A pszichológiai jóllét szociodemográfiai korrelátumai, kapcsolata a big five vonásokkal és az optimizmussal

Elméleti háttér A pszichológiai jóllét többtényezos modelljét Ryff alkotta meg 1989-ben. Korábbi kutatások rámutattak arra, hogy a pszichológiai jóllét az extraverzióval pozitív, a neuroticizmussal pedig negatív irányú összefüggést mutat, továbbá igazolták a pszichológiai jóllét és az optimizmus közötti kapcsolatot. Cél Jelen tanulmány arra keresi a választ, hogy milyen mértékben alkalmasak az ötfaktoros elmélet személyiségvonásai a pszichológiai jóllét szintjének elorejelzésére magyar mintán (figyelembe véve a demográfiai tényezok hatását is), illetve, hogy az optimizmus képes-e bejósolni a pszichológiai jóllét szintjét a big five dimenziók kontrollálása után is. Módszer Keresztmetszeti vizsgálatunkban 314 felnott (63,7% no; átlagéletkor: 29,5 év, SD =10,96 év) vett részt. Méroeszközök: szociodemográfiai kérdések, Big Five Kérdoív, Pszichológiai Jóllét Skála, Életszemlélet Teszt. Eredmények Az alábbi szociodemográfiai változók mutattak kapcsolatot a pszichológiai jólléttel: az anyagi helyzet; a jelenlegi lakóhely; az apa iskolai végzettsége; és az anya iskolai végzettsége. A személyiségváltozók közül a diszpozicionális optimizmus eros, pozitív irányú együttjárást (r = 0,61; p 2 = 59,9%; X2(17) = 156,35; p 2 = 61,7%; X2(18) = 162,75; p 2(1) = 6,39; p = 0,011). Következtetés Jelen kutatás egy újabb bizonyíték azon kutatások sorában, amelyek azt demonstrálják, hogy a személyiség lényeges szerepet játszik a pszichológiai jóllét alakulásában. Az eredmények azt is sugallják, hogy az optimizmus önálló, a big five dimenzióktól független magyarázóerovel bír a jóllét szintjének alakulása tekintetében. | Background The multidimensional model of psychological well-being (PWB) was originally proposed by Ryff in 1989. Empirical studies investigating the relationship of personality and psychological well-being have clearly shown that extraversion (+), neuroticism (−) and optimism (+) are related to well-being. Aims We seek to answer two questions: (1) can personality predict psychological well-being after controlling for demographic variables? and (2) can optimism predict well-being after controlling for the effects of the Big Five dimensions? Method In our cross-sectional study 314 persons (63.7% women, mean age: 29.5 years, SD =10.96 years) took part. As the first step of the study, we recorded sociodemographic data, then participants completed the Big Five Questionnaire, Scales of Psychological Well-Being and the Life Orientation Test. Results We found that financial status, current place of residence and parent’s education had a significant effect on psychological well-being. Dispositional optimism was found to be moderately correlated with PWB (r = .61, p 2 = 59.9%; χ2(17) = 156.35, p 2 = 61.7%; χ2(18) = 162.75; p 2(1) = 6.39; p = .011). Conclusions Our findings are consistent with previous research suggesting that the big five factors play an important role in PWB. Furthermore, they also demonstrate that optimism has a significant effect on one’s psychological well-being, and this effect is independent from that of the big five factors

Midfrontal theta activity in psychiatric illness: An index of cognitive vulnerabilities across disorders

There is an urgent need to identify the mechanisms that contribute to atypical thinking and behavior associated with psychiatric illness. Behavioral and brain measures of cognitive control are associated with a variety of psychiatric disorders and conditions as well as daily life functioning. Recognition of the importance of cognitive control in human behavior has led to intensive research into behavioral and neurobiological correlates. Oscillations in the theta band (4–8 Hz) over medial frontal recording sites are becoming increasingly established as a direct neural index of certain aspects of cognitive control. In this review, we point toward evidence that theta acts to coordinate multiple neural processes in disparate brain regions during task processing to optimize behavior. Theta-related signals in human electroencephalography include the N2, the error-related negativity, and measures of theta power in the (time-)frequency domain. We investigate how these theta signals are affected in a wide range of psychiatric conditions with known deficiencies in cognitive control: anxiety, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, and substance abuse. Theta-related control signals and their temporal consistency were found to differ in most patient groups compared with healthy control subjects, suggesting fundamental deficits in reactive and proactive control. Notably, however, clinical studies directly investigating the role of theta in the coordination of goal-directed processes across different brain regions are uncommon and are encouraged in future research. A finer-grained analysis of flexible, subsecond-scale functional networks in psychiatric disorders could contribute to a dimensional understanding of psychopathology

