Multidimensional cognitive evaluation of patients with disorders of consciousness using EEG: A proof of concept study

Abstract

The use of cognitive evoked potentials in EEG is now part of the routine evaluation of non-communicating patients with disorders of consciousness in several specialized medical centers around the world. They typically focus on one or two cognitive markers, such as the mismatch negativity or the P3 to global auditory regularity. However it has become clear that none of these markers in isolation is at the same time sufficiently specific and sufficiently sensitive to be taken as the unique gold standard for diagnosing consciousness. A good way forward would be to combine several cognitive markers within the same test to improve evaluation. Furthermore, given the diversity of lesions leading to disorders of consciousness, it is important not only to probe whether a patient is conscious or not, but also to establish a more general and nuanced profile of the residual cognitive capacities of each patient using a combination of markers. In the present study we built a unique EEG protocol that probed 8 dimensions of cognitive processing in a single 1.5 h session. This protocol probed variants of classical markers together with new markers of spatial attention, which has not yet been studied in these patients. The eight dimensions were: (1) own name recognition, (2) temporal attention, (3) spatial attention, (4) detection of spatial incongruence (5) motor planning, and (6,7,8) modulations of these effects by the global context, reflecting higher-level functions. This protocol was tested in 15 healthy control subjects and in 17 patients with various etiologies, among which 13 could be included in the analysis. The results in the control group allowed a validation and a specific description of the cognitive levels probed by each marker. At the single-subject level, this combined protocol allowed assessing the presence of both classical and newly introduced markers for each patient and control, and revealed that the combination of several markers increased diagnostic sensitivity. The presence of a high-level effect in any of the three tested domains distinguished between minimally conscious and vegetative patients, while the presence of low-level effects was similar in both groups. In summary, this study constitutes a validated proof of concept in favor of probing multiple cognitive dimensions to improve the evaluation of non-communicating patients. At a more conceptual level, this EEG tool can help achieve a better understanding of disorders of consciousness by exploring consciousness in its multiple cognitive facets.

Keywords: ADAN, Anterior Directing Attention Negativity; Attention; CNV, contingent negative variation; Cognition; DOC, disorders of consciousness; Disorders of consciousness; EEG; Event related potentials; LRP, lateralized readiness potential; MCS, minimally conscious state; Non-communicating patients; VS, vegetative state.

Figures

Graphical abstract

Supplementary Fig. 1

False negatives in controls argue for a pragmatic threshold of pclust 

Supplementary Fig. 2

Individual topographies of the CNV and modulation of CNV.

Supplementary Table 1

Details of the patients included in the analysis.

Supplementary Table 2

Details of the patients discarded from the analysis.

Fig. 1

Experimental design and behavioral results in controls. (A) Graphical summary of the experimental design: an auditory cue (either the subject's own name, another name or a non vocal control) was played on the left or on the right, followed by a target «beep» on the same side (congruent) or on the other side (incongruent). The control participants were asked to press a button with the hand corresponding with the target side, the patients were instructed to imaging squeezing their hand on the target's side. (B) Behavioral results for the control group: the left panel shows average reaction times to the target across participants for correct responses, in the non-predictive context (50% of congruent trials, dotted lines) and in the predictive context (75% of congruent trials, plain lines) as a function of the cue type (x axis) and spatial congruence between the cue and the target (blue for congruent, red for incongruent). Error bars represent ± the standard error of the mean (SEM). The right panel shows the results on accuracy, with the same conventions.

Fig. 2

Own name perception. (A) ERP contrast between trials where the cue was the participant's own name versus the other name for the control group. The left panel shows the topographies evoked by the other name, the own name, and the difference at the time of peak of the group effect (350 ms). The right panel shows the time course of the GFP of the own name versus other name difference for the control group. (B) source reconstruction of the effect for the control group at the time of the peak (350 ms), and time course of reconstructed activity in the posterior ventral cingulate cortex (Destrieux parcellation). (C and D) Topographies and GFP time course of the effect for one individual control (C) and for one individual patient (D). For all GFP time courses, periods where the cluster-level p-value was below 0.075 are indicated under the curve by red to yellow lines with the following convention: red for pclust t-test with no correction).

