An electrophysiological investigation of emotional change: preliminary data

Many psychotherapy researchers agree that emotional change is critical to therapeutic progress. In emotion-focused and Gestalt therapy, one technique to foster emotional change is the empty chair dialogue. Psychotherapy research has yielded ample evidence that this technique helps to alleviate longstanding interpersonal grievances (‘unfinished business’) and facilitates emotional change. Until now, little is known about the neurophysiological correlates of such emotional change. The present study thus aims at adding a further level of analysis to psychotherapy research, and may enrich knowledge about mechanisms of change. Neurophysiological correlates of emotional change were investigated using multi-channel electroencephalography. Individuals experiencing ‘unfinished business’ were guided by experienced therapists to participate in an empty chair dialogue. Event-related brain potentials were recorded before and after the intervention while participants were viewing pictures of the person central to their interpersonal grievance as well as pictures of control persons. Event related potentials are compared regarding topography and overall signal strength. Preliminary results will be discussed regarding neurophysiological mechanisms of action potentially occurring during emotional change.

A neurophysiological fingerprint of the empty-chair dialogue

The empty chair dialogue is a validated technique used in Gestalt and emotion focused therapy to help clients overcome unresolved interpersonal grievances. It aims at influencing emotional processing in a way that emotional states characterized by advanced meaning making, thus by the integration of cognition and affect, are facilitated. Even though a variety of studies demonstrated the effectiveness of this technique as well as the usefulness of improvements in emotional processing, it remains unclear how these changes are characterized on a neuronal level. The present study aimed at tracing changes induced by the empty-chair dialogue with electrophysiological methods. Subjects reporting long-standing interpersonal grievances were recruited. After informed consent, an experienced therapist guided subjects to work on their individual interpersonal theme using the empty chair dialogue. During this one-session intervention, multichannel EEG was recorded and the session was video-taped. Afterwards, a validated observational rating instrument was used to identify time periods representing emotional states characterized by either high or low meaning making and the preprocessed, artifact-free EEG-data was labeled accordingly. Thus the comparison of neurophysiological activity during two distinct types of emotional processing becomes possible. EEG-data will be analyzed with modern methods of frequency analysis. Furthermore global field synchronization will be compared between the two types of emotional processing.

A Neural Trait Approach to Exploring Individual Differences in Social Preferences

Research demonstrates that social preferences are characterized by significant individual differences. An important question, often overlooked, is from where do these individual differences originate? And what are the processes that underlie such differences? In this paper, we outline the neural trait approach to uncovering sources of individual differences in social preferences, particularly as evidenced in economic games. We focus on two primary methods—resting-state electroencephalography and structural magnetic resonance imaging—used by researchers to quantify task-independent, brain-based characteristics that are stable over time. We review research that has employed these methods to investigate social preferences with an emphasis on a key psychological process in social decision-making; namely, self-control. We then highlight future opportunities for the neural trait approach in cutting-edge decision-making research. Finally, we explore the debate about self-control in social decision-making and the potential role neural trait research could play in this issue.

The value of susceptibility-weighted imaging (SWI) in patients with non-neonatal hypoxic-ischemic encephalopathy

OBJECTIVE In susceptibility-weighted imaging (SWI) in the normal brain, cortical veins appear hypointense due to paramagnetic properties of deoxy-hemoglobin. Global cerebral anoxia decreases cerebral oxygen metabolism, thereby increasing oxy-hemoglobin levels in cerebral veins. We hypothesized that a lower cerebral oxygen extraction fraction in comatose patients with non-neonatal hypoxic ischemic encephalopathy (IHE) produce a pattern of global rarefied or pseudo-diminished cortical veins due to higher oxy-hemoglobin. PURPOSE 1. To investigate the topographic relationship between susceptibility effects in cortical veins and related diffusion restrictions on diffusion-weighted imaging (DWI) in patients with IHE. 2. To relate imaging findings to patterns of altered resting activity on surface EEG. METHODS Twenty-three IHE patients underwent MRI. EEG patterns were used to classify the depth of coma. Regional vs. global susceptibility changes on SWI and patterns of DWI restrictions were compared with the depth of coma. RESULTS All patients exhibited areas of restricted cortical diffusion and SWI abnormalities. The dominant DWI restrictions encompassed widespread areas along the precuneus, frontal and parietal association cortices and basal ganglia. For SWI, nineteen patients had generalized bi-hemispherical patterns, the EEG patterns correlated with coma grades III to V. Four patients had focal decreases of deoxy-hemoglobin following DWI restrictions; associated with normal EEGs. CONCLUSION Focal patterns of diamagnetic effects on SWI according to relative decreases in deoxy-hemoglobin due to reduced metabolic demand are associated with normal EEG in IHE patients. Global patterns indicated increased depth of coma and widespread cortical damage. CLINICAL RELEVANCE The results indicate a potential diagnostic value of SWI in patients with IHE.

