Literature DB >> 26034283

Amphetamine modulates brain signal variability and working memory in younger and older adults.

Douglas D Garrett1, Irene E Nagel2, Claudia Preuschhof3, Agnieszka Z Burzynska4, Janina Marchner5, Steffen Wiegert5, Gerhard J Jungehülsing6, Lars Nyberg7, Arno Villringer8, Shu-Chen Li9, Hauke R Heekeren10, Lars Bäckman11, Ulman Lindenberger12.   

Abstract

Better-performing younger adults typically express greater brain signal variability relative to older, poorer performers. Mechanisms for age and performance-graded differences in brain dynamics have, however, not yet been uncovered. Given the age-related decline of the dopamine (DA) system in normal cognitive aging, DA neuromodulation is one plausible mechanism. Hence, agents that boost systemic DA [such as d-amphetamine (AMPH)] may help to restore deficient signal variability levels. Furthermore, despite the standard practice of counterbalancing drug session order (AMPH first vs. placebo first), it remains understudied how AMPH may interact with practice effects, possibly influencing whether DA up-regulation is functional. We examined the effects of AMPH on functional-MRI-based blood oxygen level-dependent (BOLD) signal variability (SD(BOLD)) in younger and older adults during a working memory task (letter n-back). Older adults expressed lower brain signal variability at placebo, but met or exceeded young adult SD(BOLD) levels in the presence of AMPH. Drug session order greatly moderated change-change relations between AMPH-driven SD(BOLD) and reaction time means (RT(mean)) and SDs (RT(SD)). Older adults who received AMPH in the first session tended to improve in RT(mean) and RT(SD) when SD(BOLD) was boosted on AMPH, whereas younger and older adults who received AMPH in the second session showed either a performance improvement when SD(BOLD) decreased (for RT(mean)) or no effect at all (for RT(SD)). The present findings support the hypothesis that age differences in brain signal variability reflect aging-induced changes in dopaminergic neuromodulation. The observed interactions among AMPH, age, and session order highlight the state- and practice-dependent neurochemical basis of human brain dynamics.

Entities:  

Keywords:  aging; brain signal variability; dopamine; fMRI; working memory

Mesh:

Substances:

Year:  2015        PMID: 26034283      PMCID: PMC4475975          DOI: 10.1073/pnas.1504090112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  42 in total

1.  Aging cognition: from neuromodulation to representation.

Authors:  Shu Chen Li; Ulman Lindenberger; Sverker Sikström
Journal:  Trends Cogn Sci       Date:  2001-11-01       Impact factor: 20.229

Review 2.  Neuroimaging studies of working memory: a meta-analysis.

Authors:  Tor D Wager; Edward E Smith
Journal:  Cogn Affect Behav Neurosci       Date:  2003-12       Impact factor: 3.282

3.  Inverted-U dopamine D1 receptor actions on prefrontal neurons engaged in working memory.

Authors:  Susheel Vijayraghavan; Min Wang; Shari G Birnbaum; Graham V Williams; Amy F T Arnsten
Journal:  Nat Neurosci       Date:  2007-02-04       Impact factor: 24.884

Review 4.  Advances in functional and structural MR image analysis and implementation as FSL.

Authors:  Stephen M Smith; Mark Jenkinson; Mark W Woolrich; Christian F Beckmann; Timothy E J Behrens; Heidi Johansen-Berg; Peter R Bannister; Marilena De Luca; Ivana Drobnjak; David E Flitney; Rami K Niazy; James Saunders; John Vickers; Yongyue Zhang; Nicola De Stefano; J Michael Brady; Paul M Matthews
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

Review 5.  Linking cognitive aging to alterations in dopamine neurotransmitter functioning: recent data and future avenues.

Authors:  Lars Bäckman; Ulman Lindenberger; Shu-Chen Li; Lars Nyberg
Journal:  Neurosci Biobehav Rev       Date:  2009-12-21       Impact factor: 8.989

Review 6.  The correlative triad among aging, dopamine, and cognition: current status and future prospects.

Authors:  Lars Bäckman; Lars Nyberg; Ulman Lindenberger; Shu-Chen Li; Lars Farde
Journal:  Neurosci Biobehav Rev       Date:  2006-08-09       Impact factor: 8.989

7.  Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine.

Authors:  Venkata S Mattay; Terry E Goldberg; Francesco Fera; Ahmad R Hariri; Alessandro Tessitore; Michael F Egan; Bhaskar Kolachana; Joseph H Callicott; Daniel R Weinberger
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-25       Impact factor: 11.205

Review 8.  Moment-to-moment brain signal variability: a next frontier in human brain mapping?

