Autonomic pain responses during sleep: a study of heart rate variability

The autonomic nervous system (ANS) reacts to nociceptive stimulation during sleep, but whether this reaction is contingent to cortical arousal, and whether one of the autonomic arms (sympathetic/parasympathetic) predominates over the other remains unknown. We assessed ANS reactivity to nociceptive stimulation during all sleep stages through heart rate variability, and correlated the results with the presence of cortical arousal measured in concomitant 32-channel EEG. Fourteen healthy volunteers underwent whole-night polysomnography during which nociceptive laser stimuli were applied over the hand. RR intervals (RR) and spectral analysis by wavelet transform were performed to assess parasympathetic (HF(WV)) and sympathetic (LF(WV) and LF(WV)/HF(WV) ratio) reactivity. During all sleep stages, RR significantly decreased in reaction to nociceptive stimulations, reaching a level similar to that of wakefulness, at the 3rd beat post-stimulus and returning to baseline after seven beats. This RR decrease was associated with an increase in sympathetic LF(WV) and LF(WV)/HF(WV) ratio without any parasympathetic HF(WV) change. Albeit RR decrease existed even in the absence of arousals, it was significantly higher when an arousal followed the noxious stimulus. These results suggest that the sympathetic-dependent cardiac activation induced by nociceptive stimuli is modulated by a sleep dependent phenomenon related to cortical activation and not by sleep itself, since it reaches a same intensity whatever the state of vigilance

A Multi-Resolution Framework for Fractal Image Representation and its applications

The starting point of this paper is the basic fractal coder suggested by Jacquin. The coder finds and encodes the parameters of a partitioned iterated function system (PIFS), which approximates the signal as a fixed-point of a contractive transformation. The work presented here can be divided into two parts. The first part begins with a presentation of the hierarchical structure of the PIFS code. This structure relates the code and its fixed-point in different resolutions. It is shown that there exists a function of a continuous variable which is directly related to the PIFS. It is shown that by properly manipulating this function, called the PIFS embedded-function, one can compute the fixed-points related to the code in any desired resolution. We end the first part with a brief description of several applications, such as a fast non-iterative decoder, a method for fractal interpolation of the signal via its PIFS code, and an improved collage-bound. This research was supported by the ..