Effective psychological therapy for PTSD changes the dynamics of specific large-scale brain networks

In posttraumatic stress disorder (PTSD), re-experiencing of the trauma is a hallmark symptom proposed to emerge from a de-contextualised trauma memory. Cognitive therapy for PTSD (CT-PTSD) addresses this de-contextualisation through different strategies. At the brain level, recent research suggests that the dynamics of specific large-scale brain networks play an essential role in both the healthy response to a threatening situation and the development of PTSD. However, very little is known about how these dynamics are altered in the disorder and rebalanced after treatment and successful recovery. Using a data-driven approach and fMRI, we detected recurring large-scale brain functional states with high temporal precision in a population of healthy trauma-exposed and PTSD participants before and after successful CT-PTSD. We estimated the total amount of time that each participant spent on each of the states while being exposed to trauma-related and neutral pictures. We found that PTSD participants spent less time on two default mode subnetworks involved in different forms of self-referential processing in contrast to PTSD participants after CT-PTSD (mtDMN+ and dmDMN+) and healthy trauma-exposed controls (only mtDMN+). Furthermore, re-experiencing severity was related to decreased time spent on the default mode subnetwork involved in contextualised retrieval of autobiographical memories, and increased time spent on the salience and visual networks. Overall, our results support the hypothesis that PTSD involves an imbalance in the dynamics of specific large-scale brain network states involved in self-referential processes and threat detection, and suggest that successful CT-PTSD might rebalance this dynamic aspect of brain function

Using highly time-resolved online mass spectrometry to examine biogenic and anthropogenic contributions to organic aerosol in Beijing

Organic aerosols, a major constituent of fine particulate mass in megacities, can be directly emitted or formed from secondary processing of biogenic and anthropogenic volatile organic compound emissions. The complexity of volatile organic compound emission sources, speciation and oxidation pathways leads to uncertainties in the key sources and chemistry leading to formation of organic aerosol in urban areas. Historically, online measurements of organic aerosol composition have been unable to resolve specific markers of volatile organic compound oxidation, while offline analysis of markers focus on a small proportion of organic aerosol and lack the time resolution to carry out detailed statistical analysis required to study the dynamic changes in aerosol sources and chemistry. Here we use data collected as part of the joint UK–China Air Pollution and Human Health (APHH-Beijing) collaboration during a field campaign in urban Beijing in the summer of 2017 alongside laboratory measurements of secondary organic aerosol from oxidation of key aromatic precursors (1,3,5-trimethyl benzene, 1,2,4-trimethyl benzene, propyl benzene, isopropyl benzene and 1-methyl naphthalene) to study the anthropogenic and biogenic contributions to organic aerosol. For the first time in Beijing, this study applies positive matrix factorisation to online measurements of organic aerosol composition from a time-of-flight iodide chemical ionisation mass spectrometer fitted with a filter inlet for gases and aerosols (FIGAERO-ToF-I-CIMS). This approach identifies the real-time variations in sources and oxidation processes influencing aerosol composition at a near-molecular level. We identify eight factors with distinct temporal variability, highlighting episodic differences in OA composition attributed to regional influences and in situ formation. These have average carbon numbers ranging from C5–C9 and can be associated with oxidation of anthropogenic aromatic hydrocarbons alongside biogenic emissions of isoprene, α-pinene and sesquiterpenes

Rebuilding lives in the Recovery College

In April 2018, I enrolled on a tutor training course with the Oxfordshire Recovery College. Could I use my experiences of mental ill health, time within ‘the system’ and eventual recovery in order to benefit others on similar journeys

Autistic Cognition:Charting Routes to Anxiety

Autism Spectrum Conditions are typified by a divergence in cognitive style from that of the non-autistic population. Cognitive differences in autism may underlie significant strengths, but also increase vulnerability to psychopathology such as anxiety, which is a major problem for many autistic people. Many autistic people also do not respond to typical psychotherapeutic interventions, suggesting that autism-specific models and interventions are needed. We advance a theoretical model explaining how three constructs, attenuated predictions, intolerance of uncertainty, and 'black and white thinking', may interact to lead to anxiety in autism. We hope to start a dialogue surrounding how we can best address specific autistic cognitive differences that may lead to distress by developing appropriate models, measurements, and psychotherapeutic interventions

The meditative brain: State and trait changes in harmonic complexity for long-term mindfulness meditators

Meditation is an ancient practice that is shown to yield benefits for cognition, emotion regulation and human flourishing. In the last two decades, there has been a surge of interest in extracting the neural correlates of meditation, in particular of mindfulness meditation. Yet, these efforts have been mostly limited to the analysis of certain regions or networks of interest and a clear understanding of meditation-induced changes in the whole-brain dynamics has been lacking. Here, we investigate meditation-induced changes in brain dynamics using a novel connectome-specific harmonic decomposition method. Specifically, utilising the connectome harmonics as brain states - elementary building blocks of complex brain dynamics - we study the immediate (state) and long-term (trait) effects of mindfulness meditation in terms of the energy, power and complexity of the repertoire of these harmonic brain states. Our results reveal increased power, energy and complexity of the connectome harmonic repertoire and demonstrate that meditation alters brain dynamics in a frequency selective manner. Remarkably, the frequency-specific alterations observed in meditation are reversed in resting state in group-wise comparison revealing for the first time the long-term (trait) changes induced by meditation. These findings also provide evidence for the entropic brain hypothesis in meditation and provide a novel understanding of state and trait changes in brain dynamics induced by mindfulness meditation revealing the unique connectome harmonic signatures of the meditative brain

