Thalamocortical dysrhythmia detected by machine learning

Cochlear implant induced changes in cortical networks associated with tinnitus severity

Objective.We investigated tinnitus-related cortical networks in cochlear implant users who experience tinnitus and whose perception of tinnitus changes with use of their implant. Tinnitus, the perception of unwanted sounds which are not present externally, can be a debilitating condition. In individuals with cochlear implants, use of the implant is known to modulate tinnitus, often improving symptoms but worsening them in some cases. Little is known about underlying cortical changes with use of the implant, which lead to changes in tinnitus perception. In this study we investigated whether changes in brain networks with the cochlear implant turned on and off, were associated with changes in tinnitus perception, as rated subjectively.Approach.Using functional near-infrared spectroscopy, we recorded cortical activity at rest, from 14 cochlear implant users who experienced tinnitus. Recordings were performed with the cochlear implant turned off and on. For each condition, participants rated the loudness and annoyance of their tinnitus using a visual rating scale. Changes in neural synchrony have been reported in humans and animal models of tinnitus. To assess neural synchrony, functional connectivity networks with the implant turned on and off, were compared using two network features: node strength and diversity coefficient.Main results.Changes in subjective ratings of loudness were significantly correlated with changes in node strength, averaged across occipital channels (r=-0.65, p=0.01). Changes in both loudness and annoyance were significantly correlated with changes in diversity coefficient averaged across all channels (r=-0.79,p<0.001 and r=-0.86,p<0.001). More distributed connectivity with the implant on, compared to implant off, was associated with a reduction in tinnitus loudness and annoyance.Significance.A better understanding of neural mechanisms underlying tinnitus suppression with cochlear implant use, could lead to their application as a tinnitus treatment and pave the way for effective use of other less invasive stimulation-based treatments.

Chronic pain - A maladaptive compensation to unbalanced hierarchical predictive processing

The ability to perceive pain presents an interesting evolutionary advantage to adapt to an ever-changing environment. However, in the case of chronic pain (CP), pain perception hinders the capacity of the system to adapt to changing sensory environments. Similar to other chronic perceptual disorders, CP is also proposed to be a maladaptive compensation to aberrant sensory predictive processing. The local-global oddball paradigm relies on learning hierarchical rules and processing environmental irregularities at a local and global level. Prediction errors (PE) between actual and predicted input typically trigger an update of the forward model to limit the probability of encountering future PEs. It has been hypothesised that CP hinders forward model updating, reflected in increased local deviance and decreased global deviance. In the present study, we used the local-global paradigm to examine how CP influences hierarchical learning relative to healthy controls. As hypothesised, we observed that deviance in the stimulus characteristics evoked heightened local deviance and decreased global deviance of the stimulus-driven PE. This is also accompanied by respective changes in theta phase locking that is correlated with the subjective pain perception. Changes in the global deviant in the stimulus-driven-PE could also be explained by dampened attention-related responses. Changing the context of the auditory stimulus did not however show a difference in the context-driven PE. These findings suggest that CP is accompanied by maladaptive forward model updating where the constant presence of pain perception disrupts local deviance in non-nociceptive domains. Furthermore, we hypothesise that the auditory-processing based biomarker identified here could be a marker of domain-general dysfunction that could be confirmed by future research.

Switching tinnitus on or off: An initial investigation into the role of the pregenual and rostral to dorsal anterior cingulate cortices

Research indicates that hearing loss significantly contributes to tinnitus, but it alone does not fully explain its occurrence, as many people with hearing loss do not experience tinnitus. To identify a secondary factor for tinnitus generation, we examined a unique dataset of individuals with intermittent chronic tinnitus, who experience fluctuating periods of tinnitus. EEGs of healthy controls were compared to EEGs of participants who reported perceiving tinnitus on certain days, but no tinnitus on other days.. The EEG data revealed that tinnitus onset is associated with increased theta activity in the pregenual anterior cingulate cortex and decreased theta functional connectivity between the pregenual anterior cingulate cortex and the auditory cortex. Additionally, there is increased alpha effective connectivity from the dorsal anterior cingulate cortex to the pregenual anterior cingulate cortex. When tinnitus is not perceived, differences from healthy controls include increased alpha activity in the pregenual anterior cingulate cortex and heightened alpha connectivity between the pregenual anterior cingulate cortex and auditory cortex. This suggests that tinnitus is triggered by a switch involving increased theta activity in the pregenual anterior cingulate cortex and decreased theta connectivity between the pregenual anterior cingulate cortex and auditory cortex, leading to increased theta-gamma cross-frequency coupling, which correlates with tinnitus loudness. Increased alpha activity in the dorsal anterior cingulate cortex correlates with distress. Conversely, increased alpha activity in the pregenual anterior cingulate cortex can transiently suppress the phantom sound by enhancing theta connectivity to the auditory cortex. This mechanism parallels chronic neuropathic pain and suggests potential treatments for tinnitus by promoting alpha activity in the pregenual anterior cingulate cortex and reducing alpha activity in the dorsal anterior cingulate cortex through pharmacological or neuromodulatory approaches.

Closed-Loop Infraslow Brain-Computer Interface can Modulate Cortical Activity and Connectivity in Individuals With Chronic Painful Knee Osteoarthritis: A Secondary Analysis of a Randomized Placebo-Controlled Clinical Trial

Introduction. Chronic pain is a percept due to an imbalance in the activity between sensory-discriminative, motivational-affective, and descending pain-inhibitory brain regions. Evidence suggests that electroencephalography (EEG) infraslow fluctuation neurofeedback (ISF-NF) training can improve clinical outcomes. It is unknown whether such training can induce EEG activity and functional connectivity (FC) changes. A secondary data analysis of a feasibility clinical trial was conducted to determine whether EEG ISF-NF training can significantly alter EEG activity and FC between the targeted cortical regions in people with chronic painful knee osteoarthritis (OA). Methods. A parallel, two-arm, double-blind, randomized, sham-controlled clinical trial was conducted. People with chronic knee pain associated with OA were randomized to receive sham NF training or source-localized ratio ISF-NF training protocol to down-train ISF bands at the somatosensory (SSC), dorsal anterior cingulate (dACC), and uptrain pregenual anterior cingulate cortices (pgACC). Resting state EEG was recorded at baseline and immediate post-training. Results. The source localization mapping demonstrated a reduction (P = .04) in the ISF band activity at the left dorsolateral prefrontal cortex (LdlPFC) in the active NF group. Region of interest analysis yielded significant differences for ISF (P = .008), slow (P = .007), beta (P = .043), and gamma (P = .012) band activities at LdlPFC, dACC, and bilateral SSC. The FC between pgACC and left SSC in the delta band was negatively correlated with pain bothersomeness in the ISF-NF group. Conclusion. The EEG ISF-NF training can modulate EEG activity and connectivity in individuals with chronic painful knee osteoarthritis, and the observed EEG changes correlate with clinical pain measures.

The neuron mixer and its impact on human brain dynamics

A signal mixer facilitates rich computation, which has been the building block of modern telecommunication. This frequency mixing produces new signals at the sum and difference frequencies of input signals, enabling powerful operations such as heterodyning and multiplexing. Here, we report that a neuron is a signal mixer. We found through ex vivo and in vivo whole-cell measurements that neurons mix exogenous (controlled) and endogenous (spontaneous) subthreshold membrane potential oscillations, producing new oscillation frequencies, and that neural mixing originates in voltage-gated ion channels. Furthermore, we demonstrate that mixing is evident in human brain activity and is associated with cognitive functions. We found that the human electroencephalogram displays distinct clusters of local and inter-region mixing and that conversion of the salient posterior alpha-beta oscillations into gamma-band oscillations regulates visual attention. Signal mixing may enable individual neurons to sculpt the spectrum of neural circuit oscillations and utilize them for computational operations.

