Neural Mechanisms Underlying Sensorimotor Synchronization with Different Forms of Rhythms

Introduction: Neural activity exhibits non-periodic rhythm [2] but it is unknown if neural activity synchronizes with non-periodic, as it does with periodic rhythms [1]. The purpose of this research is to determine the neural mechanisms present leading to synchronized finger tapping to varying rhythms. Methods: Twenty young healthy adults will be recruited to participate in the present study (see Figure 1 for the protocol). Electroencephalography (EEG) will be used to measure the amplitude (AE) and beats for interbeat intervals (IBIs), and a pressure sensor will be used to measure intertap intervals (ITIs). The AE will be assessed for activity spike timing called event related potentials (ERPs) to allow for assessment for differences in neural activity timing with a two-way analysis of variance. The AE, ITIs, and IBIs will be assessed with detrended fluctuation analysis (DFA) and compared with a pearson-r correlation. Results and Discussion: Data for the present study is currently in the process of being collected. The DFA of the IBIs, ITIs, ERP, and AE are expected to match to varying degrees but the fractal condition is expected to present the greatest degree of synchronization. Conclusions: This research will give insight into the ability of the brain to complexity match to not only recreate the rhythm of auditory signals within the brain but also with behavior. Fractal and isochronous metronomes may be more readily matched within the brain and behavior because they are more biologically relevant and predictable than the random metronome

Degeneracy and long-range correlations

Degeneracy is a ubiquitous property of complex adaptive systems, which refers to the ability of structurally different components to perform the same function in some conditions and different functions in other conditions. Here, we suppose a causal link between the level of degeneracy in the system and the strength of long-range correlations in its behavior. In a numerical experiment, we manipulated degeneracy through the number of networks available in a model composed of a chain of correlated networks over which a series of random jumps are performed. Results showed that correlations in the outcome series increased with the number of available networks, and that a minimal threshold of degeneracy was required to generate long-range correlations. We conclude that degeneracy could underlie the presence of long-range correlations in the outcome series produced by complex systems. In turn, we suggest that quantifying long-range correlations could allow to assess the level of degeneracy of the system. Degeneracy affords a maybe more intuitive way than former hypotheses for understanding the effects of complexity on essential properties such as robustness and adaptability

Complexity, Coordination, and Health: Avoiding Pitfalls and Erroneous Interpretations in Fractal Analyses

Background and Objective. The analysis of fractal fluctuation has become very popular because of the close relationships between health, adaptability, and long-range correlations. 1/f noise is considered a “magical” threshold, characterizing optimal functioning, and a decrease or conversely and increase of serial correlations, with respect to 1/f noise, is supposed to sign a kind of disadaptation of the system. Empirical results, however, should be interpreted with caution. In experimental series, serial correlations often present a complex pattern, resulting from the combination of long-range and short-term correlated processes. We show, in the present paper, that an increase in serial correlations cannot be directly interpreted as an increase in long-range correlations. Material and Methods. Eleven participants performed four walking bouts following 4 individually determined velocities (slow, comfortable, high, and critical). Series of 512 stride intervals were collected under each condition. The strength of serial correlation was measured by the detrended fluctuation analysis. The effective presence of 1/f fluctuation was tested through ARFIMA modeling. Results. The strength of serial correlations tended to increase with walking velocity. However, the ARFIMA modeling showed that long-range correlations were significantly present only at slow and comfortable velocities. Conclusions. The strength of correlations, as measured by classical methods, cannot be considered as predictive of the genuine presence of long-range correlations. Sometimes systems can present the moderate levels of effective long-range correlations, whereas in others cases, series can present high correlation levels without being long-range correlated

Relative Roughness: An Index for Testing the Suitability of the Monofractal Model

Fractal analyses have become very popular and have been applied on a wide variety of empirical time series. The application of these methods supposes that the monofractal framework can offer a suitable model for the analyzed series. However, this model takes into account a quite specific kind of fluctuations, and we consider that fractal analyses have been often applied to series that were completely outside of its relevance. The problem is that fractal methods can be applied to all types of series, and they always give a result, that one can then erroneously interpret in the context of the monofractal framework. We propose in this paper an easily computable index, the relative roughness (RR), defined as the ratio between local and global variances, that allows to test for the applicability of fractal analyses. We show that RR is confined within a limited range (between 1.21 and 0.12, approximately) for long-range correlated series. We propose some examples of empirical series that have been recently analyzed using fractal methods, but, with respect to their RR, should not have been considered in the monofractal model. An acceptable level of RR, however, is a necessary but not sufficient condition for considering series as long-range correlated. Specific methods should be used in complement for testing for the effective presence of long-range correlations in empirical series

