From brain to earth and climate systems: small-world interaction networks or not?

PubMed

Bialonski, Stephan; Horstmann, Marie-Therese; Lehnertz, Klaus

2010-03-01

We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.

Graph Theoretical Analysis of BOLD Functional Connectivity during Human Sleep without EEG Monitoring.

PubMed

Lv, Jun; Liu, Dongdong; Ma, Jing; Wang, Xiaoying; Zhang, Jue

2015-01-01

Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) time series. In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD) images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep. In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.

Small-World Brain Networks Revisited

PubMed Central

Bassett, Danielle S.; Bullmore, Edward T.

2016-01-01

It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of high clustering and short path length; and about 10 years since this metric of complex network topology began to be widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field of connectomics. Here, we review briefly the foundational concepts of graph theoretical estimation and generation of small-world networks. We take stock of some of the key developments in the field in the past decade and we consider in some detail the implications of recent studies using high-resolution tract-tracing methods to map the anatomical networks of the macaque and the mouse. In doing so, we draw attention to the important methodological distinction between topological analysis of binary or unweighted graphs, which have provided a popular but simple approach to brain network analysis in the past, and the topology of weighted graphs, which retain more biologically relevant information and are more appropriate to the increasingly sophisticated data on brain connectivity emerging from contemporary tract-tracing and other imaging studies. We conclude by highlighting some possible future trends in the further development of weighted small-worldness as part of a deeper and broader understanding of the topology and the functional value of the strong and weak links between areas of mammalian cortex. PMID:27655008

Correlation between standardized assessment of concussion scores and small-world brain network in mild traumatic brain injury.

PubMed

Yan, Yan; Song, Jian; Xu, Guozheng; Yao, Shun; Cao, Chenglong; Li, Chang; Peng, Guibao; Du, Hao

2017-10-01

This study investigated the characteristics of the small-world brain network architecture of patients with mild traumatic brain injury (MTBI), and a correlation between brain functional connectivity network properties in the resting-state fMRI and Standardized Assessment of Concussion (SAC) parameters. The neurological conditions of 22 MTBI patients and 17 normal control individuals were evaluated according to the SAC. Resting-state fMRI was performed in all subjects 3 and 7days after injury respectively. After preprocessing the fMRI data, cortex functional regions were marked using AAL90 and Dosenbach160 templates. The small-world network parameters and areas under the integral curves were computed in the range of sparsity from 0.01 to 0.5. Independent-sample t-tests were used to compare these parameters between the MTBI and control group. Significantly different parameters were investigated for correlations with SAC scores; those that correlated were chosen for further curve fitting. The clustering coefficient, the communication efficiency across in local networks, and the strength of connectivity were all higher in MTBI patients relative to control individuals. Parameters in 160 brain regions of the MTBI group significantly correlated with total SAC score and score for attention; the network parameters may be a quadratic function of attention scores of SAC and a cubic function of SAC scores. MTBI patients were characterized by elevated communication efficiency across global brain regions, and in local networks, and strength of mean connectivity. These features may be associated with brain function compensation. The network parameters significantly correlated with SAC total and attention scores. Copyright © 2017 Elsevier Ltd. All rights reserved.

The effects of working memory training on functional brain network efficiency.

PubMed

Langer, Nicolas; von Bastian, Claudia C; Wirz, Helen; Oberauer, Klaus; Jäncke, Lutz

2013-10-01

The human brain is a highly interconnected network. Recent studies have shown that the functional and anatomical features of this network are organized in an efficient small-world manner that confers high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of functional brain networks is related to performance in working memory (WM) tasks and if these networks can be modified by WM training. Therefore, we conducted a double-blind training study enrolling 66 young adults. Half of the subjects practiced three WM tasks and were compared to an active control group practicing three tasks with low WM demand. High-density resting-state electroencephalography (EEG) was recorded before and after training to analyze graph-theoretical functional network characteristics at an intracortical level. WM performance was uniquely correlated with power in the theta frequency, and theta power was increased by WM training. Moreover, the better a person's WM performance, the more their network exhibited small-world topology. WM training shifted network characteristics in the direction of high performers, showing increased small-worldness within a distributed fronto-parietal network. Taken together, this is the first longitudinal study that provides evidence for the plasticity of the functional brain network underlying WM. Copyright © 2013 Elsevier Ltd. All rights reserved.

A review of structural and functional brain networks: small world and atlas.

PubMed

Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Moore, Philip; Zheng, Jiaxiang

2015-03-01

Brain networks can be divided into two categories: structural and functional networks. Many studies of neuroscience have reported that the complex brain networks are characterized by small-world or scale-free properties. The identification of nodes is the key factor in studying the properties of networks on the macro-, micro- or mesoscale in both structural and functional networks. In the study of brain networks, nodes are always determined by atlases. Therefore, the selection of atlases is critical, and appropriate atlases are helpful to combine the analyses of structural and functional networks. Currently, some problems still exist in the establishment or usage of atlases, which are often caused by the segmentation or the parcellation of the brain. We suggest that quantification of brain networks might be affected by the selection of atlases to a large extent. In the process of building atlases, the influences of single subjects and groups should be balanced. In this article, we focused on the effects of atlases on the analysis of brain networks and the improved divisions based on the tractography or connectivity in the parcellation of atlases.

The brainstem reticular formation is a small-world, not scale-free, network

PubMed Central

Humphries, M.D; Gurney, K; Prescott, T.J

2005-01-01

Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called ‘small-world’ and ‘scale-free’ networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain—the medial reticular formation (RF) of the brainstem—and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement. PMID:16615219

"Small World" architecture in brain connectivity and hippocampal volume in Alzheimer's disease: a study via graph theory from EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Piludu, Francesca; Granata, Giuseppe; Romanello, Roberto; Caulo, Massimo; Onofrj, Valeria; Bramanti, Placido; Colosimo, Cesare; Rossini, Paolo Maria

2017-04-01

Brain imaging plays an important role in the study of Alzheimer's disease (AD), where atrophy has been found to occur in the hippocampal formation during the very early disease stages and to progress in parallel with the disease's evolution. The aim of the present study was to evaluate a possible correlation between "Small World" characteristics of the brain connectivity architecture-as extracted from EEG recordings-and hippocampal volume in AD patients. A dataset of 144 subjects, including 110 AD (MMSE 21.3) and 34 healthy Nold (MMSE 29.8) individuals, was evaluated. Weighted and undirected networks were built by the eLORETA solutions of the cortical sources' activities moving from EEG recordings. The evaluation of the hippocampal volume was carried out on a subgroup of 60 AD patients who received a high-resolution T1-weighted sequence and underwent processing for surface-based cortex reconstruction and volumetric segmentation using the Freesurfer image analysis software. Results showed that, quantitatively, more correlation was observed in the right hemisphere, but the same trend was seen in both hemispheres. Alpha band connectivity was negatively correlated, while slow (delta) and fast-frequency (beta, gamma) bands positively correlated with hippocampal volume. Namely, the larger the hippocampal volume, the lower the alpha and the higher the delta, beta, and gamma Small World characteristics of connectivity. Accordingly, the Small World connectivity pattern could represent a functional counterpart of structural hippocampal atrophying and related-network disconnection.

Small-world bias of correlation networks: From brain to climate

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan

2017-03-01

Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.

Small-world bias of correlation networks: From brain to climate.

PubMed

Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan

2017-03-01

Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.

Vulnerability of complex networks

NASA Astrophysics Data System (ADS)

Mishkovski, Igor; Biey, Mario; Kocarev, Ljupco

2011-01-01

We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős-Rényi (ER) random networks, Barabási-Albert (BA) model of scale-free networks, Watts-Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.

Positron Emission Tomography Reveals Abnormal Topological Organization in Functional Brain Network in Diabetic Patients.

PubMed

Qiu, Xiangzhe; Zhang, Yanjun; Feng, Hongbo; Jiang, Donglang

2016-01-01

Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM). However, the DM-related changes in the topological properties in functional brain networks are unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET) data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs), followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized characteristic path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing functional evidence for the abnormalities of brain networks in DM.

The topology of large Open Connectome networks for the human brain.

PubMed

Gastner, Michael T; Ódor, Géza

2016-06-07

The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.

The topology of large Open Connectome networks for the human brain

NASA Astrophysics Data System (ADS)

Gastner, Michael T.; Ódor, Géza

2016-06-01

The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.

Increased Small-World Network Topology Following Deployment-Acquired Traumatic Brain Injury Associated with the Development of Post-Traumatic Stress Disorder.

PubMed

Rowland, Jared A; Stapleton-Kotloski, Jennifer R; Dobbins, Dorothy L; Rogers, Emily; Godwin, Dwayne W; Taber, Katherine H

2018-05-01

Cross-sectional and longitudinal studies in active duty and veteran cohorts have both demonstrated that deployment-acquired traumatic brain injury (TBI) is an independent risk factor for developing post-traumatic stress disorder (PTSD), beyond confounds such as combat exposure, physical injury, predeployment TBI, and pre-deployment psychiatric symptoms. This study investigated how resting-state brain networks differ between individuals who developed PTSD and those who did not following deployment-acquired TBI. Participants included postdeployment veterans with deployment-acquired TBI history both with and without current PTSD diagnosis. Graph metrics, including small-worldness, clustering coefficient, and modularity, were calculated from individually constructed whole-brain networks based on 5-min eyes-open resting-state magnetoencephalography (MEG) recordings. Analyses were adjusted for age and premorbid IQ. Results demonstrated that participants with current PTSD displayed higher levels of small-worldness, F(1,12) = 5.364, p < 0.039, partial eta squared = 0.309, and Cohen's d = 0.972, and clustering coefficient, F(1, 12) = 12.204, p < 0.004, partial eta squared = 0.504, and Cohen's d = 0.905, than participants without current PTSD. There were no between-group differences in modularity or the number of modules present. These findings are consistent with a hyperconnectivity hypothesis of the effect of TBI history on functional networks rather than a disconnection hypothesis, demonstrating increased levels of clustering coefficient rather than a decrease as might be expected; however, these results do not account for potential changes in brain structure. These results demonstrate the potential pathological sequelae of changes in functional brain networks following deployment-acquired TBI and represent potential neurobiological changes associated with deployment-acquired TBI that may increase the risk of subsequently developing PTSD.

Enhanced functional connectivity properties of human brains during in-situ nature experience

PubMed Central

2016-01-01

In this study, we investigated the impacts of in-situ nature and urban exposure on human brain activities and their dynamics. We randomly assigned 32 healthy right-handed college students (mean age = 20.6 years, SD = 1.6; 16 males) to a 20 min in-situ sitting exposure in either a nature (n = 16) or urban environment (n = 16) and measured their Electroencephalography (EEG) signals. Analyses revealed that a brief in-situ restorative nature experience may induce more efficient and stronger brain connectivity with enhanced small-world properties compared with a stressful urban experience. The enhanced small-world properties were found to be correlated with “coherent” experience measured by Perceived Restorativeness Scale (PRS). Exposure to nature also induces stronger long-term correlated activity across different brain regions with a right lateralization. These findings may advance our understanding of the functional activities during in-situ environmental exposures and imply that a nature or nature-like environment may potentially benefit cognitive processes and mental well-being. PMID:27547533

Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Gorgoni, Maurizio; Ferrara, Michele; Iberite, Francesco; Bramanti, Placido; De Gennaro, Luigi; Rossini, Paolo Maria

2017-11-01

Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how "small world" characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness-sleep transition comparing the pre- and post-sleep onset epochs. The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset. Hum Brain Mapp 38:5456-5464, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

78 FR 32670 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-31

... Scientific Review Special Emphasis Panel; Fellowships: Brain Disorders, Language, Communication, and Related...: Center for Scientific Review Special Emphasis Panel; PAR Panel: Brain Disorders in the Developing World... Review Special Emphasis Panel; Small Business: Health Informatics. Date: June 28, 2013. Time: 8:30 a.m...

FPGA implementation of motifs-based neuronal network and synchronization analysis

NASA Astrophysics Data System (ADS)

Deng, Bin; Zhu, Zechen; Yang, Shuangming; Wei, Xile; Wang, Jiang; Yu, Haitao

2016-06-01

Motifs in complex networks play a crucial role in determining the brain functions. In this paper, 13 kinds of motifs are implemented with Field Programmable Gate Array (FPGA) to investigate the relationships between the networks properties and motifs properties. We use discretization method and pipelined architecture to construct various motifs with Hindmarsh-Rose (HR) neuron as the node model. We also build a small-world network based on these motifs and conduct the synchronization analysis of motifs as well as the constructed network. We find that the synchronization properties of motif determine that of motif-based small-world network, which demonstrates effectiveness of our proposed hardware simulation platform. By imitation of some vital nuclei in the brain to generate normal discharges, our proposed FPGA-based artificial neuronal networks have the potential to replace the injured nuclei to complete the brain function in the treatment of Parkinson's disease and epilepsy.

Metabolic Brain Network Analysis of Hypothyroidism Symptom Based on [18F]FDG-PET of Rats.

PubMed

Wan, Hongkai; Tan, Ziyu; Zheng, Qiang; Yu, Jing

2018-03-12

Recent researches have demonstrated the value of using 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) positron emission tomography (PET) imaging to reveal the hypothyroidism-related damages in local brain regions. However, the influence of hypothyroidism on the entire brain network is barely studied. This study focuses on the application of graph theory on analyzing functional brain networks of the hypothyroidism symptom. For both the hypothyroidism and the control groups of Wistar rats, the functional brain networks were constructed by thresholding the glucose metabolism correlation matrices of 58 brain regions. The network topological properties (including the small-world properties and the nodal centralities) were calculated and compared between the two groups. We found that the rat brains, like human brains, have typical properties of the small-world network in both the hypothyroidism and the control groups. However, the hypothyroidism group demonstrated lower global efficiency and decreased local cliquishness of the brain network, indicating hypothyroidism-related impairment to the brain network. The hypothyroidism group also has decreased nodal centrality in the left posterior hippocampus, the right hypothalamus, pituitary, pons, and medulla. This observation accorded with the hypothyroidism-related functional disorder of hypothalamus-pituitary-thyroid (HPT) feedback regulation mechanism. Our research quantitatively confirms that hypothyroidism hampers brain cognitive function by causing impairment to the brain network of glucose metabolism. This study reveals the feasibility and validity of applying graph theory method to preclinical [ 18 F]FDG-PET images and facilitates future study on human subjects.

Disrupted Structural and Functional Networks and Their Correlation with Alertness in Right Temporal Lobe Epilepsy: A Graph Theory Study.

PubMed

Jiang, Wenyu; Li, Jianping; Chen, Xuemei; Ye, Wei; Zheng, Jinou

2017-01-01

Previous studies have shown that temporal lobe epilepsy (TLE) involves abnormal structural or functional connectivity in specific brain areas. However, limited comprehensive studies have been conducted on TLE associated changes in the topological organization of structural and functional networks. Additionally, epilepsy is associated with impairment in alertness, a fundamental component of attention. In this study, structural networks were constructed using diffusion tensor imaging tractography, and functional networks were obtained from resting-state functional MRI temporal series correlations in 20 right temporal lobe epilepsy (rTLE) patients and 19 healthy controls. Global network properties were computed by graph theoretical analysis, and correlations were assessed between global network properties and alertness. The results from these analyses showed that rTLE patients exhibit abnormal small-world attributes in structural and functional networks. Structural networks shifted toward more regular attributes, but functional networks trended toward more random attributes. After controlling for the influence of the disease duration, negative correlations were found between alertness, small-worldness, and the cluster coefficient. However, alertness did not correlate with either the characteristic path length or global efficiency in rTLE patients. Our findings show that disruptions of the topological construction of brain structural and functional networks as well as small-world property bias are associated with deficits in alertness in rTLE patients. These data suggest that reorganization of brain networks develops as a mechanism to compensate for altered structural and functional brain function during disease progression.

Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study.

PubMed

Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong

2011-01-01

We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.

Altered brain functional networks in people with Internet gaming disorder: Evidence from resting-state fMRI.

PubMed

Wang, Lingxiao; Wu, Lingdan; Lin, Xiao; Zhang, Yifen; Zhou, Hongli; Du, Xiaoxia; Dong, Guangheng

2016-08-30

Although numerous neuroimaging studies have detected structural and functional abnormality in specific brain regions and connections in subjects with Internet gaming disorder (IGD), the topological organization of the whole-brain network in IGD remain unclear. In this study, we applied graph theoretical analysis to explore the intrinsic topological properties of brain networks in Internet gaming disorder (IGD). 37 IGD subjects and 35 matched healthy control (HC) subjects underwent a resting-state functional magnetic resonance imaging scan. The functional networks were constructed by thresholding partial correlation matrices of 90 brain regions. Then we applied graph-based approaches to analysis their topological attributes, including small-worldness, nodal metrics, and efficiency. Both IGD and HC subjects show efficient and economic brain network, and small-world topology. Although there was no significant group difference in global topology metrics, the IGD subjects showed reduced regional centralities in the prefrontal cortex, left posterior cingulate cortex, right amygdala, and bilateral lingual gyrus, and increased functional connectivity in sensory-motor-related brain networks compared to the HC subjects. These results imply that people with IGD may be associated with functional network dysfunction, including impaired executive control and emotional management, but enhanced coordination among visual, sensorimotor, auditory and visuospatial systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Analysis of the Characteristics of Infantile Small World Neural Network Node Properties Correlated with the Influencing Factors].

PubMed

Qu, Haibo; Lu, Su; Zhang, Wenjing; Xiao, Yuan; Ning, Gang; Sun, Huaiqiang

2016-10-01

We applied resting-state functional magnetic resonance imaging(rfMRI)combined with graph theory to analyze 90 regions of the infantile small world neural network of the whole brain.We tried to get the following two points clear:1 whether the parameters of the node property of the infantile small world neural network are correlated with the level of infantile intelligence development;2 whether the parameters of the infantile small world neural network are correlated with the children’s baseline parameters,i.e.,the demographic parameters such as gender,age,parents’ education level,etc.Twelve cases of healthy infants were included in the investigation(9males and 3females with the average age of 33.42±8.42 months.)We then evaluated the level of infantile intelligence of all the cases and graded by Gesell Development Scale Test.We used a Siemens 3.0T Trio imaging system to perform resting-state(rs)EPI scans,and collected the BOLD functional Magnetic Resonance Imaging(fMRI)data.We performed the data processing with Statistical Parametric Mapping 5(SPM5)based on Matlab environment.Furthermore,we got the attributes of the whole brain small world and node attributes of 90 encephalic regions of templates of Anatomatic Automatic Labeling(ALL).At last,we carried out correlation study between the above-mentioned attitudes,intelligence scale parameters and demographic data.The results showed that many node attributes of small world neural network were closely correlated with intelligence scale parameters.Betweeness was mainly centered in thalamus,superior frontal gyrus,and occipital lobe(negative correlation).The r value of superior occipital gyrus associated with the individual and social intelligent scale was-0.729(P=0.007);degree was mainly centered in amygdaloid nucleus,superior frontal gyrus,and inferior parietal gyrus(positive correlation).The r value of inferior parietal gyrus associated with the gross motor intelligent scale was 0.725(P=0.008);efficiency was mainly centered in inferior frontal gyrus,inferior parietal gyrus,and insular lobe(positive correlation).The r value of inferior parietal gyrus associated with the language intelligent scale was 0.738(P=0.006);Anoda cluster coefficient(anodalCp)was centered in frontal lobe,inferior parietal gyrus,and paracentral lobule(positive correlation);Node shortest path length(nlp)was centered in frontal lobe,inferior parietal gyrus,and insular lobe.The distribution of the encephalic regions in the left and right brain was different.However,no statistical significance was found between the correlation of monolithic attributes of small world and intelligence scale.The encephalic regions,in which node attributes of small world were related to other demographic indices,were mainly centered in temporal lobe,cuneus,cingulated gyrus,angular gyrus,and paracentral lobule areas.Most of them belong to the default mode network(DMN).The node attributes of small world neural network are widely related to infantile intelligence level,moreover the distribution is characteristic in different encephalic regions.The distribution of dominant encephalic is in accordance the related functions.The existing correlations reflect the ever changing small world nervous network during infantile development.

