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Ketamine-Medetomidine General Anesthesia Occurs With Alternation of Cortical Electrophysiological Activity Among High and Low Complex States

Anesthetic agents are known to induce a series of alterations in cortical electrophysiological activity, such as the rise of signature patterns, changes in statistical properties, and altered dynamic behavior of neural records. Plenty of methods can be used to trace and monitor these changes, among them complexity metrics demonstrated to have the power to discriminate states of distinct levels of awareness. There is a consensus that anesthetic drugs are capable of interfering with neural activities at different levels and time scales, being able to induce alterations both locally as well as on the spatiotemporal patterns throughout the whole cortex. However, it is still unclear how such changes in the complexity of cortical activity are supposed to occur, and experimental evidence is still needed. To this purpose, we have analyzed an ECoG records database of a Ketamine-Medetomidine anesthetic induction experiment in a non-human primate subject. The MDR-ECoG provided records of cortical activity with both high temporal and spatial resolution allied with extensive coverage of the cortical surface. The Permutation Entropy and the Fractal Dimension were employed to evaluate the complexity of the neural time series. The complexity of cortical activity was relatively constant during awakened conditions. The transition to unconsciousness occurred in a fast manner, requiring about 30 to 40 seconds for the first changes to take place. During general anesthesia, the complexity assumed a considerable variation at local levels and fluctuated without a defined period. On a global scale, the cortex dynamically alternated among high and low complex states. This study brings novel evidence of the effects of anesthetics on neural activity and cortical dynamics, complementing the actual scenario for the elucidation of anesthesia mechanisms in terms of circuits, pathways, and global brain functioning.

I. Introduction E lectrophysiological cortical records are known to exhibit highly complex patterns, and it is a fact that changes in levels of awareness, whether caused by anesthetic agents, epileptiform activity, or sleep, reflect in signals with characteristic patterns that are distinguished from those typically observed under alert conditions. Since electrophysiological activity signals contain relevant information about the physiological state of individuals, a variety of methods can be used to evaluate changes in behavior, patterns, and statistical properties of neural time series. In particular, when we are interested in making inferences about different levels of awareness, it is possible to highlight complexity-related metrics, which have proven to have the power to discriminate physiological states involving distinct levels of consciousness. Because of this, complexity metrics are even used in clinical medicine to monitor patients during procedures involving sedation and general anesthesia. In these applications and neuroscience ex-periments, most of the time, a reduced number of electrodes are used, thus giving information about changes that occur locally at certain cortical areas, without providing detailed information about what is happening in the cortex as a whole.
Since anesthetic agents can concomitantly interfere with local molecular environments, neuronal circuits in the thalamic nuclei, circuits widespread throughout the cortex, and also with the communication established between the thalamus and the cortex, anesthetic drugs are able not only to affect the activity of certain cortical regions but in fact can interfere with the dynamics of neural activities in the brain as a whole, at a systems level. In this manner, we assert that the elucidation of the spatiotemporal organization of the complexity of neural activity over extensive cortical areas, may bring new relevant information to complement the actual scenario, and contribute with novel experimental evidence for the comprehension of the effects of general anesthesia in terms of neural circuits, pathways, and global brain functioning.
The objective of the present research was to verify and describe how statistical properties associated with the complexity of cortical electrophysiological activity change as soon as an anesthetic induction agent is administered to a subject. Particularly verifying the changes in patterns and dynamics that occur along with the unfolding of the transition to unconsciousness, as well as the spatiotemporal organization of the cortical activity's complexity during general anesthesia.
For this objective, a database respective to an experiment that involved Ketamine-Medetomidine anesthetic induction in an old-world monkey was analyzed. In this database, electrophysiological neural activity was recorded by the use of a technique that offered simultaneously extensive coverage of cortical surfaces along with high spatial and temporal resolution. Two different complexitymetrics methods, the Fractal Dimension, and the Permutation Entropy were used to infer the complexity of the neural time series.
In this research, we have characterized the complexity of the electrophysiological neural activity in the awakened resting-state, Ketamine-Medetomidine general anesthesia, and also during the transition to induced unconsiousness. We have analyzed the complexity over distinct cortical regions at a local level, and also the spatiotemporal patterns established throughout the cortex at a systems level. Under resting-state conditions, the complexity of cortical activity demonstrated to be relatively constant along time, despite some events of reduced complexity that appeared and vanished quite frequently, taking place mainly over the temporal and occipital lobes. The transition to unconsciousness demonstrated to be quite fast, requiring about 30 to 40 seconds for the first remarkable alterations to take place. First, the complexity decreased at the occipital and temporal lobes, later diminished over the parietal and frontal lobes. During the transition, the central sulcus and areas nearby continued to display high complexity. We contemplated that the administration of the anesthetics promoted a novel specific dynamics and not a single overall decrease effect on the complexity of brain activity. Locally, the complexity assumed a higher variation and randomly fluctuated without having a definite period. During general induced anesthesia the whole cortical spatiotemporal patterns dynamically alternated among high and low complex states, the states of high complexity observed had some features that resembled those respective to the awakened resting-state, nonetheless, we verified that both conditions were distinguishable at all times.

