Cognitive science is the interdisciplinary, scientific study of the mind and its processes with input from linguistics, psychology, neuroscience, philosophy, computer science/artificial intelligence, and anthropology. It examines the nature, the tasks, and the functions of cognition. Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology. The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. One of the fundamental concepts of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."
Phonetics is a branch of linguistics that studies how humans produce and perceive sounds, or in the case of sign languages, the equivalent aspects of sign. Linguists who specialize in studying the physical properties of speech are phoneticians. The field of phonetics is traditionally divided into three sub-disciplines based on the research questions involved such as how humans plan and execute movements to produce speech, how various movements affect the properties of the resulting sound, or how humans convert sound waves to linguistic information. Traditionally, the minimal linguistic unit of phonetics is the phone—a speech sound in a language which differs from the phonological unit of phoneme; the phoneme is an abstract categorization of phones, and it is also defined as the smallest unit that discerns meaning between sounds in any given language.
Perception is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information or environment. All perception involves signals that go through the nervous system, which in turn result from physical or chemical stimulation of the sensory system. Vision involves light striking the retina of the eye; smell is mediated by odor molecules; and hearing involves pressure waves.
In psychology, parallel processing is the ability of the brain to simultaneously process incoming stimuli of differing quality. Parallel processing is associated with the visual system in that the brain divides what it sees into four components: color, motion, shape, and depth. These are individually analyzed and then compared to stored memories, which helps the brain identify what you are viewing. The brain then combines all of these into the field of view that is then seen and comprehended. This is a continual and seamless operation. For example, if one is standing between two different groups of people who are simultaneously carrying on two different conversations, one may be able to pick up only some information of both conversations at the same time. Parallel processing has been linked, by some experimental psychologists, to the stroop effect. In the stroop effect, an inability to attend to all stimuli is seen through people's selective attention.
Psycholinguistics or psychology of language is the study of the interrelation between linguistic factors and psychological aspects. The discipline is mainly concerned with the mechanisms by which language is processed and represented in the mind and brain; that is, the psychological and neurobiological factors that enable humans to acquire, use, comprehend, and produce language.
Connectionism is the name of an approach to the study of human mental processes and cognition that utilizes mathematical models known as connectionist networks or artificial neural networks. Connectionism has had many 'waves' since its beginnings.
A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Multiple neural circuits interconnect with one another to form large scale brain networks.
In cognitive psychology, the word superiority effect (WSE) refers to the phenomenon that people have better recognition of letters presented within words as compared to isolated letters and to letters presented within nonword strings. Studies have also found a WSE when letter identification within words is compared to letter identification within pseudowords and pseudohomophones.
Speech perception is the process by which the sounds of language are heard, interpreted, and understood. The study of speech perception is closely linked to the fields of phonology and phonetics in linguistics and cognitive psychology and perception in psychology. Research in speech perception seeks to understand how human listeners recognize speech sounds and use this information to understand spoken language. Speech perception research has applications in building computer systems that can recognize speech, in improving speech recognition for hearing- and language-impaired listeners, and in foreign-language teaching.
Language production is the production of spoken or written language. In psycholinguistics, it describes all of the stages between having a concept to express and translating that concept into linguistic forms. These stages have been described in two types of processing models: the lexical access models and the serial models. Through these models, psycholinguists can look into how speeches are produced in different ways, such as when the speaker is bilingual. Psycholinguists learn more about these models and different kinds of speech by using language production research methods that include collecting speech errors and elicited production tasks.
Sentence processing takes place whenever a reader or listener processes a language utterance, either in isolation or in the context of a conversation or a text. Many studies of the human language comprehension process have focused on reading of single utterances (sentences) without context. Extensive research has shown that language comprehension is affected by context preceding a given utterance as well as many other factors.
The logogen model of 1969 is a model of speech recognition that uses units called "logogens" to explain how humans comprehend spoken or written words. Logogens are a vast number of specialized recognition units, each able to recognize one specific word. This model provides for the effects of context on word recognition.
The cohort model in psycholinguistics and neurolinguistics is a model of lexical retrieval first proposed by William Marslen-Wilson in the late 1970s. It attempts to describe how visual or auditory input is mapped onto a word in a hearer's lexicon. According to the model, when a person hears speech segments real-time, each speech segment "activates" every word in the lexicon that begins with that segment, and as more segments are added, more words are ruled out, until only one word is left that still matches the input.
Time delay neural network (TDNN) is a multilayer artificial neural network architecture whose purpose is to 1) classify patterns with shift-invariance, and 2) model context at each layer of the network.
Word recognition, according to Literacy Information and Communication System (LINCS) is "the ability of a reader to recognize written words correctly and virtually effortlessly". It is sometimes referred to as "isolated word recognition" because it involves a reader's ability to recognize words individually from a list without needing similar words for contextual help. LINCS continues to say that "rapid and effortless word recognition is the main component of fluent reading" and explains that these skills can be improved by "practic[ing] with flashcards, lists, and word grids".
Statistical language acquisition, a branch of developmental psycholinguistics, studies the process by which humans develop the ability to perceive, produce, comprehend, and communicate with natural language in all of its aspects through the use of general learning mechanisms operating on statistical patterns in the linguistic input. Statistical learning acquisition claims that infants' language-learning is based on pattern perception rather than an innate biological grammar. Several statistical elements such as frequency of words, frequent frames, phonotactic patterns and other regularities provide information on language structure and meaning for facilitation of language acquisition.
The dual-route theory of reading aloud was first described in the early 1970s. This theory suggests that two separate mental mechanisms, or cognitive routes, are involved in reading aloud, with output of both mechanisms contributing to the pronunciation of a written stimulus.
Catastrophic interference, also known as catastrophic forgetting, is the tendency of an artificial neural network to abruptly and drastically forget previously learned information upon learning new information. Neural networks are an important part of the network approach and connectionist approach to cognitive science. With these networks, human capabilities such as memory and learning can be modeled using computer simulations.
Embodied bilingual language, also known as L2 embodiment, is the idea that people mentally simulate their actions, perceptions, and emotions when speaking and understanding a second language (L2) as with their first language (L1). It is closely related to embodied cognition and embodied language processing, both of which only refer to native language thinking and speaking. An example of embodied bilingual language would be situation in which a L1 English speaker learning Spanish as a second language hears the word rápido ("fast") in Spanish while taking notes and then proceeds to take notes more quickly.
In neuroscience, predictive coding is a theory of brain function which postulates that the brain is constantly generating and updating a "mental model" of the environment. According to the theory, such a mental model is used to predict input signals from the senses that are then compared with the actual input signals from those senses. With the rising popularity of representation learning, the theory is being actively pursued and applied in machine learning and related fields.