Effect of sampling frequency on fractal fluctuations during treadmill walking

The temporal dynamics of stride-to-stride fluctuations in steady-state walking reveal important information about locomotor control and can be quantified using so-called fractal analyses, notably the detrended fluctuation analysis (DFA). Gait dynamics are often collected during treadmill walking using 3-D motion capture to identify gait events from kinematic data. The sampling frequency of motion capture systems may impact the precision of event detection and consequently impact the quantification of stride-to-stride variability. This study aimed i) to determine if collecting multiple walking trials with different sampling frequency affects DFA values of spatiotemporal parameters during treadmill walking, and ii) to determine the reliability of DFA values across downsampled conditions. Seventeen healthy young adults walked on a treadmill while their gait dynamics was captured using different sampling frequency (60, 120 and 240 Hz) in each condition. We also compared data from the highest sampling frequency to downsampled versions of itself. We applied DFA to the following time series: step length, time and speed, and stride length, time and speed. Reliability between experimental conditions and between downsampled conditions were measured with 1) intraclass correlation estimates and their 95% confident intervals, calculated based on a single-measurement, absolute-agreement, two-way mixed-effects model (ICC 3,1), and 2) Bland-Altman bias and limits of agreement. Both analyses revealed a poor reliability of DFA results between conditions using different sampling frequencies, but a relatively good reliability between original and downsampled spatiotemporal variables. Collectively, our results suggest that using sampling frequencies of 120 Hz or 240 Hz provide similar results, but that using 60 Hz may alter DFA values. We recommend that gait kinematics should be collected at around 120 Hz, which provides a compromise between event detection accuracy and processing time

Reliability of a feedback-controlled treadmill algorithm dependent on the user\u27s behavior

he reliability of the treadmill belt speed using a feedback-controlled treadmill algorithm was analyzed in this study. Using biomechanical factors of the participant\u27s walking behavior, an estimated walking speed was calculated and used to adjust the speed of the treadmill. Our proposed algorithm expands on the current hypotheses of feedback-controlled treadmill algorithms and is presented below. Nine healthy, young adults walked on a treadmill controlled by the algorithm for three trials over two days. Each participant walked on the feedback-controlled treadmill for one 16-minute and one five-minute trial during day one and one 16-minute trial during day two. Mean, standard deviation, interclass correlation coefficient (ICC), and standard error of measurement (SEM) were analyzed on the treadmill belt speed mean, standard deviation, and coefficient of variation. There were significantly high ICC for mean treadmill speed within- and between-days. Treadmill speed standard deviation and coefficient of variation were significantly reliable within-day. These results suggest the algorithm will reliably produce the same treadmill belt speed mean, but may only produce a similar treadmill belt speed standard deviation and coefficient of variation if the trials are performed in the same day. A feedback-controlled treadmill algorithm that accounts for the user\u27s behavior provides a greater level of control and minimizes any possible constraints of walking on a conventional treadmill

Walking speed and spatiotemporal step mean measures are reliable during feedback-controlled treadmill walking; however, spatiotemporal step variability is not reliable

The purpose of the study was to compare the effects of a feedback-controlled treadmill (FeedbackTM) to a traditional fixed-speed treadmill (FixedTM) on spatiotemporal gait means, variability, and dynamics. The study also examined inter-session reliability when using the FeedbackTM. Ten young adults walked on the FeedbackTM for a 5-minute familiarization followed by a 16-minute experimental trial. They returned within one week and completed a 5-minute familiarization followed by a 16-minute experimental trial each for FeedbackTM and FixedTM conditions. Mean walking speed and step time, length, width, and speed means and coefficient of variation were calculated from all experimental conditions. Step time, length, width, and speed gait dynamics were analyzed using detrended fluctuation analysis. Mean differences between experimental trials were determined using ANOVAs and reliability between FeedbackTM sessions was determined by intraclass correlation coefficient. No difference was found in mean walking speed nor spatiotemporal variables, with the exception of step width, between the experimental trials. All mean spatiotemporal variables demonstrated good to excellent reliability between sessions, while coefficient of variation was not reliable. Gait dynamics of step time, length, width, and speed were significantly more persistent during the FeedbackTM condition compared to FixedTM, especially step speed. However, gait dynamics demonstrated fair to poor reliability between FeedbackTM sessions. When walking on the FeedbackTM, users maintain a consistent set point, yet the gait dynamics around the mean are different when compared to walking on a FixedTM. In addition, spatiotemporal gait dynamics and variability may not be consistent across separate days when using the FeedbackTM