I. Neural Records Database
In the present study, a database of cortical electrophysiological activity was analyzed. The database came from the laboratory of adaptive intelligence at the Riken Brain Science Institute, Japan. All surgical and experimental procedures were idealized and performed by the re-searchers of the corresponding institution. Experiments were approved by the Riken's scientific ethics committee following the experimental protocols ) and the recommendations of the Weatherall report: "The use of non-human primates in research". Detailed information regarding methodology, subjects and materials is available on (Nagasaka et al., 2011) and (http://neurotycho.org).
The electrophysiological activity data analyzed is respective to an experiment that involved anesthetic induction in a non-human primate subject of the species Macaca fuscata. The data recording technique adopted was the MDR-ECoG, which is considered to be one of the most advanced technologies available. This technique provided a large coverage of the cortical surface and offered concomitant high spatial (5 mm) and high temporal resolution (1 KHz). The animal subject had an array of 128 ECoG electrodes chronically implanted at the subdural space covering the lateral cortical surface of the right brain hemisphere, some electrodes were also implanted at frontal and occipital medial walls.
In the experiment, the macaque was blindfolded and restrained in an appropriate chair. Neural activity was recorded for approximately 10 minutes under these conditions. After that, a cocktail of Ketamine and Medetomidine was administered for the induction of general anesthesia; thereafter neural activity continued to be monitored for the next 25 minutes.

II.1 Permutation Entropy
For the calculation of the Permutation Entropy, we have used the algorithm presented and described in (Bandt and Pompe, 2002). For each of the 128 time series from the ECoG electrodes array, the Permutation Entropy was calculated serially over time throughout the experiment as a sliding window. For each calculation, 2000 points of the time series were used, equivalent to 2 seconds of recording of neural activity, with the order parameter of the Permutation Entropy m = 4, and the time delay t = 15.

II.2 Fractal Dimension
For each of the 128 time series from the ECoG electrodes array, the Fractal Dimension values were calculated serially over time as a sliding window. To decrease the number of measurements, the Fractal Dimension was calculated once every 2.5 seconds respective to the recording time of the experiment. Higuchi's algorithm (Higuchi, 1988) was used to calculate the Fractal Dimension. For each calculation, 1000 points of the time series were used (equivalent to 1 second of recording the neural activities), with the time interval parameter k = 100.

III. Statistical Analysis Wilcoxon Signed-Rank Test
In aiming to verify whether the decrease observed in the complexity during general anesthesia compared to the awake resting state conditions was statistically significant, the Wilcoxon signed-rank test was applied. The resulting p-values of the statistical test are shown in Table ·

IV. t-SNE Plots
We have defined the time-resolved vector states, as vectors containing as entries the values of complexity at a given time of each one of the 128 electrodes, resulting in 128-Dimensional vectors that were estimated serially over time throughout the experiment. For the permutation entropy, the time-resolved vector states were estimated at every 2.0 seconds of the recording experiment, and for the Fractal Dimension at every 2.5 seconds. The timeresolved vector states (128-D) were used as input features into the t-SNE algorithm (Van der Maaten and Hinton, 2008) implemented in the R-CRAN package Rtsne (Krijthe et al., 2018), with the parameters: perplexity = 30, exaggeration factor = 12, and the maximum number of interactions = 500. This analysis was independently performed for the Fractal Dimension and for the Permutation Entropy.

III. Results
In this research, we were able to trace the spatiotemporal patterns of the cortical electrophysiological activity's complexity from the macaque under study. The dynamic patterns were characterized in awakened resting-state conditions and Ketamine-Medetomidine general anesthesia. A substantial difference between these two states has been verified. The unfolding dynamics of the loss of consciousness have also been observed, and we were able to follow the alterations that occurred over specific cortical areas as well as in the cortex at a global level.
Two different methodologies were employed to estimate the complexity of neural time series: the Fractal Dimension and the Permutation Entropy. Although some distinctions were observed among the results from each methodology, in a broad sense the findings obtained were fairly equivalent, and we were able to draw the same conclusions from both approaches.