Genetic overlap between midfrontal theta signals and ADHD and ASD in a longitudinal twin cohort

Background: Cognitive control has been strongly linked to midfrontal theta (4-8 Hz) brain activity. Such control processes are known to be impaired in those with psychiatric conditions, and neurodevelopmental diagnoses, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Temporal variability in theta in particular is associated with ADHD with shared genetic variance underlying the relationship. Here, we investigated the phenotypic and genetic relationships between theta phase variability, theta-related signals (N2, ERN, Pe), reaction time, and ADHD and ASD longitudinally in a large twin study of young adults to investigate the stability of the genetic relationships between these measures over time. Methods: Genetic multivariate liability threshold models were run on a longitudinal sample of 566 participants (283 twin pairs). Characteristics of ADHD and ASD were measured in childhood and in young adulthood, while EEG was recorded in young adulthood during an arrow flanker task. Results: Cross-trial theta phase variability in adulthood showed large positive phenotypic and genetic relationships with reaction time variability and both childhood and adult ADHD characteristics. Pe amplitude was negatively related phenotypically and genetically to ADHD and ASD at both time points. Conclusions: We show significant genetic associations between variability in theta signalling and ADHD. In a novel finding, we show that these relationships are stable across time, indicating a core dysregulation of the temporal coordination of control processes in ADHD that persists in those with childhood symptoms. Error processing, indexed by the Pe, was altered in both ADHD and ASD, with a strong genetic contribution

Event-induced modulation of aperiodic background EEG: Attention-dependent and age-related shifts in E:I balance, and their consequences for behavior

The broadband shape of the EEG spectrum, summarized using the slope of a 1/fx function, is thought to reflect the balance between excitation and inhibition in cortical regions (E:I balance). This balance is an important characteristic of neural circuits and could inform studies of aging, as older adults show a relative deficit in inhibitory activity. Thus far, no studies have leveraged the event-related temporal dynamics of 1/fx activity to better understand the phases of information processing, especially in the context of aging. Here, for the first time, we examined variations of this activity during the foreperiod of a cued flanker task in younger (YA) and older adults (OA), with picture cues varying in task relevance, relative novelty, and valence. We report a biphasic change in the spectral slope after cue presentation, independent of cue-elicited event-related potentials (ERPs), with an initial period of steeper slope (indicating cortical inhibition, similar in YA and OA) followed by a flattening (indicating cortical excitation, especially in OA). The reduction in slope steepness was associated with lower performance and greater congruency costs in the flanker task. Finally, more novel cues reduced the shift towards excitation in OA, partly restoring their E:I balance, and diminishing congruency costs. These findings demonstrate that the broadband shape of the EEG spectrum varies dynamically in a manner that is predictive of subsequent behavior. They also expand our understanding of how neural communication shapes cognition in YA and OA and has implications for neuroscientific models of cognitive processing and age-related cognitive decline

What has been learned from using EEG methods in research of ADHD?

Electrophysiological recording methods, including electroencephalography (EEG) and magnetoencephalography (MEG), have an unparalleled capacity to provide insights into the timing and frequency (spectral) composition of rapidly changing neural activity associated with various cognitive processes. The current chapter provides an overview of EEG studies examining alterations in brain activity in ADHD, measured both at rest and during cognitive tasks. While EEG resting state studies of ADHD indicate no universal alterations in the disorder, event-related studies reveal consistent deficits in attentional and inhibitory control and consequently inform the proposed cognitive models of ADHD. Similar to other neuroimaging measures, EEG research indicates alterations in multiple neural circuits and cognitive functions. EEG methods – supported by the constant refinement of analytic strategies – have the potential to contribute to improved diagnostics and interventions for ADHD, underlining their clinical utility