Fig. 3

Temporal attention (CNV) and contextual modulation. (A–D) CNV effect in the control group. (A) shows the evolution of the topography evoked by the cue, irrespective of its type, in the 200 ms preceding the target's expected time (at 550 ms). The frontal negativity characteristic of the CNV increases with time both in the unpredictive and predictive context, but with a steeper slope in the predictive context, as can be seen on the topographies of the difference. (B) Accordingly, the GFP gradually increased between the cue and the target, with a steeper slope in the predictive context (75% of congruent trials). Corrected p-value of the contextual effect (GFP of the difference between 75 and 50% context) are indicated on this graph, with the same convention as in Fig. 2. (C) Group averaged topographies of the slope (nV/ms) estimated using a linear regression of the voltage of each electrode between 300 ms and 100 ms before target for the 75% context, the 50% context and for the difference 75 minus 50%. Electrodes showing a significant negative slope are highlighted (p 

Fig. 4

Spatial attention (ADAN) and contextual modulation. (A–D) Effect of cue side in the non-predictive context (50%). (A) GFP time course of the effect of cue side (right panel) and corresponding topographies at 300 ms (left panel) for the control group. (B) Source reconstruction for the control group at 300 ms (left panel) and lateralization of the reconstructed activity in premotor cortices towards the future target's side (premotor activity ipsilateral minus contralateral to the future target's side) when the cue is on the same side as the future target (congruent, blue) or on the other side (incongruent, red). The premotor cortices correspond to the left and right middle frontal gyri of Destrieux parcellation. (C–D) Topographies and time course of the effect of cue side in an individual control (C) and an individual patient (D). Time of the topographies is indicated with an arrow on the corresponding GFP time course. (E–H) Modulation of the effect of cue side by the predictive context in the control group (E–F) and in the two individuals (G–H). Conventions for statistical significance as in Fig. 2.

Fig. 5

Local and global incongruence detection. (A–D) Effect of cue-target incongruence in the non-predictive context (50%), reflecting local incongruence detection (A) GFP time course of the effect of cue-target congruence (right panel) and corresponding topographies at 480 ms (left panel) for the control group. (B) Source reconstruction of the effect for the control group at 480 ms (left panel) and activity in the Inferior Frontal Sulcus (IFS, Destrieux) in the congruent and incongruent conditions. (C–D) Topographies and time course of the effect in an individual control (C) and an individual patient (D). (E–H) Interaction between context and cue-target congruence. (E) In the control group, incongruent trials were processed differently in the predictive versus non-predictive context, while congruent trials were processes similarly in the two contexts, reflecting global incongruence detection. (F) In source reconstruction this effect could be seen for example in the middle posterior part of the anterior cingulated cortex (ACC). (G–H) Topographies and time course of the effect in an individual control (G) and an individual patient (H). None of the patients showed both the local and global incongruence effect, hence different individual patients were chosen to illustrate these two effects. Conventions for statistical significance as in Fig. 2. In (E) right panel, the cluster shown in grey had a corrected p value of 0.25.

Fig. 6

Motor planning (LRP). (A) Effect of target side in the control group, mostly reflecting a lateralized readiness potential (LRP). Topographies of the LRP at 230 ms are shown on the left panel. The time course of the GFP is shown on the right. (B) Source reconstruction of the target left minus right difference in the control group at 230 ms (left panel) and time course of the activity in the left and right motor cortex and SMA. Left and Right motor cortex were selected using the Destrieux parcellation (left and right precentral gyri). For selecting the supplementary motor areas (SMAs), we used the left and right paracentral regions from the Desikan-Killiany parcellation, the Destrieux parcellation being less precise in this region. (C-D) Topographies and time course of the effect in an individual control (C) and an individual patient (D). Conventions for statistical significance as in Fig. 2.

Fig. 7

EEG cognitive charts. (A) Average statistical scores for the MCS + Conscious group and the VS group over the 8 cognitive dimensions tested represented on a radar/spider plot. On this graph, the average scores in the control group were set to 100%, and the scores in the other groups were normalized according to this reference. (B) Bayes Factors in favor of hypothesis 1 (MCS > VS) over hypothesis 0 (MCS = VS) and conversely (BF10 and BF01, with BF10 = 1/BF01) on the different cognitive dimensions. The dotted lines denote the value beyond which there is positive evidence in favor of one of the hypothesis (BF > 3) according to Raftery's terminology (Raftery, 1995) (C) Cognitive chart of each individual, without normalization.