Clinical data from the real world: efficacy of Crizotinib in Chinese patients with advanced ALK-rearranged non-small cell lung cancer and brain metastases.

PubMed

Xing, Puyuan; Wang, Shouzheng; Hao, Xuezhi; Zhang, Tongtong; Li, Junling

2016-12-20

Brain metastasis in non small cell lung cancer (NSCLC) patients is often considered as a terminal stage of advanced disease. Crizotinib is a small-molecule tyrosine kinase inhibitor (TKI) for ALK-rearranged NSCLC patients. Herein, we conducted a retrospective study to explore how Crizotinib affects the control of brain metastases and the overall prognosis in advanced ALK-rearranged NSCLC patients with brain metastases in Chinese population. A total of 34 patients were enrolled, of whom 20 (58.8%) patients had baseline brain metastases before Crizotinib treatment. Among patients with brain metastases before Crizotinib, overall survival (OS) after brain metastases was significantly longer than that of patients with brain metastases after Crizotinib (median OS, not reached vs. 10.3 months, respectively, p = 0.001). There was also a significant difference in systemic progression-free survival (PFS) between patients developing brain metastases before and after Crizotinib treatment (21.2 months vs. 13.9 months, p = 0.003). In conclusion, ALK-rearranged NSCLC patients with brain metastases before Crizotinib may benefit more from Crizotinib than those developing brain metastases during Crizotinib treatment.

Levodopa modulates small-world architecture of functional brain networks in Parkinson's disease.

PubMed

Berman, Brian D; Smucny, Jason; Wylie, Korey P; Shelton, Erika; Kronberg, Eugene; Leehey, Maureen; Tregellas, Jason R

2016-11-01

PD is associated with disrupted connectivity to a large number of distributed brain regions. How the disease alters the functional topological organization of the brain, however, remains poorly understood. Furthermore, how levodopa modulates network topology in PD is largely unknown. The objective of this study was to use resting-state functional MRI and graph theory to determine how small-world architecture is altered in PD and affected by levodopa administration. Twenty-one PD patients and 20 controls underwent functional MRI scanning. PD patients were scanned off medication and 1 hour after 200 mg levodopa. Imaging data were analyzed using 226 nodes comprising 10 intrinsic brain networks. Correlation matrices were generated for each subject and converted into cost-thresholded, binarized adjacency matrices. Cost-integrated whole-brain global and local efficiencies were compared across groups and tested for relationships with disease duration and severity. Data from 2 patients and 4 controls were excluded because of excess motion. Patients off medication showed no significant changes in global efficiency and overall local efficiency, but in a subnetwork analysis did show increased local efficiency in executive (P = 0.006) and salience (P = 0.018) networks. Levodopa significantly decreased local efficiency (P = 0.039) in patients except within the subcortical network, in which it significantly increased local efficiency (P = 0.007). Levodopa modulates global and local efficiency measures of small-world topology in PD, suggesting that degeneration of nigrostriatal neurons in PD may be associated with a large-scale network reorganization and that levodopa tends to normalize the disrupted network topology in PD. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Disrupted functional connectome in antisocial personality disorder.

PubMed

Jiang, Weixiong; Shi, Feng; Liao, Jian; Liu, Huasheng; Wang, Tao; Shen, Celina; Shen, Hui; Hu, Dewen; Wang, Wei; Shen, Dinggang

2017-08-01

Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD.

Disrupted functional connectome in antisocial personality disorder

PubMed Central

Jiang, Weixiong; Shi, Feng; Liao, Jian; Liu, Huasheng; Wang, Tao; Shen, Celina; Shen, Hui; Hu, Dewen

2017-01-01

Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD. PMID:27541949

Brain Network Analysis from High-Resolution EEG Signals

NASA Astrophysics Data System (ADS)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an effective methodology improving the comprehension of the complex interactions in the brain.

Dysfunctional whole brain networks in mild cognitive impairment patients: an fMRI study

NASA Astrophysics Data System (ADS)

Liu, Zhenyu; Bai, Lijun; Dai, Ruwei; Zhong, Chongguang; Xue, Ting; You, Youbo; Tian, Jie

2012-03-01

Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimer's disease (AD). Recent researches have shown that cognitive and memory decline in AD patients is coupled with losses of small-world attributes. However, few studies pay attention to the characteristics of the whole brain networks in MCI patients. In the present study, we investigated the topological properties of the whole brain networks utilizing graph theoretical approaches in 16 MCI patients, compared with 18 age-matched healthy subjects as a control. Both MCI patients and normal controls showed small-world architectures, with large clustering coefficients and short characteristic path lengths. We detected significantly longer characteristic path length in MCI patients compared with normal controls at the low sparsity. The longer characteristic path lengths in MCI indicated disrupted information processing among distant brain regions. Compared with normal controls, MCI patients showed decreased nodal centrality in the brain areas of the angular gyrus, heschl gyrus, hippocampus and superior parietal gyrus, while increased nodal centrality in the calcarine, inferior occipital gyrus and superior frontal gyrus. These changes in nodal centrality suggested a widespread rewiring in MCI patients, which may be an integrated reflection of reorganization of the brain networks accompanied with the cognitive decline. Our findings may be helpful for further understanding the pathological mechanisms of MCI.

The Neonatal Connectome During Preterm Brain Development

PubMed Central

van den Heuvel, Martijn P.; Kersbergen, Karina J.; de Reus, Marcel A.; Keunen, Kristin; Kahn, René S.; Groenendaal, Floris; de Vries, Linda S.; Benders, Manon J.N.L.

2015-01-01

The human connectome is the result of an elaborate developmental trajectory. Acquiring diffusion-weighted imaging and resting-state fMRI, we studied connectome formation during the preterm phase of macroscopic connectome genesis. In total, 27 neonates were scanned at week 30 and/or week 40 gestational age (GA). Examining the architecture of the neonatal anatomical brain network revealed a clear presence of a small-world modular organization before term birth. Analysis of neonatal functional connectivity (FC) showed the early formation of resting-state networks, suggesting that functional networks are present in the preterm brain, albeit being in an immature state. Moreover, structural and FC patterns of the neonatal brain network showed strong overlap with connectome architecture of the adult brain (85 and 81%, respectively). Analysis of brain development between week 30 and week 40 GA revealed clear developmental effects in neonatal connectome architecture, including a significant increase in white matter microstructure (P < 0.01), small-world topology (P < 0.01) and interhemispheric FC (P < 0.01). Computational analysis further showed that developmental changes involved an increase in integration capacity of the connectivity network as a whole. Taken together, we conclude that hallmark organizational structures of the human connectome are present before term birth and subject to early development. PMID:24833018

Altered characteristic of brain networks in mild cognitive impairment during a selective attention task: An EEG study.

PubMed

Wei, Ling; Li, Yingjie; Yang, Xiaoli; Xue, Qing; Wang, Yuping

2015-10-01

The present study evaluated the topological properties of whole brain networks using graph theoretical concepts and investigated the time-evolution characteristic of brain network in mild cognitive impairment patients during a selective attention task. Electroencephalography (EEG) activities were recorded in 10 MCI patients and 17 healthy subjects when they performed a color match task. We calculated the phase synchrony index between each possible pairs of EEG channels in alpha and beta frequency bands and analyzed the local interconnectedness, overall connectedness and small-world characteristic of brain network in different degree for two groups. Relative to healthy normal controls, the properties of cortical networks in MCI patients tend to be a shift of randomization. Lower σ of MCI had suggested that patients had a further loss of small-world attribute both during active and resting states. Our results provide evidence for the functional disconnection of brain regions in MCI. Furthermore, we found the properties of cortical networks could reflect the processing of conflict information in the selective attention task. The human brain tends to be a more regular and efficient neural architecture in the late stage of information processing. In addition, the processing of conflict information needs stronger information integration and transfer between cortical areas. Copyright © 2015 Elsevier B.V. All rights reserved.

Altered brain network measures in patients with primary writing tremor.

PubMed

Lenka, Abhishek; Jhunjhunwala, Ketan Ramakant; Panda, Rajanikant; Saini, Jitender; Bharath, Rose Dawn; Yadav, Ravi; Pal, Pramod Kumar

2017-10-01

Primary writing tremor (PWT) is a rare task-specific tremor, which occurs only while writing or while adopting the hand in the writing position. The basic pathophysiology of PWT has not been fully understood. The objective of this study is to explore the alterations in the resting state functional brain connectivity, if any, in patients with PWT using graph theory-based analysis. This prospective case-control study included 10 patients with PWT and 10 age and gender matched healthy controls. All subjects underwent MRI in a 3-Tesla scanner. Several parameters of small-world functional connectivity were compared between patients and healthy controls by using graph theory-based analysis. There were no significant differences in age, handedness (all right handed), gender distribution (all were males), and MMSE scores between the patients and controls. The mean age at presentation of tremor in the patient group was 51.7 ± 8.6 years, and the mean duration of tremor was 3.5 ± 1.9 years. Graph theory-based analysis revealed that patients with PWT had significantly lower clustering coefficient and higher path length compared to healthy controls suggesting alterations in small-world architecture of the brain. The clustering coefficients were lower in PWT patients in left and right medial cerebellum, right dorsolateral prefrontal cortex (DLPFC), and left posterior parietal cortex (PPC). Patients with PWT have significantly altered small-world brain connectivity in bilateral medial cerebellum, right DLPFC, and left PPC. Further studies with larger sample size are required to confirm our results.

Functional brain networks in Alzheimer's disease: EEG analysis based on limited penetrable visibility graph and phase space method

NASA Astrophysics Data System (ADS)

Wang, Jiang; Yang, Chen; Wang, Ruofan; Yu, Haitao; Cao, Yibin; Liu, Jing

2016-10-01

In this paper, EEG series are applied to construct functional connections with the correlation between different regions in order to investigate the nonlinear characteristic and the cognitive function of the brain with Alzheimer's disease (AD). First, limited penetrable visibility graph (LPVG) and phase space method map single EEG series into networks, and investigate the underlying chaotic system dynamics of AD brain. Topological properties of the networks are extracted, such as average path length and clustering coefficient. It is found that the network topology of AD in several local brain regions are different from that of the control group with no statistically significant difference existing all over the brain. Furthermore, in order to detect the abnormality of AD brain as a whole, functional connections among different brain regions are reconstructed based on similarity of clustering coefficient sequence (CCSS) of EEG series in the four frequency bands (delta, theta, alpha, and beta), which exhibit obvious small-world properties. Graph analysis demonstrates that for both methodologies, the functional connections between regions of AD brain decrease, particularly in the alpha frequency band. AD causes the graph index complexity of the functional network decreased, the small-world properties weakened, and the vulnerability increased. The obtained results show that the brain functional network constructed by LPVG and phase space method might be more effective to distinguish AD from the normal control than the analysis of single series, which is helpful for revealing the underlying pathological mechanism of the disease.

Evaluating the Small-World-Ness of a Sampled Network: Functional Connectivity of Entorhinal-Hippocampal Circuitry

NASA Astrophysics Data System (ADS)

She, Qi; Chen, Guanrong; Chan, Rosa H. M.

2016-02-01

The amount of publicly accessible experimental data has gradually increased in recent years, which makes it possible to reconsider many longstanding questions in neuroscience. In this paper, an efficient framework is presented for reconstructing functional connectivity using experimental spike-train data. A modified generalized linear model (GLM) with L1-norm penalty was used to investigate 10 datasets. These datasets contain spike-train data collected from the entorhinal-hippocampal region in the brains of rats performing different tasks. The analysis shows that entorhinal-hippocampal network of well-trained rats demonstrated significant small-world features. It is found that the connectivity structure generated by distance-dependent models is responsible for the observed small-world features of the reconstructed networks. The models are utilized to simulate a subset of units recorded from a large biological neural network using multiple electrodes. Two metrics for quantifying the small-world-ness both suggest that the reconstructed network from the sampled nodes estimates a more prominent small-world-ness feature than that of the original unknown network when the number of recorded neurons is small. Finally, this study shows that it is feasible to adjust the estimated small-world-ness results based on the number of neurons recorded to provide a more accurate reference of the network property.

Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence

PubMed Central

Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C.; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi

2013-01-01

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence. PMID:23390528

Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

PubMed

Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi

2013-01-01

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

Neuronal factors determining high intelligence.

PubMed

Dicke, Ursula; Roth, Gerhard

2016-01-05

Many attempts have been made to correlate degrees of both animal and human intelligence with brain properties. With respect to mammals, a much-discussed trait concerns absolute and relative brain size, either uncorrected or corrected for body size. However, the correlation of both with degrees of intelligence yields large inconsistencies, because although they are regarded as the most intelligent mammals, monkeys and apes, including humans, have neither the absolutely nor the relatively largest brains. The best fit between brain traits and degrees of intelligence among mammals is reached by a combination of the number of cortical neurons, neuron packing density, interneuronal distance and axonal conduction velocity--factors that determine general information processing capacity (IPC), as reflected by general intelligence. The highest IPC is found in humans, followed by the great apes, Old World and New World monkeys. The IPC of cetaceans and elephants is much lower because of a thin cortex, low neuron packing density and low axonal conduction velocity. By contrast, corvid and psittacid birds have very small and densely packed pallial neurons and relatively many neurons, which, despite very small brain volumes, might explain their high intelligence. The evolution of a syntactical and grammatical language in humans most probably has served as an additional intelligence amplifier, which may have happened in songbirds and psittacids in a convergent manner. © 2015 The Author(s).

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

PubMed Central

Zheng, Gaoxing; Qi, Xiaoying; Li, Yuzhu; Zhang, Wei; Yu, Yuguo

2018-01-01

The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG) signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST) has been increasingly applied, while the average reference (AR) was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening). The analysis results revealed the following observations: (1) there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2) there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3) the global brain functional connectivity density (FCD) and local FCD have higher values for REST than for AR under different behavior states; and (4) the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands) higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording. PMID:29593490

Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach.

PubMed

Min, Yu-Sun; Chang, Yongmin; Park, Jang Woo; Lee, Jong-Min; Cha, Jungho; Yang, Jin-Ju; Kim, Chul-Hyun; Hwang, Jong-Moon; Yoo, Ji-Na; Jung, Tae-Du

2015-06-01

To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls. Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55±14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9±13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness. Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected). The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.

Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

NASA Astrophysics Data System (ADS)

Stoop, Ralph; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

2013-03-01

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic—intercolumnar—scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

PubMed

Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Progressive gender differences of structural brain networks in healthy adults: a longitudinal, diffusion tensor imaging study.

PubMed

Sun, Yu; Lee, Renick; Chen, Yu; Collinson, Simon; Thakor, Nitish; Bezerianos, Anastasios; Sim, Kang

2015-01-01

Sexual dimorphism in the brain maturation during childhood and adolescence has been repeatedly documented, which may underlie the differences in behaviors and cognitive performance. However, our understanding of how gender modulates the development of structural connectome in healthy adults is still not entirely clear. Here we utilized graph theoretical analysis of longitudinal diffusion tensor imaging data over a five-year period to investigate the progressive gender differences of brain network topology. The brain networks of both genders showed prominent economical "small-world" architecture (high local clustering and short paths between nodes). Additional analysis revealed a more economical "small-world" architecture in females as well as a greater global efficiency in males regardless of scan time point. At the regional level, both increased and decreased efficiency were found across the cerebral cortex for both males and females, indicating a compensation mechanism of cortical network reorganization over time. Furthermore, we found that weighted clustering coefficient exhibited significant gender-time interactions, implying different development trends between males and females. Moreover, several specific brain regions (e.g., insula, superior temporal gyrus, cuneus, putamen, and parahippocampal gyrus) exhibited different development trajectories between males and females. Our findings further prove the presence of sexual dimorphism in brain structures that may underlie gender differences in behavioral and cognitive functioning. The sex-specific progress trajectories in brain connectome revealed in this work provide an important foundation to delineate the gender related pathophysiological mechanisms in various neuropsychiatric disorders, which may potentially guide the development of sex-specific treatments for these devastating brain disorders.

Small Worldness in Dense and Weighted Connectomes

NASA Astrophysics Data System (ADS)

Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas

2016-05-01

The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.

Cerebral complexity preceded enlarged brain size and reduced olfactory bulbs in Old World monkeys

PubMed Central

Gonzales, Lauren A.; Benefit, Brenda R.; McCrossin, Monte L.; Spoor, Fred

2015-01-01

Analysis of the only complete early cercopithecoid (Old World monkey) endocast currently known, that of 15-million-year (Myr)-old Victoriapithecus, reveals an unexpectedly small endocranial volume (ECV) relative to body size and a large olfactory bulb volume relative to ECV, similar to extant lemurs and Oligocene anthropoids. However, the Victoriapithecus brain has principal and arcuate sulci of the frontal lobe not seen in the stem catarrhine Aegyptopithecus, as well as a distinctive cercopithecoid pattern of gyrification, indicating that cerebral complexity preceded encephalization in cercopithecoids. Since larger ECVs, expanded frontal lobes, and reduced olfactory bulbs are already present in the 17- to 18-Myr-old ape Proconsul these features evolved independently in hominoids (apes) and cercopithecoids and much earlier in the former. Moreover, the order of encephalization and brain reorganization was apparently different in hominoids and cercopithecoids, showing that brain size and cerebral organization evolve independently. PMID:26138795

Self-organized Criticality in Hierarchical Brain Network

NASA Astrophysics Data System (ADS)

Yang, Qiu-Ying; Zhang, Ying-Yue; Chen, Tian-Lun

2008-11-01

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

Functional connectivity patterns of normal human swallowing: difference among various viscosity swallows in normal and chin-tuck head positions

PubMed Central

Jestrović, Iva; Coyle, James L.; Perera, Subashan

2016-01-01

Consuming thicker fluids and swallowing in the chin-tuck position has been shown to be advantageous for some patients with neurogenic dysphagia who aspirate due to various causes. The anatomical changes caused by these therapeutic techniques are well known, but it is unclear whether these changes alter the cerebral processing of swallow-related sensorimotor activity. We sought to investigate the effect of increased fluid viscosity and chin-down posture during swallowing on brain networks. 55 healthy adults performed water, nectar-thick, and honey thick liquid swallows in the neutral and chin-tuck positions while EEG signals were recorded. After pre-processing of the EEG timeseries, the time-frequency based synchrony measure was used for forming the brain networks to investigate whether there were differences among the brain networks between the swallowing of different fluid viscosities and swallowing in different head positions. We also investigated whether swallowing under various conditions exhibit small-world properties. Results showed that fluid viscosity affects the brain network in the Delta, Theta, Alpha, Beta, and Gamma frequency bands and that swallowing in the chin-tuck head position affects brain networks in the Alpha, Beta, and Gamma frequency bands. In addition, we showed that swallowing in all tested conditions exhibited small-world properties. Therefore, fluid viscosity and head positions should be considered in future swallowing EEG investigations. PMID:27693396

Brain cancer associated with environmental lead exposure: evidence from implementation of a National Petrol-Lead Phase-Out Program (PLPOP) in Taiwan between 1979 and 2007.