Individualized Closed-Loop Acoustic Stimulation Suggests an Alpha Phase Dependence of Sound Evoked and Induced Brain Activity Measured with EEG Recordings

Following repetitive visual stimulation, post hoc phase analysis finds that visually evoked response magnitudes vary with the cortical alpha oscillation phase that temporally coincides with sensory stimulus. This approach has not successfully revealed an alpha phase dependence for auditory evoked or induced responses. Here, we test the feasibility of tracking alpha with scalp electroencephalogram (EEG) recordings and play sounds phase-locked to individualized alpha phases in real-time using a novel end-point corrected Hilbert transform (ecHT) algorithm implemented on a research device. Based on prior work, we hypothesize that sound-evoked and induced responses vary with the alpha phase at sound onset and the alpha phase that coincides with the early sound-evoked response potential (ERP) measured with EEG. Thus, we use each subject's individualized alpha frequency (IAF) and individual auditory ERP latency to define target trough and peak alpha phases that allow an early component of the auditory ERP to align to the estimated poststimulus peak and trough phases, respectively. With this closed-loop and individualized approach, we find opposing alpha phase-dependent effects on the auditory ERP and alpha oscillations that follow stimulus onset. Trough and peak phase-locked sounds result in distinct evoked and induced post-stimulus alpha level and frequency modulations. Though additional studies are needed to localize the sources underlying these phase-dependent effects, these results suggest a general principle for alpha phase-dependence of sensory processing that includes the auditory system. Moreover, this study demonstrates the feasibility of using individualized neurophysiological indices to deliver automated, closed-loop, phase-locked auditory stimulation.

NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?

OBJECTIVES

Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irrespective of the brain-related disorder. Thus, there is still a large margin for improvement. The goal of this manuscript is to 1) develop a general theoretical framework of brain functioning that is amenable to surgical neuromodulation, and 2) describe the engineering requirements of the next generation of implantable brain stimulators that follow from this theoretic model.

MATERIALS AND METHODS

A neuroscience and engineering literature review was performed to develop a universal theoretical model of brain functioning and dysfunctioning amenable to surgical neuromodulation.

RESULTS

Even though a single target can modulate an entire network, research in network science reveals that many brain disorders are the consequence of maladaptive interactions among multiple networks rather than a single network. Consequently, targeting the main connector hubs of those multiple interacting networks involved in a brain disorder is theoretically more beneficial. We, thus, envision next-generation network implants that will rely on distributed, multisite neuromodulation targeting correlated and anticorrelated interacting brain networks, juxtaposing alternative implant configurations, and finally providing solid recommendations for the realization of such implants. In doing so, this study pinpoints the potential shortcomings of other similar efforts in the field, which somehow fall short of the requirements.

CONCLUSION

The concept of network stimulation holds great promise as a universal approach for treating neurologic and psychiatric disorders.

EEG-Based Cortical Alterations in Individuals With Chronic Knee Pain Secondary to Osteoarthritis: A Cross-sectional Investigation

Chronic painful knee osteoarthritis (OA) is a disabling physical health condition. Alterations in brain responses to arthritic changes in the knee may explain persistent pain. This study investigated source localized, resting-state electroencephalography activity and functional connectivity in people with knee OA, compared to healthy controls. Adults aged 44 to 85 years with knee OA (n = 37) and healthy control (n = 39) were recruited. Resting-state electroencephalography was collected for 10 minutes and decomposed into infraslow frequency (ISF) to gamma frequency bands. Standard low-resolution electromagnetic brain tomography statistical nonparametric maps were conducted, current densities of regions of interest were compared between groups and correlation analyses were performed between electroencephalography (EEG) measures and clinical pain and functional outcomes in the knee OA group. Standard low-resolution electromagnetic brain tomography nonparametric maps revealed higher (P = .006) gamma band activity over the right insula (RIns) in the knee OA group. A significant (P < .0001) reduction in ISF band activity at the pregenual anterior cingulate cortex, whereas higher theta, alpha, beta, and gamma band activity at the dorsal anterior cingulate cortex, pregenual anterior cingulate cortex, the somatosensory cortex, and RIns in the knee OA group were identified. ISF activity of the dorsal anterior cingulate cortex was positively correlated with pain measures and psychological distress scores. Theta and alpha activity of RIns were negatively correlated with pain interference. In conclusion, aberrations in infraslow and faster frequency EEG oscillations at sensory discriminative, motivational-affective, and descending inhibitory cortical regions were demonstrated in people with chronic painful knee OA. Moreover, EEG oscillations were correlated with pain and functional outcome measures. PERSPECTIVE: This study confirms alterations in the rsEEG oscillations and its relationship with pain experience in people with knee OA. The study provides potential cortical targets and the EEG frequency bands for neuromodulatory interventions for managing chronic pain experience in knee OA.

EEG Microstates as Markers for Cognitive Impairments in Fragile X Syndrome

Fragile X syndrome (FXS) is one of the most common inherited causes of intellectual disabilities. While there is currently no cure for FXS, EEG is considered an important method to investigate the pathophysiology and evaluate behavioral and cognitive treatments. We conducted EEG microstate analysis to investigate resting brain dynamics in FXS participants. Resting-state recordings from 70 FXS participants and 71 chronological age-matched typically developing control (TDC) participants were used to derive microstates via modified k-means clustering. The occurrence, mean global field power (GFP), and global explained variance (GEV) of microstate C were significantly higher in the FXS group compared to the TDC group. The mean GFP was significantly negatively correlated with non-verbal IQ (NVIQ) in the FXS group, where lower NVIQ scores were associated with greater GFP. In addition, the occurrence, mean duration, mean GFP, and GEV of microstate D were significantly greater in the FXS group than the TDC group. The mean GFP and occurrence of microstate D were also correlated with individual alpha frequencies in the FXS group, where lower IAF frequencies accompanied greater microstate GFP and occurrence. Alterations in microstates C and D may be related to the two well-established cognitive characteristics of FXS, intellectual disabilities and attention impairments, suggesting that microstate parameters could serve as markers to study cognitive impairments and evaluate treatment outcomes in this population. Slowing of the alpha peak frequency and its correlation to microstate D parameters may suggest changes in thalamocortical dynamics in FXS, which could be specifically related to attention control. (250 words).

Combined cortical thickness and blink reflex recovery cycle to differentiate essential tremor with and without resting tremor

Objective

To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET.

Methods

We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100-300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients.

Results

ML models based exclusively on MRI features reached acceptable performance (AUC: 0.85-0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81-0.82 in rET vs. ET and AUC: 0.88-0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms.

Conclusion

This study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes.

Consensus Statements on the Definition, Classification, and Diagnostic Tests for Tinnitus: A Delphi Study Conducted by the Korean Tinnitus Study Group

BACKGROUND

Tinnitus is a bothersome condition associated with various symptoms. However, the mechanisms of tinnitus are still uncertain, and a standardized assessment of the diagnostic criteria for tinnitus is required. We aimed to reach a consensus on diagnosing tinnitus with professional experts by conducting a Delphi study with systematic review of the literature.

METHODS

Twenty-six experts in managing tinnitus in Korea were recruited, and a two-round modified Delphi study was performed online. The experts evaluated the level of agreement of potential criteria for tinnitus using a scale of 1-9. After the survey, a consensus meeting was held to establish agreement on the results obtained from the Delphi process. Consensus was defined when over 70% of the participants scored 7-9 (agreement) and fewer than 15% scored 1-3 (disagreement). To analyze the responses of the Delphi survey, the content validity ratio and Kendall's coefficient of concordance were evaluated.

RESULTS

Consensus was reached for 22 of the 38 statements. For the definition of tinnitus, 10 out of 17 statements reached consensus, with three statements achieving complete agreement including; 1) Tinnitus is a conscious perception of an auditory sensation in the absence of a corresponding external stimulus, 2) Tinnitus can affect one's quality of life, and 3) Tinnitus can be associated with hearing disorders including sensorineural hearing loss, vestibular schwannoma, Meniere's disease, otosclerosis, and others. For the classification of tinnitus, 11 out of 18 statements reached consensus. The participants highly agreed with statements such as; 1) Vascular origin is expected in pulse-synchronous tinnitus, and 2) Tinnitus can be divided into acute or chronic tinnitus. Among three statements on the diagnostic tests for tinnitus only Statement 3, "There are no reliable biomarkers for sensory or emotional factors of tinnitus." reached consensus. All participants agreed to perform pure-tone audiometry and tinnitus questionnaires, including the Tinnitus Handicap Inventory and Tinnitus Questionnaire.

CONCLUSION

We used a modified Delphi method to establish a consensus-based definition, a classification, and diagnostic tests for tinnitus. The expert panel reached agreement for several statements, with a high level of consensus. This may provide practical information for clinicians in managing tinnitus.

