Increased neural noise and impaired brain synchronization in fibromyalgia patients during cognitive interference

Estimating Systemic Cognitive States from a Mixture of Physiological and Brain Signals

As human-machine teams are being considered for a variety of mixed-initiative tasks, detecting and being responsive to human cognitive states, in particular systematic cognitive states, is among the most critical capabilities for artificial systems to ensure smooth interactions with humans and high overall team performance. Various human physiological parameters, such as heart rate, respiration rate, blood pressure, and skin conductance, as well as brain activity inferred from functional near-infrared spectroscopy or electroencephalogram, have been linked to different systemic cognitive states, such as workload, distraction, or mind-wandering among others. Whether these multimodal signals are indeed sufficient to isolate such cognitive states across individuals performing tasks or whether additional contextual information (e.g., about the task state or the task environment) is required for making appropriate inferences remains an important open problem. In this paper, we introduce an experimental and machine learning framework for investigating these questions and focus specifically on using physiological and neurophysiological measurements to learn classifiers associated with systemic cognitive states like cognitive load, distraction, sense of urgency, mind wandering, and interference. Specifically, we describe a multitasking interactive experimental setting used to obtain a comprehensive multimodal data set which provided the foundation for a first evaluation of various standard state-of-the-art machine learning techniques with respect to their effectiveness in inferring systemic cognitive states. While the classification success of these standard methods based on just the physiological and neurophysiological signals across subjects was modest, which is to be expected given the complexity of the classification problem and the possibility that higher accuracy rates might not in general be achievable, the results nevertheless can serve as a baseline for evaluating future efforts to improve classification, especially methods that take contextual aspects such as task and environmental states into account.

Noise improves the association between effects of local stimulation and structural degree of brain networks

Stimulation to local areas remarkably affects brain activity patterns, which can be exploited to investigate neural bases of cognitive function and modify pathological brain statuses. There has been growing interest in exploring the fundamental action mechanisms of local stimulation. Nevertheless, how noise amplitude, an essential element in neural dynamics, influences stimulation-induced brain states remains unknown. Here, we systematically examine the effects of local stimulation by using a large-scale biophysical model under different combinations of noise amplitudes and stimulation sites. We demonstrate that noise amplitude nonlinearly and heterogeneously tunes the stimulation effects from both regional and network perspectives. Furthermore, by incorporating the role of the anatomical network, we show that the peak frequencies of unstimulated areas at different stimulation sites averaged across noise amplitudes are highly positively related to structural connectivity. Crucially, the association between the overall changes in functional connectivity as well as the alterations in the constraints imposed by structural connectivity with the structural degree of stimulation sites is nonmonotonically influenced by the noise amplitude, with the association increasing in specific noise amplitude ranges. Moreover, the impacts of local stimulation of cognitive systems depend on the complex interplay between the noise amplitude and average structural degree. Overall, this work provides theoretical insights into how noise amplitude and network structure jointly modulate brain dynamics during stimulation and introduces possibilities for better predicting and controlling stimulation outcomes.

Working memory dysfunction in fibromyalgia is associated with genotypes of the catechol- O-methyltransferase gene: an event-related potential study

Recent findings have associated different COMT genotypes with working memory capacity in patients with fibromyalgia. Although it is thought that the COMT gene may influence neural correlates (P2 and P3 ERP components) underlying working memory impairment in this chronic-pain syndrome, it has not yet been explored. Therefore, the aim of the present research was to investigate the potential effect of the COMT gene in fibromyalgia patients on ERP working memory indices (P2 and P3 components). For this purpose, 102 participants (51 patients and 51 healthy control participants) took part in the experiment. Event-related potentials and behavioral responses were recorded while participants performed a spatial n-back task. Participants had to decide if the stimulus coincided or not in the same location as the one presented one (1-back condition) or two (2-back condition) trials before. Genotypes of the COMT gene were determined through a saliva sample from all participants. Present results significantly showed lower working memory performance (p < 0.05) in patients with fibromyalgia as compared to control participants (higher rate of errors and slower reaction times). At neural level, we found that patients exhibited enhanced frontocentral and parieto-occipital P2 amplitudes compared to control participants (p < 0.05). Interestingly, we also observed that only fibromyalgia patients carrying the Val/Val genotype of the COMT gene showed higher frontocentral P2 amplitudes than control participants (p < 0.05). Current results (behavioral outcomes and P2 amplitudes) confirmed the presence of an alteration in working memory functioning in fibromyalgia. The enhancement of frontocentral P2 could be reflecting that these patients would manifest an inefficient way of activating executive attention processes, in carriers of the Val/Val genotype of COMT. To our knowledge, the present findings are the first linking neural indices of working memory dysfunctions and COMT genotypes in fibromyalgia. Applying a subgroup of patient's strategy based on this genetic marker could be useful to establish more tailored therapeutical approaches.