PubMed

Wu, Wei-Te; Lin, Yu-Jen; Liou, Saou-Hsing; Yang, Chun-Yuh; Cheng, Kuang-Fu; Tsai, Perng-Jy; Wu, Trong-Neng

2012-04-01

In 1981, a Petrol-Lead Phase-Out Program (PLPOP) was launched in Taiwan for the abatement of environmental lead emissions. The present study was intended to examine whether the high Petrol-Lead Emission Areas (PLEA) would result in an increase in the incidence rate of brain cancer based on a national data bank. The national brain cancer incidence data was obtained from the Taiwan National Cancer Registry. Age standardized incidence rates were calculated based on the 2000 WHO world standard population, and gasoline consumption data was obtained from the Bureau of Energy. The differences in the trend tests for age-standardized incidence rates of brain cancer between high, median, low, and small PLEA were analyzed. A significant increase was found from small to high PLEA in age-standardized incidence rates of brain cancer. By taking six possible confounders into account, the age-standardized incidence rates for brain cancer were highly correlated with the median and high PLEA by reference to the small PLEA. After being adjusted for a number of relevant confounders, it could be concluded that high PLEA might result in an increase in the incidence rate of brain cancer resulting from high lead exposures. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dopamine precursor depletion impairs structure and efficiency of resting state brain functional networks.

PubMed

Carbonell, Felix; Nagano-Saito, Atsuko; Leyton, Marco; Cisek, Paul; Benkelfat, Chawki; He, Yong; Dagher, Alain

2014-09-01

Spatial patterns of functional connectivity derived from resting brain activity may be used to elucidate the topological properties of brain networks. Such networks are amenable to study using graph theory, which shows that they possess small world properties and can be used to differentiate healthy subjects and patient populations. Of particular interest is the possibility that some of these differences are related to alterations in the dopamine system. To investigate the role of dopamine in the topological organization of brain networks at rest, we tested the effects of reducing dopamine synthesis in 13 healthy subjects undergoing functional magnetic resonance imaging. All subjects were scanned twice, in a resting state, following ingestion of one of two amino acid drinks in a randomized, double-blind manner. One drink was a nutritionally balanced amino acid mixture, and the other was tyrosine and phenylalanine deficient. Functional connectivity between 90 cortical and subcortical regions was estimated for each individual subject under each dopaminergic condition. The lowered dopamine state caused the following network changes: reduced global and local efficiency of the whole brain network, reduced regional efficiency in limbic areas, reduced modularity of brain networks, and greater connection between the normally anti-correlated task-positive and default-mode networks. We conclude that dopamine plays a role in maintaining the efficient small-world properties and high modularity of functional brain networks, and in segregating the task-positive and default-mode networks. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Changes in Brain Structural Networks and Cognitive Functions in Testicular Cancer Patients Receiving Cisplatin-Based Chemotherapy.

PubMed

Amidi, Ali; Hosseini, S M Hadi; Leemans, Alexander; Kesler, Shelli R; Agerbæk, Mads; Wu, Lisa M; Zachariae, Robert

2017-12-01

Cisplatin-based chemotherapy may have neurotoxic effects within the central nervous system. The aims of this study were 1) to longitudinally investigate the impact of cisplatin-based chemotherapy on whole-brain networks in testicular cancer patients undergoing treatment and 2) to explore whether possible changes are related to decline in cognitive functioning. Sixty-four newly orchiectomized TC patients underwent structural magnetic resonance imaging (T1-weighted and diffusion-weighted imaging) and cognitive testing at baseline prior to further treatment and again at a six-month follow-up. At follow-up, 22 participants had received cisplatin-based chemotherapy (CT) while 42 were in active surveillance (S). Brain structural networks were constructed for each participant, and network properties were investigated using graph theory and longitudinally compared across groups. Cognitive functioning was evaluated using standardized neuropsychological tests. All statistical tests were two-sided. Compared with the S group, the CT group demonstrated altered global and local brain network properties from baseline to follow-up as evidenced by decreases in important brain network properties such as small-worldness (P = .04), network clustering (P = .04), and local efficiency (P = .02). In the CT group, poorer overall cognitive performance was associated with decreased small-worldness (r = -0.46, P = .04) and local efficiency (r = -0.51, P = .02), and verbal fluency was associated with decreased local efficiency (r = -0.55, P = .008). Brain structural networks may be disrupted following treatment with cisplatin-based chemotherapy. Impaired brain networks may underlie poorer performance over time on both specific and nonspecific cognitive functions in patients undergoing chemotherapy. To the best of our knowledge, this is the first study to longitudinally investigate changes in structural brain networks in a cancer population, providing novel insights regarding the neurobiological mechanisms of cancer-related cognitive impairment.

Modern network science of neurological disorders.

PubMed

Stam, Cornelis J

2014-10-01

Modern network science has revealed fundamental aspects of normal brain-network organization, such as small-world and scale-free patterns, hierarchical modularity, hubs and rich clubs. The next challenge is to use this knowledge to gain a better understanding of brain disease. Recent developments in the application of network science to conditions such as Alzheimer's disease, multiple sclerosis, traumatic brain injury and epilepsy have challenged the classical concept of neurological disorders being either 'local' or 'global', and have pointed to the overload and failure of hubs as a possible final common pathway in neurological disorders.

Temporal efficiency evaluation and small-worldness characterization in temporal networks

PubMed Central

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-01-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks. PMID:27682314

Temporal efficiency evaluation and small-worldness characterization in temporal networks

NASA Astrophysics Data System (ADS)

Dai, Zhongxiang; Chen, Yu; Li, Junhua; Fam, Johnson; Bezerianos, Anastasios; Sun, Yu

2016-09-01

Numerous real-world systems can be modeled as networks. To date, most network studies have been conducted assuming stationary network characteristics. Many systems, however, undergo topological changes over time. Temporal networks, which incorporate time into conventional network models, are therefore more accurate representations of such dynamic systems. Here, we introduce a novel generalized analytical framework for temporal networks, which enables 1) robust evaluation of the efficiency of temporal information exchange using two new network metrics and 2) quantitative inspection of the temporal small-worldness. Specifically, we define new robust temporal network efficiency measures by incorporating the time dependency of temporal distance. We propose a temporal regular network model, and based on this plus the redefined temporal efficiency metrics and widely used temporal random network models, we introduce a quantitative approach for identifying temporal small-world architectures (featuring high temporal network efficiency both globally and locally). In addition, within this framework, we can uncover network-specific dynamic structures. Applications to brain networks, international trade networks, and social networks reveal prominent temporal small-world properties with distinct dynamic network structures. We believe that the framework can provide further insight into dynamic changes in the network topology of various real-world systems and significantly promote research on temporal networks.

Large-scale cortical volume correlation networks reveal disrupted small world patterns in Parkinson's disease.

PubMed

Wu, Qiong; Gao, Yang; Liu, Ai-Shi; Xie, Li-Zhi; Qian, Long; Yang, Xiao-Guang

2018-01-01

To date, the most frequently reported neuroimaging biomarkers in Parkinson's disease (PD) are direct brain imaging measurements focusing on local disrupted regions. However, the notion that PD is related to abnormal functional and structural connectivity has received support in the past few years. Here, we employed graph theory to analyze the structural co-variance networks derived from 50 PD patients and 48 normal controls (NC). Then, the small world properties of brain networks were assessed in the structural networks that were constructed based on cortical volume data. Our results showed that both the PD and NC groups had a small world architecture in brain structural networks. However, the PD patients had a higher characteristic path length and clustering coefficients compared with the NC group. With regard to the nodal centrality, 11 regions, including 3 association cortices, 5 paralimbic cortices, and 3 subcortical regions were identified as hubs in the PD group. In contrast, 10 regions, including 7 association cortical regions, 2 paralimbic cortical regions, and the primary motor cortex region, were identified as hubs. Moreover, the regional centrality was profoundly affected in PD patients, including decreased nodal centrality in the right inferior occipital gyrus and the middle temporal gyrus and increased nodal centrality in the right amygdala, the left caudate and the superior temporal gyrus. In addition, the structural cortical network of PD showed reduced topological stability for targeted attacks. Together, this study shows that the coordinated patterns of cortical volume network are widely altered in PD patients with a decrease in the efficiency of parallel information processing. These changes provide structural evidence to support the concept that the core pathophysiology of PD is associated with disruptive alterations in the coordination of large-scale brain networks that underlie high-level cognition. Copyright © 2017. Published by Elsevier B.V.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

Functional connectivity patterns of normal human swallowing: difference among various viscosity swallows in normal and chin-tuck head positions.

PubMed

Jestrović, Iva; Coyle, James L; Perera, Subashan; Sejdić, Ervin

2016-12-01

Consuming thicker fluids and swallowing in the chin-tuck position has been shown to be advantageous for some patients with neurogenic dysphagia who aspirate due to various causes. The anatomical changes caused by these therapeutic techniques are well known, but it is unclear whether these changes alter the cerebral processing of swallow-related sensorimotor activity. We sought to investigate the effect of increased fluid viscosity and chin-down posture during swallowing on brain networks. 55 healthy adults performed water, nectar-thick, and honey thick liquid swallows in the neutral and chin-tuck positions while EEG signals were recorded. After pre-processing of the EEG timeseries, the time-frequency based synchrony measure was used for forming the brain networks to investigate whether there were differences among the brain networks between the swallowing of different fluid viscosities and swallowing in different head positions. We also investigated whether swallowing under various conditions exhibit small-world properties. Results showed that fluid viscosity affects the brain network in the Delta, Theta, Alpha, Beta, and Gamma frequency bands and that swallowing in the chin-tuck head position affects brain networks in the Alpha, Beta, and Gamma frequency bands. In addition, we showed that swallowing in all tested conditions exhibited small-world properties. Therefore, fluid viscosity and head positions should be considered in future swallowing EEG investigations. Copyright © 2016 Elsevier B.V. All rights reserved.

Functional organization of intrinsic connectivity networks in Chinese-chess experts.

PubMed

Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

2014-04-16

The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

Teaching face-name associations to survivors of traumatic brain injury: a sequential treatment approach.

PubMed

Manasse, N J; Hux, K; Snell, J

2005-08-10

Recalling names in real-world contexts is often difficult for survivors of traumatic brain injury despite successful completion of face-name association training programmes. This small number study utilized a sequential treatment approach in which a traditional training programme preceded real-world training. The traditional training component was identical across programmes: one-on-one intervention using visual imagery and photographs to assist in mastery of face-name associations. The real-world training component compared the effectiveness of three cueing strategies--name restating, phonemic cueing and visual imagery--and was conducted by the actual to-be-named people. Results revealed improved name learning and use by the participants regardless of cueing strategy. After treatment targeting six names, four of five participants consistently used two or more names spontaneously and consistently knew three or more names in response to questioning. In addition to documenting the effectiveness of real-world treatment paradigms, the findings call into question the necessity for preliminary traditional intervention.

Role of physical and mental training in brain network configuration

PubMed Central

Foster, Philip P.

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of “energy cost-driven small-world network disorder” with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.). However, mental training, meditation or virtual reality (films, games) require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com.) molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g., amyotrophic lateral sclerosis, traumatism) also achieve successful cognitive enhancement albeit they may only elicit mental practice. PMID:26157387

Role of physical and mental training in brain network configuration.

PubMed

Foster, Philip P

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of "energy cost-driven small-world network disorder" with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.). However, mental training, meditation or virtual reality (films, games) require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com.) molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g., amyotrophic lateral sclerosis, traumatism) also achieve successful cognitive enhancement albeit they may only elicit mental practice.

Functional disorganization of small-world brain networks in mild Alzheimer's Disease and amnestic Mild Cognitive Impairment: an EEG study using Relative Wavelet Entropy (RWE).

PubMed

Frantzidis, Christos A; Vivas, Ana B; Tsolaki, Anthoula; Klados, Manousos A; Tsolaki, Magda; Bamidis, Panagiotis D

2014-01-01

Previous neuroscientific findings have linked Alzheimer's Disease (AD) with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI) remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD). Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG) data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT), and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N = 500, 600, 700, 800 edges) across all participants and groups (fixed density values). All groups exhibited a small-world (SW) brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant's generic cognitive status. The deterioration of the network's organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.

Altered brain network modules induce helplessness in major depressive disorder.

PubMed

Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Fang, Yiru; Shen, Dinggang

2014-10-01

The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. Copyright © 2014 Elsevier B.V. All rights reserved.

Altered brain network modules induce helplessness in major depressive disorder

PubMed Central

Peng, Daihui; Shi, Feng; Shen, Ting; Peng, Ziwen; Zhang, Chen; Liu, Xiaohua; Qiu, Meihui; Liu, Jun; Jiang, Kaida; Shen, Dinggang

2017-01-01

Objective The abnormal brain functional connectivity (FC) has been assumed to be a pathophysiological aspect of major depressive disorder (MDD). However, it is poorly understood, regarding the underlying patterns of global FC network and their relationships with the clinical characteristics of MDD. Methods Resting-state functional magnetic resonance imaging data were acquired from 16 first episode, medication-naïve MDD patients and 16 healthy control subjects. The global FC network was constructed using 90 brain regions. The global topological patterns, e.g., small-worldness and modularity, and their relationships with depressive characteristics were investigated. Furthermore, the participant coefficient and module degree of MDD patients were measured to reflect the regional roles in module network, and the impairment of FC was examined by network based statistic. Results Small-world property was not altered in MDD. However, MDD patients exhibited 5 atypically reorganized modules compared to the controls. A positive relationship was also found among MDD patients between the intra-module I and helplessness factor evaluated via the Hamilton Depression Scale. Specifically, eight regions exhibited the abnormal participant coefficient or module degree, e.g., left superior orbital frontal cortex and right amygdala. The decreased FC was identified among the sub-network of 24 brain regions, e.g., frontal cortex, supplementary motor area, amygdala, thalamus, and hippocampus. Limitation The limited size of MDD samples precluded meaningful study of distinct clinical characteristics in relation to aberrant FC. Conclusions The results revealed altered patterns of brain module network at the global level in MDD patients, which might contribute to the feelings of helplessness. PMID:25033474

Disrupted resting brain graph measures in individuals at high risk for alcoholism.

PubMed

Holla, Bharath; Panda, Rajanikant; Venkatasubramanian, Ganesan; Biswal, Bharat; Bharath, Rose Dawn; Benegal, Vivek

2017-07-30

Familial susceptibility to alcoholism is likely to be linked to the externalizing diathesis seen in high-risk offspring from high-density alcohol use disorder (AUD) families. The present study aimed at comparing resting brain functional connectivity and their association with externalizing symptoms and alcoholism familial density in 40 substance-naive high-risk (HR) male offspring from high-density AUD families and 30 matched healthy low-risk (LR) males without a family history of substance dependence using graph theory-based network analysis. The HR subjects from high-density AUD families compared with LR, showed significantly reduced clustering, small-worldness, and local network efficiency. The frontoparietal, cingulo-opercular, sensorimotor and cerebellar networks exhibited significantly reduced functional segregation. These disruptions exhibited independent incremental value in predicting the externalizing symptoms over and above the demographic variables. The reduction of functional segregation in HR subjects was significant across both the younger and older age groups and was proportional to the family loading of AUDs. Detection and estimation of these developmentally relevant disruptions in small-world architecture at critical brain regions sub-serving cognitive, affective, and sensorimotor processes are vital for understanding the familial risk for early onset alcoholism as well as for understanding the pathophysiological mechanism of externalizing behaviors. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Capsule independent uptake of the fungal pathogen Cryptococcus neoformans into brain microvascular endothelial cells.

PubMed

Sabiiti, Wilber; May, Robin C

2012-01-01

Cryptococcosis is a life-threatening fungal disease with a high rate of mortality among HIV/AIDS patients across the world. The ability to penetrate the blood-brain barrier (BBB) is central to the pathogenesis of cryptococcosis, but the way in which this occurs remains unclear. Here we use both mouse and human brain derived endothelial cells (bEnd3 and hCMEC/D3) to accurately quantify fungal uptake and survival within brain endothelial cells. Our data indicate that the adherence and internalisation of cryptococci by brain microvascular endothelial cells is an infrequent event involving small numbers of cryptococcal yeast cells. Interestingly, this process requires neither active signalling from the fungus nor the presence of the fungal capsule. Thus entry into brain microvascular endothelial cells is most likely a passive event that occurs following 'trapping' within capillary beds of the BBB.

Capsule Independent Uptake of the Fungal Pathogen Cryptococcus neoformans into Brain Microvascular Endothelial Cells

PubMed Central

Sabiiti, Wilber; May, Robin C.

2012-01-01

Cryptococcosis is a life-threatening fungal disease with a high rate of mortality among HIV/AIDS patients across the world. The ability to penetrate the blood-brain barrier (BBB) is central to the pathogenesis of cryptococcosis, but the way in which this occurs remains unclear. Here we use both mouse and human brain derived endothelial cells (bEnd3 and hCMEC/D3) to accurately quantify fungal uptake and survival within brain endothelial cells. Our data indicate that the adherence and internalisation of cryptococci by brain microvascular endothelial cells is an infrequent event involving small numbers of cryptococcal yeast cells. Interestingly, this process requires neither active signalling from the fungus nor the presence of the fungal capsule. Thus entry into brain microvascular endothelial cells is most likely a passive event that occurs following ‘trapping’ within capillary beds of the BBB. PMID:22530025

Hierarchical functional modularity in the resting-state human brain.

PubMed

Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

2009-07-01

Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

Long-duration transcutaneous electric acupoint stimulation alters small-world brain functional networks.

PubMed

Zhang, Yue; Jiang, Yin; Glielmi, Christopher B; Li, Longchuan; Hu, Xiaoping; Wang, Xiaoying; Han, Jisheng; Zhang, Jue; Cui, Cailian; Fang, Jing

2013-09-01

Acupuncture, which is recognized as an alternative and complementary treatment in Western medicine, has long shown efficiencies in chronic pain relief, drug addiction treatment, stroke rehabilitation and other clinical practices. The neural mechanism underlying acupuncture, however, is still unclear. Many studies have focused on the sustained effects of acupuncture on healthy subjects, yet there are very few on the topological organization of functional networks in the whole brain in response to long-duration acupuncture (longer than 20 min). This paper presents a novel study on the effects of long-duration transcutaneous electric acupoint stimulation (TEAS) on the small-world properties of brain functional networks. Functional magnetic resonance imaging was used to construct brain functional networks of 18 healthy subjects (9 males and 9 females) during the resting state. All subjects received both TEAS and minimal TEAS (MTEAS) and were scanned before and after each stimulation. An altered functional network was found with lower local efficiency and no significant change in global efficiency for healthy subjects after TEAS, while no significant difference was observed after MTEAS. The experiments also showed that the nodal efficiencies in several paralimbic/limbic regions were altered by TEAS, and those in middle frontal gyrus and other regions by MTEAS. To remove the psychological effects and the baseline, we compared the difference between diffTEAS (difference between after and before TEAS) and diffMTEAS (difference between after and before MTEAS). The results showed that the local efficiency was decreased and that the nodal efficiencies in frontal gyrus, orbitofrontal cortex, anterior cingulate gyrus and hippocampus gyrus were changed. Based on those observations, we conclude that long-duration TEAS may modulate the short-range connections of brain functional networks and also the limbic system. Copyright © 2013 Elsevier Inc. All rights reserved.