Is There a Difference in EEG Characteristics in Acute, Chronic, and Experimentally Induced Musculoskeletal Pain States? a Systematic Review

Electroencephalographic (EEG) alterations have been demonstrated in acute, chronic, and experimentally induced musculoskeletal (MSK) pain conditions. However, there is no cumulative evidence on the associated EEG characteristics differentiating acute, chronic, and experimentally induced musculoskeletal pain states, especially compared to healthy controls. The present systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines (PRISMA) to review and summarize available evidence for cortical brain activity and connectivity alterations in acute, chronic, and experimentally induced MSK pain states. Five electronic databases were systematically searched from their inception to 2022. A total of 3471 articles were screened, and 26 full articles (five studies on chronic pain and 21 studies on experimentally induced pain) were included for the final synthesis. Using the Downs and Black risk of assessment tool, 92% of the studies were assessed as low to moderate quality. The review identified a 'very low' level of evidence for the changes in EEG and subjective outcome measures for both chronic and experimentally induced MSK pain based on the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. Overall, the findings of this review indicate a trend toward decreased alpha and beta EEG power in evoked chronic clinical pain conditions and increased theta and alpha power in resting-state EEG recorded from chronic MSK pain conditions. EEG characteristics are unclear under experimentally induced pain conditions.

The central role of the Thalamus in psychosis, lessons from neurodegenerative diseases and psychedelics

The PD-DLB psychosis complex found in Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB) includes hallucinations, Somatic Symptom/Functional Disorders, and delusions. These disorders exhibit similar presentation patterns and progression. Mechanisms at the root of these symptoms also share similarities with processes promoting altered states of consciousness found in Rapid Eye Movement sleep, psychiatric disorders, or the intake of psychedelic compounds. We propose that these mechanisms find a crucial driver and trigger in the dysregulated activity of high-order thalamic nuclei set in motion by ThalamoCortical Dysrhythmia (TCD). TCD generates the loss of finely tuned cortico-cortical modulations promoted by the thalamus and unleashes the aberrant activity of the Default Mode Network (DMN). TCD moves in parallel with altered thalamic filtering of external and internal information. The process produces an input overload to the cortex, thereby exacerbating DMN decoupling from task-positive networks. These phenomena alter the brain metastability, creating dreamlike, dissociative, or altered states of consciousness. In support of this hypothesis, mind-altering psychedelic drugs also modulate thalamic-cortical pathways. Understanding the pathophysiological background of these conditions provides a conceptual bridge between neurology and psychiatry, thereby helping to generate a promising and converging area of investigation and therapeutic efforts.

Eavesdropping on Tinnitus Using MEG: Lessons Learned and Future Perspectives

Tinnitus has been widely investigated in order to draw conclusions about the underlying causes and altered neural activity in various brain regions. Existing studies have based their work on different tinnitus frameworks, ranging from a more local perspective on the auditory cortex to the inclusion of broader networks and various approaches towards tinnitus perception and distress. Magnetoencephalography (MEG) provides a powerful tool for efficiently investigating tinnitus and aberrant neural activity both spatially and temporally. However, results are inconclusive, and studies are rarely mapped to theoretical frameworks. The purpose of this review was to firstly introduce MEG to interested researchers and secondly provide a synopsis of the current state. We divided recent tinnitus research in MEG into study designs using resting state measurements and studies implementing tone stimulation paradigms. The studies were categorized based on their theoretical foundation, and we outlined shortcomings as well as inconsistencies within the different approaches. Finally, we provided future perspectives on how to benefit more efficiently from the enormous potential of MEG. We suggested novel approaches from a theoretical, conceptual, and methodological point of view to allow future research to obtain a more comprehensive understanding of tinnitus and its underlying processes.

Multimodal quantitative magnetic resonance imaging of the thalamus in tinnitus patients with different outcomes after sound therapy

AIMS

This study systematically investigated structural and functional alterations in the thalamus and its subregions using multimodal magnetic resonance imaging (MRI) and examined its clinical relevance in tinnitus patients with different outcomes after sound therapy (narrowband noise).

METHODS

In total, 60 patients with persistent tinnitus and 57 healthy controls (HCs) were recruited. Based on treatment efficacy, 28 patients were categorized into the effective group and 32 into the ineffective group. Five MRI measurements of the thalamus and its seven subregions, including gray matter volume, fractional anisotropy, fractional amplitude of low-frequency fluctuation, and functional connectivity (FC), were obtained for each participant and compared between the groups.

RESULTS

Patients in both the groups exhibited widespread functional and diffusion abnormalities in the whole thalamus and several subregions, with more obvious changes observed in the effective group. All tinnitus patients had abnormal FC compared with the HCs; FC differences between the two patient groups were only observed in the striatal network, auditory-related cortex, and the core area of the limbic system. We combined the multimodal quantitative thalamic alterations and used it as an imaging indicator to evaluate prognosis before sound therapy and achieved a sensitivity of 71.9% and a specificity of 85.7%.

CONCLUSION

Similar patterns of thalamic alterations were identified in tinnitus patients with different outcomes, with more obvious changes observed in the effective group. Our findings support the tinnitus generation hypothesis of frontostriatal gating system dysfunction. A combination of multimodal quantitative thalamic properties may be used as indicators to predict tinnitus prognosis before sound therapy.

Screening for Circulating Inflammatory Proteins Does Not Reveal Plasma Biomarkers of Constant Tinnitus

BACKGROUND AND OBJECTIVE

Tinnitus would benefit from an objective biomarker. The goal of this study is to identify plasma biomarkers of constant and chronic tinnitus among selected circulating inflammatory proteins.

METHODS

A case-control retrospective study on 548 cases with constant tinnitus and 548 matched controls from the Swedish Tinnitus Outreach Project (STOP), whose plasma samples were examined using Olink's Inflammatory panel. Replication and meta-analysis were performed using the same method on samples from the TwinsUK cohort. Participants from LifeGene, whose blood was collected in Stockholm and Umeå, were recruited to STOP for a tinnitus subtyping study. An age and sex matching was performed at the individual level. TwinsUK participants (n = 928) were selected based on self-reported tinnitus status over 2 to 10 years. Primary outcomes include normalized levels for 96 circulating proteins, which were used as an index test. No reference standard was available in this study.

RESULTS

After adjustment for age, sex, BMI, smoking, hearing loss, and laboratory site, the top proteins identified were FGF-21, MCP4, GDNF, CXCL9, and MCP-1; however, these were no longer statistically significant after correction for multiple testing. Stratification by sex did not yield any significant associations. Similarly, associations with hearing loss or other tinnitus-related comorbidities such as stress, anxiety, depression, hyperacusis, temporomandibular joint disorders, and headache did not yield any significant associations. Analysis in the TwinsUK failed in replicating the top candidates. Meta-analysis of STOP and TwinsUK did not reveal any significant association. Using elastic net regularization, models exhibited poor predictive capacity tinnitus based on inflammatory markers [sensitivity = 0.52 (95% CI 0.47-0.57), specificity = 0.53 (0.48-0.58), positive predictive value = 0.52 (0.47-0.56), negative predictive values = 0.53 (0.49-0.58), and AUC = 0.53 (0.49-0.56)].

DISCUSSION

Our results did not identify significant associations of the selected inflammatory proteins with constant tinnitus. Future studies examining longitudinal relations among those with more severe tinnitus and using more recent expanded proteomics platforms and sampling of cerebrospinal fluid could increase the likelihood of identifying relevant molecular biomarkers.

Functional disruptions of the brain network in low back pain: a graph-theoretical study

PURPOSE

The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics.

METHODS

Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored.

RESULTS

At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity.

CONCLUSION

This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches.

Budget-Based Classification of Parkinson's Disease From Resting State EEG

Early detection is vital for future neuroprotective treatments of Parkinson's disease (PD). Resting state electroencephalographic (EEG) recording has shown potential as a cost-effective means to aid in detection of neurological disorders such as PD. In this study, we investigated how the number and placement of electrodes affects classifying PD patients and healthy controls using machine learning based on EEG sample entropy. We used a custom budget-based search algorithm for selecting optimized sets of channels for classification, and iterated over variable channel budgets to investigate changes in classification performance. Our data consisted of 60-channel EEG collected at three different recording sites, each of which included observations collected both eyes open (total N = 178) and eyes closed (total N = 131). Our results with the data recorded eyes open demonstrated reasonable classification performance (ACC = .76; AUC = .76) with only 5 channels placed far away from each other, the selected regions including right-frontal, left-temporal and midline-occipital sites. Comparison to randomly selected subsets of channels indicated improved classifier performance only with relatively small channel-budgets. The results with the data recorded eyes closed demonstrated consistently worse classification performance (when compared to eyes open data), and classifier performance improved more steadily as a function of number of channels. In summary, our results suggest that a small subset of electrodes of an EEG recording can suffice for detecting PD with a classification performance on par with a full set of electrodes. Furthermore our results demonstrate that separately collected EEG data sets can be used for pooled machine learning based PD detection with reasonable classification performance.

