Affective and interpersonal psychopathic traits associated with reduced corpus callosum volume among male inmates – RETRACTED

2018 ◽  
Vol 49 (08) ◽  
pp. 1401-1408
Author(s):  
Nathaniel E. Anderson ◽  
J. Michael Maurer ◽  
Prashanth Nyalakanti ◽  
Keith A. Harenski ◽  
Carla L. Harenski ◽  
...  
Keyword(s):  
Corpus Callosum ◽  
Emotional Processing ◽  
Large Scale ◽  
Psychopathic Traits ◽  
Large White ◽  
Total Brain Volume ◽  
Psychopathy Checklist Revised ◽  
Male Inmates ◽  
Large Scale Networks ◽  
The Brain

AbstractBackgroundPsychopathy is a personality disorder associated with severe emotional and interpersonal consequences and persistent antisocial behavior. Neurobiological models of psychopathy emphasize impairments in emotional processing, attention, and integration of information across large-scale neural networks in the brain. One of the largest integrative hubs in the brain is the corpus callosum (CC) – a large white matter structure that connects the two cerebral hemispheres.MethodThe current study examines CC volume, measured via Freesurfer parcellation, in a large sample (n= 495) of incarcerated men who were assessed for psychopathic traits using the Hare Psychopathy Checklist-Revised (PCL-R).ResultsPsychopathy was associated with reduced volume across all five sub-regions of the CC. These relationships were primarily driven by the affective/interpersonal elements of psychopathy (PCL-R Factor 1), as no significant associations were found between the CC and the lifestyle/antisocial traits of psychopathy. The observed effects were not attributable to differences in substance use severity, age, IQ, or total brain volume.ConclusionsThese findings align with suggestions that core psychopathic traits may be fostered by reduced integrative capacity across large-scale networks in the brain.

scholarly journals Brain network dynamics are hierarchically organized in time

2017 ◽  
Vol 114 (48) ◽  
pp. 12827-12832 ◽  
Author(s):  
Diego Vidaurre ◽  
Stephen M. Smith ◽  
Mark W. Woolrich
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Network ◽  
Specific Measure ◽  
Brain Areas ◽  
Neuronal Populations ◽  
Subject Specific ◽  
Large Scale Networks ◽  
Network Patterns ◽  
The Brain

The brain recruits neuronal populations in a temporally coordinated manner in task and at rest. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. We use an approach designed to find repeating network patterns in whole-brain resting fMRI data, where networks are defined as graphs of interacting brain areas. We find that the transitions between networks are nonrandom, with certain networks more likely to occur after others. Further, this nonrandom sequencing is itself hierarchically organized, revealing two distinct sets of networks, or metastates, that the brain has a tendency to cycle within. One metastate is associated with sensory and motor regions, and the other involves areas related to higher order cognition. Moreover, we find that the proportion of time that a subject spends in each brain network and metastate is a consistent subject-specific measure, is heritable, and shows a significant relationship with cognitive traits.

scholarly journals Attention Networks and the Intrinsic Network Structure of the Human Brain

2021 ◽  
Author(s):  
Sebastian Markett ◽  
David Nothdurfter ◽  
Antonia Focsa ◽  
Martin Reuter ◽  
Philippe Jawinski
Keyword(s):  
Network Structure ◽  
Network Theory ◽  
Large Scale ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Relevant Information ◽  
Attention Network ◽  
Attention Networks ◽  
Large Scale Networks ◽  
The Brain

Attention network theory states that attention is not a unified construct but consists of three independent systems that are supported by separable distributed networks: an alerting network to deploy attentional resources in anticipation of upcoming events, an orienting network to direct attention to a cued location, and a control network to select relevant information at the expense of concurrently available information. Ample behavioral and neuroimaging evidence supports the dissociation of the three attention domains. The strong assumption that each attentional system is realized through a separable network, however, raises the question how these networks relate to the intrinsic network structure of the brain. Our understanding of brain networks has advanced majorly in the past years due to the increasing focus on brain connectivity. It is well established that the brain is intrinsically organized into several large-scale networks whose modular structure persists across task states. Existing proposals on how the presumed attention networks relate to intrinsic networks rely mostly on anecdotal and partly contradictory arguments. We addressed this issue by mapping different attention networks with highest spatial precision at the level of cifti-grayordinates. Resulting group maps were compared to the group-level topology of 23 intrinsic networks which we reconstructed from the same participants' resting state fMRI data. We found that all attention domains recruited multiple and partly overlapping intrinsic networks and converged in the dorsal fronto-parietal and midcingulo-insular network. While we observed a preference of each attentional domain for its own set of intrinsic networks, implicated networks did not match well to those proposed in the literature. Our results indicate a necessary refinement of the attention network theory.

scholarly journals Trips and Neurotransmitters: Discovering Principled Patterns across 6,850 Hallucinogenic Experiences