Relations between short-term memory and the within-subject variability of experimental pain intensity reports: Results from healthy and Fibromyalgia patients

While factors contributing to between-subjects differences in pain have been studied extensively, factors contributing to the within-subjects variability of pain reports are yet unexplored. The aim of this investigation was to assess possible associations between short-term memory and the within-subjects variability of pain reports in healthy and chronic pain patients. Healthy participants were recruited at the University of Haifa, Israel, and Fibromyalgia patients were recruited at a rheumatology department in a central hospital in Lisbon, Portugal. Following consent, both cohorts underwent the same procedures, including the digit-span test, assessing short-term memory, and the FAST procedure, assessing within-subject variability of pain intensity reports in response to experimental pain. One-hundred twenty-one healthy volunteers and 29 Fibromyalgia patients completed the study. While a significant correlation was found between the within-subjects variability and the total score of the short-term memory task (Spearman's r = 0.394, P = 0.046) in the Fibromyalgia group, a marginal correlation emerged in the healthy cohort (r = 0.174, P = 0.056). A possible interpretation of these results is that in the patients' group, at least some of the within-subjects variability of pain intensity reports might be due to error measurement derived by poorer short-term memory, rather than true fluctuations in perception.

Spectral parameterization for studying neurodevelopment: How and why

A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how parameterization can be readily accomplished with an automated spectral parameterization ("specparam") algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; Mage = 9.97, SD = 0.95) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, the explicit parameterization of EEG power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub as a supplement to the open-access specparam toolbox.

Pathophysiology and Clinical Implications of Cognitive Dysfunction in Fibromyalgia

Cognitive dysfunction is a complaint of many patients diagnosed with fibromyalgia. Although the main symptoms of the disease are fatigue, widespread musculoskeletal pain, poor sleep quality, and tenderness points, the cognitive symptoms can be more distressing than the pain itself, and negatively affect their lives; however, many healthcare professionals underestimate these cognitive complaints and it is still one of the least researched topics. Proper management of these symptoms at an early stage may have a great impact to improve the mental health, physical function, and overall health of these patients. Hence, this traditional review aimed to look at the previous body of literature in PubMed in the past five years to address the pathophysiology of the cognitive dysfunction in fibromyalgia patients, to find the risk factors of cognitive dysfunction in these patients, to discover the recent modalities for treatment, and to figure out the clinical implications and recent recommendations by researchers on screening, diagnosis, and management of fibromyalgia and its cognitive dysfunction symptoms.

This review has shown the various mechanisms of cognitive dysfunction. Some mechanisms are related to disease symptomologies, such as excessive pain perception, and others are related to hormonal and metabolite changes in the brain. Tobacco smoking and high body mass index showed an inverse impact on cognitive dysfunction and quality of life in fibromyalgia. Other risk factors and clinical implications were discussed in detail.

A lateralized model of the pain-depression dyad

Chronic pain and depression are two frequently co-occurring and debilitating conditions. Even though the former is treated as a physical affliction, and the latter as a mental illness, both disorders closely share neural substrates. Here, we review the association of pain with depression, especially when symptoms are lateralized on either side of the body. We also explore the overlapping regions in the forebrain implicated in these conditions. Finally, we synthesize these findings into a model, which addresses gaps in our understanding of comorbid pain and depression. Our lateralized pain-depression dyad model suggests that individuals diagnosed with depression should be closely monitored for pain symptoms in the left hemibody. Conversely, for patients in pain, with the exception of acute pain with a known source, referrals in today's pain centers for psychological evaluation should be part of standard practice, within the framework of an interdisciplinary approach to pain treatment.