I. Awakened Resting State
By analyzing the figures of the Permutation Entropy (Figure · 1) and the Fractal Dimension (Figure · 6) along time throughout the anesthetic induction, we verified that during resting state conditions, the complexity of cortical activity did not present an expressive and remarkable variation, in general being considerably constant over time (see Figure · 1 and Figure · 6, the values obtained before the vertical red line at 10.5 minutes in both figures). Regarding the magnitude of the values, during the resting state, the Permutation Entropy varied among the range of ≈ 3.1 to 3.2 (see Figure · 1), and the Fractal Dimension among the range of ≈ 1.7 to 1.8 (see Figure · 6). We also noticed some differences in the dynamic behavior according to the position of the electrodes over the cortex. Among all electrodes, those positioned over the frontal lobe (electrodes A to L) were the ones that exhibited the lowest variation, whereas electrodes located over the occipital and temporal lobes (electrodes N to V) were more prone to display some variation (see Figure · 1 and Table · 1 for the Permutation Entropy; Figure · 6 and Table · 2 for the Fractal Dimension). By analyzing the values of complexity over the coordinates of the electrodes, we verified the spatiotemporal patterns respective to the complexity of neural activity over distinct cortical regions, as well as the behavior of the cortex at a system's level during the awakened resting-state conditions (see Figure · 3, and Figure · 8). We have noticed that the complexity of the cortical activity was approximately the same over the whole cortex, no particular region that stood out for presenting complexity intrinsically significantly higher or inferior all the time was verified. We observe in Figure · 3 and also in Figure · 8, that the general aspect and most frequent patterns consisted of the majority of the electrodes displaying a predominantly red color according to the gradient chart. Localized events characterized by a reduction in the complexity of cortical activity were quite common although, these consisted of events that constantly appeared and vanished, not being present all the time. These events occurred mainly at the occipital and temporal lobes (see Figure Figures), the complexity of the electrophysiological activity remained the same without presenting noticeable changes for approximately 1.5 to 2.0 minutes. After this time interval, we were able to contemplate an abrupt and expressive transition, which, due to its rapid occurrence, seemed to be consistent with a single-step process. The previously higher and approximately constant values presented a decrease and started to exhibit a considerably larger variation (see Figure ·  By analyzing the values of complexity over the coordinates of the electrodes, we could contemplate how distinct specialized areas, as well as the cortex at a systems level, behaved along with the transition (see Figure Figure · 9). Considering that the time interval between each Sub-Figure and its subsequent is 2.5 seconds, we thereby estimate that the change between the patterns occurred within approximately 30 to 40 seconds (see Figure · 9). We thus arrive at the same conclusion from both figures.
The unfolding of the transition over different cortical regions can be ascertained by observing the consecutive Sub-Figures of Figure · 9 respective to the Fractal Dimension. First, a substantial decrease in the Fractal Dimension values in the occipital, temporal and parietal areas occurred without a significant reduction in the electrodes of the frontal region, (see Figure · 9, Sub- Figures 23, 24, 28, 29, 31 and 32). Later on, the complexity of the electrodes located over frontal areas also started to decline, (see Figure · 9, 40,42,43 and 48). A remarkable feature verified along the transition was that electrodes located over the central sulcus and areas nearby showed a tendency to display higher complexity when compared to the rest of the frontal and parietal lobes (see Figure · 9, Sub- Figures 37 to 48). Another recurrent pattern observed was that both the central sulcus and the occipital lobe displayed a higher complexity in comparison with other areas of the cortex during the transition, (see Figure · 9, 43,44,45 and 46). All these changes observed on the spatiotemporal patterns contrast the features found during awaken conditions. However, the recurrent spatiotemporal patterns characteristic of the general anesthesia that are represented on  ) over time throughout the anesthetic induction, we have noticed that the first remarkable effects on the electrophysiological cortical activity complexity occurred within about 1.5 to 2.0 minutes after the administration of the anesthetics. After a few minutes following these first substantial changes, the dynamics of the complexity of cortical activity assumed a regime that prevailed during general anesthesia. It was observed on both Figure · 1 and Figure · 6, that the cortical activity's complexity started to assume a wider variation, and seemed to fluctuate without possessing a definite period, having the upper limits about the same as the values found during the resting state, and the magnitude of the lower values was much smaller. Specifically, the Permutation Entropy varied in the range of ≈ 2.2 to 3.2, and the Fractal Dimension in the interval of ≈ 1.3 to 1.8. By applying the Wilcoxon signed-rank test with a p-value of 5%, we confirmed that the general decrease observed on the magnitude values of complexity over all the electrodes of the ECoG matrix 1 was statistically significant on both Permutation Entropy and Fractal Dimension.
Examining the histograms (see Figure · 2 and Figure · 7) we can find a considerable distinction among the distributions of the two conditions. During general anesthesia, the distributions tended to be lower and substantially more widespread than during resting-state conditions. This divergence was markedly pronounced in the electrodes located over the frontal lobe.
When we analyze Figure · 1 and Figure · 6 that comprise the complexity of neural activity over time, we may have the impression that during general anesthesia, the complexity of each electrode fluctuated in a seemingly random manner. Although when we have plotted the complexity values over the coordinates of the electrodes by using a color gradient, a remarkable phenomenon has been observed. We have found that, during general anesthesia, the complexity of cortical activity alternates among high and low complex states. There were times when the majority of the electrodes presented reduced complexity and thus assumed a predominantly blue color. And there were periods in which most of the electrodes showed high complexity and had mainly red coloring, apparently resembling the patterns and features observed during alert resting-state conditions (see Figure · 5 and Figure · 10).
To visualize how the time-resolved complexity vector states (high dimensional 128-D, see methods section -IV) were spatially distributed, we have used the t-SNE algorithm (Van der Maaten and Hinton, 2008) to project them into a bidimensional map. We have verified that points respective to each experimental condition, awakened resting state, and general anesthesia positioned spread at distinct regions of the plane without mixing among themselves (see Figure · 11). We have verified these results in both complexity measures used, the Permutation Entropy and the Fractal Dimension. From these findings, we can conclude that re-garding the time-resolved complexity vector states, the awakened resting-state and general anesthesia compromise two distinct states, that are distinguishable from each other at all times. Although some patterns found during general anesthesia (see Figure · 5 and Figure · 6) seemed to resemble those found during alert conditions (see Figure · 3 and Figure · 8), they were in reality distinct.

