An improved human anxiety process biomarker: characterization of frequency band, personality and pharmacology

Midfrontal theta reactivity to conflict and error are linked to externalizing and internalizing respectively

Dimensional psychopathology scores measure symptom severity; cutting across disorder categories. Their clinical utility is high given comorbidity, but their neural basis is unclear. We used scalp electroencephalography (EEG) to concurrently assess neural activity across internalizing and externalizing traits. "Theta rhythm" (4-7 Hz) spectral power at the frontal midline site Fz in specific goal conflict and action error phases within a trial of a Stop-Signal Task was extracted using process-specific contrasts. A final sample of 146 community participants (63 males, 83 females; mean age = 36; SD = 9; range = 18 - 56), oversampled for externalizing disorder (49% diagnosed with a DSM-5 externalizing disorder), also supplied psychopathology and personality data. We used the Minnesota Multiphasic Personality Inventory-3 (MMPI-3) to measure symptoms and traits of psychopathology. An MMPI-3 measure of the higher-order internalizing psychopathology spectrum was positively correlated with action error theta. An MMPI-3 measure of the higher-order spectrum of externalizing psychopathology was negatively correlated with goal-conflict theta. We showed that goal-conflict and error theta activity are higher-order processes that index psychopathology severity. The associations extend into the nominally healthy range, and so reflect theta-related factors that apply to the general population as well as patients with sub-threshold diagnoses.

Midfrontal conflict theta and parietal P300 are linked to a latent factor of DSM externalising disorders

Psychiatric illnesses form spectra rather than categories, with symptoms varying continuously across individuals, i.e., there is no clear break between health and disorder. Dimensional measures of behaviour and brain activity are promising targets for studying biological mechanisms that are common across disorders. Here, we assessed the extent to which neural measures of the sensitivity of the three biological systems in the reinforcement sensitivity theory (RST) could account for individual differences in a latent general factor estimated from symptom counts across externalising disorders (EXTs). RST explanatory power was pitted against reduced P300, a reliable indicator of externalising per previous research. We assessed 206 participants for DSM-5 EXTs (antisocial personality disorder, conduct disorder, attention-deficit/hyperactivity disorder, intermittent explosive disorder symptoms, alcohol use disorder, and cannabis use disorder). Of the final sample, 49% met diagnostic criteria for at least one of the EXTs. Electroencephalographic measures of the sensitivities of the behavioural activation system (BAS), the fight/flight/freeze system, and the behavioural inhibition system (BIS), as well as P300 were extracted from the gold bar-lemon and stop-signal tasks. As predicted, we found that low neural BIS sensitivity and low P300 were uniquely and negatively associated with our latent factor of externalising. Contrary to prediction, neural BAS/"dopamine" sensitivity was not associated with externalising. Our results provide empirical support for low BIS sensitivity and P300 as neural mechanisms common to disorders within the externalising spectrum; but, given the low N involved, future studies should seek to assess the replicability of our findings and, in particular, the differential involvement of the three RST systems.

Right Frontal Theta: Is It a Response Biomarker for Ketamine’s Therapeutic Action in Anxiety Disorders?

Anxiety disorders are the most prevalent mental disorders in the world, creating huge economic burdens on health systems and impairing the quality of life for those affected. Recently, ketamine has emerged as an effective anxiolytic even in cases resistant to conventional treatments (TR); but its therapeutic mechanism is unknown. Previous data suggest that ketamine anxiety therapy is mediated by reduced right frontal electroencephalogram (EEG) theta power measured during relaxation. Here we test for a similar theta reduction between population-sample, presumed treatment-sensitive, (TS) anxiety patients and healthy controls. Patients with TS DSM-5 anxiety disorder and healthy controls provided EEG during 10 min of relaxation and completed anxiety-related questionnaires. Frontal delta, theta, alpha1, alpha2, beta, and gamma power, Higuchi’s fractal dimension (HFD) and frontal alpha asymmetry (FAA) values were extracted to match ketamine testing; and we predicted that the controls would have less theta power at F4, relative to the TS anxious patients, and no differences in HFD or FAA. We provide graphical comparisons of our frontal band power patient-control differences with previously published post-pre ketamine TR differences. As predicted, theta power at F4 was significantly lower in controls than patients and FAA was not significantly different. However, HFD was unexpectedly reduced at lateral sites. Gamma power did not increase between controls and patients suggesting that the increased gamma produced by ketamine relates to dissociation rather than therapy. Although preliminary, and indirect, our results suggest that the anxiolytic action of ketamine is mediated through reduced right frontal theta power.