2021 ◽  
Author(s):  
Galen Ballentine ◽  
Sam Freesun Friedman ◽  
Danilo Bzdok
Keyword(s):  
Large Scale ◽  
Free Form ◽  
Association Cortex ◽  
Receptor Subtypes ◽  
Drug Induced ◽  
Psychological Phenomena ◽  
Input Pole ◽  
Large Scale Networks ◽  
Induced Changes ◽  
The Brain

Psychedelics are thought to alter states of consciousness by disrupting how the higher association cortex governs bottom-up sensory signals. Individual hallucinogenic drugs are usually studied in participants in controlled laboratory settings. Here, we have explored word usage in 6,850 free-form testimonials with 27 drugs through the prism of 40 neurotransmitter receptor subtypes, which were then mapped to 3D coordinates in the brain via their gene transcription levels from invasive tissue probes. Despite the variable subjective nature of hallucinogenic experiences, our pattern-learning approach delineated how drug-induced changes of conscious awareness (e.g., dissolving self-world boundaries or fractal distortion of visual perception) are linked to cortex-wide anatomical distributions of receptor density proxies. The dominant explanatory factor related ego-dissolution-like phenomena to a constellation of 5-HT2A, D2, KOR, and NMDA receptors, anchored especially in the brain's deep hierarchy (epitomized by the associative higher-order cortex) and shallow hierarchy (epitomized by the visual cortex). Additional factors captured psychological phenomena in which emotions (5-HT2A and Imidazoline1) were in tension with auditory (SERT, 5-HT1A) or visual (5-HT2A) sensations. Each discovered receptor-experience factor spanned between a higher-level association pole and a sensory input pole, which may relate to the previously reported collapse of hierarchical order among large-scale networks. Simultaneously considering many psychoactive molecules and thousands of natural language descriptions of drug experiences our framework finds the underlying semantic structure and maps it directly to the brain. These advances could assist in unlocking their wide-ranging potential for medical treatment.

scholarly journals Post-Stroke Cognitive Impairment: Pathophysiological Insights into Brain Disconnectome from Advanced Neuroimaging Analysis Techniques

2021 ◽  
Vol 23 (3) ◽  
pp. 297-311
Author(s):  
Jae-Sung Lim ◽  
Jae-Joong Lee ◽  
Choong-Wan Woo
Keyword(s):  
Cognitive Impairment ◽  
Large Scale ◽  
Imaging Techniques ◽  
Brain Network ◽  
Clinical Neurology ◽  
Post Stroke ◽  
Large Scale Networks ◽  
High Level ◽  
New Treatments ◽  
The Brain

The neurological symptoms of stroke have traditionally provided the foundation for functional mapping of the brain. However, there are many unresolved aspects in our understanding of cerebral activity, especially regarding high-level cognitive functions. This review provides a comprehensive look at the pathophysiology of post-stroke cognitive impairment in light of recent findings from advanced imaging techniques. Combining network neuroscience and clinical neurology, our research focuses on how changes in brain networks correlate with post-stroke cognitive prognosis. More specifically, we first discuss the general consequences of stroke lesions due to damage of canonical resting-state large-scale networks or changes in the composition of the entire brain. We also review emerging methods, such as lesion-network mapping and gradient analysis, used to study the aforementioned events caused by stroke lesions. Lastly, we examine other patient vulnerabilities, such as superimposed amyloid pathology and blood-brain barrier leakage, which potentially lead to different outcomes for the brain network compositions even in the presence of similar stroke lesions. This knowledge will allow a better understanding of the pathophysiology of post-stroke cognitive impairment and provide a theoretical basis for the development of new treatments, such as neuromodulation.

scholarly journals Affective and Interpersonal Psychopathic Traits Associated with Reduced Corpus Callosum Volume among Male Inmates – Retraction

2019 ◽  
Vol 49 (08) ◽  
pp. 1400
Author(s):  
Nathaniel E. Anderson ◽  
J. Michael Maurer ◽  
Prashanth Nyalakanti ◽  
Keith A. Harenski ◽  
Carla L. Harenski ◽  
...  
Keyword(s):  
Corpus Callosum ◽  
Psychopathic Traits ◽  
Male Inmates

Challenges of Complex Systems in Cognitive and Complex Systems

2010 ◽  
pp. 367-384
Author(s):  
Klaus Mainzer
Keyword(s):  
Neural Networks ◽  
Complex Systems ◽  
Large Scale ◽  
Computational Models ◽  
Self Control ◽  
Self Organization ◽  
Embodied Mind ◽  
Future Technology ◽  
Large Scale Networks ◽  
The Brain

