skip to main content

Title: Topological analysis of differential effects of ketamine and propofol anaesthesia on brain dynamics
Research has found that the vividness of conscious experience is related to brain dynamics. Despite both being anaesthetics, propofol and ketamine produce different subjective states: we explore the different effects of these two anaesthetics on the structure of dynamic attractors reconstructed from electrophysiological activity recorded from cerebral cortex of two macaques. We used two methods: the first embeds the recordings in a continuous high-dimensional manifold on which we use topological data analysis to infer the presence of higher-order dynamics. The second reconstruction, an ordinal partition network embedding, allows us to create a discrete state-transition network, which is amenable to information-theoretic analysis and contains rich information about state-transition dynamics. We find that the awake condition generally had the ‘richest’ structure, visiting the most states, the presence of pronounced higher-order structures, and the least deterministic dynamics. By contrast, the propofol condition had the most dissimilar dynamics, transitioning to a more impoverished, constrained, low-structure regime. The ketamine condition, interestingly, seemed to combine aspects of both: while it was generally less complex than the awake condition, it remained well above propofol in almost all measures. These results provide deeper and more comprehensive insights than what is typically gained by using point-measures of complexity.
; ; ;
Award ID(s):
Publication Date:
Journal Name:
Royal Society Open Science
Page Range or eLocation-ID:
Sponsoring Org:
National Science Foundation
More Like this
  1. Jbabdi, Saad (Ed.)
    Whether the brain operates at a critical “tipping” point is a long standing scientific question, with evidence from both cellular and systems-scale studies suggesting that the brain does sit in, or near, a critical regime. Neuroimaging studies of humans in altered states of consciousness have prompted the suggestion that maintenance of critical dynamics is necessary for the emergence of consciousness and complex cognition, and that reduced or disorganized consciousness may be associated with deviations from criticality. Unfortunately, many of the cellular-level studies reporting signs of criticality were performed in non-conscious systems (in vitro neuronal cultures) or unconscious animals (e.g. anaesthetized rats). Here we attempted to address this knowledge gap by exploring critical brain dynamics in invasive ECoG recordings from multiple sessions with a single macaque as the animal transitioned from consciousness to unconsciousness under different anaesthetics (ketamine and propofol). We use a previously-validated test of criticality: avalanche dynamics to assess the differences in brain dynamics between normal consciousness and both drug-states. Propofol and ketamine were selected due to their differential effects on consciousness (ketamine, but not propofol, is known to induce an unusual state known as “dissociative anaesthesia”). Our analyses indicate that propofol dramatically restricted the size and duration ofmore »avalanches, while ketamine allowed for more awake-like dynamics to persist. In addition, propofol, but not ketamine, triggered a large reduction in the complexity of brain dynamics. All states, however, showed some signs of persistent criticality when testing for exponent relations and universal shape-collapse. Further, maintenance of critical brain dynamics may be important for regulation and control of conscious awareness.« less
  2. Abstract Sustained attention is a critical cognitive function reflected in an individual’s whole-brain pattern of functional magnetic resonance imaging functional connectivity. However, sustained attention is not a purely static trait. Rather, attention waxes and wanes over time. Do functional brain networks that underlie individual differences in sustained attention also underlie changes in attentional state? To investigate, we replicate the finding that a validated connectome-based model of individual differences in sustained attention tracks pharmacologically induced changes in attentional state. Specifically, preregistered analyses revealed that participants exhibited functional connectivity signatures of stronger attention when awake than when under deep sedation with the anesthetic agent propofol. Furthermore, this effect was relatively selective to the predefined sustained attention networks: propofol administration modulated strength of the sustained attention networks more than it modulated strength of canonical resting-state networks and a network defined to predict fluid intelligence, and the functional connections most affected by propofol sedation overlapped with the sustained attention networks. Thus, propofol modulates functional connectivity signatures of sustained attention within individuals. More broadly, these findings underscore the utility of pharmacological intervention in testing both the generalizability and specificity of network-based models of cognitive function.
