Differential Effects of Deep Sedation with Propofol on the Specific and Nonspecific Thalamocortical Systems

How general anesthetics suppress consciousness is not fully understood. Recent conceptual approaches focus on the effect of anesthetics on integrated information as the defining property of human consciousness.1,2According to a theory, the brain’s capacity for information integration3,4is determined by the repertoire of its states (information) and the causal interaction of its elements (integration). A reduction of either component, for example, due to anesthesia, could result in a reduction of the level of consciousness. Accordingly, general anesthetics exert a preferential effect on integrative processes of the brain, as opposed to simply a block of sensory transmission or reactivity during reduced consciousness.1As we have proposed, under general anesthesia, information in the brain may be “received but not perceived.”5It has also been suggested that the thalamocortical system plays a central role in information integration in the brain.6–8In particular, the two major divisions of the thalamus, the specific relay nuclei and the more diffusely projecting “nonspecific” nuclei, may collaborate to accomplish this task,9–11with the specific system responsible for the transmission and encoding of sensory and motor information and the nonspecific system engaged in the control of cortical arousal and temporal conjunction of information across distributed cortical areas.11These considerations emphasize the importance of the nonspecific thalamocortical system in information integration and raise the possibility that its dysfunction may be a primary, and possibly unitary, mechanism of anesthetic-induced unconsciousness.Previous studies implied a critical involvement of the nonspecific (intralaminar) thalamic nuclei in the loss and recovery of consciousness in patients in vegetative12or minimally conscious state13and in anesthetized animals.14One of these studies also emphasized the importance of intralaminar thalamocortical functional connectivity in the recovery of consciousness.12However, the role of nonspecific thalamic nuclei under general anesthesia in humans has not been investigated. Therefore, the goal of this work was to examine the effect of propofol sedation on functional connectivity of the specific and nonspecific thalamocortical systems.We chose to investigate thalamocortical functional connectivity using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in healthy human volunteers. Functional connectivity has been defined as the temporal correlation of BOLD signals among spatially remote regions of the brain15and is currently a favored approach of neuroimaging. To learn about functional connectivity changes upon loss of consciousness, we targeted an anesthetic depth at which responses to verbal commands and auditory verbal memory were suppressed, but auditory cortical sensory reactivity was preserved. We hypothesized that, under this condition, nonspecific thalamocortical connectivity would be disrupted more than specific thalamocortical connectivity, consistent with a failure of cortical integration but not sensory information transmission. Functional connectivity was evaluated in four conditions (wakeful baseline, light sedation, deep sedation, and recovery) while volunteers listened to word lists that were later used to assess their implicit memory. Seed regions used for functional connectivity analysis were manually defined within the specific (medial dorsal, ventral lateral, ventral posterior, and other) and nonspecific (centromedian and parafascicular) thalamic nuclei. We found that propofol sedation indeed produced distinct changes in the functional connectivity of the two divisions of the thalamocortical system, consistent with their postulated roles in information and integration in specific states of human consciousness.Eight volunteers of both sexes (four men and four women; aged 24–42 yr; body mass index < 25) provided written informed consent to participate in this study. Experimental protocols were approved by the Institutional Review Board of the Medical College of Wisconsin (Milwaukee, WI). The study participants were native English speakers from Medical College of Wisconsin communities, free of drug administration, and with no history of neurological or psychiatric conditions or structural brain abnormalities.All participants were made to lie in the scanner and instructed to listen to and try to remember (encode) a distinct set of 40 high-frequency English words (nouns) presented during each of the four experimental sessions in four different states of consciousness: wakeful baseline, light sedation, deep sedation, and recovery (fig. 1A). The rate of word presentation was approximately seven words per minute with a random interstimulus interval during each of the approximately 6-min scanning sessions. BOLD time course data were obtained from the entire duration of word presentation without interruption.16Participants were informed that their recall/recognition performance of words heard during each of the four experimental sessions would be assessed after scanning. The experimental sessions were separated by approximately 15 min for experimental preparations.The anesthetic agent, propofol, was administered by a bolus followed by a target-controlled continuous infusion (STANPUMP).17We targeted plasma concentration of 1 μg/ml for light sedation and 2 μg/ml for deep sedation. The higher dose for deep sedation was chosen to achieve the desired endpoints of unresponsiveness to verbal commands, intended to induce a global loss of memory.18A behavioral assessment of the level of consciousness was performed right before the start of each fMRI scan. Study participants were asked to respond to questions like “how are doing?,”“take a deep breath,” and “can you squeeze my hand?” by the anesthesiologist through a speaker (the one used in the task or at the bedside of the scanner between recording sessions). In general, during light sedation, participants