The borderlands of waking:quantifying the transition from reflective thought to hallucination in sleep onset

We lose waking consciousness spontaneously and regularly over the circadian cycle. It seems that every time we fall asleep, reflective thinking gradually gives way to our interactions with an imaginary, hallucinatory world that brings multimodal experiences in the absence of adequate external stimuli. The present study investigates this transition, proposing a new measure of hallucinatory states. Reflective thinking and motor imagery were quantified in 150 mentation reports provided by 16 participants after forced awakenings from different physiology-monitored time intervals after sleep onset. Cognitive agency analysis and motor agency analysis – which are objective (grammatical–semantic) tools derived from linguistic theories – show (i) a decrease in reflective thinking which sleepers would need to acknowledge the hallucinatory quality of their state, and (ii) an increase in motor imagery, indicating interactions with a hallucinatory world. By mapping these spontaneous changes in human consciousness onto physiology, we can in the long run explore the conditions of its decline, and possibilities for treatment

Hippocampal and amygdala volumes in borderline personality disorder: A meta-analysis of magnetic resonance imaging studies

Background Structural brain abnormalities have been described in borderline personality disorder (BPD), but previous studies have generally been small and have implicated different brain regions to varying extents.Method We therefore conducted a systematic review and meta-analysis of published volumetric region-of-interest structural magnetic resonance imaging studies of patients with BPD and healthy controls. We additionally used meta-regression to investigate the modulating effects of clinical parameters, including age, on regional brain volumes.Results The meta-analysis revealed significant bilateral decreases in hippocampal and amygdala volumes in patients with BPD compared with healthy control participants, in the absence of differences in whole-brain volume. Metaregression demonstrated an association between increasing age and reduced hippocampal volumes in BPD.Discussion Overall, these findings demonstrate clear structural changes in the medial temporal lobe in BPD, showing similarity to the biological effects of early life stress. Copyright (C) 2010 John Wiley &amp; Sons, Ltd.</p

Amygdala and dlPFC abnormalities, with aberrant connectivity and habituation in response to emotional stimuli in females with BPD

Background: Little is known about the frontolimbic abnormalities thought to underlie borderline personality disorder (BPD). We endeavoured to study regional responses, as well as their connectivity and habituation during emotion processing. Methods: 14 BPD patients and 14 normal female controls (NC) controlled for menstrual phase underwent emotion-induction during an fMRI task using standardised images in a block design. We then performed psychophysiological interaction (PPI) analysis to investigate functional connectivity. Results: BPD patients reported more disgust in questionnaires compared to controls. Relative to NC, they showed reduced left amygdala and increased dorsolateral prefrontal cortex (dlPFC) activation to all emotions collapsed versus neutral. Habituation of ventral striatal activity to repeated emotional stimuli was observed in controls but not in BPD. Finally, in the context of disgust (but not other emotions) versus neutral, BPD patients displayed enhanced left amygdala coupling with the dlPFC and ventral striatum. Limitations: Strict inclusion criteria reduced the sample size. Conclusions: In summary, BPD showed abnormal patterns of activation, habituation and connectivity in regions linked to emotion regulation. Amygdala deactivation may be mediated by abnormal top-down regulatory control from the dorsolateral prefrontal cortex. Aberrant emotion processing may play a unique role in the pathophysiology of BPD

A computationally inspired in-vivo approach identifies a link between amygdalar transcriptional heterogeneity, socialization and anxiety

Pharmaceutical breakthroughs for anxiety have been lackluster in the last half-century. Converging behavior and limbic molecular heterogeneity has the potential to revolutionize biomarker-driven interventions. However, current in vivo models too often deploy artificial systems including directed evolution, mutations and fear induction, which poorly mirror clinical manifestations. Here, we explore transcriptional heterogeneity of the amygdala in isogenic mice using an unbiased multidimensional computational approach that segregates intra-cohort reactions to moderate situational adversity and intersects it with high content molecular profiling. We show that while the computational approach stratifies known features of clinical anxiety including nitric oxide, opioid and corticotropin signaling, previously unrecognized druggable biomarkers emerge, such as calpain11 and scand1. Through ingenuity pathway analyses, we further describe a role for neurosteroid estradiol signaling, heat shock proteins, ubiquitin ligases and lipid metabolism. In addition, we report a remarkable behavioral pattern that maps to molecular features of anxiety in mice through counterphobic social attitudes, which manifest as increased, yet spatially distant socialization. These findings provide an unbiased approach for interrogating anxiolytics, and hint toward biomarkers underpinning behavioral and social patterns that merit further exploration