The brain’s default state interacts with working memory processes in a complex and load-dependent manner

Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.

The brain’s pre-stimulus default state interacts with working memory in a load-dependent manner

Recently, multiple studies showed that spatial and temporal features of a task-negative default mode network (DMN) (Greicius et al., 2003) are important markers for psychiatric diseases (Balsters et al., 2013). Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG and MEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects (Brookes et al., 2011). Negative correlations between DMN activity and theta amplitude have been found during resting state (Jann et al., 2010) as well as during WM (Michels et al., 2010). Likewise, WM training resulted in higher resting state theta power as well as increased small-worldness of the resting brain (Langer et al., 2013). Further, increased fMRI connectivity between nodes of the DMN correlated with better WM performance (Hampson et al., 2006). Hence, the brain’s default state might influence it’s functioning during task. We therefore hypothesized correlations between pre-stimulus DMN activity and EEG-theta power during WM maintenance, depending on the WM load. 17 healthy subjects performed a Sternberg WM task while being measured simultaneously with EEG and fMRI. Data was recorded within a multicenter-study: 12 subjects were measured in Zurich with a 64-channels MR-compatible system (Brain Products) in a 3T Philips scanner, 5 subjects with a 96-channel MR-compatible system (Brain Products) in a 3T Siemens Scanner in Bern. The DMN components was obtained by a group BOLD-ICA approach over the full task duration (figure 1). The subject-wise dynamics were obtained by back-reconstructed onto each subject’s fMRI data and normalized to percent signal change values. The single trial pre-stimulus-DMN activation was then temporally correlated with the single trial EEG-theta (3-8 Hz) spectral power during retention intervals. This so-called covariance mapping (Jann et al., 2010) yielded the spatial distribution of the theta EEG fluctuations during retention associated with the dynamics of the pre-stimulus DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention (figure 2). However, correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance in the middle of the retention period (TANOVA, p<0.05) (figure 3). Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over time. While at a more global, load-independent view pre-stimulus DMN activity correlated positively with theta power during retention, the correlation was inversed during certain time windows in high-load trials, meaning that in trials with enhanced pre-stimulus DMN activity theta power decreases during retention. Since both WM performance and DMN activity are markers of mental health our results could be important for further investigations of psychiatric populations.

Amplitude, Topographie und Latenz von EKP-Komponenten analysiert mit Hilfe von Randomisierungsstatistiken: Ein anwendungsorientierter Ragu-Workshop

Bei EKP-Experimenten ist oft nicht von vornherein klar, in welchen Zeitfenstern Effekte erwartet werden. Daher müssen Analysen die Daten über mehrere Zeitfenster hinweg explorieren. Darüber hinaus sind statistische Analysen, die alle Elektroden berücksichtigen, wünschenswert, aber nicht trivial. Zur Lösung dieser Probleme präsentieren wir hier das Programm Ragu (Randomization Graphical User interface), das spezifisch für die statistische Auswertung von Mehrkanal EEG-Experimenten eingesetzt werden kann. Ragu soll Wissenschaftlern die Möglichkeit geben, die Signifikanzen von EKP-Effekten global zu untersuchen, ohne die Notwendigkeit von A-Priori-Annahmen. Das Programm basiert auf der Messung von Feldstärke-Differenzen unter Berücksichtigung aller Elektroden. Im ersten Teil dieses Workshops werden wir die Notwendigkeit von topografischen ERP-Analysen angesichts des Volumenleitungsproblems herausarbeiten und Vergleiche zu Einzelelektroden-Ansätzen anstellen. Wir werden an Hand unserer frei erhältlichen in-house Software Ragu das Prinzip von Randomisierungsstatistiken erklären und deren unterschiedliche Anwendungsmöglichkeiten für ERP-Analysen. In einem zweiten Teil haben die Teilnehmenden die Gelegenheit, Ragu an einem Beispielsatz auszuprobieren und Möglichkeiten der Anwendung von Ragu in ihrer eigenen Forschungs zu besprechen.