had lethargic responses to the questions. During deep sedation, participants showed no response to verbal commands. Once a desired sedative state was achieved, the next fMRI scan was initiated. During the scan, the sedation level was maintained by computer-controlled infusion with the preset plasma concentration. Immediately after the scanning of the last sedated state, the administration of propofol was stopped. On the confirmation that participants had recovered responsiveness to verbal commands, the last scanning session defined as “recovery” was initiated. Every participant had two intravenous catheters, one for propofol administration and another for the withdrawal of blood samples for measuring propofol plasma concentration. However, due to a problem with red blood cell lysis, the actually plasma propofol concentrations could not be determined in this study. The order of light and deep sedation was counterbalanced in participants, with four participants receiving the low dose before a high dose and the other four receiving them in a reversed order. Standard American Society of Anesthesiologists monitoring was performed during the experiment, including electrocardiogram, noninvasive blood pressure cuff, pulse oximetry, and end-tidal carbon dioxide gas analysis.The auditory verbal material was presented using a headphone set (Koss Corporation, Milwaukee, WI) designed to work in the magnetic resonance scanner environment. The word lists were matched for the maximum number of letters, frequency of usage in English, concreteness, and imageability (Paivio, Yuille, and Madigan norms for 925 nouns).19Approximately 20–30 min after the completion of all the experiments (after study participants had been taken out of the scanner), all participants completed a free-recall test followed by a forced-choice recognition test. The time separation between the memory tests and the last scan was intended to neutralize the primacy and recency effects, which occur when the recognition memory test is administered immediately after the stimulus presentations. In the forced-choice recognition test, participants were presented auditorily 320 words, of which 160 words were what they had heard during the experiment and the other 160 words were foils or distractors. Participants were required to press a button if they thought they had already heard the word and another button if the word was new. Participants were instructed to make a decision regarding every presented word as quickly as possible. Each participant’s residual memory to words heard during each of the four experimental sessions was assessed by a few performance indices: the percentage of recalled words, the recognition ratio versus chance, and the discriminability index (d’ ). Of these, the value of d’ , computed from the hit (correct recognition) rate and false-alarm rate, provides a criterion-independent measure of the internal response of participants (i.e. , regardless of how conservative or liberal participants are in making decisions).20A d’ equal to zero indicates same hit and false-alarm rates, and a d’ value significantly greater than zero indicates a higher hit than a false-alarm rate (a d’ value of three represents minimal overlap between the probability of the occurrence of hit and false alarm).Imaging acquisition was performed using a 1.5 Tesla GE Signa scanner (General Electric Medical Systems, Milwaukee, WI) with a locally designed gradient and radio frequency coil. Potential head movements were minimized using a chin support system developed at the Medical College of Wisconsin. Functional echo-planar images were obtained using whole-brain imaging in the sagittal plane during each task session (repetition time, 2000 ms; echo time, 40 ms; thickness, 6 mm; in-plane resolution, 3.75 × 3.75 mm; 22 slices; flip angle, 90°; field of view, 24 cm; matrix size, 64 × 64). High-resolution spoiled-gradient–recalled anatomical images were always acquired after the third experimental session for each participant (repetition time, 24 ms; echo time, 5 ms; slice thickness, 1.2 mm; flip angle, 40°; field of view, 24 cm; matrix size, 256 × 128).The specific and nonspecific thalamic nuclei to be used as seeds for functional connectivity analysis were determined in the coronal plane editorof each individual’s high-resolution spoiled-gradient–recalled images after transformation into the standard Talairach space. Specifically, the nonspecific seed mainly consisted of the intralaminar nuclei, including the centromedian and parafascicular thalamic nuclei located at the ventromedial corners of the left and right thalami (fig. 1B). Anatomical references that could be used to enhance the accuracy of defining the nonspecific thalamic seed included the lateral maximum stretch point of the third ventricle, red nucleus, and the interthalamic adhesion. These referential structures were identifiable in the high-resolution anatomical images of each participant by properly adjusting the brightness and contrast of image pixels. The remaining parts of the thalamus were used as an aggregate for seeding the specific thalamic connections (fig. 1C).Imaging data analysis was conducted using the software packages Analysis of Functional NeuroImages (AFNI, Bethesda, MD) and Matlab (The MathWorks, Natick, MA). The high-resolution anatomical images were first manually transformed into the standard Talairach space, followed by coregistering the functional data to the Talairach space in 2-mm cubic voxels (adwarp in AFNI). Subsequent data preprocessing included despiking, detrending (3dDetrend in AFNI, using the Legendre polynomials with an order of three), and motion correction (3dvolreg in AFNI, obtaining three translational and three rotational parameters for each image). The first four points of the voxel time series of each section were discarded to reduce the transient effects. To minimize contaminating signals from the white matter and the cerebrospinal fluid, we extracted the average BOLD signal from these brain structures manually identified