Brain Map of Intrinsic Functional Flexibility in Anesthetized Monkeys and Awake Humans

Emerging neuroimaging studies emphasize the dynamic organization of spontaneous brain activity in both human and non-human primates, even under anesthesia. In a recent study, we were able to characterize the heterogeneous architecture of intrinsic functional flexibility in the awake, resting human brain using time-resolved analysis and a probabilistic model. However, it is unknown whether this organizational principle is preserved in the anesthetized monkey brain, and how anesthesia affects dynamic and static measurements of spontaneous brain activity. To investigate these issues, we collected resting-state functional magnetic resonance imaging (fMRI) datasets from 178 awake humans and 11 anesthetized monkeys (all healthy). Our recently established method, a complexity measurement (i.e., Shannon entropy) of dynamic functional connectivity patterns of each brain region, was used to map the intrinsic functional flexibility across the cerebral cortex. To further explore the potential effects of anesthesia, we performed time series analysis and correlation analysis between dynamic and static measurements within awake human and anesthetized monkey brains, respectively. We observed a heterogeneous profile of intrinsic functional flexibility in the anesthetized monkey brain, which showed some similarities to that of awake humans (r = 0.30, p = 0.007). However, we found that brain activity in anesthetized monkeys generally shifted toward random fluctuations. Moreover, there is a negative correlation between nodal entropy for the distribution of dynamic functional connectivity patterns and static functional connectivity strength in anesthetized monkeys, but not in awake humans. Our findings indicate that the heterogeneous architecture of intrinsic functional flexibility across cortex probably reflects an evolutionarily conserved aspect of functional brain organization, which persists across levels of cognitive processing (states of consciousness). The coupling between nodal entropy for the distribution of dynamic functional connectivity patterns and static functional connectivity strength may serve as a potential signature of anesthesia. This study not only offers fresh insight into the evolution of brain functional architecture, but also advances our understanding of the dynamics of spontaneous brain activity

Isoflurane-Induced Burst Suppression Increases Intrinsic Functional Connectivity of the Monkey Brain

Animal functional magnetic resonance imaging (fMRI) has provided key insights into the physiological mechanisms underlying healthy and diseased brain states. In non-human primates, resting-state fMRI studies are commonly conducted under isoflurane anesthesia, where anesthetic concentration is used to roughly infer anesthesia depth. However, within the recommended isoflurane concentration range (1.00–1.50%), the brain state can switch from moderate anesthesia characterized by stable slow wave (SW) electroencephalogram (EEG) signals to deep anesthesia characterized by burst suppression (BS), which is electrophysiologically distinct from the resting state. To confirm the occurrence rate of BS activity in common setting of animal fMRI study, we conducted simultaneous resting-state EEG and fMRI experiments on 16 monkeys anesthetized using 0.80–1.30% isoflurane, and detected BS activity in two of them. Datasets either featured with BS or SW activity from these two monkeys were analyzed to investigate the intrinsic functional connectivity (FC) patterns during BS. In datasets with BS activity, we observed robust coupling between the BS pattern (the binary alternation between burst and suppression activity in EEG signal) and filtered BOLD signals in most brain areas, which was associated with a non-specific enhancement in whole brain connectivity. After eliminating the BS coupling effect by regressing out the BS pattern, we detected an overall increase in FC with a few decreased connectivity compared to datasets with SW activity. These affected connections were preferentially distributed within orbitofrontal cortex, between orbitofrontal and prefrontal/cingulate/occipital cortex, and between temporal and parietal cortex. Persistence of the default mode network and recovery of thalamocortical connections were also detected under deep anesthesia with BS activity. Taken together, the observed spatially specific alterations in BS activity induced by isoflurane not only highlight the necessity of EEG monitoring and careful data preprocessing in fMRI studies on anesthetized animals, but also advance our understanding of the underlying multi-phased mechanisms of anesthesia

The emerging role of the FKBP5 gene polymorphisms in vulnerability-stress model of schizophrenia: further evidence from a Serbian population