Dynamic interaction between hippocampus, orbitofrontal cortex, and subthalamic nucleus during goal conflict in the stop signal task in rats

Action stopping depends on at least two (fast, slow) frontal circuits depending on the urgency of execution of the 'go' response. Human EEG suggests a third (even slower, limbic) circuit that activates frontal areas at frequencies typical of 'hippocampal theta'. Here we test in male rats whether stop-go conflict engages the hippocampus and so may send theta-modulated information via the frontal cortex to the subthalamic nucleus. We recorded from multi-electrode arrays in the hippocampus, orbitofrontal cortex, and subthalamus in 5 male Long Evans rats performing a stop signal task and, as in previous human experiments, assessed stop-signal specific power for effects of goal conflict. Conflict increased 11-12 Hz theta power modestly in all three structures but with the largest increase in power being at 5 Hz in the frontal cortex but not the hippocampus. There was increased conflict-related coherence in all circuits in the range 5-8 Hz and particularly at 5-6 Hz. Increased coherence coupled with an increase in conflict-induced low frequency power in the frontal cortex may reflect communication with the hippocampus. The data are consistent with a third limbic circuit that can generate stopping when go responses are particularly slow (as, e.g., in a go/no go task). [199 words; 200 max].

Utility of Cognitive Neural Features for Predicting Mental Health Behaviors

Cognitive dysfunction underlies common mental health behavioral symptoms including depression, anxiety, inattention, and hyperactivity. In this study of 97 healthy adults, we aimed to classify healthy vs. mild-to-moderate self-reported symptoms of each disorder using cognitive neural markers measured with an electroencephalography (EEG). We analyzed source-reconstructed EEG data for event-related spectral perturbations in the theta, alpha, and beta frequency bands in five tasks, a selective attention and response inhibition task, a visuospatial working memory task, a Flanker interference processing task, and an emotion interference task. From the cortical source activation features, we derived augmented features involving co-activations between any two sources. Logistic regression on the augmented feature set, but not the original feature set, predicted the presence of psychiatric symptoms, particularly for anxiety and inattention with >80% sensitivity and specificity. We also computed current flow closeness and betweenness centralities to identify the “hub” source signal predictors. We found that the Flanker interference processing task was the most useful for assessing the connectivity hubs in general, followed by the inhibitory control go-nogo paradigm. Overall, these interpretable machine learning analyses suggest that EEG biomarkers collected on a rapid suite of cognitive assessments may have utility in classifying diverse self-reported mental health symptoms.

Non-human contributions to personality neuroscience – from fish through primates. An introduction to the special issue

The most fundamental emotional systems that show trait control are evolutionarily old and extensively conserved. Psychology in general has benefited from non-human neuroscience and from the analytical simplicity of behaviour in those with simpler nervous systems. It has been argued that integration between personality, psychopathology, and neuroscience is particularly promising if we are to understand the neurobiology of human experience. Here, we provide some general arguments for a non-human approach being at least as productive in relation to personality, psychopathology, and their interface. Some early personality theories were directly linked to psychopathology (e.g., Eysenck, Panksepp, and Cloninger). They shared a common interest in brain systems that naturally led to the use of non-human data; behavioural, neural, and pharmacological. In Eysenck’s case, this also led to the selective breeding, at the Maudsley Institute, of emotionally reactive and non-reactive strains of rat as models of trait neuroticism or trait emotionality. Dimensional personality research and categorical approaches to clinical disorder then drifted apart from each other, from neuropsychology, and from non-human data. Recently, the conceptualizations of both healthy personality and psychopathology have moved towards a common hierarchical trait perspective. Indeed, the proposed two sets of trait dimensions appear similar and may even be eventually the same. We provide, here, an introduction to this special issue of Personality Neuroscience, where the authors provide overviews of detailed areas where non-human data inform human personality and its psychopathology or provide explicit models for translation to human neuroscience. Once all the papers in the issue have appeared, we will also provide a concluding summary of them.

