Stimulus–response model

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Stimulation

Types of stimulus (psychology)

Afferent stimulation Auditory stimulation Aversive stimulation Brain self stimulation Brain stimulation Chemical brain stimulation Dichoptic stimulation Dichotic stimulation Electrical brain stimulation Olfactory stimulation Perceptual stimulation Photopic stimulation Pictorial stimuli Prismatic stimulation Scotopic stimulation Self stimulation Somesthetic stimulation Spinal cord stimulation Stimulus modality Subliminal stimulation Tactual stimulation Taste stimulation Verbal stimuli Visual stimulation Stimulators (apparatus)

Stimulus parameters

Cues Interstimulus interval Stimulus ambiguity Stimulus attenuation Stimulus change Stimulus complexity Stimulus control Stimulus deprivation Stimulus discrimination Stimulus duration Stimulus frequency Stimulus generalization Stimulus intensity Stimulus intervals Stimulus novelty Stimulus offset Stimulus onset Stimulus presentation methods Stimulus salience Stimulus similarity Stimulus variability

Related topics

Association value Biofeedback Conditioned stimulus Conditioning Feedback Stimulus novelty Transposition Unconditioned stimulus

The stimulus–response model is a characterization of a statistical unit (such as a neuron) as a black box model, predicting a quantitative response to a quantitative stimulus, for example one administered by a researcher. Such models conceptually tie together stimulus and response

Fields of application

Stimulus–response models are applied in international relations, psychology, risk assessment, neuroscience, neurally-inspired system design, and many other fields.

Mathematical formulation

The object of a stimulus–response model is to establish a mathematical function that describes the relation f between the stimulus x and the expected value (or other measure of location) of the response Y:^{[citation needed]}

$E(Y) = f(x)$

A common simplification assumed for such functions is linear, thus we expect to see a relationship like

$E(Y) = \alpha + \beta x.$

Statistical theory for linear models has been well developed for more than fifty years, and a standard form of analysis called linear regression has been developed.

References

Responses

Response parameters

Interresponse time Response amplitude Response duration Response frequency Response generalization Response inhibition Response latency Response probability Response set Response variability

Types of responses

Conditioned responses Emotional responses Mediated responses Orientating responses Reflexes Unconditioned responses

Related topics

Reaction time Response bias Response cost Stimulus-response model