Abnormal Functional Connectivity Within Default Mode Network and Salience Network Related to Tinnitus Severity

BACKGROUND

Previous studies have demonstrated that tinnitus is associated with neural changes in the cerebral cortex. This study is aimed at investigating the central nervous characteristics of tinnitus patients with different severity by using a rs-EEG.

PARTICIPANTS AND METHODS

rs-EEG was recorded in fifty-seven patients with chronic tinnitus and twenty-seven healthy controls. Tinnitus patients were divided into moderate-to-severe tinnitus group and slight-to-mild tinnitus group based on their Tinnitus Handicap Inventory (THI) scores. Source localization and functional connectivity analyses were used to measure the changes in central levels and examine the altered network patterns. The correlation between functional connectivity and tinnitus severity was analyzed.

RESULT

Compared to the healthy controls, all tinnitus patients showed significant activation in the auditory cortex (middle temporal lobe, BA 21), while moderate-to-severe tinnitus group showed enhanced connectivity between the parahippocampus and posterior cingulate gyrus. Moreover, the moderate-to-severe tinnitus group had enhanced functional connectivity between auditory cortex and insula compared to the slight-to-mild tinnitus group. The connections between the insula and the parahippocampal and posterior cingulate gyrus were positively correlated with THI scores.

CONCLUSION

The current study reveals that patients with moderate-to-severe tinnitus demonstrate greater changes in the central brain areas, including the auditory cortex, insula, parahippocampus and posterior cingulate gyrus. In addition, enhanced connections were found between the insula and the auditory cortex, as well as the posterior cingulate gyrus and the parahippocampus, which suggests abnormality in the auditory network, salience network, and default mode network. Specifically, the insula is the core region of the neural pathway that is composed of the auditory cortex, insula, and parahippocampus/posterior cingulate gyrus. This suggests that the severity of tinnitus is affected by multiple brain regions.

Brain imaging signatures of neuropathic facial pain derived by artificial intelligence

Advances in neuroimaging have permitted the non-invasive examination of the human brain in pain. However, a persisting challenge is in the objective differentiation of neuropathic facial pain subtypes, as diagnosis is based on patients' symptom descriptions. We use artificial intelligence (AI) models with neuroimaging data to distinguish subtypes of neuropathic facial pain and differentiate them from healthy controls. We conducted a retrospective analysis of diffusion tensor and T1-weighted imaging data using random forest and logistic regression AI models on 371 adults with trigeminal pain (265 classical trigeminal neuralgia (CTN), 106 trigeminal neuropathic pain (TNP)) and 108 healthy controls (HC). These models distinguished CTN from HC with up to 95% accuracy, and TNP from HC with up to 91% accuracy. Both classifiers identified gray and white matter-based predictive metrics (gray matter thickness, surface area, and volume; white matter diffusivity metrics) that significantly differed across groups. Classification of TNP and CTN did not show significant accuracy (51%) but highlighted two structures that differed between pain groups-the insula and orbitofrontal cortex. Our work demonstrates that AI models with brain imaging data alone can differentiate neuropathic facial pain subtypes from healthy data and identify regional structural indicates of pain.

Spectral features of resting-state EEG in Parkinson's Disease: A multicenter study using functional data analysis

OBJECTIVE

This study aims 1) To analyse differences in resting-state electroencephalogram (rs-EEG) spectral features of Parkinson's Disease (PD) and healthy subjects (non-PD) using Functional Data Analysis (FDA) and 2) To explore, in four independent cohorts, the external validity and reproducibility of the findings using both epoch-to-epoch FDA and averaged-epochs approach.

METHODS

We included 169 subjects (85 non-PD; 84 PD) from four centres. Rs-EEG signals were preprocessed with a combination of automated pipelines. Sensor-level relative power spectral density (PSD), dominant frequency (DF), and DF variability (DFV) features were extracted. Differences in each feature were compared between PD and non-PD on averaged epochs and using FDA to model the epoch-to-epoch change of each feature.

RESULTS

For averaged epochs, significantly higher theta relative PSD in PD was found across all datasets. Also, higher pre-alpha relative PSD was observed in three of four datasets in PD patients. For FDA, similar findings were achieved in theta, but all datasets showed consistently significant posterior pre-alpha differences across multiple epochs.

CONCLUSIONS

Increased generalised theta, with posterior pre-alpha relative PSD, was the most reproducible finding in PD.

SIGNIFICANCE

Rs-EEG theta and pre-alpha findings are generalisable in PD. FDA constitutes a reliable and powerful tool to analyse epoch-to-epoch the rs-EEG.

BurstDR spinal cord stimulation rebalances pain input and pain suppression in the brain in chronic neuropathic pain

OBJECTIVE

Chronic pain is processed by at least three well-known pathways, two pain provoking pathways including a medial 'suffering' and lateral 'painfulness' pathway. A third descending pain pathway modulates pain but is predominantly inhibitory. Chronic pain can be seen as an imbalance between the two pain-provoking and the pain inhibitory pathways. If this assumption is correct, then the imbalance between pain input and pain suppression should reverse and normalize in response to successful, i.e., pain reducing burstDR spinal cord stimulation, one of the current treatment options for neuropathic pain.

MATERIALS AND METHODS

Fifteen patients, who received spinal cord stimulation for failed back surgery were included in this study, using source localized electrical brain activity and connectivity recording via EEG to identify the purported imbalance.

RESULTS

BurstDR spinal cord stimulation induces a significant change in EEG activity in both the left and right somatosensory cortex (SSC) for both θ and γ oscillations. In the dorsal anterior cingulate cortex (dACC), we observed a significant drop in both α and β oscillations. This reduction is accompanied by a change in pain intensity and suffering. BurstDR spinal cord stimulation is also associated with a reduction in θ at the pregenual anterior cingulate cortex (pgACC). Analyzing effective connectivity indicates that for the θ band, more information is sent from the pgACC to the left and right SSC. For α, increased information is sent from the pgACC to the dACC and both the left and right SSC. This is associated with a reduced θ-γ coupling in the SSC and reduced α-β coupling in dACC.

CONCLUSION

This study suggests that chronic pain is indeed an imbalance between the ascending and descending pathways in the brain and that burst spinal cord stimulation can normalize this imbalance in the brain.

In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?

Machine learning is becoming an increasingly common component of routine data analyses in clinical research. The past decade in pain research has witnessed great advances in human neuroimaging and machine learning. With each finding, the pain research community takes one step closer to uncovering fundamental mechanisms underlying chronic pain and at the same time proposing neurophysiological biomarkers. However, it remains challenging to fully understand chronic pain due to its multidimensional representations within the brain. By utilizing cost-effective and non-invasive imaging techniques such as electroencephalography (EEG) and analyzing the resulting data with advanced analytic methods, we have the opportunity to better understand and identify specific neural mechanisms associated with the processing and perception of chronic pain. This narrative literature review summarizes studies from the last decade describing the utility of EEG as a potential biomarker for chronic pain by synergizing clinical and computational perspectives.

Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: a systematic review

ABSTRACT

Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.

Distinguishing Parkinson's Disease with GLCM Features from the Hankelization of EEG Signals

This study proposes a novel method that uses electroencephalography (EEG) signals to classify Parkinson's Disease (PD) and demographically matched healthy control groups. The method utilizes the reduced beta activity and amplitude decrease in EEG signals that are associated with PD. The study involved 61 PD patients and 61 demographically matched controls groups, and EEG signals were recorded in various conditions (eyes closed, eyes open, eyes both open and closed, on-drug, off-drug) from three publicly available EEG data sources (New Mexico, Iowa, and Turku). The preprocessed EEG signals were classified using features obtained from gray-level co-occurrence matrix (GLCM) features through the Hankelization of EEG signals. The performance of classifiers with these novel features was evaluated using extensive cross-validations (CV) and leave-one-out cross-validation (LOOCV) schemes. This method under 10 × 10 fold CV, the method was able to differentiate PD groups from healthy control groups using a support vector machine (SVM) with an accuracy of 92.4 ± 0.01, 85.7 ± 0.02, and 77.1 ± 0.06 for New Mexico, Iowa, and Turku datasets, respectively. After a head-to-head comparison with state-of-the-art methods, this study showed an increase in the classification of PD and controls.

