words tend to be more iconic than words denoting concepts related to taste, smell and sight. Last, we examined the relationship between iconicity and systematicity. We find that iconicity in English words is more strongly related to sensory meanings than systematicity. Altogether, our results shed light on the extent and distribution of iconicity in modern English. (shrink)

My reply to Macpherson begins by addressing whether it is effects of cognition on early vision or perceptual performance that I am interested in. I proceed to address Macpherson’s comments on evidence from cross-modal effects, interpretations of linguistic effects on image detection, evidence from illusions, and the usefulness of predictive coding for understanding cognitive penetration. By stressing the interactive and distributed nature of neural processing, I am committing to a collapse between perception and cognition. Following such a collapse, the very (...) question of whether cognition affects perception becomes ill-posed, but this may be for the best. (shrink)

To what extent do people attribute meanings to “nonsense” words? How general is such attribution of meaning? We used a set of words lacking conventional meanings to elicit drawings of made‐up creatures. Separate groups of participants rated the nonsense words and the drawings on several semantic dimensions and selected what name best corresponded to each creature. Despite lacking conventional meanings, “nonsense” words elicited a high level of consistency in the produced drawings. Meaning attributions made to nonsense words corresponded with meaning (...) attributions made by separate people to drawings that were inspired by the name. Naïve participants were able to recover the name that inspired the drawing with greater‐than‐chance accuracy. These results suggest that people make liberal and consistent use of non‐arbitrary relationships between forms and meanings.Open Research Badges This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the Open Science Framework at https://osf.io/8juyc/. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki. (shrink)

What makes a word easy to learn? Early‐learned words are frequent and tend to name concrete referents. But words typically do not occur in isolation. Some words are predictable from their contexts; others are less so. Here, we investigate whether predictability relates to when children start producing different words (age of acquisition; AoA). We operationalized predictability in terms of a word's surprisal in child‐directed speech, computed using n‐gram and long‐short‐term‐memory (LSTM) language models. Predictability derived from LSTMs was generally a better (...) predictor than predictability derived from n‐gram models. Across five languages, average surprisal was positively correlated with the AoA of predicates and function words but not nouns. Controlling for concreteness and word frequency, more predictable predicates and function words were learned earlier. Differences in predictability between languages were associated with cross‐linguistic differences in AoA: the same word (when it was a predicate) was produced earlier in languages where the word was more predictable. (shrink)

People believe that perception is reliable and that what they perceive reflects objective reality. On this view, we perceive a red circle because there is something out there that is a red circle. It is also commonly believed that perceptual reliability is threatened if what we see is allowed to be influenced by what we know or expect. I argue that although human perception is often highly consistent and stable, it is difficult to evaluate its reliability because when it comes (...) to perception, it is unclear how one could establish a fact of the matter. An alternative to thinking of perception as being in the business of truth, is thinking of it as being in the business of transducing sensory energy into a form useful for guiding adaptive behavior. On this position, perception ought to be richly influenced by some types of knowledge insofar as this knowledge can aid in the construction of useful representations from sensory input. (shrink)

George Lakoff (2016) discusses how emotion metaphors reflect the discrete bodily states associated with each emotion. The analysis raises questions about the context for and frequency of use of emotion metaphors and, indeed, emotion labels (e.g., “angry”), per se. An assumption implicit to most theories of emotion is that emotion language is just another channel through which people express ongoing emotion states. Drawing from recent evidence that labeling ongoing emotions reduces their intensity, we propose that a primary function of emotion (...) language is regulatory rather than expressive. (shrink)

The target article provides a convincing argument that nonhuman animals cannot process role-governed rules, relational schemas, and so on, in a human-like fashion. However, actual human performance is often more similar to that of nonhuman animals than Penn et al. admit. The kind of rule-governed performance the authors take for granted may rely to a substantial degree on language on external symbol systems such as those provided by language and culture.

The question of whether perception can be penetrated by cognition is in the limelight again. The reason this question keeps coming up is that there is so much at stake: Is it possible to have theory-neutral observation? Is it possible to study perception without recourse to expectations, context, and beliefs? What are the boundaries between perception, memory, and inference (and do they even exist)? Are findings from neuroscience that paint a picture of perception as an inherently bidirectional and interactive process (...) relevant for understanding the relationship between cognition and perception? We have assembled a group of philosophers and psychologists who have been considering the thesis of cognitive (im)penetrability in light of these questions (Abdel Rahman & Sommer, 2008; Goldstone, Landy, & Brunel, 2011; Lupyan, Thompson-Schill, & Swingley, 2010; Macpherson, 2012; Stokes, 2011). Rather than rehashing previous arguments which appear, in retrospect, to have been somewhat ill-posed (Pylyshyn, 1999), this symposium will present a thesis of cognitive (im)penetrability that is at once philosophically satisfying, empirically testable, and relevant to the questions that cognitive scientists find most interesting. (shrink)

There are towns in which language-of-thought (LoT) is the best game. But do we live in one? I go through three properties that characterize the LoT hypothesis: Discrete constituents, role-filler independence, and logical operators, and argue that in each case predictions from the LoT hypothesis are a poor fit to actual human cognition. As a hypothesis of what human cognition ought to be like, LoT departs from empirical reality.

We argue that the Rules-Similarity continuum is only a useful formalism for particular, isolated tasks and must rest on the assumption that representations formed during a particular task are independent of other tasks. We show this to be an unrealistic conjecture. We additionally point out that describing categorization as selective weighing and abstracting of features misses the important step of discovering what the possible features are.

Cognitive scientists and psychometricians are unaccustomed to thinking about culture, often treating their measures – memory, vocabulary, intelligence – as natural kinds. Relying on these measures, behavioral geneticists likewise seem to not wonder about their origin and cultural provenance. I argue that complex human traits – the sort we are most interested in measuring – are cultural products. We can measure them and their heritability, but to conclude that what we have measured is unbound to a time and place is (...) hubris. (shrink)

Different developmental anomalies produce contrasting deficits in a single, integrated system. In a network that inflects regular and exception verbs correctly, a disproportionate deficit with exceptions occurs if connections are deleted, whereas a disproportionate deficit with regulars occurs when an auditory deficit impairs perception of the regular inflection. In general, contrasting deficits do not license the inference of underlying modularity.

We agree with many theoretical points presented by Rogers & McClelland (R&M), especially the role of domain-general learning of coherent covariation. Nonetheless, we argue that in failing to be informed by key aspects of development, including the role of labels on categorization and the emergence of constraints on learning, their model fails to capture important features of the ontogeny of knowledge.