Patients' Perspectives on Life and Recovery 1 Year After COVID-19 Hospitalization.

BACKGROUND: Many patients hospitalized for COVID-19 experience prolonged symptoms months after discharge. Little is known abou t patients' personal experiences recovering from COVID-19 in the United States (US), where medically underserved populations are at particular risk of adverse outcomes. OBJECTIVE: To explore patients' perspectives on the impact of COVID-19 hospitalization and barriers to and facilitators of recovery 1 year after hospital discharge in a predominantly Black American study population with high neighborhood-level socioeconomic disadvantage. DESIGN: Qualitative study utilizing individual, semi-structured interviews. PARTICIPANTS: Adult patients hospitalized for COVID-19 approximately 1 year after discharge home who were engaged in a COVID-19 longitudinal cohort study. APPROACH: The interview guide was developed and piloted by a multidisciplinary team. Interviews were audio-recorded and transcribed. Data were coded and organized into discrete themes using qualitative content analysis with constant comparison techniques. KEY RESULTS: Of 24 participants, 17 (71%) self-identified as Black, and 13 (54%) resided in neighborhoods with the most severe neighborhood-level socioeconomic disadvantage. One year after discharge, participants described persistent deficits in physical, cognitive, or psychological health that impacted their current lives. Repercussions included financial suffering and a loss of identity. Participants reported that clinicians often focused on physical health over cognitive and psychological health, an emphasis that posed a barrier to recovering holistically. Facilitators of recovery included robust financial or social support systems and personal agency in health maintenance. Spirituality and gratitude were common coping mechanisms. CONCLUSIONS: Persistent health deficits after COVID-19 resulted in downstream consequences in participants' lives. Though participants received adequate care to address physical needs, many described persistent unmet cognitive and psychological needs. A more comprehensive understanding of barriers and facilitators for COVID-19 recovery, contextualized by specific healthcare and socioeconomic needs related to socioeconomic disadvantage, is needed to better inform intervention delivery to patients that experience long-term sequelae of COVID-19 hospitalization.

Neuropsychology of Human Body Parts: Exploring Categorical Boundaries of Tactile Perception Using Somatosensory Mismatch Responses.

The focus of the current study is on a particular aspect of tactile perception: categorical segmentation on the body surface into discrete body parts. The MMN has been shown to be sensitive to categorical boundaries and language experience in the auditory modality. Here we recorded the somatosensory MMN (sMMN) using two tactile oddball protocols and compared sMMN amplitudes elicited by within- and across-boundary oddball pairs. Both protocols employed the identity MMN method that controls for responsivity at each body location. In the first protocol, we investigated the categorical segmentation of tactile space at the wrist by presenting pairs of tactile oddball stimuli across equal spatial distances, either across the wrist or within the forearm. Amplitude of the sMMN elicited by stimuli presented across the wrist boundary was significantly greater than for stimuli presented within the forearm, suggesting a categorical effect at an early stage of somatosensory processing. The second protocol was designed to investigate the generality of this MMN effect, and involved three digits on one hand. Amplitude of the sMMN elicited by a contrast of the third digit and the thumb was significantly larger than a contrast between the third and fifth digits, suggesting a functional boundary effect that may derive from the way that objects are typically grasped. These findings demonstrate that the sMMN is a useful index of processing of somatosensory spatial discrimination that can be used to study body part categories.

Structural brain network deviations predict recovery after traumatic brain injury.

