Frontal encephalographic (EEG) alpha asymmetry has been proposed as a measure of the relative difference in average cortical activity between the right and left anterior cortex, where this difference is taken as a physiological marker of trait and state level variables associated with affect. The validity of asymmetry as an indicator of both physiological and psychological variables is in part determined by the psychometric properties of asymmetry scores. The present studies focus on the psychometric assessment of frontal alpha asymmetry measured during rest. The first study involves a novel approach in the assessment of the internal consistency reliability of asymmetry scores. Previous studies estimated internal consistency reliability via Cronbach's alpha, using a relatively small set of asymmetry score that summarized activity over segments of the EEG data (e.g. one minute). Such an approach, however, will create estimates dependent on the number of segments utilized rather than the total amount of data recorded. Thus in the first study, individual FFT epochs were treated as items, thereby maximizing the total number of items used to estimate internal consistency reliability. Results of this study suggest internal consistency reliability is greater than previously reported, and as such, the duration of resting EEG data necessary to achieve a reasonable reliability criterion may be shorter than the current standard. In the second study, asymmetry scores were assessed as a specific case of difference scores, which are susceptible to a statistical artifact associated with differences in true-score variance for the component measures. Predicted asymmetry scores associated with the statistical artifact were obtained by estimating the true-score variance of right and left alpha power. The use of hierarchical linear regression showed some influence of the statistical artifact on the relationship between asymmetry scores and a measure of depressive severity, suggesting that some caution may be warranted in interpreting asymmetry results with relatively small effect sizes.

<div> <div> <div> <p>Major depressive disorder (MDD) and risk for its development are characterized by reduced reactivity and flexibility to environmental demands. Frontal alpha asymmetry (FAA), heart rate variability (HRV), and salivary cortisol reactivity are each well-established indicators of regulation across neural, autonomic, and hypothalamic-pituitary-adrenal (HPA) physiological systems, respectively. Growing literature suggests that each of these processes is dysregulated in individuals with a history of MDD. However, patterns of dysregulation across these physiological systems and relative MDD risk are unknown. Moreover, these physiological regulatory patterns may extent beyond markers of MDD risk in adulthood to also capture the transmission of risk for MDD from parent to offspring. The following series of five studies investigated the pathophysiology of MDD and the permeability of risk across the lifespan. First, the pattern of dysregulation across physiological indices—representing neural, autonomic, and HPA functioning—in adults was examined with regard to depressive symptoms. Second, the associations amongst infant FAA, HRV, and cortisol reactivity and maternal depressive symptoms were assessed as potential early markers of depression risk. Third, mother-infant associations across physiological indices were investigated to assess direct intergenerational transmission of depression risk. Studies 4 and 5 further investigated pathophysiological functioning in mothers and infants within the context of comorbid anxiety and current depressive symptomatology versus lifetime MDD illness. Mothers and their 12-month-old infants (n = 35 dyads) completed resting- state and stressor tasks to assess regulatory patterns across neural, autonomic, and HPA systems, associations with MDD, and intergenerational transmission. In adults, results suggest that lifetime history of MDD is significantly associated with blunted cortisol reactivity; FAA and high- frequency HRV also demonstrated the same direction of associations. In infants, results demonstrated that maternal depressive symptoms, particularly current symptoms, relate to blunted physiological regulation in infants specifically for FAA and HRV indices. For mothers and infants, there was support for the direct intergenerational transmission of FAA and HRV indices. These intergenerational associations did not fully account for intergenerational risk of depression, as maternal physiological regulation and maternal depression were found to each significantly predict infant regulation as simultaneous predictors. Accounting for comorbid anxiety and examining current symptoms versus lifetime illness were essential to investigating associations amongst physiological functioning and depression. These patterns in conjunction with the literature suggest a developmental model to MDD pathophysiology that encompasses multiple theoretical frameworks. Future research is necessary to clarify regulatory patterns across physiological systems within individuals and across time with regard to MDD risk, onset, and course.</p></div></div></div>

Frontal Alpha Asymmetry (FAA) has been associated with individual differences such as various aspects of personality. However, the nature of the relationship between FAA and personality traits is not yet fully understood. The present study further investigated this relationship by exploring the correlation between resting-state FAA and the Big Five personality traits: openness, agreeableness, conscientiousness, extraversion, and neuroticism. 15 healthy participants completed resting-state EEG recordings three times and the Big Five Personality Inventory (BFI) twice. The results showed only one statistically significant correlation among the 20 correlations examined, between the F4-F3 resting-state FAA and openness scores. Besides, the direction of the relationship was the opposite of what would be expected. The small sample size of this study may have contributed to results, indicating the need for future research with larger samples. Nonetheless, the current findings add to the existing literature and suggest that the relationship between resting-state FAA and personality traits may be more complex than previously thought.

