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

Proceedings of the National Academy of Sciences of the United States of America

Volumn 112, Issue 24, 2015, Pages 7593-7598

  Garrett, Douglas D ^a,b   Nagel, Irene E ^a,c   Preuschhof, Claudia ^a,c,d   Burzynska, Agnieszka Z ^a,e   Marchner, Janina ^a   Wiegert, Steffen ^a   Jungehülsing, Gerhard J ^f   Nyberg, Lars ^g,h   Villringer, Arno ⁱ   Li, Shu Chen ^a,j   Heekeren, Hauke R ^a,c,i   Bäckman, Lars ^k   Lindenberger, Ulman ^a,b  

^a MAX PLANCK INSTITUTE FOR HUMAN DEVELOPMENT   (Germany)

^b MAX PLANCK UCL CENTRE FOR COMPUTATIONAL PSYCHIATRY AND AGEING RESEARCH   (United Kingdom)

^c FREIE UNIVERSITÄT BERLIN   (Germany)

^d OTTO VON GUERICKE UNIVERSITY   (Germany)

^e UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^f MARTIN LUTHER KRANKENHAUS   (Germany)

^g UMEÅ UNIVERSITY   (Sweden)

^h UMEÅ UNIVERSITY   (Sweden)

ⁱ MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

^j DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^k AGING RESEARCH CENTER   (Sweden)

more..

Author keywords

Aging; Brain signal variability; Dopamine; fMRI; Working memory

Indexed keywords

AMPHETAMINE; DEXAMPHETAMINE; DOPAMINE; PLACEBO;

ADULT; AGED; ARTICLE; BOLD SIGNAL; BRAIN FUNCTION; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HUMAN; LOW DRUG DOSE; MAJOR CLINICAL STUDY; MALE; MENTAL PERFORMANCE; MIDDLE AGED; MINI MENTAL STATE EXAMINATION; MOTOR PERFORMANCE; NEUROMODULATION; NUCLEAR MAGNETIC RESONANCE SCANNER; OXYGEN BLOOD LEVEL; PRIORITY JOURNAL; REACTION TIME; STATE DEPENDENT LEARNING; TASK PERFORMANCE; UPREGULATION; WORKING MEMORY; YOUNG ADULT; AGING; BIOLOGICAL MODEL; BRAIN; CLINICAL TRIAL; DOUBLE BLIND PROCEDURE; DRUG EFFECTS; MULTIVARIATE ANALYSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PSYCHOLOGICAL MODEL; PSYCHOLOGY; REGRESSION ANALYSIS; SHORT TERM MEMORY;

ADULT; AGED; AGING; BRAIN; DEXTROAMPHETAMINE; DOPAMINE; DOUBLE-BLIND METHOD; FEMALE; FUNCTIONAL NEUROIMAGING; HUMANS; LEAST-SQUARES ANALYSIS; MAGNETIC RESONANCE IMAGING; MALE; MEMORY, SHORT-TERM; MIDDLE AGED; MODELS, NEUROLOGICAL; MODELS, PSYCHOLOGICAL; MULTIVARIATE ANALYSIS; YOUNG ADULT;

EID: 84935850982     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1504090112     Document Type: Article

References (48)