Increased reactivity to stress is observed in patients with schizophrenia spectrum disorders and their healthy siblings in comparison with the general population. Additionally, higher levels of neuroticism, as a proposed psychological measure of stress sensitivity, increase the risk of schizophrenia. HPA axis dysregulation is one of the possible mechanisms related to the vulnerability–stress model of schizophrenia, and recent studies revealed a possible role of the functional genetic variants of FK506-binding protein 51 (FKBP5) gene which modulate activity of HPA axis. The purpose of the present study was to investigate impact of FKBP5 on schizophrenia in Serbian patients and to explore relationship between genetic variants and neuroticism by using the case–sibling–control design. In 158 subjects, we measured psychotic experiences, childhood trauma and neuroticism. Nine single-nucleotide polymorphisms (rs9295158, rs3800373, rs9740080, rs737054, rs6926133, rs9380529, rs9394314, rs2766533 and rs12200498) were genotyped. The genetic influence was modeled using logistic regression, and the relationship between genetic variants and neuroticism was assessed by linear mixed model. Our results revealed genetic main effect of FKBP5 risk alleles (A allele of rs9296158 and T allele of rs3800373) and AGTC “risk” haplotype combination (rs9296158, rs3800373, rs9470080 and rs737054, respectively) on schizophrenia, particularly when childhood trauma was set as a confounding factor. We confirmed strong relationship between neuroticism and psychotic experiences in patients and siblings and further showed relationship between higher levels of neuroticism and FKBP5 risk variants suggesting potential link between biological and psychosocial risk factors. Our data support previous findings that trauma exposure shapes FKBP5 impact on schizophreni

Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P \u3c 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies

Modular Functional-Metabolic Coupling Alterations of Frontoparietal Network in Schizophrenia Patients

Background: Brain functional dysconnectivity, as well as altered network organization, have been demonstrated to occur in schizophrenia. Brain networks are increasingly understood to exhibit modular community structures, which provides advantages in robustness and functional adaptivity. The frontoparietal network (FPN) serves as an important functional module, and metabolic and functional alterations in the FPN are associated with the pathophysiology of schizophrenia. However, how intra-modular biochemical disruptions lead to inter-modular dysfunction of the FPN, remains unclear. In this study, we aim to investigate alterations in the modular functional-metabolic coupling of the FPN, in patients with schizophrenia.Methods: We combined resting-state functional magnetic resonance imaging (rs-fMRI) and magnetic resonance spectroscopy (MRS) technology and acquired multimodal neuroimaging data in 20 patients with schizophrenia and 26 healthy controls. For the MRS, the dorsolateral prefrontal cortex (DLPFC) region within the FPN was explored. Metabolites including gamma aminobutyric acid (GABA), N-aspart-acetyl (NAA) and glutamate + glutamine (Glx) were quantified, using LCModel software. A graph theoretical approach was applied for functional modular parcellation. The relationship between inter/intra-modular connectivity and metabolic concentration was examined using the Pearson correlation analysis. Moreover, correlations with schizophrenia symptomatology were investigated by the Spearman correlation analysis.Results: The functional topological network consisted of six modules in both subject groups, namely, the default mode, frontoparietal, central, hippocampus, occipital, and subcortical modules. Inter-modular connectivity between the frontoparietal and central modules, and the frontoparietal and the hippocampus modules was decreased in the patient group compared to the healthy controls, while the connectivity within the frontoparietal modular increased in the patient group. Moreover, a positive correlation between the frontoparietal and central module functional connectivity and the NAA in the DLPFC was found in the healthy control group (r = 0.614, p = 0.001), but not in the patient group. Significant functional dysconnectivity between the frontoparietal and limbic modules was correlated with the clinical symptoms of patients.Conclusions: This study examined the links between functional connectivity and the neuronal metabolic level in the DLPFC of SCZ. Impaired functional connectivity of the frontoparietal areas in SCZ, may be partially explained by a neurochemical-functional connectivity decoupling effect. This disconnection pattern can further provide useful insights in the cognitive and perceptual impairments of schizophrenia in future studies

Anterior limb of the internal capsule tractography: relationship with capsulotomy outcomes in obsessive-compulsive disorder.

