Literature DB >> 30834431

Good practice in food-related neuroimaging.

Paul A M Smeets1,2, Alain Dagher3, Todd A Hare4, Stephanie Kullmann5, Laura N van der Laan6, Russell A Poldrack7, Hubert Preissl5, Dana Small8, Eric Stice9, Maria G Veldhuizen8.   

Abstract

The use of neuroimaging tools, especially functional magnetic resonance imaging, in nutritional research has increased substantially over the past 2 decades. Neuroimaging is a research tool with great potential impact on the field of nutrition, but to achieve that potential, appropriate use of techniques and interpretation of neuroimaging results is necessary. In this article, we present guidelines for good methodological practice in functional magnetic resonance imaging studies and flag specific limitations in the hope of helping researchers to make the most of neuroimaging tools and avoid potential pitfalls. We highlight specific considerations for food-related studies, such as how to adjust statistically for common confounders, like, for example, hunger state, menstrual phase, and BMI, as well as how to optimally match different types of food stimuli. Finally, we summarize current research needs and future directions, such as the use of prospective designs and more realistic paradigms for studying eating behavior.
© 2019 American Society for Nutrition.

Keywords:  aroma; data sharing; food choice; food viewing; functional magnetic resonance imaging; good practice; neuroimaging; satiation; taste

Mesh:

Year:  2019        PMID: 30834431      PMCID: PMC7945961          DOI: 10.1093/ajcn/nqy344

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  118 in total

1.  ANIMA: A data-sharing initiative for neuroimaging meta-analyses.

Authors:  Andrew T Reid; Danilo Bzdok; Sarah Genon; Robert Langner; Veronika I Müller; Claudia R Eickhoff; Felix Hoffstaedter; Edna-Clarisse Cieslik; Peter T Fox; Angela R Laird; Katrin Amunts; Svenja Caspers; Simon B Eickhoff
Journal:  Neuroimage       Date:  2015-07-29       Impact factor: 6.556

2.  Can cognitive processes be inferred from neuroimaging data?

Authors:  Russell A Poldrack
Journal:  Trends Cogn Sci       Date:  2006-01-06       Impact factor: 20.229

3.  Shared Genetic Factors Influence Head Motion During MRI and Body Mass Index.

Authors:  Karen Hodgson; Russell A Poldrack; Joanne E Curran; Emma E Knowles; Samuel Mathias; Harald H H Göring; Nailin Yao; Rene L Olvera; Peter T Fox; Laura Almasy; Ravi Duggirala; Deanna M Barch; John Blangero; David C Glahn
Journal:  Cereb Cortex       Date:  2017-12-01       Impact factor: 5.357

Review 4.  Power failure: why small sample size undermines the reliability of neuroscience.

Authors:  Katherine S Button; John P A Ioannidis; Claire Mokrysz; Brian A Nosek; Jonathan Flint; Emma S J Robinson; Marcus R Munafò
Journal:  Nat Rev Neurosci       Date:  2013-04-10       Impact factor: 34.870

5.  Variation in the obesity risk gene FTO determines the postprandial cerebral processing of food stimuli in the prefrontal cortex.

Authors:  Martin Heni; Stephanie Kullmann; Ralf Veit; Caroline Ketterer; Sabine Frank; Fausto Machicao; Harald Staiger; Hans-Ulrich Häring; Hubert Preissl; Andreas Fritsche
Journal:  Mol Metab       Date:  2013-12-08       Impact factor: 7.422

6.  Cluster-extent based thresholding in fMRI analyses: pitfalls and recommendations.

Authors:  Choong-Wan Woo; Anjali Krishnan; Tor D Wager
Journal:  Neuroimage       Date:  2014-01-08       Impact factor: 6.556

7.  Using a 3D virtual supermarket to measure food purchase behavior: a validation study.

Authors:  Wilma Elzeline Waterlander; Yannan Jiang; Ingrid Hendrika Margaretha Steenhuis; Cliona Ni Mhurchu
Journal:  J Med Internet Res       Date:  2015-04-28       Impact factor: 5.428

8.  Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T.