Effect of acute alcohol intoxication on scale-free neural activity in the lateral septum in rats

Electrophysiological recordings of brain activity show both oscillatory dynamics that typically are analyzed in the time-frequency domain to describe brain oscillatory phenomena and scale-free arrhythmic activity defined as neural noise. Recent studies consider this arrhythmic fractal dynamics of neural noise as a sensitive biomarker of a number of cognitive processes, activity of neurotransmitter systems, changes that accompany neurodegenerative and psychiatric disorders including alcohol use disorder. We tested the changes in neural noise induced by acute alcohol intoxication in the lateral septum for the entire spectrum (1–200 Hz) of local field potential signal and for frequency specific ranges (delta, theta, beta, gamma and epsilon bands). Five male Wistar rats were implanted with intracranial electrodes and local field potential signal was measured for baseline activity and activity induced by acute ethanol intoxication (2 g/kg). Change in neural noise dynamics was assessed as a change in the slope of linear regression fit of power spectral density curves in double logarithmic scale. In our study alcohol resulted in lower incline of scale-free activity in the lateral septum for high frequency range and for the whole spectrum, which is interpreted generally as increase in neural noise and change in neuronal processing in a more stochastic way initiated by the acute alcohol intoxication. At the same time, we observed decrease in neural noise for low frequency range. The observed changes may be related to the shift of the excitatory-inhibitory balance towards inhibition and changes in neurotransmission mostly in the GABAergic system. Scale-free activity was sensitive in the conditions of acute alcohol intoxication, therefore to understand its role in alcohol use disorder we need more data and studies on the underlying processes. Future studies should include simultaneous recordings and analysis of arrhythmic dynamics with the oscillatory and multiunit spiking activity in the lateral septum. It can reveal the contribution of different-scale processes in changes driven by acute alcohol intoxication and clarify the specific electrophysiological mechanisms.

Exploring the reliability and sensitivity of the EEG power spectrum as a biomarker

INTRODUCTION

The slope of the electroencephalography (EEG) power spectrum (also referred to as 1/f noise) is an important consideration when calculating narrow-band power. However, psychophysiological data also suggest this slope is a meaningful signal itself, not merely background activity or noise. We present two different methods for quantifying the slope of the power spectrum and assess their reliability and sensitivity.

METHODS

We used data from N = 60 participants who had EEG collected during rest, a videogame task, and a second period of rest. At all phases of the experiment, we calculated the "spectral slope" (a regression-based method fit to all datapoints) and the "aperiodic slope" (estimated with the fitting oscillations with 1/f algorithm FOOOF). For both methods we assessed: their reliability, their sensitivity to the transition from rest to task, their sensitivity to changes during the videogame task itself, and the agreement between the two measures.

RESULTS

Across resting phases, both spectral and aperiodic slopes showed a high degree of reliability. Both methods also showed a steepening of the power spectrum on-task compared to rest. There was also a high degree of consistency between the two methods in their estimate of the underlying slope, but FOOOF explained more variance in the power spectra across regions and type of activity (rest versus task).

CONCLUSION

The slope of the power spectrum is a highly reliable individual difference and sensitive to within-subject changes across two different methods of estimation. Moving forward, we generally recommend the use of the FOOOF algorithm for its ability to account for narrow-band signals, but these data show how regression-based approaches produce similar estimates of the spectral slope, which may be useful in some applications.

Chronic jaw pain attenuates neural oscillations during motor-evoked pain

Motor- and pain-related processes separately induce a reduction in alpha and beta power. When movement and pain occur simultaneously but are independent of each other, the effects on alpha and beta power are additive. It is not clear whether this additive effect is evident during motor-evoked pain in individuals with chronic pain. We combined highdensity electroencephalography (EEG) with a paradigm in which motor-evoked pain was induced during a jaw force task. Participants with chronic jaw pain and pain-free controls produced jaw force at 2% and 15% of their maximum voluntary contraction. The chronic jaw pain group showed exacerbated motor-evoked pain as force amplitude increased and showed increased motor variability and motor error irrespective of force amplitude. The chronic jaw pain group had an attenuated decrease in power in alpha and lower-beta frequencies in the occipital cortex during the anticipation and experience of motor-evoked pain. Rather than being additive, motor-evoked pain attenuated the modulation of alpha and beta power, and this was most evident in occipital cortex. Our findings provide the first evidence of changes in neural oscillations in the cortex during motor-evoked jaw pain.