Role of Specialized Pro-resolving Mediators in Reducing Neuroinflammation in Neurodegenerative Disorders

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are neurodegenerative disorders that affect millions of individuals worldwide. As incidence of these conditions increases with age, there will undoubtedly be an increased prevalence of cases in the near future. Neuroinflammation is a hallmark in the development and progression of neurodegenerative diseases and prevention or resolution of chronic neuroinflammation may represent a novel approach to treatment. The present review highlights the potential of the anti-inflammatory and pro-resolving effects of polyunsaturated fatty acid (PUFA)- derived mediators (Specialized Pro-resolving Mediators—SPM) in neurodegenerative disorders. PUFA-derived SPM are biosynthesized in response to chemicals produced from acute inflammatory responses. Preclinical studies from both AD and PD models suggest a dysregulation of SPM and their receptors in neurological disorders. Decreased SPM may be due to inadequate substrate, an imbalance between SPM and proinflammatory mediators or a disruption in SPM synthesis. SPMs hold great promise for neuroprotection in AD by altering expression of pro-inflammatory genes, modulating macrophage function, serving as a biomarker for AD status, and promoting resolution of neuroinflammation. In PD, data suggest SPM are able to cross the blood-brain barrier, inhibit microglial activation and decrease induced markers of inflammation, possibly as a result of their ability to downregulate NFκB signaling pathways. Several in vivo and in vitro studies suggest a benefit from administration of SPMs in both neurodegenerative disorders. However, extrapolation of these outcomes to humans is difficult as no models are able to replicate all features of AD or PD. Minimal data evaluating these PUFAderived metabolites in humans with neurodegenerative disorders are available and a gap in knowledge exists regarding behavior of SPM and their receptors in patients with these conditions. There is also large gap in our knowledge regarding which lipid mediator would be most effective in which model of AD or PD and how dietary intake or supplementation can impact SPM levels. Future direction should include focused, translational efforts to investigate SPM as an add-on (in addition to standard treatment) or as standalone agents in patients with neurodegenerative disorders

Persistent fluctuations in stride intervals under fractal auditory stimulation

Copyright @ 2014 Marmelat et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Stride sequences of healthy gait are characterized by persistent long-range correlations, which become anti-persistent in the presence of an isochronous metronome. The latter phenomenon is of particular interest because auditory cueing is generally considered to reduce stride variability and may hence be beneficial for stabilizing gait. Complex systems tend to match their correlation structure when synchronizing. In gait training, can one capitalize on this tendency by using a fractal metronome rather than an isochronous one? We examined whether auditory cues with fractal variations in inter-beat intervals yield similar fractal inter-stride interval variability as isochronous auditory cueing in two complementary experiments. In Experiment 1, participants walked on a treadmill while being paced by either an isochronous or a fractal metronome with different variation strengths between beats in order to test whether participants managed to synchronize with a fractal metronome and to determine the necessary amount of variability for participants to switch from anti-persistent to persistent inter-stride intervals. Participants did synchronize with the metronome despite its fractal randomness. The corresponding coefficient of variation of inter-beat intervals was fixed in Experiment 2, in which participants walked on a treadmill while being paced by non-isochronous metronomes with different scaling exponents. As expected, inter-stride intervals showed persistent correlations similar to self-paced walking only when cueing contained persistent correlations. Our results open up a new window to optimize rhythmic auditory cueing for gait stabilization by integrating fractal fluctuations in the inter-beat intervals.Commission of the European Community and the Netherlands Organisation for Scientific Research