1. Faisal AA, Selen LPJ, Wolpert DM (2008) Noise in the nervous system. Nat Rev Neurosci 9(4):292-303.
2. Garrett DD, et al. (2013) Moment-to-moment brain signal variability: A next frontier in human brain mapping? Neurosci Biobehav Rev 37(4):610-624.
3. Welford AT (1965) Performance, biological mechanisms and age: A theoretical sketch. Behavior, Aging, and the Nervous System, eds Welford AT, Birren J (Charles C. Thomas, Springfield, IL).
4. Cremer R, Zeef EJ (1987) What kind of noise increases with age? J Gerontol 42(5):515-518.
5. Garrett DD, Kovacevic N, McIntosh AR, Grady CL (2010) Blood oxygen level-dependent signal variability is more than just noise. J Neurosci 30(14):4914-4921.
6. Garrett DD, Kovacevic N, McIntosh AR, Grady CL (2011) The importance of being variable. J Neurosci 31(12):4496-4503.
7. Garrett DD, Kovacevic N, McIntosh AR, Grady CL (2013) The modulation of BOLD variability between cognitive states varies by age and processing speed. Cereb Cortex 23(3):684-693.
8. Li S-C, Lindenberger U, Sikström S (2001) Aging cognition: From neuromodulation to representation. Trends Cogn Sci 5(11):479-486.
9. Bäckman L, Nyberg L, Lindenberger U, Li S-C, Farde L (2006) The correlative triad among aging, dopamine, and cognition: Current status and future prospects. Neurosci Biobehav Rev 30(6):791-807.
10. Bäckman L, Lindenberger U, Li S-C, Nyberg L (2010) Linking cognitive aging to alterations in dopamine neurotransmitter functioning: Recent data and future avenues. Neurosci Biobehav Rev 34(5):670-677.
11. Lindenberger U (2014) Human cognitive aging: Corriger la fortune? Science 346(6209):572-578.
12. Vijayraghavan S, Wang M, Birnbaum SG, Williams GV, Arnsten AFT (2007) Inverted-U dopamine D1 receptor actions on prefrontal neurons engaged in working memory. Nat Neurosci 10(3):376-384.
13. Cools R, D'Esposito M (2011) Inverted-U-shaped dopamine actions on human working memory and cognitive control. Biol Psychiatry 69(12):e113-e125.
14. Cools R (2011) Dopaminergic control of the striatum for high-level cognition. Curr Opin Neurobiol 21(3):402-407.
15. Li S-C, von Oertzen T, Lindenberger U (2006) A neurocomputational model of stochastic resonance and aging. Neurocomputing 69:1553-1560.
16. Venton BJ, et al. (2003) Real-time decoding of dopamine concentration changes in the caudate-putamen during tonic and phasic firing. J Neurochem 87(5):1284-1295.
17. Montague PR, Hyman SE, Cohen JD (2004) Computational roles for dopamine in behavioural control. Nature 431(7010):760-767.
18. Day JJ, Roitman MF, Wightman RM, Carelli RM (2007) Associative learning mediates dynamic shifts in dopamine signaling in the nucleus accumbens. Nat Neurosci 10(8):1020-1028.
19. Paladini CA, Robinson S, Morikawa H, Williams JT, Palmiter RD (2003) Dopamine controls the firing pattern of dopamine neurons via a network feedback mechanism. Proc Natl Acad Sci USA 100(5):2866-2871.
20. Owesson-White CA, Cheer JF, Beyene M, Carelli RM, Wightman RM (2008) Dynamic changes in accumbens dopamine correlate with learning during intracranial self-stimulation. Proc Natl Acad Sci USA 105(33):11957-11962.
21. Mattay VS, et al. (2003) Catechol O-methyltransferase val158-met genotype and individual variation in the brain response to amphetamine. Proc Natl Acad Sci USA 100(10):6186-6191.
22. Chowdhury R, et al. (2013) Dopamine restores reward prediction errors in old age. Nat Neurosci 16(5):648-653.
23. Anderson ED, Horak FB, Lasarev MR, Nutt JG (2014) Performance of a motor task learned on levodopa deteriorates when subsequently practiced off. Mov Disord 29(1):54-60.
24. McIntosh AR, Bookstein FL, Haxby JV, Grady CL (1996) Spatial pattern analysis of functional brain images using partial least squares. Neuroimage 3(3 Pt 1):143-157.
25. Wager TD, Smith EE (2003) Neuroimaging studies of working memory: A meta-analysis. Cogn Affect Behav Neurosci 3(4):255-274.
26. Nagel IE, et al. (2011) Load modulation of BOLD response and connectivity predicts working memory performance in younger and older adults. J Cogn Neurosci 23(8):2030-2045.
27. Landau SM, Lal R, O'Neil JP, Baker S, Jagust WJ (2009) Striatal dopamine and working memory. Cereb Cortex 19(2):445-454.
28. Singer JD, Willett JB (2003) Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence (Oxford Univ Press, New York).
29. Garrett DD, McIntosh AR, Grady CL (2014) Brain signal variability is parametrically modifiable. Cereb Cortex 24(11):2931-2940.
30. Grady CL, Garrett DD (2014) Understanding variability in the BOLD signal and why it matters for aging. Brain Imaging Behav 8(2):274-283.
31. Samanez-Larkin GR, Kuhnen CM, Yoo DJ, Knutson B (2010) Variability in nucleus accumbens activity mediates age-related suboptimal financial risk taking. J Neurosci 30(4):1426-1434.
32. Seamans JK, Yang CR (2004) The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Prog Neurobiol 74(1):1-58.
33. Wang M, Vijayraghavan S, Goldman-Rakic PS (2004) Selective D2 receptor actions on the functional circuitry of working memory. Science 303(5659):853-856.
34. Samanez-Larkin GR, et al. (2013) A thalamocorticostriatal dopamine network for psychostimulant-enhanced human cognitive flexibility. Biol Psychiatry 74(2):99-105.
35. Ranaldi R, Beninger RJ (1993) Dopamine D1 and D2 antagonists attenuate amphetamine-produced enhancement of responding for conditioned reward in rats. Psychopharmacology (Berl) 113(1):110-118.
36. MacRae PG, Spirduso WW, Wilcox RE (1988) Reaction time and nigrostriatal dopamine function: The effects of age and practice. Brain Res 451(1-2):139-146.
37. Servan-Schreiber D, Carter CS, Bruno RM, Cohen JD (1998) Dopamine and the mechanisms of cognition: Part II. D-amphetamine effects in human subjects performing a selective attention task. Biol Psychiatry 43(10):723-729.
38. Bartels C, Wegrzyn M, Wiedl A, Ackermann V, Ehrenreich H (2010) Practice effects in healthy adults: A longitudinal study on frequent repetitive cognitive testing. BMC Neurosci 11:118.
39. Dayan P (2012) Twenty-five lessons from computational neuromodulation. Neuron 76(1):240-256.
40. Eckart C, Bunzeck N (2013) Dopamine modulates processing speed in the human mesolimbic system. Neuroimage 66:293-300.
41. Farrell SM, Tunbridge EM, Braeutigam S, Harrison PJ (2012) COMT Val(158)Met genotype determines the direction of cognitive effects produced by catechol-O-methyltransferase inhibition. Biol Psychiatry 71(6):538-544.
42. Godden DR, Baddeley AD (1975) Context-dependent memory in two natural environments: On land and underwater. Br J Psychol 66(3):325-331.
43. Rosenthal R (1979) The file drawer problem and tolerance for null results. Psychol Bull 86(3):638-641.
44. Folstein MF, Folstein SE, McHugh PR (1975) "Mini-mental state." A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12(3):189-198.
45. Smith SM, et al. (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl 1):S208-S219.
46. Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM (2012) FSL. Neuroimage 62(2):782-790.
47. Churchill NW, Strother SC (2013) PHYCAA+: An optimized, adaptive procedure for measuring and controlling physiological noise in BOLD fMRI. Neuroimage 82:306-325.
48. Efron B, Tibshirani R (1993) An Introduction to the Bootstrap (Chapman & Hall/CRC, Boca Raton, FL).