92,332 research outputs found
A Language for Human Action
Human-centered computing (HCC) is centered on humans and what they do,
i.e. human actions. Thus, developing an infrastructure for HCC requires
understanding human action, at some level of detail. We need to be able to
talk about actions, synthesize actions, recognize actions, manipulate
actions, imitate actions, imagine and predict actions. How could we
achieve this in a principled fashion? This paper proposes that the space
of human actions has a linguistic structure. This is a sensory-motor space
consisting of the evolution of the joint angles of the human body in
movement. The space of human activity has its own phonemes, morphemes, and
sentences. We present a Human Activity Language (HAL) for symbolic
non-arbitrary representation of visual and motor information. In
phonology, we define atomic segments (kinetemes) that are used to compose
human activity. In morphology, we propose parallel learning to incorporate
associative learning into a language inference approach. Parallel learning
solves the problem of overgeneralization and is effective in identifying
the active joints and motion patterns in a particular action. In syntax,
we point out some of the basic constraints for sentence formation.
Finally, we demonstrate this linguistic framework on a praxicon of 200
human actions (motion capture data obtained by a suit) and we discuss the
implications of HAL on HCC
On staying grounded and avoiding Quixotic dead ends
The 15 articles in this special issue on The Representation of Concepts illustrate the rich variety of theoretical positions and supporting research that characterize the area. Although much agreement exists among contributors, much disagreement exists as well, especially about the roles of grounding and abstraction in conceptual processing. I first review theoretical approaches raised in these articles that I believe are Quixotic dead ends, namely, approaches that are principled and inspired but likely to fail. In the process, I review various theories of amodal symbols, their distortions of grounded theories, and fallacies in the evidence used to support them. Incorporating further contributions across articles, I then sketch a theoretical approach that I believe is likely to be successful, which includes grounding, abstraction, flexibility, explaining classic conceptual phenomena, and making contact with real-world situations. This account further proposes that (1) a key element of grounding is neural reuse, (2) abstraction takes the forms of multimodal compression, distilled abstraction, and distributed linguistic representation (but not amodal symbols), and (3) flexible context-dependent representations are a hallmark of conceptual processing
Creativity and the Brain
Neurocognitive approach to higher cognitive functions that bridges the gap between psychological and neural level of description is introduced. Relevant facts about the brain, working memory and representation of symbols in the brain are summarized. Putative brain processes responsible for problem solving, intuition, skill learning and automatization are described. The role of non-dominant brain hemisphere in solving problems requiring insight is conjectured. Two factors seem to be essential for creativity: imagination constrained by experience, and filtering that selects most interesting solutions. Experiments with paired words association are analyzed in details and evidence for stochastic resonance effects is found. Brain activity in the process of invention of novel words is proposed as the simplest way to understand creativity using experimental and computational means. Perspectives on computational models of creativity are discussed
Neural Dynamics of Autistic Behaviors: Cognitive, Emotional, and Timing Substrates
What brain mechanisms underlie autism and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the iSTART model, which proposes how cognitive, emotional, timing, and motor processes may interact together to create and perpetuate autistic symptoms. These model processes were originally developed to explain data concerning how the brain controls normal behaviors. The iSTART model shows how autistic behavioral symptoms may arise from prescribed breakdowns in these brain processes.Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624
Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future
Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)
Beyond Gazing, Pointing, and Reaching: A Survey of Developmental Robotics
Developmental robotics is an emerging field located
at the intersection of developmental psychology
and robotics, that has lately attracted
quite some attention. This paper gives a survey of
a variety of research projects dealing with or inspired
by developmental issues, and outlines possible
future directions
THE CHILD AND THE WORLD: How Children acquire Language
HOW CHILDREN ACQUIRE LANGUAGE
Over the last few decades research into child language acquisition has been revolutionized by the use of ingenious new techniques which allow one to investigate what in fact infants (that is children not yet able to speak) can perceive when exposed to a stream of speech sound, the
