Expectations induced by natural-like temporal fluctuations are independent of attention decrement: evidence from behavior and early visual evoked potentials.

Temporal expectations and attention decrement affect human behavior in opposing ways: the former positively, the latter negatively yet both exhibit similar neural signatures - i.e., reduction in the early event-related potential components' amplitude - despite different underlying mechanisms. Furthermore, there is a significant and growing debate in the literature regarding the putative role of attention in the encoding of expectations in perception. The question then arises as to what are the behavioral and neural consequences, if any, of attention decrement on temporal expectations and related enhancement of sensory information processing. Here, we investigated behavioral performance and visual N1a, N1p and P1 components during a sustained attention reaction time task inducing attention decrement under two conditions. In one condition, the inter-stimulus intervals (ISIs) were randomly distributed to impede expectation effects while for the other, the ISI exhibited natural-like long-term correlations supposed to induce temporal expectations. Behavioral results show that natural-like fluctuations in ISI indeed induced faster RT due to temporal expectations. These temporal expectations were beneficial even under attention decrement circumstances. Further, temporal expectations were associated with reduced N1a amplitude while attention decrement was associated with reduced N1p amplitude. Our findings provide evidence that the effects of temporal expectations and attention decrement induced in a single task can be independent at the behavioral level, and are supported at separate information processing stages at the neural level in vision.

Asymmetries of bilateral isometric force matching with movement intention and unilateral fatigue.

During bilateral coordination, some level of inter-hemispheric remapping (i.e., the congruency between afferent and efferent force signals from both hemispheres) is required. In this case, sensory-motor information is exchanged between the two hemispheres, but it remains unclear whether this information exchange is always equivalent or not, especially in a bilateral isometric force-matching task. We used unilateral fatigue applied to one arm in order to determine whether inter-hemispheric remapping can vary asymmetrically during a bilateral isometric matching task. Because fatigue is considered to bias the sensory-motor system, we hypothesized that if bimanual coordination is modulated solely in function of the state of the sensory-motor system (motor efferences, inter-hemispheric inhibitions, and sensory reafferences), we should not observe any asymmetric effect of fatigue with movement intention (leading vs. matching arm). However, if any other process could participate in the modulation of inter-hemispheric remapping, we should observe an interaction between movement intentions and fatigue on the force produced. We found that, when the leading arm was the non-fatigued arm, participants succeeded in reproducing the force level with their fatigued arm. By contrast, when the leading arm was fatigued, subjects over-estimated the force level produced with their non-fatigued arm. Hence, lateralized fatigue exacerbates an asymmetric behavior that seems modulated by movement intention (leading vs. matching). In other words, when unilateral fatigue is introduced in a bilateral isometric force-matching task, inter-hemispheric remapping is asymmetrical. Intensity levels of motor commands sent to both arms (directly or modulated through inter-hemispheric inhibitions) and sensory reafferences alone cannot explain these observations. Some attentional focus may be not balanced continuously between both arms but may be mainly directed toward the matching arm.

Predicting the biological variability of environmental rhythms: weak or strong anticipation for sensorimotor synchronization?

The internal processes involved in synchronizing our movements with environmental stimuli have traditionally been addressed using regular metronomic sequences. Regarding real-life environments, however, biological rhythms are known to have intrinsic variability, ubiquitously characterized as fractal long-range correlations. In our research we thus investigate to what extent the synchronization processes drawn from regular metronome paradigms can be generalized to other (biologically) variable rhythms. Participants performed synchronized finger tapping under five conditions of long-range and/or short-range correlated, randomly variable, and regular auditory sequences. Combining experimental data analysis and numerical simulation, we found that synchronizing with biologically variable rhythms involves the same internal processes as with other variable rhythms (whether totally random or comprising lawful regularities), but different from those involved with a regular metronome. This challenges both the generalizability of conclusions drawn from regular-metronome paradigms, and recent research assuming that biologically variable rhythms may trigger specific strong anticipatory processes to achieve synchronization.

Complex systems approaches to the adaptability of human functions and behavior in health, aging, and chronic diseases: protocol for a meta-narrative review.

