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Alterations in the affective component of pain perception are related to the development of chronic pain and may contribute to the increased vulnerability to pain observed in aging. The present study analyzed age-related changes in resting-state brain activity and their possible relation to an increased pain perception in older adults. For this purpose, we compared EEG current source density and fMRI functional-connectivity at rest in older (n = 20, 66.21 ± 3.08 years) and younger adults (n = 21, 20.71 ± 2.30 years) and correlated those brain activity parameters with pain intensity and unpleasantness ratings elicited by painful stimulation. We found an age-related increase in beta2 and beta3 activity in temporal, frontal, and limbic areas, and a decrease in alpha activity in frontal areas. Moreover, older participants displayed increased functional connectivity in the anterior cingulate cortex (ACC) and the insula with precentral and postcentral gyrus. Finally, ACC beta3 activity was positively correlated with pain intensity and unpleasantness ratings in older, and ACC-precentral/postcentral gyrus connectivity was positively correlated with unpleasantness ratings in older and younger participants. These results reveal that ACC resting-state hyperactivity is a stable trait of brain aging and may underlie their characteristic altered pain perception.

Chronic pain is known as a complex disease due to its comorbidities with other symptoms and the lack of effective treatments. As a consequence, chronic pain seems to be under-diagnosed in more than 75% of patients. At the same time, the advance in brain imaging, the popularization of machine learning techniques and the development of new diagnostic tools based on these technologies have shown that these tools could be an option in supporting decision-making of healthcare professionals. In this study, we computed functional brain connectivity using resting-state fMRI data from one hundred and fifty participants to assess the performance of different machine learning models, including deep learning (DL) neural networks in classifying chronic pain patients and pain-free controls. The best result was obtained by training a convolutional neural network fed with data preprocessed using the MSDL probabilistic atlas and using the dynamic time warping (DTW) as connectivity measure. DL models had a better performance compared to other less costly models such as support vector machine (SVM) and RFC, with balanced accuracy ranged from 69 to 86%, while the area under the curve (ROC) ranged from 0.84 to 0.93. Also, DTW overperformed correlation as connectivity measure. These findings support the notion that resting-state fMRI data could be used as a potential biomarker of chronic pain conditions., Frontiers in Neuroscience, 13, ISSN:1662-453X, ISSN:1662-4548

Objective: To study the time course of the electrocortical activity evoked by gains and losses in the Iowa Gambling Task (IGT), the brain sources of this electrical activity, and its association with behavioral parameters of task performance in order to achieve a better knowledge of decision-making processes. Method: Event-related potentials (ERPs) were obtained from a 64-channel EEG in 25 participants when performing the IGT. Brain source localization analyses of the ERP components were also assessed. Results: ERP amplitudes were sensitive to gains and losses. An early fronto-central negativity was elicited when feedback was provided for both gains and losses, and correlated with the number of gains at FCz and with the number of both gains and losses at Cz. The P200 component had larger amplitudes to losses and correlated positively with the number of losses. Feedback related negativity (FRN) was higher at frontal, temporal and occipital electrodes in trials with monetary losses. In addition, trials with monetary losses elicited larger P300 magnitudes than trials with monetary gains at all electrode localizations. Conclusions: All ERP components (except P300) were related to participants’ performance in the IGT. Amplitudes of P200 and P300 were associated with the conscious recognition of the error during the decision-making. Performance data and source analysis underline the importance of the medial prefrontal cortex when processing feedback about monetary losses in the IGT., This research was supported by grants from the Spanish Ministry of Science and Innovation (Ministerio de Ciencia y Tecnología), European Regional Development Funds (ERDF) and Ministry of Economy, Industry and Competitiveness (Ministerio de Economía, Industria y Competitividad, Gobierno de España). References: PSI2008-04394, PSI2017-88388-C4-1-R and PSI2017-88388-C4-3-R.

[EN] The neurovisceral integration model proposes a neuronal network that is related to heart rate activity and cognitive performance. The aim of this study was to determine whether heart rate variability (HRV) and variability in electroencephalographic (EEG) functional connectivity in the resting state are related to cognitive flexibility. Thirty-eight right-handed students completed the CAMBIOS test, and their heart and EEG activity was recorded during 6 min in the resting state with their eyes open. We calculated correlations, partial correlations and multiple linear regressions among HRV indices, functional brain connectivity variability and CAMBIOS scores. Furthermore, the sample was divided into groups according to CAMBIOS performance, and one-way ANOVA was applied to evaluate group differences. Our results show direct and inverse correlations among cognitive flexibility, connectivity (positive and negative task networks) and heartbeat variability. Partial correlations and multiple linear regressions suggest that the relation between HRV and CAMBIOS performance is mediated by neuronal oscillations. ANOVA confirms that HRV and variability in functional brain connectivity is related to cognitive performance. In conclusion, the levels of brain signal variability might predict cognitive flexibility in a cognitive task, while HRV might predict cognitive flexibility only when it is mediated by neuronal oscillations., This work was supported by the Spanish Ministry of Economy and Competitiveness (PSI2014-57231-R). Research was funded by Grant Nos. PSI2014-57231-R and PSI2017-88388-C4-3-R from Spanish Ministry of Science. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors have declared that no competing interests exist.

