Variability and effect sizes of intracranial current source density estimations during pain: Systematic review, experimental findings, and future perspectives

Pain arises from the integration of sensory and cognitive processes in the brain, resulting in specific patterns of neural oscillations that can be characterized by measuring electrical brain activity. Current source density (CSD) estimation from low-resolution brain electromagnetic tomography (LORETA) and its standardized (sLORETA) and exact (eLORETA) variants, is a common approach to identify the spatiotemporal dynamics of the brain sources in physiological and pathological pain-related conditions. However, there is no consensus on the magnitude and variability of clinically or experimentally relevant effects for CSD estimations. Here, we systematically examined reports of sample size calculations and effect size estimations in all studies that included the keywords pain, and LORETA, sLORETA, or eLORETA in Scopus and PubMed. We also assessed the reliability of LORETA CSD estimations during non-painful and painful conditions to estimate hypothetical sample sizes for future experiments using CSD estimations. We found that none of the studies included in the systematic review reported sample size calculations, and less than 20% reported measures of central tendency and dispersion, which are necessary to estimate effect sizes. Based on these data and our experimental results, we determined that sample sizes commonly used in pain studies using CSD estimations are suitable to detect medium and large effect sizes in crossover designs and only large effects in parallel designs. These results provide a comprehensive summary of the effect sizes observed using LORETA in pain research, and this information can be used by clinicians and researchers to improve settings and designs of future pain studies.Fil: Völker, Juan Manuel. Aalborg University; DinamarcaFil: Arguissain, Federico Gabriel. Aalborg University; DinamarcaFil: Kæseler Andersen, Ole. Aalborg University; DinamarcaFil: Biurrun Manresa, José Alberto. Aalborg University; Dinamarca. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; Argentin

Psychophysical and electrophysiological evidence for enhanced pain facilitation and unaltered pain inhibition in acute low back pain patients

The aim of this case-control study was to examine differences in neural correlates of pain facilitatory and inhibitory mechanisms between acute low back pain (LBP) patients and healthy individuals. Pressure pain tolerance, electrical pain detection thresholds, pain ratings to repetitive suprathreshold electrical stimulation (SES) and conditioned pain modulation (CPM) were assessed in 18 patients with acute LBP and 18 healthy control participants. Furthermore, event-related potentials (ERPs) in response to repetitive SES were obtained from high-density electroencephalography. Results showed that the LBP group presented lower pressure pain tolerance and higher pain ratings to SES compared with the control group. Both groups displayed effective CPM, with no differences in CPM magnitude between groups. Both groups presented similar reductions in ERP amplitudes during CPM, but ERP responses to repetitive SES were significantly larger in the LBP group. In conclusion, acute LBP patients presented enhanced pain facilitatory mechanisms, whereas no significant changes in pain inhibitory mechanisms were observed. These results provide new insight into the central mechanisms underlying acute LBP. Perspective: This article present evidence that acute LBP patients show enhanced pain facilitation and unaltered pain inhibition compared with pain-free volunteers. These results provide new insight into the central mechanisms underlying acute LBP.Fil: Vuilleumier, Pascal Henri. University of Bern; SuizaFil: Arguissain, Federico Gabriel. Aalborg University; DinamarcaFil: Biurrun Manresa, José Alberto. Aalborg University; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Entre Rios. Universidad Nacional de Entre Rios. Centro de Investigaciones y Transferencia de Entre Rios; ArgentinaFil: Neziri, Alban Ymer. University of Bern; Suiza. Regional Hospital of Langenthal; SuizaFil: Nirkko, Arto Christian. University of Bern; SuizaFil: Andersen, Ole Kæseler. Aalborg University; DinamarcaFil: Arendt-Nielsen, Lars. Aalborg University; DinamarcaFil: Curatolo, Michele. Aalborg University; Dinamarca. University of Washington; Estados Unido

Characterization of Source-Localized EEG Activity During Sustained Deep-Tissue Pain