BACKGROUND: Evaluating the adaptability of human functions and behavior has become a subject of growing interest due to aging populations and the increased prevalence of chronic diseases. Various research traditions, based on complex systems theories, have addressed the adaptability of human functions and behavior. However, despite the different research traditions, no review has so far compared them to provide a reliable and useful synthetic tool. Based on an adapted methodology, study objectives are to refine common and divergent traits in the way adaptability of the human functions and behavior has been studied via complex system approaches, with a special focus on aging and chronic diseases. In order to meet this objective, we will use the methodology of the meta-narrative review, and we present in this article the protocol that we will follow. METHODS: The meta-narrative review explores the contrasting and complementary ways in which researchers have studied a subject in order to synthesize information and extract theoretical and applied recommendations. In order to carry out this protocol, we detail our methodology of article extraction, coding, and synthesis. We present the six main stages of our review, from the planning stage to the recommendation stage, and the way we will implement the six principles that underpin the construction of a meta-narrative review. DISCUSSION: The use of a meta-narrative review methodology will yield greater visibility and comprehension of the adaptability of human functions and behavior studied via complex systems-based approaches. In a broader perspective, this paper is also geared to help future researchers carry out a meta-narrative review by highlighting the main challenges encountered and anticipated as well as elements to be taken into account before starting such a project.

Transition from persistent to anti-persistent correlations in postural sway indicates velocity-based control.

The displacement of the center-of-pressure (COP) during quiet stance has often been accounted for by the control of COP position dynamics. In this paper, we discuss the conclusions drawn from previous analyses of COP dynamics using fractal-related methods. On the basis of some methodological clarification and the analysis of experimental data using stabilogram diffusion analysis, detrended fluctuation analysis, and an improved version of spectral analysis, we show that COP velocity is typically bounded between upper and lower limits. We argue that the hypothesis of an intermittent velocity-based control of posture is more relevant than position-based control. A simple model for COP velocity dynamics, based on a bounded correlated random walk, reproduces the main statistical signatures evidenced in the experimental series. The implications of these results are discussed.

Complexity in neurobiology: perspectives from the study of noise in human motor systems.

This article serves as an introduction to the themed special issue on "Complex Systems in Neurobiology." The study of complexity in neurobiology has been sensitive to the stochastic processes that dominate the micro-level architecture of neurobiological systems and the deterministic processes that govern the macroscopic behavior of these systems. A large body of research has traversed these scales of interest, seeking to determine how noise at one spatial or temporal scale influences the activity of the system at another scale. In introducing this special issue, we pay special attention to the history of inquiry in complex systems and why scientists have tended to favor linear, causally driven, reductionist approaches in Neurobiology. We follow this with an elaboration of how an alternative approach might be formulated. To illustrate our position on how the sciences of complexity and the study of noise can inform neurobiology, we use three systematic examples from the study of human motor control and learning: 1) phase transitions in bimanual coordination; 2) balance, intermittency, and discontinuous control; and 3) sensorimotor synchronization and timing. Using these examples and showing that noise is adaptively utilized by the nervous system, we make the case for the studying complexity with a perspective of understanding the macroscopic stability in biological systems by focusing on component processes at extended spatial and temporal scales. This special issue continues this theme with contributions in topics as diverse as neural network models, physical biology, motor learning, and statistical physics.

Relationship between gait complexity and pain attention in chronic low back pain.

ABSTRACT: Clinical models of chronic low back pain (cLBP) highlight the role of excessive attention to pain and kinesiophobia on the origin of disability. At the motor control level, various mechanisms are involved in the impairments observed in patients with cLBP. We aimed to assess the role of maladaptative attentional behaviors by using a complex systems approach and a visual display as a distraction during walking. Sixteen patients with cLBP with no previous surgery or significant leg pain and 16 healthy matched controls were included. Patients walked on a treadmill at preferred walking speed with and without distraction. Stride time (ST) fractal complexity was assessed using detrended fluctuation analysis. A two-way analysis of variance with repeated measures on distraction was performed on fractal exponents. We found a significant group × distraction interaction effect on fractal complexity of ST series (F(1,30) = 9.972, P = 0.004). Post hoc analysis showed that, without distraction, patients with cLBP had significantly lower ST complexity than controls, but when distracted, they regained gait complexity, recovering the level of controls. Our results suggest that excessive attention to pain causes loss of complexity and adaptability in cLBP and explain alterations of motor control with pain. Fractal analysis seems to be a promising method to explore movement variability and individual adaptability in musculoskeletal disorders.

