Human anxiety-specific "theta" occurs with selective stopping and localizes to right inferior frontal gyrus

Neural activation changes following attention bias modification treatment or a selective serotonin reuptake inhibitor for social anxiety disorder

BACKGROUND

Delineation of changes in neural function associated with novel and established treatments for social anxiety disorder (SAD) can advance treatment development. We examined such changes following selective serotonin reuptake inhibitor (SSRI) and attention bias modification (ABM) variant - gaze-contingent music reward therapy (GC-MRT), a first-line and an emerging treatments for SAD.

METHODS

Eighty-one patients with SAD were allocated to 12-week treatments of either SSRI or GC-MRT, or waitlist (ns = 22, 29, and 30, respectively). Baseline and post-treatment functional magnetic resonance imaging (fMRI) data were collected during a social-threat processing task, in which attention was directed toward and away from threat/neutral faces.

RESULTS

Patients who received GC-MRT or SSRI showed greater clinical improvement relative to patients in waitlist. Compared to waitlist patients, treated patients showed greater activation increase in the right inferior frontal gyrus and anterior cingulate cortex when instructed to attend toward social threats and away from neutral stimuli. An additional anterior cingulate cortex cluster differentiated between the two active groups. Activation in this region increased in ABM and decreased in SSRI. In the ABM group, symptom change was positively correlated with neural activation change in the dorsolateral prefrontal cortex.

CONCLUSIONS

Brain function measures show both shared and treatment-specific changes following ABM and SSRI treatments for SAD, highlighting the multiple pathways through which the two treatments might work. Treatment-specific neural responses suggest that patients with SAD who do not fully benefit from SSRI or ABM may potentially benefit from the alternative treatment, or from a combination of the two.

TRIAL REGISTRATION

ClinicalTrials.gov, Identifier: NCT03346239. https://clinicaltrials.gov/ct2/show/NCT03346239.

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].

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.

Early and late signals of unexpected reward contribute to low extraversion and high disinhibition, respectively

Like socio-economic status and cognitive abilities, personality traits predict important life outcomes. Traits that reflect unusually low or high approach motivations, such as low extraversion and high disinhibition, are linked to various forms of mental disorder. Similarly, the dopamine system is theoretically linked to approach motivation traits and to various forms of mental disorder. Identifying neural contributions to extremes of such traits should map to neural sources of psychopathology, with dopamine a prime candidate. Notably, dopamine cells fire in response to unexpected reward, which suggests that the size of non-invasive, scalp-recorded potentials evoked by unexpected reward could reflect sensitivity in approach motivation traits. Here, we evaluated the validity of evoked electroencephalography (EEG) responses to unexpected reward in a monetary gain/loss task to assess approach motivation traits in 137 participants, oversampled for externalizing psychopathology symptoms. We demonstrated that over the 0–400 ms period in which feedback on the outcome was presented, responses evoked by unexpected reward contributed to all theoretically relevant approach motivation trait domains (disinhibition, extraversion and the behavioural activation system); and did so only at times when dopamine responses normally peak and reportedly code salience (70–100 ms) and valuation (200–300 ms). In particular, we linked “dopaminergic” salience and valuation to the psychopathology-related constructs of low extraversion (social anxiety) and high disinhibition (impulsivity) respectively, making the evoked potential components biomarker candidates for indexing aberrant processing of unexpected reward.

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.

Floating ideas on theta waves

This special issue on the theta rhythm highlights recent experiments aimed at understanding the relationship between this slow, large amplitude oscillation and plasticity, fast oscillations, cellular activity and disease in both animals and humans. The articles in this issue of Behavioral Neuroscience use a number of approaches across different model systems and behavioral paradigms to provide an up-to-date account of recent progress in understanding how the theta rhythm coordinates neural activity in the service of cognition. Prominent themes that emerge are how theta is tightly related to movement in humans and rodents and how this rhythm could be leveraged as a biomarker for understanding and testing therapeutic approaches to treat psychiatric and neurological diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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.