Impact of transcutaneous electrical nerve stimulation on sleep in chronic low back pain: a real-world retrospective cohort study.

OBJECTIVE: The purpose of this study was to determine if transcutaneous electrical nerve stimulation (TENS) improves sleep in chronic low back pain (CLBP). BACKGROUND: There is uncertainty over the effectiveness of TENS in CLBP. In most studies, pain intensity has been the primary outcome measure. Although sleep abnormalities are common in CLBP, sleep outcomes have not been evaluated in most studies of TENS effectiveness. Subjective and objective sleep measures are often inconsistent in CLBP, suggesting that perception of sleep and actual sleep may differ. METHODS: This retrospective cohort study evaluated TENS for CLBP over 10 weeks. The source database included demographics, pain characteristics, pain intensity and interference on an 11-point numerical rating scale, adherence and actigraphic sleep data from real-world TENS users. Key inclusion criteria were CLBP with self-reported history of back injury and baseline pain interference with sleep ≥4. Study participants were stratified into improved and unimproved groups based on changes in pain interference with sleep (improved ≥1-point decrease). Actigraphic sleep metrics were compared between the two groups for weeks 1-2 and weeks 9-10. RESULTS: The inclusion criteria were met by 554 TENS users. There were 282 (50.9%) participants in the improved group and 272 (49.1%) in the unimproved group. The two groups had similar baseline characteristics and high TENS adherence. At the weeks 1-2 assessment, there were no differences among actigraphic sleep. At the weeks 9-10 assessment, there was a difference in total sleep time, with the improved group sleeping 29 minutes longer. In addition, the periodic leg movement (PLM) index was lower in the improved group. CONCLUSION: Regular TENS improved self-reported and objective sleep measures in individuals with CLBP. When compared to the unimproved group, the improved group had longer total sleep time and fewer PLMs. Sleep may be an important outcome for TENS effectiveness in CLBP.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task.

Frontal theta and alpha power and coherence changes are modulated by semantic complexity in Go/NoGo tasks.

To study the interactions between semantic processing and motor response inhibition, we recorded scalp EEG as subjects performed a series of Go/NoGo response inhibition tasks whose response criteria depended on different levels of semantic processing. Three different tasks were used. The first required the subject to make a Go/NoGo decision based on pictures of one particular car or one particular dog. The second used pictures of different types of cars and of dogs, and the final task used stimuli that ranged across multiple types of objects and animals. We found that the theta-band EEG power recorded during the NoGo response was attenuated as a function of semantic complexity while the peak latency was delayed in only the most complex category task. Further, frontal alpha-band desynchronization was strongest for the simplest task and remained close to baseline for the other tasks. Finally, there was significant theta-band coherence between the frontal pole and pre-SMA for the NoGo conditions across tasks, which was not found in the Go trials. These findings provide information about how more rostral frontal regions interact with the pre-SMA during response inhibition across different stimuli and task demands: specifically, level of processing affects latency, difficulty affects amplitude, and coherence is affected by whether the decision is Go or NoGo.

Impaired response inhibition in ill Gulf War veterans.

Poor performance on tasks requiring response inhibition has been observed among chronically ill veterans of the 1991 Persian Gulf War. Semantic difficulties have also been reported. We collected event-related potential (ERP) and behavioral data from 25 Gulf War veterans who complained of cognitive difficulties and from 23 matched controls, who were deployed but not symptomatic, while they performed a GO-NOGO task that required both a semantic decision and inhibitory processing. A significantly greater false-alarm rate among the ill veterans was accompanied in the ERP data by significantly reduced amplitude in the NOGO P3, consistent with previous ERP studies of other patient groups that have shown poor inhibitory response performance. This supports the contention that the ill veterans' deficit lies more in inhibiting than in detecting task-related differences in the stimuli.

EEG theta and alpha responses reveal qualitative differences in processing taxonomic versus thematic semantic relationships.

Despite the importance of semantic relationships to our understanding of semantic knowledge, the nature of the neural processes underlying these abilities are not well understood. In order to investigate these processes, 20 healthy adults listened to thematically related (e.g., leash-dog), taxonomically related (e.g., horse-dog), or unrelated (e.g., desk-dog) noun pairs as their EEG was recorded. The data were analyzed using both event-related potentials (ERP) and event-related spectral perturbation (ERSP) analyses. The spatiotemporal ERP and ERSP results were analyzed further with principal component analysis (PCA). When comparing unrelated to related word pairs, the expected N400 effect was confirmed, as well as differences in theta and alpha oscillations. When comparing thematically and taxonomically related word pairs, the ERP revealed no significant differences, but the ERSP did. Specifically, theta power increased over right frontal areas for thematic versus taxonomic relationships and alpha power increased over parietal areas for taxonomic versus thematic relationships. The different oscillatory patterns over different brain regions suggest that thematic and taxonomic relationships engage distinct neural processes. Specifically, thematic relationships engage memory processes, while taxonomic relationships may require additional inhibitory or attention processes.

The influence of perceptual and semantic categorization on inhibitory processing as measured by the N2-P3 response.

