David Joseph Madden
Professor of Medical Psychology in the Department of Psychiatry and Behavioral Sciences
The behavioral measures have focused on reaction time, with the goal of distinguishing age-related changes in specific cognitive abilities from more general effects arising from a slowing in elementary perceptual processes. The cognitive abilities of interest include selective attention as measured in visual search tasks, semantic and episodic memory retrieval, and executive control processes.
The behavioral measures are necessary to define the cognitive abilities of interest, and the neuroimaging techniques help define the functional neuroanatomy of those abilities. The PET and fMRI measures provide information regarding neural activity during cognitive performance. DTI is a recently developed technique that images the structural integrity of white matter. The white matter tracts of the brain provide critical pathways linking the gray matter regions, and thus this work will complement the studies using PET and fMRI that focus on gray matter activation.
A current focus of the research program is the functional connectivity among regions, not only during cognitive task performance but also during rest. These latter measures, referred to as intrinsic functional connectivity, are beginning to show promise as an index of overall brain functional efficiency, which can be assessed without the implementation of a specific cognitive task. From DTI, information can be obtained regarding how anatomical connectivity constrains intrinsic functional connectivity. It will be important to determine the relative influence of white matter pathway integrity, intrinsic functional connectivity, and task-related functional connectivity, as mediators of age-related differences in behavioral measures of cognitive performance.
Ultimately, the research program can help link age-related changes in cognitive performance to changes in the structure and function of specific neural systems. The results also have implications for clinical translation, in terms of the identification of neural biomarkers for the diagnosis of neural pathology and targeting rehabilitation procedures.
Neuroimaging of Visual Attention in Aging awarded by National Institutes of Health (Principal Investigator). 2011 to 2023
Neurobehavioral Mechanisms of Emotion Regulation in Depression across the Adult Lifespan awarded by National Institutes of Health (Co Investigator). 2017 to 2022
Quantitative Susceptibility Mapping of Iron Accumulation in Neurocognitive Aging awarded by National Institutes of Health (Principal Investigator). 2017 to 2020
Neuroimaging of Age-Related Changes in Language awarded by Pennsylvania State University (Principal Investigator). 2017 to 2020
Cognitive Changes and Brain Connectivity in Age-Related Macular Degeneration awarded by National Institutes of Health (Co Investigator). 2013 to 2019
Imaging of Intrinsic Connectivity Networks awarded by National Institutes of Health (Co Investigator). 2011 to 2018
Dorsal Cingulate Activity and Cognitive Decline in Late-Life Depression awarded by National Institutes of Health (Principal Investigator). 2012 to 2018
Effects of Aging on Visual Memory: Neuroimaging Studies awarded by National Institutes of Health (Co Investigator). 2001 to 2018
A Compute Cluster for Brain Imaging and Analysis awarded by National Institutes of Health (Major User). 2016 to 2017
Neural Substrates Associated with Executive Functioning in Marijuana and HIV awarded by National Institutes of Health (Investigator). 2014 to 2016
Madden, D. J., et al. “Age-related changes in neural activity during visual perception and attention.” Cognitive Neuroscience of Aging: Linking Cognitive and Cerebral Aging, 2005. Manual, doi:10.1093/acprof:oso/9780195156744.003.0007. Full Text
Madden, D. J., and E. L. Parks. “Age differences in structural connectivity: Diffusion tensor imaging and white matter hyperintensities.” Cognitive Neuroscience of Aging: Linking Cognitive and Cerebral Aging (2nd Ed.), translated by R. Cabeza et al.
Zuo, Xintong, et al. “Relationship between neural functional connectivity and memory performance in age-related macular degeneration.” Neurobiol Aging, vol. 95, Nov. 2020, pp. 176–85. Pubmed, doi:10.1016/j.neurobiolaging.2020.07.020. Full Text
Madden, David J., et al. “Influence of structural and functional brain connectivity on age-related differences in fluid cognition.” Neurobiol Aging, vol. 96, Sept. 2020, pp. 205–22. Pubmed, doi:10.1016/j.neurobiolaging.2020.09.010. Full Text
Madden, David J., et al. “Response-level processing during visual feature search: Effects of frontoparietal activation and adult age.” Atten Percept Psychophys, vol. 82, no. 1, Jan. 2020, pp. 330–49. Pubmed, doi:10.3758/s13414-019-01823-3. Full Text
Madden, David J., et al. “Neural activation for actual and imagined movement following unilateral hand transplantation: a case study.” Neurocase, vol. 25, no. 6, Dec. 2019, pp. 225–34. Pubmed, doi:10.1080/13554794.2019.1667398. Full Text Open Access Copy
Diaz, Michele T., et al. “Age-related differences in the neural bases of phonological and semantic processes in the context of task-irrelevant information.” Cogn Affect Behav Neurosci, vol. 19, no. 4, Aug. 2019, pp. 829–44. Pubmed, doi:10.3758/s13415-018-00671-2. Full Text
Zhuang, Jie, et al. “Language processing in age-related macular degeneration associated with unique functional connectivity signatures in the right hemisphere.” Neurobiol Aging, vol. 63, Mar. 2018, pp. 65–74. Pubmed, doi:10.1016/j.neurobiolaging.2017.11.003. Full Text Open Access Copy
Monge, Zachary A., et al. “Functional modular architecture underlying attentional control in aging.” Neuroimage, vol. 155, July 2017, pp. 257–70. Pubmed, doi:10.1016/j.neuroimage.2017.05.002. Full Text
Cordero, Daniella M., et al. “Cocaine dependence does not contribute substantially to white matter abnormalities in HIV infection.” J Neurovirol, vol. 23, no. 3, June 2017, pp. 441–50. Pubmed, doi:10.1007/s13365-017-0512-5. Full Text
Siciliano, Rachel E., et al. “Task difficulty modulates brain activation in the emotional oddball task.” Brain Research, vol. 1664, June 2017, pp. 74–86. Epmc, doi:10.1016/j.brainres.2017.03.028. Full Text Open Access Copy
Madden, David J., et al. “Sources of disconnection in neurocognitive aging: cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume.” Neurobiol Aging, vol. 54, June 2017, pp. 199–213. Pubmed, doi:10.1016/j.neurobiolaging.2017.01.027. Full Text Open Access Copy
Cunha, P. P., et al. “Discrepancy between self-reported vision and visual acuity in patients with age-related macular degeneration.” Journal of the American Geriatrics Society, vol. 66, WILEY, 2018, pp. S315–S315.
Diaz, Michele T., et al. “FUNCTIONAL AND BEHAVIORAL AGE-RELATED CHANGES IN PHONOLOGICAL AND SEMANTIC PROCESSES UNDER DISTRACTING CONDITIONS.” Journal of Cognitive Neuroscience, MIT PRESS, 2013, pp. 223–223.
Johnson, Micah A., et al. “DIFFUSION TENSOR IMAGING (DTI) OF CEREBRAL WHITE MATTER INTEGRITY: GLOBAL VERSUS TRACT-SPECIFIC EFFECTS AND MEDIATION OF AGE-RELATED SLOWING.” Journal of Cognitive Neuroscience, MIT PRESS, 2013, pp. 222–222.
Bucur, B., et al. “Age-related decreases in cerebral white matter integrity: Implications for episodic and semantic retrieval processes.” Journal of Cognitive Neuroscience, M I T PRESS, 2005, pp. 234–234.
Madden, D. J. Frontoparietal activation during visual conjunction search: Effects of bottom-up guidance and adult age. Edited by E. L. Parks et al.