Extending Gurwitsch's field theory of consciousness.

PubMed

Yoshimi, Jeff; Vinson, David W

2015-07-01

Aron Gurwitsch's theory of the structure and dynamics of consciousness has much to offer contemporary theorizing about consciousness and its basis in the embodied brain. On Gurwitsch's account, as we develop it, the field of consciousness has a variable sized focus or "theme" of attention surrounded by a structured periphery of inattentional contents. As the field evolves, its contents change their status, sometimes smoothly, sometimes abruptly. Inner thoughts, a sense of one's body, and the physical environment are dominant field contents. These ideas can be linked with (and help unify) contemporary theories about the neural correlates of consciousness, inattention, the small world structure of the brain, meta-stable dynamics, embodied cognition, and predictive coding in the brain. Published by Elsevier Inc.

The phenomenology of deep brain stimulation-induced changes in OCD: an enactive affordance-based model

PubMed Central

de Haan, Sanneke; Rietveld, Erik; Stokhof, Martin; Denys, Damiaan

2013-01-01

People suffering from Obsessive-Compulsive Disorder (OCD) do things they do not want to do, and/or they think things they do not want to think. In about 10% of OCD patients, none of the available treatment options is effective. A small group of these patients is currently being treated with deep brain stimulation (DBS). DBS involves the implantation of electrodes in the brain. These electrodes give a continuous electrical pulse to the brain area in which they are implanted. It turns out that patients may experience profound changes as a result of DBS treatment. It is not just the symptoms that change; patients rather seem to experience a different way of being in the world. These global effects are insufficiently captured by traditional psychiatric scales, which mainly consist of behavioral measures of the severity of the symptoms. In this article we aim to capture the changes in the patients' phenomenology and make sense of the broad range of changes they report. For that we introduce an enactive, affordance-based model that fleshes out the dynamic interactions between person and world in four aspects. The first aspect is the patients' experience of the world. We propose to specify the patients' world in terms of a field of affordances, with the three dimensions of broadness of scope (“width” of the field), temporal horizon (“depth”), and relevance of the perceived affordances (“height”). The second aspect is the person-side of the interaction, that is, the patients' self-experience, notably their moods and feelings. Thirdly, we point to the different characteristics of the way in which patients relate to the world. And lastly, the existential stance refers to the stance that patients take toward the changes they experience: the second-order evaluative relation to their interactions and themselves. With our model we intend to specify the notion of being in the world in order to do justice to the phenomenological effects of DBS treatment. PMID:24133438

Changes in Structural Connectivity Following a Cognitive Intervention in Children With Traumatic Brain Injury.

PubMed

Yuan, Weihong; Treble-Barna, Amery; Sohlberg, McKay M; Harn, Beth; Wade, Shari L

2017-02-01

Structural connectivity analysis based on graph theory and diffusion tensor imaging tractography is a novel method that quantifies the topological characteristics in the brain network. This study aimed to examine structural connectivity changes following the Attention Intervention and Management (AIM) program designed to improve attention and executive function (EF) in children with traumatic brain injury (TBI). Seventeen children with complicated mild to severe TBI (13.66 ± 2.68 years; >12 months postinjury) completed magnetic resonance imaging (MRI) and neurobehavioral measures at time 1, 10 of whom completed AIM and assessment at time 2. Eleven matched healthy comparison (HC) children (13.37 ± 2.08 years) completed MRI and neurobehavioral assessment at both time points, but did not complete AIM. Network characteristics were analyzed to quantify the structural connectivity before and after the intervention. Mixed model analyses showed that small-worldness was significantly higher in the TBI group than the HC group at time 1, and both small-worldness and normalized clustering coefficient decreased significantly at time 2 in the TBI group whereas the HC group remained relatively unchanged. Reductions in mean local efficiency were significantly correlated with improvements in verbal inhibition and both parent- and child-reported EF. Increased normalized characteristic path length was significantly correlated with improved sustained attention. The results provide preliminary evidence suggesting that graph theoretical analysis may be a sensitive tool in pediatric TBI for detecting ( a) abnormalities of structural connectivity in brain network and ( b) structural neuroplasticity associated with neurobehavioral improvement following a short-term intervention for attention and EF.

Globally altered structural brain network topology in grapheme-color synesthesia.

PubMed

Hänggi, Jürgen; Wotruba, Diana; Jäncke, Lutz

2011-04-13

Synesthesia is a perceptual phenomenon in which stimuli in one particular modality elicit a sensation within the same or another sensory modality (e.g., specific graphemes evoke the perception of particular colors). Grapheme-color synesthesia (GCS) has been proposed to arise from abnormal local cross-activation between grapheme and color areas because of their hyperconnectivity. Recently published studies did not confirm such a hyperconnectivity, although morphometric alterations were found in occipitotemporal, parietal, and frontal regions of synesthetes. We used magnetic resonance imaging surface-based morphometry and graph-theoretical network analyses to investigate the topology of structural brain networks in 24 synesthetes and 24 nonsynesthetes. Connectivity matrices were derived from region-wise cortical thickness correlations of 2366 different cortical parcellations across the whole cortex and from 154 more common brain divisions as well. Compared with nonsynesthetes, synesthetes revealed a globally altered structural network topology as reflected by reduced small-worldness, increased clustering, increased degree, and decreased betweenness centrality. Connectivity of the fusiform gyrus (FuG) and intraparietal sulcus (IPS) was changed as well. Hierarchical modularity analysis revealed increased intramodular and intermodular connectivity of the IPS in GCS. However, connectivity differences in the FuG and IPS showed a low specificity because of global changes. We provide first evidence that GCS is rooted in a reduced small-world network organization that is driven by increased clustering suggesting global hyperconnectivity within the synesthetes' brain. Connectivity alterations were widespread and not restricted to the FuG and IPS. Therefore, synesthetic experience might be only one phenotypic manifestation of the globally altered network architecture in GCS.

Brain-machine interface control of a manipulator using small-world neural network and shared control strategy.

PubMed

Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng

2014-03-15

The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. Copyright © 2013 Elsevier B.V. All rights reserved.

Measures for brain connectivity analysis: nodes centrality and their invariant patterns

NASA Astrophysics Data System (ADS)

da Silva, Laysa Mayra Uchôa; Baltazar, Carlos Arruda; Silva, Camila Aquemi; Ribeiro, Mauricio Watanabe; de Aratanha, Maria Adelia Albano; Deolindo, Camila Sardeto; Rodrigues, Abner Cardoso; Machado, Birajara Soares

2017-07-01

The high dynamical complexity of the brain is related to its small-world topology, which enable both segregated and integrated information processing capabilities. Several measures of connectivity estimation have already been employed to characterize functional brain networks from multivariate electrophysiological data. However, understanding the properties of each measure that lead to a better description of the real topology and capture the complex phenomena present in the brain remains challenging. In this work we compared four nonlinear connectivity measures and show that each method characterizes distinct features of brain interactions. The results suggest an invariance of global network parameters from different behavioral states and that more complete description may be reached considering local features, independently of the connectivity measure employed. Our findings also point to future perspectives in connectivity studies that combine distinct and complementary dependence measures in assembling higher dimensions manifolds.

Altered Cerebral Blood Flow Covariance Network in Schizophrenia.

PubMed

Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui

2016-01-01

Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia.

Disorganized cortical thickness covariance network in major depressive disorder implicated by aberrant hubs in large-scale networks

PubMed Central

Wang, Tao; Wang, Kangcheng; Qu, Hang; Zhou, Jingjing; Li, Qi; Deng, Zhou; Du, Xue; Lv, Fajin; Ren, Gaoping; Guo, Jing; Qiu, Jiang; Xie, Peng

2016-01-01

Major depressive disorder is associated with abnormal anatomical and functional connectivity, yet alterations in whole cortical thickness topology remain unknown. Here, we examined cortical thickness in medication-free adult depression patients (n = 76) and matched healthy controls (n = 116). Inter-regional correlation was performed to construct brain networks. By applying graph theory analysis, global (i.e., small-worldness) and regional (centrality) topology was compared between major depressive disorder patients and healthy controls. We found that in depression patients, topological organization of the cortical thickness network shifted towards randomness, and lower small-worldness was driven by a decreased clustering coefficient. Consistently, altered nodal centrality was identified in the isthmus of the cingulate cortex, insula, supra-marginal gyrus, middle temporal gyrus and inferior parietal gyrus, all of which are components within the default mode, salience and central executive networks. Disrupted nodes anchored in the default mode and executive networks were associated with depression severity. The brain systems involved sustain core symptoms in depression and implicate a structural basis for depression. Our results highlight the possibility that developmental and genetic factors are crucial to understand the neuropathology of depression. PMID:27302485

Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer.

PubMed

Kesler, Shelli R; Watson, Christa L; Blayney, Douglas W

2015-08-01

Breast cancer and its treatments are associated with mild cognitive impairment and brain changes that could indicate an altered or accelerated brain aging process. We applied diffusion tensor imaging and graph theory to measure white matter organization and connectivity in 34 breast cancer survivors compared with 36 matched healthy female controls. We also investigated how brain networks (connectomes) in each group responded to simulated neurodegeneration based on network attack analysis. Compared with controls, the breast cancer group demonstrated significantly lower fractional anisotropy, altered small-world connectome properties, lower brain network tolerance to systematic region (node), and connection (edge) attacks and significant cognitive impairment. Lower tolerance to network attack was associated with cognitive impairment in the breast cancer group. These findings provide further evidence of diffuse white matter pathology after breast cancer and extend the literature in this area with unique data demonstrating increased vulnerability of the post-breast cancer brain network to future neurodegenerative processes. Copyright © 2015 Elsevier Inc. All rights reserved.

Hemispheric lateralization of topological organization in structural brain networks.

PubMed

Caeyenberghs, Karen; Leemans, Alexander

2014-09-01

The study on structural brain asymmetries in healthy individuals plays an important role in our understanding of the factors that modulate cognitive specialization in the brain. Here, we used fiber tractography to reconstruct the left and right hemispheric networks of a large cohort of 346 healthy participants (20-86 years) and performed a graph theoretical analysis to investigate this brain laterality from a network perspective. Findings revealed that the left hemisphere is significantly more "efficient" than the right hemisphere, whereas the right hemisphere showed higher values of "betweenness centrality" and "small-worldness." In particular, left-hemispheric networks displayed increased nodal efficiency in brain regions related to language and motor actions, whereas the right hemisphere showed an increase in nodal efficiency in brain regions involved in memory and visuospatial attention. In addition, we found that hemispheric networks decrease in efficiency with age. Finally, we observed significant gender differences in measures of global connectivity. By analyzing the structural hemispheric brain networks, we have provided new insights into understanding the neuroanatomical basis of lateralized brain functions. Copyright © 2014 Wiley Periodicals, Inc.

Ravens, New Caledonian crows and jackdaws parallel great apes in motor self-regulation despite smaller brains.

PubMed

Kabadayi, Can; Taylor, Lucy A; von Bayern, Auguste M P; Osvath, Mathias

2016-04-01

Overriding motor impulses instigated by salient perceptual stimuli represent a fundamental inhibitory skill. Such motor self-regulation facilitates more rational behaviour, as it brings economy into the bodily interaction with the physical and social world. It also underlies certain complex cognitive processes including decision making. Recently, MacLean et al. (MacLean et al. 2014 Proc. Natl Acad. Sci. USA 111, 2140-2148. (doi:10.1073/pnas.1323533111)) conducted a large-scale study involving 36 species, comparing motor self-regulation across taxa. They concluded that absolute brain size predicts level of performance. The great apes were most successful. Only a few of the species tested were birds. Given birds' small brain size-in absolute terms-yet flexible behaviour, their motor self-regulation calls for closer study. Corvids exhibit some of the largest relative avian brain sizes-although small in absolute measure-as well as the most flexible cognition in the animal kingdom. We therefore tested ravens, New Caledonian crows and jackdaws in the so-called cylinder task. We found performance indistinguishable from that of great apes despite the much smaller brains. We found both absolute and relative brain volume to be a reliable predictor of performance within Aves. The complex cognition of corvids is often likened to that of great apes; our results show further that they share similar fundamental cognitive mechanisms.

Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder.

PubMed

Cao, Qingjiu; Shu, Ni; An, Li; Wang, Peng; Sun, Li; Xia, Ming-Rui; Wang, Jin-Hui; Gong, Gao-Lang; Zang, Yu-Feng; Wang, Yu-Feng; He, Yong

2013-06-26

Attention-deficit/hyperactivity disorder (ADHD), which is characterized by core symptoms of inattention and hyperactivity/impulsivity, is one of the most common neurodevelopmental disorders of childhood. Neuroimaging studies have suggested that these behavioral disturbances are associated with abnormal functional connectivity among brain regions. However, the alterations in the structural connections that underlie these behavioral and functional deficits remain poorly understood. Here, we used diffusion magnetic resonance imaging and probabilistic tractography method to examine whole-brain white matter (WM) structural connectivity in 30 drug-naive boys with ADHD and 30 healthy controls. The WM networks of the human brain were constructed by estimating inter-regional connectivity probability. The topological properties of the resultant networks (e.g., small-world and network efficiency) were then analyzed using graph theoretical approaches. Nonparametric permutation tests were applied for between-group comparisons of these graphic metrics. We found that both the ADHD and control groups showed an efficient small-world organization in the whole-brain WM networks, suggesting a balance between structurally segregated and integrated connectivity patterns. However, relative to controls, patients with ADHD exhibited decreased global efficiency and increased shortest path length, with the most pronounced efficiency decreases in the left parietal, frontal, and occipital cortices. Intriguingly, the ADHD group showed decreased structural connectivity in the prefrontal-dominant circuitry and increased connectivity in the orbitofrontal-striatal circuitry, and these changes significantly correlated with the inattention and hyperactivity/impulsivity symptoms, respectively. The present study shows disrupted topological organization of large-scale WM networks in ADHD, extending our understanding of how structural disruptions of neuronal circuits underlie behavioral disturbances in patients with ADHD.

Positive and negative affective processing exhibit dissociable functional hubs during the viewing of affective pictures.

PubMed

Zhang, Wenhai; Li, Hong; Pan, Xiaohong

2015-02-01

Recent resting-state functional magnetic resonance imaging (fMRI) studies using graph theory metrics have revealed that the functional network of the human brain possesses small-world characteristics and comprises several functional hub regions. However, it is unclear how the affective functional network is organized in the brain during the processing of affective information. In this study, the fMRI data were collected from 25 healthy college students as they viewed a total of 81 positive, neutral, and negative pictures. The results indicated that affective functional networks exhibit weaker small-worldness properties with higher local efficiency, implying that local connections increase during viewing affective pictures. Moreover, positive and negative emotional processing exhibit dissociable functional hubs, emerging mainly in task-positive regions. These functional hubs, which are the centers of information processing, have nodal betweenness centrality values that are at least 1.5 times larger than the average betweenness centrality of the network. Positive affect scores correlated with the betweenness values of the right orbital frontal cortex (OFC) and the right putamen in the positive emotional network; negative affect scores correlated with the betweenness values of the left OFC and the left amygdala in the negative emotional network. The local efficiencies in the left superior and inferior parietal lobe correlated with subsequent arousal ratings of positive and negative pictures, respectively. These observations provide important evidence for the organizational principles of the human brain functional connectome during the processing of affective information. © 2014 Wiley Periodicals, Inc.

Sparsely-synchronized brain rhythm in a small-world neural network

NASA Astrophysics Data System (ADS)

Kim, Sang-Yoon; Lim, Woochang

2013-07-01

Sparsely-synchronized cortical rhythms, associated with diverse cognitive functions, have been observed in electric recordings of brain activity. At the population level, cortical rhythms exhibit small-amplitude fast oscillations while at the cellular level, individual neurons show stochastic firings sparsely at a much lower rate than the population rate. We study the effect of network architecture on sparse synchronization in an inhibitory population of subthreshold Morris-Lecar neurons (which cannot fire spontaneously without noise). Previously, sparse synchronization was found to occur for cases of both global coupling ( i.e., regular all-to-all coupling) and random coupling. However, a real neural network is known to be non-regular and non-random. Here, we consider sparse Watts-Strogatz small-world networks which interpolate between a regular lattice and a random graph via rewiring. We start from a regular lattice with only short-range connections and then investigate the emergence of sparse synchronization by increasing the rewiring probability p for the short-range connections. For p = 0, the average synaptic path length between pairs of neurons becomes long; hence, only an unsynchronized population state exists because the global efficiency of information transfer is low. However, as p is increased, long-range connections begin to appear, and global effective communication between distant neurons may be available via shorter synaptic paths. Consequently, as p passes a threshold p th (}~ 0.044), sparsely-synchronized population rhythms emerge. However, with increasing p, longer axon wirings become expensive because of their material and energy costs. At an optimal value p* DE (}~ 0.24) of the rewiring probability, the ratio of the synchrony degree to the wiring cost is found to become maximal. In this way, an optimal sparse synchronization is found to occur at a minimal wiring cost in an economic small-world network through trade-off between synchrony and wiring cost.

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

A Small World of Neuronal Synchrony

PubMed Central

Yu, Shan; Huang, Debin; Singer, Wolf

2008-01-01

A small-world network has been suggested to be an efficient solution for achieving both modular and global processing—a property highly desirable for brain computations. Here, we investigated functional networks of cortical neurons using correlation analysis to identify functional connectivity. To reconstruct the interaction network, we applied the Ising model based on the principle of maximum entropy. This allowed us to assess the interactions by measuring pairwise correlations and to assess the strength of coupling from the degree of synchrony. Visual responses were recorded in visual cortex of anesthetized cats, simultaneously from up to 24 neurons. First, pairwise correlations captured most of the patterns in the population's activity and, therefore, provided a reliable basis for the reconstruction of the interaction networks. Second, and most importantly, the resulting networks had small-world properties; the average path lengths were as short as in simulated random networks, but the clustering coefficients were larger. Neurons differed considerably with respect to the number and strength of interactions, suggesting the existence of “hubs” in the network. Notably, there was no evidence for scale-free properties. These results suggest that cortical networks are optimized for the coexistence of local and global computations: feature detection and feature integration or binding. PMID:18400792

Autoassociative memory retrieval and spontaneous activity bumps in small-world networks of integrate-and-fire neurons.

PubMed

Anishchenko, Anastasia; Treves, Alessandro

2006-10-01

The metric structure of synaptic connections is obviously an important factor in shaping the properties of neural networks, in particular the capacity to retrieve memories, with which are endowed autoassociative nets operating via attractor dynamics. Qualitatively, some real networks in the brain could be characterized as 'small worlds', in the sense that the structure of their connections is intermediate between the extremes of an orderly geometric arrangement and of a geometry-independent random mesh. Small worlds can be defined more precisely in terms of their mean path length and clustering coefficient; but is such a precise description useful for a better understanding of how the type of connectivity affects memory retrieval? We have simulated an autoassociative memory network of integrate-and-fire units, positioned on a ring, with the network connectivity varied parametrically between ordered and random. We find that the network retrieves previously stored memory patterns when the connectivity is close to random, and displays the characteristic behavior of ordered nets (localized 'bumps' of activity) when the connectivity is close to ordered. Recent analytical work shows that these two behaviors can coexist in a network of simple threshold-linear units, leading to localized retrieval states. We find that they tend to be mutually exclusive behaviors, however, with our integrate-and-fire units. Moreover, the transition between the two occurs for values of the connectivity parameter which are not simply related to the notion of small worlds.