Baclofen facilitates sleep, neuroplasticity, and recovery after stroke in rats.

OBJECTIVE Sleep disruption in the acute phase after stroke has detrimental effects on recovery in both humans and animals. Conversely, the effect of sleep promotion remains unclear. Baclofen (Bac) is a known non-rapid eye movement (NREM) sleep-promoting drug in both humans and animals. The aim of this study was to investigate the effect of Bac on stroke recovery in a rat model of focal cerebral ischemia (isch). METHODS Rats, assigned to three experimental groups (Bac/isch, saline/isch, or Bac/sham), were injected twice daily for 10 consecutive days with Bac or saline, starting 24 h after induction of stroke. The sleep-wake cycle was assessed by EEG recordings and functional motor recovery by single pellet reaching test (SPR). In order to identify potential neuroplasticity mechanisms, axonal sprouting and neurogenesis were evaluated. Brain damage was assessed by Nissl staining. RESULTS Repeated Bac treatment after ischemia affected sleep, motor function, and neuroplasticity, but not the size of brain damage. NREM sleep amount was increased significantly during the dark phase in Bac/isch compared to the saline/isch group. SPR performance dropped to 0 immediately after stroke and was recovered slowly thereafter in both ischemic groups. However, Bac-treated ischemic rats performed significantly better than saline-treated animals. Axonal sprouting in the ipsilesional motor cortex and striatum, and neurogenesis in the peri-infarct region were significantly increased in Bac/isch group. CONCLUSION Delayed repeated Bac treatment after stroke increased NREM sleep and promoted both neuroplasticity and functional outcome. These data support the hypothesis of the role of sleep as a modulator of poststroke recovery.

Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

Taking personalized medicine seriously: Biomarker approaches in phase IIb/III studies in major depression and schizophrenia

The success rate in the development of psychopharmacological compounds is insufficient. Two main reasons for failure have been frequently identified: 1) treating the wrong patients and 2) using the wrong dose. This is potentially based on the known heterogeneity among patients, both on a syndromal and a biological level. A focus on personalized medicine through better characterization with biomarkers has been successful in other therapeutic areas. Nevertheless, obstacles toward this goal that exist are 1) the perception of a lack of validation, 2) the perception of an expensive and complicated enterprise, and 3) the perception of regulatory hurdles. The authors tackle these concerns and focus on the utilization of biomarkers as predictive markers for treatment outcome. The authors primarily cover examples from the areas of major depression and schizophrenia. Methodologies covered include salivary and plasma collection of neuroendocrine, metabolic, and inflammatory markers, which identified subgroups of patients in the Netherlands Study of Depression and Anxiety. A battery of vegetative markers, including sleep-electroencephalography parameters, heart rate variability, and bedside functional tests, can be utilized to characterize the activity of a functional system that is related to treatment refractoriness in depression (e.g., the renin-angiotensin-aldosterone system). Actigraphy and skin conductance can be utilized to classify patients with schizophrenia and provide objective readouts for vegetative activation as a functional marker of target engagement. Genetic markers, related to folate metabolism, or folate itself, has prognostic value for the treatment response in patients with schizophrenia. Already, several biomarkers are routinely collected in standard clinical trials (e.g., blood pressure and plasma electrolytes), and appear to be differentiating factors for treatment outcome. Given the availability of a wide variety of markers, the further development and integration of such markers into clinical research is both required and feasible in order to meet the benefit of personalized medicine. This article is based on proceedings from the "Taking Personalized Medicine Seriously-Biomarker Approaches in Phase IIb/III Studies in Major Depression and Schizophrenia" session, which was held during the 10th Annual Scientific Meeting of the International Society for Clinical Trials Meeting (ISCTM) in Washington, DC, February 18 to 20, 2014.