Right frontal anxiolytic-sensitive EEG 'theta' rhythm in the stop-signal task is a theory-based anxiety disorder biomarker

Psychiatric diagnoses currently rely on a patient’s presenting symptoms or signs, lacking much-needed theory-based biomarkers. Our neuropsychological theory of anxiety, recently supported by human imaging, is founded on a longstanding, reliable, rodent ‘theta’ brain rhythm model of human clinical anxiolytic drug action. We have now developed a human scalp EEG homolog—goal-conflict-specific rhythmicity (GCSR), i.e., EEG rhythmicity specific to a balanced conflict between goals (e.g., approach-avoidance). Critically, GCSR is consistently reduced by different classes of anxiolytic drug and correlates with clinically-relevant trait anxiety scores (STAI-T). Here we show elevated GCSR in student volunteers divided, after testing, on their STAI-T scores into low, medium, and high (typical of clinical anxiety) groups. We then tested anxiety disorder patients (meeting diagnostic criteria) and similar controls recruited separately from the community. The patient group had higher average GCSR than their controls—with a mixture of high and low GCSR that varied with, but cut across, conventional disorder diagnosis. Consequently, GCSR scores should provide the first theoretically-based biomarker that could help diagnose, and so redefine, a psychiatric disorder.

Trimethylamine-N-oxide and Precursors as Novel Potential Biomarkers for Anxiety Disorder

BACKGROUND

Anxiety disorder (AD) is closely related to changes in the composition of the gut microbiota, and changes in gut microbiota abundance affect the synthesis of trimethylamine N-oxide (TMAO).

OBJECTIVE

To explore whether TMAO is related to and serves as a potential biomarker for the diagnosis of AD.

METHODS

The concentrations of TMAO, choline, and betaine were analyzed in 60 patients with AD and 60 control individuals using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method.

RESULTS

Compared with controls, TMAO was significantly reduced in patients with AD. Logistic regression analysis demonstrated that decreased TMAO concentrations were associated with an increased risk of AD. The multiplication of TMAO and its precursors (choline and betaine) produced the best AUC for the diagnosis of AD (AUC = 0.847; 95% CI, 0.780-0.914; P <.001).

CONCLUSION

The decrease of TMAO concentration is related to the increase of anxiety disorder. TMAO and precursors could be identified as novel potential biomarkers for the diagnosis of AD.

Evaluating the feasibility of a consumer-grade wearable EEG headband to aid assessment of state and trait mindfulness

OBJECTIVES

Measures from wearable devices could be a valuable supplement to mindfulness assessment and intervention. This observational study evaluated measures from a consumer-grade EEG headband (Muse, InteraXon, Inc.) as novel correlates of state mindfulness during focused attention meditation.

METHODS

Adult participants (N = 68, M_age  = 22.66, SD_age  = 7.35) completed a task-based measure of state mindfulness and thought probe measures of subjective mind wandering while meditating with the EEG headband. A subset completed 14 days of home practice (n = 29).

RESULTS

Device measures were sensitive to attention lapses within-participants in the state mindfulness task (d = 0.56) and had large between-participants associations for the same task (r = -0.50). Mean device metrics from home practice together explained approximately 30% of variance in self-reported trait mindfulness, attentional control, nonattachment, and decentering.

CONCLUSION

EEG biomarkers show potential as correlates of mindfulness with distinct benefits over existing assessment methods.

Laterality of an EEG anxiety disorder biomarker largely follows handedness

Anxiety disorders are the most common mental disorders impacting people worldwide. Using an auditory Stop Signal Task (SST), we have developed an anxiety disorder biomarker (goal-conflict specific rhythmicity/GCSR) that occurs at the right frontal site F8 in right-handed participants. Here, we compare its laterality in left-handers (n = 26) versus demographically-matched right-handers (n = 26) between the ages of 18-30. We assessed the effects on GCSR power of the handedness of the participants (left or right), blocks of the SST, left-right variation across frontal channels (F7, F3, Fz, F4, F8), and EEG frequency (4-12 Hz). Left-handers differed from right-handers most at the channels furthest from the midline. This difference was largely a mirroring of right hander responses by left handers. With frontal channels coded in reverse order for left handers the original significant differences disappeared. Some differences remained between the groups in the frequency variation across blocks of testing. These and other data suggest that the circuitry engaged by conflict in the SST is different from that directly controlling stopping behaviour. Our results also suggest that where GCSR is used as an anxiety process or disorder biomarker in groups that combine both left and right-handed people, data only from the channel ipsilateral to the dominant hand should be used (F7, or F8, respectively).

