Relation of Learned Heart Rate Control to Self‐Report in Different Task Environments

Williams, Robert J.; Roberts, Larry E.

doi:10.1111/j.1469-8986.1988.tb01254.x

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…However, the research findings summarized above make it difficult to defend a strong version of the traditional conceptualization of conditioning as automatic, unconscious, and compartmentalized from higher-order cognition. Furthermore, similar conclusions have been reached from reviews of related forms of learning in humans, including instrumental conditioning (see Brewer 1974;Williams and Roberts 1988) and implicit learning (Shanks and St. John 1994). It seems worthwhile, then, to consider the implications of the cognitive model for how we conceptualize extinction.…”

Section: Human Pavlovian Conditioningmentioning

confidence: 52%

Cognitive Processes in Extinction: Figure 1

Lovibond

2004

Learn. Mem.

111

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Human conditioning research shows that learning is closely related to consciously available contingency knowledge, requires attentional resources, and is influenced by language. This research suggests a cognitive model in which extinction consists of changes in contingency beliefs in long-term memory. Laboratory and clinical evidence on extinction is briefly reviewed, and it is concluded that the evidence supports the cognitive position. There is little evidence for a separate, noncognitive conditioning system. The primary implication for neural analysis is that learning and extinction are unlikely to be reducible to direct connections in which one stimulus simply activates or inhibits the memory representation of another. Rather, an adequate neural model will involve the integration of both low-level and high-level systems, including attention, representation of stimulus relations in long-term memory, and a dynamic performance mechanism based on anticipation, not just activation.Extinction refers to the loss of an associatively based behavior when the associative relationships that generated the original learning have been changed. For example, in Pavlovian conditioning, the conditioned response (CR) declines over trials when the conditioned stimulus (CS) is no longer followed by the unconditioned stimulus (US). The way in which we view extinction necessarily follows from the way in which we conceptualize the initial conditioning. Psychologists, neuroscientists, and lay people alike share a common conceptualization of conditioning: It is seen as an automatic, unconscious, and low-level process that establishes excitatory or inhibitory associations between CS and US nodes in memory. In humans, conditioning is almost universally agreed to involve separate mechanisms from those involved in reasoning, language, and consciousness. Accordingly, extinction is also seen as an automatic and unconscious process that either reverses the original learned associations, or establishes new competing associations. But what if this traditional view of conditioning and extinction is wrong?In fact, research on conditioning in humans suggests it to be an entirely different process from that suggested by the traditional view. Evidence for a separate conditioning mechanism that is independent of higher cognitive processes has been remarkably difficult to obtain (Brewer 1974;Dawson and Schell 1985;Lovibond and Shanks 2002). Instead, conditioning in humans appears to be closely tied to attention, consciousness, and language. In this article, I will briefly summarize this research, then focus specifically on extinction in human conditioning, and finally consider the implications for research into the neural basis of conditioning and extinction in both animals and humans.

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Section: Human Pavlovian Conditioningmentioning

confidence: 52%

Cognitive Processes in Extinction: Figure 1

Lovibond

2004

Learn. Mem.

111

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“…In addition to this uncertainty, utilizing peripheral ANS signals as an access pathway present several unique challenges, including a very slow rate of response (e.g. heart rate, 30 s per trial [33]), high metabolic noise and high incidence of pathological change in the target population [34]. While some peripheral autonomic signals have been investigated as access pathways [35][36][37][38], the question of learned control of these signals has yet to be answered and these aforementioned challenges remain unaddressed.…”

Section: Current Access Pathways To Assistive Technologiesmentioning

confidence: 99%

Peripheral Autonomic Signals as Access Pathways for Individuals with Severe Disabilities: A Literature Appraisal

Blain¹,

Chau

Mihailidis³

2008

TOREHJ

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Many individuals with severe and multiple disabilities do not have an access pathway that enables them to interface with their environment because they are not afforded a binary switch that they can reliably control. While recent research has focused on the self-regulation of central signals of the autonomic nervous system (ANS) to create braincomputer interfaces (BCIs) for these individuals, there has been less focus on the peripheral signals of the ANS as an access pathway. An appraisal of the literature in the areas of biofeedback, polygraphy and mental exercises uncovered considerable evidence that peripheral ANS signals can be voluntarily controlled and thus have the potential to be used as an access pathway by the target population. However, the issues of speed, metabolic noise and pathological change must be addressed before peripheral ANS signals can be used as either a complementary or alternative access pathway to existing brain-computer interfaces.

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“…However, the very slow rate of responsivity (e.g., heart rate, 30 s per trial; R. J. Williams & Roberts, 1988) and the high metabolic noise of some autonomic responses, as well as the high incidence of pathological changes in locked-in patients, make autonomic functions useless for precise and reliable communication. The electrical signals of the brain (electroencephalogram; EEG), with their fast responsivity and covariation with cognitive processes, are more suitable as candidates for nonmotor mediation between person and computer.…”

Section: Spontaneous Eec and Event-related Potentialsmentioning

confidence: 99%

“…Indeed, people with motor disabilities can learn to control these functions to some extent using operant conditioning techniques (Engel, 1977). However, the very slow rate of responsivity (e.g., heart rate, 30 s per trial; R. J. Williams & Roberts, 1988) and the high metabolic noise of some autonomic responses, as well as the high incidence of pathological changes in locked-in patients, make autonomic functions useless for precise and reliable communication.…”

Section: Use Of Electrical Brain Activity For Communicationmentioning

confidence: 99%

Brain–computer communication: Unlocking the locked in.

Kübler¹,

Kotchoubey²,

Kaiser³

et al. 2001

Psychological Bulletin

459

264

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With the increasing efficiency of life-support systems and better intensive care, more patients survive severe injuries of the brain and spinal cord. Many of these patients experience locked-in syndrome: The active mind is locked in a paralyzed body. Consequently, communication is extremely restricted or impossible. A muscle-independent communication channel overcomes this problem and is realized through a brain-computer interface, a direct connection between brain and computer. The number of technically elaborated brain-computer interfaces is in contrast with the number of systems used in the daily life of locked-in patients. It is hypothesized that a profound knowledge and consideration of psychological principles are necessary to make brain-computer interfaces feasible for locked-in patients.

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Relation of Learned Heart Rate Control to Self‐Report in Different Task Environments

Cited by 8 publications

References 37 publications

Cognitive Processes in Extinction: Figure 1

Cognitive Processes in Extinction: Figure 1

Peripheral Autonomic Signals as Access Pathways for Individuals with Severe Disabilities: A Literature Appraisal

Brain–computer communication: Unlocking the locked in.

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