Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling.

BACKGROUND: It is increasingly recognized that existing diagnostic approaches do not capture the underlying heterogeneity and complexity of psychiatric disorders such as depression. This study uses a data-driven approach to define fluid depressive states and explore how patients transition between these states in response to cognitive behavioural therapy (CBT). METHODS: Item-level Patient Health Questionnaire (PHQ-9) data were collected from 9891 patients with a diagnosis of depression, at each CBT treatment session. Latent Markov modelling was used on these data to define depressive states and explore transition probabilities between states. Clinical outcomes and patient demographics were compared between patients starting at different depressive states. RESULTS: A model with seven depressive states emerged as the best compromise between optimal fit and interpretability. States loading preferentially on cognitive/affective v. somatic symptoms of depression were identified. Analysis of transition probabilities revealed that patients in cognitive/affective states do not typically transition towards somatic states and vice-versa. Post-hoc analyses also showed that patients who start in a somatic depressive state are less likely to engage with or improve with therapy. These patients are also more likely to be female, suffer from a comorbid long-term physical condition and be taking psychotropic medication. CONCLUSIONS: This study presents a novel approach for depression sub-typing, defining fluid depressive states and exploring transitions between states in response to CBT. Understanding how different symptom profiles respond to therapy will inform the development and delivery of stratified treatment protocols, improving clinical outcomes and cost-effectiveness of psychological therapies for patients with depression.

The effects of transcranial direct current stimulation on within- and cross-paradigm transfer following multi-session backward recall training.

Transcranial direct current stimulation (tDCS) has been shown to enhance the efficacy and generalisation of working memory (WM) training, but there has been little systematic investigation into how coupling task-specific WM training with stimulation impacts more specifically on transfer to untrained tasks. This randomised controlled trial investigated the boundary conditions to transfer by testing firstly whether the benefits of training on backward digit recall (BDR) extend to untrained backward recall tasks and n-back tasks with different materials, and secondly which, if any, form of transfer is enhanced by tDCS. Forty-eight participants were allocated to one of three conditions: BDR training with anodal (10 min, 1 mA) or sham tDCS, or visual search training with sham tDCS, applied over the left dorsolateral prefrontal cortex. Transfer was assessed on within- (backward recall with digits, letters, and spatial locations) and cross-paradigm (n-back with digits and letters) transfer tests following three sessions of training and stimulation. On-task training gains were found, with transfer to other backward span but not n-back tasks. There was little evidence that tDCS enhanced on-task training or transfer. These findings indicate that training enhances paradigm-specific processes within WM, but that tDCS does not enhance these gains.

Repetition Suppression and Memory for Faces is Reduced in Adults with Autism Spectrum Conditions.

Autism spectrum conditions (ASC) are associated with a number of atypicalities in face processing, including difficulties in face memory. However, the neural mechanisms underlying this difficulty are unclear. In neurotypical individuals, repeated presentation of the same face is associated with a reduction in activity, known as repetition suppression (RS), in the fusiform face area (FFA). However, to date, no studies have investigated RS to faces in individuals with ASC, or the relationship between RS and face memory. Here, we measured RS to faces and geometric shapes in individuals with a clinical diagnosis of an ASC and in age and IQ matched controls. Relative to controls, the ASC group showed reduced RS to faces in bilateral FFA and reduced performance on a standardized test of face memory. By contrast, RS to shapes in object-selective regions and object memory did not differ between groups. Individual variation in face-memory performance was positively correlated with RS in regions of left parietal and prefrontal cortex. These findings suggest difficulties in face memory in ASC may be a consequence of differences in the way faces are stored and/or maintained across a network of regions involved in both visual perception and short-term/working memory.

Transcranial Random Noise Stimulation Does Not Enhance the Effects of Working Memory Training.

Transcranial random noise stimulation (tRNS), a noninvasive brain stimulation technique, enhances the generalization and sustainability of gains following mathematical training. Here it is combined for the first time with working memory training in a double-blind randomized controlled trial. Adults completed 10 sessions of Cogmed Working Memory Training with either active tRNS or sham stimulation applied bilaterally to dorsolateral pFC. Training was associated with gains on both the training tasks and on untrained tests of working memory that shared overlapping processes with the training tasks, but not with improvements on working memory tasks with distinct processing demands or tests of other cognitive abilities (e.g., IQ, maths). There was no evidence that tRNS increased the magnitude or transfer of these gains. Thus, combining tRNS with Cogmed Working Memory Training provides no additional therapeutic value.

Repetition Suppression in Ventral Visual Cortex Is Diminished as a Function of Increasing Autistic Traits.

Repeated viewing of a stimulus causes a change in perceptual sensitivity, known as a visual aftereffect. Similarly, in neuroimaging, repetitions of the same stimulus result in a reduction in the neural response, known as repetition suppression (RS). Previous research shows that aftereffects for faces are reduced in both children with autism and in first-degree relatives. With functional magnetic resonance imaging, we found that the magnitude of RS to faces in neurotypical participants was negatively correlated with individual differences in autistic traits. We replicated this finding in a second experiment, while additional experiments showed that autistic traits also negatively predicted RS to images of scenes and simple geometric shapes. These findings suggest that a core aspect of neural function--the brain's response to repetition--is modulated by autistic traits.

Different neural mechanisms within occipitotemporal cortex underlie repetition suppression across same and different-size faces.

Repetition suppression (RS) (or functional magnetic resonance imaging adaptation) refers to the reduction in blood oxygen level-dependent signal following repeated presentation of a stimulus. RS is frequently used to investigate the role of face-selective regions in human visual cortex and is commonly thought to be a "localized" effect, reflecting fatigue of a neuronal population representing a given stimulus. In contrast, predictive coding theories characterize RS as a consequence of "top-down" changes in between-region modulation. Differentiating between these accounts is crucial for the correct interpretation of RS effects in the face-processing network. Here, dynamic causal modeling revealed that different mechanisms underlie different forms of RS to faces in occipitotemporal cortex. For both familiar and unfamiliar faces, repetition of identical face images (same size) was associated with changes in "forward" connectivity between the occipital face area (OFA) and the fusiform face area (FFA) (OFA-to-FFA). In contrast, RS across image size was characterized by altered "backward" connectivity (FFA-to-OFA). In addition, evidence was higher for models in which information projected directly into both OFA and FFA, challenging the role of OFA as the input stage of the face-processing network. These findings suggest "size-invariant" RS to faces is a consequence of interactions between regions rather than being a localized effect.

A deep learning quantification of patient specificity as a predictor of session attendance and treatment response to internet-enabled cognitive behavioural therapy for common mental health disorders.

BACKGROUND: Increasing an individual's ability to focus on concrete, specific detail, thus reducing the tendency toward overly broad, decontextualised generalisations about the self and world, is a target within cognitive behavioural therapy (CBT). However, empirical investigation of the impact of within-treatment specificity on treatment outcomes is scarce. We evaluated whether the specificity of patient dialogue predicted a) end-of-treatment symptoms and b) session completion for CBT for common mental health issues. METHODS: This preregistered (https://osf.io/agr4t) study trained a deep learning model to score the specificity of patient dialogue in transcripts from 353,614 internet-enabled CBT sessions for common mental health disorders, delivered on behalf of UK NHS services. Data were from obtained from 65,030 participants (n = 47,308 female, n = 241 unstated) aged 18-94 years (M = 34.69, SD = 12.35). Depressive disorders were the most common (39.1 %) primary diagnosis. Primary outcome was end-of-treatment score on the Patient Health Questionnaire-9 (PHQ-9). Secondary outcome was number of sessions attended. RESULTS: Linear mixed-effects models demonstrated that increased patient specificity significantly predicted lower post-treatment symptoms on the PHQ-9, although the size and direction of the effect varied depending on the type of therapeutic activity being completed. Effect sizes were consistently small. Higher patient specificity was associated with completing a greater number of sessions. LIMITATIONS: We are unable to infer causation from our data. CONCLUSIONS: Although effect sizes were small, an effect of specificity was observed across common mental health disorders. Further studies are needed to explore whether encouraging patient specificity during CBT may provide an enhancement of treatment attendance and treatment effects.

Changes in "top-down" connectivity underlie repetition suppression in the ventral visual pathway.

Repetition of the same stimulus leads to a reduction in neural activity known as repetition suppression (RS). In functional magnetic resonance imaging (fMRI), RS is found for multiple object categories. One proposal is that RS reflects locally based "within-region" changes, such as neural fatigue. Thus, if a given region shows RS across changes in stimulus size or view, then it is inferred to hold size- or view-invariant representations. An alternative hypothesis characterizes RS as a consequence of "top-down" between-region modulation. Differentiating between these accounts is central to the correct interpretation of fMRI RS data. It is also unknown whether the same mechanisms underlie RS to identical stimuli and RS across changes in stimulus size or view. Using fMRI, we investigated RS within a body-sensitive network in human visual cortex comprising the extrastriate body area (EBA) and the fusiform body area (FBA). Both regions showed RS to identical images of the same body that was unaffected by changes in body size or view. Dynamic causal modeling demonstrated that changes in backward, top-down (FBA-to-EBA) effective connectivity play a critical role in RS. Furthermore, only repetition of the identical image showed additional changes in forward connectivity (EBA-to-FBA). These results suggest that RS is driven by changes in top-down modulation, whereas the contribution of "feedforward" changes in connectivity is dependent on the precise nature of the repetition. Our results challenge previous interpretations regarding the underlying nature of neural representations made using fMRI RS paradigms.

5-HTTLPR-environment interplay and its effects on neural reactivity in adolescents.

It is not known how 5-HTTLPR genotype x childhood adversity (CA) interactions that are associated with an increased risk for affective disorders in population studies operate at the neural systems level. We hypothesized that healthy adolescents at increased genetic and environmental risk for developing mood disorders (depression and anxiety) would demonstrate increased amygdala reactivity to emotional stimuli compared to those with only one such risk factor or those with none. Participants (n=67) were classified into one of 4 groups dependent on being homozygous for the long or short alleles within the serotonin-transporter-linked polymorphic region (5-HTTLPR) of the SLC6A4 gene and exposure to CA in the first 11 years of life (present or absent). A functional magnetic resonance imaging investigation was undertaken which involved viewing emotionally-salient face stimuli. In addition, we assessed the role of other variables hypothesized to influence amygdala reactivity, namely recent negative life-events (RNLE) assessed at ages 14 and 17, current anxiety symptoms and psychiatric history. We replicated prior findings demonstrating moderation by gene variants in 5-HTTLPR, but found no support for an effect of CA on amygdala reactivity. We also found a significant effect of RNLE aged 17 with amygdala reactivity demonstrating additive, but not interactive effects with 5-HTTLPR. A whole-brain analysis found a 5-HTTLPR×CA interaction in the lingual gyrus whereby CA appears to differentially modify neural reactivity depending on genotype. These results demonstrate that two different forms of environmental adversities interplay with 5-HTTLPR and thereby differentially impact amygdala and cortical reactivity.

Autism spectrum traits in the typical population predict structure and function in the posterior superior temporal sulcus.

Autism spectrum disorders (ASDs) are typically characterized by impaired social interaction and communication, narrow interests, and repetitive behaviors. The heterogeneity in the severity of these characteristics across individuals with ASD has led some researchers to suggest that these disorders form a continuum which extends into the general, or "typical," population, and there is growing evidence that the extent to which typical adults display autistic traits, as measured using the autism-spectrum quotient (AQ), predicts performance on behavioral tasks that are impaired in ASD. Here, we show that variation in autism spectrum traits is related to cortical structure and function within the typical population. Voxel-based morphometry showed that increased AQ scores were associated with decreased white matter volume in the posterior superior temporal sulcus (pSTS), a region important in processing socially relevant stimuli and associated with structural and functional impairments in ASD. In addition, AQ was correlated with the extent of cortical deactivation of an adjacent area of pSTS during a Stroop task relative to rest, reflecting variation in resting state function. The results provide evidence that autism spectrum characteristics are reflected in neural structure and function across the typical (non-ASD) population.

Emotion and personality factors influence the neural response to emotional stimuli.

Lindquist et al. assess the neural evidence for locationist versus psychological construction accounts of human emotion. A wealth of experimental and clinical investigations show that individual differences in emotion and personality influence emotion processing. These factors may also influence the brain's response to emotional stimuli. A synthesis of the relevant neuroimaging data must therefore take these factors into consideration.

Personality predicts the brain's response to viewing appetizing foods: the neural basis of a risk factor for overeating.

Eating is not only triggered by hunger but also by the sight of foods. Viewing appetizing foods alone can induce food craving and eating, although there is considerable variation in this "external food sensitivity" (EFS). Because increased EFS is associated with overeating, identifying its neural correlates is important for understanding the current epidemic of obesity. Animal research has identified the ventral striatum, amygdala, hypothalamus, medial prefrontal and premotor cortices as key interacting structures for feeding. However, it is unclear whether a similar network exists in humans and how it is affected by EFS. Using functional magnetic resonance imaging, we showed that viewing appetizing compared with bland foods produced changes in connectivity among the human ventral striatum, amygdala, anterior cingulate and premotor cortex that were strongly correlated with EFS. Differences in the dynamic interactions within the human appetitive network in response to pictures of appetizing foods may determine an individual's risk of obesity.

"You talkin' to me?" Self-relevant auditory signals influence perception of gaze direction.

