BackgroundA major problem in pain medicine is the lack of knowledge about which treatment suits a specific patient. We tested the ability of quantitative sensory testing to predict the analgesic effect of pregabalin and placebo in patients with chronic pancreatitis.MethodsSixty-four patients with painful chronic pancreatitis received pregabalin (150–300 mg BID) or matching placebo for three consecutive weeks. Analgesic effect was documented in a pain diary based on a visual analogue scale. Responders were defined as patients with a reduction in clinical pain score of 30% or more after three weeks of study treatment compared to baseline recordings. Prior to study medication, pain thresholds to electric skin and pressure stimulation were measured in dermatomes T10 (pancreatic area) and C5 (control area). To eliminate inter-subject differences in absolute pain thresholds an index of sensitivity between stimulation areas was determined (ratio of pain detection thresholds in pancreatic versus control area, ePDT ratio). Pain modulation was recorded by a conditioned pain modulation paradigm. A support vector machine was used to screen sensory parameters for their predictive power of pregabalin efficacy.ResultsThe pregabalin responders group was hypersensitive to electric tetanic stimulation of the pancreatic area (ePDT ratio 1.2 (0.9–1.3)) compared to non-responders group (ePDT ratio: 1.6 (1.5–2.0)) (P = 0.001). The electrical pain detection ratio was predictive for pregabalin effect with a classification accuracy of 83.9% (P = 0.007). The corresponding sensitivity was 87.5% and specificity was 80.0%. No other parameters were predictive of pregabalin or placebo efficacy.ConclusionsThe present study provides first evidence that quantitative sensory testing predicts the analgesic effect of pregabalin in patients with painful chronic pancreatitis. The method can be used to tailor pain medication based on patient’s individual sensory profile and thus comprises a significant step towards personalized pain medicine.

In sum, our findings show that the EEG response from a single-channel, hearing-aid-compatible configuration provides valuable information to identify a listener's focus of attention.

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Individuals with hearing loss allocate cognitive resources to comprehend noisy speech in everyday life scenarios. Such a scenario could be when they are exposed to ongoing speech and need to sustain their attention for a rather long period of time, which requires listening effort. Two well-established physiological methods that have been found to be sensitive to identify changes in listening effort are pupillometry and electroencephalography (EEG). However, these measurements have been used mainly for momentary, evoked or episodic effort. The aim of this study was to investigate how sustained effort manifests in pupillometry and EEG, using continuous speech with varying signal-to-noise ratio (SNR). Eight hearing-aid users participated in this exploratory study and performed a continuous speech-in-noise task. The speech material consisted of 30-second continuous streams that were presented from loudspeakers to the right and left side of the listener (±30˚azimuth) in the presence of 4-talker background noise (+180˚azimuth). The participants were instructed to attend either to the right or left speaker and ignore the other in a randomized order with two different SNR conditions: 0 dB and-5 dB (the difference between the target and the competing talker). The effects of SNR on listening effort were explored objectively using pupillometry and EEG. The results showed larger mean pupil dilation and decreased EEG alpha power in the parietal lobe during the more effortful condition. This study demonstrates that both measures are sensitive to changes in SNR during continuous speech.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Pregabalin is an anticonvulsive agent prescribed as a secondary analgesic for patients when standard pain treatment is insufficient.• The analgesic effect resides in the central nervous system. • The central analgesic effect can be evaluated by electroencephalography. WHAT THIS STUDY ADDS• The analgesic effect of pregabalin is reflected as a slowing of brain oscillations.• The slowing of brain oscillations for each individual patient is correlated with subjective pain scores.• The developed methodology may be used as a mechanistic approach to monitor the analgesic effect of pregabalin in pharmacological studies. AIMTo identify electroencephalographic (EEG) biomarkers for the analgesic effect of pregabalin in patients with chronic visceral pain. METHODSThis was a double-blind, placebo-controlled study in 31 patients suffering from visceral pain due to chronic pancreatitis. Patients received increasing doses of pregabalin (75 mg-300 mg twice a day) or matching placebo during 3 weeks of treatment. Pain scores were documented in a diary based on a visual analogue scale. In addition, brief pain inventory-short form (BPI) and quality of life questionnaires were collected prior to and after the study period. Multi-channel resting EEG was recorded before treatment onset and at the end of the study. Changes in EEG spectral indices were extracted, and individual changes were classified by a support vector machine (SVM) to discriminate the pregabalin and placebo responses. Changes in individual spectral indices and pain scores were correlated. RESULTSPregabalin increased normalized intensity in low spectral indices, most prominent in the theta band (3.5-7.5 Hz), difference of -3.18, 95% CI -3.57, -2.80; P = 0.03. No changes in spectral indices were seen for placebo. The maximum difference between pregabalin and placebo treated patients was seen in the parietal region, with a classification accuracy of 85.7% (P = 0.009). Individual changes in EEG indices were correlated with changes in pain diary (P = 0.04) and BPI pain composite scores (P = 0.02). CONCLUSIONSChanges in spectral indices caused by slowing of brain oscillations were identified as a biomarker for the central analgesic effect of pregabalin. The developed methodology may provide perspectives to assess individual responses to treatment in personalized medicine.