After an introduction (1) the article analyzes complex systems and the evolution of the embodied mind (2), complex systems and the innovation of embodied robotics (3), and finally discusses challenges of handling a world with increasing complexity: Large-scale networks have the same universal properties in evolution and technology (4). Considering the evolution of the embodied mind (2), we start with an introduction of complex systems and nonlinear dynamics (2.1), apply this approach to neural self-organization (2.2), distinguish degrees of complexity of the brain (2.3), explain the emergence of cognitive states by complex systems dynamics (2.4), and discuss criteria for modeling the brain as complex nonlinear system (2.5). The innovation of embodied robotics (3) is a challenge of complex systems and future technology. We start with the distinction of symbolic and embodied AI (3.1). Embodied robotics is inspired by the evolution of life. Modern systems biology integrates the molecular, organic, human, and ecological levels of life with computational models of complex systems (3.2). Embodied robots are explained as dynamical systems (3.3). Self-organization of complex systems needs self-control of technical systems (3.4). Cellular neural networks (CNN) are an example of self-organizing complex systems offering new avenues for neurobionics (3.5). In general, technical neural networks support different kinds of learning robots (3.6). Embodied robotics aims at the development of cognitive and conscious robots (3.7).

scholarly journals Cerebral cartography and connectomics

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140173 ◽  
Author(s):  
Olaf Sporns
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Network Science ◽  
Temporal Dynamics ◽  
Functional Organization ◽  
Brain Connectivity ◽  
Hierarchical Organization ◽  
Large Scale Networks ◽  
Definition Of ◽  
The Brain

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics.

scholarly journals Disentangling predictive processing in the brain: a meta-analytic study in favour of a predictive network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Linda Ficco ◽  
Lorenzo Mancuso ◽  
Jordi Manuello ◽  
Alessia Teneggi ◽  
Donato Liloia ◽  
...  
Keyword(s):  
Large Scale ◽  
Inferior Frontal Gyrus ◽  
Predictive Coding ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Predictive Processing ◽  
Spatial Convergence ◽  
Large Scale Networks ◽  
The Brain

AbstractAccording to the predictive coding (PC) theory, the brain is constantly engaged in predicting its upcoming states and refining these predictions through error signals. Despite extensive research investigating the neural bases of this theory, to date no previous study has systematically attempted to define the neural mechanisms of predictive coding across studies and sensory channels, focussing on functional connectivity. In this study, we employ a coordinate-based meta-analytical approach to address this issue. We first use the Activation Likelihood Estimation (ALE) algorithm to detect spatial convergence across studies, related to prediction error and encoding. Overall, our ALE results suggest the ultimate role of the left inferior frontal gyrus and left insula in both processes. Moreover, we employ a meta-analytic connectivity method (Seed-Voxel Correlations Consensus). This technique reveals a large, bilateral predictive network, which resembles large-scale networks involved in task-driven attention and execution. In sum, we find that: (i) predictive processing seems to occur more in certain brain regions than others, when considering different sensory modalities at a time; (ii) there is no evidence, at the network level, for a distinction between error and prediction processing.

scholarly journals The neurodevelopment of anomalous perception: Evidence in cortical folding patterns for prenatal predispositions to hallucinations in schizophrenia

2020 ◽  
Author(s):  
Colleen P.E. Rollins ◽  
Jane R. Garrison ◽  
Maite Arribas ◽  
Aida Seyedsalehi ◽  
Zhi Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Fetal Brain ◽  
Brain Structures ◽  
Physical Reality ◽  
Healthy Controls ◽  
Cortical Folding ◽  
Diverse World ◽  
Fetal Brain Development ◽  
Large Scale Networks ◽  
The Brain

Background: All perception is a construction of the brain from sensory input. Our first perceptions begin during gestation, making fetal brain development fundamental to how we experience a diverse world. Hallucinations are percepts without origin in physical reality that occur in health and disease. Despite longstanding research on the brain structures supporting hallucinations and on perinatal contributions to the pathophysiology of schizophrenia, what links these two distinct lines of research remains unclear. Methods: We studied two independent datasets of patients with schizophrenia who underwent clinical assessment and 3T structural magnetic resonance (MR) imaging from the United Kingdom and Shanghai, China (n = 181 combined) and 63 healthy controls from Shanghai. Participants were stratified into those with (n = 79 UK; n = 22 Shanghai) and without (n = 43 UK; n = 37 Shanghai) hallucinations from the PANSS P3 scores for hallucinatory behaviour. We quantified the length, depth, and asymmetry indices of the paracingulate and superior temporal sulci (PCS, STS) from MR images and constructed cortical folding covariance matrices organized by large-scale networks. Results: In both ethnic groups, we replicated a significantly shorter left PCS in patients with hallucinations compared to those without, and healthy controls. Reduced PCS length and STS depth corresponded to focal deviations in their geometry and to significantly increased covariance within and between areas of the salience and auditory networks. Conclusion: The discovery of neurodevelopmental alterations contributing to hallucinations establishes testable models for these enigmatic, sometimes highly distressing, perceptions and provides mechanistic insight into the pathological consequences of prenatal origins.

Sign in / Sign up

Export Citation Format

Share Document