OBJECTIVE: Traumatic brain injury results in diffuse axonal injury and the ensuing maladaptive alterations in network function are associated with incomplete recovery and persistent disability. Despite the importance of axonal injury as an endophenotype in TBI, there is no biomarker that can measure the aggregate and region-specific burden of axonal injury. Normative modeling is an emerging quantitative case-control technique that can capture region-specific and aggregate deviations in brain networks at the individual patient level. Our objective was to apply normative modeling in TBI to study deviations in brain networks after primarily complicated mild TBI and study its relationship with other validated measures of injury severity, burden of post-TBI symptoms, and functional impairment. METHOD: We analyzed 70 T1-weighted and diffusion-weighted MRIs longitudinally collected from 35 individuals with primarily complicated mild TBI during the subacute and chronic post-injury periods. Each individual underwent longitudinal blood sampling to characterize blood protein biomarkers of axonal and glial injury and assessment of post-injury recovery in the subacute and chronic periods. By comparing the MRI data of individual TBI participants with 35 uninjured controls, we estimated the longitudinal change in structural brain network deviations. We compared network deviation with independent measures of acute intracranial injury estimated from head CT and blood protein biomarkers. Using elastic net regression models, we identified brain regions in which deviations present in the subacute period predict chronic post-TBI symptoms and functional status. RESULTS: Post-injury structural network deviation was significantly higher than controls in both subacute and chronic periods, associated with an acute CT lesion and subacute blood levels of glial fibrillary acid protein (r = 0.5, p = 0.008) and neurofilament light (r = 0.41, p = 0.02). Longitudinal change in network deviation associated with change in functional outcome status (r = -0.51, p = 0.003) and post-concussive symptoms (BSI: r = 0.46, p = 0.03; RPQ: r = 0.46, p = 0.02). The brain regions where the node deviation index measured in the subacute period predicted chronic TBI symptoms and functional status corresponded to areas known to be susceptible to neurotrauma. CONCLUSION: Normative modeling can capture structural network deviations, which may be useful in estimating the aggregate and region-specific burden of network changes induced by TAI. If validated in larger studies, structural network deviation scores could be useful for enrichment of clinical trials of targeted TAI-directed therapies.

Differential Impact of Anxious Misery Psychopathology on Multiple Representations of the Functional Connectome.

Background: One aim of characterizing dimensional psychopathology is associating different domains of affective dysfunction with brain circuitry. The functional connectome, as measured by functional magnetic resonance imaging, can be modeled and associated with psychopathology through multiple methods; some methods assess univariate relationships while others summarize broad patterns of activity. It remains unclear whether different dimensions of psychopathology require different representations of the connectome to generate reproducible associations. Methods: Patients experiencing anxious misery symptomology (depression, anxiety, and trauma; n = 192) received resting-state functional magnetic resonance imaging scans. Three modeling approaches (seed-based correlation analysis, edgewise regression, and brain basis set modeling), each relying on increasingly broader representations of the functional connectome, were used to associate connectivity patterns with six data-driven dimensions of psychopathology: anxiety sensitivity, anxious arousal, rumination, anhedonia, insomnia, and negative affect. To protect against overfitting, 50 participants were held out in a testing dataset, leaving 142 participants as training data. Results: Different modeling approaches varied in the extent to which they could model different symptom dimensions: seed-based correlation analysis failed to reproducibly model any symptoms, subsets of the connectome (edgewise regression) were sufficient to model insomnia and anxious arousal, and broad representations of the entire connectome (brain basis set modeling) were necessary to model negative affect and ruminative thought. Conclusions: These results indicate that different methods of representing the functional connectome differ in the degree that they can model different symptom dimensions, highlighting the potential sufficiency of subsets of connections for some dimensions and the necessity of connectome-wide approaches in others.

Proof of concept study to develop a novel connectivity-based electric-field modelling approach for individualized targeting of transcranial magnetic stimulation treatment.

Resting state functional connectivity (rsFC) offers promise for individualizing stimulation targets for transcranial magnetic stimulation (TMS) treatments. However, current targeting approaches do not account for non-focal TMS effects or large-scale connectivity patterns. To overcome these limitations, we propose a novel targeting optimization approach that combines whole-brain rsFC and electric-field (e-field) modelling to identify single-subject, symptom-specific TMS targets. In this proof of concept study, we recruited 91 anxious misery (AM) patients and 25 controls. We measured depression symptoms (MADRS/HAMD) and recorded rsFC. We used a PCA regression to predict symptoms from rsFC and estimate the parameter vector, for input into our e-field augmented model. We modeled 17 left dlPFC and 7 M1 sites using 24 equally spaced coil orientations. We computed single-subject predicted ΔMADRS/HAMD scores for each site/orientation using the e-field augmented model, which comprises a linear combination of the following elementwise products (1) the estimated connectivity/symptom coefficients, (2) a vectorized e-field model for site/orientation, (3) rsFC matrix, scaled by a proportionality constant. In AM patients, our connectivity-based model predicted a significant decrease depression for sites near BA9, but not M1 for coil orientations perpendicular to the cortical gyrus. In control subjects, no site/orientation combination showed a significant predicted change. These results corroborate previous work suggesting the efficacy of left dlPFC stimulation for depression treatment, and predict better outcomes with individualized targeting. They also suggest that our novel connectivity-based e-field modelling approach may effectively identify potential TMS treatment responders and individualize TMS targeting to maximize the therapeutic impact.