Patients with fibromyalgia show increased beta connectivity across distant networks and microstates alterations in resting-state electroencephalogram

Fibromyalgia (FM) is a chronic condition characterized by widespread pain of unknown etiology associated with alterations in the central nervous system. Although previous studies demonstrated altered patterns of brain activity during pain processing in patients with FM, alterations in spontaneous brain oscillations, in terms of functional connectivity or microstates, have been barely explored so far. Here we recorded the EEG from 43 patients with FM and 51 healthy controls during open-eyes resting-state. We analyzed the functional connectivity between different brain networks computing the phase lag index after group Independent Component Analysis, and also performed an EEG microstates analysis. Patients with FM showed increased beta band connectivity between different brain networks and alterations in some microstates parameters (specifically lower occurrence and coverage of microstate class C). We speculate that the observed alterations in spontaneous EEG may suggest the dominance of endogenous top-down influences; this could be related to limited processing of novel external events and the deterioration of flexible behavior and cognitive control frequently reported for FM. These findings provide the first evidence of alterations in long-distance phase connectivity and microstate indices at rest, and represent progress towards the understanding of the pathophysiology of fibromyalgia and the identification of novel biomarkers for its diagnosis.

Altered neural oscillations within and between sensorimotor cortex and parietal cortex in chronic jaw pain

Pain perception is associated with priming of the motor system and the orienting of attention in healthy adults. These processes correspond with decreases in alpha and beta power in the sensorimotor and parietal cortices. The goal of the present study was to determine whether these findings extend to individuals with chronic pain. Individuals with chronic jaw pain and pain-free controls anticipated and experienced a low pain or a moderate pain-eliciting heat stimulus. Although stimuli were calibrated for each subject, stimulus temperature was not different between groups. High-density EEG data were collected during the anticipation and heat stimulation periods and were analyzed using independent component analyses, EEG source localization, and measure projection analyses. Direct directed transfer function was also estimated to identify frequency specific effective connectivity between regions. Between group differences were most evident during the heat stimulation period. We report three novel findings. First, the chronic jaw pain group had a relative increase in alpha and beta power and a relative decrease in theta and gamma power in sensorimotor cortex. Second, the chronic jaw pain group had a relative increase in power in the alpha and beta bands in parietal cortex. Third, the chronic jaw pain group had less connectivity strength in the beta and gamma bands between sensorimotor cortex and parietal cortex. Our findings show that the effect of chronic pain attenuates rather than magnifies neural responses to heat stimuli. We interpret these findings in the context of system-level changes in intrinsic sensorimotor and attentional circuits in chronic pain.

Cortical Mapping in Conventional and High Dose Spinal Cord Stimulation: An Exploratory Power Spectrum and Functional Connectivity Analysis With Electroencephalography

OBJECTIVES

Spinal cord stimulation (SCS) is considered an effective pain-relieving treatment for patients with Failed Back Surgery Syndrome (FBSS). Despite the clinical effectiveness, it is unknown whether the altered functional connectivity in such patients, as compared to healthy persons, can be influenced by SCS. Therefore, the goal of this study is to evaluate whether brain connectivity assessed by EEG differs between baseline and SCS in patients with FBSS.

MATERIALS AND METHODS

Eight patients with FBSS underwent a resting-state EEG protocol before SCS, 1.5 months and 2.5 months after receiving SCS. At each frequency band, power spectrums were compared for no SCS, conventional (CON) SCS and High Dose (HD) SCS. Functional connectivity, with the aid of eConnectome was also calculated.

RESULTS

Significant differences in the average power density spectrum over the whole scalp were observed between no SCS, CON SCS and HD SCS in delta, theta and beta frequency bands (p < 0.01). The average power spectrum for CON SCS was significantly lower than the average power spectrum for HD SCS. Marked increases in strength of the information flow between electrode pair FC3-TP9 in the beta frequency band (p = 0.006) were found in favor of HD SCS.

CONCLUSIONS

The differences in power spectrum and connectivity between the three conditions lead to the hypothesis that HD SCS differs from CON SCS on average power spectrum, suggesting that HD SCS may have a higher contribution on the excitatory bottom-up pathway.