across each individual’s anatomical images. We then constructed eight regressors using the signals corresponding to the six motion parameters (obtained during the volume registration), white matter, and cerebrospinal fluid signals for the subsequent analysis.After data preprocessing, the event-related fMRI time series of all task sessions were analyzed by a general linear regression (3dDeconvolve in AFNI). The regression analysis takes into consideration the eight regressors representing the contribution of noise artifacts from the motion, white matter, and cerebrospinal fluid. The residual signals were considered representative of the task-induced BOLD responses with the potential contamination minimized. In the next step, the averaged voxel time courses of the predefined specific and nonspecific thalamic seed regions were used separately to perform in of the The × was to the obtained correlation to the of the was performed using a to for the of the specific and nonspecific thalamocortical functional connections across defined brain we the obtained functional connectivity with a brain provided in The provides a that the brain into anatomical regions in a in the Talairach corresponding voxel of each is taken as a measure of thalamocortical functional connections in each state of consciousness. We defined two A and , to the changes in the voxel of thalamocortical functional connectivity by the wakeful states and recovery) to deep sedation and the recovery to wakeful , , and the voxel of the specific or nonspecific thalamocortical functional connections in the states of wakeful baseline, deep sedation, and the analysis of the at the low propofol we could a distinct of responses in the was with which is at low anesthetic during the experiments and memory tests a of at the low propofol of the in the state of consciousness and the at this the imaging data obtained at the low propofol dose were not fully referential we provided the thalamocortical connectivity obtained at the low propofol dose in These be with in the of connectivity were evaluated by tests followed by transformation to considered at value than after correction for in AFNI, a of voxels of 2-mm cubic in the Talairach were The both voxel probability and to the probability of from the frequency of in each The of this is that regions of or to occur noise has of a to The was obtained on a of the specific and nonspecific thalamic functional connections in human participants in the state, which we a level of about the we performed a test on the functional connectivity analysis for each state of consciousness. The test a of corresponding to eight of participants and test, participant between the of different participants produced responses to verbal commands during wakeful baseline, light sedation, and These responses were during deep sedation. The memory tests showed that participants could a percentage of words heard in the scanner at light sedation and recovery but not during deep sedation not The auditory forced-choice recognition tests performed the scanner showed the same Participants were to words from foils heard at (d’ , light sedation (d’ , and recovery (d’ , 1.5 but not the words heard during deep sedation (d’ , regarding the task and the performance we the to the condition, auditory verbal mainly BOLD in temporal and regions and BOLD responses in the and the During deep sedation, of the were suppressed, in a few brain in the temporal at the auditory In the BOLD in the and the participants behavioral brain were to a to at functional showed distinct within the two thalamic divisions (fig. In the condition, specific and nonspecific connections were in the the and and the (fig. and In both thalamocortical the from the ventral to the of the The functional connectivity of the and was more in the nonspecific than in the specific In functional connectivity of the specific thalamus in the and temporal in the and temporal was more than that with the nonspecific The specific thalamocortical connections also in the the nonspecific connections Functional connections in the of the the and were in both thalamocortical also which the correlation obtained by across the two thalamocortical different changes in functional connectivity in deep sedation as with wakeful (fig. The of connections by the number of significantly voxels was reduced in both the specific and the nonspecific across the However, the nonspecific connections were more suppressed, a few of connectivity in the and in the specific thalamic connectivity were more in of both the brain regions and the voxel During the specific and nonspecific connections were to a to that in the with baseline, the of connectivity in both was in recovery (fig. changes of functional connectivity of the two thalamic divisions across wakeful baseline, deep sedation, and recovery were by the number of significantly voxels for anatomical regions that of the major structures of the brain (fig. The that during deep sedation, specific connectivity was reduced (fig. and nonspecific connectivity was reduced (fig. The functional connections were then in the voxel data from all regions that the reduction from wakeful to deep sedation was significantly < through a in the nonspecific system than in the specific system (fig. the in functional connectivity from deep sedation to recovery and from to recovery were both significantly < and < in the nonspecific and than in the specific system and (fig. also the of thalamic functional connections (fig. The of the specific and nonspecific thalamocortical connections equal number of voxels in the left and right However, in deep sedation, the of connectivity was significantly < in the left than in the right with a left versus right ratio voxel of in the specific system and in the nonspecific During the of connectivity was in the nonspecific thalamocortical system, but not in the specific These that the of the nonspecific thalamocortical connectivity with the loss and of consciousness than that of the specific thalamocortical of the changes of functional