78 FR 42795 - Submission for OMB review; 30-Day Comment Request: Evaluation of the Brain Disorders in the...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-17

...; 30-Day Comment Request: Evaluation of the Brain Disorders in the Developing World Program of the John... Collection: Evaluation of the Brain Disorders in the Developing World Program of the John E. Fogarty... outcomes of the Brain Disorders in the Developing World extramural research program administered by the...

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

Abnormal small-world architecture of top–down control networks in obsessive–compulsive disorder

PubMed Central

Zhang, Tijiang; Wang, Jinhui; Yang, Yanchun; Wu, Qizhu; Li, Bin; Chen, Long; Yue, Qiang; Tang, Hehan; Yan, Chaogan; Lui, Su; Huang, Xiaoqi; Chan, Raymond C.K.; Zang, Yufeng; He, Yong; Gong, Qiyong

2011-01-01

Background Obsessive–compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD–related alterations in functional connectivity patterns in the brain’s top–down control network. Methods We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level–dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top–down control and then analyzed using graph theory-based approaches. Results Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain’s control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. Limitations The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. Conclusion Our preliminary results suggest that the organizational patterns of intrinsic brain activity in the control networks are altered in patients with OCD and thus provide empirical evidence for aberrant functional connectivity in the large-scale brain systems in people with this disorder. PMID:20964957

Using Individualized Brain Network for Analyzing Structural Covariance of the Cerebral Cortex in Alzheimer's Patients.

PubMed

Kim, Hee-Jong; Shin, Jeong-Hyeon; Han, Cheol E; Kim, Hee Jin; Na, Duk L; Seo, Sang Won; Seong, Joon-Kyung

2016-01-01

Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.

Prognostic value of electroencephalography (EEG) for brain injury after cardiopulmonary resuscitation.

PubMed

Feng, Guibo; Jiang, Guohui; Li, Zhiwei; Wang, Xuefeng

2016-06-01

Cardiac arrest (CA) patients can experience neurological sequelae or even death after successful cardiopulmonary resuscitation (CPR) due to cerebral hypoxia- and ischemia-reperfusion-mediated brain injury. Thus, it is important to perform early prognostic evaluations in CA patients. Electroencephalography (EEG) is an important tool for determining the prognosis of hypoxic-ischemic encephalopathy due to its real-time measurement of brain function. Based on EEG, burst suppression, a burst suppression ratio >0.239, periodic discharges, status epilepticus, stimulus-induced rhythmic, periodic or ictal discharges, non-reactive EEG, and the BIS value based on quantitative EEG may be associated with the prognosis of CA after successful CPR. As measures of neural network integrity, the values of small-world characteristics of the neural network derived from EEG patterns have potential applications.

Subjective cognitive impairment and brain structural networks in Chinese gynaecological cancer survivors compared with age-matched controls: a cross-sectional study.

PubMed

Zeng, Yingchun; Cheng, Andy S K; Song, Ting; Sheng, Xiujie; Zhang, Yang; Liu, Xiangyu; Chan, Chetwyn C H

2017-11-28

Subjective cognitive impairment can be a significant and prevalent problem for gynaecological cancer survivors. The aims of this study were to assess subjective cognitive functioning in gynaecological cancer survivors after primary cancer treatment, and to investigate the impact of cancer treatment on brain structural networks and its association with subjective cognitive impairment. This was a cross-sectional survey using a self-reported questionnaire by the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) to assess subjective cognitive functioning, and applying DTI (diffusion tensor imaging) and graph theoretical analyses to investigate brain structural networks after primary cancer treatment. A total of 158 patients with gynaecological cancer (mean age, 45.86 years) and 130 age-matched non-cancer controls (mean age, 44.55 years) were assessed. Patients reported significantly greater subjective cognitive functioning on the FACT-Cog total score and two subscales of perceived cognitive impairment and perceived cognitive ability (all p values <0.001). Compared with patients who had received surgery only and non-cancer controls, patients treated with chemotherapy indicated the most altered global brain structural networks, especially in one of properties of small-worldness (p = 0.004). Reduced small-worldness was significantly associated with a lower FACT-Cog total score (r = 0.412, p = 0.024). Increased characteristic path length was also significantly associated with more subjective cognitive impairment (r = -0.388, p = 0.034). When compared with non-cancer controls, a considerable proportion of gynaecological cancer survivors may exhibit subjective cognitive impairment. This study provides the first evidence of brain structural network alteration in gynaecological cancer patients at post-treatment, and offers novel insights regarding the possible neurobiological mechanism of cancer-related cognitive impairment (CRCI) in gynaecological cancer patients. As primary cancer treatment can result in a more random organisation of structural brain networks, this may reduce brain functional specificity and segregation, and have implications for cognitive impairment. Future prospective and longitudinal studies are needed to build upon the study findings in order to assess potentially relevant clinical and psychosocial variables and brain network measures, so as to more accurately understand the specific risk factors related to subjective cognitive impairment in the gynaecological cancer population. Such knowledge could inform the development of appropriate treatment and rehabilitation efforts to ameliorate cognitive impairment in gynaecological cancer survivors.

Structural connectivity asymmetry in the neonatal brain.

PubMed

Ratnarajah, Nagulan; Rifkin-Graboi, Anne; Fortier, Marielle V; Chong, Yap Seng; Kwek, Kenneth; Saw, Seang-Mei; Godfrey, Keith M; Gluckman, Peter D; Meaney, Michael J; Qiu, Anqi

2013-07-15

Asymmetry of the neonatal brain is not yet understood at the level of structural connectivity. We utilized DTI deterministic tractography and structural network analysis based on graph theory to determine the pattern of structural connectivity asymmetry in 124 normal neonates. We tracted white matter axonal pathways characterizing interregional connections among brain regions and inferred asymmetry in left and right anatomical network properties. Our findings revealed that in neonates, small-world characteristics were exhibited, but did not differ between the two hemispheres, suggesting that neighboring brain regions connect tightly with each other, and that one region is only a few paths away from any other region within each hemisphere. Moreover, the neonatal brain showed greater structural efficiency in the left hemisphere than that in the right. In neonates, brain regions involved in motor, language, and memory functions play crucial roles in efficient communication in the left hemisphere, while brain regions involved in emotional processes play crucial roles in efficient communication in the right hemisphere. These findings suggest that even at birth, the topology of each cerebral hemisphere is organized in an efficient and compact manner that maps onto asymmetric functional specializations seen in adults, implying lateralized brain functions in infancy. Copyright © 2013 Elsevier Inc. All rights reserved.

EEG-based research on brain functional networks in cognition.

PubMed

Wang, Niannian; Zhang, Li; Liu, Guozhong

2015-01-01

Recently, exploring the cognitive functions of the brain by establishing a network model to understand the working mechanism of the brain has become a popular research topic in the field of neuroscience. In this study, electroencephalography (EEG) was used to collect data from subjects given four different mathematical cognitive tasks: recite numbers clockwise and counter-clockwise, and letters clockwise and counter-clockwise to build a complex brain function network (BFN). By studying the connectivity features and parameters of those brain functional networks, it was found that the average clustering coefficient is much larger than its corresponding random network and the average shortest path length is similar to the corresponding random networks, which clearly shows the characteristics of the small-world network. The brain regions stimulated during the experiment are consistent with traditional cognitive science regarding learning, memory, comprehension, and other rational judgment results. The new method of complex networking involves studying the mathematical cognitive process of reciting, providing an effective research foundation for exploring the relationship between brain cognition and human learning skills and memory. This could help detect memory deficits early in young and mentally handicapped children, and help scientists understand the causes of cognitive brain disorders.

Generating Extractive Summaries of Scientific Paradigms (Open Access, Publisher’s Version)

DTIC Science & Technology

2013-02-01

international joint conference on Artifical intelligence , IJCAI’07, pp. 2060–2065. Bassett, D. S., & Bullmore, E. (2006). Small-world brain networks. The...Journal of Artificial Intelligence Research 46 (2013) 165-201 Submitted 7/12; published 2/13 Generating Extractive Summaries of Scientific Paradigms...Whidby and Taesun Moon were supported, in part, by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior Na- tional

Cost Benefit Analysis for Turkish Navy.

DTIC Science & Technology

1987-12-01

must be added to the irreplaceable human eye -brain combination, can be carried by ships or patrol aircraft. In the silent world below the surface...with relatively low banks are of a brownish grey color wherever they are not covered by the maquis and other species of Mediterranean vegetation. The...respectively and a dry dock for small vessels of about 5()() tonN. V2V." ." . -. ,",.’,’. v

Graph theoretical analysis of EEG functional connectivity during music perception.

PubMed

Wu, Junjie; Zhang, Junsong; Liu, Chu; Liu, Dongwei; Ding, Xiaojun; Zhou, Changle

2012-11-05

The present study evaluated the effect of music on large-scale structure of functional brain networks using graph theoretical concepts. While most studies on music perception used Western music as an acoustic stimulus, Guqin music, representative of Eastern music, was selected for this experiment to increase our knowledge of music perception. Electroencephalography (EEG) was recorded from non-musician volunteers in three conditions: Guqin music, noise and silence backgrounds. Phase coherence was calculated in the alpha band and between all pairs of EEG channels to construct correlation matrices. Each resulting matrix was converted into a weighted graph using a threshold, and two network measures: the clustering coefficient and characteristic path length were calculated. Music perception was found to display a higher level mean phase coherence. Over the whole range of thresholds, the clustering coefficient was larger while listening to music, whereas the path length was smaller. Networks in music background still had a shorter characteristic path length even after the correction for differences in mean synchronization level among background conditions. This topological change indicated a more optimal structure under music perception. Thus, prominent small-world properties are confirmed in functional brain networks. Furthermore, music perception shows an increase of functional connectivity and an enhancement of small-world network organizations. Copyright © 2012 Elsevier B.V. All rights reserved.

Wavelet multiresolution complex network for decoding brain fatigued behavior from P300 signals

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Wang, Zi-Bo; Yang, Yu-Xuan; Li, Shan; Dang, Wei-Dong; Mao, Xiao-Qian

2018-09-01

Brain-computer interface (BCI) enables users to interact with the environment without relying on neural pathways and muscles. P300 based BCI systems have been extensively used to achieve human-machine interaction. However, the appearance of fatigue symptoms during operation process leads to the decline in classification accuracy of P300. Characterizing brain cognitive process underlying normal and fatigue conditions constitutes a problem of vital importance in the field of brain science. We in this paper propose a novel wavelet decomposition based complex network method to efficiently analyze the P300 signals recorded in the image stimulus test based on classical 'Oddball' paradigm. Initially, multichannel EEG signals are decomposed into wavelet coefficient series. Then we construct complex network by treating electrodes as nodes and determining the connections according to the 2-norm distances between wavelet coefficient series. The analysis of topological structure and statistical index indicates that the properties of brain network demonstrate significant distinctions between normal status and fatigue status. More specifically, the brain network reconfiguration in response to the cognitive task in fatigue status is reflected as the enhancement of the small-worldness.

Intra- and interbrain synchronization and network properties when playing guitar in duets

PubMed Central

Sänger, Johanna; Müller, Viktor; Lindenberger, Ulman

2012-01-01

To further test and explore the hypothesis that synchronous oscillatory brain activity supports interpersonally coordinated behavior during dyadic music performance, we simultaneously recorded the electroencephalogram (EEG) from the brains of each of 12 guitar duets repeatedly playing a modified Rondo in two voices by C.G. Scheidler. Indicators of phase locking and of within-brain and between-brain phase coherence were obtained from complex time-frequency signals based on the Gabor transform. Analyses were restricted to the delta (1–4 Hz) and theta (4–8 Hz) frequency bands. We found that phase locking as well as within-brain and between-brain phase-coherence connection strengths were enhanced at frontal and central electrodes during periods that put particularly high demands on musical coordination. Phase locking was modulated in relation to the experimentally assigned musical roles of leader and follower, corroborating the functional significance of synchronous oscillations in dyadic music performance. Graph theory analyses revealed within-brain and hyperbrain networks with small-worldness properties that were enhanced during musical coordination periods, and community structures encompassing electrodes from both brains (hyperbrain modules). We conclude that brain mechanisms indexed by phase locking, phase coherence, and structural properties of within-brain and hyperbrain networks support interpersonal action coordination (IAC). PMID:23226120

Volumetric electromagnetic phase-shift spectroscopy of brain edema and hematoma.

PubMed

Gonzalez, Cesar A; Valencia, Jose A; Mora, Alfredo; Gonzalez, Fernando; Velasco, Beatriz; Porras, Martin A; Salgado, Javier; Polo, Salvador M; Hevia-Montiel, Nidiyare; Cordero, Sergio; Rubinsky, Boris

2013-01-01

Motivated by the need of poor and rural Mexico, where the population has limited access to advanced medical technology and services, we have developed a new paradigm for medical diagnostic based on the technology of "Volumetric Electromagnetic Phase Shift Spectroscopy" (VEPS), as an inexpensive partial substitute to medical imaging. VEPS, can detect changes in tissue properties inside the body through non-contact, multi-frequency electromagnetic measurements from the exterior of the body, and thereby provide rapid and inexpensive diagnostics in a way that is amenable for use in economically disadvantaged parts of the world. We describe the technology and report results from a limited pilot study with 46 healthy volunteers and eight patients with CT radiology confirmed brain edema and brain hematoma. Data analysis with a non-parametric statistical Mann-Whitney U test, shows that in the frequency range of from 26 MHz to 39 MHz, VEPS can distinguish non-invasively and without contact, with a statistical significance of p<0.05, between healthy subjects and those with a medical conditions in the brain. In the frequency range of between 153 MHz to 166 MHz it can distinguish with a statistical significance of p<0.05 between subjects with brain edema and those with a hematoma in the brain. A classifier build from measurements in these two frequency ranges can provide instantaneous diagnostic of the medical condition of the brain of a patient, from a single set of measurements. While this is a small-scale pilot study, it illustrates the potential of VEPS to change the paradigm of medical diagnostic of brain injury through a VEPS classifier-based technology. Obviously substantially larger-scale studies are needed to verify and expand on the findings in this small pilot study.

Volumetric Electromagnetic Phase-Shift Spectroscopy of Brain Edema and Hematoma

PubMed Central

Gonzalez, Cesar A.; Valencia, Jose A.; Mora, Alfredo; Gonzalez, Fernando; Velasco, Beatriz; Porras, Martin A.; Salgado, Javier; Polo, Salvador M.; Hevia-Montiel, Nidiyare; Cordero, Sergio; Rubinsky, Boris

2013-01-01

Motivated by the need of poor and rural Mexico, where the population has limited access to advanced medical technology and services, we have developed a new paradigm for medical diagnostic based on the technology of “Volumetric Electromagnetic Phase Shift Spectroscopy” (VEPS), as an inexpensive partial substitute to medical imaging. VEPS, can detect changes in tissue properties inside the body through non-contact, multi-frequency electromagnetic measurements from the exterior of the body, and thereby provide rapid and inexpensive diagnostics in a way that is amenable for use in economically disadvantaged parts of the world. We describe the technology and report results from a limited pilot study with 46 healthy volunteers and eight patients with CT radiology confirmed brain edema and brain hematoma. Data analysis with a non-parametric statistical Mann-Whitney U test, shows that in the frequency range of from 26 MHz to 39 MHz, VEPS can distinguish non-invasively and without contact, with a statistical significance of p<0.05, between healthy subjects and those with a medical conditions in the brain. In the frequency range of between 153 MHz to 166 MHz it can distinguish with a statistical significance of p<0.05 between subjects with brain edema and those with a hematoma in the brain. A classifier build from measurements in these two frequency ranges can provide instantaneous diagnostic of the medical condition of the brain of a patient, from a single set of measurements. While this is a small-scale pilot study, it illustrates the potential of VEPS to change the paradigm of medical diagnostic of brain injury through a VEPS classifier-based technology. Obviously substantially larger-scale studies are needed to verify and expand on the findings in this small pilot study. PMID:23691001

Resting state network topology of the ferret brain.

PubMed

Zhou, Zhe Charles; Salzwedel, Andrew P; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K; Gilmore, John H; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-12-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury.

PubMed

Caeyenberghs, Karen; Leemans, Alexander; Heitger, Marcus H; Leunissen, Inge; Dhollander, Thijs; Sunaert, Stefan; Dupont, Patrick; Swinnen, Stephan P

2012-04-01

Patients with traumatic brain injury show clear impairments in behavioural flexibility and inhibition that often persist beyond the time of injury, affecting independent living and psychosocial functioning. Functional magnetic resonance imaging studies have shown that patients with traumatic brain injury typically show increased and more broadly dispersed frontal and parietal activity during performance of cognitive control tasks. We constructed binary and weighted functional networks and calculated their topological properties using a graph theoretical approach. Twenty-three adults with traumatic brain injury and 26 age-matched controls were instructed to switch between coordination modes while making spatially and temporally coupled circular motions with joysticks during event-related functional magnetic resonance imaging. Results demonstrated that switching performance was significantly lower in patients with traumatic brain injury compared with control subjects. Furthermore, although brain networks of both groups exhibited economical small-world topology, altered functional connectivity was demonstrated in patients with traumatic brain injury. In particular, compared with controls, patients with traumatic brain injury showed increased connectivity degree and strength, and higher values of local efficiency, suggesting adaptive mechanisms in this group. Finally, the degree of increased connectivity was significantly correlated with poorer switching task performance and more severe brain injury. We conclude that analysing the functional brain network connectivity provides new insights into understanding cognitive control changes following brain injury.

Complex network inference from P300 signals: Decoding brain state under visual stimulus for able-bodied and disabled subjects

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Cai, Qing; Dong, Na; Zhang, Shan-Shan; Bo, Yun; Zhang, Jie

2016-10-01

Distinguishing brain cognitive behavior underlying disabled and able-bodied subjects constitutes a challenging problem of significant importance. Complex network has established itself as a powerful tool for exploring functional brain networks, which sheds light on the inner workings of the human brain. Most existing works in constructing brain network focus on phase-synchronization measures between regional neural activities. In contrast, we propose a novel approach for inferring functional networks from P300 event-related potentials by integrating time and frequency domain information extracted from each channel signal, which we show to be efficient in subsequent pattern recognition. In particular, we construct brain network by regarding each channel signal as a node and determining the edges in terms of correlation of the extracted feature vectors. A six-choice P300 paradigm with six different images is used in testing our new approach, involving one able-bodied subject and three disabled subjects suffering from multiple sclerosis, cerebral palsy, traumatic brain and spinal-cord injury, respectively. We then exploit global efficiency, local efficiency and small-world indices from the derived brain networks to assess the network topological structure associated with different target images. The findings suggest that our method allows identifying brain cognitive behaviors related to visual stimulus between able-bodied and disabled subjects.