Adaptive Capacities and Complexity of Heart Rate Variability in Patients With Chronic Obstructive Pulmonary Disease Throughout Pulmonary Rehabilitation.

INTRODUCTION: The complexity of bio-signals, like R-R intervals, is considered a reflection of the organism's capacity to adapt. However, this association still remains to be consolidated. We investigated whether the complexity of R-R intervals at rest and during perturbation [6-minute walking test (6MWT)], yielded information regarding adaptive capacities in Chronic Obstructive Pulmonary Disease (COPD) patients during pulmonary rehabilitation (PR). METHODS: In total, 23 COPD patients (64 ± 8 years, with forced expiratory volume in 1 s of 55 ± 19% predicted) were tested three times at the start (T1), middle (T2), and end (T3) of 4 weeks PR. Each time, R-R intervals were measured at rest and during 6MWT. The complexity of R-R intervals was assessed by evenly spaced Detrended Fluctuations Analysis and evaluated by the fractal exponent α and deviation from maximal complexity |1-α|. RESULTS: The 6MWT distance was significantly increased at T2 and T3 compared to T1. Neither α nor |1-α| at rest and during perturbation significantly changed throughout PR, nor were they consistently associated with 6MWT distances at each time. Throughout the PR program, complexity during the 6MWT was significantly lower compared to the rest. The level of α during 6MWT at T1 was positively correlated with the improvement of the 6MWT distance throughout the PR program. DISCUSSION: Reduced complexity in COPD patients during acute perturbation at the beginning of PR supports a decreased improvement of the 6MWT distance throughout PR. This result seems consistent with the notion that the complexity reflects the patients' adaptive capacities and could therefore become a clinical indicator in an applied perspective.

Fractal dynamics of human gait: a reassessment of the 1996 data of Hausdorff et al.

We propose in this paper a reassessment of the original data of Hausdorff et al. (Hausdorff JM, Purdon PL, Peng C-K, Ladin Z, Wei JY, Goldberger AR. J Appl Physiol 80: 1448-1457, 1996). We confirm, using autoregressive fractionally integrated moving average modeling, the presence of genuine fractal correlations in stride interval series in self-paced conditions. In contrast with the conclusions of the authors, we show that correlations did not disappear in metronomic conditions. The series of stride intervals presented antipersistent correlations, and 1/f fluctuations were evidenced in the asynchronies to the metronome. We show that the super central pattern generator model (West B, Scafetta N. Phys Rev E Stat Nonlin Soft Matter Phys 67: 051917, 2003) allows accounting for the experimentally observed correlations in both self-paced and metronomic conditions, by the simple setting of the coupling strength parameter. We conclude that 1/f fluctuations in gait are not overridden by supraspinal influences when walking is paced by a metronome. The source of 1/f noise is still at work in this condition, but expressed differently under the influence of a continuous coupling process.

Two different processes for sensorimotor synchronization in continuous and discontinuous rhythmic movements.

To account for sensorimotor synchronization, the information processing and the dynamical systems perspectives have developed different classes of models. While the former has focused on cycle-to-cycle correction of the timing errors, the latter deals with a continuous, state-dependent within-cycle coupling between the oscillating limb and the metronome. The purpose of the present study was to investigate the extent to which the two modeling frameworks partially capture the same behavior or, instead, account for different aspects of synchronization. A comparative two-level analysis (time intervals and movement trajectories) of synchronized tapping and synchronized oscillation data revealed distinct patterns of results with regard to (1) the relationship between the (a)symmetry of movement cycles and the achievement of timing goals, and (2) the sequential or within-cycle organization of synchronization processes. Our results support the idea that movement trajectories contribute to the achievement of synchronized movement timing in two different ways as a function of the (dis)continuous nature of movement. We suggest that the two modeling frameworks indeed account for different synchronization processes involved in the process of keeping time with the beat.

