Jeffrey Fischer

Increased anterior cingulate/medial prefrontal cortical glutamate and creatine in bipolar depression

Proton magnetic resonance spectroscopy (1HMRS) is an in vivo brain imaging method that can be used to investigate psychotropic drug mechanism of action. This study evaluated baseline 1HMRS spectra of bipolar depressed patients and whether the level of cerebral metabolites changed after an open trial of lamotrigine, an anti-glutamatergic mood stabilizer. Twenty-three bipolar depressed and 12 control subjects underwent a MRS scan of the anterior cingulate/medial prefrontal cortex. The scan was performed on a GE whole-body 1.5 T MRI scanner using single-voxel PRESS (TE/TR=30/3000 ms, 3 × 3 × 3 cm3 and post-processed offline with LCModel. Baseline CSF-corrected absolute concentrations of glutamate+glutamine ([Glx]), glutamate ([Glu]), and creatine+phosphocreatine ([Cr]) were significantly higher in bipolar depressed subjects vs healthy controls. The non-melancholic subtype had significantly higher baseline [Glx] and [Glu] levels than the melancholic subtype. Remission with lamotrigine was associated with significantly lower post-treatment glutamine ([Gln]) in comparison to non-remission. These data suggest that non-melancholic bipolar depression is characterized by increased glutamate coupled with increased energy expenditure. Lamotrigine appears to reduce glutamine levels associated with treatment remission. Further study is encouraged to determine if these MR spectroscopic markers can delineate drug mechanism of action and subsequent treatment response.

Engage: a deployment management system

Many modern applications are built by combining independently developed packages and services that are distributed over many machines with complex inter-dependencies. The assembly, installation, and management of such applications is hard, and usually performed either manually or by writing customized scripts. We present Engage, a system for configuring, installing, and managing complex application stacks. Engage consists of three components: a domain-specific model to describe component metadata and inter-component dependencies; a constraint-based algorithm that takes a partial installation specification and computes a full installation plan; and a runtime system that co-ordinates the deployment of the application across multiple machines and manages the deployed system. By explicitly modeling configuration metadata and inter-component dependencies, Engage enables static checking of application configurations and automated, constraint-driven, generation of installation plans across multiple machines. This reduces the tedious manual process of application configuration, installation, and management. We have implemented Engage and we have used it to successfully host a number of applications. We describe our experiences in using Engage to manage a generic platform that hosts Django applications in the cloud or on premises.

Joining dataflow with predicates

Dataflow analyses sacrifice path-sensitivity for efficiency and lead to false positives when used for verification. Predicate refinement based model checking methods are path-sensitive but must perform many expensive iterations to find all the relevant facts about a program, not all of which are naturally expressed and analyzed using predicates. We show how to join these complementary techniques to obtain efficient and precise versions of any lattice-based dataflow analysis using predicated lattices. A predicated lattice partitions the program state according to a set of predicates and tracks a lattice element for each partition. The resulting dataflow analysis is more precise than the eager dataflow analysis without the predicates.In addition, we automatically infer predicates to rule out imprecisions. The result is a dataflow analysis that can adaptively refine its precision. We then instantiate this generic framework using a symbolic execution lattice, which tracks pointer and value information precisely. We give experimental evidence that our combined analysis is both more precise than the eager analysis in that it is sensitive enough to prove various properties, as well as much faster than the lazy analysis, as many relevant facts are eagerly computed, thus reducing the number of iterations.This results in an order of magnitude improvement in the running times from a purely lazy analysis.

Normal amygdala activation but deficient ventrolateral prefrontal activation in adults with bipolar disorder during euthymia

Functional neuroimaging studies have implicated the involvement of the amygdala and ventrolateral prefrontal cortex (vlPFC) in the pathophysiology of bipolar disorder. Hyperactivity in the amygdala and hypoactivity in the vlPFC have been reported in manic bipolar patients scanned during the performance of an affective faces task. Whether this pattern of dysfunction persists during euthymia is unclear. Using functional magnetic resonance imaging (fMRI), 24 euthymic bipolar and 26 demographically matched healthy control subjects were scanned while performing an affective task paradigm involving the matching and labeling of emotional facial expressions. Neuroimaging results showed that, while amygdala activation did not differ significantly between groups, euthymic patients showed a significant decrease in activation of the right vlPFC (BA47) compared to healthy controls during emotion labeling. Additionally, significant decreases in activation of the right insula, putamen, thalamus and lingual gyrus were observed in euthymic bipolar relative to healthy control subjects during the emotion labeling condition. These data, taken in context with prior studies of bipolar mania using the same emotion recognition task, could suggest that amygdala dysfunction may be a state-related abnormality in bipolar disorder, whereas vlPFC dysfunction may represent a trait-related abnormality of the illness. Characterizing these patterns of activation is likely to help in understanding the neural changes related to the different mood states in bipolar disorder, as well as changes that represent more sustained abnormalities. Future studies that assess mood-state related changes in brain activation in longitudinal bipolar samples would be of interest.

Tasks: language support for event-driven programming

The event-driven programming style is pervasive as an efficient method for interacting with the environment. Unfortunately, the event-driven style severely complicates program maintenance and understanding, as it requires each logical flow of control to be fragmented across multiple independent callbacks. We propose tasks as a new programming model for organizing event-driven programs. Tasks are a variant of cooperative multi-threading and allow each logical control flow to be modularized in the traditional manner, including usage of standard control mechanisms like procedures and exceptions. At the same time, by using method annotations, task-based programs can be automatically and modularly translated into efficient event-based code, using a form of continuation passing style (CPS) translation. A linkable scheduler architecture permits tasks to be used in many different contexts. We have instantiated our model as a backward-compatible extension to Java, called TaskJava. We illustrate the benefits of our language through a formalization in an extension to Featherweight Java, and through a case study based on an open-source web server.