Funder: Guangci Professorship ProgramOBJECTIVES: Surgical procedures targeting the anterior limb of the internal capsule (aLIC) can be effective in patients with selected treatment-refractory obsessive-compulsive disorder (OCD). The aLIC consists of white-matter tracts connecting cortical and subcortical structures and show a topographical organisation. Here we assess how aLIC streamlines are affected in OCD compared with healthy controls (HCs) and which streamlines are related with post-capsulotomy improvement. METHODS: Diffusion-weighted MRI was used to compare white-matter microstructure via the aLIC between patients with OCD (n=100, 40 women, mean of age 31.8 years) and HCs (n=88, 39 women, mean of age 29.6 years). For each individual, the fractional anisotropy (FA) and streamline counts were calculated for each white-matter fibre bundle connecting a functionally defined prefrontal and subcortical region. Correlations between tractography measures and pre-capsulotomy and post-capsulotomy clinical outcomes (in obsessive-compulsive, anxiety and depression scores 6 months after surgery) were assessed in 41 patients with OCD. RESULTS: Hierarchical clustering dendrograms show an aLIC organisation clustering lateral and dissociating ventral and dorsal prefrontal-thalamic streamlines, findings highly relevant to surgical targeting. Compared with HCs, patients with OCD had lower aLIC FA across multiple prefrontal cortical-subcortical regions (p<0.0073, false discovery rate-adjusted). Greater streamline counts of the dorsolateral prefrontal-thalamic tracts in patients with OCD predicted greater post-capsulotomy obsessive-compulsive improvement (p=0.016). In contrast, greater counts of the dorsal cingulate-thalamic streamlines predicted surgical outcomes mediated by depressive and anxiety improvements. CONCLUSIONS: These findings shed light on the critical role of the aLIC in OCD and may potentially contribute towards precision targeting to optimise outcomes in OCD

Approximations and abstractions for reasoning about machine arithmetic

Safety-critical systems rely on various forms of machine arithmetic to perform their tasks: integer arithmetic, fixed-point arithmetic or floating-point arithmetic. The problem with machine arithmetic is that it can exhibit subtle differences in behavior compared to the ideal mathematical arithmetic, due to fixed-size representation in memory. Failure of safety-critical systems is unacceptable, because it can cost lives or huge amounts of money, time and effort. To prevent such incidents, we want to formally prove that systems satisfy certain safety properties, or otherwise discover cases when the properties are violated. However, for this we need to be able to formally reason about machine arithmetic. The main problem with existing approaches is their inability to scale well with the increasing complexity of systems and their properties. In this thesis, we explore two alternatives to bit-blasting, the core procedure lying behind many common approaches to reasoning about machine arithmetic. In the first approach, we present a general approximation framework which we apply to solve constraints over floating-point arithmetic. It is built on top of an existing decision procedure, e.g., bit-blasting. Rather than solving the original formula, we solve a sequence of approximations of the formula. Initially very crude, these approximations are frequently solved very quickly. We use results from these approximations to either obtain a solution, obtain a proof of unsatisfiability or generate a new approximation to solve. Eventually, we will either have found a solution or a proof that solution does not exist. The approximation framework improves the solving time and can solve a number of formulas that the bit-blasting cannot. In the second approach, we present a novel method to reason about the theory of fixed-width bit-vectors. This new decision procedure is called mcBV and it is based on the model constructing satisfiability calculus (mcSAT). The procedure uses a lazy representation of bit-vectors and attempts to avoid bit-blasting altogether. It is able to reason about bit-vectors on both bit- and word-level, leveraging both Boolean constraint propagation and native arithmetic reasoning. It also features a greedy explanation generalization mechanism and is capable of more general learning compared to existing approaches. mcBV is able to reason about bit-vectors with sizes that significantly exceed the usual 32, 64 and 128 bits. Evaluation of mcBV shows an improvement in performance (compared to bit-blasting) on several classes of problems.UPMAR

From Machine Arithmetic to Approximations and back again : Improved SMT Methods for Numeric Data Types