Authors:  Seong Dae Yun; N Jon Shah
Journal:  PLoS One       Date:  2017-09-25       Impact factor: 3.240

9.  Physiological noise in brainstem FMRI.

Authors:  Jonathan C W Brooks; Olivia K Faull; Kyle T S Pattinson; Mark Jenkinson
Journal:  Front Hum Neurosci       Date:  2013-10-04       Impact factor: 3.169

10.  Neural mechanisms supporting maladaptive food choices in anorexia nervosa.

Authors:  Karin Foerde; Joanna E Steinglass; Daphna Shohamy; B Timothy Walsh
Journal:  Nat Neurosci       Date:  2015-10-12       Impact factor: 24.884

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  21 in total

1.  Weight gain is associated with changes in neural response to palatable food tastes varying in sugar and fat and palatable food images: a repeated-measures fMRI study.

Authors:  Sonja Yokum; Eric Stice
Journal:  Am J Clin Nutr       Date:  2019-12-01       Impact factor: 7.045

Review 2.  The Impact of Restrictive and Non-restrictive Dietary Weight Loss Interventions on Neurobehavioral Factors Related to Body Weight Control: the Gaps and Challenges.

Authors:  Sylvain Iceta; Shirin Panahi; Isabel García-García; Andréanne Michaud
Journal:  Curr Obes Rep       Date:  2021-07-27

3.  Can we have a second helping? A preregistered direct replication study on the neurobiological mechanisms underlying self-control.

Authors:  Christin Scholz; Hang-Yee Chan; Russell A Poldrack; Denise T D de Ridder; Ale Smidts; Laura Nynke van der Laan
Journal:  Hum Brain Mapp       Date:  2022-09-09       Impact factor: 5.399

4.  Test-retest reliability of functional MRI food receipt, anticipated receipt, and picture tasks.

Authors:  Sonja Yokum; Cara Bohon; Elliot Berkman; Eric Stice
Journal:  Am J Clin Nutr       Date:  2021-08-02       Impact factor: 7.045

5.  Familial Obesity Risk and Current Excess Weight Influence Brain Structure in Adolescents.

Authors:  Gita Thapaliya; Liuyi Chen; Elena Jansen; Kimberly R Smith; Jennifer R Sadler; Leora Benson; Afroditi Papantoni; Susan Carnell
Journal:  Obesity (Silver Spring)       Date:  2020-12-05       Impact factor: 5.002

6.  The Hunger Games: Homeostatic State-Dependent Fluctuations in Disinhibition Measured with a Novel Gamified Test Battery.

Authors:  Katharina Voigt; Emily Giddens; Romana Stark; Emma Frisch; Neda Moskovsky; Naomi Kakoschke; Julie C Stout; Mark A Bellgrove; Zane B Andrews; Antonio Verdejo-Garcia
Journal:  Nutrients       Date:  2021-06-10       Impact factor: 5.717

7.  Reliability of neural food cue-reactivity in participants with obesity undergoing bariatric surgery: a 26-week longitudinal fMRI study.

Authors:  J Malte Bumb; Falk Kiefer; Patrick Bach; Martin Grosshans; Anne Koopmann; Peter Kienle; Georgi Vassilev; Mirko Otto
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2020-12-17       Impact factor: 5.270

8.  Reassessing relationships between appetite and adiposity in people at risk of obesity: A twin study using fMRI.

Authors:  Leticia E Sewaybricker; Susan J Melhorn; Jennifer L Rosenbaum; Mary K Askren; Vidhi Tyagi; Mary F Webb; Mary Rosalynn B De Leon; Thomas J Grabowski; Ellen A Schur
Journal:  Physiol Behav       Date:  2021-06-18

9.  Negative affect amplifies the relation between appetitive-food-related neural responses and weight gain over three-year follow-up among adolescents.

Authors:  X Yang; M Casement; S Yokum; E Stice
Journal:  Neuroimage Clin       Date:  2019-11-05       Impact factor: 4.881

10.  Empirical assessment of changing sample-characteristics in task-fMRI over two decades: An example from gustatory and food studies.

Authors:  Andy W K Yeung; Natalie S M Wong; Simon B Eickhoff
Journal:  Hum Brain Mapp       Date:  2020-03-26       Impact factor: 5.038

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