Fractal properties in sensorimotor variability unveil internal adaptations of the organism before symptomatic functional decline.

If health can be defined as adaptability, then measures of adaptability are crucial. Convergent findings across clinical areas established the notion that fractal properties in bio-behavioural variability characterize the healthy condition of the organism, and its adaptive capacities in general. However, ambiguities remain as to the significance of fractal properties: the literature mainly discriminated between healthy vs. pathological states, thereby loosing perspective on the progression in between, and overlooking the distinction between adaptability and effective adaptations of the organism. Here, we design an experimental tapping paradigm involving gradual feedback deprivation in groups of healthy subjects and one deafferented man as a pathological-limit case. We show that distinct types of fractal properties in sensorimotor behaviour characterize, on the one hand impaired functional ability, and on the other hand internal adaptations for maintaining performance despite the imposed constraints. Findings may prove promising for early detection of internal adaptations preceding symptomatic functional decline.

Fractal models for event-based and dynamical timers.

Some recent papers proposed to distinguish between event-based and emergent timing. Event-based timing is conceived as prescribed by events produced by a central clock, and seems to be used in discrete tasks (e.g., finger tapping). Emergent or dynamical timing refers to the exploitation of the dynamical properties of effectors, and is typically used in continuous tasks (e.g., circle drawing). The analysis of period series suggested that both timing control processes possess fractal properties, characterized by self-similarity and long-range dependence. The aim of this article is to present two models that produce period series presenting the statistical properties previously evidenced in discrete and continuous rhythmic tasks. The first one is an adaptation of the classical activation/threshold models, including a plateau-like evolution of the threshold over time. The second one is a hybrid limit-cycle model, including a time-dependent linear stiffness parameter. Both models reproduced satisfactorily the spectral signatures of event-based and dynamical timing processes, respectively. The models also produced auto-correlation functions similar to those experimentally observed. Using ARFIMA modeling we show that these simulated series possess fractal properties. We suggest in conclusion some possible extensions of this modeling approach, to account for the effects of metronomic pacing, or to analyze bimanual coordination.

Concurrent Changes of Brain Functional Connectivity and Motor Variability When Adapting to Task Constraints.

In behavioral neuroscience, the adaptability of humans facing different constraints has been addressed on one side at the brain level, where a variety of functional networks dynamically support the same performance, and on the other side at the behavioral level, where fractal properties in sensorimotor variables have been considered as a hallmark of adaptability. To bridge the gap between the two levels of observation, we have jointly investigated the changes of network connectivity in the sensorimotor cortex assessed by modularity analysis and the properties of motor variability assessed by multifractal analysis during a prolonged tapping task. Four groups of participants had to produce the same tapping performance while being deprived from 0, 1, 2, or 3 sensory feedbacks simultaneously (auditory and/or visual and/or tactile). Whereas tapping performance was not statistically different across groups, the number of brain networks involved and the degree of multifractality of the inter-tap interval series were significantly correlated, increasing as a function of feedback deprivation. Our findings provide first evidence that concomitant changes in brain modularity and multifractal properties characterize adaptations underlying unchanged performance. We discuss implications of our findings with respect to the degeneracy properties of complex systems, and the entanglement of adaptability and effective adaptation.

Detection of long-range dependence and estimation of fractal exponents through ARFIMA modelling.

We evaluate the performance of autoregressive, fractionally integrated, moving average (ARFIMA) modelling for detecting long-range dependence and estimating fractal exponents. More specifically, we test the procedure proposed by Wagenmakers, Farrell, and Ratcliff, and compare the results obtained with the Akaike information criterion (AIC) and the Bayes information criterion (BIC). The present studies show that ARFIMA modelling is able to adequately detect long-range dependence in simulated fractal series. Conversely, this method tends to produce a non-negligible rate of false detections in pure autoregressive and moving average (ARMA) series. Generally, ARFIMA modelling has a bias favouring the detection of long-range dependence. AIC and BIC gave dissimilar results, due to the different weights attributed by the two criteria to accuracy and parsimony. Finally, ARFIMA modelling provides good estimates of fractal exponents, and could adequately complement classical methods, such as spectral analysis, detrended fluctuation analysis or rescaled range analysis.