Brain Electrical Activity Associated With Visual Attention and Reactive Motor Inhibition in Patients With Fibromyalgia

OBJECTIVE

Fibromyalgia (FM) is a generalized chronic pain condition associated with multiple cognitive impairments, including altered inhibitory processes. Inhibition is a key component of human executive functions and shares neural substrate with pain processing, which may explain the inhibitory deficits in FM. Here, we investigated the integrity of brain inhibitory mechanisms in these patients.

METHODS

We recorded the electroencephalographic activity of 27 patients with FM and 27 healthy controls (HCs) (all women) while they performed a reactive motor inhibition task (the stop-signal paradigm). We analyzed task-induced modulations in electrophysiological markers related to inhibition (N2, P3, and midfrontal theta oscillations) and visual attention (posterior alpha oscillations).

RESULTS

The FM group performed the task correctly, with no differences relative to HCs at the behavioral level. We did not find any between-group differences in N2 amplitude (F(1,52) = 0.01, p = .93), P3 amplitude (F(1,52) = 3.46; p = .068), or theta power (F(1,52) = 0.05; p = .82). However, modulation of posterior alpha power after presentation of either the go or stop stimuli was lower in patients than in HCs (F(1,52) = 7.98; p = .007).

CONCLUSIONS

N2, P3, theta power, and behavioral results indicate that the mechanisms of motor inhibition are sufficiently preserved to enable correct performance of the stop-signal task in patients with FM. Nevertheless, the lower modulation of alpha suggests greater difficulty in mobilizing and maintaining visual attentional resources, a result that may explain the cognitive dysfunction observed in FM.

Neural correlates of cognitive dysfunction in fibromyalgia patients: Reduced brain electrical activity during the execution of a cognitive control task

OBJECTIVES

Fibromyalgia (FM) is a generalized chronic pain syndrome of unknown aetiology. Although FM patients frequently complain of cognitive dysfunction, this is one of the least studied symptoms. Research on brain activity associated with the perceived cognitive impairment is particularly scarce. To address this gap, we recorded the brain electrical activity in participants during a cognitive control task.

METHODS

Electroencephalograms (EEGs) were recorded in 19 FM patients and 22 healthy controls (all women) while they performed the Multi-Source Interference Task (MSIT). We analyzed the amplitude of the frontal N2 and parietal P3 components elicited in control and interference trials and their relation with reaction times. We also explored the relationship of perceived cognitive dysfunction, assessed using visual analogue scales (VAS) and the Memory Failures of Everyday (MFE-30) test, with N2 and P3 amplitudes.

RESULTS

The N2 amplitudes were smaller in FM patients than in controls and were negatively associated with cognitive complaints. Unlike patients, healthy controls showed significant differences in the amplitude of P3 obtained from control vs. interference trials of the MSIT. Smaller N2 and P3 amplitudes were associated to longer reaction times.

CONCLUSIONS

The findings suggest a reduction in frontal brain activity during performance of an interference task, which was associated with the patients' cognitive complaints. Findings on P3 suggest altered modulation of attention according to the task demands in FM patients. Deficits in flexibility in the allocation of attentional resources and cognitive control during complex tasks may explain the dyscognition reported by chronic pain patients.

Disrupted Resting State Network of Fibromyalgia in Theta frequency

Fibromyalgia (FM), chronic widespread pain, exhibits spontaneous pain without external stimuli and is associated with altered brain activities during resting state. To understand the topological features of brain network in FM, we employed persistent homology which is a multiple scale network modeling framework not requiring thresholding. Spontaneous magnetoencephalography (MEG) activity was recorded in 19 healthy controls (HCs) and 18 FM patients. Barcode, single linkage dendrogram and single linkage matrix were generated based on the proposed modeling framework. In theta band, the slope of decrease in the number of connected components in barcodes showed steeper in HC, suggesting FM patients had decreased global connectivity. FM patients had reduced connectivity within default mode network, between middle/inferior temporal gyrus and visual cortex. The longer pain duration was correlated with reduced connectivity between inferior temporal gyrus and visual cortex. Our findings demonstrated that the aberrant resting state network could be associated with dysfunction of sensory processing in chronic pain. The spontaneous nature of FM pain may accrue to disruption of resting state network.