Safety-critical systems, especially those found in avionics and automotive industries, rely on machine arithmetic to perform their tasks: integer arithmetic, fixed-point arithmetic or floating-point arithmetic (FPA). Machine arithmetic exhibits subtle differences in behavior compared to the ideal mathematical arithmetic, due to fixed-size representation in memory. Failure of safety-critical systems is unacceptable, due to high-stakes involving human lives or huge amounts of money, time and effort. By formally proving properties of systems, we can be assured that they meet safety requirements. However, to prove such properties it is necessary to reason about machine arithmetic. SMT techniques for machine arithmetic are lacking scalability. This thesis presents approaches that augment or complement existing SMT techniques for machine arithmetic. In this thesis, we explore approximations as a means of augmenting existing decision procedures. A general approximation refinement framework is presented, along with its implementation called UppSAT. The framework solves a sequence of approximations. Initially very crude, these approximations are fairly easy to solve. Results of solving approximate constraints are used to either reconstruct a solution of original constraints, obtain a proof of unsatisfiability or to refine the approximation. The framework preserves soundness, completeness, and termination of the underlying decision procedure, guaranteeing that eventually, either a solution is found or a proof that solution does not exist. We evaluate the impact of approximations implemented in the UppSAT framework on the state-of-the-art in SMT for floating-point arithmetic. A novel method to reason about the theory of fixed-width bit-vectors called mcBV is presented. It is an instantiation of the model constructing satisfiability calculus, mcSAT, and uses a new lazy representation of bit-vectors that allows both bit- and word-level reasoning. It uses a greedy explanation generalization mechanism capable of more general learning compared to traditional approaches. Evaluation of mcBV shows that it can outperform bit-blasting on several classes of problems

Huvudtitel:Att leda ständiga förbättringar i det hybrida arbetssättet : En studie om hur ledare på distans främjar medarbetarengagemang i förbättringsarbetet

Organisationer kan inte kringgå att de lever i en värld med en global konkurrens vars överlevnad riskeras om de inte fokuserar på det ständiga förbättringsarbetet. Skiftet till den hybrida arbetsplatsen som har blivit alltmer populärt har medfört både stora och små förändringar för inte bara ledare men även för medarbetare i organisationer. En av förutsättningarna för ett framgångsrikt förbättringsarbete är att ledare lyckas med sitt engagemang få medarbetare att vara delaktiga. Syftet med denna studie har varit att fördjupa kunskapen kring att leda just arbetet med ständiga förbättringar vid hybrid arbetssätt. För att uppnå studiens syfte valde författarna att utgå från en kvalitativ ansats med semistrukturerade intervjuer av ledare och kvalitativa enkäter som medarbetarna i organisationen fick svara på. Resultatet visade delvist att organisationen värdesätter öppet kommunikationsklimat och tydliga, men även engagerade ledare eftersom det har medarbetare som är i behov av att bli uppmärksammade och sedda. Resultatet visar också att majoriteten av organisationens ledare och medarbetare saknar tydlighet när det gäller deras strategiska kvalitetsutvecklingsarbete.Organizations cannot avoid the fact that they live in a world with increased global competition where they risk their survival if they do not focus on working with continuous improvements. The shift to the hybrid workplace that has become increasingly popular has brought both big and small changes for not only leaders but also employees in organisations. One of the prerequisites for successful improvement work is that leaders with their commitment succeed in getting employees to participate. The main focus for this study has been to deepen the knowledge around leading the work with continuous improvements in the hybrid workplace. To achieve the purpose of the study, the authors chose a qualitative approach that was obtained with semi-structured interviews of leaders and with a qualitative survey that the employees in the organisation got to answer. The results showed that the organisation values an open communication climate, clear but also committed leaders because their employees need to be noticed and seen. The result also shows that most of the leaders and employees within the organisation lack clarity regarding their strategic quality development work

Bit-Vector Interpolation and Quantifier Elimination by Lazy Reduction

The inference of program invariants over machine arithmetic, commonly called bit-vector arithmetic, is an important problem in verification. Techniques that have been successful for unbounded arithmetic, in particular Craig interpolation, have turned out to be difficult to generalise to machine arithmetic: existing bit-vector interpolation approaches are based either on eager translation from bit-vectors to unbounded arithmetic, resulting in complicated constraints that are hard to solve and interpolate, or on bit-blasting to propositional logic, in the process losing all arithmetic structure. We present a new approach to bitvector interpolation, as well as bit-vector quantifier elimination (QE), that works by lazy translation of bit-vector constraints to unbounded arithmetic. Laziness enables us to fully utilise the information available during proof search (implied by decisions and propagation) in the encoding, and this way produce constraints that can be handled relatively easily by existing interpolation and QE procedures for Presburger arithmetic. The lazy encoding is complemented with a set of native proof rules for bit-vector equations and non-linear (polynomial) constraints, this way minimising the number of cases a solver has to conside