Dynamics of the human brain network revealed by time-frequency effective connectivity in fNIRS.

Functional near infrared spectroscopy (fNIRS) is a promising neuroimaging method for investigating networks of cortical regions over time. We propose a directed effective connectivity method (TPDC) allowing the capture of both time and frequency evolution of the brain's networks using fNIRS data acquired from healthy subjects performing a continuous finger-tapping task. Using this method we show the directed connectivity patterns among cortical motor regions involved in the task and their significant variations in the strength of information flow exchanges. Intra and inter-hemispheric connections during the motor task with their temporal evolution are also provided. Characterisation of the fluctuations in brain connectivity opens up a new way to assess the organisation of the brain to adapt to changing task constraints, or under pathological conditions.

Testing for the presence of 1/f noise in continuation tapping data.

A number of recent papers have suggested that the series of time intervals produced in continuation tapping may have fractal properties. This proposition, nevertheless, was only based on the visual appraisal of graphical results, and was not statistically supported. In the present study, we applied the ARMA/ARFIMA modeling procedures proposed by Wagenmakers, Farrell, and Ratcliff (2005) to test for the presence of long-range dependencies in continuation tapping data. Our results demonstrate the presence of long-range dependencies in most series and offer strong support for the hypothesis that fluctuations in tapping series are fractal in nature.

Methodological issues in the application of monofractal analyses in psychological and behavioral research.

A number of recent research works tried to apply fractal methods to psychological or behavioral variables. Quite often, nevertheless, the use of fractal analyses remains rudimentary, and the goal of researchers seems limited to evidencing the presence of long- range correlation in data sets. This article presents some recent developments in monofractals theory, and some related methodological refinements. We also discuss a number of specific issues related to the application of fractal methods in psychological and behavioral research. Finally, we consider the potential use of such approach for a renewal of classical issues in psychology and behavioral science.

Time intervals production in tapping and oscillatory motion.

We applied spectral analysis on series of time intervals produced in a synchronization-continuation experiment. In the first condition intervals were produced by finger tapping, and in the second by an oscillatory motion of the hand. Results obtained in tapping were consistent with a discrete, event-based timing model. In the oscillatory condition, the spectra suggested a continuous, dynamic timing mechanism, based on the regulation of effector stiffness. It is concluded that the oscillatory character of movement can offer an important resource for timing control. The use of an event-based timing control such as postulated in the Wing-Kristoffersson model could be restricted to a quite limited class of rhythmic tasks, characterized by the concatenation of discrete events.

'Human paced' walking: followers adopt stride time dynamics of leaders.

Isochronous cueing is widely used in gait rehabilitation even though it alters the stride-time dynamics toward anti-persistent rather than the persistent, fractal fluctuations characteristic of human walking. In the present experiment we tested an alternative cueing method: pacing by a human. To this end, we formed sixteen pairs of walkers based on their preferred stride frequency. Each pair consisted of a designated "leader" and a "follower" who was instructed to synchronize his or her steps to those of the leader. Heel strike times were detected with tiny footswitches, and Detrended Fluctuation Analysis (DFA) was applied to estimate fractal exponents of stride-time series. To ensure that the stride-time dynamics of the follower matched those of the leader, the latter was structurally modified by artificial cueing via either an isochronous metronome or a fractal metronome, in contrast to self-paced walking. Mean relative phases between followers and leaders were close to 0°, confirming that followers effectively synchronized their footfalls with those of the leaders. Mean fractal exponents were not statistically different between followers and leaders in any condition and highly correlated, suggesting that followers matched their stride-time structure to that of leaders. Our results open perspectives for alternative, more natural cueing protocols for gait rehabilitation.

Persistent fluctuations in stride intervals under fractal auditory stimulation.

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.