Analyzing the association between functional connectivity of the brain and intellectual performance

PubMed Central

Pamplona, Gustavo S. P.; Santos Neto, Gérson S.; Rosset, Sara R. E.; Rogers, Baxter P.; Salmon, Carlos E. G.

2015-01-01

Measurements of functional connectivity support the hypothesis that the brain is composed of distinct networks with anatomically separated nodes but common functionality. A few studies have suggested that intellectual performance may be associated with greater functional connectivity in the fronto-parietal network and enhanced global efficiency. In this fMRI study, we performed an exploratory analysis of the relationship between the brain's functional connectivity and intelligence scores derived from the Portuguese language version of the Wechsler Adult Intelligence Scale (WAIS-III) in a sample of 29 people, born and raised in Brazil. We examined functional connectivity between 82 regions, including graph theoretic properties of the overall network. Some previous findings were extended to the Portuguese-speaking population, specifically the presence of small-world organization of the brain and relationships of intelligence with connectivity of frontal, pre-central, parietal, occipital, fusiform and supramarginal gyrus, and caudate nucleus. Verbal comprehension was associated with global network efficiency, a new finding. PMID:25713528

Graph-theoretical analysis of resting-state fMRI in pediatric obsessive-compulsive disorder

PubMed Central

Armstrong, Casey C.; Moody, Teena D.; Feusner, Jamie D.; McCracken, James T.; Chang, Susanna; Levitt, Jennifer G.; Piacentini, John C.; O'Neill, Joseph

2018-01-01

Background fMRI graph theory reveals resting-state brain networks, but has never been used in pediatric OCD. Methods Whole-brain resting-state fMRI was acquired at 3 T from 21 children with OCD and 20 age-matched healthy controls. BOLD connectivity was analyzed yielding global and local graph-theory metrics across 100 child-based functional nodes. We also compared local metrics between groups in frontopolar, supplementary motor, and sensorimotor cortices, regions implicated in recent neuroimaging and/or brain stimulation treatment studies in OCD. Results As in adults, the global metric small-worldness was significantly (P<0.05) lower in patients than controls, by 13.5% (%mean difference = 100%×(OCD mean – control mean)/control mean). This suggests less efficient information transfer in patients. In addition, modularity was lower in OCD (15.1%, P<0.01), suggesting less granular-- or differently organized-- functional brain parcellation. Higher clustering coefficients (23.9-32.4%, P<0.05) were observed in patients in frontopolar, supplementary motor, sensorimotor, and cortices with lower betweenness centrality (-63.6%, P<0.01) at one frontopolar site. These findings are consistent with more locally intensive connectivity or less interaction with other brain regions at these sites. Limitations Relatively large node size; relatively small sample size, comorbidities in some patients. Conclusions Pediatric OCD patients demonstrate aberrant global and local resting-state network connectivity topologies compared to healthy children. Local results accord with recent views of OCD as a disorder with sensorimotor component. PMID:26773910

Real-World Neuroimaging Technologies

DTIC Science & Technology

2013-05-10

system enables long-term wear of up to 10 consecutive hours of operation time. The system’s wireless technologies, light weight (200g), and dry sensor ...biomarkers, body sensor networks , brain computer interactionbrain, computer interfaces, data acquisition, electroencephalography monitoring, translational...brain activity in real-world scenarios. INDEX TERMS Behavioral science, biomarkers, body sensor networks , brain computer interfaces, brain computer

[Research on brain white matter network in cerebral palsy infant].

PubMed

Li, Jun; Yang, Cheng; Wang, Yuanjun; Nie, Shengdong

2017-10-01

Present study used diffusion tensor image and tractography to construct brain white matter networks of 15 cerebral palsy infants and 30 healthy infants that matched for age and gender. After white matter network analysis, we found that both cerebral palsy and healthy infants had a small-world topology in white matter network, but cerebral palsy infants exhibited abnormal topological organization: increased shortest path length but decreased normalize clustering coefficient, global efficiency and local efficiency. Furthermore, we also found that white matter network hub regions were located in the left cuneus, precuneus, and left posterior cingulate gyrus. However, some abnormal nodes existed in the frontal, temporal, occipital and parietal lobes of cerebral palsy infants. These results indicated that the white matter networks for cerebral palsy infants were disrupted, which was consistent with previous studies about the abnormal brain white matter areas. This work could help us further study the pathogenesis of cerebral palsy infants.

Disrupted small world topology and modular organisation of functional networks in late-life depression with and without amnestic mild cognitive impairment.

PubMed

Li, Wenjun; Douglas Ward, B; Liu, Xiaolin; Chen, Gang; Jones, Jennifer L; Antuono, Piero G; Li, Shi-Jiang; Goveas, Joseph S

2015-10-01

The topological architecture of the whole-brain functional networks in those with and without late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are unknown. To investigate the differences in the small-world measures and the modular community structure of the functional networks between patients with LLD and aMCI when occurring alone or in combination and cognitively healthy non-depressed controls. 79 elderly participants (LLD (n=23), aMCI (n=18), comorbid LLD and aMCI (n=13), and controls (n=25)) completed neuropsychiatric assessments. Graph theoretical methods were employed on resting-state functional connectivity MRI data. LLD and aMCI comorbidity was associated with the greatest disruptions in functional integration measures (decreased global efficiency and increased path length); both LLD groups showed abnormal functional segregation (reduced local efficiency). The modular network organisation was most variable in the comorbid group, followed by patients with LLD-only. Decreased mean global, local and nodal efficiency metrics were associated with greater depressive symptom severity but not memory performance. Considering the whole brain as a complex network may provide unique insights on the neurobiological underpinnings of LLD with and without cognitive impairment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Intrathecal delivery of protein therapeutics to the brain: a critical reassessment.

PubMed

Calias, Pericles; Banks, William A; Begley, David; Scarpa, Maurizio; Dickson, Patricia

2014-11-01

Disorders of the central nervous system (CNS), including stroke, neurodegenerative diseases, and brain tumors, are the world's leading causes of disability. Delivery of drugs to the CNS is complicated by the blood-brain barriers that protect the brain from the unregulated leakage and entry of substances, including proteins, from the blood. Yet proteins represent one of the most promising classes of therapeutics for the treatment of CNS diseases. Many strategies for overcoming these obstacles are in development, but the relatively straightforward approach of bypassing these barriers through direct intrathecal administration has been largely overlooked. Originally discounted because of its lack of usefulness for delivering small, lipid-soluble drugs to the brain, the intrathecal route has emerged as a useful, in some cases perhaps the ideal, route of administration for certain therapeutic protein and targeted disease combinations. Here, we review blood-brain barrier functions and cerebrospinal fluid dynamics and their relevance to drug delivery via the intrathecal route, discuss animal and human studies that have investigated intrathecal delivery of protein therapeutics, and outline several characteristics of protein therapeutics that can allow them to be successfully delivered intrathecally. Copyright © 2014 Elsevier Inc. All rights reserved.

78 FR 19723 - Proposed Collection; 60-Day Comment Request; Evaluation of the Brain Disorders in the Developing...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-02

... Comment Request; Evaluation of the Brain Disorders in the Developing World Program of the John E. Fogarty...: Evaluation of the Brain Disorders in the Developing World Program of the John E. Fogarty International Center... Information Collection: This study seeks to evaluate the management, effectiveness, and outcomes of the Brain...

Coexistence of Stochastic Oscillations and Self-Organized Criticality in a Neuronal Network: Sandpile Model Application.

PubMed

Saeedi, Alireza; Jannesari, Mostafa; Gharibzadeh, Shahriar; Bakouie, Fatemeh

2018-04-01

Self-organized criticality (SOC) and stochastic oscillations (SOs) are two theoretically contradictory phenomena that are suggested to coexist in the brain. Recently it has been shown that an accumulation-release process like sandpile dynamics can generate SOC and SOs simultaneously. We considered the effect of the network structure on this coexistence and showed that the sandpile dynamics on a small-world network can produce two power law regimes along with two groups of SOs-two peaks in the power spectrum of the generated signal simultaneously. We also showed that external stimuli in the sandpile dynamics do not affect the coexistence of SOC and SOs but increase the frequency of SOs, which is consistent with our knowledge of the brain.

Development of large-scale functional brain networks in children.

PubMed

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder

PubMed Central

Chen, Jian-Huai; Yao, Zhi-Jian; Qin, Jiao-Long; Yan, Rui; Hua, Ling-Ling; Lu, Qing

2016-01-01

Background: Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD). Moreover, the exactly topological organization of networks underlying MDD remains unclear. This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients. Methods: The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls. The brain fractional anisotropy-weighted structural networks were constructed, and the global network and regional nodal metrics of the networks were explored by the complex network theory. Results: Compared with the healthy controls, the brain structural network of MDD patients showed an intact small-world topology, but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found. Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions. Conclusions: All these resulted in a less optimal topological organization of networks underlying MDD patients, including an impaired capability of local information processing, reduced centrality of some brain regions and limited capacity to integrate information across different regions. Thus, these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network. PMID:26960371

Development of Human Brain Structural Networks Through Infancy and Childhood

PubMed Central

Huang, Hao; Shu, Ni; Mishra, Virendra; Jeon, Tina; Chalak, Lina; Wang, Zhiyue J.; Rollins, Nancy; Gong, Gaolang; Cheng, Hua; Peng, Yun; Dong, Qi; He, Yong

2015-01-01

During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers. PMID:24335033

Cognitive Processes in Decisions Under Risk are not the Same as in Decisions Under Uncertainty

PubMed Central

Volz, Kirsten G.; Gigerenzer, Gerd

2012-01-01

We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (“small world”), all alternatives, consequences, and probabilities are known. In uncertain (“large”) worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries), with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift toward studying decision processes in uncertain worlds and provide first examples. PMID:22807893

Use of Head Guards in AIBA Boxing Tournaments-A Cross-Sectional Observational Study.

PubMed

Loosemore, Michael P; Butler, Charles F; Khadri, Abdelhamid; McDonagh, David; Patel, Vimal A; Bailes, Julian E

2017-01-01

This study looks at the changes in injuries after the implementation of a new rule by the International Boxing Association (AIBA) to remove head guards from its competitions. A cross-sectional observational study performed prospectively. This brief report examines the removal of head guards in 2 different ways. The first was to examine the stoppages due to blows to the head by comparing World Series Boxing (WSB), without head guards, to other AIBA competitions with head guards. Secondly, we examined the last 3 world championships: 2009 and 2011 (with head guards) and 2013 (without head guards). World Series Boxing and AIBA world championship boxing. Boxers from WSB and AIBA world championships. The information was recorded by ringside medical physicians. Stoppages per 10 000 rounds; stoppages per 1000 hours. Both studies show that the number of stoppages due to head blows was significantly decreased without head guards. The studies also showed that there was a notable increase in cuts. Removing head guards may reduce the already small risk of acute brain injury in amateur boxing.

Graph-based network analysis of resting-state functional MRI.

PubMed

Wang, Jinhui; Zuo, Xinian; He, Yong

2010-01-01

In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

Brain Injury Differences in Frontal Impact Crash Using Different Simulation Strategies

PubMed Central

Ma, Chunsheng; Shen, Ming; Li, Peiyu; Zhang, Jinhuan

2015-01-01

In the real world crashes, brain injury is one of the leading causes of deaths. Using isolated human head finite element (FE) model to study the brain injury patterns and metrics has been a simplified methodology widely adopted, since it costs significantly lower computation resources than a whole human body model does. However, the degree of precision of this simplification remains questionable. This study compared these two kinds of methods: (1) using a whole human body model carried on the sled model and (2) using an isolated head model with prescribed head motions, to study the brain injury. The distribution of the von Mises stress (VMS), maximum principal strain (MPS), and cumulative strain damage measure (CSDM) was used to compare the two methods. The results showed that the VMS of brain mainly concentrated at the lower cerebrum and occipitotemporal region close to the cerebellum. The isolated head modelling strategy predicted higher levels of MPS and CSDM 5%, while the difference is small in CSDM 10% comparison. It suggests that isolated head model may not equivalently reflect the strain levels below the 10% compared to the whole human body model. PMID:26495029

Genetics Home Reference: COL4A1-related brain small-vessel disease

MedlinePlus

... COL4A1-related brain small-vessel disease COL4A1-related brain small-vessel disease Printable PDF Open All Close ... view the expand/collapse boxes. Description COL4A1 -related brain small-vessel disease is part of a group ...

The resilient brain and the guardians of sleep: New perspectives on old assumptions.

PubMed

Parrino, Liborio; Vaudano, Anna Elisabetta

2018-06-01

Resilience is the capacity of a system, enterprise or a person to maintain its core purpose and integrity in the face of dramatically changed circumstances. In human physiology, resilience is the capacity of adaptively overcoming stress and adversity while maintaining normal psychological and physical functioning. In this review, we investigate the resilient strategies of sleep. First, we discuss the concept of brain resilience, highlighting the modular structure of small-world networking, neuronal plasticity and critical brain behavior. Second, we explore the contribution of sleep to brain resilience listing the putative factors that impair sleep quality and predict susceptibility to sleep disorders. The third part details the manifold mechanisms acting as guardians of sleep, i.e., homeostatic, circadian and ultradian processes, sleep microstructure (K-complexes, delta bursts, arousals, cyclic alternating pattern, spindles), gravity, muscle tone and dreams. Mapping and pooling together the guardians of sleep in a dynamic integrated framework might lead towards an objective measure of sleep resilience and identify effective personalized strategies (biological, pharmacological, behavioral) to restore or protect the core properties of healthy sleep. Copyright © 2017 Elsevier Ltd. All rights reserved.

Whole-brain structural topology in adult attention-deficit/hyperactivity disorder: Preserved global - disturbed local network organization.

PubMed

Sidlauskaite, Justina; Caeyenberghs, Karen; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R

2015-01-01

Prior studies demonstrate altered organization of functional brain networks in attention-deficit/hyperactivity disorder (ADHD). However, the structural underpinnings of these functional disturbances are poorly understood. In the current study, we applied a graph-theoretic approach to whole-brain diffusion magnetic resonance imaging data to investigate the organization of structural brain networks in adults with ADHD and unaffected controls using deterministic fiber tractography. Groups did not differ in terms of global network metrics - small-worldness, global efficiency and clustering coefficient. However, there were widespread ADHD-related effects at the nodal level in relation to local efficiency and clustering. The affected nodes included superior occipital, supramarginal, superior temporal, inferior parietal, angular and inferior frontal gyri, as well as putamen, thalamus and posterior cerebellum. Lower local efficiency of left superior temporal and supramarginal gyri was associated with higher ADHD symptom scores. Also greater local clustering of right putamen and lower local clustering of left supramarginal gyrus correlated with ADHD symptom severity. Overall, the findings indicate preserved global but altered local network organization in adult ADHD implicating regions underpinning putative ADHD-related neuropsychological deficits.

Material translations in the Cartesian brain.

PubMed

Bassiri, Nima

2012-03-01

This article reexamines the controversial doctrine of the pineal gland in Cartesian psychophysiology. It argues initially that Descartes' combined metaphysics and natural philosophy yield a distinctly human subject who is rational, willful, but also a living and embodied being in the world, formed in the union and through the dynamics of the interaction between the soul and the body. However, Descartes only identified one site at which this union was staged: the brain, and more precisely, the pineal gland, the small bulb of nervous tissue at the brain's center. The pineal gland was charged with the incredible task of ensuring the interactive mutuality between the soul and body, while also maintaining the necessary ontological incommensurability between them. This article reconsiders the theoretical obligations placed on the pineal gland as the site of the soul-body union, and looks at how the gland was consequently forced to adopt a very precarious ontological status. The article ultimately questions how successfully the Cartesian human could be localized in the pineal gland, while briefly considering the broader historical consequences of the ensuing equivalence of the self and brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Connectomics-based analysis of information flow in the Drosophila brain.

PubMed

Shih, Chi-Tin; Sporns, Olaf; Yuan, Shou-Li; Su, Ta-Shun; Lin, Yen-Jen; Chuang, Chao-Chun; Wang, Ting-Yuan; Lo, Chung-Chuang; Greenspan, Ralph J; Chiang, Ann-Shyn

2015-05-18

Understanding the overall patterns of information flow within the brain has become a major goal of neuroscience. In the current study, we produced a first draft of the Drosophila connectome at the mesoscopic scale, reconstructed from 12,995 images of neuron projections collected in FlyCircuit (version 1.1). Neuron polarities were predicted according to morphological criteria, with nodes of the network corresponding to brain regions designated as local processing units (LPUs). The weight of each directed edge linking a pair of LPUs was determined by the number of neuron terminals that connected one LPU to the other. The resulting network showed hierarchical structure and small-world characteristics and consisted of five functional modules that corresponded to sensory modalities (olfactory, mechanoauditory, and two visual) and the pre-motor center. Rich-club organization was present in this network and involved LPUs in all sensory centers, and rich-club members formed a putative motor center of the brain. Major intra- and inter-modular loops were also identified that could play important roles for recurrent and reverberant information flow. The present analysis revealed whole-brain patterns of network structure and information flow. Additionally, we propose that the overall organizational scheme showed fundamental similarities to the network structure of the mammalian brain. Copyright © 2015 Elsevier Ltd. All rights reserved.

Disrupted topology of hippocampal connectivity is associated with short-term antidepressant response in major depressive disorder.

PubMed

Gong, Liang; Hou, Zhenghua; Wang, Zan; He, Cancan; Yin, Yingying; Yuan, Yonggui; Zhang, Haisan; Lv, Luxian; Zhang, Hongxing; Xie, Chunming; Zhang, Zhijun

2018-01-01

Graph theoretical analyses have identified disrupted functional topological organization across the brain in patients with major depressive disorder (MDD). However, the relationship between brain topology and short-term treatment responses in patients with MDD remains unknown. Sixty-eight patients with MDD and 63 cognitively normal (CN) subjects were recruited at baseline and underwent resting-state functional magnetic resonance imaging scans. Graph theory analysis was used to examine group differences in the whole-brain functional topological properties. The association between altered brain topology and the early antidepressant response was examined. Patients with MDD showed lower normalized clustering coefficients, lower small-worldness scalars and increased nodal efficiencies in the default mode network and decreased nodal efficiencies in basal ganglia and hippocampal networks. In addition, the decreased nodal efficiency in left hippocampus was negatively correlated with depressive severity at baseline and positively correlated with changes in the depressive scores after two weeks of antidepressant treatment. The patients in the present study received different medications. These findings indicated that the altered brain functional topological organization in patients with MDD is associated with the treatment response in the early phase of medication. Therefore, brain topology assessments might be considered a useful and convenient predictor of short-term antidepressant responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease.

PubMed

Xu, Jinping; Zhang, Jiuquan; Zhang, Jinlei; Wang, Yue; Zhang, Yanling; Wang, Jian; Li, Guanglin; Hu, Qingmao; Zhang, Yuanchao

2017-01-01

Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups. Compared with the HC group, PD patients showed significantly increased integrated characteristic path length and integrated clustering coefficient, as well as decreased integrated global efficiency in structural brain networks. Distinct distributions of hub regions were identified between the two groups, showing more hub regions in the frontal cortex in PD patients. Moreover, the modular analyses revealed significantly decreased integrated regional efficiency in lateral Fronto-Insula-Temporal module, and increased integrated regional efficiency in Parieto-Temporal module in the PD group as compared to the HC group. In summary, our study demonstrated altered topological properties of structural networks at a global, regional and modular level in PD patients. These findings suggests that the structural networks of PD patients have a suboptimal topological organization, resulting in less effective integration of information between brain regions.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Altered brain structural connectivity in post-traumatic stress disorder: a diffusion tensor imaging tractography study.