discriminations they can make between different speech sounds, differentspeech sound sequences and different words. However on the central features of the mystery, the extraordinarily rapid acquisition of lexicon and complex syntactic structures, little solid progress has been made. The questions being researched are how infants acquire and produce the speech sounds (phonemes) of the community language; how infants find words in the stream of speech; and how they link words to perceived objects or action, that is, discover meanings. In a recent general review in Nature of children's language acquisition, Patricia Kuhl also asked why we do not learn new languages as easily at 50 as at 5 and why computers have not cracked the human linguistic code. The motor theory of language function and origin makes possible a plausible account of child language acquisition generally from which answers can be derived also to these further questions. Why computers so far have been unable to 'crack' the language problem becomes apparent in the light of the motor theory account: computers can have no natural relation between words and their meanings; they have no conceptual store to which the
network of words is linked nor do they have the innate aspects of language functioning - represented by function words; computers have no direct links between speech sounds and movement patterns and they do not have the instantly integrated neural patterning underlying thought - they necessarily operate serially and hierarchically. Adults find the acquisition of a new language much more difficult than children do because they are already neurally committed to the link between the words of their first language and the elements in their conceptual store. A second language being acquired by an adult is in direct
competition for neural space with the network structures established for the first language
An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia
Purpose: Auditory verbal hallucinations (AVHs) are speech perceptions in the
absence of a external stimulation. An influential theoretical account of AVHs
in schizophrenia claims that a deficit in inner speech monitoring would cause
the verbal thoughts of the patient to be perceived as external voices. The
account is based on a predictive control model, in which verbal self-monitoring
is implemented. The aim of this study was to examine lip muscle activity during
AVHs in schizophrenia patients, in order to check whether inner speech
occurred. Methods: Lip muscle activity was recorded during covert AVHs (without
articulation) and rest. Surface electromyography (EMG) was used on eleven
schizophrenia patients. Results: Our results show an increase in EMG activity
in the orbicularis oris inferior muscle, during covert AVHs relative to rest.
This increase is not due to general muscular tension since there was no
increase of muscular activity in the forearm muscle. Conclusion: This evidence
that AVHs might be self-generated inner speech is discussed in the framework of
a predictive control model. Further work is needed to better describe how the
inner speech monitoring dysfunction occurs and how inner speech is controlled
and monitored. This will help better understanding how AVHs occur
Different Methods of Embodied Cognition in Pedagogy and its Effectiveness in Student Learning
The Mathematical Ideas Analysis hypothesizes that abstract mathematical reasoning is unconsciously organized and integrated with sensory-motor experience. Basic research testing movement, language, and perception during math problem solving supports this hypothesis. Applied research primarily measures students’ performance on math tests after they engage in analogous sensory-motor tasks, but findings show mixed results. Sensory-motor tasks are dependent on several moderators (e.g., instructional guidance, developmental stage) known to help students learn, and studies vary in how each moderator is implemented. There is little research on the effectiveness of sensory-motor tasks without these moderators. This study compares different approaches to working with an interactive application designed to emulate how people intrinsically solve algebraic equations. A total of 130 participants (84 females, 54 males) were drawn from a pool of Introductory Psychology students attending San Jose State University. Participants were placed in three different learning environments, and their performance was measured by comparing improvement between a pre-test and a post-test. We found no difference between participants who worked alone with the application, were instructed by the experimenter while using the application, or who instructed the experimenter on how to solve equations using the application. Further research is needed to examine how and whether analogous sensory-motor interfaces are a useful learning tool, and if so, what circumstances are ideal for sensory-motor interfaces to be used
Neural Modeling and Imaging of the Cortical Interactions Underlying Syllable Production
This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and somatosensory cortical areas. Computer simulations of the model verify its ability to account for compensation to lip and jaw perturbations during speech. Specific anatomical locations of the model's components are estimated, and these estimates are used to simulate fMRI experiments of simple syllable production with and without jaw perturbations.National Institute on Deafness and Other Communication Disorders (R01 DC02852, RO1 DC01925
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