The impact of 1/f activity and baseline correction on the results and interpretation of time-frequency analyses of EEG/MEG data: A cautionary tale

Typically, time-frequency analysis (TFA) of electrophysiological data is aimed at isolating narrowband signals (oscillatory activity) from broadband non-oscillatory (1/f) activity, so that changes in oscillatory activity resulting from experimental manipulations can be assessed. A widely used method to do this is to convert the data to the decibel (dB) scale through baseline division and log transformation. This procedure assumes that, for each frequency, sources of power (i.e., oscillations and 1/f activity) scale by the same factor relative to the baseline (multiplicative model). This assumption may be incorrect when signal and noise are independent contributors to the power spectrum (additive model). Using resting-state EEG data from 80 participants, we found that the level of 1/f activity and alpha power are not positively correlated within participants, in line with the additive but not the multiplicative model. Then, to assess the effects of dB conversion on data that violate the multiplicativity assumption, we simulated a mixed design study with one between-subject (noise level, i.e., level of 1/f activity) and one within-subject (signal amplitude, i.e., amplitude of oscillatory activity added onto the background 1/f activity) factor. The effect size of the noise level × signal amplitude interaction was examined as a function of noise difference between groups, following dB conversion. Findings revealed that dB conversion led to the over- or under-estimation of the true interaction effect when groups differing in 1/f levels were compared, and it also led to the emergence of illusory interactions when none were present. This is because signal amplitude was systematically underestimated in the noisier compared to the less noisy group. Hence, we recommend testing whether the level of 1/f activity differs across groups or conditions and using multiple baseline correction strategies to validate results if it does. Such a situation may be particularly common in aging, developmental, or clinical studies

Associations between EEG measures and persistence and remission of ADHD and autism and what it means in terms of Quality of Life