Decoding personality trait measures from resting EEG: An exploratory report

Can personality be predicted from oscillatory patterns produced by the brain at rest? To date, relatively few studies using electroencephalography (EEG) have yielded consistent relations between personality trait measures and spectral power. Thus, new exploratory research may help develop targeted hypotheses about how neural processes associated with EEG activity may relate to personality differences. We used multivariate pattern analysis to decode personality scores (i.e., Big Five traits) from resting EEG frequency power spectra. Up to 8 minutes of EEG data was recorded per participant prior to completing an unrelated task (N = 168, M_age = 23.51, 57% female) and, in a subset of participants, after task completion (N = 96, M_age = 23.22, 52% female). In each recording, participants alternated between open and closed eyes. Linear support vector regression with 10-fold cross validation was performed using the power from 62 scalp electrodes within 1 Hz frequency bins from 1 to 30 Hz. One Big Five trait, agreeableness, could be decoded from EEG power ranging from 8 to 19 Hz, and this was consistent across all four recording periods. Neuroticism was decodable using data within the 3-6 Hz range, albeit less consistently. Posterior alpha power negatively correlated with agreeableness, whereas parietal beta power positively correlated with agreeableness. We suggest methods to draw from our results and develop targeted future hypotheses, such as linking to individual alpha frequency and incorporating self-reported emotional states. Our open dataset can be harnessed to reproduce results or investigate new research questions concerning the biological basis of personality.

Increases in theta CSD power and coherence during a calibrated stop-signal task: implications for goal-conflict processing and the Behavioural Inhibition System

Psychologists have identified multiple different forms of conflict, such as information processing conflict and goal conflict. As such, there is a need to examine the similarities and differences in neurology between each form of conflict. To address this, we conducted a comprehensive electroencephalogram (EEG) analysis of Shadli, Glue, McIntosh, and McNaughton’s calibrated stop-signal task (SST) goal-conflict task. Specifically, we examined changes in scalp-wide current source density (CSD) power and coherence across a wide range of frequency bands during the calibrated SST (n = 34). We assessed differences in EEG between the high and low goal-conflict conditions using hierarchical analyses of variance (ANOVAs). We also related goal-conflict EEG to trait anxiety, neuroticism, Behavioural Inhibition System (BIS)-anxiety and revised BIS (rBIS) using regression analyses. We found that changes in CSD power during goal conflict were limited to increased midfrontocentral theta. Conversely, coherence increased across 23 scalp-wide theta region pairs and one frontal delta region pair. Finally, scalp-wide theta significantly predicted trait neuroticism but not trait anxiety, BIS-anxiety or rBIS. We conclude that goal conflict involves increased midfrontocentral CSD theta power and scalp-wide theta-dominated coherence. Therefore, compared with information processing conflict, goal conflict displays a similar EEG power profile of midfrontocentral theta but a much wider coherence profile. Furthermore, the increases in theta during goal conflict are the characteristic of BIS-driven activity. Therefore, future research should confirm whether these goal-conflict effects are driven by the BIS by examining whether the effects are attenuated by anxiolytic drugs. Overall, we have identified a unique network of goal-conflict EEG during the calibrated SST.

Does behavioural inhibition system dysfunction contribute to Attention Deficit Hyperactivity Disorder?

