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Cognitive-Motor Associations and Predictors of Motor Aging

This article provides a brief overview of the relationship between cognitive function, gait, and falls in aging. It discusses methodological issues, recent research findings, and the importance of identifying predictors and modifiable factors to improve assessments and interventions. The article also highlights the role of cognitive functions in gait and falls and the need for multidisciplinary approaches.

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Cognitive-Motor Associations and Predictors of Motor Aging

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  1. A three-level approach to identifying predictors/mechanisms of motor aging 1. Clinical Neuropsychology 2. Cognitive Neuroscience 3. Genetics Roee Holtzer Ferkauf and the Department of Neurology, Albert Einstein College of Medicine/Yeshiva University

  2. Brief overview of cognition gait and falls in aging • Methodological issues related to examining associations between cognitive and motor function • Review recent work in our Lab examining: • A) cognitive motor associations – clinical NP • B) Contributions of the cognitive neuroscience approach • C) genetics (COMT) associations with cognition and gait

  3. Why study the relationship between cognitive function gait and falls in aging? Gait impairment and falls result in: * Loss of functional independence (Alexander et al. 2005) *Increase risk of hospitalization, nursing home placement, and death (Fuller, 2000; Kramer et al., 1997) *Annual expenditures estimated to be 32 billion dollars by year 2020(Englander et al. 1996) *Fall prevention and gait rehabilitation programs have had modest success(Tinetti et al. 1994)

  4. Hence, it is of vital public health importance to identify etiological and possibly modifiable factors of decline in gait and falls as a prelude towards formulating more effective assessments and interventions.

  5. Cognitive functions: • Can be measured objectively • Potential candidates for pharmacological intervention and cognitive rehabilitation • Provide insight into neural networks sharedbyspecific cognitive and motor function whereas multidisciplinary risk assessment and interventions of falls focus on gait, balance and strength, neuropsychological assessment, with the exception of gross evaluation of dementia status, is conspicuously absent

  6. What do we know about cognition gait and falls in aging ·Walking is associated with a lower risk of dementia in men (Abbott et al. 2004)and women (Weuve et al. 2004) ·Gait abnormality predicts dementia (Verghese et al. 2002) ·Dementia is related to the risk of falls (e.g., Tinetti et al. 1988) However the directionality of the relationship is not clear!

  7. A number of studies examined the interplay between specific cognitive processes gait and falls *Focus is on attention *Most studies relied on dual-task methodology Main Conclusion: Greater dual-task costs in old compared to young individuals suggest that impaired attention is related to decline in gait and to the risk of falls in aging However…..

  8. The following issues have to be considered ·Understanding dual-task costs requires that we: a) Manipulate the extent of interference b) Characterize the primary single tasks c) Task prioritization effects ·Attention is a complex construct ·Other cognitive domains?

  9. DMS Task – Manipulating interference True positive 2-shape study set or True negative 4 Sec 10 Sec 5 Sec 5 Sec ITI Stimulus Set Retention Probe Partial Interference PI Complete Interference CI

  10. Manipulating the extent of dual-task interference DMS: working memory paradigm (Holtzer, Stern & Rakitin; Memory & Cognition, 2004)

  11. Characterize the primary single tasks DMS: working memory paradigm Standardized neuropsychological tests were submitted to factor analysis Four factors were empirically derived: 1) memory 2) attention/executive 3) general cognitive status 4) reaction time (Holtzer, Stern & Rakitin; Neuropsychology, 2005)

  12. Characterize the primary single tasks DMS: working memory paradigm The memory factor was the most powerful predictor of age-related performance differences in the single condition of the DMS The attention/executive factor was the most powerful (but not exclusive)predictor of age-related performance differences in the complete dual-task condition of the DMS (Holtzer, Stern & Rakitin; Neuropsychology, 2005)

  13. Walking While Talking: Effect Of Task Prioritization In The Elderly * Walking speed was affected by task prioritization instructions: * 28% change compared to baseline when subjects were asked to pay equal attention to both tasks * 22% change compared to baseline when subjects were asked to prioritize walking (Verghese, Kuslansky, Holtzer, et al., Arch Phys Med Reha; 2007)