The capacity to suppress irrelevant incoming input, termed sensory gating, is one of the most investigated inhibitory processes associated with cognitive impairments due to aging. The aim of this study was to examine the influence of aging on sensory gating by using somatosensory event-related potentials (ERPs) elicited by repetitive non-painful tactile stimulation (paired-pulsed task). Somatosensory ERPs were recorded in 20 healthy young adults and 20 healthy older adults while they received two identical pneumatic stimuli (S1 and S2) of 100 ms duration with an inter-stimulus interval of 550 +/- 50 ms on both forefingers. The difference between the somatosensory ERPs amplitude elicited by S1 and S2 was computed as a sensory gating measure. The amplitude and the latency of P50, N100 and late positive complex (LPC) were analyzed as well as the source generators of the gating effect. Reduced sensory gating was found in older individuals for N100 at frontal and centro-parietal electrodes and for LPC at fronto-central electrodes. Source localization analyses also revealed a reduced current density during gating effect in the older group in frontal areas in N100 and LPC. Moreover, older individuals showed delayed latencies in N100. No significant gating effect differences were found between groups in P50. These findings suggest an age-related slowing of processing speed and a reduced efficiency of inhibitory mechanisms in response to repetitive somatosensory information during stimulus evaluation, and a preservation of processing speed and inhibitory control during early stimulus coding in aging., This research was supported by grants from the Spanish Ministerio de Economia, Industria y Competitividad (ref: PSI2016-78637-P, PSI2015-66295-R and PSI2013-48260-C3-1-R), BIAL Foundation Grant (ref: #385/14) and SOIB-Joves Qualificats Program.

Chronic pain in Sickle Cell Disease (SCD) is probably related to maladaptive plasticity of brain areas involved in nociceptive processing. Transcranial Direct Current Stimulation (tDCS) and Peripheral Electrical Stimulation (PES) can modulate cortical excitability and help to control chronic pain. Studies have shown that combined use of tDCS and PES has additive effects. However, to date, no study investigated additive effects of these neuromodulatory techniques on chronic pain in patients with SCD. This protocol describes a study aiming to assess whether combined use of tDCS and PES more effectively alleviate pain in patients with SCD compared to single use of each technique. The study consists of a one-session double blind, block-randomized clinical trial (NCT02813629) in which 128 participants with SCD and femoral osteonecrosis will be enrolled. Stepwise procedures will occur on two independent days. On day 1, participants will be screened for eligibility criteria. On day 2, data collection will occur in four stages: sample characterization, baseline assessment, intervention, and post-intervention assessment. These procedures will last similar to 5 h. Participants will be divided into two groups according to homozygous for S allele (HbSS) (n = 64) and heterozygous for S and C alleles (HbSC) (n = 64) genotypes. Participants in each group will be randomly assigned, equally, to one of the following interventions: (1) active tDCS + active PES; (2) active tDCS + sham PES; (3) sham tDCS + active PES; and (4) sham tDCS + sham PES. Active tDCS intervention will consist of 20min 2mA anodic stimulation over the primary motor cortex contralateral to the most painful hip. Active PES intervention will consist of 30min sensory electrical stimulation at 100Hz over the most painful hip. The main study outcome will be pain intensity, measured by a Visual Analogue Scale. In addition, electroencephalographic power density, cortical maps of the gluteus maximus muscle elicited by Transcranial Magnetic Stimulation (TMS), serum levels of Brain- derived Neurotrophic Factor (BDNF), and Tumor Necrosis Factor (TNF) will be assessed as secondary outcomes. Data will be analyzed using ANOVA of repeated measures, controlling for confounding variables., This study is funded by the Research Support Foundation of the State of Bahia (FAPESB) through the Support Program for Emerging Center, 8133/2014 (PNE0020/2014). The first author is supported by a MSc scholarship from the Coordination for the Improvement of Higher Education Personnel (CAPES).