connectivity in the two thalamocortical we the two A and each brain A the reduction in the of voxels during deep sedation to of wakeful and the in connectivity between recovery and wakeful The of both from to a of from to regions with the specific and nonspecific are then identified by the two as two in a (fig. The that brain regions in the specific and nonspecific are a in their changes in connectivity during sedation and Specifically, the brain regions in the nonspecific thalamic functional connectivity a greater during sedation and a greater during recovery than the brain regions in the specific the was if the volume of the specific thalamic seed the specific system to propofol than the nonspecific system that was on a significantly seed To investigate this connectivity analysis was conducted on a reduced volume of the specific Specifically, we the specific seed in a that the number of voxels left in the specific seed was to that in the nonspecific seed for each The the obtained with the specific seed which the functional connectivity of the reduced specific into the of consciousness and of general anesthesia each the of anesthetics considered in the light of the of consciousness, and In the of the information integration of human that the two of consciousness, information and are by the specific and nonspecific divisions of the thalamocortical that anesthetics may exert a effect on these as they suppress consciousness. that at a level of propofol deep sedation by cortical sensory specific thalamocortical is the nonspecific thalamocortical is and after recovery of is for the role of the thalamocortical system in integrative information in the and of thalamocortical thalamic divisions across cortical structures the thalamocortical in a and for integrative for the of conscious with the and of the thalamus, from brain that the thalamocortical system is in the and of the state of into the mechanism of anesthetic-induced have the of thalamocortical information within the relay the failure of nonspecific thalamocortical functional connections in the conscious thalamocortical connections that from the matrix of the thalamus are in the intralaminar nuclei and have been in conscious to that in the central thalamus by in were in anesthesia, conducted the sensory Subsequent studies showed that a in the thalamus loss of or to intralaminar nuclei wakeful in anesthetized in one in a minimally conscious anesthetic effect on the nonspecific thalamus is suggested by a from to in the by The 40 of thalamocortical has been as a of anesthetics suppress versus in cortical has been that are for conscious that also that conscious changes in are a of cortical or thalamic anesthetic is not general from that during anesthetic sedation, the reactivity of the sensory , the to is integrative of the is is consistent with a effect of anesthetics on the functional of the thalamocortical the specific thalamic system that and sensory information is in anesthesia, the nonspecific thalamic system that temporal and integration of information in the disrupted during regarding the role of thalamocortical connectivity in anesthetic of consciousness have a of example, the studies by and a of the thalamocortical connectivity, thalamocortical connectivity during propofol sedation. The of may be to the of propofol on the specific and nonspecific thalamic is that a of thalamic nuclei may be In the two nonspecific (intralaminar) thalamic nuclei were considered as a seed they a from the anatomical images obtained at 1.5 the specific nuclei were with no into and other nuclei. is that thalamic relay nuclei may and sensory a more of thalamocortical functional connectivity at higher magnetic field may result of study was that during deep sedation, thalamocortical functional connectivity in a number of brain These regions included the as of the specific system (fig. and the temporal and as of the nonspecific system (fig. The mechanism these connectivity is currently is that a or response to the by we significantly of propofol on the specific and nonspecific thalamocortical functional the of reduction in the two which are to consciousness, be determined from the study. this information would a study with anesthetic at a In other the of functional connectivity would have to be as the experimental , anesthetic drug other magnetic field of the scanner the and the study the of propofol on the two thalamic divisions at at a deep sedative to all other fMRI are by the that they the mass the experimental included a memory task and auditory that may have the connectivity as with in the assessment of functional connectivity during sensory is not without be in the study by we also showed the connectivity of the same of analysis with task effect out of the and changes of the thalamocortical connectivity across the different states of consciousness showed as with the from data task in we a of thalamic functional connections in deep sedation, in the nonspecific is consistent with the of structures in verbal and the in the of functional connections in both thalamic divisions during recovery to was would have an recovery within the of the study due to a drug as are by example, the of connectivity from showed a upon the of consciousness from brain in the a at the of consciousness as by the for these in connectivity is they may the of a in may also be to the of in general the of of and from a more for consciousness from an anesthetized state, as opposed to from wakeful A study that be fully by but an property of the central system to in the state of as is that the of consciousness in recovery more than its at wakeful We that after anesthesia is a that on as the brain to we a effect of propofol on the specific and nonspecific thalamocortical functional The are consistent with the roles of the two thalamic divisions in information and integration as conditions for consciousness. also the that the nonspecific thalamocortical system may an role in the of and and of the for for to the study. also of and of Medical College of Milwaukee, for