PubMed

Long, Zhiliang; Duan, Xujun; Xie, Bing; Du, Handan; Li, Rong; Xu, Qiang; Wei, Luqing; Zhang, Shao-xiang; Wu, Yi; Gao, Qing; Chen, Huafu

2013-09-25

Post-traumatic stress disorder (PTSD) is characterized by dysfunction of several discrete brain regions such as medial prefrontal gyrus with hypoactivation and amygdala with hyperactivation. However, alterations of large-scale whole brain topological organization of structural networks remain unclear. Seventeen patients with PTSD in motor vehicle accident survivors and 15 normal controls were enrolled in our study. Large-scale structural connectivity network (SCN) was constructed using diffusion tensor tractography, followed by thresholding the mean factional anisotropy matrix of 90 brain regions. Graph theory analysis was then employed to investigate their aberrant topological properties. Both patient and control group showed small-world topology in their SCNs. However, patients with PTSD exhibited abnormal global properties characterized by significantly decreased characteristic shortest path length and normalized characteristic shortest path length. Furthermore, the patient group showed enhanced nodal centralities predominately in salience network including bilateral anterior cingulate and pallidum, and hippocampus/parahippocamus gyrus, and decreased nodal centralities mainly in medial orbital part of superior frontal gyrus. The main limitation of this study is the small sample of PTSD patients, which may lead to decrease the statistic power. Consequently, this study should be considered an exploratory analysis. These results are consistent with the notion that PTSD can be understood by investigating the dysfunction of large-scale, spatially distributed neural networks, and also provide structural evidences for further exploration of neurocircuitry models in PTSD. © 2013 Elsevier B.V. All rights reserved.

The correlation of metrics in complex networks with applications in functional brain networks

NASA Astrophysics Data System (ADS)

Li, C.; Wang, H.; de Haan, W.; Stam, C. J.; Van Mieghem, P.

2011-11-01

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we investigate the linear correlation coefficients between widely studied network metrics in three network models (Bárabasi-Albert graphs, Erdös-Rényi random graphs and Watts-Strogatz small-world graphs) as well as in functional brain networks of healthy subjects. The metric correlations, which we have observed and theoretically explained, motivate us to propose a small representative set of metrics by including only one metric from each subset of mutually strongly dependent metrics. The following contributions are considered important. (a) A network with a given degree distribution can indeed be characterized by a small representative set of metrics. (b) Unweighted networks, which are obtained from weighted functional brain networks with a fixed threshold, and Erdös-Rényi random graphs follow a similar degree distribution. Moreover, their metric correlations and the resultant representative metrics are similar as well. This verifies the influence of degree distribution on metric correlations. (c) Most metric correlations can be explained analytically. (d) Interestingly, the most studied metrics so far, the average shortest path length and the clustering coefficient, are strongly correlated and, thus, redundant. Whereas spectral metrics, though only studied recently in the context of complex networks, seem to be essential in network characterizations. This representative set of metrics tends to both sufficiently and effectively characterize networks with a given degree distribution. In the study of a specific network, however, we have to at least consider the representative set so that important network properties will not be neglected.

Large-scale brain networks in the awake, truly resting marmoset monkey.

PubMed

Belcher, Annabelle M; Yen, Cecil C; Stepp, Haley; Gu, Hong; Lu, Hanbing; Yang, Yihong; Silva, Afonso C; Stein, Elliot A

2013-10-16

Resting-state functional MRI is a powerful tool that is increasingly used as a noninvasive method for investigating whole-brain circuitry and holds great potential as a possible diagnostic for disease. Despite this potential, few resting-state studies have used animal models (of which nonhuman primates represent our best opportunity of understanding complex human neuropsychiatric disease), and no work has characterized networks in awake, truly resting animals. Here we present results from a small New World monkey that allows for the characterization of resting-state networks in the awake state. Six adult common marmosets (Callithrix jacchus) were acclimated to light, comfortable restraint using individualized helmets. Following behavioral training, resting BOLD data were acquired during eight consecutive 10 min scans for each conscious subject. Group independent component analysis revealed 12 brain networks that overlap substantially with known anatomically constrained circuits seen in the awake human. Specifically, we found eight sensory and "lower-order" networks (four visual, two somatomotor, one cerebellar, and one caudate-putamen network), and four "higher-order" association networks (one default mode-like network, one orbitofrontal, one frontopolar, and one network resembling the human salience network). In addition to their functional relevance, these network patterns bear great correspondence to those previously described in awake humans. This first-of-its-kind report in an awake New World nonhuman primate provides a platform for mechanistic neurobiological examination for existing disease models established in the marmoset.

The effect of education on regional brain metabolism and its functional connectivity in an aged population utilizing positron emission tomography.

PubMed

Kim, Jaeik; Chey, Jeanyung; Kim, Sang-Eun; Kim, Hoyoung

2015-05-01

Education involves learning new information and acquiring cognitive skills. These require various cognitive processes including learning, memory, and language. Since cognitive processes activate associated brain areas, we proposed that the brains of elderly people with longer education periods would show traces of repeated activation as increased synaptic connectivity and capillary in brain areas involved in learning, memory, and language. Utilizing positron emission topography (PET), this study examined the effect of education in the human brain utilizing the regional cerebral glucose metabolism rates (rCMRglcs). 26 elderly women with high-level education (HEG) and 26 with low-level education (LEG) were compared with regard to their regional brain activation and association between the regions. Further, graphical theoretical analysis using rCMRglcs was applied to examine differences in the functional network properties of the brain. The results showed that the HEG had higher rCMRglc in the ventral cerebral regions that are mainly involved in memory, language, and neurogenesis, while the LEG had higher rCMRglc in apical areas of the cerebrum mainly involved in motor and somatosensory functions. Functional connectivity investigated with graph theoretical analysis illustrated that the brain of the HEG compared to those of the LEG were overall more efficient, more resilient, and characterized by small-worldness. This may be one of the brain's mechanisms mediating the reserve effects found in people with higher education. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Development of human brain structural networks through infancy and childhood.

PubMed

Huang, Hao; Shu, Ni; Mishra, Virendra; Jeon, Tina; Chalak, Lina; Wang, Zhiyue J; Rollins, Nancy; Gong, Gaolang; Cheng, Hua; Peng, Yun; Dong, Qi; He, Yong

2015-05-01

During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

PubMed

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

Altered brain structural networks in attention deficit/hyperactivity disorder children revealed by cortical thickness.

PubMed

Liu, Tian; Chen, Yanni; Li, Chenxi; Li, Youjun; Wang, Jue

2017-07-04

This study investigated the cortical thickness and topological features of human brain anatomical networks related to attention deficit/hyperactivity disorder. Data were collected from 40 attention deficit/hyperactivity disorder children and 40 normal control children. Interregional correlation matrices were established by calculating the correlations of cortical thickness between all pairs of cortical regions (68 regions) of the whole brain. Further thresholds were applied to create binary matrices to construct a series of undirected and unweighted graphs, and global, local, and nodal efficiencies were computed as a function of the network cost. These experimental results revealed abnormal cortical thickness and correlations in attention deficit/hyperactivity disorder, and showed that the brain structural networks of attention deficit/hyperactivity disorder subjects had inefficient small-world topological features. Furthermore, their topological properties were altered abnormally. In particular, decreased global efficiency combined with increased local efficiency in attention deficit/hyperactivity disorder children led to a disorder-related shift of the network topological structure toward regular networks. In addition, nodal efficiency, cortical thickness, and correlation analyses revealed that several brain regions were altered in attention deficit/hyperactivity disorder patients. These findings are in accordance with a hypothesis of dysfunctional integration and segregation of the brain in patients with attention deficit/hyperactivity disorder and provide further evidence of brain dysfunction in attention deficit/hyperactivity disorder patients by observing cortical thickness on magnetic resonance imaging.

Cross-population myelination covariance of human cerebral cortex.

PubMed

Ma, Zhiwei; Zhang, Nanyin

2017-09-01

Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small-worldness. Furthermore, we found that the correlation between myelination covariance and resting-state functional connectivity (RSFC) was uniform within each resting-state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance-RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730-4743, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

ELUCIDATING BRAIN CONNECTIVITY NETWORKS IN MAJOR DEPRESSIVE DISORDER USING CLASSIFICATION-BASED SCORING.

PubMed

Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

2014-04-01

Graph theory is increasingly used in the field of neuroscience to understand the large-scale network structure of the human brain. There is also considerable interest in applying machine learning techniques in clinical settings, for example, to make diagnoses or predict treatment outcomes. Here we used support-vector machines (SVMs), in conjunction with whole-brain tractography, to identify graph metrics that best differentiate individuals with Major Depressive Disorder (MDD) from nondepressed controls. To do this, we applied a novel feature-scoring procedure that incorporates iterative classifier performance to assess feature robustness. We found that small-worldness , a measure of the balance between global integration and local specialization, most reliably differentiated MDD from nondepressed individuals. Post-hoc regional analyses suggested that heightened connectivity of the subcallosal cingulate gyrus (SCG) in MDDs contributes to these differences. The current study provides a novel way to assess the robustness of classification features and reveals anomalies in large-scale neural networks in MDD.

Neural encoding of large-scale three-dimensional space-properties and constraints.

PubMed

Jeffery, Kate J; Wilson, Jonathan J; Casali, Giulio; Hayman, Robin M

2015-01-01

How the brain represents represent large-scale, navigable space has been the topic of intensive investigation for several decades, resulting in the discovery that neurons in a complex network of cortical and subcortical brain regions co-operatively encode distance, direction, place, movement etc. using a variety of different sensory inputs. However, such studies have mainly been conducted in simple laboratory settings in which animals explore small, two-dimensional (i.e., flat) arenas. The real world, by contrast, is complex and three dimensional with hills, valleys, tunnels, branches, and-for species that can swim or fly-large volumetric spaces. Adding an additional dimension to space adds coding challenges, a primary reason for which is that several basic geometric properties are different in three dimensions. This article will explore the consequences of these challenges for the establishment of a functional three-dimensional metric map of space, one of which is that the brains of some species might have evolved to reduce the dimensionality of the representational space and thus sidestep some of these problems.

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

PubMed Central

Xu, Tingting; Cullen, Kathryn R.; Mueller, Bryon; Schreiner, Mindy W.; Lim, Kelvin O.; Schulz, S. Charles; Parhi, Keshab K.

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works. PMID:26977400

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

PubMed

Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works.

Reduced small world brain connectivity in probands with a family history of epilepsy.

PubMed

Bharath, R D; Chaitanya, G; Panda, R; Raghavendra, K; Sinha, S; Sahoo, A; Gohel, S; Biswal, B B; Satishchandra, P

2016-12-01

The role of inheritance in ascertaining susceptibility to epilepsy is well established, although the pathogenetic mechanisms are still not very clear. Interviewing for a positive family history is a popular epidemiological tool in the understanding of this susceptibility. Our aim was to visualize and localize network abnormalities that could be associated with a positive family history in a group of patients with hot water epilepsy (HWE) using resting-state functional magnetic resonance imaging (rsfMRI). Graph theory analysis of rsfMRI (clustering coefficient γ; path length λ; small worldness σ) in probands with a positive family history of epilepsy (FHE+, 25) were compared with probands without FHE (FHE-, 33). Whether a closer biological relationship was associated with a higher likelihood of network abnormalities was also ascertained. A positive family history of epilepsy had decreased γ, increased λ and decreased σ in bilateral temporofrontal regions compared to FHE- (false discovery rate corrected P ≤ 0.0062). These changes were more pronounced in probands having first degree relatives and siblings with epilepsy. Probands with multiple types of epilepsy in the family showed decreased σ in comparison to only HWE in the family. Graph theory analysis of the rsfMRI can be used to understand the neurobiology of diseases like genetic susceptibility in HWE. Reduced small worldness, proportional to the degree of relationship, is consistent with the current understanding that disease severity is higher in closer biological relations. © 2016 EAN.

From Brain-Environment Connections to Temporal Dynamics and Social Interaction: Principles of Human Brain Function.

PubMed

Hari, Riitta

2017-06-07

Experimental data about brain function accumulate faster than does our understanding of how the brain works. To tackle some general principles at the grain level of behavior, I start from the omnipresent brain-environment connection that forces regularities of the physical world to shape the brain. Based on top-down processing, added by sparse sensory information, people are able to form individual "caricature worlds," which are similar enough to be shared among other people and which allow quick and purposeful reactions to abrupt changes. Temporal dynamics and social interaction in natural environments serve as further essential organizing principles of human brain function. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain-to-Brain Synchrony and Learning Outcomes Vary by Student-Teacher Dynamics: Evidence from a Real-world Classroom Electroencephalography Study.

PubMed

Bevilacqua, Dana; Davidesco, Ido; Wan, Lu; Oostrik, Matthias; Chaloner, Kim; Rowland, Jess; Ding, Mingzhou; Poeppel, David; Dikker, Suzanne

2018-04-30

How does the human brain support real-world learning? We used wireless electroencephalography to collect neurophysiological data from a group of 12 senior high school students and their teacher during regular biology lessons. Six scheduled classes over the course of the semester were organized such that class materials were presented using different teaching styles (videos and lectures), and students completed a multiple-choice quiz after each class to measure their retention of that lesson's content. Both students' brain-to-brain synchrony and their content retention were higher for videos than lectures across the six classes. Brain-to-brain synchrony between the teacher and students varied as a function of student engagement as well as teacher likeability: Students who reported greater social closeness to the teacher showed higher brain-to-brain synchrony with the teacher, but this was only the case for lectures, that is, when the teacher is an integral part of the content presentation. Furthermore, students' retention of the class content correlated with student-teacher closeness, but not with brain-to-brain synchrony. These findings expand on existing social neuroscience research by showing that social factors such as perceived closeness are reflected in brain-to-brain synchrony in real-world group settings and can predict cognitive outcomes such as students' academic performance.

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

PubMed Central

Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei

2017-01-01

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197

Robert Sylwester on Electronic Media and Brain Development. Windows to the Mind, Volume 2. [Videotape].

ERIC Educational Resources Information Center

Sylwester, Robert

This videotape explores the influence of electronic media on children's cognitive development. Posing the "cyberworld" as both a window to the greater world and a mirror to the students' world, the first part of the video examines electronic media and the brain's response systems. This part notes the brain's two response systems--the…

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

PubMed

Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

2012-01-01

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Brain metastasis in lung cancer: Building a molecular and systems-level understanding to improve outcomes.

PubMed

Ebben, Johnathan D; You, Ming

2016-09-01

Lung cancer is a clinically difficult disease with rising disease burden around the world. Unfortunately, most lung cancers present at a clinically advanced stage. Of these cancers, many also present with brain metastasis which complicates the clinical picture. This review summarizes current knowledge on the molecular basis of lung cancer brain metastases. We start from the clinical perspective, aiming to provide a clinical context for a significant problem that requires much deeper scientific investigation. We review new research governing the metastatic process, including tumor cell signaling, establishment of a receptive tumor niches in the brain and evaluate potential new therapeutic options that take advantage of these new scientific advances. Lung cancer remains the largest single cause of cancer mortality in the United States (Siegel et al., 2015). This continues to be the clinical picture despite significant advances in therapy, including the advent of targeted molecular therapies and newly adopted immunotherapies for certain subtypes of lung cancer. In the vast majority of cases, lung cancer presents as advanced disease; in many instances, this advanced disease state is intimately associated with micro and macrometastatic disease (Goldberg et al., 2015). For both non-small cell lung cancer and small cell lung cancer patients, the predominant metastatic site is the brain, with up to 68% of patients with mediastinal lymph node metastasis eventually demonstrating brain metastasis (Wang et al., 2009).The frequency (incidence) of brain metastasis is highest in lung cancers, relative to other common epithelial malignancies (Schouten et al., 2002). Other studies have attempted to predict the risk of brain metastasis in the setting of previously non-metastatic disease. One of the largest studies to do this, analyzing historical data from 1973 to 2011 using the SEER database revealed a 9% risk of patients with previously non-metastatic NSCLC developing brain metastasis over the course of their disease, while 18% of small cell lung cancer patients without previous metastasis went on to develop brain metastasis as their disease progressed (Goncalves et al., 2016).The reasons underlying this predilection for the central nervous system, as well as the recent increase in the frequency of brain metastasis identified in patients remain important questions for both clinicians and basic scientists. More than ever, the question of how brain metastasis develop and how they can be treated and managed requires the involvement of interdisciplinary teams-and more importantly-scientists who are capable of thinking like clinicians and clinicians who are capable of thinking like scientists. This review aims to present a translational perspective on brain metastasis. We will investigate the scope of the problem of brain metastasis and the current management of the metastatic disease process in lung cancer. From this clinical starting point, we will investigate the literature surrounding the molecular underpinnings of lung tumor metastasis and seek to understand the process from a biological perspective to generate new hypotheses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interictal to Ictal Phase Transition in a Small-World Network

NASA Astrophysics Data System (ADS)

Nemzer, Louis; Cravens, Gary; Worth, Robert

Real-time detection and prediction of seizures in patients with epilepsy is essential for rapid intervention. Here, we perform a full Hodgkin-Huxley calculation using n 50 in silico neurons configured in a small-world network topology to generate simulated EEG signals. The connectivity matrix, constructed using a Watts-Strogatz algorithm, admits randomized or deterministic entries. We find that situations corresponding to interictal (non-seizure) and ictal (seizure) states are separated by a phase transition that can be influenced by congenital channelopathies, anticonvulsant drugs, and connectome plasticity. The interictal phase exhibits scale-free phenomena, as characterized by a power law form of the spectral power density, while the ictal state suffers from pathological synchronization. We compare the results with intracranial EEG data and show how these findings may be used to detect or even predict seizure onset. Along with the balance of excitatory and inhibitory factors, the network topology plays a large role in determining the overall characteristics of brain activity. We have developed a new platform for testing the conditions that contribute to the phase transition between non-seizure and seizure states.

Decreased Functional Brain Connectivity in Adolescents with Internet Addiction

PubMed Central

Hong, Soon-Beom; Zalesky, Andrew; Cocchi, Luca; Fornito, Alex; Choi, Eun-Jung; Kim, Ho-Hyun; Suh, Jeong-Eun; Kim, Chang-Dai; Kim, Jae-Won; Yi, Soon-Hyung

2013-01-01

Background Internet addiction has become increasingly recognized as a mental disorder, though its neurobiological basis is unknown. This study used functional neuroimaging to investigate whole-brain functional connectivity in adolescents diagnosed with internet addiction. Based on neurobiological changes seen in other addiction related disorders, it was predicted that connectivity disruptions in adolescents with internet addiction would be most prominent in cortico-striatal circuitry. Methods Participants were 12 adolescents diagnosed with internet addiction and 11 healthy comparison subjects. Resting-state functional magnetic resonance images were acquired, and group differences in brain functional connectivity were analyzed using the network-based statistic. We also analyzed network topology, testing for between-group differences in key graph-based network measures. Results Adolescents with internet addiction showed reduced functional connectivity spanning a distributed network. The majority of impaired connections involved cortico-subcortical circuits (∼24% with prefrontal and ∼27% with parietal cortex). Bilateral putamen was the most extensively involved subcortical brain region. No between-group difference was observed in network topological measures, including the clustering coefficient, characteristic path length, or the small-worldness ratio. Conclusions Internet addiction is associated with a widespread and significant decrease of functional connectivity in cortico-striatal circuits, in the absence of global changes in brain functional network topology. PMID:23451272

The "silent" imprint of musical training.

