Complexity Changes in Human Wrist Temperature Circadian Rhythms through Ageing - Foundations on Natural and Artificial Computation - page 408

5 Conclusions
We have presented a study about complexity changes in human wrist tempera-
ture circadian rhythms through ageing. The main contributions in this work is
the introduction of some measures of instantaneous phase complexity, based on
Hilbert transform and CWT. LZHP phase complexity is decoupled from global
signal complexity, thus providing independent information. Our results consis-
tently show a decrease in phase complexity with age.
Previous works [19,2] have studied ApEn and DFA in circadian skin tempe-
rature records. In our case, we have analyzed larger records (7 d vs 30 h ), with
special emphasis in the signal bandwidth, surrogate tests and phase complexity.
Weinert [20] has signaled that the changes in circadian rhythms when ageing
appear related to changes within the SCN central pacemaker. The total number
of neurons in SCN does not change with age, so changes must be due either
to changes in the molecular clock inside the cells or to alterations in the cou-
pling mechanism between individual neurons. On the one hand, there is strong
evidence showing that the molecular clockwork inside the cells remains unaf-
fected with age. On the other hand, experimental work shows that the coupling
mechanism between neurons deteriorates with age, and that both neuronal fir-
ing rates and neurotransmitters production in neurons involved in the circadian
pacemaker also decreases. Weinert concludes that the ability of the aged SCN
to transmit the circadian signal to peripheral systems may be diminished [20].
We are tempted to conjecture that in these circumstances, the simpler periph-
eral clocks could acquire prominence over the central pacemaker signaling, thus
exhibiting decreased complexity and increased regularity.
References
1. Cao, L.: Practical method for determining the minimum embedding dimension of
a scalar time series. Physica D: Nonlinear Phenomena 110(1-2), 43-50 (1997)
2. Cuesta, D., Varela, M., Miro, P., Galdos, P., Abasolo, D., Hornero, R., Aboy,
M.: Predicting survival in critical patients by use of body temperature regularity
measurement based on approximate entropy. Medical and Biological Engineering
and Computing 45(7), 671-678 (2007)
3. Fraser, A.M., Swinney, H.L.: Independent coordinates for strange attractors from
mutual information. Physical Review A 33(2), 1134-1140 (1986)
4. Gonze, D., Goldbeter, A.: Entrainment versus chaos in a model for a circa-
dian oscillator driven by light-dark cycles. Journal of Statistical Physics 101(1),
649-663 (2000)
5. Hofman, M.A., Swaab, D.F.: Living by the clock: the circadian pacemaker in older
people. Ageing Research Reviews 5(1), 33-51 (2006)
6. Huang, Y.L., Liu, R.Y., Wang, Q.S., Van Someren, E.J.W., Xu, H., Zhou, J.N.:
Age-associated difference in circadian sleep-wake and rest-activity rhythms. Phys-
iology & Behavior 76(4-5), 597-603 (2002)
7. Keylock, C.J.: A wavelet-based method for surrogate data generation. Physica D:
Nonlinear Phenomena 225(2), 219-228 (2007)