IV. Conclusions
In the present research, we inferred the complexity of electrophysiological neural records of a database respective to a Ketamine-Medetomidine anesthetic induction experiment in a macaque subject chronically implanted with a dense ECoG electrodes array at the subdural space along the right brain hemisphere. We have inferred the dynamics of the complexity of the neural activity over distinct cortical areas and the spatial-temporal patterns established along the cortex, during awakened resting state and general anesthesia conditions. The unfolding of the transition to induced unconsciousness has also been followed. We have verified that during awakened resting-state conditions, the complexity is relatively uniform across the cortex, despite some events of localized reduction of complexity frequently occurring at the occipital and temporal lobes. We have found that the first remarkable changes in the complexity of neural activity occurred within about ≈ 1.5 to 2.0 minutes after the Ketamine-Medetomidine cocktail was administrated, and unrolled as a considerably rapid process that took about 30 to 40 seconds to succeed. During general anesthesia, at a local level, the complexity of neural activity assumed a remarkable higher variation having the maximum values about the same as those found during the resting state, and the lower values much smaller. The frontal region was the one that presented the most prominent alterations. Regarding the spatiotemporal patterns assumed by the cortex as a whole, we verified that during Ketamine-Medetomidine general anesthesia the cortex alternated among high and low complex states. Those high complex states displayed features that resembled the patterns found during the awakened resting-state conditions, nonetheless, they were still distinguishable at all times. In general terms, it was noted that in alert conditions, on the majority of the electrodes, the Permutation Entropy of the neural records presented relatively small variation over time. After the administration of the cocktail of anesthetics, the Permutation Entropy remained about the same for about 1.5 to 2.0 minutes, then abrupt changes were verified. It was noticed that the complexity of the neural records assumed a considerable greater variation, being the upper values about the same as those found during alert conditions, and the bottom values were fairly lower. It was also possible to observe that not all electrodes behaved the same, evidencing that the effects of the anesthetics on electrophysiological activities present some variation throughout the cortex.    Figure, it is possible to visualize the characteristic pattern of the complexity in awakened resting-state conditions. It is noticeable that under these conditions the majority of the electrodes present a Permutation Entropy value of around 3.0 and over, and the whole cortex did not display an expressive variation over time, as the Sub-Figures display one main similar pattern. Nonetheless, it is possible to observe that electrodes located in the occipital regions showed some tendency to variation (see 20,21,and 30). Considering the cortex as a whole, the region that was less prone to variation was the frontal lobe.  Figure, it is possible to visualize the first alterations that happened in the patterns of the awake resting-state following the administration of the anesthetics. Primarily some regions of the temporal and occipital lobes presented a reduction while frontal electrodes did not display expressive alterations (see Sub- Figures 10, 14, 15, 16, and 19). Thereafter, from Sub- Figure 26 onwards, a reduction in the electrodes of the frontal lobe was verified. A remarkable characteristic observed during these first moments of the transition was that the central sulcus and nearby areas showed a tendency to exhibit high Permutation Entropy (see Sub- Figures 15 to 36). Sub- Figures 8 and 9 had patterns characteristic of awake conditions, whereas Sub- Figures 28 and 29 already displayed substantially different features. Considering that the time interval among consecutive Sub-Figures is 2.0 seconds, we infer that the first abrupt changes on the complexity of the electrophysiological activity of the cortex as a whole took place within