Literature DB >> 15924906

Dietary learning in humans: directions for future research.

Jeffrey M Brunstrom1.   

Abstract

There is every indication that most of our flavor preferences and dietary behaviors are learned. Despite this, we know very little about the underlying mechanisms. This paper considers reasons why this might be the case. In addition to considering particular methodological issues and the potential relevance of a 'critical developmental period', emphasis is placed on the need to resolve whether learning results from an implicit or an explicit process. Addressing this issue has important implications for the way that studies should be designed. It also leads to one of two diametrically opposite conclusions. Either behavior is governed by a rather rare form of automatic and involuntary associative learning, or otherwise, it should be regarded as non-automatic and subject to attentional and other constraints associated with most other forms of learning in humans. This latter proposition invites speculation that learning might also be governed by more complex representations (beliefs and attitudes) associated with the foods and flavors that are presented in learning studies. More generally, an analysis of this kind is important because it has the potential to explain differences that might underpin particular aberrant eating habits.

Entities:  

Mesh:

Year:  2005        PMID: 15924906     DOI: 10.1016/j.physbeh.2005.04.004

Source DB:  PubMed          Journal:  Physiol Behav        ISSN: 0031-9384


  8 in total

Review 1.  Role of gut nutrient sensing in stimulating appetite and conditioning food preferences.

Authors:  Anthony Sclafani; Karen Ackroff
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2012-03-21       Impact factor: 3.619

2.  Integration of Sweet Taste and Metabolism Determines Carbohydrate Reward.

Authors:  Maria Geraldine Veldhuizen; Richard Keith Babbs; Barkha Patel; Wambura Fobbs; Nils B Kroemer; Elizabeth Garcia; Martin R Yeomans; Dana M Small
Journal:  Curr Biol       Date:  2017-08-10       Impact factor: 10.834

3.  GPR40 and GPR120 fatty acid sensors are critical for postoral but not oral mediation of fat preferences in the mouse.

Authors:  Anthony Sclafani; Steven Zukerman; Karen Ackroff
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2013-10-23       Impact factor: 3.619

Review 4.  Learned flavor preferences. The variable potency of post-oral nutrient reinforcers.

Authors:  Karen Ackroff
Journal:  Appetite       Date:  2008-07-07       Impact factor: 3.868

5.  So Many Brands and Varieties to Choose from: Does This Compromise the Control of Food Intake in Humans?

Authors:  Charlotte A Hardman; Danielle Ferriday; Lesley Kyle; Peter J Rogers; Jeffrey M Brunstrom
Journal:  PLoS One       Date:  2015-04-29       Impact factor: 3.240

6.  Individual variability in preference for energy-dense foods fails to predict child BMI percentile.

Authors:  Christina Potter; Rebecca L Griggs; Danielle Ferriday; Peter J Rogers; Jeffrey M Brunstrom
Journal:  Physiol Behav       Date:  2017-04-01

7.  Visual food stimulus changes resting oscillatory brain activities related to appetitive motive.

Authors:  Takahiro Yoshikawa; Masaaki Tanaka; Akira Ishii; Yoko Yamano; Yasuyoshi Watanabe
Journal:  Behav Brain Funct       Date:  2016-09-26       Impact factor: 3.759

8.  Planned morning aerobic exercise in a fasted state increases energy intake in the preceding 24 h.

Authors:  Asya Barutcu; Elizabeth Briasco; Jake Moon; David J Stensel; James A King; Gemma L Witcomb; Lewis J James
Journal:  Eur J Nutr       Date:  2021-02-23       Impact factor: 5.614

  8 in total

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