Empirical Frequency Bound Derivation Reveals Prominent Mid-Frontal Alpha Associated with Neurosensory Dysfunction in Fragile X Syndrome

The FMR1 gene is inactive in Fragile X syndrome (FXS), resulting in low levels of FMRP and consequent neurochemical, synaptic, and local circuit neurophysiological alterations in the fmr1 KO mouse. In FXS patients, electrophysiological studies have demonstrated a marked reduction in global alpha activity and regional increases in gamma oscillations associated with intellectual disability and sensory hypersensitivity. Since alpha activity is associated with a thalamocortical function with widely distributed modulatory effects on neocortical excitability, insight into alpha physiology may provide insight into systems-level disease mechanisms. Herein, we took a data-driven approach to clarify the temporal and spatial properties of alpha and theta activity in participants with FXS. High-resolution resting-state EEG data were collected from participants affected by FXS (n = 65) and matched controls (n = 70). We used a multivariate technique to empirically classify neural oscillatory bands based on their coherent spatiotemporal patterns. Participants with FXS demonstrated: 1) redistribution of lower-frequency boundaries indicating a "slower" dominant alpha rhythm, 2) an anteriorization of alpha frequency activity, and 3) a correlation of increased individualized alpha power measurements with auditory neurosensory dysfunction. These findings suggest an important role for alterations in thalamocortical physiology for the well-established neocortical hyper-excitability in FXS and, thus, a role for neural systems level disruption to cortical hyperexcitability that has been studied primarily at the local circuit level in animal models.

A parahippocampal-sensory Bayesian vicious circle generates pain or tinnitus: a source-localized EEG study

Pain and tinnitus share common pathophysiological mechanisms, clinical features, and treatment approaches. A source-localized resting-state EEG study was conducted in 150 participants: 50 healthy controls, 50 pain, and 50 tinnitus patients. Resting-state activity as well as functional and effective connectivity was computed in source space. Pain and tinnitus were characterized by increased theta activity in the pregenual anterior cingulate cortex, extending to the lateral prefrontal cortex and medial anterior temporal lobe. Gamma-band activity was increased in both auditory and somatosensory cortex, irrespective of the pathology, and extended to the dorsal anterior cingulate cortex and parahippocampus. Functional and effective connectivity were largely similar in pain and tinnitus, except for a parahippocampal-sensory loop that distinguished pain from tinnitus. In tinnitus, the effective connectivity between parahippocampus and auditory cortex is bidirectional, whereas the effective connectivity between parahippocampus and somatosensory cortex is unidirectional. In pain, the parahippocampal-somatosensory cortex is bidirectional, but parahippocampal auditory cortex unidirectional. These modality-specific loops exhibited theta-gamma nesting. Applying a Bayesian brain model of brain functioning, these findings suggest that the phenomenological difference between auditory and somatosensory phantom percepts result from a vicious circle of belief updating in the context of missing sensory information. This finding may further our understanding of multisensory integration and speaks to a universal treatment for pain and tinnitus-by selectively disrupting parahippocampal-somatosensory and parahippocampal-auditory theta-gamma activity and connectivity.

Tinnitus and distress: an electroencephalography classification study

There exist no objective markers for tinnitus or tinnitus disorders, which complicates diagnosis and treatments. The combination of EEG with sophisticated classification procedures may reveal biomarkers that can identify tinnitus and accurately differentiate different levels of distress experienced by patients. EEG recordings were obtained from 129 tinnitus patients and 142 healthy controls. Linear support vector machines were used to develop two classifiers: the first differentiated tinnitus patients from controls, while the second differentiated tinnitus patients with low and high distress levels. The classifier for healthy controls and tinnitus patients performed with an average accuracy of 96 and 94% for the training and test sets, respectively. For the distress classifier, these average accuracies were 89 and 84%. Minimal overlap was observed between the features of the two classifiers. EEG-derived features made it possible to accurately differentiate healthy controls and tinnitus patients as well as low and high distress tinnitus patients. The minimal overlap between the features of the two classifiers indicates that the source of distress in tinnitus, which could also be involved in distress related to other conditions, stems from different neuronal mechanisms compared to those causing the tinnitus pathology itself.

Pain control based on oscillatory brain activity using transcranial alternating current stimulation: An integrative review

Developing effective tools and strategies to relieve chronic pain is a high-priority scientific and clinical goal. In particular, the brain regions related to pain processing have been investigated as potential targets to relieve pain by non-invasive brain stimulation (NIBS). In addition to elucidating the relationship between pain and oscillatory brain activity, transcranial alternating current stimulation (tACS), which can non-invasively entrain oscillatory brain activity and modulate oscillatory brain communication, has attracted scientific attention as a possible technique to control pain. This review focuses on the use of tACS to relieve pain through the manipulation of oscillatory brain activity and its potential clinical applications. Several studies have reported that tACS on a single brain reduces pain by normalizing abnormal oscillatory brain activity in patients with chronic pain. Interpersonal tACS approaches based on inter-brain synchrony to manipulate inter-brain communication may result in pain relief via prosocial effects. Pain is encoded by the spatiotemporal neural communication that represents the integration of cognitive, emotional-affective, and sensorimotor aspects of pain. Therefore, future studies should seek to identify the pathological oscillatory brain communication in chronic pain as a therapeutic target for tACS. In conclusion, tACS could be effective for re-establishing oscillatory brain activity and assisting social interaction, and it might help develop novel approaches for pain control.

Brain network dynamics in people with visual snow syndrome

Visual snow syndrome (VSS) is a neurological disorder characterized by a range of continuous visual disturbances. Little is known about the functional pathological mechanisms underlying VSS and their effect on brain network topology, studied using high-resolution resting-state (RS) 7 T MRI. Forty VSS patients and 60 healthy controls underwent RS MRI. Functional connectivity matrices were calculated, and global efficiency (network integration), modularity (network segregation), local efficiency (LE, connectedness neighbors) and eigenvector centrality (significance node in network) were derived using a dynamic approach (temporal fluctuations during acquisition). Network measures were compared between groups, with regions of significant difference correlated with known aberrant ocular motor VSS metrics (shortened latencies and higher number of inhibitory errors) in VSS patients. Lastly, nodal co-modularity, a binary measure of node pairs belonging to the same module, was studied. VSS patients had lower modularity, supramarginal centrality and LE dynamics of multiple (sub)cortical regions, centered around occipital and parietal lobules. In VSS patients, lateral occipital cortex LE dynamics correlated positively with shortened prosaccade latencies (p = .041, r = .353). In VSS patients, occipital, parietal, and motor nodes belonged more often to the same module and demonstrated lower nodal co-modularity with temporal and frontal regions. This study revealed reduced dynamic variation in modularity and local efficiency strength in the VSS brain, suggesting that brain network dynamics are less variable in terms of segregation and local clustering. Further investigation of these changes could inform our understanding of the pathogenesis of the disorder and potentially lead to treatment strategies.

Using coding and non-coding rare variants to target candidate genes in patients with severe tinnitus

Tinnitus is the phantom percept of an internal non-verbal set of noises and tones. It is reported by 15% of the population and it is usually associated with hearing and/or brain disorders. The role of structural variants (SVs) in coding and non-coding regions has not been investigated in patients with severe tinnitus. In this study, we performed whole-genome sequencing in 97 unrelated Swedish individuals with chronic tinnitus (TIGER cohort). Rare single nucleotide variants (SNV), large structural variants (LSV), and copy number variations (CNV) were retrieved to perform a gene enrichment analysis in TIGER and in a subgroup of patients with severe tinnitus (SEVTIN, n = 34), according to the tinnitus handicap inventory (THI) scores. An independent exome sequencing dataset of 147 Swedish tinnitus patients was used as a replication cohort (JAGUAR cohort) and population-specific datasets from Sweden (SweGen) and Non-Finish Europeans (NFE) from gnomAD were used as control groups. SEVTIN patients showed a higher prevalence of hyperacusis, hearing loss, and anxiety when they were compared to individuals in the TIGER cohort. We found an enrichment of rare missense variants in 6 and 8 high-constraint genes in SEVTIN and TIGER cohorts, respectively. Of note, an enrichment of missense variants was found in the CACNA1E gene in both SEVTIN and TIGER. We replicated the burden of missense variants in 9 high-constrained genes in the JAGUAR cohort, including the gene NAV2, when data were compared with NFE. Moreover, LSVs in constrained regions overlapping CACNA1E, NAV2, and TMEM132D genes were observed in TIGER and SEVTIN.