about 30 to 40 seconds. It is noticeable that the cortex alternates between high complexity states that resemble those observed during alert conditions (see 5,10,16,24,27 and 29), and low complexity states in which the vast majority of cortical areas display reduced Permutation Entropy values (see 6,9,11,12,14,17,20,22,23,25,26,28 and 30). It was also observed that even at periods of low complexity there was still a tendency for the temporal lobe and the central sulcus to assume slightly higher values than the rest of the cortex (see 7,12,15,18,19,and 26), being a recurrent pattern that appeared with a relative frequency over general anesthesia conditions, although not always present throughout all the time. Brain activity started to be recorded in awakening resting-state conditions. The anesthetic drugs cocktail was administrated at 10.5 minutes, this event is indicated in each Sub-Figure by a vertical red line. The Fractal Dimension was calculated at every 2.5 seconds throughout the experiment, being this the time interval among each point and its subsequent one. In this Figure, it is possible to observe the dynamics of the Fractal Dimension throughout the anesthetic induction experiment. During awakened alert conditions, there was a tendency to remain approximately constant around ≈ 1.7 to 1.8 in most electrodes. Within about 1.5 to 2.0 minutes after the anesthetic agents administration, the Fractal Dimension values presented an abrupt change, it decreased and started to assume a considerably larger variation than in alert conditions, apparently fluctuating randomly between a minimum of approximately 1.3 and a maximum of about 1.8. It was noticeable that the behavior of the Fractal Dimension was not the same over different cortical regions, evidencing that the effects of the anesthetics on the electrophysiological activity are not the same throughout the whole cortex.    Figure, it is possible to visualize the characteristic patterns of the complexity in awakened resting-state conditions. It is noticeable that under these conditions the majority of the electrodes present Fractal Dimension values of around 1.6 and over. It is possible to observe that electrodes located at the occipital regions showed some tendency to display variation (see 10,11,12,19,29,and 30).  Figure, it is possible to visualize the first alterations that happened in the patterns of the awake resting-state condition following the administration of the anesthetics. Primarily some regions of the temporal and occipital lobes presented a reduction while frontal electrodes did not display expressive alterations (see 30,31,and 32). Thereafter, a reduction in the electrodes of the frontal lobe was verified (see 40,42,43,46,48,50,51,and 53  It is possible to visualize the characteristic patterns as well as the dynamics of the Fractal Dimension during the state of general anesthesia, it is noticeable that the cortex alternates between high complexity states that appear similar to those observed during alert conditions (see 6,14,17,23,29,32,35,38,and 41 ) and low complexity states in which the vast majority of cortical areas display reduced Fractal Dimension values (see 4,10,13,15,18,19,21,24,25,27,28,30,31,33,34,36,37,39,40,and 42 ). It was also observed that even at periods of low complexity there was still a tendency for the occipital-frontal and central sulcus to assume slightly higher values than the rest of the cortex (see 8,9,11,12,17,19,20,22,26,and 27).
That was a recurrent pattern that has shown up with a relative frequency over general anesthesia conditions, although not always present throughout all the time.  Figure B) onto a bi-dimensional map by the use of the t-SNE algorithm. Alert resting-state conditions are indicated in blue, and general anesthesia in red, see legends. By examining this Figure it is verified that in both methods, the Permutation Entropy and the Fractal Dimension, the projections of the alert state (indicated in blue) and general anesthesia (indicated in red) occupy distinct regions of the map. This result thus evidences that concerning the complexity of the electrophysiological cortical activity, alert resting-state and general anesthesia constitute two different states and are distinguishable at every moment.