In humans, direct gaze typically signals a deliberate attempt to communicate with an observer. An auditory signal with similar signal value is calling someone's name. We investigated whether the presence of this personally relevant signal in the auditory modality would influence perception of another individual's gaze. Participants viewed neutral faces displaying different gaze deviations while hearing someone call their own name or the name of another person. Results were consistent with our predictions, as participants judged faces with a wider range of gaze deviations as looking directly at them when they simultaneously heard their own name. The influence of this personally relevant signal was present only at ambiguous gaze deviations; thus, an overall response bias to categorize gaze as direct when hearing one's own name cannot account for the results. This study provides the first evidence that communicative intent signaled via the auditory modality influences the perception of another individual's gaze.

Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.

Importance: Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for measuring the delivery of psychotherapy. Objective: To use a deep learning model applied to a large-scale clinical data set of cognitive behavioral therapy (CBT) session transcripts to generate a quantifiable measure of treatment delivered and to determine the association between the quantity of each aspect of therapy delivered and clinical outcomes. Design, Setting, and Participants: All data were obtained from patients receiving internet-enabled CBT for the treatment of a mental health disorder between June 2012 and March 2018 in England. Cognitive behavioral therapy was delivered in a secure online therapy room via instant synchronous messaging. The initial sample comprised a total of 17 572 patients (90 934 therapy session transcripts). Patients self-referred or were referred by a primary health care worker directly to the service. Exposures: All patients received National Institute for Heath and Care Excellence-approved disorder-specific CBT treatment protocols delivered by a qualified CBT therapist. Main Outcomes and Measures: Clinical outcomes were measured in terms of reliable improvement in patient symptoms and treatment engagement. Reliable improvement was calculated based on 2 severity measures: Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder 7-item scale (GAD-7), corresponding to depressive and anxiety symptoms respectively, completed by the patient at initial assessment and before every therapy session (see eMethods in the Supplement for details). Results: Treatment sessions from a total of 14 899 patients (10 882 women) aged between 18 and 94 years (median age, 34.8 years) were included in the final analysis. We trained a deep learning model to automatically categorize therapist utterances into 1 or more of 24 feature categories. The trained model was applied to our data set to obtain quantifiable measures of each feature of treatment delivered. A logistic regression revealed that increased quantities of a number of session features, including change methods (cognitive and behavioral techniques used in CBT), were associated with greater odds of reliable improvement in patient symptoms (odds ratio, 1.11; 95% CI, 1.06-1.17) and patient engagement (odds ratio, 1.20, 95% CI, 1.12-1.27). The quantity of nontherapy-related content was associated with reduced odds of symptom improvement (odds ratio, 0.89; 95% CI, 0.85-0.92) and patient engagement (odds ratio, 0.88, 95% CI, 0.84-0.92). Conclusions and Relevance: This work demonstrates an association between clinical outcomes in psychotherapy and the content of therapist utterances. These findings support the principle that CBT change methods help produce improvements in patients' presenting symptoms. The application of deep learning to large clinical data sets can provide valuable insights into psychotherapy, informing the development of new treatments and helping standardize clinical practice.

Anxiety predicts a differential neural response to attended and unattended facial signals of anger and fear.

Behavioural evidence indicates that individual differences in anxiety influence the response to facial signals of threat. Angry and fearful faces represent qualitatively different forms of threat. Fearful faces are thought to signal the presence of a significant, yet undetermined source of danger within the environment, referred to as 'ambiguous threat'. In contrast, angry faces represent a more direct form of threat, often used in face-to-face encounters to exert dominance. Given the inherent differences between anger and fear, we hypothesised that anxiety would modulate the amygdala response to angry faces to a greater extent when attended. Following previous research, we expected anxiety to show a stronger relationship with the amygdala response to unattended fearful faces. In an event-related fMRI study, we presented images of two houses and two faces (consisting of fearful, angry or neutral expressions) in horizontal and vertical pairs around a central fixation cross, with participants instructed to attend to either the face or house stimuli. The results showed that higher anxiety levels produced an increased right amygdala response to viewer directed angry facial expressions (versus neutral or fearful faces) only when attended. By contrast, increased anxiety was associated with a greater left amygdala response to fearful faces (versus neutral or angry faces) in the unattended condition, with only borderline evidence for attended fear (relative to neutral). Our findings demonstrate the striking effects of personality in a non-clinical population, and show how this can distinguish the neural coding of anger and fear faces.

The M170 reflects a viewpoint-dependent representation for both familiar and unfamiliar faces.