Periodic electroencephalographic discharges and epileptic spasms involve cortico-striatal-thalamic loops on Arterial Spin Labeling Magnetic Resonance Imaging

Periodic discharges are a rare peculiar electroencephalogram pattern, occasionally associated with motor or other clinical manifestations, usually observed in critically ill patients. Their underlying pathophysiology remains poorly understood. Epileptic spasms in clusters and periodic discharges with motor manifestations share similar electroencephalogram pattern and some aetiologies of unfavourable prognosis such as subacute sclerosing panencephalitis or herpes encephalitis. Arterial spin labelling magnetic resonance imaging identifies localizing ictal and inter-ictal changes in neurovascular coupling, therefore assumed able to reveal concerned cerebral structures. Here, we retrospectively analysed ictal and inter-ictal arterial spin labelling magnetic resonance imaging in patients aged 6 months to 15 years (median 3 years 4 months) with periodic discharges including epileptic spasms, and compared these findings with those of patients with drug-resistant focal epilepsy who never presented periodic discharges nor epileptic spasms as well as to those of age-matched healthy controls. Ictal electroencephalogram was recorded either simultaneously with arterial spin labelling magnetic resonance imaging or during the close time lapse of patients' periodic discharges, whereas inter-ictal examinations were performed during the patients' active epilepsy but without seizures during the arterial spin labelling magnetic resonance imaging. Ictal arterial spin labelling magnetic resonance imaging was acquired in five patients with periodic discharges [subacute sclerosing panencephalitis (1), stroke-like events (3), West syndrome with cortical malformation (1), two of them also had inter-ictal arterial spin labelling magnetic resonance imaging]. Inter-ictal group included patients with drug-resistant epileptic spasms of various aetiologies (14) and structural drug-resistant focal epilepsy (8). Cortex, striatum and thalamus were segmented and divided in six functional subregions: prefrontal, motor (rostral, caudal), parietal, occipital and temporal. Rest cerebral blood flow values, absolute and relative to whole brain, were compared with those of age-matched controls for each subregion. Main findings were diffuse striatal as well as cortical motor cerebral blood flow increase during ictal examinations in generalized periodic discharges with motor manifestations (subacute sclerosing panencephalitis) and focal cerebral blood flow increase in corresponding cortical-striatal-thalamic subdivisions in lateralized periodic discharges with or without motor manifestations (stroke-like events and asymmetrical epileptic spasms) with straight topographical correlation with the electroencephalogram focus. For inter-ictal examinations, patients with epileptic spasms disclosed cerebral blood flow changes in corresponding cortical-striatal-thalamic subdivisions (absolute-cerebral blood flow decrease and relative-cerebral blood flow increase), more frequently when compared with the group of drug-resistant focal epilepsies, and not related to Vigabatrin treatment. Our results suggest that corresponding cortical-striatal-thalamic circuits are involved in periodic discharges with and without motor manifestations, including epileptic spasms, opening new insights in their pathophysiology and new therapeutical perspectives. Based on these findings, we propose a model for the generation of periodic discharges and of epileptic spasms combining existing pathophysiological models of cortical-striatal-thalamic network dynamics.

Accurate classification of pain experiences using wearable electroencephalography in adolescents with and without chronic musculoskeletal pain

Objective

We assessed the potential of using EEG to detect cold thermal pain in adolescents with and without chronic musculoskeletal pain.

Methods

Thirty-nine healthy controls (15.2 ± 2.1 years, 18 females) and 121 chronic pain participants (15.0 ± 2.0 years, 100 females, 85 experiencing pain ≥12-months) had 19-channel EEG recorded at rest and throughout a cold-pressor task (CPT). Permutation entropy, directed phase lag index, peak frequency, and binary graph theory features were calculated across 10-second EEG epochs (Healthy: 292 baseline / 273 CPT epochs; Pain: 1039 baseline / 755 CPT epochs). Support vector machine (SVM) and logistic regression models were trained to classify between baseline and CPT conditions separately for control and pain participants.

Results

SVM models significantly distinguished between baseline and CPT conditions in chronic pain (75.2% accuracy, 95% CI: 71.4%–77.1%; p < 0.0001) and control (74.8% accuracy, 95% CI: 66.3%–77.6%; p < 0.0001) participants. Logistic regression models performed similar to the SVM (Pain: 75.8% accuracy, 95% CI: 69.5%–76.6%, p < 0.0001; Controls: 72.0% accuracy, 95% CI: 64.5%–78.5%, p < 0.0001). Permutation entropy features in the theta frequency band were the largest contributor to model accuracy for both groups.

Conclusions

Our results demonstrate that subjective pain experiences can accurately be detected from electrophysiological data, and represent the first step towards the development of a point-of-care system to detect pain in the absence of self-report.

Source localized infraslow neurofeedback training in people with chronic painful knee osteoarthritis: A randomized, double-blind, sham-controlled feasibility clinical trial

Persistent pain is a key symptom in people living with knee osteoarthritis (KOA). Infra-slow Neurofeedback (ISF-NF) training is a recent development focusing on modulating cortical slow-wave activity to improve pain outcomes. A parallel, two-armed double-blinded, randomized sham-controlled, feasibility clinical trial aimed to determine the feasibility and safety of a novel electroencephalography-based infraslow fluctuation neurofeedback (EEG ISF-NF) training in people with KOA and determine the variability of clinical outcomes and EEG changes following NF training. Eligible participants attended nine 30-min ISF-NF training sessions involving three cortical regions linked to pain. Feasibility measures were monitored during the trial period. Pain and functional outcomes were measured at baseline, post-intervention, and follow-up after 2 weeks. Resting-state EEG was recorded at baseline and immediate post-intervention. Participants were middle-aged (61.7 ± 7.6 years), New Zealand European (90.5%), and mostly females (62%) with an average knee pain duration of 4 ± 3.4 years. The study achieved a retention rate of 91%, with 20/22 participants completing all the sessions. Participants rated high levels of acceptance and “moderate to high levels of perceived effectiveness of the training.” No serious adverse events were reported during the trial. Mean difference (95% CI) for clinical pain and function measures are as follows for pain severity [active: 0.89 ± 1.7 (−0.27 to 2.0); sham: 0.98 ± 1.1 (0.22–1.7)], pain interference [active: 0.75 ± 2.3 (−0.82 to 2.3); Sham: 0.89 ± 2.1 (−0.60 to 2.4)], pain unpleasantness [active: 2.6 ± 3.7 (0.17–5.1); sham: 2.8 ± 3 (0.62–5.0)] and physical function [active: 6.2 ± 13 (−2.6 to 15); sham: 1.6 ± 12 (−6.8 to 10)]. EEG sources demonstrated frequency-specific neuronal activity, functional connectivity, and ISF ratio changes following NF training. The findings of the study indicated that the ISF-NF training is a feasible, safe, and acceptable intervention for pain management in people with KOA, with high levels of perceived effectiveness. The study also reports the variability in clinical, brain activity, and connectivity changes following training.

Tinnitus and the triple network model: a perspective

Tinnitus is defined as the conscious awareness of a sound without an identifiable external sound source, and tinnitus disorder as tinnitus with associated suffering. Chronic tinnitus has been anatomically and phenomenologically separated into three pathways: a lateral “sound” pathway, a medial “suffering” pathway, and a descending noise-canceling pathway. Here, the triple network model is proposed as a unifying framework common to neuropsychiatric disorders. It proposes that abnormal interactions among three cardinal networks—the self-representational default mode network, the behavioral relevance-encoding salience network and the goal-oriented central executive network—underlie brain disorders. Tinnitus commonly leads to negative cognitive, emotional, and autonomic responses, phenomenologically expressed as tinnitus-related suffering, processed by the medial pathway. This anatomically overlaps with the salience network, encoding the behavioral relevance of the sound stimulus. Chronic tinnitus can also become associated with the self-representing default mode network and becomes an intrinsic part of the self-percept. This is likely an energy-saving evolutionary adaptation, by detaching tinnitus from sympathetic energy-consuming activity. Eventually, this can lead to functional disability by interfering with the central executive network. In conclusion, these three pathways can be extended to a triple network model explaining all tinnitus-associated comorbidities. This model paves the way for the development of individualized treatment modalities.