Alterations in functional activation in euthymic bipolar disorder and schizophrenia during a working memory task

Dysfunctions in prefrontal cortical networks are thought to underlie working memory (WM) impairments consistently observed in both subjects with bipolar disorder and schizophrenia. It remains unclear, however, whether patterns of WM‐related hemodynamic responses are similar in bipolar and schizophrenia subjects compared to controls. We used fMRI to investigate differences in blood oxygen level dependent activation during a WM task in 21 patients with euthymic bipolar I, 20 patients with schizophrenia, and 38 healthy controls. Subjects were presented with four stimuli (abstract designs) followed by a fifth stimulus and required to recall whether the last stimulus was among the four presented previously. Task‐related brain activity was compared within and across groups. All groups activated prefrontal cortex (PFC), primary and supplementary motor cortex, and visual cortex during the WM task. There were no significant differences in PFC activation between controls and euthymic bipolar subjects, but controls exhibited significantly increased activation (cluster‐corrected P < 0.05) compared to patients with schizophrenia in prefrontal regions including dorsolateral prefrontal cortex (DLPFC). Although the bipolar group exhibited intermediate percent signal change in a functionally defined DLPFC region of interest with respect to the schizophrenia and control groups, effects remained significant only between patients with schizophrenia and controls. Schizophrenia and bipolar disorder may share some behavioral, diagnostic, and genetic features. Differences in the patterns of WM‐related brain activity across groups, however, suggest some diagnostic specificity. Both patient groups showed some regional task‐related hypoactivation compared to controls across the brain. Within DLPFC specifically, patients with schizophrenia exhibited more severe WM‐related dysfunction than bipolar subjects. Hum Brain Mapp, 2009.

Fine-Grained Access Control with Object-Sensitive Roles

Role-based access control (RBAC) is a common paradigm to ensure that users have sufficient rights to perform various system operations. In many cases though, traditional RBAC does not easily express application-level security requirements. For instance, in a medical records system it is difficult to express that doctors should only update the records of their own patients. Further, traditional RBAC frameworks like Javas Enterprise Edition rely solely on dynamic checks, which makes application code fragile and difficult to ensure correct. We introduce Object-sensitive RBAC (ORBAC), a generalized RBAC model for object-oriented languages. ORBAC resolves the expressiveness limitations of RBAC by allowing roles to be parameterized by properties of the business objects being manipulated. We formalize and prove sound a dependent type system that statically validates a programs conformance to an ORBAC policy. We have implemented our type system for Java and have used it to validate fine-grained access control in the OpenMRS medical records system.

Three-dimensional mapping of hippocampal and amygdalar structure in euthymic adults with bipolar disorder not treated with lithium.

Structural neuroimaging studies of the amygdala and hippocampus in bipolar disorder have been largely inconsistent. This may be due in part to differences in the proportion of subjects taking lithium or experiencing an acute mood state, as both factors have recently been shown to influence gray matter structure. To avoid these problems, we evaluated euthymic subjects not currently taking lithium. Thirty-two subjects with bipolar type I disorder and 32 healthy subjects were scanned using magnetic resonance imaging. Subcortical regions were manually traced, and converted to three-dimensional meshes to evaluate the main effect of bipolar illness on radial distance. Statistical analyses found no evidence for a main effect of bipolar illness in either region, although exploratory analyses found a significant age by diagnosis interaction in the right amygdala, as well as positive associations between radial distance of the left amygdala and both prior hospitalizations for mania and current medication status. These findings suggest that, when not treated with lithium or in an acute mood state, patients with bipolar disorder exhibit no structural abnormalities of the amygdala or hippocampus. Future studies, nevertheless, that further elucidate the impact of age, course of illness, and medication on amygdala structure in bipolar disorder are warranted.

Ensuring consistency in long running transactions

Flow composition languages permit the construction of long-running transactions from collections of independent atomic services. Due to environmental limitations, such transactions usually cannot be made to conform to standard ACID semantics. We propose set consistency, a powerful, yet intuitive, notion of consistency for long-running transactions. Set consistency considers the collection of permanent (non-intermittent) changes made by a process, when viewed at the end of its execution. Consistency requirements for such collections of changes are specified as predicates over the atomic actions of a process. Set consistency generalizes self-cancellation, a standard consistency requirement for long-running transactions, where failed processes are responsible for undoing any partially completed work. Set consistency can also express strictly stronger requirements, such as mutual exclusion or dependency. We show that the set consistency verification problem for processes is co-NP complete and present an algorithm for verifying set consistency by reduction to propositional validity. We have implemented this algorithm and demonstrate the value and tractability of our approach on three real-world case studies. In each case, the consistency requirements can be verified within a second, demonstrating the practicality of our approach.

A Theory of Role Composition

We study the access control integration problem for web services. Organizations frequently use many services, each with its own access control policies, which must interoperate while maintaining secure access to information. The integration problem is to take the set of such services and to find a globally consistent access control policy that ensures that the system composed from the services does not have any authorization failures or information disclosures. We give a sound and complete algorithm for access control integration by reducing the problem to Boolean constraint solving. We have implemented ROLEMATCHER, a tool to infer global role-based access control schemas for a set of services, and show on examples that it can quickly infer global roles for composed systems, or determine the absence of a globally consistent role schema.