Decision Models and Technology Can Help Psychiatry Develop Biomarkers

Why is psychiatry unable to define clinically useful biomarkers? We explore this question from the vantage of data and decision science and consider biomarkers as a form of phenotypic data that resolves a well-defined clinical decision. We introduce a framework that systematizes different forms of phenotypic data and further introduce the concept of decision model to describe the strategies a clinician uses to seek out, combine, and act on clinical data. Though many medical specialties rely on quantitative clinical data and operationalized decision models, we observe that, in psychiatry, clinical data are gathered and used in idiosyncratic decision models that exist solely in the clinician's mind and therefore are outside empirical evaluation. This, we argue, is a fundamental reason why psychiatry is unable to define clinically useful biomarkers: because psychiatry does not currently quantify clinical data, decision models cannot be operationalized and, in the absence of an operationalized decision model, it is impossible to define how a biomarker might be of use. Here, psychiatry might benefit from digital technologies that have recently emerged specifically to quantify clinically relevant facets of human behavior. We propose that digital tools might help psychiatry in two ways: first, by quantifying data already present in the standard clinical interaction and by allowing decision models to be operationalized and evaluated; second, by testing whether new forms of data might have value within an operationalized decision model. We reference successes from other medical specialties to illustrate how quantitative data and operationalized decision models improve patient care

Imaging Inflammation in a Patient with Epilepsy Due to Focal Cortical Dysplasia

BACKGROUND AND PURPOSE Evidence from animal models and examination of human epilepsy surgery specimens indicates that inflammation plays an important role in epilepsy. Positron emission tomography (PET) using [C11]PK11195, a marker of activated microglia, provides a means to visualize neuroinflammation in vivo in humans. We hypothesize that in patients with active epilepsy, [C11]PK11195 PET (PK-PET) may be able to identify areas of focally increased inflammation corresponding to the seizure onset zone. METHODS A young woman with intractable epilepsy underwent PK-PET as part of an approved research study. PK-PET results were compared with results from other clinical studies. RESULTS PK-PET revealed an area of focally increased radiotracer uptake in the right frontal lobe corresponding to this patient’s seizure focus as identified by ictal and interictal 18Ffluorodeoxyglucose (FDG)-PET and EEG. Routine brain magnetic resonance imaging (MRI) was initially considered normal, though high-resolution studies showed possible subtle dysplasia of the right frontal lobe. The patient underwent a right frontal lobe resection, and pathological evaluation showed focal cortical dysplasia with activated microglia. CONCLUSIONS PK-PET can identify neuroinflammation associated with subtle focal cortical dysplasia, and may therefore have a clinical role in guiding epilepsy surgery for patients with difficult-to-localize seizure foci

Контент социальных медиа как условие эффективных коммуникаций малого бизнеса с потребителем (на примере компании "Полли-Вилли")

Актуальность проблем связана с динамикой роста популярности социальных медиа среди предпринимателей разного масштаба в России. В связи с этим необходимо сформировать методологию для наиболее эффективного применения инструментов, находящихся в арсенале социальных медиа. Объект – контент социальных медиа, формируемый для продвижения в социальных сетях. Предмет – подходы к технологиям создания контента для эффективной коммуникации предприятия малого бизнеса с потребителями. Проблема – отсутствие прописанных комплексных технологий, приемов и методов продвижения бизнеса в социальных медиа (Российский сегмент). Цель – разработка подходов к созданию эффективного контента для предприятий малого бизнеса.Objective: to develop the approaches of creating effective content for small businesses. Problem: the lack of prescribed complex technologies, techniques and methods of business promotion in social media (Russian Segment). Object: social media content generated for promotion in social networks. Subject: approaches to content creation technologies for effective communication between small businesses with consumers

Nonparametric permutation tests for functional neuroimaging: A primer with examples

Requiring only minimal assumptions for validity, nonparametric permutation testing provides a flexible and intuitive methodology for the statistical analysis of data from functional neuroimaging experiments, at some computational expense. Introduced into the functional neuroimaging literature by Holmes et al. ([ 1996 ]: J Cereb Blood Flow Metab 16:7–22), the permutation approach readily accounts for the multiple comparisons problem implicit in the standard voxel-by-voxel hypothesis testing framework. When the appropriate assumptions hold, the nonparametric permutation approach gives results similar to those obtained from a comparable Statistical Parametric Mapping approach using a general linear model with multiple comparisons corrections derived from random field theory. For analyses with low degrees of freedom, such as single subject PET/SPECT experiments or multi-subject PET/SPECT or f MRI designs assessed for population effects, the nonparametric approach employing a locally pooled (smoothed) variance estimate can outperform the comparable Statistical Parametric Mapping approach. Thus, these nonparametric techniques can be used to verify the validity of less computationally expensive parametric approaches. Although the theory and relative advantages of permutation approaches have been discussed by various authors, there has been no accessible explication of the method, and no freely distributed software implementing it. Consequently, there have been few practical applications of the technique. This article, and the accompanying MATLAB software, attempts to address these issues. The standard nonparametric randomization and permutation testing ideas are developed at an accessible level, using practical examples from functional neuroimaging, and the extensions for multiple comparisons described. Three worked examples from PET and f MRI are presented, with discussion, and comparisons with standard parametric approaches made where appropriate. Practical considerations are given throughout, and relevant statistical concepts are expounded in appendices. Hum. Brain Mapping 15:1–25, 2001. © 2001 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/35194/1/1058_ftp.pd