A Dynamical Systems Approach to Aging and Frailty

Fragilité
et
Préven.on
de
la
Dépendance
chez
le
Sujet
Agé


 Marseille
3‐4
Avril
2014


A Dynamical Systems Approach to Aging and Frailty Prof.
Jean‐Jacques
Temprado
 Institute of Movement Sciences Aix Marseille University - Faculty of Sport Sciences – Marseille - France

e‐mail:
jean‐jacques.temprado@univ‐amu.fr


Current definitions of Frailty Frailty: “a clinically recognizable state of increased vulnerability, resulting from age-related decline functions across, multiple systems, such as the ability to cope with stressors is compromised” Frailty: a clinical syndrome of multiple subsystems dysfunctions (MODS, Buchman, 1996)

How to address age- and frailty-related changes in the systemic organization of the whole NMSS?

Current approaches consider aging as a sum of alterations in separate sub-systems

As a consequence of this component-dominant approach, aging research is a puzzle of knowledge. It is data rich and theoretically poor.

Frailty: a collection of dysfunctions in multiple, separate sub-systems - Cumulative logic: aggregate dysfunction Cognitive decline?

- Component-dominant approach to Frailty (cognitive frailty, physical frailty…) - In search of a (behavioral) phenotype and low level, biological factors of Frailty.

Gait speed Weight loss Low energy Low Physical Activity Fatigability

Low strength

Do we know exactly what Aging and Frailty are, if not simply the sum of alterations in separate sub-systems?

Working hypothesis Frailty is a syndrome of neuro-behavioral dysfunctioning. It reflects a failure in interactions/ couplings within and between the functional subsystems of the neuro-musculo-skeletal system

Evidence supporting such a view of Aging and Frailty - Interaction-dominant approach: “Frailty… is a dysregulation of the dynamic interactions within and across the complex adaptive system” (e.g., Fried et al., 2009; Varadhan et al., 2008). - Time-evolution (dynamics) and phase transition in individual trajectory: “Frailty is a transitional state in the progression from robustness to functional decline” (e.g., Lang et al., 2009). - Loss of adaptability (balance stability-flexibility): lack of resistance to perturbation, lack of resilience, reduced compensation capacity, loss of redundancy (e.g., Fried et al., 2005). - Dimensional reduction of system’s complexity: search for a few common causal factors (e.g., inflam-aging) to multi-system alterations (e.g., sarcopenia-cognitive decline) (e.g., Abellan van Kan et al., 2013; Fried et al., 2009).

How to test this hypothesis?

The theoretical framework of Complexity Theories (CT) and Nonlinear Dynamical Systems (NLDS) CT and NLDS: aim at describing and explaining how (behavioral) patterns resulting from coupling interactions form, adapt and change over time in complex systems

The NMSS is a self-organizing, complex system composed of (complex) interacting/coupled sub-systems

NMSS Dynamics: from robustness to frailty: How one system’s state develops into another state over the course of time?

Hypothesis Frailty

Aging and Frailty result in a (progressive?) breakdown of coupling and loss of redundancy of DOF, so that the NMSS and its sub-systems lose complexity, stability and flexibility.

How to study age-related changes in the Dynamics of the Complex NMSS?

Internal mechanisms

Functional markers Neuro-behavioral level

Mechanisms of age-related changes in subsystems organization (Sleimen-Malkoun et al., 2014)

Loss of Complexity “The process by which the redundancy of the system, the links between the components and the circulation of information (coupling) are altered, thereby impairing system’s adaptability”

Dedifferentiation “The process by which structures, mechanisms that were specialized for a given function lose their specialization and become simplified, less distinct and common to different functions”

Markers of age- and frailty related loss of complexity and dedifferentiation Behavioral output fluctuations Changes in amplitude and regularity of behavioral fluctuations (variability) are hypothesized to provide information about: i) noise and ii) modifications of functional organization of interacting components (couplings) in the system, respectively

Entropy versus variability measures

‐  
 The
 larger
 the
 entropy,
 the
 more
 irregular
 the
 fluctua4ons,
 the
 less
 predictable
the
system.