Survey of Machine Learning Techniques in the Analysis of EEG Signals for Parkinson’s Disease: A Systematic Review

Background: Parkinson’s disease (PD) affects 7–10 million people worldwide. Its diagnosis is clinical and can be supported by image-based tests, which are expensive and not always accessible. Electroencephalograms (EEG) are non-invasive, widely accessible, low-cost tests. However, the signals obtained are difficult to analyze visually, so advanced techniques, such as Machine Learning (ML), need to be used. In this article, we review those studies that consider ML techniques to study the EEG of patients with PD. Methods: The review process was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, which are used to provide quality standards for the objective evaluation of various studies. All publications before February 2022 were included, and their main characteristics and results were evaluated and documented through three key points associated with the development of ML techniques: dataset quality, data preprocessing, and model evaluation. Results: 59 studies were included. The predominating models were Support Vector Machine (SVM) and Artificial Neural Networks (ANNs). In total, 31 articles diagnosed PD with a mean accuracy of 97.35 ± 3.46%. There was no standard cleaning protocol for EEG and a great heterogeneity in EEG characteristics was shown, although spectral features predominated by 88.37%. Conclusions: Neither the cleaning protocol nor the number of EEG channels influenced the classification results. A baseline value was provided for the PD diagnostic problem, although recent studies focus on the identification of cognitive impairment.

Microstructure in patients with visual snow syndrome: an ultra-high field morphological and quantitative MRI study

Visual snow syndrome is a neurological condition characterized by continuous visual disturbance and a range of non-visual symptoms, including tinnitus and migraine. Little is known about the pathological mechanisms underlying visual snow syndrome. Here, we assessed brain morphometry and microstructure in visual snow syndrome patients using high-resolution structural and quantitative MRI. Forty visual snow syndrome patients (22 with migraine) and 43 controls underwent 7-Tesla MRI (MP2RAGE, 0.75 mm isotropic resolution). Volumetric and quantitative T1 values were extracted for white and grey matter regions and compared between groups. Where regions were significantly different between groups (false discovery rate corrected for multiple comparisons), post hoc comparisons were examined between patients with and without migraine. For visual snow syndrome patients, significant MRI variables were correlated with clinical severity (number of visual symptoms, perceived visual snow intensity, disruptiveness, fatigue and quality of life) and psychiatric symptoms prevalent in visual snow syndrome (depression, anxiety and depersonalization). Finally, cortical regions and individual thalamic nuclei were studied. Compared with controls, visual snow syndrome patients demonstrated a trend towards larger brain and white matter volumes and significantly lower T1 values for the entire cortex (P < 0.001), thalamus (P = 0.001) and pallidum (P = 0.001). For the patient group, thalamic T1 correlated with number of visual symptoms (P = 0.019, r = 0.390) and perceived disruptiveness of visual snow (P = 0.010, r = 0.424). These correlations did not survive multiple comparison corrections. As for specificity in visual snow syndrome group, T1 changes were most evident in caudal regions (occipital cortices) followed by parietal, temporal and prefrontal cortices. T1 values differed between groups for most individual thalamic nuclei. No differences were revealed between patients with and without migraine. In visual snow syndrome patients, we observed no changes in morphometry, instead widespread changes in grey matter microstructure, which followed a caudal-rostral pattern and affected the occipital cortices most profoundly. Migraine did not appear to independently affect these changes. Lower T1 values may potentially result from higher neurite density, myelination or increased iron levels in the visual snow syndrome brain. Further investigation of these changes may enhance our understanding of the pathogenesis of visual snow syndrome, ultimately leading to new treatment strategies.

Exploring sex differences in alpha brain activity as a potential neuromarker associated with neuropathic pain

ABSTRACT

Alpha oscillatory activity (8-13 Hz) is the dominant rhythm in the awake brain and is known to play an important role in pain states. Previous studies have identified alpha band slowing and increased power in the dynamic pain connectome (DPC) of people with chronic neuropathic pain. However, a link between alpha-band abnormalities and sex differences in brain organization in healthy individuals and those with chronic pain is not known. Here, we used resting-state magnetoencephalography to test the hypothesis that peak alpha frequency (PAF) abnormalities are general features across chronic central and peripheral conditions causing neuropathic pain but exhibit sex-specific differences in networks of the DPC (ascending nociceptive pathway [ANP], default mode network, salience network [SN], and subgenual anterior cingulate cortex). We found that neuropathic pain (N = 25 men and 25 women) was associated with increased PAF power in the DPC compared with 50 age- and sex-matched healthy controls, whereas slower PAF in nodes of the SN (temporoparietal junction) and the ANP (posterior insula) was associated with higher trait pain intensity. In the neuropathic pain group, women exhibited lower PAF power in the subgenual anterior cingulate cortex and faster PAF in the ANP and SN than men. The within-sex analyses indicated that women had neuropathic pain-related increased PAF power in the ANP, SN, and default mode network, whereas men with neuropathic pain had increased PAF power restricted to the ANP. These findings highlight neuropathic pain-related and sex-specific abnormalities in alpha oscillations across the DPC that could underlie aberrant neuronal communication in nociceptive processing and modulation.

Semi-Implantable Bioelectronics

Developing techniques to effectively and real-time monitor and regulate the interior environment of biological objects is significantly important for many biomedical engineering and scientific applications, including drug delivery, electrophysiological recording and regulation of intracellular activities. Semi-implantable bioelectronics is currently a hot spot in biomedical engineering research area, because it not only meets the increasing technical demands for precise detection or regulation of biological activities, but also provides a desirable platform for externally incorporating complex functionalities and electronic integration. Although there is less definition and summary to distinguish it from the well-reviewed non-invasive bioelectronics and fully implantable bioelectronics, semi-implantable bioelectronics have emerged as highly unique technology to boost the development of biochips and smart wearable device. Here, we reviewed the recent progress in this field and raised the concept of "Semi-implantable bioelectronics", summarizing the principle and strategies of semi-implantable device for cell applications and in vivo applications, discussing the typical methodologies to access to intracellular environment or in vivo environment, biosafety aspects and typical applications. This review is meaningful for understanding in-depth the design principles, materials fabrication techniques, device integration processes, cell/tissue penetration methodologies, biosafety aspects, and applications strategies that are essential to the development of future minimally invasive bioelectronics.

Neocortical localization and thalamocortical modulation of neuronal hyperexcitability contribute to Fragile X Syndrome

Fragile X Syndrome (FXS) is a monogenetic form of intellectual disability and autism in which well-established knockout (KO) animal models point to neuronal hyperexcitability and abnormal gamma-frequency physiology as a basis for key disorder features. Translating these findings into patients may identify tractable treatment targets. Using source modeling of resting-state electroencephalography data, we report findings in FXS, including 1) increases in localized gamma activity, 2) pervasive changes of theta/alpha activity, indicative of disrupted thalamocortical modulation coupled with elevated gamma power, 3) stepwise moderation of low and high-frequency abnormalities based on female sex, and 4) relationship of this physiology to intellectual disability and neuropsychiatric symptoms. Our observations extend findings in Fmr1-/- KO mice to patients with FXS and raise a key role for disrupted thalamocortical modulation in local hyperexcitability. This systems-level mechanism has received limited preclinical attention but has implications for understanding fundamental disease mechanisms.

Evaluating the Different Stages of Parkinson's Disease Using Electroencephalography With Holo-Hilbert Spectral Analysis

Electroencephalography (EEG) can reveal the abnormalities of dopaminergic subcortico-cortical circuits in patients with Parkinson's disease (PD). However, conventional time-frequency analysis of EEG signals cannot fully reveal the non-linear processes of neural activities and interactions. A novel Holo-Hilbert Spectral Analysis (HHSA) was applied to reveal non-linear features of resting state EEG in 99 PD patients and 59 healthy controls (HCs). PD patients demonstrated a reduction of β bands in frontal and central regions, and reduction of γ bands in central, parietal, and temporal regions. Compared with early-stage PD patients, late-stage PD patients demonstrated reduction of β bands in the posterior central region, and increased θ and δ2 bands in the left parietal region. θ and β bands in all brain regions were positively correlated with Hamilton depression rating scale scores. Machine learning algorithms using three prioritized HHSA features demonstrated "Bag" with the best accuracy of 0.90, followed by "LogitBoost" with an accuracy of 0.89. Our findings strengthen the application of HHSA to reveal high-dimensional frequency features in EEG signals of PD patients. The EEG characteristics extracted by HHSA are important markers for the identification of depression severity and diagnosis of PD.