The Reinforcement Sensitivity Theory of Personality has as its main foundation a Behavioural Inhibition System (BIS), defined by anxiolytic drugs, in which high trait sensitivity should lead to internalising, anxiety, disorders. Conversely, it has been suggested that low BIS sensitivity would be a characteristic of externalising disorders. BIS output should lead to increased arousal and attention as well as behavioural inhibition. Here, therefore, we tested whether an externalising disorder, Attention Deficit Hyperactivity Disorder (ADHD), involves low BIS sensitivity. Goal-Conflict-Specific Rhythmicity (GCSR) in an auditory Stop Signal Task is a right frontal EEG biomarker of BIS function. We assessed children diagnosed with ADHD-I (inattentive) or ADHD-C (combined) and healthy control groups for GCSR in: a) an initial smaller study in Dunedin, New Zealand (population ~120,000: 15 control, 10 ADHD-I, 10 ADHD-C); and b) a main larger one in Tehran, Iran (population ~9 [city]-16 [metropolis] million: 27 control, 18 ADHD-I, 21 ADHD-C). GCSR was clear in controls (particularly at 6–7 Hz) and in ADHD-C (particularly at 8–9 Hz) but was reduced in ADHD-I. Reduced attention and arousal in ADHD-I could be due, in part, to BIS dysfunction. However, hyperactivity and impulsivity in ADHD-C are unlikely to reflect reduced BIS activity. Increased GCSR frequency in ADHD-C may be due to increased input to the BIS. BIS dysfunction may contribute to some aspects of ADHD (and potentially other externalising disorders) and to some differences between the ADHD subtypes but other prefrontal systems (and, e.g. dopamine) are also important.

Personality neuroscience and psychopathology: should we start with biology and look for neural-level factors?

"Personality is an abstraction used to explain consistency and coherency in an individual's pattern of affects, cognitions, desires and behaviors [ABCDs]" (Revelle, 2007, p. 37). But personality research currently provides more a taxonomy of patterns than theories of fundamental causes. Psychiatric disorders can be viewed as involving extremes of personality but are diagnosed via symptom patterns not biological causes. Such surface-level taxonomic description is necessary for science, but consistent predictive explanation requires causal theory. Personality constructs, and especially their clinical extremes, should predict variation in ABCD patterns, with parsimony requiring the lowest effective causal level of explanation. But, even biologically inspired personality theories currently use an intuitive language-based approach for scale development that lacks biological anchors. I argue that teleonomic "purpose" explains the organisation and outputs of conserved brain emotion systems, where high activation is adaptive in specific situations but is otherwise maladaptive. Simple modulators of whole-system sensitivity evolved because the requisite adaptive level can vary across people and time. Sensitivity to a modulator is an abstract predictive personality factor that operates at the neural level but provides a causal explanation of both coherence and occasional apparent incoherence in ABCD variation. Neuromodulators impact all levels of the "personality hierarchy" from metatraits to aspects: stability appears altered by serotonergic drugs, neuroticism by ketamine and trait anxiety by simple anxiolytic drugs. Here, the tools of psychiatry transfer to personality research and imply both interaction between levels and oblique factor mappings to ABCD. On this view, much psychopathology reflects extremes of neural-level personality factors, and we can view much pharmacotherapy as temporarily altering personality. So, particularly for personality factors linked to basic emotions and their disorders, I think we should start with evolutionary biology and look directly at conserved neural-level modulators for our explanatory personality constructs and only invoke higher order, emergent, explanations when neural-level explanation fails.

Goal-Conflict EEG Theta and Biased Economic Decisions: A Role for a Second Negative Motivation System

Economic decision biases can reflect emotion and emotion dysfunction. Economic paradigms thus provide a solid framework for analysis of brain processes related to emotion and its disorders. Importantly for economic decisions, goal-conflict activates different negative motivational processes than pure loss; generating negative decision biases linked to anxiety and fear, respectively. Previously, right frontal goal-conflict specific EEG rhythmicity (GCSR) was shown to reflect anxiety processing. Here, we assessed GCSR in a forced-choice, economic decision-making task. Ninety participants were tested in three key conditions where gain:loss ratios of left mouse clicks were set to 75:25 (GAIN), 50:50 (CONFLICT) and 25:75 (LOSS). Right clicks produced no monetary consequences and skipped the current trial. The participants were not told the different conditions but could learn about them by associating the background stimulus color with the specific payoff. Goal-conflict was defined as the mathematical contrast of activity in CONFLICT minus the average of that in GAIN and LOSS. Replicating previous findings with somewhat different conditions, right frontal GCSR was detected. Importantly, greater right frontal GCSR significantly predicted a preference for economic safety in CONFLICT but not in GAIN or LOSS; but did not predict trait anxiety or neuroticism. We conclude that goal-conflict has unique neuroeconomics effects on choice biases; and that these reflect anxiety processing that is not effectively captured by trait anxiety or neuroticism.

