Yan Chen,Xiangyue Xiao,Zhicai Dong,Junhua Ding,Sara Cruz,Ming Zhang,Yuhan Lu,Nai Ding,Charlène Aubinet,Steven Laureys,Haibo Di
{"title":"Clinical diagnostic and prognostic value of residual language learning ability in patients with disorders of consciousness.","authors":"Yan Chen,Xiangyue Xiao,Zhicai Dong,Junhua Ding,Sara Cruz,Ming Zhang,Yuhan Lu,Nai Ding,Charlène Aubinet,Steven Laureys,Haibo Di","doi":"10.1523/jneurosci.1684-24.2025","DOIUrl":null,"url":null,"abstract":"Recent research suggests that the detection of preserved cognitive function can assist in the diagnosis and prognosis of patients with disorders of consciousness (DoC). This study investigates EEG signals as indicators of neural activity associated with the processing of transitional probabilities during a learning paradigm in patients with DoC. By examining the sensitivity to transitional probabilities across levels of consciousness, we aim to assess the potential value of this indicator in clinical diagnosis and prognosis.We collected EEG recordings from 51 DoC patients (10 female) and 26 healthy controls (9 female). EEG activity was recorded while participants listened to artificial vocabulary speech sequences before and after the learning phase. Inter-trial phase coherence (ITPC) was used to examine differences in neural responses in different learning phases.Results showed that minimally conscious patients showed a significant increase in the word-tracking response after the learning phase, similar to healthy controls. Moreover, their learning-mediated word-rate ITPC difference correlated significantly with their Coma Recovery Scale-Revised score and 6-month outcome. However, these correlations were absent in unresponsive wakefulness syndrome patients. Crucially, differences in vocabulary ITPC before and after the learning phase effectively discriminated between healthy controls and patients, as well as between minimally conscious and unresponsive wakefulness syndrome patients. Combining EEG indicators with clinical performance accurately predicted patients' prognosis.In conclusion, the language learning paradigm has the potential to contribute to both diagnosis and prognosis in this challenging population, thereby significantly reducing prognostic uncertainty in medical decision-making and benefiting the rehabilitation of DoC patients.Significance Statement This study explores the electroencephalogram sensitivity to changes in transitional probabilities during a learning paradigm, and its relationship to diagnosis and prognosis in patients with disorders of consciousness (DoC). Our results demonstrated that minimally conscious patients exhibited a significant increase in inter-trial phase coherence values at word frequencies after the learning phase, similar to healthy controls, suggesting retained language ability. In contrast, patients with unresponsive wakefulness syndrome did not show such improvements. Combining electroencephalogram indicators with clinical assessments in a predictive model could improve the accuracy of diagnosis and prognosis of patients. In sum, this objective measurement of brain responses could reduce the prognostic uncertainty in clinical decision making and better guide the care and rehabilitation of DoC patients.","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":"418 1","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1523/jneurosci.1684-24.2025","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Recent research suggests that the detection of preserved cognitive function can assist in the diagnosis and prognosis of patients with disorders of consciousness (DoC). This study investigates EEG signals as indicators of neural activity associated with the processing of transitional probabilities during a learning paradigm in patients with DoC. By examining the sensitivity to transitional probabilities across levels of consciousness, we aim to assess the potential value of this indicator in clinical diagnosis and prognosis.We collected EEG recordings from 51 DoC patients (10 female) and 26 healthy controls (9 female). EEG activity was recorded while participants listened to artificial vocabulary speech sequences before and after the learning phase. Inter-trial phase coherence (ITPC) was used to examine differences in neural responses in different learning phases.Results showed that minimally conscious patients showed a significant increase in the word-tracking response after the learning phase, similar to healthy controls. Moreover, their learning-mediated word-rate ITPC difference correlated significantly with their Coma Recovery Scale-Revised score and 6-month outcome. However, these correlations were absent in unresponsive wakefulness syndrome patients. Crucially, differences in vocabulary ITPC before and after the learning phase effectively discriminated between healthy controls and patients, as well as between minimally conscious and unresponsive wakefulness syndrome patients. Combining EEG indicators with clinical performance accurately predicted patients' prognosis.In conclusion, the language learning paradigm has the potential to contribute to both diagnosis and prognosis in this challenging population, thereby significantly reducing prognostic uncertainty in medical decision-making and benefiting the rehabilitation of DoC patients.Significance Statement This study explores the electroencephalogram sensitivity to changes in transitional probabilities during a learning paradigm, and its relationship to diagnosis and prognosis in patients with disorders of consciousness (DoC). Our results demonstrated that minimally conscious patients exhibited a significant increase in inter-trial phase coherence values at word frequencies after the learning phase, similar to healthy controls, suggesting retained language ability. In contrast, patients with unresponsive wakefulness syndrome did not show such improvements. Combining electroencephalogram indicators with clinical assessments in a predictive model could improve the accuracy of diagnosis and prognosis of patients. In sum, this objective measurement of brain responses could reduce the prognostic uncertainty in clinical decision making and better guide the care and rehabilitation of DoC patients.
期刊介绍:
JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles