The effect of propofol on effective brain networks

Objective: We compared the effective networks derived from Single Pulse Electrical Stimulation (SPES) in intracranial electrocorticography (ECoG) of awake epilepsy patients and while under general propofol-anesthesia to investigate the effect of propofol on these brain networks. Methods: We included nine patients who underwent ECoG for epilepsy surgery evaluation. We performed SPES when the patient was awake (SPES-clinical) and repeated this under propofol-anesthesia during the surgery in which the ECoG grids were removed (SPES-propofol). We detected the cortico-cortical evoked potentials (CCEPs) with an automatic detector. We constructed two effective networks derived from SPES-clinical and SPES-propofol. We compared three network measures (indegree, outdegree and betweenness centrality), the N1-peak-latency and amplitude of CCEPs between the two effective networks. Results: Fewer CCEPs were observed during SPES-propofol (median: 6.0, range: 0–29) compared to SPES-clinical (median: 10.0, range: 0–36). We found a significant correlation for the indegree, outdegree and betweenness centrality between SPES-clinical and SPES-propofol (respectively r s = 0.77, r s = 0.70, r s = 0.55, p &lt; 0.001). The median N1-peak-latency increased from 22.0 ms during SPES-clinical to 26.4 ms during SPES-propofol. Conclusions: Our findings suggest that the number of effective network connections decreases, but network measures are only marginally affected. Significance: The primary network topology is preserved under propofol.</p

The effect of propofol on effective brain networks

Objective: We compared the effective networks derived from Single Pulse Electrical Stimulation (SPES) in intracranial electrocorticography (ECoG) of awake epilepsy patients and while under general propofol-anesthesia to investigate the effect of propofol on these brain networks. Methods: We included nine patients who underwent ECoG for epilepsy surgery evaluation. We performed SPES when the patient was awake (SPES-clinical) and repeated this under propofol-anesthesia during the surgery in which the ECoG grids were removed (SPES-propofol). We detected the cortico-cortical evoked potentials (CCEPs) with an automatic detector. We constructed two effective networks derived from SPES-clinical and SPES-propofol. We compared three network measures (indegree, outdegree and betweenness centrality), the N1-peak-latency and amplitude of CCEPs between the two effective networks. Results: Fewer CCEPs were observed during SPES-propofol (median: 6.0, range: 0–29) compared to SPES-clinical (median: 10.0, range: 0–36). We found a significant correlation for the indegree, outdegree and betweenness centrality between SPES-clinical and SPES-propofol (respectively rs = 0.77, rs = 0.70, rs = 0.55, p < 0.001). The median N1-peak-latency increased from 22.0 ms during SPES-clinical to 26.4 ms during SPES-propofol. Conclusions: Our findings suggest that the number of effective network connections decreases, but network measures are only marginally affected. Significance: The primary network topology is preserved under propofol

Dynamical neural network reconstruction based on stimulation data

Single-pulse electrical stimulation (SPES) during clinical intracranial electrocorticography (iEEG) monitoring allows active probing of epileptogenic tissue. Two electrodes are stimulated, and the responses at other electrodes are recorded.These responses show physiological early responses (ERs) and more epileptogenic delayed responses (DRs). Earlier, we have demonstrated that neural mass models also produce and explain these responses. Here we propose to combine neural masses to create individualized neural mass networks reproducing the measured responses.We first show a dynamical inventory of small interacting neural masses using simulations and bifurcation analysis. Here we vary parameters related to intrinsic excitability, connectivity strength and background input. Second, we fit networks of small artificial topology and four real patient networks changing those parameters. We find that the ERs are nearly all reproduced. For the DRs, we can fit them in the small networks but to a lesser extent for the patient data. The resulting models may be helpful to explore the effect of stimulation protocols and surgery

Detailed view on slow sinusoidal, hemodynamic oscillations on the human brain cortex by Fourier transforming oxy/deoxy hyperspectral images

Slow sinusoidal, hemodynamic oscillations (SSHOs) around 0.1 Hz are frequently seen in mammalian and human brains. In four patients undergoing epilepsy surgery, subtle but robust fluctuations in oxy- and deoxyhemoglobin were detected using hyperspectral imaging of the cortex. These SSHOs were stationary during the entire 4 to 10 min acquisition time. By Fourier filtering the oxy- and deoxyhemoglobin time signals with a small bandwidth, SSHOs became visible within localized regions of the brain, with distinctive frequencies and a continuous phase variation within that region. SSHOs of deoxyhemoglobin appeared to have an opposite phase and 11% smaller amplitude with respect to the oxyhemoglobin SSHOs. Although the origin of SSHOs remains unclear, we find indications that the observed SSHOs may embody a local propagating hemodynamic wave with velocities in line with capillary blood velocities, and conceivably related to vasomotion and maintenance of adequate tissue perfusion. Hyperspectral imaging of the human cortex during surgery allow in-depth characterization of SSHOs, and may give further insight in the nature and potential (clinical) use of SSHOs

Detailed view on slow sinusoidal, hemodynamic oscillations on the human brain cortex by Fourier transforming oxy/deoxy hyperspectral images

Slow sinusoidal, hemodynamic oscillations (SSHOs) around 0.1 Hz are frequently seen in mammalian and human brains. In four patients undergoing epilepsy surgery, subtle but robust fluctuations in oxy- and deoxyhemoglobin were detected using hyperspectral imaging of the cortex. These SSHOs were stationary during the entire 4 to 10 min acquisition time. By Fourier filtering the oxy- and deoxyhemoglobin time signals with a small bandwidth, SSHOs became visible within localized regions of the brain, with distinctive frequencies and a continuous phase variation within that region. SSHOs of deoxyhemoglobin appeared to have an opposite phase and 11% smaller amplitude with respect to the oxyhemoglobin SSHOs. Although the origin of SSHOs remains unclear, we find indications that the observed SSHOs may embody a local propagating hemodynamic wave with velocities in line with capillary blood velocities, and conceivably related to vasomotion and maintenance of adequate tissue perfusion. Hyperspectral imaging of the human cortex during surgery allow in-depth characterization of SSHOs, and may give further insight in the nature and potential (clinical) use of SSHOs

Evoked versus spontaneous high frequency oscillations in the chronic electrocorticogram in focal epilepsy

Objective: Spontaneous high frequency oscillations (HFOs; ripples 80-250. Hz, fast ripples (FRs) 250-500. Hz) are biomarkers for epileptogenic tissue in focal epilepsy. Single pulse electrical stimulation (SPES) can evoke HFOs. We hypothesized that stimulation distinguishes pathological from physiological ripples and compared the occurrence of evoked and spontaneous HFOs within the seizure onset zone (SOZ) and eloquent functional areas. Methods: Ten patients underwent SPES during 2048. Hz electrocorticography (ECoG). Evoked HFOs in time-frequency plots and spontaneous HFOs were visually analyzed. We compared electrodes with evoked and spontaneous HFOs for: percentages in the SOZ, sensitivity and specificity for the SOZ, percentages in functional areas outside the SOZ. Results: Two patients without spontaneous FRs showed evoked FRs in the SOZ. Percentages of evoked and spontaneous HFOs in the SOZ were similar (ripples 32:33%, p = 0.77; FRs 43:48%, p = 0.63), but evoked HFOs had generally a lower specificity (ripples 45:69%, p = 0.02; FRs 83:92%, p = 0.04) and higher sensitivity (ripples 85:70%, p = 0.27; FRs 52:37%, p = 0.05). More electrodes with evoked than spontaneous ripples were found in functional (54:30%, p = 0.03) and 'silent' areas (57:27%, p = 0.01) outside the SOZ. Conclusions: SPES can elicit SOZ-specific FRs in patients without spontaneous FRs, but activates ripples in all areas. Significance: SPES is an alternative for waiting for spontaneous HFOs, but does not warrant exclusively pathological ripples