The aim of this study was to determine the extent to which the neural representation of faces in visual cortex is viewpoint dependent or viewpoint invariant. Magnetoencephalography was used to measure evoked responses to faces during an adaptation paradigm. Using familiar and unfamiliar faces, we compared the amplitude of the M170 response to repeated images of the same face with images of different faces. We found a reduction in the M170 amplitude to repeated presentations of the same face image compared with images of different faces when shown from the same viewpoint. To establish if this adaptation to the identity of a face was invariant to changes in viewpoint, we varied the viewing angle of the face within a block. We found a reduction in response was no longer evident when images of the same face were shown from different viewpoints. This viewpoint-dependent pattern of results was the same for both familiar and unfamiliar faces. These results imply that either the face-selective M170 response reflects an early stage of face processing or that the computations underlying face recognition depend on a viewpoint-dependent neuronal representation.

Why are you angry with me? Facial expressions of threat influence perception of gaze direction.

Gaze direction can influence the processing of facial expressions. Angry faces are judged more angry when displaying a direct gaze compared to an averted gaze. We investigated whether facial expressions have a reciprocal influence on the perception of gaze. Participants judged the gaze of angry, fearful and neutral faces across a range of gaze directions. Angry faces were perceived as looking at the observer over a wider range than were fearful or neutral faces, which did not significantly differ. This effect was eliminated when presenting inverted faces, suggesting these results cannot be accounted for by differences in visible eye information. Our findings suggest the existence of a reciprocal influence between gaze direction and angry expressions.

Connectivity from the ventral anterior cingulate to the amygdala is modulated by appetitive motivation in response to facial signals of aggression.

For some people facial expressions of aggression are intimidating, for others they are perceived as provocative, evoking an aggressive response. Identifying the key neurobiological factors that underlie this variation is fundamental to our understanding of aggressive behaviour. The amygdala and the ventral anterior cingulate cortex (ACC) have been implicated in aggression. Using functional magnetic resonance imaging (fMRI), we studied how the interaction between these regions is influenced by the drive to obtain reward (reward-drive or appetitive motivation), a personality trait consistently associated with aggression. Two distinct techniques showed that the connectivity between the ventral ACC and the amygdala was strongly correlated with personality, with high reward-drive participants displaying reduced negative connectivity. Furthermore, the direction of this effect was restricted from ventral ACC to the amygdala but not vice versa. The personality-mediated variation in the pathway from the ventral anterior cingulate cortex to the amygdala provides an account of why signals of aggression are interpreted as provocative by some individuals more than others.

Psychopathic traits influence amygdala-anterior cingulate cortex connectivity during facial emotion processing.

There is accumulating evidence that youths with antisocial behavior or psychopathic traits show deficits in facial emotion recognition, but little is known about the neural mechanisms underlying these impairments. A number of neuroimaging studies have investigated brain activity during facial emotion processing in youths with Conduct Disorder (CD) and adults with psychopathy, but few of these studies tested for group differences in effective connectivity-i.e. changes in connectivity during emotion processing. Using functional magnetic resonance imaging and psycho-physiological interaction methods, we investigated the impact of CD and psychopathic traits on amygdala activity and effective connectivity in 46 male youths with CD and 25 typically-developing controls when processing emotional faces. All participants were aged 16-21 years. Relative to controls, youths with CD showed reduced amygdala activity when processing angry or sad faces relative to neutral faces, but the groups did not significantly differ in amygdala-related effective connectivity. In contrast, psychopathic traits were negatively correlated with amygdala-ventral anterior cingulate cortex connectivity for angry vs neutral faces, but were unrelated to amygdala responses to angry or sad faces. These findings suggest that CD and psychopathic traits have differential effects on amygdala activation and functional interactions between limbic regions during facial emotion processing.

Threat visibility modulates the defensive brain circuit underlying fear and anxiety.

Recent theories distinguish anxiety from fear in the brain. Anxiety is associated with activation in ventromedial prefrontal cortex and hippocampus, while fear is associated with activation in periaqueductal gray, with amygdala involved in processing aspects of both emotional responses. These theories propose that the amount of information available about threat determines which of the two defensive responses is elicited, with fear and anxiety associated with well-defined and uncertain threats respectively. However, a direct test of this hypothesis is lacking. Here we provide such a test using fMRI to record participants' brain activity while they performed a computer-based task which required to press a button to move an artificial agent to a target position while an artificial predator chased the agent. In one condition (associated with fear) the predator was visible, while in another condition (associated with anxiety) the predator was invisible. Ventromedial prefrontal cortex, hippocampus, and amygdala showed increased activity when the predator was invisible compared to visible, while the opposite effect was observed in periaqueductal gray. We also observed that participants with high but not low trait-anxiety showed an hippocampal activation with invisible threat at an earlier time stage during the trial. These findings help clarify the neural mechanisms that underlie different defensive emotions and shed light on how these mechanisms may contribute to exaggerated anxiety.