Increased interictal synchronicity of respiratory related brain pulsations in epilepsy

Abstract

Respiratory brain pulsations have recently been shown to drive electrophysiological brain activity in patients with epilepsy. Furthermore, functional neuroimaging indicates that respiratory brain pulsations have increased variability and amplitude in patients with epilepsy compared to healthy individuals. To determine whether the respiratory drive is altered in epilepsy, we compared respiratory brain pulsation synchronicity between healthy controls and patients. Whole brain fast functional magnetic resonance imaging was performed on 40 medicated patients with focal epilepsy, 20 drug-naïve patients and 102 healthy controls. Cerebrospinal fluid associated respiratory pulsations were used to generate individual whole brain respiratory synchronization maps, which were compared between groups. Finally, we analyzed the seizure frequency effect and diagnostic accuracy of the respiratory synchronization defect in epilepsy. Respiratory brain pulsations related to the verified fourth ventricle pulsations were significantly more synchronous in patients in frontal, periventricular and mid-temporal regions, while the seizure frequency correlated positively with synchronicity. The respiratory brain synchronicity had a good diagnostic accuracy (ROC_AUC = 0.75) in discriminating controls from medicated patients. The elevated respiratory brain synchronicity in focal epilepsy suggests altered physiological effect of cerebrospinal fluid pulsations possibly linked to regional brain water dynamics involved with interictal brain physiology.

Keywords: Brain physiology; brain pulsations; epilepsy; fast fMRI; respiratory synchronization.

Figure 1.

(a) Cerebrospinal fluid (CSF) flow modulation by respiratory intrathoracic pressure changes (blue arrow). During inhalation the venous return from the brain increases (long white arrow) and CSF flows (yellow) towards the brain to counterbalance the blood volume loss. During exhalation, CSF returns from the brain and venous return declines, which gradually inflates cortical veins (short white arrow). (b) CSF convection (yellow) in the brain tissue is driven by arterial (red) pulsations (cardiac) into periarterial influx channels (light blue surrounding red) and into the interstitium via AQP4 water channels (pink). In the veins (blue) the counterbalancing CSF/venous pulsations (inhalation/exhalation) may move water into perivenous efflux channels (light blue surrounding blue). (c) The mean correlation map of respiratory BELT vs. MREG data (representative signals and raw image data shown) from 30 healthy subjects determined in a region of interest (white area) placed on the fourth ventricle, yielding MREG data that tracks the respiratory phase with high precision. (d) 30 healthy subject's respiration rate in breaths per minute (bpm) determined from respiratory belt and MREG indicates a high correlation coefficient of 0.97 (Pearson, p < 0.0001). Additionally, the differences between the groups (PWE, DN, HC) respiratory frequencies were compared and (e) The individual examples of extracted MREG respiratory signals (mean signal of white area from c) were used for each subject to calculate respiratory pulse synchronization at each voxel across the whole brain as individual Resp_sync maps (n = 162). Representative maps from one PWE case and one HC, with single brain voxel signals and their Resp_sync values against the fourth ventricle.

Figure 2.

Distributions of mean positive (a) and negative (b) Resp_sync maps in each group calculated from maps on the right of the figure. Despite an overlap between the three similar distributions (HC: yellow, DN: orange, PWE: red), the differences between group means were highly significant (p < 0.0001) in both positive and negative Resp_sync values. Additionally, histograms show an increase of Resp_sync values as a function of diagnosis occurrence and (c) Mean positive and negative Resp_sync correlation lag maps. Despite visual dissimilarities, there were no statistical differences between these maps.

Figure 3.

(a) Synchronization of positive respiratory related brain pulsations (Resp_sync) was significantly (p < 0.05) higher in PWE compared to HC group. Significant increases were brain-wide, covering key functional structures, e.g., the upper brain stem respiratory pneumotaxic center and midbrain, along with the hippocampi and pallida. Additionally, the cingulate gyrus and temporal lobes clearly showed increased Resp_sync in the PWE group. (b) With negative synchronization Resp_sync values there were significant increases especially in the temporal and occipital structures and (c) The seizure frequency single group analysis showed that the Resp_sync values increase in the caudate, putamina, superior frontal gyrus and cingulate gyrus areas as a function of seizure density (p < 0.05).

Figure 4.

For ROC analysis, group-level differences in Resp_sync values of significantly different areas/voxels from the hippocampi were used. (a) The AUC between HC and PWE was 0.745 (p < 0.0001) and (b) with HC against DN the AUC was 0.677 (p = 0.0125). The same analysis was performed with previously published coefficient of variation and spectral power data with the addition of gathered subjects included to the previous population. Here, (c) coefficient of variation provided an AUC of 0.678 between HC and PWE (p = 0.001) and with (d) power data AUC was 0.664 (p = 0.002).