Effective psychological therapy for PTSD changes the dynamics of specific large-scale brain networks

In posttraumatic stress disorder (PTSD), re-experiencing of the trauma is a hallmark symptom proposed to emerge from a de-contextualised trauma memory. Cognitive therapy for PTSD (CT-PTSD) addresses this de-contextualisation through different strategies. At the brain level, recent research suggests that the dynamics of specific large-scale brain networks play an essential role in both the healthy response to a threatening situation and the development of PTSD. However, very little is known about how these dynamics are altered in the disorder and rebalanced after treatment and successful recovery. Using a data-driven approach and fMRI, we detected recurring large-scale brain functional states with high temporal precision in a population of healthy trauma-exposed and PTSD participants before and after successful CT-PTSD. We estimated the total amount of time that each participant spent on each of the states while being exposed to trauma-related and neutral pictures. We found that PTSD participants spent less time on two default mode subnetworks involved in different forms of self-referential processing in contrast to PTSD participants after CT-PTSD (mtDMN+ and dmDMN+) and healthy trauma-exposed controls (only mtDMN+). Furthermore, re-experiencing severity was related to decreased time spent on the default mode subnetwork involved in contextualised retrieval of autobiographical memories, and increased time spent on the salience and visual networks. Overall, our results support the hypothesis that PTSD involves an imbalance in the dynamics of specific large-scale brain network states involved in self-referential processes and threat detection, and suggest that successful CT-PTSD might rebalance this dynamic aspect of brain function

The power of smiling: the adult brain networks underlying learned infant emotionality

The perception of infant emotionality, one aspect of temperament, starts to form in infancy, yet the underlying mechanisms of how infant emotionality affects adult neural dynamics remain unclear. We used a social reward task with probabilistic visual and auditory feedback (infant laughter or crying) to train 47 nulliparous women to perceive the emotional style of six different infants. Using functional neuroimaging, we subsequently measured brain activity while participants were tested on the learned emotionality of the six infants. We characterized the elicited patterns of dynamic functional brain connectivity using Leading Eigenvector Dynamics Analysis and found significant activity in a brain network linking the orbitofrontal cortex with the amygdala and hippocampus, where the probability of occurrence significantly correlated with the valence of the learned infant emotional disposition. In other words, seeing infants with neutral face expressions after having interacted and learned their various degrees of positive and negative emotional dispositions proportionally increased the activity in a brain network previously shown to be involved in pleasure, emotion, and memory. These findings provide novel neuroimaging insights into how the perception of happy versus sad infant emotionality shapes adult brain networks

Telehealth Autism Diagnostic Assessments with Children, Young People, and Adults:Qualitative Interview Study with England-Wide Multidisciplinary Health Professionals

BACKGROUND: Autism spectrum disorder (hereafter, autism) is a common neurodevelopmental condition. Core traits can range from subtle to severe and fluctuate depending on context. Individuals can present for diagnostic assessments during childhood or adulthood. However, waiting times for assessment are typically lengthy, and many individuals wait months or even years to be seen. Traditionally, there has been a lack of standardization between services regarding how many and which multidisciplinary health professionals are involved in the assessment and the methods (diagnostic tools) that are used. The COVID-19 pandemic has affected routine service provision because of stay-at-home mandates and social distancing guidelines. Autism diagnostic services have had to adapt, such as by switching from conducting assessments in person to doing these fully via telehealth (defined as the use of remote technologies for the provision of health care) or using blended in-person or telehealth methods. OBJECTIVE: This study explored health professionals’ experiences of and perspectives about conducting telehealth autism diagnostic assessments, including barriers and facilitators to this, during the COVID-19 pandemic; potential telehealth training and supervision needs of health professionals; how the quality and effectiveness of telehealth autism diagnostic services can be enhanced; and experiences of delivering postdiagnostic support remotely. METHODS: A total of 45 health professionals, working in varied settings across England, participated in one-off, in-depth semistructured qualitative interviews. These were conducted via videoconferencing or telephone. Altogether, participants represented 7 professional disciplines (psychiatry, medicine, psychology, speech and language therapy, occupational therapy, nursing, and social work). The data were then analyzed thematically. RESULTS: Thematic analysis indicated the following 7 themes: practicalities of telehealth, telehealth autism diagnostic assessments, diagnostic conclusions, clinical considerations, postdiagnostic support, future ways of working, and health professionals’ experiences and needs. Overall, telehealth autism diagnostic assessments were deemed by many participants to be convenient, flexible, and efficient for some patients, families, and health professionals. However, not all patients could be assessed in this way, for example, because of digital poverty, complex clinical presentation, or concerns about risk and safeguarding. Working remotely encouraged innovation, including the development of novel assessment measures. However, some participants expressed significant concerns about the validity and reliability of remotely assessing social communication conditions. CONCLUSIONS: A shift to telehealth meant that autism diagnostic services remained operational during the COVID-19 pandemic. However, this method of working has potentially affected the parity of service, with people presenting with clinical complexity having to potentially wait longer to be seen or given a diagnostic opinion. There is also a lack of standardization in the provision of services. Further research should identify evidence-based ways of enhancing the timeliness, accessibility, and robustness of the autism diagnostic pathway, as well as the validity and reliability of telehealth methods