The current paper examined the relationship between frontal alpha asymmetry (FAA) and threatening face stimuli. Participants were presented with threatening faces, and this was compared to non-threatening (neutral) faces, on the assumption that the threatening faces would trigger a withdrawal motivation and a corresponding decrease in state FAA scores. The EEG data used in the present analysis was taken from an earlier study at the University of Skövde, consisting of twenty-eight participants with no reported current ongoing neurological or psychiatric illnesses, or epilepsy. Based on the paired samples t-test there was no significant statistical difference between participants’ FAA scores in the threatening and non-threatening conditions. The relatively small sample of the present study may be a contributing factor. Furthermore, threatening face images may elicit weaker responses than non-facial images such as threatening images of domestic violence or natural disasters. In the future, the field of FAA may benefit from investigating the connection between FAA and non-facial threatening and non-threatening images, instead of faces.

Background: Postpartum Depression (PPD) affects up to one in five mothers. While psychotherapy can effectively reduce symptoms of PPD, it is unclear how PPD treatment affects maternal psychophysiology. Determining physiological changes in response to cognitive behavioural therapy (CBT) could provide insights into the mechanisms underlying effective treatment and/or help predict treatment outcomes. This study examined if treating PPD with CBT led to changes in frontal cortical activity and heart rate variability, two markers of maternal emotion regulatory capacity. Methods: Community-dwelling mothers with PPD (Edinburgh Postnatal Depression Scores ≥10) were randomized to receive nine weeks of group CBT delivered by recovered peers (i.e., those who had previously recovered from PPD) (n=26) or be put on a waitlist to receive the intervention nine weeks later (n=24). Electroencephalographic (frontal alpha asymmetry), electrocardiographic (heart rate variability), and clinical (depression, anxiety) data were collected at baseline and nine weeks later. Results: Participants in both the immediate treatment and waitlist control groups reported moderate levels of depression and anxiety at baseline. After treatment, mothers in the treatment group showed greater improvements in depression (p<0.01, Cohen d=1.22), and anxiety (p<0.005, Cohen d = 1.48), and high-frequency heart rate variability (p<0.05, Cohen d=0.70), but not frontal alpha asymmetry, compared to the waitlist control group. Conclusion: Group CBT for PPD can improve symptoms of depression and anxiety and parasympathetic nervous system function. Future research should attempt to replicate and extend these findings using larger samples, additional biomarkers, and longer periods of follow up. Examining how evidence-based treatments for PPD affect maternal psychophysiology can improve our understanding and potentially predict treatment effects. / Thesis / Master of Science (MSc) / Postpartum depression affects up to one in five mothers in the first year after delivery. When treated promptly with talking therapies (i.e., psychotherapy) such as cognitive behavioural therapy (CBT), many experience significant improvements in their symptoms. However, the changes occurring in the brain and the remainder of the nervous system occurring in response to psychotherapy is not well known. It is important that this is understood so that we can develop more effective treatments and better predict who will respond to different types of treatments. In particular, the role of the frontal lobe of the brain, and the body’s parasympathetic system is poorly understood in the context of PPD. This thesis aimed to examine the impact of CBT on women’s frontal lobe functioning using a measure called frontal alpha asymmetry (FAA) measured via electroencephalography (EEG), and parasympathetic nervous system-based heart rate variability (HRV) using electrocardiography (ECG). In this study, we compared mothers with PPD treated with CBT to those who did not receive this treatment. We found that HRV responded in mothers who received CBT compared to women who were in the control group. No significant changes were found for FAA after treatment. These results suggest that HRV may be explored further as a valid treatment outcome for CBT when provided to women with PPD.

