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The recent DSM5 and ICD-11 diagnostic manuals include provisional grief disorders, yet mechanisms of complicated grief are still debated. Effective coping with bereavement requires flexible oscillation between mental states, thus perseverative internally-oriented thought processes may interfere with successful integration of loss into ongoing life. However, frequency of these mental shifts and how they occur in the brain is unknown. I test the idea that grief adaptation may be related to large-scale brain network configuration during unconstrained thought, using resting state fMRI and an intranasal oxytocin manipulation. Older widowed adults (n = 40) with and without complicated grief participated in two resting state fMRI sessions (oxytocin; placebo) as part of a larger within-subjects crossover study. Group spatial ICA identified resting state functional networks. I examined both static and dynamic functional connectivity between network pairs implicated in my theoretical model. Static functional connectivity between core midline default and cingulo-opercular network components predicted complicated grief symptom scores, controlling for age, sex, and depressive symptoms. Oxytocin increased static connectivity between retrosplenial default network and cingulo-opercular network components for the sample as a whole, but did not differentially impact participants based on complicated grief symptoms. Dynamic functional connectivity analyses identified four cluster centroids (or dynamic “states”) that represent time-varying changes in connections between selected network components. The grief severity x state interaction revealed that participants with higher grief severity spent more time in a dynamic state featuring large positive fluctuations in retrosplenial default network connectivity with right frontoparietal, cingulo-opercular, and midline core default components, indicating that higher-grief participants spent more time in a state characterized by lower network

Modern medicine has allowed individuals with metastatic cancer to live longer than ever before, sometimes extending a patient’s life by several years. However, these individuals are still living with an incurable disease, and therefore live with the awareness of their own upcoming death. In this context, double awareness is a term that refers to a patient’s ability to engage meaningfully in life while also acknowledging and preparing for their death. Understanding this phenomenon holds great potential for supporting individuals living with metastatic and incurable cancers. Double awareness has been conceptualized as a sign of psychological health and is already being studied as a target for change in interventions that seek to support individuals at the end of life. However, until now there has previously been no instrument to measure or quantify this construct. The present study aims to create the first measure of double awareness by conducting a three-phase, mixed-method approach involving (1) instrument development, (2) qualitative inquiry and (3) quantitative analysis and validation. The first two phases have been completed successfully and the third phase remains in progress. Preliminary analyses of the third phase include a sample of 46 patients with metastatic cancer. Data from this sample resulted in a twenty-item, tentative measure called the “Double Awareness Scale”. This instrument has two distinct subscales, which we call Life Engagement and Death Contemplation, each containing ten items. These subscales are not additive, but instead create a “profile” in which an individual can be high or low on either subscale. The Double Awareness Scale demonstrated internal consistency and preliminary evidence for discriminant and convergent validity in this sample. Scores on the Death Contemplation subscale predicted openness to hospice services, indicating that the scale has psychological and behavioral implications for end-of-life care.

Closed-loop neuromodulation is presumed to be the logical evolution for improving the effectiveness of deep brain stimulation (DBS) treatment protocols (Widge a al., 2018). Identifying symptom-relevant biomarkers that provide meaningful feedback to stimulator devices is an important initial step in this direction. This report demonstrates a technique for assaying neural circuitry hypothesized to contribute to OCD and DBS treatment outcomes. We computed phase-lag connectivity between LFPs and EEGs in thirteen treatment-refractory OCD patients. Simultaneous recordings from scalp EEG and externalized DBS electrodes in the ventral capsule/ventral striatum (VC/VS) were collected at rest during the perioperative treatment stage. Connectivity strength between midfrontal EEG sensors and VC/VS electrodes correlated with baseline OCD symptoms and 12-month post-treatment OCD symptoms. Results are qualified by a relatively small sample size, and limitations regarding the conclusiveness of VS and mPFC as neural generators given some concerns about volume conduction. Nonetheless, findings are consistent with treatment-relevant tractography findings and theories that link frontostriatal hyperconnectivity to the etiopathogenesis of OCD. Findings support the continued investigation of connectivity-based assays for aiding in determination of optimal stimulation location, and are an initial step towards the identification of biomarkers that can guide closed-loop neuromodulation systems.