Association between intraoperative electroencephalographic suppression and postoperative mortality

BACKGROUND Low bispectral index values frequently reflect EEG suppression and have been associated with postoperative mortality. This study investigated whether intraoperative EEG suppression was an independent predictor of 90 day postoperative mortality and explored risk factors for EEG suppression. METHODS This observational study included 2662 adults enrolled in the B-Unaware or BAG-RECALL trials. A cohort was defined with >5 cumulative minutes of EEG suppression, and 1:2 propensity-matched to a non-suppressed cohort (≤5 min suppression). We evaluated the association between EEG suppression and mortality using multivariable logistic regression, and examined risk factors for EEG suppression using zero-inflated mixed effects analysis. RESULTS Ninety day postoperative mortality was 3.9% overall, 6.3% in the suppressed cohort, and 3.0% in the non-suppressed cohort {odds ratio (OR) [95% confidence interval (CI)]=2.19 (1.48-3.26)}. After matching and multivariable adjustment, EEG suppression was not associated with mortality [OR (95% CI)=0.83 (0.55-1.25)]; however, the interaction between EEG suppression and mean arterial pressure (MAP) <55 mm Hg was [OR (95% CI)=2.96 (1.34-6.52)]. Risk factors for EEG suppression were older age, number of comorbidities, chronic obstructive pulmonary disease, and higher intraoperative doses of benzodiazepines, opioids, or volatile anaesthetics. EEG suppression was less likely in patients with cancer, preoperative alcohol, opioid or benzodiazepine consumption, and intraoperative nitrous oxide exposure. CONCLUSIONS Although EEG suppression was associated with increasing anaesthetic administration and comorbidities, the hypothesis that intraoperative EEG suppression is a predictor of postoperative mortality was only supported if it was coincident with low MAP. CLINICAL TRIAL REGISTRATION NCT00281489 and NCT00682825.

Psychomotor retardation is linked to frontal alpha asymmetry in major depression

BACKGROUND Psychomotor disturbances are a main clinical feature of major depressive disorder (MDD) but little is known about their EEG signature. One of the most replicated EEG findings in MDD is resting frontal asymmetry in the alpha band (FAA), which is thought to be a correlate of withdrawal behavior and reduced approach motivation. The purpose of this study was to assess psychomotor alterations, alpha band power, FAA and investigate the association between them. METHODS 20 MDD patients and 19 healthy subjects were enrolled. Alpha power and FAA scores were calculated from a resting state EEG. Wrist actigraphy was recorded from the non-dominant arm for 24 h and activity level scores (AL) were extrapolated from the wakeful periods. RESULTS MDD patients had a left-lateralized frontal alpha activity and lower AL scores when compared to healthy subjects. A significant correlation was found between mean FAA and AL scores. A negative covariance between power in the lower alpha range and AL scores over the motor cortex bilaterally was detected. LIMITATIONS Relatively small sample size. Patients were pharmacologically treated with antidepressants. CONCLUSIONS This study replicates the finding of left-lateralized FAA and lower AL scores in MDD patients, and establishes the first evidence of significant correlations between alpha power, FAA scores and measures of motor activity, which may be interpreted as an expression of impaired motivational drive in MDD.

Statistical Learning, Syllable Processing, and Speech Production in Healthy Hearing and Hearing-Impaired Preschool Children: A Mismatch Negativity Study