Dimensional connectomics of anxious misery, a human connectome study related to human disease: Overview of protocol and data quality.

Disparate diagnostic categories from the Diagnostic and Statistical Manual of Mental Disorders (DSM), including generalized anxiety disorder, major depressive disorder and post-traumatic stress disorder, share common behavioral and phenomenological dysfunctions. While high levels of comorbidity and common features across these disorders suggest shared mechanisms, past research in psychopathology has largely proceeded based on the syndromal taxonomy established by the DSM rather than on a biologically-informed framework of neural, cognitive and behavioral dysfunctions. In line with the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, we present a Human Connectome Study Related to Human Disease that is intentionally designed to generate and test novel, biologically-motivated dimensions of psychopathology. The Dimensional Connectomics of Anxious Misery study is collecting neuroimaging, cognitive and behavioral data from a heterogeneous population of adults with varying degrees of depression, anxiety and trauma, as well as a set of healthy comparators (to date, n = 97 and n = 24, respectively). This sample constitutes a dataset uniquely situated to elucidate relationships between brain circuitry and dysfunctions of the Negative Valence construct of the RDoC framework. We present a comprehensive overview of the eligibility criteria, clinical procedures and neuroimaging methods of our project. After describing our protocol, we present group-level activation maps from task fMRI data and independent components maps from resting state data. Finally, using quantitative measures of neuroimaging data quality, we demonstrate excellent data quality relative to a subset of the Human Connectome Project of Young Adults (n = 97), as well as comparable profiles of cortical thickness from T1-weighted imaging and generalized fractional anisotropy from diffusion weighted imaging. This manuscript presents results from the first 121 participants of our full target 250 participant dataset, timed with the release of this data to the National Institute of Mental Health Data Archive in fall 2020, with the remaining half of the dataset to be released in 2021.

Sensorimotor Oscillations During a Reciprocal Touch Paradigm With a Human or Robot Partner.

Robots provide an opportunity to extend research on the cognitive, perceptual, and neural processes involved in social interaction. This study examined how sensorimotor oscillatory electroencephalogram (EEG) activity can be influenced by the perceived nature of a task partner - human or robot - during a novel "reciprocal touch" paradigm. Twenty adult participants viewed a demonstration of a robot that could "feel" tactile stimulation through a haptic sensor on its hand and "see" changes in light through a photoreceptor at the level of the eyes; the robot responded to touch or changes in light by moving a contralateral digit. During EEG collection, participants engaged in a joint task that involved sending tactile stimulation to a partner (robot or human) and receiving tactile stimulation back. Tactile stimulation sent by the participant was initiated by a button press and was delivered 1500 ms later via an inflatable membrane on the hand of the human or on the haptic sensor of the robot partner. Stimulation to the participant's finger (from the partner) was sent on a fixed schedule, regardless of partner type. We analyzed activity of the sensorimotor mu rhythm during anticipation of tactile stimulation to the right hand, comparing mu activity at central electrode sites when participants believed that tactile stimulation was initiated by a robot or a human, and to trials in which "nobody" received stimulation. There was a significant difference in contralateral mu rhythm activity between anticipating stimulation from a human partner and the "nobody" condition. This effect was less pronounced for anticipation of stimulation from the robot partner. Analyses also examined beta rhythm responses to the execution of the button press, comparing oscillatory activity when participants sent tactile stimulation to the robot or the human partner. The extent of beta rebound at frontocentral electrode sites following the button press differed between conditions, with a significantly larger increase in beta power when participants sent tactile stimulation to a robot partner compared to the human partner. This increase in beta power may reflect greater predictably in event outcomes. This new paradigm and the novel findings advance the neuroscientific study of human-robot interaction.

The stability of engagement over comprehensive neuropsychological assessment in student athletes diagnosed with sports related concussion.

We documented effort stability during neuropsychological (NP) testing examining failure rates on three Performance Validity Tests (PVTs). 65 student athletes, ages 8-21, were evaluated in an outpatient practice, following sports-related concussion over three sessions within 18 months of injury (mean=6 months). 7.7% of student athletes failed PVTs at all three test sessions, 7.7% failed PVTs at two test sessions, and 12.3% failed PVTs at one session; 28% of this sample was sub-optimally engaged for at least one test session, producing invalid neuropsychological data at the time of testing and 72% produced valid neuropsychological data across the comprehensive evaluation.

Using somatosensory mismatch responses as a window into somatotopic processing of tactile stimulation.

Brain responses to tactile stimulation have often been studied through the examination of ERPs elicited to touch on the body surface. Here, we examined two factors potentially modulating the amplitude of the somatosensory mismatch negativity (sMMN) and P300 responses elicited by touch to pairs of body parts: (a) the distance between the representation of these body parts in somatosensory cortex, and (b) the physical distances between the stimulated points on the body surface. The sMMN and the P300 response were elicited by tactile stimulation in two oddball protocols. One protocol leveraged a discontinuity in cortical somatotopic organization, and involved stimulation of either the neck or the hand in relation to stimulation of the lip. The other protocol involved stimulation to the third or fifth finger in relation to the second finger. The neck-lip pairing resulted in significantly larger sMMN responses (with shorter latencies) than the hand-lip pairing, whereas the reverse was true for the amplitude of the P300. Mean sMMN amplitude and latency did not differ between finger pairings. However, larger P300 responses were elicited to stimulation of the fifth finger than the third finger. These results suggest that, for certain combinations of body parts, early automatic somatosensory mismatch responses may be influenced by distance between the cortical representations of these body parts, whereas the later P300 response may be more influenced by the distance between stimulated body parts on the body surface. Future investigations can shed more light on this novel suggestion.

Long-term Stability and Reliability of Baseline Cognitive Assessments in High School Athletes Using ImPACT at 1-, 2-, and 3-year Test-Retest Intervals.

OBJECTIVE: The ImPACT (Immediate Post-Concussion Assessment and Cognitive Testing) neurocognitive testing battery is a widely used tool used for the assessment and management of sports-related concussion. Research on the stability of ImPACT in high school athletes at a 1- and 2-year intervals have been inconsistent, requiring further investigation. We documented 1-, 2-, and 3-year test-retest reliability of repeated ImPACT baseline assessments in a sample of high school athletes, using multiple statistical methods for examining stability. METHODS: A total of 1,510 high school athletes completed baseline cognitive testing using online ImPACT test battery at three time periods of approximately 1- (N = 250), 2- (N = 1146), and 3-year (N = 114) intervals. No participant sustained a concussion between assessments. RESULTS: Intraclass correlation coefficients (ICCs) ranged in composite scores from 0.36 to 0.90 and showed little change as intervals between assessments increased. Reliable change indices and regression-based measures (RBMs) examining the test-retest stability demonstrated a lack of significant change in composite scores across the various time intervals, with very few cases (0%-6%) falling outside of 95% confidence intervals. CONCLUSION: The results suggest ImPACT composites scores remain considerably stability across 1-, 2-, and 3-year test-retest intervals in high school athletes, when considering both ICCs and RBM. Annually ascertaining baseline scores continues to be optimal for ensuring accurate and individualized management of injury for concussed athletes. For instances in which more recent baselines are not available (1-2 years), clinicians should seek to utilize more conservative range estimates in determining the presence of clinically meaningful change in cognitive performance.