Attention-deficit/hyperactivity disorder (ADHD) and autism are the most common childhood neurodevelopmental conditions with a prevalence of 1% and 5%, respectively (Polanczyk et al. 2007; Brugha et al. 2011). While the prevalence of autism appears to stay unchanged from childhood with a prevalence of around 1% reported for the adult population (Brugha et al. 2011), many studies indicate a decrease in ADHD diagnosis in adulthood (Asherson et al. 2007; Fayyad et al. 2007; Cheung et al. 2016) with a prevalence of 3.4% (Fayyad et al. 2007). Recent work suggested cognitive EEG measures related to preparation-vigilance and error detection could distinguish ADHD remitters, that no longer meet criteria for ADHD diagnosis in adulthood, from the persisters (Cheung et al. 2016; Michelini et al. 2016). Young adulthood is a neurodevelopmentally sensitive period that is critical for understanding adult outcomes of the conditions and their persistence or remission (Lau-Zhu et al. 2019). The use of cognitive biomarkers to predict and track outcomes in ADHD and autism has the potential for greater clinical impact than a focus on diagnosis alone by providing an anchor point for intervention planning and personalised interventions. This is in line with a dimensional analysis approach (e.g., Research Domain Criterion Initiative, (Insel et al. 2010)) seeking to identify biomarkers based on cognition and brain function that could detect vulnerability in behaviour preceding or even in the absence of symptoms (McLoughlin et al. 2014a). In line with this, difficulties with executive function (self-reported and neuropsychologically assessed) has been related to poorer QoL in both ADHD and autism (de Vries and Geurts 2015; Stern et al. 2017). In this project we will use the EEG measures from the arrow flanker task. This task elicits event-related potential (ERP) components related to conflict monitoring (N2) and error processing (Ne), which are shown to be impaired in ADHD (McLoughlin et al. 2009; Michelini et al. 2016). Furthermore, arrow flanker task is known to elicit strong theta oscillations that are related to both ADHD and to the behavioural outcomes such as reaction time variability (RTV) (McLoughlin et al. 2014b). A particular method we plan to use on the analysis of theta oscillations is inter-trial coherence (ITC). Unlike averaged ERPs which represents the average of many trials, ITC is a measure related to the cortical synchrony of the oscillations and computed from single trial EEG. Therefore, it could provide a measure of consistency of the response in terms of the temporal and spectral synchronization. We are planning to investigate the associations between remission of ADHD and these ERP components, ITC, RT mean and variability. We will also study the associations between these EEG measures and Quality of Life and functional impairment (using Weiss Functional Impairment Rating Scale (WFIRS)) with a particular focus on ADHD remitters. References: - Asherson P, Chen W, Craddock B, Taylor E (2007) Adult attention-deficit hyperactivity disorder: recognition and treatment in general adult psychiatry. The British Journal of Psychiatry 190:4–5. https://doi.org/10.1192/bjp.bp.106.026484 - Brugha TS, McManus S, Bankart J, et al (2011) Epidemiology of Autism Spectrum Disorders in Adults in the Community in England. Arch Gen Psychiatry 68:459. https://doi.org/10.1001/archgenpsychiatry.2011.38 - Cheung CHM, Rijsdijk F, McLoughlin G, et al (2016) Cognitive and neurophysiological markers of ADHD persistence and remission. The British Journal of Psychiatry 208:548–555. https://doi.org/10.1192/bjp.bp.114.145185 - Cohen M, Cavanagh JF (2011) Single-Trial Regression Elucidates the Role of Prefrontal Theta Oscillations in Response Conflict. Frontiers in Psychology 2:30. https://doi.org/10.3389/fpsyg.2011.00030 - de Vries M, Geurts H (2015) Influence of Autism Traits and Executive Functioning on Quality of Life in Children with an Autism Spectrum Disorder. J Autism Dev Disord 45:2734–2743. https://doi.org/10.1007/s10803-015-2438-1 - Fayyad J, Graaf RD, Kessler R, et al (2007) Cross-national prevalence and correlates of adult attention-deficit hyperactivity disorder. The British Journal of Psychiatry 190:402–409. https://doi.org/10.1192/bjp.bp.106.034389 - Insel T, Cuthbert B, Garvey M, et al (2010) Research Domain Criteria (RDoC): Toward a New Classification Framework for Research on Mental Disorders. AJP 167:748–751. https://doi.org/10.1176/appi.ajp.2010.09091379 - Lau-Zhu A, Fritz A, McLoughlin G (2019) Overlaps and distinctions between attention deficit/hyperactivity disorder and autism spectrum disorder in young adulthood: Systematic review and guiding framework for EEG-imaging research. Neuroscience & Biobehavioral Reviews 96:93–115. https://doi.org/10.1016/j.neubiorev.2018.10.009 - McLoughlin G, Albrecht B, Banaschewski T, et al (2009) Performance monitoring is altered in adult ADHD: A familial event-related potential investigation. Neuropsychologia 47:3134–3142. https://doi.org/10.1016/j.neuropsychologia.2009.07.013 - McLoughlin G, Makeig S, Tsuang MT (2014a) In search of biomarkers in psychiatry: EEG-based measures of brain function. Am J Med Genet 165:111–121. https://doi.org/10.1002/ajmg.b.32208 - McLoughlin G, Palmer JA, Rijsdijk F, Makeig S (2014b) Genetic Overlap between Evoked Frontocentral Theta-Band Phase Variability, Reaction Time Variability, and Attention-Deficit/Hyperactivity Disorder Symptoms in a Twin Study. Biological Psychiatry 75:238–247. https://doi.org/10.1016/j.biopsych.2013.07.020 - Michelini G, Kitsune GL, Cheung CHM, et al (2016) Attention-Deficit/Hyperactivity Disorder Remission Is Linked to Better Neurophysiological Error Detection and Attention-Vigilance Processes. Biological Psychiatry 80:923–932. https://doi.org/10.1016/j.biopsych.2016.06.021 - Polanczyk G, de Lima MS, Horta BL, et al (2007) The Worldwide Prevalence of ADHD: A Systematic Review and Metaregression Analysis. AJP 164:942–948. https://doi.org/10.1176/ajp.2007.164.6.942 - Stern A, Pollak Y, Bonne O, et al (2017) The Relationship Between Executive Functions and Quality of Life in Adults With ADHD. J Atten Disord 21:323–330. https://doi.org/10.1177/108705471350413

