Editing Stimulus–response model

{{Short description | Conceptual framework in psychology}}

The '''stimulus–response model''' is a [[conceptual framework]] in psychology that describes how individuals react to external [[Stimulus_(psychology)|stimuli]]. According to this model, an external stimulus triggers a reaction in an organism, often without the need for conscious thought. This model emphasizes the mechanistic aspects of behavior, suggesting that behavior can often be predicted and controlled by understanding and manipulating the stimuli that trigger responses.

==Fields of application==

Stimulus–response models are applied in international relations,<ref>
{{cite book
 | title = What causes war?: an introduction to theories of international conflict
 | chapter = International Interaction: Stimulus–Response Theory and Arms Races
 | author = Greg Cashman
 | publisher = Lexington Books
 | year = 2000
 | isbn = 978-0-7391-0112-4
 | pages = 160–192
 | chapter-url = https://books.google.com/books?id=I9xIfeijGhMC&q=stimulus-response-model+statistical&pg=PA167
 }}</ref> 
[[:en:Neuropsychological test|psychology]],<ref>
{{cite book
 | title = The Counselor's Companion: What Every Beginning Counselor Needs to Know
 | editor = Jocelyn Gregoire and Christin Jungers
 | chapter = Counseling Across the Life Span
 | author = Stephen P. Kachmar and Kimberly Blair
 | publisher = Routledge
 | year = 2007
 | isbn = 978-0-8058-5684-2
 | page = 143
 | chapter-url = https://books.google.com/books?id=5V9nvsKeBgIC&q=stimulus-response-model++behavior&pg=RA1-PA143
 }}</ref> 
[[risk assessment]],<ref>
{{cite book
 | title = Analyzing environmental data
 | chapter = Quantitative Risk Assessment with Stimulus–Response Data
 | author = Walter W. Piegorsch and A. John Bailer
 | publisher = John Wiley and Sons
 | year = 2005
 | isbn = 978-0-470-84836-4
 | pages = 171–214
 | chapter-url = https://books.google.com/books?id=FrNv8AwkoKgC&q=stimulus-response-model+statistical&pg=PA172
 }}</ref> 
[[:en:Neuroscience|neuroscience]],<ref>
{{cite book
 | title = Computer simulation in brain science
 | chapter = Neurons with hysteresis?
 | author = Geoffrey W. Hoffmann
 | editor = Rodney Cotterill
 | publisher = Cambridge University Press
 | year = 1988
 | isbn = 978-0-521-34179-0
 | pages = 74–87
 | chapter-url = https://books.google.com/books?id=B6nfz--ePEEC&q=stimulus-response++neuron&pg=PA79
 }}</ref>
neurally-inspired system design,<ref>
{{cite book
 | title = Systems methodology for software
 | author = Teodor Rus
 | publisher = World Scientific
 | year = 1993
 | isbn = 978-981-02-1254-4
 | page = 12
 | url = https://books.google.com/books?id=l7o31p-6dlAC&q=stimulus-response-model++neuron&pg=PA12
 }}</ref>
and many other fields.

Pharmacological [[dose response relationships]] are an application of stimulus-response models.

Another field this model can be applied to is psychological problems/disorders such as [[Tourette syndrome]]. Research shows Gilles de la Tourette syndrome (GTS)<ref>{{Cite web |title=Tourette syndrome - Symptoms and causes |url=https://www.mayoclinic.org/diseases-conditions/tourette-syndrome/symptoms-causes/syc-20350465 |access-date=2023-04-22 |website=Mayo Clinic |language=en}}</ref> can be characterized by enhanced cognitive functions related to creating, modifying and maintaining connections between stimuli and responses (S‐R links). Specifically, two areas, procedural sequence learning and, as a novel finding, also event file binding, show converging evidence of hyperfunctioning in GTS.<ref>{{Cite journal |last1=Wang |first1=Sujie |last2=Berbekova |first2=Adiyukh |last3=Uysal |first3=Muzaffer |last4=Wang |first4=Jiahui |date=2022-12-26 |title=Emotional Solidarity and Co-creation of Experience as Determinants of Environmentally Responsible Behavior: A Stimulus-Organism-Response Theory Perspective |url=http://journals.sagepub.com/doi/10.1177/00472875221146786 |journal=Journal of Travel Research |volume=63 |language=en |pages=115–135 |doi=10.1177/00472875221146786 |s2cid=255223259 |issn=0047-2875|url-access=subscription }}</ref>

Previous research on E-learning has proven that studying online can be even more daunting for lecturers and students who suddenly change their learning patterns from the classrooms to the virtual ones. This is mainly because the suddenness of this change makes it difficult for lecturers to fully prepare to lecture in the virtual learning environment. In light of the above-mentioned facts, this research proposes a novel model and integrates flow theory into the theory of technology acceptance model (TAM), based on stimulus-organism-response (S-O-R) theory, the SOR model has been widely used in previous studies of online customer behavior, and the model theory includes three components: stimulus, organism, and response. Assuming that stimuli contained in the external environment cause people to change, which affects their behavior.<ref>{{Cite journal |last=Chang |first=Chen-Cheng |date=2022-08-25 |title=Factors affecting m-learning continuance – From the perspectives of flow theory and stimulus-organism-response theory |url=https://papers.academic-conferences.org/index.php/eckm/article/view/710 |journal=European Conference on Knowledge Management |language=en |volume=23 |issue=2 |pages=1396–1402 |doi=10.34190/eckm.23.2.710 |issn=2048-8971|doi-access=free }}</ref>

==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'':<ref name="meyeretal2017">Meyer, A. F., Williamson, R. S., Linden, J. F., & Sahani, M. (2017). Models of neuronal stimulus-response functions: elaboration, estimation, and evaluation. ''Frontiers in systems neuroscience'', 10, 109.</ref>

