Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    The veridical Near-Death Experience Scale: construction and a first validation with human and artificial raters
    (Frontiers Media S A, 2025-10-16) Greyson B; Long J; Holden JM; Jourdan J-P; King RA; Mays S; Mays R; Rivas T; Tassell-Matamua N; van Lommel P; Woollacott M; Tressoldi P; Panda R
    Introduction: In this study, we describe the construction of the veridical Near-Death Experience Scale (vNDE Scale), a structured instrument for evaluating the evidential strength of perceptions reported during near-death experiences (NDEs), and its first validation by human and artificial raters. Methods: The construction was implemented using a typical Delphi Method. The first draft of the scale was evaluated by 13 experts in NDE, who were asked to suggest revisions and comments within a month for the first round and 20 days for the second round. Results: A general consensus was achieved on the second round on eight criteria related to the timing of the investigation, the medical and physical conditions, the level of third-person verification, and the number, type, and quality of perceptions reported by the near-death experiencer, to be rated on a four-level Likert scale. The validation phase consisted of the application of the vNDE Scale to 17 cases of potentially veridical NDEs by 11 independent human raters and three artificial raters based on Large-Language Models. In 14 of the17 cases (82.3%), the overall agreement between human and artificial judges was over 75%, considering the two close levels of evidence strength, i.e., moderate plus strong, low plus very low, or vice-versa. Discussion: The vNDE Scale is a practical tool for evaluating the evidential strength of perceptions reported by near-death experiencers.
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    Longitudinal Bedside Assessments of Brain Networks in Disorders of Consciousness: Case Reports From the Field
    (Frontiers Media S.A, 2018) Bareham CA; Allanson J; Roberts N; Hutchinson PJA; Pickard JD; Menon DK; Chennu S
    Clinicians are regularly faced with the difficult challenge of diagnosing consciousness after severe brain injury. As such, as many as 40% of minimally conscious patients who demonstrate fluctuations in arousal and awareness are known to be misdiagnosed as unresponsive/vegetative based on clinical consensus. Further, a significant minority of patients show evidence of hidden awareness not evident in their behavior. Despite this, clinical assessments of behavior are commonly used as bedside indicators of consciousness. Recent advances in functional high-density electroencephalography (hdEEG) have indicated that specific patterns of resting brain connectivity measured at the bedside are strongly correlated with the re-emergence of consciousness after brain injury. We report case studies of four patients with traumatic brain injury who underwent regular assessments of hdEEG connectivity and Coma Recovery Scale-Revised (CRS-R) at the bedside, as part of an ongoing longitudinal study. The first, a patient in an unresponsive wakefulness state (UWS), progressed to a minimally-conscious state several years after injury. HdEEG measures of alpha network centrality in this patient tracked this behavioral improvement. The second patient, contrasted with patient 1, presented with a persistent UWS diagnosis that paralleled with stability on the same alpha network centrality measure. Patient 3, diagnosed as minimally conscious minus (MCS–), demonstrated a significant late increase in behavioral awareness to minimally conscious plus (MCS+). This patient's hdEEG connectivity across the previous 18 months showed a trajectory consistent with this increase alongside a decrease in delta power. Patient 4 contrasted with patient 3, with a persistent MCS- diagnosis that was similarly tracked by consistently high delta power over time. Across these contrasting cases, hdEEG connectivity captures both stability and recovery of behavioral trajectories both within and between patients. Our preliminary findings highlight the feasibility of bedside hdEEG assessments in the rehabilitation context and suggest that they can complement clinical evaluation with portable, accurate and timely generation of brain-based patient profiles. Further, such hdEEG assessments could be used to estimate the potential utility of complementary neuroimaging assessments, and to evaluate the efficacy of interventions.