  14. Walking Paradigm (Gaitrite systems) • Subjects were tested in two walking conditions: • Alone • Interference (walking while talking)

  15. Conceptualizing motor outcomes of interest Gait performance:ability to walk in uninterrupted conditions Gait adaptability:ability to maintain locomotion in the presence of cognitiveand environmental perturbations

  16. Approach Orthogonal cognitive factors served as predictors in linear multiple regressions • A) Meaningful data reduction • B) Cognitive domains are orthogonal • C) Cognitive function is adequately sampled • D) Provide direction to future hypothesis testing Gait velocity in the alone and interference conditions served as dependent measures in separate regression models

  17. Cognitive function: PCA Verbal IQ: 26% of the variance S/executive attention: 23% of the variance Verbal Memory: 13% of the variance

  18. Cognitive functions predicting gait velocity Adjusted for demographic covariates and clinical gait abnormality (Holtzer, Verghese, Xue, Lipton; Neuropsychology, 2006)

  19. Conclusions * Cognitive correlates of gait are complex and NOT limited to attention only * Association between cognition and gait varies as a function of walking condition * Relationship is consistent with the knowledge of neuroanatomical substrate underlying cognitive processes and gait

  20. Cognition and falls (Verghese, et al., Am Geriatr Soc 2002)

  21. Cognitive functions and falls Single falls Recurrent falls (Holtzer, Friedman, Lipton, Katz Verghese;Neuropsychology, 2007)

  22. Conclusions *S/Executive attention is the single most powerful predictor of falls (failure of gait adaptability) in non-demented elders *Verbal IQ was also related to recurrent falls *Memory was NOT related to the risk of falls

  23. Gait performance Gait adaptability Failure of Gait adaptability S/Executive attention S/Executive attention S/Executive attention Memory Memory Cognitive reserve? Verbal IQ

  24. Implication of the current findings Clinical Neuropsychology Genetics Cognitive Neuroscience Specific attention networks DA pathways COMT genotype

  25. Cognitive NeuroscienceSpecific Attention Networks Function Structures Modulator Orient Superior parietal Acetylcholine Temporal parietal junction Frontal eye fields Superior colliculus Alert Locus coeruleus Norepinephrine Right frontal Parietal cortex Executive/ Anterior cingulate Dopamine Attention Lateral ventral Prefrontal Basal ganglia Posner and Rotbbart, 2007

  26. ANT - Procedure (Fan et al., 2002)

  27. ANT -Networks correlations ANT -Networks correlations with NP

  28. Implication of the current findings Clinical Neuropsychology Genetics Cognitive Neuroscience Specific attention networks DA pathways COMT genotype

  29. Genetics: relation of COMT genotype polymorphism to cognition and gait Attention/Executive Verbal IQ Memory Gait Velocity COMT Met/Met (n=51).396 (.16) .13 (.16) -.18 (.18) 91.1 (2.8) Met/Val (n=144) .18 (.09) -.09 (.09) -.01 (.09) 100.3 (2.1) Val/Val (n=94) -.09 (.12) -.05 (.13) .02 (.12) 97.1 (2.3) *Cognitive factor scores are standardized regression scores with a mean of 0 and SD of 1. Higher factor scores indicate better cognitive performance.

  30. Logistic regression using COMT genotype to predict executive attention and gait velocity

  31. Regression analyses: fatigue scores predicting working memory performance in each of the three DMS conditions controlling for age and depression. _________________________________________________ DMS Alone PI CI Fatigue -0.182 0.50+ 0.645* Depression 0.698* 0.006 -0.118 Age -0.186 0.307 -0.061 _________________________________________________ • *<.05 • + = marginal p=0.065

  32. Correlations between total fatigue scores (self-report) and attention networks in aging. __________________________________________________________________ ANT (RT ms) Alerting Orienting E/attention Subjects (n=32) Fatigue (M=3.9 SD=2.3 ) -0.159 -0.305 0.359* __________________________________________________________________ Fatigue - assessed immediately after administering the ANT ANT= Attention Network Test *<.05

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