 ‐  
 Changes
 in
 irregularity
 are
 usually
 considered
 as
 reflec4ng
 changes
 in
 system’s
 organiza4onal
 complexity
 (Vaillancourt
&
Newell,
2002).


The Loss of Complexity Hypothesis (Lipsitz & Goldberger, 1992; Newell et al., 2006; Rey-Robert et al., 2011; Vaillancourt & Newell, 2002)

Complexity, information transmission efficiency, cognitive load and force control The optimal Signal to Noise ratio corresponds to a specific % of MVC and to the optimal complexity of force fluctuations

Application to gait speed and cognitive load

Complexity and Adaptability Optimal complexity confers an important advantage to the system with respect to the capability to preserve stability and flexibility.

+ -

Markers of Dedifferentiation Dimensional
reducJon:
A
Dynamical
Principle
 underlying
Aging
and
Frailty


Dimensional reduction in cognitive and motor systems

Increased cognitive-motor interactions. Common cause(s) hypothesis.

Dimensional reduction in brain functioning

Dimensional reduction in muscular functioning Age-related dedifferentiation in muscle structure and function (Lexell, 1995). Homogeneity in contractile rate and force generation capacity.

Consequences on the assembly of neuro-muscular synergies

Dimensional reduction in behavioral responses

Inability to maintain specific behavioral patterns when task constraints increase

Dimensional reduction in behavioral repertoire

How to apply this framework to the study of Frailty? The Coord-Age Project

UMR INSERM 1106

Centre Gérontologique Départemental

UMR CNRS 7287

Working hypothesis 1: Aging and Frailty: a dynamic reorganization in the NMSS Dedifferentiation-Loss of complexity

Working hypothesis 2: Frailty: a model a Loss of Complexity and Dimensional reduction A macroscopic dynamics captured by the behavioral landscape

Sleimen-Malkoun et al. (2014) adapted from Lipsitz (2002)

Working hypothesis 3: Transition to frailty can be characterized by changes in Coordination Dynamics within and between brain, muscular and behavioral levels

A General Research Strategy

* Objective: understanding system(s) dysfunction underlying the dynamics of aging and frailty * Same concepts, methods and variables to explore individual systems dynamics and cross-systems interactions (complex fluctuations, pattern dynamics, behavioral repertoire….) . * Perspectives: exploring how to restore complexity and differentiation through specific training programs: physical activity, multi-systems interventions (notion of complexity reserve).

Take home message…

Thanks to… People involved in the Coord-Age project: - Permanent: JJ Temprado (ISM, Project Coordinator), V. Jirsa (INS), R. Huys (INS), G. Rao (ISM), F. Retornaz (CGD13) - Post-doc and engineers: R. Sleimen-Malkoun (ISM-INS), S. Vieluf (ISM), Carlijn Vernooij (ISM), D. Perdikis (INS), Spase Petkovksi (INS).

Special thanks to R. Sleimen-Malkoun and F. Retornaz Selected References (available on Research Gate page) Sleimen-Malkoun, Temprado, J.J., R., & Hong, S.L. (2014). Frontiers in Aging Neurosciences. Temprado, J.J., Sleimen-Malkoun R, Lemaire P, Rey-Robert B, Retornaz F, Berton E. (2013). Experimental Brain Research. Sleimen-Malkoun R, Temprado JJ, & Berton E (2103). Frontiers in Aging Neurosciences. Sleimen-Malkoun R, Temprado JJ, Berton E (2013). BMC Neurosciences Rey-Robert, B, Temprado, JJ, & Berton, E (2011). Medicina. Rey-Robert, B, Temprado, JJ, Lemaire, P, & Berton, E (2011). Gerontology.