Behavioural inhibition and valuation of gain/loss are neurally distinct from approach/withdrawal

Gain or omission/termination of loss produces approach; while loss or omission/termination of gain produces withdrawal. Control of approach/withdrawal motivation is distinct from valuation of gain/loss and does not entail learning - making "reward" and "punishment" ambiguous. Approach-withdrawal goal conflict engages a neurally distinct Behavioural Inhibition System, which controls "anxiety" (conflict/passive avoidance) but not "fear" (withdrawal/active avoidance).

Anxiety as a Common Biomarker for School Children With Additional Health and Developmental Needs Irrespective of Diagnosis

Currently very little evidence is available regarding the biological characteristics and common comorbid behaviors that are associated with children characterized by learning difficulties who require additional support at school. These children are usually referred to as having Additional Health and Developmental Needs by the Australian Government and the associated public education system more broadly though the problems may arise from academic, social and/or emotional stressors and may or may not include children with clinically diagnosed Neurodevelopmental Disorders. Thus, the aim of this study was to investigate the relationship between anxiety levels (Spence Children's Anxiety Scale- Parent Report), autism traits (Autism Spectrum Quotient - Child Version) and sleep quality (Sleep Disturbance Scale for Children) in children with Additional Health and Developmental Needs without an intellectual disability, but with either a diagnosis of Autism Spectrum Disorder (ASD) (N = 25), Speech and Language Impairment (N = 37) or Other Diagnosis (N = 22). Our results demonstrated that these children with Additional Health and Developmental Needs showed atypically high levels of anxiety and impaired sleep quality, with the ASD group reporting more impairments associated with comorbid anxiety and sleep quality than either of the other clinically diagnosed groups. In fact, greater anxiety level was associated with a greater number of autism traits and poorer sleep quality regardless of diagnostic group suggesting that anxiety is a common experience for children with Additional Health and Developmental Needs. It is suggested that assessment of anxiety, sleep behaviors and autism traits may be useful markers for early identification of children within this population, thus providing scope for early and targeted intervention.

Ketamine Effects on EEG during Therapy of Treatment-Resistant Generalized Anxiety and Social Anxiety

BACKGROUND

Ketamine is swiftly effective in a range of neurotic disorders that are resistant to conventional antidepressant and anxiolytic drugs. The neural basis for its therapeutic action is unknown. Here we report the effects of ketamine on the EEG of patients with treatment-resistant generalized anxiety and social anxiety disorders.

METHODS

Twelve patients with refractory DSM-IV generalized anxiety disorder and/or social anxiety disorder provided EEG during 10 minutes of relaxation before and 2 hours after receiving double-blind drug administration. Three ascending ketamine dose levels (0.25, 0.5, and 1 mg/kg) and midazolam (0.01 mg/kg) were given at 1-week intervals to each patient, with the midazolam counterbalanced in dosing position across patients. Anxiety was assessed pre- and postdose with the Fear Questionnaire and HAM-A.

RESULTS

Ketamine dose-dependently improved Fear Questionnaire but not HAM-A scores, decreased EEG power most at low (delta) frequency, and increased it most at high (gamma) frequency. Only the decrease in medium-low (theta) frequency at right frontal sites predicted the effect of ketamine on the Fear Questionnaire. Ketamine produced no improvement in Higuchi's fractal dimension at any dose or systematic changes in frontal alpha asymmetry.

CONCLUSIONS

Ketamine may achieve its effects on treatment-resistant generalized anxiety disorder and social anxiety disorder through related mechanisms to the common reduction by conventional anxiolytic drugs in right frontal theta. However, in the current study midazolam did not have such an effect, and it remains to be determined whether, unlike conventional anxiolytics, ketamine changes right frontal theta when it is effective in treatment-resistant depression.

