Test-retest reliability of regression dynamic causal modeling

Regression dynamic causal modeling (rDCM) is a novel and computationally highly efficient method for inferring effective connectivity at the whole-brain level. While face and construct validity of rDCM have already been demonstrated, here we assessed its test-retest reliability-a test-theoretical property of particular importance for clinical applications-together with group-level consistency of connection-specific estimates and consistency of whole-brain connectivity patterns over sessions. Using the Human Connectome Project dataset for eight different paradigms (tasks and rest) and two different parcellation schemes, we found that rDCM provided highly consistent connectivity estimates at the group level across sessions. Second, while test-retest reliability was limited when averaging over all connections (range of mean intraclass correlation coefficient 0.24-0.42 over tasks), reliability increased with connection strength, with stronger connections showing good to excellent test-retest reliability. Third, whole-brain connectivity patterns by rDCM allowed for identifying individual participants with high (and in some cases perfect) accuracy. Comparing the test-retest reliability of rDCM connectivity estimates with measures of functional connectivity, rDCM performed favorably-particularly when focusing on strong connections. Generally, for all methods and metrics, task-based connectivity estimates showed greater reliability than those from the resting state. Our results underscore the potential of rDCM for human connectomics and clinical applications. Keywords: Connectomics; Effective connectivity; Generative model; Regression dynamic causal modeling; Test-retest reliability; rDC

Whole-brain estimates of directed connectivity for human connectomics

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics

Allostatic self-efficacy: a metacognitive theory of dyshomeostasis-induced fatigue and depression

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future

Timing of repetition suppression of event-related potentials to unattended objects

Current theories of object perception emphasize the automatic nature of perceptual inference. Repetition suppression (RS), the successive decrease of brain responses to repeated stimuli, is thought to reflect the optimization of perceptual inference through neural plasticity. While functional imaging studies revealed brain regions that show suppressed responses to the repeated presentation of an object, little is known about the intra‐trial time course of repetition effects to everyday objects. Here, we used event‐related potentials (ERPs) to task‐irrelevant line‐drawn objects, while participants engaged in a distractor task. We quantified changes in ERPs over repetitions using three general linear models that modeled RS by an exponential, linear, or categorical “change detection” function in each subject. Our aim was to select the model with highest evidence and determine the within‐trial time‐course and scalp distribution of repetition effects using that model. Model comparison revealed the superiority of the exponential model indicating that repetition effects are observable for trials beyond the first repetition. Model parameter estimates revealed a sequence of RS effects in three time windows (86–140, 322–360, and 400–446 ms) and with occipital, temporoparietal, and frontotemporal distribution, respectively. An interval of repetition enhancement (RE) was also observed (320–340 ms) over occipitotemporal sensors. Our results show that automatic processing of task‐irrelevant objects involves multiple intervals of RS with distinct scalp topographies. These sequential intervals of RS and RE might reflect the short‐term plasticity required for optimization of perceptual inference and the associated changes in prediction errors and predictions, respectively, over stimulus repetitions during automatic object processing

Computational psychosomatics and computational psychiatry: toward a joint framework for differential diagnosis

This article outlines how a core concept from theories of homeostasis and cybernetics, the inference-control loop, may be used to guide differential diagnosis in computational psychiatry and computational psychosomatics. In particular, we discuss 1) how conceptualizing perception and action as inference-control loops yields a joint computational perspective on brain-world and brain-body interactions and 2) how the concrete formulation of this loop as a hierarchical Bayesian model points to key computational quantities that inform a taxonomy of potential disease mechanisms. We consider the utility of this perspective for differential diagnosis in concrete clinical applications

Using standardized patients for undergraduate clinical skills training in an introductory course to psychiatry

Background The goal of this study was to assess the value and acceptance of Standardized or Simulated Patients (SPs) for training clinically inexperienced undergraduate medical students in psychiatric history taking, psychopathological assessment, and communication with psychiatric patients. Methods As part of a newly developed introductory course to psychiatry, pairs of 3rd year medical students conducted psychiatric assessments of SPs, including history and psychopathological state, under the supervision of a clinical lecturer. Prior to the assessment, students attended introductory lectures to communication in psychiatry and psychopathology but were clinically inexperienced. After the interview, the students’ summary of their findings was discussed with other students and the lecturer. Students, lecturers, and actors were invited to a survey after the course. Questions for the students included self-reports about perceived learning success and authenticity of the interviews. Results 41 students, 6 actors and 8 lecturers completed the survey (response rates of 48%, 50%, and 100%, respectively). The survey results indicated that, despite their lack of clinical experience, students learned how to conduct a psychiatric interview, communicate in a non-judgmental and empathetic manner, take a psychiatric history and perform a psychopathological examination. SPs were perceived as authentic. The survey results suggested that this setting allowed for an enjoyable, non-distressful and motivating learning experience within a restricted time frame of just two afternoons. Conclusion The results indicated that the SP approach presented is useful for teaching clinical skills in psychiatry to students with limited previous clinical experience and knowledge of psychiatry. We argue that SPs can be used to teach practical psychiatric skills already during an early phase of the curriculum. Limitations of our study include a limited sample size, a temporal gap between the course and the survey, reliance on self-reports, and lack of comparison to alternative interventions

Morphometric characterisation of wing feathers of the barn owl Tyto alba pratincola and the pigeon Columba livia

<p>Abstract</p> <p>Background</p> <p>Owls are known for their silent flight. Even though there is some information available on the mechanisms that lead to a reduction of noise emission, neither the morphological basis, nor the biological mechanisms of the owl's silent flight are known. Therefore, we have initiated a systematic analysis of wing morphology in both a specialist, the barn owl, and a generalist, the pigeon. This report presents a comparison between the feathers of the barn owl and the pigeon and emphasise the specific characteristics of the owl's feathers on macroscopic and microscopic level. An understanding of the features and mechanisms underlying this silent flight might eventually be employed for aerodynamic purposes and lead to a new wing design in modern aircrafts.</p> <p>Results</p> <p>A variety of different feathers (six remiges and six coverts), taken from several specimen in either species, were investigated. Quantitative analysis of digital images and scanning electron microscopy were used for a morphometric characterisation. Although both species have comparable body weights, barn owl feathers were in general larger than pigeon feathers. For both species, the depth and the area of the outer vanes of the remiges were typically smaller than those of the inner vanes. This difference was more pronounced in the barn owl than in the pigeon. Owl feathers also had lesser radiates, longer pennula, and were more translucent than pigeon feathers. The two species achieved smooth edges and regular surfaces of the vanes by different construction principles: while the angles of attachment to the rachis and the length of the barbs was nearly constant for the barn owl, these parameters varied in the pigeon. We also present a quantitative description of several characteristic features of barn owl feathers, e.g., the serrations at the leading edge of the wing, the fringes at the edges of each feather, and the velvet-like dorsal surface.</p> <p>Conclusion</p> <p>The quantitative description of the feathers and the specific structures of owl feathers can be used as a model for the construction of a biomimetic airplane wing or, in general, as a source for noise-reducing applications on any surfaces subjected to flow fields.</p