  3. The purpose of this research paper is to understand how diverse students are incorporated into the social structure of a large enrollment first-year engineering design course. Despite previous work demonstrating the benefits of diverse individuals in engineering, little work has examined how diverse students are incorporated into the social networks that exist within engineering classrooms. Social interactions are one of the most influential sources for integration into communities of practice. Through understanding how students interact and the structure of these interactions, we can elucidate how the engineering community includes members of underrepresented populations. Previous social network analysis (SNA) studies have scrutinized student classroom interactions. These studies typically attempt to link classroom interactions to academic outcomes (i.e., grades). In this study, we start to shift the focus away from connecting student interactions to academic outcomes and examine how the structure of student interactions can encourage an inclusive environment in a formal engineering environment. SNA data was collected via an online survey (n = 502, 74% response rate) one month into the semester at a Western land-grant institution. The survey asked first-year engineering students to indicate with whom they had interacted using a pre-populated list of the class roster and open-ended questions.more »The number of students that were mentioned by a participant (out-degree) is interpreted as a proxy of their sociableness. Whereas, the number of times a student was mentioned by others (in-degree) is interpreted as popularity. We posit that in an inclusive network structure the social behaviors (i.e., in and out-degree) will be independent of students’ demographic characteristics (e.g., race and gender). Nonparametric hypothesis testing (i.e., Kruskal-Wallis and Dunn’s test) was used to investigate the effects of gender and race on both in and out-degree. Results indicate that the social structure of the first-year engineering community is inclusive of both gender and race. Specifically, results indicated no significant differences for in-degree based on measures of race and gender, for students who provided race and gender information. Out-degree was not significantly different based on race. However, women did demonstrate significantly higher out-degree scores (i.e., greater sociableness) than their peers. Building on previous SNA literature, the increased connections expressed by women may lead to increased learning gains or performance within engineering. Results indicated that the social structure of this first-year engineering course, as indicated by in-degree and out-degree, is not significantly different for underrepresented groups. This result begins to illustrate a more complex story than the existing literature has documented of engineering as an unwelcoming environment for underrepresented students. Future work will explore how these structures do or do not persist over time and how individuals develop attitudes towards diverse individuals as a result of these interactions. We hope that the results of this work will provide practical ways to improve engineering climate for underrepresented students.« less
  4. The image of the highly intelligent, pack-hunting raptor has become engrained in scientific literature and popular works alike. First proposed to explain the relatively common co-occurrence of the large-bodied iguanodontian Tenontosaurus tilletti and the wolf-sized Deinonychus antirrhopus from the Lower Cretaceous of NorthAmerica, a canid-like social hunting structure has become the standard depiction of dromaeosaurs in popular works over the last three decades. This reconstruction is, however, problematic largely due to the fact that highly coordinated hunting strategies are rarely observed in modern archosaurs. This has led to the alternative hypothesis that D. antirrhopus was more analogous to agonistic reptilian carnivores, like the Komodo dragon (Varanus komodoensis). Among the many differences between these two analogs is how social and asocial organisms rear their young, producing a diagnostic pattern based on the presence or absence of ontogenetic dietary changes. In order to test for dietary changes through growth, stable carbon and oxygen isotope (δ13C, δ18O)analysis was performed on tooth carbonate from small (<4.5 mm crown height) and large (>9 mm crown height) D. antirrhopus specimens from two microsites from the Lower Cretaceous Cloverly (Montana) and Antlers(Oklahoma) formations. Teeth from goniopholidid crocodylians and Tenontosaurus tilletti from the Cloverly Formation were also testedmore »for comparison. The results show that the Cloverly goniopholidids, like their modern counterparts, went through a distinct transition in diet as they grew. The smallest teeth were the relatively most enriched in13C (mean = −9.32‰; n= 5), the medium-sized teeth were the most-depleted in13C(mean = −10.56‰; n = 5), and the largest teeth were intermediate (mean = −10.12‰; n= 6). These factors are characteristic of the dietary shifts seen in modern asocial reptiles. D. antirrhopus showed this same pattern in tooth samples collected from both rock units, with small teeth being the more enriched in13C (mean = −8.99‰; n= 10) and the large teeth being more depleted in13C (mean = −10.38‰; n = 10). These differences suggest that juvenile and adult D. antirrhopus from both formations likely consumed different prey. Hypothetical food sources, such as T. tilletti, are close to the13C isotopic signal of adult D. antirrhopus, consistent with the hypothesized trophic relationship (predator-prey) between these two species. Juvenile D. antirrhopus had a diet more enriched in13C, likely composed of smaller-bodied, but trophically higher species. Taken together, these data add to the growing evidence that D. antirrhopus was not a complex social hunter by modern mammalian standards« less
  5. Networks provide a powerful formalism for modeling complex sys- tems, by representing the underlying set of pairwise interactions. But much of the structure within these systems involves interac- tions that take place among more than two nodes at once — for example, communication within a group rather than person-to- person, collaboration among a team rather than a pair of co-authors, or biological interaction between a set of molecules rather than just two. We refer to these type of simultaneous interactions on sets of more than two nodes as higher-order interactions; they are ubiquitous, but the empirical study of them has lacked a general framework for evaluating higher-order models. Here we introduce such a framework, based on link prediction, a fundamental prob- lem in network analysis. The traditional link prediction problem seeks to predict the appearance of new links in a network, and here we adapt it to predict which (larger) sets of elements will have fu- ture interactions. We study the temporal evolution of 19 datasets from a variety of domains, and use our higher-order formulation of link prediction to assess the types of structural features that are most predictive of new multi-way interactions. Among our results, we find thatmore »different domains vary considerably in their distri- bution of higher-order structural parameters, and that the higher- order link prediction problem exhibits some fundamental differ- ences from traditional pairwise link prediction, with a greater role for local rather than long-range information in predicting the ap- pearance of new interactions.« less