Literature DB >> 28300278

Behavior analysis and neuroscience: Complementary disciplines.

John W Donahoe1.   

Abstract

Behavior analysis and neuroscience are disciplines in their own right but are united in that both are subfields of a common overarching field-biology. What most fundamentally unites these disciplines is a shared commitment to selectionism, the Darwinian mode of explanation. In selectionism, the order and complexity observed in nature are seen as the cumulative products of selection processes acting over time on a population of variants-favoring some and disfavoring others-with the affected variants contributing to the population on which future selections operate. In the case of behavior analysis, the central selection process is selection by reinforcement; in neuroscience it is natural selection. The two selection processes are inter-related in that selection by reinforcement is itself the product of natural selection. The present paper illustrates the complementary nature of behavior analysis and neuroscience through considering their joint contributions to three central problem areas: reinforcement-including conditioned reinforcement, stimulus control-including equivalence classes, and memory-including reminding and remembering.
© 2017 Society for the Experimental Analysis of Behavior.

Keywords:  conditioned reinforcement; equivalence classes; memory; neuroscience; reinforcement; selectionism; stimulus control

Mesh:

Substances:

Year:  2017        PMID: 28300278     DOI: 10.1002/jeab.251

Source DB:  PubMed          Journal:  J Exp Anal Behav        ISSN: 0022-5002            Impact factor:   2.468


  3 in total

1.  Translations in Stimulus-Stimulus Pairing: Autoshaping of Learner Vocalizations.

Authors:  Stephanie P da Silva; April Michele Williams
Journal:  Perspect Behav Sci       Date:  2019-11-25

2.  Editorial: The Behavior of Organizations in a Scalable Selectionist System.

Authors:  Donald A Hantula
Journal:  Perspect Behav Sci       Date:  2019-06-17

3.  Switching to online: Testing the validity of supervised remote testing for online reinforcement learning experiments.

Authors:  Gibson Weydmann; Igor Palmieri; Reinaldo A G Simões; João C Centurion Cabral; Joseane Eckhardt; Patrice Tavares; Candice Moro; Paulina Alves; Samara Buchmann; Eduardo Schmidt; Rogério Friedman; Lisiane Bizarro
Journal:  Behav Res Methods       Date:  2022-10-11
  3 in total

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