Stephen Aichele
Cited by
Cited by
Intensive meditation training improves perceptual discrimination and sustained attention
KA MacLean, E Ferrer, SR Aichele, DA Bridwell, AP Zanesco, TL Jacobs, ...
Psychological science 21 (6), 829-839, 2010
Intensive meditation training, immune cell telomerase activity, and psychological mediators
TL Jacobs, ES Epel, J Lin, EH Blackburn, OM Wolkowitz, DA Bridwell, ...
Psychoneuroendocrinology 36 (5), 664-681, 2011
Enhanced response inhibition during intensive meditation training predicts improvements in self-reported adaptive socioemotional functioning.
BK Sahdra, KA MacLean, E Ferrer, PR Shaver, EL Rosenberg, TL Jacobs, ...
Emotion 11 (2), 299, 2011
Interactions between endogenous and exogenous attention during vigilance
KA MacLean, SR Aichele, DA Bridwell, GR Mangun, E Wojciulik, ...
Attention, Perception, & Psychophysics 71 (5), 1042-1058, 2009
Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity
M Saggar, BG King, AP Zanesco, KA MacLean, SR Aichele, TL Jacobs, ...
Frontiers in human neuroscience 6, 256, 2012
Intensive meditation training influences emotional responses to suffering.
EL Rosenberg, AP Zanesco, BG King, SR Aichele, TL Jacobs, ...
Emotion 15 (6), 775, 2015
Self-reported mindfulness and cortisol during a Shamatha meditation retreat.
TL Jacobs, PR Shaver, ES Epel, AP Zanesco, SR Aichele, DA Bridwell, ...
Health Psychology 32 (10), 1104, 2013
Meditation training influences mind wandering and mindless reading.
AP Zanesco, BG King, KA MacLean, TL Jacobs, SR Aichele, BA Wallace, ...
Psychology of Consciousness: Theory, Research, and Practice 3 (1), 12, 2016
Think fast, feel fine, live long: A 29-year study of cognition, health, and survival in middle-aged and older adults
S Aichele, P Rabbitt, P Ghisletta
Psychological science 27 (4), 518-529, 2016
Predicting cognitive impairment and dementia: A machine learning approach
D Aschwanden, S Aichele, P Ghisletta, A Terracciano, M Kliegel, AR Sutin, ...
Journal of Alzheimer's Disease 75 (3), 717-728, 2020
Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training
M Saggar, AP Zanesco, BG King, DA Bridwell, KA MacLean, SR Aichele, ...
NeuroImage 114, 88-104, 2015
Predictors of depression among middle-aged and older men and women in Europe: a machine learning approach
EP Handing, C Strobl, Y Jiao, L Feliciano, S Aichele
The Lancet Regional Health–Europe 18, 2022
Life span decrements in fluid intelligence and processing speed predict mortality risk.
S Aichele, P Rabbitt, P Ghisletta
Psychology and Aging 30 (3), 598, 2015
Memory deficits precede increases in depressive symptoms in later adulthood
S Aichele, P Ghisletta
The Journals of Gerontology: Series B 74 (6), 943-953, 2019
Dementia incidence, burden and cost of care: a Filipino community-based study
J Dominguez, L Jiloca, KC Fowler, MF De Guzman, JK Dominguez-Awao, ...
Frontiers in Public Health 9, 628700, 2021
Fluid intelligence predicts change in depressive symptoms in later life: The Lothian birth cohort 1936
S Aichele, P Ghisletta, J Corley, A Pattie, AM Taylor, JM Starr, IJ Deary
Psychological Science 29 (12), 1984-1995, 2018
A tutorial for joint modeling of longitudinal and time-to-event data in R
S Cekic, S Aichele, AM Brandmaier, Y Köhncke, P Ghisletta
arXiv preprint arXiv:1909.05661, 2019
Illness and intelligence are comparatively strong predictors of individual differences in depressive symptoms following middle age
S Aichele, P Rabbitt, P Ghisletta
Aging & mental health 23 (1), 122-131, 2019
Attitudinal and behavioral characteristics predict high risk sexual activity in rural Tanzanian youth
SR Aichele, M Borgerhoff Mulder, S James, K Grimm
PloS one 9 (6), e99987, 2014
Quantitative methods in psychological aging research: a mini-review
P Ghisletta, S Aichele
Gerontology 63 (6), 529-537, 2017
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