In daily activities, humans must attend and respond to a range of important items and inhibit and not respond to unimportant distractions. Our current understanding of these processes is largely based on perceptually simple stimuli. This study investigates the interaction of conceptual-semantic categorization and inhibitory processing using Event Related Potentials (ERPs). Participants completed three Go-NoGo tasks that increased systematically in the degree of conceptual-semantic information necessary to respond correctly (from single items to categories of objects and animals). Findings indicate that the N2 response reflects inhibitory processing but does not change significantly with task difficulty. The P3 NoGo amplitude, on the other hand, is attenuated by task difficulty. Further, the latency of the peak of the P3 NoGo response elicited by the most difficult task is significantly later than are the peaks detected during performance of the other two tasks. Thus, the level of complexity of conceptual-semantic representations influences inhibitory processing in a systematic way. This inhibition paradigm may be a key for investigating inhibitory dysfunction in patient populations.

Space-time-frequency analysis of EEG data using within-subject statistical tests followed by sequential PCA.

A new method is developed for analyzing the time-varying spectral content of EEG data collected in cognitive tasks. The goal is to extract and summarize the most salient features of numerical results, which span space, time, frequency, task conditions, and multiple subjects. Direct generalization of an established approach for analyzing event-related potentials, which uses sequential PCA followed by ANOVA to test for differences between conditions across subjects, gave unacceptable results. The new method, termed STAT-PCA, advocates statistical testing for differences between conditions within single subjects, followed by sequential PCA across subjects. In contrast to PCA-ANOVA, it is demonstrated that STAT-PCA gives results which: 1) isolate task-related spectral changes, 2) are insensitive to the precise definition of baseline power, 3) are stable under deletion of a random subject, and 4) are interpretable in terms of the group-averaged power. Furthermore, STAT-PCA permits the detection of activity that is not only different between conditions, but also common to both conditions, providing a complete yet parsimonious view of the data. It is concluded that STAT-PCA is well suited for analyzing the time-varying spectral content of EEG during cognitive tasks.

Spherical splines and average referencing in scalp electroencephalography.

EEG analysis and interpretation are affected by the reference electrode. Average referenced potentials are used widely to approximate the potentials relative to infinity, but estimates of the average surface potential are prone to errors due to incomplete sampling of the scalp surface. Even if the electrode density is high, this arises by not sampling the inferior scalp surface. This paper shows analytically how the spherical splines represent the average surface potential. It also shows that, for spline orders m > or = 3, the interpolating function is well approximated by its large-m limit, weighting near and distant electrodes with opposite signs. Together these motivate the hypothesis that spherical splines permit a better estimate of the potentials relative to infinity than the discrete average computed over superior scalp electrodes. It tests this hypothesis using numerical simulations in a four-sphere head model with single- and many-dipole sources, and variations in spline order, electrode number and head model parameters. The results confirm that the spherical splines yield a better estimate of the potentials relative to infinity, provided the electrode sampling density is adequate.

Theoretical study of BOLD response to sinusoidal input.

This is a theoretical study of a compelling model of blood oxygen level-dependent (BOLD) response dynamics, measured in functional magnetic resonance imaging (fMRI). The novelty of this study involves the way the model is driven sinusoidally, in order to avoid onset and offset transients that pose difficulties in data analysis and interpretation. The driving frequency ranges over the natural time scales of the hemodynamic response (0.01-1 Hz), which also corresponds to the period in typical boxcar stimulus designs. At low stimulus amplitude, the predicted BOLD response is quasi-linear. The amplitude exhibits a mild peak near the modulation frequency 0.1 Hz, and falls rapidly for higher frequencies. The phase lag relative to the stimulus is a monotonically increasing function of the modulation frequency. These findings illustrate the dynamical nature of the BOLD response, and could be used to optimize experimental designs that admit sinusoidal modulation. Higher stimulus amplitude elicits nonlinear behavior characterized by a double peak during the positive deflection of the BOLD response. This finding is particularly interesting, because similar double peaks are seen frequently in BOLD data.

The global effects of stroke on the human electroencephalogram.

The scaling properties of the fluctuations of EEG time series are used in an investigation of acute stroke in humans. We use detrended fluctuation analysis to characterize the fluctuations in 10-second time series in terms of two dimensionless scaling exponents. The statistics of these scaling exponents across 129 scalp sites define measures which may be used to distinguish normal subjects from those with acute cerebral ischemia. By their nature, these statistics emphasize the global properties of EEG dynamics. Simulation of a focal anomaly which accurately reproduces the mean scaling exponents for stroke subjects contradicts the data for the variances, which we take as evidence that the effect of stroke on EEG is global.

Scaling properties of fluctuations in the human electroencephalogram.

The fluctuation properties of the human electroencephalogram time series are studied using detrended fluctuation analysis. For nearly all 128 channels in each of the 28 subjects studied, it is found that the standard deviation of the fluctuations exhibits scaling behaviors in two regions. Topographical plots of the scaling exponents reveal the spatial structure of the nonlinear electrical activities recorded on the scalp. Moment analyses are performed to summarize the global variability across channels. The correlation between the two scaling exponents in each channel is also examined. Two global measures are found that succinctly characterize the overall properties of the fluctuation behaviors of the brain dynamics for each subject. Together they distinguish the stroke subjects from the normal ones with 90% accuracy, suggesting the possibility that this analysis could lead to an effective diagnostic tool.