Impulsivity and behaviour problems in dogs: A Reinforcement Sensitivity Theory perspective

Trait impulsivity is an increasingly relevant topic for human and non-human animal personality research. There are similarities in dog and human manifestations of trait impulsivity at the behavioural, genetic, and neurobiological level. We investigated a well-validated measure of dog impulsivity and responsivity (the Dog Impulsivity Assessment Scale, DIAS) and a neuropsychological theory of human trait approach and avoidance (the Reinforcement Sensitivity Theory of personality, RST). Owners reported their dogs' dispositional behaviour on the DIAS, an RST scale modified to describe dogs' behaviour, and a list of common dog behaviour problems. In a sample of 730 dogs, we observed convergence between the RST and the DIAS. There was a negative correlation between RST 'Behaviour Inhibition System' and DIAS impulsivity factor ('Behavioural Regulation'). RST 'Behavioural Approach System' correlated positively with DIAS 'Responsiveness'. The RST 'Fight-Flight-Freeze System' (FFFS) and the DIAS 'Aggression and response to novelty factor were both distinct from other factors. However, the DIAS 'Aggression and response to novelty' factor and the RST FFFS explained different aspects of dog behaviour problems. Importantly, whilst the DIAS factors indicated tendencies towards avoidant behaviours, the FFFS discriminated between active and passive avoidance. The findings suggest a partial overlapping between the DIAS and RST scales, and highlights the utility of personality models in investigating behaviour problems in dogs.

Group and individual analyses of pre-, peri-, and post-movement related alpha and beta oscillations during a single continuous monitoring task

Band power linked to lower and upper alpha (i.e. 8-10Hz; 10-12Hz) and lower and upper beta (i.e. 12-20Hz; 20-30Hz) were examined during response related stages, including anticipation, response execution (RE), response inhibition (RI) and post response recovery (PRR). Group and individual data from 34 participants were considered. The participant's objective was to press a response key immediately following 4 non-repeating, single integer odd digits. These were presented amongst a continuous stream of digits and Xs. Electroencephalogram (EEG) signals were recorded from 32 electrodes (pooled to 12 regions). In the group analyses, participant EEG response was compared to baseline revealing that upper alpha desynchronised during anticipation, RE and RI; lower beta during anticipation and RE; and upper beta just RE. Upper alpha desynchronisation during rapid, unplanned RI is novel. Also, upper alpha and lower/upper beta synchronised during PRR. For upper alpha, we speculate this indexes brief cortical deactivation; for beta we propose this indexes response set maintenance. Lastly, lower alpha fluctuations correlated negatively with RT, indexing neural efficiency. Individual analyses involved calculation of the proportion of individuals displaying the typical RE and PRR trends; these were not reflected by all participants. The former was displayed individually by the largest proportion in upper alpha recorded left fronto-centrally; the latter was most reliably displayed individually in lower beta recorded mid centro-parietally. Therefore, group analyses identified typical alpha and beta synchronisation/desynchronisation trends, whilst individual analyses identified their degree of representation in single participants. Attention is drawn to the clinical relevance of this issue.

Mechanisms of comorbidity, continuity, and discontinuity in anxiety-related disorders

We discuss comorbidity, continuity, and discontinuity of anxiety-related disorders from the perspective of a two-dimensional neuropsychology of fear (threat avoidance) and anxiety (threat approach). Pharmacological dissection of the “neurotic” disorders justifies both a categorical division between fear and anxiety and a subdivision of each mapped to a hierarchy of neural modules that process different immediacies of threat. It is critical that each module can generate normal responses, symptoms of another syndrome, or syndromal responses. We discuss the resultant possibilities for comorbid dysfunction of these modules both with each other and with some disorders not usually classified as anxiety related. The simplest case is symptomatic fear/anxiety comorbidity, where dysfunction in one module results in excess activity in a second, otherwise normal, module to generate symptoms and apparent comorbidity. More complex is syndromal fear/anxiety comorbidity, where more than one module is concurrently dysfunctional. Yet more complex are syndromal comorbidities of anxiety that go beyond the two dimensional fear/anxiety systems: depression, substance use disorder, and attention-deficit/hyperactivity disorder. Our account of attention-deficit/hyperactivity disorder–anxiety comorbidity entails discussion of the neuropsychology of externalizing disorders to account for the lack of anxiety comorbidity in some of these. Finally, we link the neuropsychology of disorder to personality variation, and to the development of a biomarker of variation in the anxiety system among individuals that, if extreme, may provide a means of unambiguously identifying the first of a range of anxiety syndromes.