Authors:  Douglas D Garrett; Gregory R Samanez-Larkin; Stuart W S MacDonald; Ulman Lindenberger; Anthony R McIntosh; Cheryl L Grady
Journal:  Neurosci Biobehav Rev       Date:  2013-03-01       Impact factor: 8.989

Review 9.  FSL.

Authors:  Mark Jenkinson; Christian F Beckmann; Timothy E J Behrens; Mark W Woolrich; Stephen M Smith
Journal:  Neuroimage       Date:  2011-09-16       Impact factor: 6.556

10.  COMT Val(158)Met genotype determines the direction of cognitive effects produced by catechol-O-methyltransferase inhibition.

Authors:  Sarah M Farrell; Elizabeth M Tunbridge; Sven Braeutigam; Paul J Harrison
Journal:  Biol Psychiatry       Date:  2012-03-15       Impact factor: 13.382

View more
  33 in total

1.  Neural Variability Is Quenched by Attention.

Authors:  Ayelet Arazi; Yaffa Yeshurun; Ilan Dinstein
Journal:  J Neurosci       Date:  2019-05-31       Impact factor: 6.167

Review 2.  The pharmacology of amphetamine and methylphenidate: Relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities.

Authors:  Stephen V Faraone
Journal:  Neurosci Biobehav Rev       Date:  2018-02-08       Impact factor: 8.989

3.  Evaluating Cognitive Relationships with Resting-State and Task-driven Blood Oxygen Level-Dependent Variability.

Authors:  Peter R Millar; Beau M Ances; Brian A Gordon; Tammie L S Benzinger; John C Morris; David A Balota
Journal:  J Cogn Neurosci       Date:  2020-11-02       Impact factor: 3.225

4.  Boosts in brain signal variability track liberal shifts in decision bias.

Authors:  Niels A Kloosterman; Julian Q Kosciessa; Ulman Lindenberger; Johannes Jacobus Fahrenfort; Douglas D Garrett
Journal:  Elife       Date:  2020-08-03       Impact factor: 8.140

Review 5.  Working Memory: Maintenance, Updating, and the Realization of Intentions.

Authors:  Lars Nyberg; Johan Eriksson
Journal:  Cold Spring Harb Perspect Biol       Date:  2015-12-04       Impact factor: 10.005

6.  Latent-Profile Analysis Reveals Behavioral and Brain Correlates of Dopamine-Cognition Associations.

Authors:  Martin Lövdén; Nina Karalija; Micael Andersson; Anders Wåhlin; Jan Axelsson; Ylva Köhncke; Lars S Jonasson; Anna Rieckman; Goran Papenberg; Douglas D Garrett; Marc Guitart-Masip; Alireza Salami; Katrine Riklund; Lars Bäckman; Lars Nyberg; Ulman Lindenberger
Journal:  Cereb Cortex       Date:  2018-11-01       Impact factor: 5.357

7.  Brain Signal Variability Differentially Affects Cognitive Flexibility and Cognitive Stability.

Authors:  Diana J N Armbruster-Genç; Kai Ueltzhöffer; Christian J Fiebach
Journal:  J Neurosci       Date:  2016-04-06       Impact factor: 6.167

8.  Post-Traumatic Stress Constrains the Dynamic Repertoire of Neural Activity.

Authors:  Bratislav Mišić; Benjamin T Dunkley; Paul A Sedge; Leodante Da Costa; Zainab Fatima; Marc G Berman; Sam M Doesburg; Anthony R McIntosh; Richard Grodecki; Rakesh Jetly; Elizabeth W Pang; Margot J Taylor
Journal:  J Neurosci       Date:  2016-01-13       Impact factor: 6.167

9.  Reproducibility of the correlative triad among aging, dopamine receptor availability, and cognition.

Authors:  Eric J Juarez; Jaime J Castrellon; Mikella A Green; Jennifer L Crawford; Kendra L Seaman; Christopher T Smith; Linh C Dang; David Matuskey; Evan D Morris; Ronald L Cowan; David H Zald; Gregory R Samanez-Larkin
Journal:  Psychol Aging       Date:  2019-10-07

10.  Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Authors:  Peter R Millar; Steven E Petersen; Beau M Ances; Brian A Gordon; Tammie L S Benzinger; John C Morris; David A Balota
Journal:  Cereb Cortex       Date:  2020-10-01       Impact factor: 5.357

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.