Registered Replication Report of Weissman, D. H., Jiang, J., & Egner, T. (2014). Determinants of congruency sequence effects without learning and memory confounds

The congruency sequence effect (CSE) refers to the finding that the effect of cognitive conflict is smaller following conflicting, incongruent trials than after non-conflicting, congruent trials in conflict tasks, such as the Stroop, Simon, and flanker tasks. This is typically interpreted as an upregulation of cognitive control in response to conflict. Weissman, Jiang, & Egner (2014) investigated whether the CSE appears in these three tasks and a further variant where task-irrelevant distractors precede the target (prime-probe task), in the absence of learning and memory confounds in samples collected online. They found significant CSEs only in the prime-probe and Simon tasks, suggesting that the effect is more robust in tasks where the distractor can be translated into a response faster than the target. In this Registered Replication Report we collected data online from samples approx. 2.5 times larger than in the original study for each of the four tasks to investigate whether the task-related differences in themagnitude of the CSE are replicable (Nmin = 115, Nmax = 130). Our findings extend but do not contradict the original results: Bayesian analyses suggested that the CSE was present in all four tasks in RT but only in the Simon task in accuracy. The size of the effect did not differ between tasks, and the size of the congruency effect was not correlated with the size of the CSE across participants. These findings suggest it might be premature to conclude that the difference in the speed of distractor- vs target-related response activation is a determinant of the size of cross-trialmodulations of control. The practical implications of our results for online data collection in cognitive control research are also discussed

The effect of context on mind-wandering in younger and older adults

Older adults report less mind-wandering (MW) during tasks of sustained attention than younger adults. The control failure × current concerns account argues that this is due to age differences in how contexts cue personally relevant task-unrelated thoughts. For older adults, the university laboratory contains few reminders of their current concerns and unfinished goals. For younger adults, however, the university laboratory is more directly tied to their current concerns. Therefore, if the context for triggering current concerns is the critical difference between younger and older adults’ reported MW frequencies, then testing the two groups in contexts that equate the salience of self-relevant cues (i.e., their homes) should result in an increase in older but not younger adults’ MW rates. The present study directly compared rates of MW and involuntary autobiographical memories (IAMs) in the home versus in the lab for younger and older adults using a within-subjects manipulation of context. Inconsistent with the control failure × current concerns account, no significant reduction in the age-gap in MW was found. Suggesting a lack of cues rather than an abundance of cues elicits MW, participants in both age groups reported more MW in the lab than at home. The number of IAMs recalled did not differ across contexts but was lower in older than younger adults. These findings suggest that a cognitive rather than an environmental mechanism may be behind the reduction in spontaneous cognition in aging

Genetic overlap between midfrontal theta signals and ADHD and ASD in a longitudinal twin cohort

Background Cognitive control has been strongly linked to midfrontal theta (4-8 Hz) brain activity. Such control processes are known to be impaired in those with psychiatric conditions, and neurodevelopmental diagnoses, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Temporal variability in theta in particular is associated with ADHD with shared genetic variance underlying the relationship. Here, we investigated the phenotypic and genetic relationships between theta phase variability, theta-related signals (N2, ERN, Pe), reaction time, and ADHD and ASD longitudinally in a large twin study of young adults to investigate the stability of the genetic relationships between these measures over time. Methods Genetic multivariate liability threshold models were run on a longitudinal sample of 566 participants (283 twin pairs). Characteristics of ADHD and ASD were measured in childhood and in young adulthood, while EEG was recorded in young adulthood during an arrow flanker task. Results Cross-trial theta phase variability in adulthood showed large positive phenotypic and genetic relationships with reaction time variability and both childhood and adult ADHD characteristics. Pe amplitude was negatively related phenotypically and genetically to ADHD and ASD at both time points. Conclusions We show significant genetic associations between variability in theta signalling and ADHD. In a novel finding, we show that these relationships are stable across time, indicating a core dysregulation of the temporal coordination of control processes in ADHD that persists in those with childhood symptoms. Error processing, indexed by the Pe, was altered in both ADHD and ASD, with a strong genetic contribution