Single-trial decoding of auditory novelty responses facilitates the detection of residual consciousness

Detecting residual consciousness in unresponsive patients is a major clinical concern and a challenge for theoretical neuroscience. To tackle this issue, we recently designed a paradigm that dissociates two electro-encephalographic (EEG) responses to auditory novelty. Whereas a local change in pitch automatically elicits a mismatch negativity (MMN), a change in global sound sequence leads to a late P300b response. The latter component is thought to be present only when subjects consciously perceive the global novelty. Unfortunately, it can be difficult to detect because individual variability is high, especially in clinical recordings. Here, we show that multivariate pattern classifiers can extract subject-specific EEG patterns and predict single-trial local or global novelty responses. We first validate our method with 38 high-density EEG, MEG and intracranial EEG recordings. We empirically demonstrate that our approach circumvents the issues associated with multiple comparisons and individual variability while improving the statistics. Moreover, we confirm in control subjects that local responses are robust to distraction whereas global responses depend on attention. We then investigate 104 vegetative state (VS), minimally conscious state (MCS) and conscious state (CS) patients recorded with high-density EEG. For the local response, the proportion of significant decoding scores (M=60%) does not vary with the state of consciousness. By contrast, for the global response, only 14% of the VS patients' EEG recordings presented a significant effect, compared to 31% in MCS patients' and 52% in CS patients'. In conclusion, single-trial multivariate decoding of novelty responses provides valuable information in non-communicating patients and paves the way towards real-time monitoring of the state of consciousness.

A multimodal approach to the assessment of patients with disorders of consciousness

Unlike other neurological conditions, the heterogeneous pathology linked to disorders of consciousness currently excludes a distinction between the vegetative and minimally conscious states based upon pathological presentation. The clinical assessment is therefore made on the basis of the patient's clinical history and exhibited behaviour. This creates a particular challenge for the clinician who has to decide whether a certain behaviour, which might be inconsistent or incomplete, reflects a conscious or an unconscious process. In an alarmingly high number of cases, identified during clinical audit, this decision process has been shown to be particularly fallible. The behavioural assessment is not only highly subjective, but also dependent upon the ability of the patient to move or speak; it is the only way someone can demonstrate they are aware. To address this problem we propose a multimodal approach, which integrates objective tools, such as electrophysiology and functional brain imaging, with traditional behavioural scales. Together this approach informs the clinical decision process and resolves many of the dilemmas faced by clinicians interpreting solely behavioural indices. This approach not only provides objective information regarding the integrity of residual cognitive function, but also removes the dependency on the patient to move or speak by using specially designed paradigms that do not require a motor output in order to reveal awareness of self or environment. To demonstrate this approach we describe the case of BW, who sustained a traumatic brain injury seven months prior to investigation. BW was admitted to a five-day assessment programme, which implemented our multimodal approach. On behavioural assessment BW demonstrated evidence of orientation and visual pursuit. However, he showed no response to written or verbal command, despite holding command cards and scanning text. Electrophysiology confirmed that he retained a preserved neural axis supporting vision and hearing, and suggested some evidence that he was able to create a basic memory trace. A hierarchical fMRI auditory paradigm suggested he was able to perceive sound and speech, but revealed no evidence of speech comprehension or ability to respond to command. This was corroborated in the visual modality using a hierarchical paradigm demonstrating that he was able to perceive motion, objects and faces, but retained no evidence of being able to respond to command. We briefly review work by other teams advocating the use of brain imaging and electrophysiology and discuss the steps that are now required in order to create an international standard for the assessment of persons with impaired consciousness after brain injury.

White matter hyperintensities are significantly associated with cortical atrophy in Alzheimer's disease

BACKGROUND AND OBJECTIVE

Methodological variability in the assessment of white matter hyperintensities (WMH) in dementia may explain inconsistent reports of its prevalence and impact on cognition. We used a method of brain MRI segmentation for quantifying both tissue and WMH volumes in Alzheimer's disease (AD) and examined the association between WMH and structural and cognitive variables.

METHODS

A consecutive series of 81 patients meeting NINCDS-ADRDA criteria for probable AD was studied. Nineteen healthy volunteers of comparable age served as the control group. Patients had a complete neurological and neuropsychological evaluation, and a three dimensional MRI was obtained. Images were segmented into grey matter, white matter, and cerebrospinal fluid. WMH were edited on segmented images, and lobar assignments were based on Talairach coordinates.

RESULTS

Mild and moderate to severe AD patients had significantly more WMH than controls (p<0.05). WMH preferentially involved the frontal lobes (70%), were inversely correlated with grey matter cortical volume (R(2) = 0.23, p<0.001), and were significantly associated with vascular risk factors and with a worse performance on memory tasks.

CONCLUSION

Objective measurements of tissue volumes in AD demonstrated that WMH are significantly related to cortical atrophy and neuropsychological impairment.