Dataset Information

Assessing residual reasoning ability in overtly non-communicative patients using fMRI.

ABSTRACT: It is now well established that some patients who are diagnosed as being in a vegetative state or a minimally conscious state show reliable signs of volition that may only be detected by measuring neural responses. A pertinent question is whether these patients are also capable of logical thought. Here, we validate an fMRI paradigm that can detect the neural fingerprint of reasoning processes and moreover, can confirm whether a participant derives logical answers. We demonstrate the efficacy of this approach in a physically non-communicative patient who had been shown to engage in mental imagery in response to simple auditory instructions. Our results demonstrate that this individual retains a remarkable capacity for higher cognition, engaging in the reasoning task and deducing logical answers. We suggest that this approach is suitable for detecting residual reasoning ability using neural responses and could readily be adapted to assess other aspects of cognition.

SUBMITTER: Hampshire A

PROVIDER: S-EPMC3777757 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Assessing residual reasoning ability in overtly non-communicative patients using fMRI.

Hampshire Adam A Parkin Beth L BL Cusack Rhodri R Espejo Davinia Fernández DF Allanson Judith J Kamau Evelyn E Pickard John D JD Owen Adrian M AM

NeuroImage. Clinical 20121130

It is now well established that some patients who are diagnosed as being in a vegetative state or a minimally conscious state show reliable signs of volition that may only be detected by measuring neural responses. A pertinent question is whether these patients are also capable of logical thought. Here, we validate an fMRI paradigm that can detect the neural fingerprint of reasoning processes and moreover, can confirm whether a participant derives logical answers. We demonstrate the efficacy of ...[more]

PMID: 24179769

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Project description:Drug-induced cardiac toxicity has been implicated in 31% of drug withdrawals in the USA. The fact that the risk for cardiac-related adverse events goes undetected in preclinical studies for so many drugs underscores the need for better, more predictive in vitro safety screens to be deployed early in the drug discovery process. Unfortunately, many questions remain about the ability to accurately translate findings from simple cellular systems to the mechanisms that drive toxicity in the complex in vivo environment. In this study, we analyzed translatability of cardiotoxic effects for a diverse set of drugs from rodents to two different cell systems (rat heart tissue-derived cells (H9C2) and primary rat cardiomyocytes (RCM)) based on their transcriptional response. To unravel the altered pathway, we applied a novel computational systems biology approach, the Causal Reasoning Engine (CRE), to infer upstream molecular events causing the observed gene expression changes. By cross-referencing the cardiotoxicity annotations with the pathway analysis, we found evidence of mechanistic convergence towards common molecular mechanisms regardless of the cardiotoxic phenotype. We also experimentally verified two specific molecular hypotheses that translated well from in vivo to in vitro (Kruppel-like factor 4, KLF4 and Transforming growth factor beta 1, TGFB1) supporting the validity of the predictions of the computational pathway analysis. In conclusion, this work demonstrates the use of a novel systems biology approach to predict mechanisms of toxicity such as KLF4 and TGFB1 that translate from in vivo to in vitro. We also show that more complex in vitro models such as primary rat cardiomyocytes may not offer any advantage over simpler models such as immortalized H9C2 cells in terms of translatability to in vivo effects if we consider the right endpoints for the model. Further assessment and validation of the generated molecular hypotheses would greatly enhance our ability to design predictive in vitro cardiotoxicity assays.

Project description:BACKGROUND:The clinical reasoning process, which requires biomedical knowledge, knowledge about problem-solving strategies, and knowledge about reasons for diagnostic procedures, is a key element of physicians' daily practice but difficult to assess. The aim of this study was to empirically develop a Clinical Reasoning Indicators-History Taking-Scale (CRI-HT-S) and to assess the clinical reasoning ability of advanced medical students during a simulation involving history taking. METHODS:The Clinical Reasoning Indictors-History Taking-Scale (CRI-HT-S) including a 5-point Likert scale for assessment was designed from clinical reasoning indicators identified in a qualitative study in 2017. To assess indicators of clinical reasoning ability, 65 advanced medical students (semester 10, n =?25 versus final year, n =?40) from three medical schools participated in a 360-degree competence assessment in the role of beginning residents during a simulated first workday in hospital. This assessment included a consultation hour with five simulated patients which was videotaped. Videos of 325 patient consultations were assessed using the CRI-HT-S. A factor analysis was conducted and the students' results were compared according to their advancement in undergraduate medical training. RESULTS:The clinical reasoning indicators of the CRI-HT-S loaded on three factors relevant for clinical reasoning: 1) focusing questions, 2) creating context, and 3) securing information. Students reached significantly different scores (p <?.001) for the three factors (factor 1: 4.07?±?.47, factor 2: 3.72?±?.43, factor 3: 2.79?±?.83). Students in semester 10 reached significantly lower scores for factor 3 than students in their final year (p <?.05). CONCLUSIONS:The newly developed CRI-HT-S worked well for quantitative assessment of clinical reasoning indicators during history taking. Its three-factored structure helped to explore different aspects of clinical reasoning. Whether the CRI-HT-S has the potential to be used as a scale in objective structured clinical examinations (OCSEs) or in workplace-based assessments of clinical reasoning has to be investigated in further studies with larger student cohorts.

Dataset Information

Assessing residual reasoning ability in overtly non-communicative patients using fMRI.

Publications

Assessing residual reasoning ability in overtly non-communicative patients using fMRI.

Similar Datasets

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