: <math>\mathrm{E}(Y) = f(x)</math>

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

: <math>\mathrm{E}(Y) = \alpha + \beta x.</math>

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

== Bounded response functions ==

Since many types of response have inherent physical limitations (e.g. minimal maximal muscle contraction), it is often applicable to use a bounded function (such as the [[logistic function]]) to model the response. Similarly, a linear response function may be unrealistic as it would imply arbitrarily large responses. For binary dependent variables, statistical analysis with regression methods such as the [[probit model]] or [[logit model]], or other methods such as the Spearman–Kärber method.<ref name="HamiltonRusso1977">{{cite journal |last1= Hamilton |first1= MA |last2= Russo |first2= RC |last3= Thurston |first3= RV |title= Trimmed Spearman–Karber method for estimating median lethal concentrations in toxicity bioassays |journal= [[Environmental Science & Technology]] |volume= 11 |issue= 7 |year= 1977 |pages= 714–9 |doi= 10.1021/es60130a004|bibcode= 1977EnST...11..714H }}</ref> Empirical models based on nonlinear regression are usually preferred over the use of some transformation of the data that linearizes the stimulus-response relationship.<ref name="BatesWatts1988">{{cite book |last1= Bates |first1= Douglas M. |last2= Watts |first2= Donald G. |title= Nonlinear Regression Analysis and its Applications |year= 1988 |publisher= [[John Wiley & Sons|Wiley]] |isbn= 9780471816430 |page= 365}}</ref>

[[Logistic regression#Definition of the logistic function|One example]] of a logit model for the probability of a response to the real input (stimulus) <math>x</math>, (<math>x\in \mathbb R</math>) is

:<math>p(x) = \frac {1}{1+e^{-(\beta_0 + \beta_1 x)}}</math>

where <math>\beta_0, \beta_1</math> are the parameters of the function.

Conversely, a [[Probit model]] would be of the form

:<math>p(x) = \Phi(\beta_0 + \beta_1 x)</math>

where <math>\Phi(x)</math> is the [[Normal distribution#Cumulative distribution function|cumulative distribution function]] of the [[normal distribution]].

=== Hill equation ===

In [[biochemistry]] and [[pharmacology]], the [[Hill equation (biochemistry)|Hill equation]] refers to two closely related equations, one of which describes the response (the physiological output of the system, such as muscle contraction) to [[Drug]] or [[Toxin]], as a function of the drug's [[concentration]].<ref name = Terms>{{cite journal |title=International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. XXXVIII. Update on Terms and Symbols in Quantitative Pharmacology|url=https://www.guidetopharmacology.org/pdfs/termsAndSymbols.pdf|last1=Neubig|first1=Richard R.|journal=Pharmacological Reviews|year=2003|volume=55|issue=4|pages=597–606|doi=10.1124/pr.55.4.4|pmid=14657418|s2cid=1729572}}</ref> The Hill equation is important in the construction of [[dose-response curves]]. The Hill equation is the following formula, where <math>E</math> is the magnitude of the response, <chem>[A]</chem> is the drug concentration (or equivalently, stimulus intensity), [[EC50|<math>\mathrm{EC}_{50}</math>]] is the drug concentration that produces a half-maximal response and <math>n</math> is the [[Hill coefficient]].

:[[File:Ivan Pavlov nobel.jpg|thumb|Ivan Pavlov]]<math>\frac{E}{E_{\mathrm{max}}}=\frac{1}{1+\left(\frac{\mathrm{EC}_{50}}{[A]}\right)^{n}}</math><ref name = Terms/>

The Hill equation rearranges to a logistic function with respect to the logarithm of the dose (similar to a logit model).

== Founder of the Model ==

=== Ivan Pavlov ===
[[Ivan Pavlov|Pavlov]] started studying the digestive system in dogs by performing chronic implants of fistulas in the stomach, by which he was able to show with extreme clarity that the nervous system plays a dominant role in the regulation of the digestive process. Experiments on digestion led to the development of the first experimental model of learning, in which a neutral stimulus acquires the capacity to evoke a specific response further to repeated pairing with another stimulus that evokes the response.<ref>{{Cite journal |last1=Cambiaghi |first1=Marco |last2=Sacchetti |first2=Benedetto |date=2015-06-01 |title=Ivan Petrovich Pavlov (1849–1936) |url=https://doi.org/10.1007/s00415-015-7743-2 |journal=Journal of Neurology |language=en |volume=262 |issue=6 |pages=1599–1600 |doi=10.1007/s00415-015-7743-2 |pmid=25893257 |issn=1432-1459|hdl=2318/1526427 |s2cid=22347968 |hdl-access=free }}</ref> 

==== Edward Thorndike ====
[[File:PSM V80 D211 Edward Lee Thorndike.png|thumb|Edward Thorndike]]
[[Edward Thorndike|Thorndike]], who proposed the model, believed that learning stemmed from stimulus and response.<ref>{{Cite web |date=2020-11-24 |title=Thorndike's Stimulus Response Theory of Learning (Definition + Examples) |url=https://practicalpie.com/stimulus-response-theory/ |access-date=2023-04-22 |website=Practical Psychology |language=en-US}}</ref> Pavlov popularized and revolutionized the theory though by experimenting on the dogs.

==References==

<references/>

==Further reading==
* {{cite journal|first1=Peter C.|last1=Holland|title=Cognitive versus stimulus-response theories of learning|journal=Learning & Behavior|volume=36|issue=3|pages=227–241|year=2008|pmc = 3065938 |pmid=18683467 |doi=10.3758/lb.36.3.227}}

{{DEFAULTSORT:Stimulus-Response Model}}
[[Category:Behavioral concepts]]
[[Category:Psychological models]]


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