Musculoskeletal pain is a clinical condition that is characterized by ongoing pain and discomfort in the deep tissues such as muscle, bones, ligaments, nerves, and tendons. In the last decades, it was subject to extensive research due to its high prevalence. Still, a quantitative description of the electrical brain activity during musculoskeletal pain is lacking. This study aimed to characterize intracranial current source density (CSD) estimations during sustained deep-tissue experimental pain. Twenty-three healthy volunteers received three types of tonic stimuli for three minutes each: computer-controlled cuff pressure (1) below pain threshold (sustained deep-tissue no-pain, SDTnP), (2) above pain threshold (sustained deep-tissue pain, SDTP) and (3) vibrotactile stimulation (VT). The CSD in response to these stimuli was calculated in seven regions of interest (ROIs) likely involved in pain processing: contralateral anterior cingulate cortex, contralateral primary somatosensory cortex, bilateral anterior insula, contralateral dorsolateral prefrontal cortex, posterior parietal cortex and contralateral premotor cortex. Results showed that participants exhibited an overall increase in spectral power during SDTP in all seven ROIs compared to both SDTnP and VT, likely reflecting the differences in the salience of these stimuli. Moreover, we observed a difference is CSD due to the type of stimulus, likely reflecting somatosensory discrimination of stimulus intensity. These results describe the different contributions of neural oscillations within these brain regions in the processing of sustained deep-tissue pain.Fil: Völker, Juan Manuel. Aalborg University; DinamarcaFil: Arguissain, Federico Gabriel. Aalborg University; DinamarcaFil: Biurrun Manresa, José Alberto. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Kæseler Andersen, Ole. Aalborg University; Dinamarc

Accuracy of the Upper Limb Prediction Algorithm PREP2 Applied 2 Weeks Poststroke: A Prospective Longitudinal Study

BackgroundThe Predict Recovery Potential algorithm (PREP2) was developed to predict upper limb (UL) function early after stroke. However, assessment in the acute phase is not always possible.ObjectiveTo assess the prognostic accuracy of the PREP2 when applied in a subacute neurorehabilitation setting.MethodsThis prospective longitudinal study included patients ≥18 years old with UL impairment following stroke. Patients were assessed in accordance with the PREP2 approach. However, 2 main components, the shoulder abduction finger extension (SAFE) score and motor-evoked potentials (MEPs) were obtained 2 weeks poststroke. UL function at 3 months was predicted in 1 of 4 categories and compared with the actual outcome at 3 months as assessed by the Action Research Arm Test. The prediction accuracy of the PREP2 was quantified using the correct classification rate (CCR).ResultsNinety-one patients were included. Overall CCR of the PREP2 was 60% (95% CI 50%-71%). Within the 4 categories, CCR ranged from the lowest value at 33% (95% CI 4%-85%) for the category Limited to the highest value at 78% (95% CI 43%-95%) for the category Poor. In the present study, the overall CCR was significantly lower (P < .001) than the 75% reported by the PREP2 developers.ConclusionsThe low overall CCR makes PREP2 obtained 2 weeks poststroke unsuited for clinical implementation. However, PREP2 may be used to predict either excellent UL function in already well-recovered patients or poor UL function in patients with persistent severe UL paresis

Accuracy of the Upper Limb Prediction Algorithm PREP2 Applied 2 Weeks Poststroke: A Prospective Longitudinal Study

BackgroundThe Predict Recovery Potential algorithm (PREP2) was developed to predict upper limb (UL) function early after stroke. However, assessment in the acute phase is not always possible.ObjectiveTo assess the prognostic accuracy of the PREP2 when applied in a subacute neurorehabilitation setting.MethodsThis prospective longitudinal study included patients ≥18 years old with UL impairment following stroke. Patients were assessed in accordance with the PREP2 approach. However, 2 main components, the shoulder abduction finger extension (SAFE) score and motor-evoked potentials (MEPs) were obtained 2 weeks poststroke. UL function at 3 months was predicted in 1 of 4 categories and compared with the actual outcome at 3 months as assessed by the Action Research Arm Test. The prediction accuracy of the PREP2 was quantified using the correct classification rate (CCR).ResultsNinety-one patients were included. Overall CCR of the PREP2 was 60% (95% CI 50%-71%). Within the 4 categories, CCR ranged from the lowest value at 33% (95% CI 4%-85%) for the category Limited to the highest value at 78% (95% CI 43%-95%) for the category Poor. In the present study, the overall CCR was significantly lower (P < .001) than the 75% reported by the PREP2 developers.ConclusionsThe low overall CCR makes PREP2 obtained 2 weeks poststroke unsuited for clinical implementation. However, PREP2 may be used to predict either excellent UL function in already well-recovered patients or poor UL function in patients with persistent severe UL paresis

sj-pdf-1-nnr-10.1177_1545968320971763 – Supplemental material for Accuracy of the Upper Limb Prediction Algorithm PREP2 Applied 2 Weeks Poststroke: A Prospective Longitudinal Study

Supplemental material, sj-pdf-1-nnr-10.1177_1545968320971763 for Accuracy of the Upper Limb Prediction Algorithm PREP2 Applied 2 Weeks Poststroke: A Prospective Longitudinal Study by Camilla Biering Lundquist, Jørgen Feldbæk Nielsen, Federico Gabriel Arguissain and Iris Charlotte Brunner in Neurorehabilitation and Neural Repai