Altered basal ganglia infraslow oscillation and resting functional connectivity in complex regional pain syndrome

Complex regional pain syndrome (CRPS) is a painful condition commonly accompanied by movement disturbances and often affects the upper limbs. The basal ganglia motor loop is central to movement, however, non-motor basal ganglia loops are involved in pain, sensory integration, visual processing, cognition, and emotion. Systematic evaluation of each basal ganglia functional loop and its relation to motor and non-motor disturbances in CRPS has not been investigated. We recruited 15 upper limb CRPS and 45 matched healthy control subjects. Using functional magnetic resonance imaging, infraslow oscillations (ISO) and resting-state functional connectivity in motor and non-motor basal ganglia loops were investigated using putamen and caudate seeds. Compared to controls, CRPS subjects displayed increased ISO power in the putamen contralateral to the CRPS affected limb, specifically, in contralateral putamen areas representing the supplementary motor area hand, motor hand, and motor tongue. Furthermore, compared to controls, CRPS subjects displayed increased resting connectivity between these putaminal areas as well as from the caudate body to cortical areas such as the primary motor cortex, supplementary and cingulate motor areas, parietal association areas, and the orbitofrontal cortex. These findings demonstrate changes in basal ganglia loop function in CRPS subjects and may underpin motor disturbances of CRPS.

Dissecting neuropathic from poststroke pain: the white matter within

ABSTRACT

Poststroke pain (PSP) is a heterogeneous term encompassing both central neuropathic (ie, central poststroke pain [CPSP]) and nonneuropathic poststroke pain (CNNP) syndromes. Central poststroke pain is classically related to damage in the lateral brainstem, posterior thalamus, and parietoinsular areas, whereas the role of white matter connecting these structures is frequently ignored. In addition, the relationship between stroke topography and CNNP is not completely understood. In this study, we address these issues comparing stroke location in a CPSP group of 35 patients with 2 control groups: 27 patients with CNNP and 27 patients with stroke without pain. Brain MRI images were analyzed by 2 complementary approaches: an exploratory analysis using voxel-wise lesion symptom mapping, to detect significant voxels damaged in CPSP across the whole brain, and a hypothesis-driven, region of interest-based analysis, to replicate previously reported sites involved in CPSP. Odds ratio maps were also calculated to demonstrate the risk for CPSP in each damaged voxel. Our exploratory analysis showed that, besides known thalamic and parietoinsular areas, significant voxels carrying a high risk for CPSP were located in the white matter encompassing thalamoinsular connections (one-tailed threshold Z > 3.96, corrected P value <0.05, odds ratio = 39.7). These results show that the interruption of thalamocortical white matter connections is an important component of CPSP, which is in contrast with findings from nonneuropathic PSP and from strokes without pain. These data can aid in the selection of patients at risk to develop CPSP who could be candidates to pre-emptive or therapeutic interventions.

Abnormal Anatomical and Functional Connectivity of the Thalamo-sensorimotor Circuit in Chronic Low Back Pain: Resting-state Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging Study

Thalamocortical dysfunction is thought to underlie the pathophysiology of chronic pain revealed by electroencephalographic studies. The thalamus serves as a primary relay center to transmit sensory information and motor impulses via dense connections with the somatosensory and motor cortex. In this study, diffusion tensor imaging (DTI) (probabilistic tractography) and resting-state functional magnetic resonance imaging (functional connectivity) were used to characterize the anatomical and functional integrity of the thalamo-sensorimotor pathway in chronic low back pain (cLBP). Fifty-four patients with cLBP and 54 healthy controls were included. The results suggested significantly increased anatomical connectivity of the left thalamo-motor pathway characterized by probabilistic tractography in patients with cLBP. Moreover, there was significantly altered resting-state functional connectivity (rsFC) of bilateral thalamo-motor/somatosensory pathways in patients with cLBP as compared to healthy controls. We also detected a significant correlation between pain intensity during the MRI scan and rsFC of the right thalamo-somatosensory pathway in cLBP. Our findings highlight the involvement of the thalamo-sensorimotor circuit in the pathophysiology of cLBP.

Pain and the Triple Network Model

Acute pain is a physiological response that causes an unpleasant sensory and emotional experience in the presence of actual or potential tissue injury. Anatomically and symptomatically, chronic pathological pain can be divided into three distinct but interconnected pathways, a lateral “painfulness” pathway, a medial “suffering” pathway and a descending pain inhibitory circuit. Pain (fullness) can exist without suffering and suffering can exist without pain (fullness). The triple network model is offering a generic unifying framework that may be used to understand a variety of neuropsychiatric illnesses. It claims that brain disorders are caused by aberrant interactions within and between three cardinal brain networks: the self-representational default mode network, the behavioral relevance encoding salience network and the goal oriented central executive network. A painful stimulus usually leads to a negative cognitive, emotional, and autonomic response, phenomenologically expressed as pain related suffering, processed by the medial pathway. This anatomically overlaps with the salience network, which encodes behavioral relevance of the painful stimuli and the central sympathetic control network. When pain lasts longer than the healing time and becomes chronic, the pain- associated somatosensory cortex activity may become functionally connected to the self-representational default mode network, i.e., it becomes an intrinsic part of the self-percept. This is most likely an evolutionary adaptation to save energy, by separating pain from sympathetic energy-consuming action. By interacting with the frontoparietal central executive network, this can eventually lead to functional impairment. In conclusion, the three well-known pain pathways can be combined into the triple network model explaining the whole range of pain related co-morbidities. This paves the path for the creation of new customized and personalized treatment methods.

Neural processes responsible for the translation of sustained nociceptive inputs into subjective pain experience

Tracking and predicting the temporal structure of nociceptive inputs is crucial to promote survival, as proper and immediate reactions are necessary to avoid actual or potential bodily injury. Neural activities elicited by nociceptive stimuli with different temporal structures have been described, but the neural processes responsible for translating nociception into pain perception are not fully elucidated. To tap into this issue, we recorded electroencephalographic signals from 48 healthy participants receiving thermo-nociceptive stimuli with 3 different durations and 2 different intensities. We observed that pain perception and several brain responses are modulated by stimulus duration and intensity. Crucially, we identified 2 sustained brain responses that were related to the emergence of painful percepts: a low-frequency component (LFC, < 1 Hz) originated from the insula and anterior cingulate cortex, and an alpha-band event-related desynchronization (α-ERD, 8-13 Hz) generated from the sensorimotor cortex. These 2 sustained brain responses were highly coupled, with the α-oscillation amplitude that fluctuated with the LFC phase. Furthermore, the translation of stimulus duration into pain perception was serially mediated by α-ERD and LFC. The present study reveals how brain responses elicited by nociceptive stimulation reflect the complex processes occurring during the translation of nociceptive information into pain perception.

Thalamocortical dysrhythmia in patients with schizophrenia spectrum disorder and individuals at clinical high risk for psychosis

Thalamocortical dysrhythmia (TCD) is a model characterized by abnormal resting-state thalamic oscillatory patterns where the alpha rhythm is replaced by cross-frequency coupling of low- and high-frequency rhythms. Although disrupted thalamic function is a suggested important pathophysiological mechanism underlying schizophrenia, knowledge regarding the TCD model in schizophrenia spectrum disorder (SSD) patients and individuals at clinical high risk (CHR) for psychosis is limited. A total of 169 SSD patients, 106 individuals at CHR for psychosis, and 105 healthy controls (HCs) underwent resting-state electroencephalography recordings. We performed mean global field power (MGFP) spectral analysis between 1 and 49 Hz as well as source-level theta phase-gamma amplitude coupling (TGC) analysis and compared resting-state oscillatory patterns across groups. Correlations between altered TGC values and psychotic symptom severity in the patient group were investigated. Spectral MGFP of low- and high-frequencies was larger in the SSD and CHR groups than in the HC group. The TGC of SSD patients was greater than that of HCs in the right frontal, right parietal, and left and right limbic lobes. Greater TGC in the right frontal and limbic lobes was associated with positive symptom severity in SSD patients. However, TGC in the CHR group was comparable to that in the HCs and was smaller than that in the SSD group in widespread cortical regions. The TCD pattern may be apparent after frank psychotic disorder onset in tandem with overt positive symptoms. A psychosis-risk state without overt psychotic symptoms could be characterized by abnormally increased low- and high-frequency activities with relatively preserved TGC.