To assess centrally mediated analgesic mechanisms in clinical trials with pain patients, objective standardized methods such as electroencephalography (EEG) has many advantages. The aim of this review is to provide the reader with an overview of present findings in analgesics assessed with spontaneous EEG and evoked brain potentials (EPs) in humans. Furthermore, EEG methodologies will be discussed with respect to translation from animals to humans and future perspectives in predicting analgesic efficacy. We searched PubMed with MeSH terms 'analgesics' , 'electroencephalography' and 'evoked potentials' for relevant articles. Combined with a search in their reference lists 15 articles on spontaneous EEG and 55 papers on EPs were identified. Overall, opioids produced increased activity in the delta band in the spontaneous EEG, but increases in higher frequency bands were also seen. The EP amplitudes decreased in the majority of studies. Anticonvulsants used as analgesics showed inconsistent results. The N-methyl-D-aspartate receptor antagonist ketamine showed an increase in the theta band in spontaneous EEG and decreases in EP amplitudes. Tricyclic antidepressants increased the activity in the delta, theta and beta bands in the spontaneous EEG while EPs were inconsistently affected. Weak analgesics were mainly investigated with EPs and a decrease in amplitudes was generally observed. This review reveals that both spontaneous EEG and EPs are widely used as biomarkers for analgesic drug effects. Methodological differences are common and a more uniform approach will further enhance the value of such biomarkers for drug development and prediction of treatment response in individual patients.

Conventional, multi-channel scalp electroencephalography (EEG) allows the identification of the attended speaker in concurrent-listening ("cocktail party") scenarios. This implies that EEG might provide valuable information to complement hearing aids with some form of EEG and to install a level of neuro-feedback. To investigate whether a listener's attentional focus can be predicted from singlechannel hearing-aid-compatible EEG configurations, we recorded EEG from three electrodes inside the ear canal ("in-Ear-EEG") and additionally from 64 electrodes on the scalp. In two different, concurrent listening tasks, participants (n = 7) were fitted with individualized in-Ear-EEG pieces and were either asked to attend to one of two dichotically-presented, concurrent tone streams or to one of two dioticallypresented, concurrent audiobooks. A forward encoding model was trained to predict the EEG response at single EEG channels. We found that all individual participants' attentional focus could be predicted from single-channel EEG response recorded from short-distance configurations consisting only of a single in-Ear-EEG electrode and an adjacent scalp-EEG electrode. The responses to attended and ignored stimuli reveal differences consistent across subjects. In sum, our findings show that the EEG response from a single-channel, hearing-aid-compatible configuration provides valuable information to identify a listener's focus of attention.

Objectives:The investigation of auditory cognitive processes recently moved from strictly controlled, trial-based paradigms towards the presentation of continuous speech. This also allows the investigation of listening effort on larger time scales (i.e., sustained listening effort). Here we investigated the modulation of sustained listening effort by a noise reduction algorithm as applied in hearing aids in a listening scenario with noisy continuous speech. The investigated directional noise reduction algorithm mainly suppresses noise from the background. Design:We recorded the pupil size and the electroencephalogram (EEG) in 22 hearingimpaired participants who listened to audio news clips in the presence of background multi-talker babble noise. We estimated how noise reduction (off, on) and signal-tonoise ratio (SNR; +3 dB, +8 dB) affect pupil size and the power in the parietal EEG alpha band (i.e., parietal alpha power) as well as the behavioral performance.Results: Our results show that noise reduction reduces pupil size, while there was no significant effect of the SNR. Importantly, we found interactions of SNR and noise reduction, which suggested that noise reduction reduces pupil size predominantly under the lower SNR. Parietal alpha power showed a similar, yet non-significant pattern, with increased power under easier conditions. In line with the participants' reports that one of the two presented talkers was more intelligible, we found a reduced pupil size, increased parietal alpha power and better performance when people listened to the more intelligible talker.3 Conclusions: We show that the modulation of sustained listening effort (e.g. by hearing aid noise reduction) as indicated by pupil size and parietal alpha power can be studied under more ecologically valid conditions. Mainly concluded from pupil size, we demonstrate that hearing aid noise reduction lowers sustained listening effort. Our study approximates to real-world listening scenarios and evaluates the benefit of the signal processing as can be found in a modern hearing aid.