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Abstract Background The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Patients in a vegetative state are considered to lack awareness of themselves or the environment, but preserve respiratory and cardiac functions, as well as sleep/wake cycles. These patients are incapable of producing intentional responses to external stimulation and do not demonstrate any communication skills. Recent studies have shown that around 40% of vegetative state patients have been misdiagnosed. However, in recent years there has been a revolution in the tools that are available for the assessment of these patients. The objective of this article is to discuss the role of behavioural scales, as well as advanced neuroimaging techniques, in reducing the misdiagnosis rate. We review the scope and limitations of these approaches for the identification of overt and covert signs of awareness, and we present evidence to support a multimodal assessment that combines information from behavioural, structural, and functional imaging tools to ensure an accurate diagnosis for each individual patient. [ABSTRACT FROM AUTHOR]

Patients in a vegetative state are considered to lack awareness of themselves or the environment, but preserve respiratory and cardiac functions, as well as sleep/wake cycles. These patients are incapable of producing intentional responses to external stimulation and do not demonstrate any communication skills. Recent studies have shown that around 40% of vegetative state patients have been misdiagnosed. However, in recent years there has been a revolution in the tools that are available for the assessment of these patients. The objective of this article is to discuss the diagnostic role of behavioural scales, as well as advanced neuroimaging techniques in reducing the misdiagnosis rate. We review the scope and limitations of these approaches for the identification of overt and covert signs of awareness, and we present evidence to support a multimodal assessment that combines information from behavioural, structural, and functional imaging tools to ensure an accurate diagnosis for each individual patient. [ABSTRACT FROM AUTHOR]

Minimal or inconsistent behavioral responses to command make it challenging to accurately diagnose the level of awareness of a patient with a Disorder of consciousness (DOC). By identifying markers of mental imagery being covertly performed to command, functional neuroimaging (fMRI), electroencephalography (EEG) has shown that some of these patients are aware despite their lack of behavioral responsiveness. We report the findings of behavioral, fMRI, and EEG approaches to detecting command-following in a group of patients with DOC. From an initial sample of 14 patients, complete data across all tasks was obtained in six cases. Behavioral evaluations were performed with the Coma Recovery Scale--Revised. Both fMRI and EEG evaluations involved the completion of previously validated mental imagery tasks--i.e., motor imagery (EEG and fMRI) and spatial navigation imagery (fMRI). One patient exhibited statistically significant evidence of motor imagery in both the fMRI and EEG tasks, despite being unable to follow commands behaviorally. Two behaviorally non-responsive patients produced appropriate activation during the spatial navigation fMRI task. However, neither of these patients successfully completed the motor imagery tasks, likely due to specific motor area damage in at least one of these cases. A further patient demonstrated command following only in the EEG motor imagery task, and two patients did not demonstrate command following in any of the behavioral, EEG, or fMRI assessments. Due to the heterogeneity of etiology and pathology in this group, DOC patients vary in terms of their suitability for some forms of neuroimaging, the preservation of specific neural structures, and the cognitive resources that may be available to them. Assessments of a range of cognitive abilities supported by spatially-distinct brain regions and indexed by multiple neural signatures are therefore required in order to accurately characterize a patient's level of residual cognition and awareness. [ABSTRACT FROM AUTHOR]

Abstract Background Memory is one of the most impaired functions after traumatic brain injury (TBI). We used diffusion tensor imaging (DTI) to determine the structural basis of memory deficit. We correlated fractional anisotropy (FA) of the fasciculi connecting the main cerebral regions that are involved in declarative and working memory functions. Methods Fifteen patients with severe and diffuse TBI and sixteen healthy controls matched by age and years of education were scanned. The neuropsychological assessment included: Letter-number sequencing test (LNS), 2-back task, digit span (forwards and backwards) and the Rivermead profilet. DTI was analyzed by a tract-based spatial statics (TBSS) approach. Results Whole brain DTI analysis showed a global decrease in FA values that correlated with the 2-back d-prime index, but not with the Rivermead profile. ROI analysis revealed positive correlations between working memory performance assessed by 2-back d-prime and superior longitudinal fasciculi, corpus callosum, arcuate fasciculi and fornix. Declarative memory assessed by the Rivermead profile scores correlated with the fornix and the corpus callosum. Conclusions Diffuse TBI is associated with a general decrease of white matter integrity. Nevertheless deficits in specific memory domains are related to different patterns of white matter damage.

The specific neural bases of disorders of consciousness (DOC) are still not well understood. Some studies have suggested that functional and structural impairments in the default mode network may play a role in explaining these disorders. In contrast, others have proposed that dysfunctions in the anterior forebrain mesocircuit involving striatum, globus pallidus, and thalamus may be the main underlying mechanism. Here, we provide the first report of structural integrity of fiber tracts connecting the nodes of the mesocircuit and the default mode network in 8 patients with DOC. We found evidence of significant damage to subcortico-cortical and cortico-cortical fibers, which were more severe in vegetative state patients and correlated with clinical severity as determined by Coma Recovery Scale-Revised (CRS-R) scores. In contrast, fiber tracts interconnecting subcortical nodes were not significantly impaired. Lastly, we found significant damage in all fiber tracts connecting the precuneus with cortical and subcortical areas. Our results suggest a strong relationship between the default mode network - and most importantly the precuneus - and the anterior forebrain mesocircuit in the neural basis of the DOC.