Extensive research has been conducted on the relationship between brain activity and personality traits, and several theories propose a lateralization of specific personality qualities. A prominent model suggests frontal lateralization of motivational direction, specifically, the behavioral inhibition and activation systems (BIS/BAS), with greater right frontal activity linked to behavioral inhibition and greater left frontal activity linked to behavioral activation. Recent studies have presented contrasting findings in the absence of this correlation. With the present study I aimed to investigate the link between frontal lateralization and the BIS/BAS. I further examined the test-retest reliability of resting-state frontal alpha asymmetry (FAA), and of the BIS/BAS scale. Resting-state frontal EEG asymmetry and participants’ responses to the BIS/BAS scale were collected from University of Skövde students on multiple occasions. FAA were obtained from electrode sites F4-F3, F6-F5, and F8-F7 over three sessions, two weeks apart, along with BIS/BAS scores from the first and third sessions. Within-subject FAA showed variability over time, suggesting FAA to be a less reliable measure of personality traits. Only two out of the four BIS/BAS subscales demonstrated consistent scores, raising doubts about the reliability of using it to assess personality traits. BAS Drive correlated negatively with FAA, contrary to the expected direction, but no other significant correlation was observed between resting-state FAA and BIS/BAS. Verifying FAA as an indicator of BIS and BAS is important for drawing meaningful associations between them. Future research should consider employing a repeated measures design and a larger sample size to enhance the understanding of this relationship.

<p dir="ltr">Abstract: Atypical frontal alpha asymmetry is the difference in EEG-measured alpha-band power between right and left hemispheres, and patterns of lateralization are thought to reflect motivational direction (approach/withdrawal) and affective processing. Increased rightward frontal alpha asymmetry is associated with tendency toward approach-related behavior often displayed in attention-deficit/hyperactivity disorder (ADHD), though findings have been inconsistent. While differences in results may be partially accounted for by within-diagnosis heterogeneity, growing evidence suggests individual response tendency and emotional salience of a situation may influence one another. Investigating the potential interactions between trait and state measured variables may therefore clarify lateralization patterns in ADHD. The current study measured frontal alpha asymmetry in a well-characterized sample of school-aged children with and without ADHD. EEG during standard resting-state and emotional passive-viewing tasks were recorded from 220 children (nADHD = 97). A semi-structured clinical interview and standardized rating scales were collected to assign DSM-5 diagnoses and temperament group belonging. Parent measures included the behaviorally-rated Temperament in Middle Childhood Questionnaire (TMCQ). Latent profile analysis within the ADHD group revealed two temperament subgroups: emotionally regulated and emotionally dysregulated (high anger and sadness). EEG assessment suggests children broadly produced a more rightward asymmetry while in resting state compared to a task-based condition, though show no notable differences between neutral and negative emotional task conditions. ADHD diagnostic status, temperament group, and sex assigned at birth did not impact patterns of asymmetry. Results emphasize measurement differences in frontal alpha asymmetry between lab-based tasks and further highlight the importance of state influences on alpha lateralization.</p>

The immune system has been suggested as crucial in brain and psychological functioning. More precisely, immune markers reflecting immune system activity are important for psychological and mental health, as evident by their role in the physiopathology of depression and in the impairment of executive functions. Frontal alpha asymmetry (FAA), an electroencephalographic marker of brain function, has also been linked to such psychopathology and is thought to reflect psychological processes underlying approach- versus withdrawal-related motivation and higher-order inhibitory control. Only a few studies have linked FAA to immune markers but notably found a negative association between IL-6, a pleiotropic pro-inflammatory cytokine, and FAA. The aim of the present work is thus to study the relationship between various immune markers (including pro-inflammatory cytokines and IL-6) and FAA. 35 healthy young male participants underwent a resting EEG recording and blood sampling from which immune markers were measured. The results did not suggest an association between IL-6 and FAA. No other immune markers were either suggested to be associated to FAA. The complexity of the immune system (e.g., effect of cytokines) is underlined and may explain the results. Despite such results, the implication of true negative correlations between FAA and circulating immune markers, as suggested in previous studies, is discussed in the light of the theoretical models of FAA.

<p> Although interest in brain-computer interfaces (BCIs) from researchers and consumers continues to increase, many BCIs lack the complexity and imaginative properties thought to guide users towards successful brain activity modulation. In this research, an experimental story brain-computer interface (ES-BCI) was developed, with which users could interact using cognitive strategies; specifically, thinking about the story and engaging with the main character of the story through their thought processes. In this system, the user’s frontal alpha asymmetry (FAA) measured with electroencephalography (EEG) was linearly mapped to the color saturation of the main character in the story. Therefore, the color saturation of the main character increased as FAA recorded from the participant’s brain activity increased above the FAA threshold required to receive visual feedback. A user-friendly experimental design was implemented using a comfortable EEG device and short neurofeedback (NF) training protocol. Eight distinct story scenes, each with a View and Engage NF component were created, and are referred to as blocks. In this system, seven out of 19 participants successfully increased FAA during the course of the study, for a total of ten successful blocks out of 152. Results concerning left (Lact) and right (Ract) prefrontal cortical activity contributions to FAA in both successful and unsuccessful blocks were examined to understand FAA measurements in greater detail. Additionally, electrodermal activity data (EDA) and self-reported questionnaire data were investigated to understand the user experience with this ES-BCI. Results suggest the potential of ES-BCI environments for engaging users and allowing for FAA modulation. New research directions for artistic BCIs investigating affect are discussed. </p>

In this thesis we examine the question whether it is possible to model approach and avoidance behaviour with probabilistic machine learning. The results from this project will primarily aid in our collective understanding of human existence. Secondly, it will extend the knowledge with regards to probabilistic machine learning in the Neuroscience domain. We aid this through building a Variational Recurrent Neural Network (VRNN) that is trained on Electroencephalography (EEG)-data from participants that is subjected to odours with varying pleasantness. The pleasantness of the odours is used to divide the participants into two classes based on their self reported experience. This data is used to train the VRNN. The performance of the VRNN is evaluated by how well we are able to reconstruct the original data from a low dimensional latent representation. In this task the model performs on a similar level as related works. We further investigate how changes in the latent space effects reconstructed data. Despite being disentangled, the latent variables are hard to interpret. Furthermore we try to classify and cluster the latent space as either approach or avoidance behaviour with a Support Vector Machine and Uniform Manifold Approximation. The classification results are only slightly better than random, indicating that the learned latent space is not suitable for the task This is most likely due to the patterns that make up approach and avoidance behaviour is seen as noise by the VRNN. This leads to the patterns not being accurately modelled. This is shown by the evidence that frontal α -asymmetry that exists in the data is not reconstructed by the model. The conclusion is therefore that a VRNN is less suitable for modelling underlying behaviour from raw EEG data due to the low signal to noise ratio. We instead suggests to focus on specific frequency ranges in specific regions when applying machine learning in this domain. / Den här uppsatsen behandlar frågan huruvida det är möjligt att modellera närmande och frånstötande beteendemönster med hjälp av maskininlärning. Resultaten från detta projekt ämnar huvudsakligen att främja vidare förståelse av den mänskliga existensen. Vidare ämnar den även att utvidga förståelsen av hur probabilistisk maskininlärning kan användas för att utforska dylika hänseenden. Vi genomför detta genom att bygga en Variational Recurrent Neural Network-modell (VRNN) som tränas på data från experiment där personer utsätts för olika lukter samtidigt som deras Elektroencefalografi (EEG) spelas in. Deltagarna delas in i två klasser beroende på deras självrapporterade upplevelse av luktens njutbarhet. Maskininlärningsmodellen utvärderas genom att vi analyserar hur väl den lyckas rekonstruera datan. Detta lyckas den väl med. Vidare så undersöker vi hur förändringar i modellens latenta rum påverkar rekonstrueringen av datan. Resultaten från det experimentet är ej tydliga. Vidare så försöker vi klassificera och klustra det latenta rummet med avseende på närmande och frånstötande beteende med hjälp av en Support Vector Machine och Uniform Manifold Approximation. Resultaten från dessa experiment är att vi inte lyckas klassificera eller klustra det latenta rummet med avseende på närmande och frånstötande beteende bättre än slumpen. Vi argumenterar för att detta beror på att de underliggande mönster som skapar dessa beteenden ses som brus av VRNN-modellen och därmed inte modelleras. Detta visas genom att frontal α-asymmetri som existerar i datan ej rekonstrueras av modellen. Slutsaten blir därmed att en VRNN är mindre passande att använda vid modellering av underliggande beteenden av obehandlad EEG data. Detta på grund av det låga signal till brus-förhållandet i EEG-datan. Vi föreslår att istället fokusera på specifika frekvensområden i specifika hjärnregioner när maskininlärning appliceras på EEG.