OBJECTIVES The objectives of the present study were to investigate temporal/spectral sound-feature processing in preschool children (4 to 7 years old) with peripheral hearing loss compared with age-matched controls. The results verified the presence of statistical learning, which was diminished in children with hearing impairments (HIs), and elucidated possible perceptual mediators of speech production. DESIGN Perception and production of the syllables /ba/, /da/, /ta/, and /na/ were recorded in 13 children with normal hearing and 13 children with HI. Perception was assessed physiologically through event-related potentials (ERPs) recorded by EEG in a multifeature mismatch negativity paradigm and behaviorally through a discrimination task. Temporal and spectral features of the ERPs during speech perception were analyzed, and speech production was quantitatively evaluated using speech motor maximum performance tasks. RESULTS Proximal to stimulus onset, children with HI displayed a difference in map topography, indicating diminished statistical learning. In later ERP components, children with HI exhibited reduced amplitudes in the N2 and early parts of the late disciminative negativity components specifically, which are associated with temporal and spectral control mechanisms. Abnormalities of speech perception were only subtly reflected in speech production, as the lone difference found in speech production studies was a mild delay in regulating speech intensity. CONCLUSIONS In addition to previously reported deficits of sound-feature discriminations, the present study results reflect diminished statistical learning in children with HI, which plays an early and important, but so far neglected, role in phonological processing. Furthermore, the lack of corresponding behavioral abnormalities in speech production implies that impaired perceptual capacities do not necessarily translate into productive deficits.

Subjective perception of sleepiness in a driving simulator is different from that in the Maintenance of Wakefulness Test.

OBJECTIVE To test whether sleep-deprived, healthy subjects who do not always signal spontaneously perceived sleepiness (SPS) before falling asleep during the Maintenance of Wakefulness Test (MWT) would do so in a driving simulator. METHODS Twenty-four healthy subjects (20-26 years old) underwent a MWT for 40 min and a driving simulator test for 1 h, before and after one night of sleep deprivation. Standard electroencephalography, electrooculography, submental electromyography, and face videography were recorded simultaneously to score wakefulness and sleep. Subjects were instructed to signal SPS as soon as they subjectively felt sleepy and to try to stay awake for as long as possible in every test. They were rewarded for both "appropriate" perception of SPS and staying awake for as long as possible. RESULTS After sleep deprivation, seven subjects (29%) did not signal SPS before falling asleep in the MWT, but all subjects signalled SPS before falling asleep in the driving simulator (p <0.004). CONCLUSIONS The previous results of an "inaccurate" SPS in the MWT were confirmed, and a perfect SPS was shown in the driving simulator. It was hypothesised that SPS is more accurate for tasks involving continuous feedback of performance, such as driving, compared to the less active situation of the MWT. Spontaneously perceived sleepiness in the MWT cannot be used to judge sleepiness perception while driving. Further studies are needed to define the accuracy of SPS in working tasks or occupations with minimal or no performance feedback.

Towards Using Microstate-Neurofeedback for the Treatment of Psychotic Symptoms in Schizophrenia. A Feasibility Study in Healthy Participants

Spontaneous EEG signal can be parsed into sub-second periods of stable functional states (microstates) that assumingly correspond to brief large scale synchronization events. In schizophrenia, a specific class of microstate (class "D") has been found to be shorter than in healthy controls and to be correlated with positive symptoms. To explore potential new treatment options in schizophrenia, we tested in healthy controls if neurofeedback training to self-regulate microstate D presence is feasible and what learning patterns are observed. Twenty subjects underwent EEG-neurofeedback training to up-regulate microstate D presence. The protocol included 20 training sessions, consisting of baseline trials (resting state), regulation trials with auditory feedback contingent on microstate D presence, and a transfer trial. Response to neurofeedback was assessed with mixed effects modelling. All participants increased the percentage of time spent producing microstate D in at least one of the three conditions (p < 0.05). Significant between-subjects across-sessions results showed an increase of 0.42 % of time spent producing microstate D in baseline (reflecting a sustained change in the resting state), 1.93 % of increase during regulation and 1.83 % during transfer. Within-session analysis (performed in baseline and regulation trials only) showed a significant 1.65 % increase in baseline and 0.53 % increase in regulation. These values are in a range that is expected to have an impact upon psychotic experiences. Additionally, we found a negative correlation between alpha power and microstate D contribution during neurofeedback training. Given that microstate D has been related to attentional processes, this result provides further evidence that the training was to some degree specific for the attentional network. We conclude that microstate-neurofeedback training proved feasible in healthy subjects. The implementation of the same protocol in schizophrenia patients may promote skills useful to reduce positive symptoms by means of EEG-neurofeedback.