Neuroimaging Markers of Cognitive Reserve and Brain Aging Lihong Wang Department of Psychiatry 09/05/2018

Overview Neural Compensatory Activation & Cognitive Reserve Semi-quantitative Measure of Neural Compensation Physical Exercise & Neural Compensatory Activation Future Directions

Cognitive Aging Park et al, Psychol Aging, 2002; Dialogues Clin Neurosci. 2013

Structural Changes across Life Span Sowell et al, Nat Neurosci, 2003

Over-Activation in Older Adults HAROLD (hemispheric asymmetry reduction in older adults) model – Cabeza, 2002

Compensatory or Deficiency Rossi, et al, J Neurosci,2005 Cabeza, NeuroImage, 2002

Task demands Brain Activation Compensation Successful Compensation Failure Brain Activation Older Younger

(Compensation-Related Utilization of Neural Circuits) The CRUNCH model (Compensation-Related Utilization of Neural Circuits) Mattay, et al. Neurosci Lett 2006

Reserve Capaticy Cognitive Reserve Brain Function Reserve Brain Reserve Brain Structures Stern Y, Neuropsychologia. 2009; Lancet Neurol. 2012

Quantitative Measure of Cognitive Reserve -Decomposing Episodic Memory Variance  Residual Variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes) x1: education, sex x2: gray matter volume, hippocampus volume, WMH Reed B.R., et al, 2010 High Residual Reserve ∞ higher reading ability, lower likelihood of MCI, lower odds of dementia conversion independent of age, and less decline in language abilities over 3 years Zahodne, et al, J Int Neuropsychol Soc, 2014

Network-based Neural Compensation Model Compensatory Networks Aging/Neurodegeneration

Participants: healthy older adults > 60 yrs N=26 Neuropsych test MMSE HVLT-R Immediate and Delayed Story Recall WAIS-III Digital symbol Trail Making Test Stoop test Mood State POM Gait Speed 6MWT

Cognitively Challenging Task Involved whole brain – attentional working memory Ji et al. Front. Aging Neurosci., 2018 

Task Activations Encoding Retrieval Involved whole brain – attentional working memory

Correlations to the hemodynamic response the task design Neural Networks – Independent Component Analysis (ICA) Spatial ICA 15 components 26 subjects Correlations to the hemodynamic response the task design Networks’ time courses showing significant correlations to task design (p<0.001) were counted as task-related networks Number of activated networks of each subject Activation rate of each network ICA – count the network

Validation of Threshold

Compensatory Capacity Why we want to control the core networks volume Compensatory capacity was defined as the number of activated networks in the challenging task controlled with core networks’ volume.

Compensatory Capacity & Cognitive Reserve x1: education, sex x2: gray matter volume, hippocampus volume Reed B.R., et al, 2010 1.5 Good Performance Poor Performance 25-50% 1 50-75% More Network 0.5 Cognitive Reserve Only one for quantitative to cognitive reserve Fewer Network -0.5 -1 Fewer Network More Network

Working Memory 6 MWT Compensatory capacity Compensatory capacity 21 17 13 9 5 -3 -2 -1 1 2 r16= 0.528, p=0.035 700 300 500 100 -2 2 6 MWT r16= 0.660, p=0.015 Compensatory capacity Only one for quantitative to cognitive reserve

The Effect of Physical Exercise on Neural Compensation

Participants: healthy older adults > 60 yrs N=25 Dance training First T1/fmri scan Second T1/fmri scan Output measures Cognition Gait speed Mood state Week0 Week6 Ji et al. Int J. Geriatric Psychiatry, 2018

Memory function

Physical Exercise Increases Gait Speed, Memory, and Cognitive Reserve in Older Adults Motor Cortices Cerebellum Memory function Gait Speed X-box Pre-exercise Post-exercise 0.35 0.65 0.76 0.94 Activated ratio of motor cortices Activated ratio of cerebellum J Int Geriatric Psychiatry, 2018 13 12 11 10 9 8 7 6 5 Pre-exercise Post-exercise Logical Memory Individual subject Average

Summary We proposed a new data-driven measure for neural compensatory capacity using a highly cognitive-demanding task and a brain network-based approach. We demonstrated that our neural compensatory capacity measure is correlated with cognitive function as well as gait speed. We also demonstrated that physical exercise may improve cognitive function through increasing neural compensatory capacity in older adults.

Motor System with Cognition & Aging

Ji et al. Front Aging Neurosci. 2017

Exercise Improved Executive Function and Memory

Structural MRI Results

Resting-State ALFF ALFF change in Striatum / Caudate/Insula

Resting-State ReHo ReHo change in PCC / Precuneus ReHo change in Caudate/Thalamus

Functional Connectivity

Functional Connectivity

Correlation with Cognitive Improvement

Index of Aging 44-73 years

Index of Aging Predicted Age Random Forest Analysis Actual Age (years) The correlation of predicted age based on these imaging data and actual age was 0.92 in the training set, and was 0.72 in the test set. Unpublished data

Index of Aging

Future Directions Validate our neural compensatory capacity measure in MCI, AD, and late-life depression Refine index of aging- combines Random Forest imputation and LASSO Clarifying the relationship between sensorimotor network with cognitive function

Resource of Attention Bias (RAB) RAB= FC (RAI-RDLPFC) + FC (RAI-PCC) RAB (Post-Pre Math) RAB (ATD – Control)

Stress level_ 24months RAB RAB r40=0.41, p=0.007 r34=0.35, p=0.039 Unpublished data

Acknowledgement Tsinghua University UCHC ONRC/IOL Lanxin Ji David Steffens Godfrey Pearlson Xue Zhang Kevin Manning Keith Hawkins Hua Guo NSFC 31271080 1R01MH098391-01A1

Thank you for your attention!!!