PubMed

Klein, Carina; Liem, Franziskus; Hänggi, Jürgen; Elmer, Stefan; Jäncke, Lutz

2016-02-01

Playing a musical instrument at a professional level is a complex multimodal task requiring information integration between different brain regions supporting auditory, somatosensory, motor, and cognitive functions. These kinds of task-specific activations are known to have a profound influence on both the functional and structural architecture of the human brain. However, until now, it is widely unknown whether this specific imprint of musical practice can still be detected during rest when no musical instrument is used. Therefore, we applied high-density electroencephalography and evaluated whole-brain functional connectivity as well as small-world topologies (i.e., node degree) during resting state in a sample of 15 professional musicians and 15 nonmusicians. As expected, musicians demonstrate increased intra- and interhemispheric functional connectivity between those brain regions that are typically involved in music perception and production, such as the auditory, the sensorimotor, and prefrontal cortex as well as Broca's area. In addition, mean connectivity within this specific network was positively related to musical skill and the total number of training hours. Thus, we conclude that musical training distinctively shapes intrinsic functional network characteristics in such a manner that its signature can still be detected during a task-free condition. Hum Brain Mapp 37:536-546, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Reduced hemispheric asymmetry of brain anatomical networks in attention deficit hyperactivity disorder.

PubMed

Li, Dandan; Li, Ting; Niu, Yan; Xiang, Jie; Cao, Rui; Liu, Bo; Zhang, Hui; Wang, Bin

2018-05-11

Despite many studies reporting a variety of alterations in brain networks in patients with attention deficit hyperactivity disorder (ADHD), alterations in hemispheric anatomical networks are still unclear. In this study, we investigated topology alterations in hemispheric white matter in patients with ADHD and the relationship between these alterations and clinical features of the illness. Weighted hemispheric brain anatomical networks were first constructed for each of 40 right-handed patients with ADHD and 53 matched normal controls. Then, graph theoretical approaches were utilized to compute hemispheric topological properties. The small-world property was preserved in the hemispheric network. Furthermore, a significant group-by-hemisphere interaction was revealed in global efficiency, local efficiency and characteristic path length, attributed to the significantly reduced hemispheric asymmetry of global and local integration in patients with ADHD compared with normal controls. Specifically, reduced asymmetric regional efficiency was found in three regions. Finally, we found that the abnormal asymmetry of hemispheric brain anatomical network topology and regional efficiency were both associated with clinical features (the Adult ADHD Self-Report Scale and Wechsler Adult Intelligence Scale) in patients. Our findings provide new insights into the lateralized nature of hemispheric dysconnectivity and highlight the potential for using brain network measures of hemispheric asymmetry as neural biomarkers for ADHD and its clinical features.

Are We Ready for Real-world Neuroscience?

PubMed

Matusz, Pawel J; Dikker, Suzanne; Huth, Alexander G; Perrodin, Catherine

2018-06-19

Real-world environments are typically dynamic, complex, and multisensory in nature and require the support of top-down attention and memory mechanisms for us to be able to drive a car, make a shopping list, or pour a cup of coffee. Fundamental principles of perception and functional brain organization have been established by research utilizing well-controlled but simplified paradigms with basic stimuli. The last 30 years ushered a revolution in computational power, brain mapping, and signal processing techniques. Drawing on those theoretical and methodological advances, over the years, research has departed more and more from traditional, rigorous, and well-understood paradigms to directly investigate cognitive functions and their underlying brain mechanisms in real-world environments. These investigations typically address the role of one or, more recently, multiple attributes of real-world environments. Fundamental assumptions about perception, attention, or brain functional organization have been challenged-by studies adapting the traditional paradigms to emulate, for example, the multisensory nature or varying relevance of stimulation or dynamically changing task demands. Here, we present the state of the field within the emerging heterogeneous domain of real-world neuroscience. To be precise, the aim of this Special Focus is to bring together a variety of the emerging "real-world neuroscientific" approaches. These approaches differ in their principal aims, assumptions, or even definitions of "real-world neuroscience" research. Here, we showcase the commonalities and distinctive features of the different "real-world neuroscience" approaches. To do so, four early-career researchers and the speakers of the Cognitive Neuroscience Society 2017 Meeting symposium under the same title answer questions pertaining to the added value of such approaches in bringing us closer to accurate models of functional brain organization and cognitive functions.

Disrupted topological properties of brain white matter networks in left temporal lobe epilepsy: a diffusion tensor imaging study.

PubMed

Xu, Y; Qiu, S; Wang, J; Liu, Z; Zhang, R; Li, S; Cheng, L; Liu, Z; Wang, W; Huang, R

2014-10-24

Mesial temporal lobe epilepsy (mTLE) is the most common drug-refractory focal epilepsy in adults. Although previous functional and morphological studies have revealed abnormalities in the brain networks of mTLE, the topological organization of the brain white matter (WM) networks in mTLE patients is still ambiguous. In this study, we constructed brain WM networks for 14 left mTLE patients and 22 age- and gender-matched normal controls using diffusion tensor tractography and estimated the alterations of network properties in the mTLE brain networks using graph theoretical analysis. We found that networks for both the mTLE patients and the controls exhibited prominent small-world properties, suggesting a balanced topology of integration and segregation. However, the brain WM networks of mTLE patients showed a significant increased characteristic path length but significant decreased global efficiency, which indicate a disruption in the organization of the brain WM networks in mTLE patients. Moreover, we found significant between-group differences in the nodal properties in several brain regions, such as the left superior temporal gyrus, left hippocampus, the right occipital and right temporal cortices. The robustness analysis showed that the results were likely to be consistent for the networks constructed with different definitions of node and edge weight. Taken together, our findings may suggest an adverse effect of epileptic seizures on the organization of large-scale brain WM networks in mTLE patients. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Disrupted Structural Brain Network in AD and aMCI: A Finding of Long Fiber Degeneration.

PubMed

Fang, Rong; Yan, Xiao-Xiao; Wu, Zhi-Yuan; Sun, Yu; Yin, Qi-Hua; Wang, Ying; Tang, Hui-Dong; Sun, Jun-Feng; Miao, Fei; Chen, Sheng-Di

2015-01-01

Although recent evidence has emerged that Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) patients show both regional brain abnormalities and topological degeneration in brain networks, our understanding of the effects of white matter fiber aberrations on brain network topology in AD and aMCI is still rudimentary. In this study, we investigated the regional volumetric aberrations and the global topological abnormalities in AD and aMCI patients. The results showed a widely distributed atrophy in both gray and white matters in the AD and aMCI groups. In particular, AD patients had weaker connectivity with long fiber length than aMCI and normal control (NC) groups, as assessed by fractional anisotropy (FA). Furthermore, the brain networks of all three groups exhibited prominent economical small-world properties. Interestingly, the topological characteristics estimated from binary brain networks showed no significant group effect, indicating a tendency of preserving an optimal topological architecture in AD and aMCI during degeneration. However, significantly longer characteristic path length was observed in the FA weighted brain networks of AD and aMCI patients, suggesting dysfunctional global integration. Moreover, the abnormality of the characteristic path length was negatively correlated with the clinical ratings of cognitive impairment. Thus, the results therefore suggested that the topological alterations in weighted brain networks of AD are induced by the loss of connectivity with long fiber lengths. Our findings provide new insights into the alterations of the brain network in AD and may indicate the predictive value of the network metrics as biomarkers of disease development.

Big words, halved brains and small worlds: complex brain networks of figurative language comprehension.

PubMed

Arzouan, Yossi; Solomon, Sorin; Faust, Miriam; Goldstein, Abraham

2011-04-27

Language comprehension is a complex task that involves a wide network of brain regions. We used topological measures to qualify and quantify the functional connectivity of the networks used under various comprehension conditions. To that aim we developed a technique to represent functional networks based on EEG recordings, taking advantage of their excellent time resolution in order to capture the fast processes that occur during language comprehension. Networks were created by searching for a specific causal relation between areas, the negative feedback loop, which is ubiquitous in many systems. This method is a simple way to construct directed graphs using event-related activity, which can then be analyzed topologically. Brain activity was recorded while subjects read expressions of various types and indicated whether they found them meaningful. Slightly different functional networks were obtained for event-related activity evoked by each expression type. The differences reflect the special contribution of specific regions in each condition and the balance of hemispheric activity involved in comprehending different types of expressions and are consistent with the literature in the field. Our results indicate that representing event-related brain activity as a network using a simple temporal relation, such as the negative feedback loop, to indicate directional connectivity is a viable option for investigation which also derives new information about aspects not reflected in the classical methods for investigating brain activity.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

The influence of damage distribution on serious brain injury in occupants in frontal motor vehicle crashes.

PubMed

Coimbra, Raul; Conroy, Carol; Hoyt, David B; Pacyna, Sharon; May, MarSue; Erwin, Steve; Tominaga, Gail; Kennedy, Frank; Sise, Michael; Velky, Tom

2008-07-01

In spite of improvements in motor vehicle safety systems and crashworthiness, motor vehicle crashes remain one of the leading causes of brain injury. The purpose of this study was to determine if the damage distribution across the frontal plane affected brain injury severity of occupants in frontal impacts. Occupants in "head on" frontal impacts with a Principal Direction of Force (PDOF) equal to 11, 12, or 1o'clock who sustained serious brain injury were identified using the Crash Injury Research Engineering Network (CIREN) database. Impacts were further classified based on the damage distribution across the frontal plane as distributed, offset, and extreme offset (corner). Overall, there was no significant difference for brain injury severity (based on Glasgow Coma Scale<9, or brain injury AIS>2) comparing occupants in the different impact categories. For occupants in distributed frontal impacts, safety belt use was protective (odds ratio (OR)=0.61) and intrusion at the occupant's seat position was four times more likely to result in severe (Glasgow Coma Scale (GCS)<9) brain injury (OR=4.35). For occupants in offset frontal impacts, again safety belt use was protective against severe brain injury (OR=0.25). Possibly due to the small number of brain-injured occupants in corner impacts, safety belts did not significantly protect against increased brain injury severity during corner impacts. This study supports the importance of safety belt use to decrease brain injury severity for occupants in distributed and offset frontal crashes. It also illustrates how studying "real world" crashes may provide useful information on occupant injuries under impact circumstances not currently covered by crash testing.

A Hybrid CPU-GPU Accelerated Framework for Fast Mapping of High-Resolution Human Brain Connectome

PubMed Central

Ren, Ling; Xu, Mo; Xie, Teng; Gong, Gaolang; Xu, Ningyi; Yang, Huazhong; He, Yong

2013-01-01

Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson’s Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states. PMID:23675425

Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease.

PubMed

Mears, David; Pollard, Harvey B

2016-06-01

Over the past 15 years, the emerging field of network science has revealed the key features of brain networks, which include small-world topology, the presence of highly connected hubs, and hierarchical modularity. The value of network studies of the brain is underscored by the range of network alterations that have been identified in neurological and psychiatric disorders, including epilepsy, depression, Alzheimer's disease, schizophrenia, and many others. Here we briefly summarize the concepts of graph theory that are used to quantify network properties and describe common experimental approaches for analysis of brain networks of structural and functional connectivity. These range from tract tracing to functional magnetic resonance imaging, diffusion tensor imaging, electroencephalography, and magnetoencephalography. We then summarize the major findings from the application of graph theory to nervous systems ranging from Caenorhabditis elegans to more complex primate brains, including man. Focusing, then, on studies involving the amygdala, a brain region that has attracted intense interest as a center for emotional processing, fear, and motivation, we discuss the features of the amygdala in brain networks for fear conditioning and emotional perception. Finally, to highlight the utility of graph theory for studying dysfunction of the amygdala in mental illness, we review data with regard to changes in the hub properties of the amygdala in brain networks of patients with depression. We suggest that network studies of the human brain may serve to focus attention on regions and connections that act as principal drivers and controllers of brain function in health and disease. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Third World adversity: African infant precocity and the role of environment.

PubMed

Saugstad, Letten F

2002-01-01

The war against illiteracy has not been won. The number of illiterates approaches a billion. Most reside in Third World countries--former colonies--where they are caught in a poverty trap of disease, low agricultural production and environmental adversity requiring technology beyond their means. I argue against the commonly held view that this is mainly attributable to the four hundred years of traffic in men. According to the late K.O. Dike, middle men along the African coast barred foreign merchants from the hinterland, and because of this the social, political structure and sovereignty of the African states remained fundamentally unchanged during the period 1400-1807, whereas a few decades after colonisation the socio-political system collapsed and was replaced by a small rich elite and many poor, while resources were taken out of Africa. Present poverty and underdevelopment represent as great a challenge as the trade in slaves. As did the African Middle-Men of that time, African leaders now must unite in an ambitious and confident Pan-African Union demonstrating strength. Western countries should focus on reducing poverty and improving nutrition. This also makes terrorism and legal and illegal migration less likely. Education is important, but the West should not limit its effort to fighting illiteracy but should also support the establishment of institutions for higher education. Africa possessed optimal conditions and an enriched environment for human evolution. African Infant Precocity is a persistent example. The human brain, like other brains, consists 60% of poly-unsaturated fatty acids (Marine-Fat), the rest being water. A sufficient amount is required to secure optimal brain growth. It normalizes brain function, and prevents sudden cardiac and infant death, which have been increasing in Western societies. Humans are unique in having a mismatch between the need for brain food--marine fat--and our common high protein diet. Nowhere is the neglect of the brain greater than in pregnancy when protein is the only major nutrient considered. Declining levels of polyunsaturated fatty acids have been observed in human milk. Deficient intake could, if not corrected, gradually impair brain function as has been seen in animal experiments.

Safety Validation of Repeated Blood-Brain Barrier Disruption Using Focused Ultrasound.

PubMed

Kobus, Thiele; Vykhodtseva, Natalia; Pilatou, Magdalini; Zhang, Yongzhi; McDannold, Nathan

2016-02-01

The purpose of this study was to investigate the effects on the brain of multiple sessions of blood-brain barrier (BBB) disruption using focused ultrasound (FUS) in combination with micro-bubbles over a range of acoustic exposure levels. Six weekly sessions of FUS, using acoustical pressures between 0.66 and 0.80 MPa, were performed under magnetic resonance guidance. The success and degree of BBB disruption was estimated by signal enhancement of post-contrast T1-weighted imaging of the treated area. Histopathological analysis was performed after the last treatment. The consequences of repeated BBB disruption varied from no indications of vascular damage to signs of micro-hemorrhages, macrophage infiltration, micro-scar formations and cystic cavities. The signal enhancement on the contrast-enhanced T1-weighted imaging had limited value for predicting small-vessel damage. T2-weighted imaging corresponded well with the effects on histopathology and could be used to study treatment effects over time. This study demonstrates that repeated BBB disruption by FUS can be performed with no or limited damage to the brain tissue. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Study of amyloid-β peptide functional brain networks in AD, MCI and HC.

PubMed

Jiang, Jiehui; Duan, Huoqiang; Huang, Zheming; Yu, Zhihua

2015-01-01

One medical challenge in studying the amyloid-β (Aβ) peptide mechanism for Alzheimer's disease (AD) is exploring the law of beta toxic oligomers' diffusion in human brains in vivo. One beneficial means of solving this problem is brain network analysis based on graph theory. In this study, the characteristics of Aβ functional brain networks of Healthy Control (HC), Mild Cognitive Impairment (MCI), and AD groups were compared by applying graph theoretical analyses to Carbon 11-labeled Pittsburgh compound B positron emission tomography (11C PiB-PET) data. 120 groups of PiB-PET images from the ADNI database were analyzed. The results showed that the small-world property of MCI and AD were lost as compared to HC. Furthermore, the local clustering of networks was higher in both MCI and AD as compared to HC, whereas the path length was similar among the three groups. The results also showed that there could be four potential Aβ toxic oligomer seeds: Frontal_Sup_Medial_L, Parietal_Inf_L, Frontal_Med_Orb_R, and Parietal_Inf_R. These four seeds are corresponding to Regions of Interests referred by physicians to clinically diagnose AD.

Support Vector Machine Classification of Major Depressive Disorder Using Diffusion-Weighted Neuroimaging and Graph Theory

PubMed Central

Sacchet, Matthew D.; Prasad, Gautam; Foland-Ross, Lara C.; Thompson, Paul M.; Gotlib, Ian H.

2015-01-01

Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on “support vector machines” to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and comorbidities. PMID:25762941

Support vector machine classification of major depressive disorder using diffusion-weighted neuroimaging and graph theory.

PubMed

Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

2015-01-01

Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on "support vector machines" to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and comorbidities.

Disrupted Topological Patterns of Large-Scale Network in Conduct Disorder

PubMed Central

Jiang, Yali; Liu, Weixiang; Ming, Qingsen; Gao, Yidian; Ma, Ren; Zhang, Xiaocui; Situ, Weijun; Wang, Xiang; Yao, Shuqiao; Huang, Bingsheng

2016-01-01

Regional abnormalities in brain structure and function, as well as disrupted connectivity, have been found repeatedly in adolescents with conduct disorder (CD). Yet, the large-scale brain topology associated with CD is not well characterized, and little is known about the systematic neural mechanisms of CD. We employed graphic theory to investigate systematically the structural connectivity derived from cortical thickness correlation in a group of patients with CD (N = 43) and healthy controls (HCs, N = 73). Nonparametric permutation tests were applied for between-group comparisons of graphical metrics. Compared with HCs, network measures including global/local efficiency and modularity all pointed to hypo-functioning in CD, despite of preserved small-world organization in both groups. The hubs distribution is only partially overlapped with each other. These results indicate that CD is accompanied by both impaired integration and segregation patterns of brain networks, and the distribution of highly connected neural network ‘hubs’ is also distinct between groups. Such misconfiguration extends our understanding regarding how structural neural network disruptions may underlie behavioral disturbances in adolescents with CD, and potentially, implicates an aberrant cytoarchitectonic profiles in the brain of CD patients. PMID:27841320

Real-World Treatment Patterns, Survival, and Prediction of CNS Progression in ALK-Positive Non-Small-Cell Lung Cancer Patients Treated with First-Line Crizotinib in Latin America Oncology Practices.

PubMed

Martín, Claudio; Cardona, Andrés F; Zatarain-Barrón, Zyanya Lucia; Ruiz-Patiño, Alejandro; Castillo, Omar; Oblitas, George; Corrales, Luis; Lupinacci, Lorena; Pérez, María Angelina; Rojas, Leonardo; González, Lisde; Chirinos, Luis; Ortíz, Carlos; Lema, Mauricio; Vargas, Carlos; Puparelli, Carmen; Carranza, Hernán; Otero, Jorge; Arrieta, Oscar

2018-01-01

This study describes the real-world characteristics, treatment sequencing, and outcomes among Hispanic patients with locally advanced/metastatic ALK-positive non-small-cell lung cancer (NSCLC) treated with crizotinib. A retrospective patient review was conducted for several centers in Latin America. Clinicians identified ALK-positive NSCLC patients who received crizotinib and reported their clinical characteristics, treatments, and survival. Overall survival and progression-free survival (PFS) were described. A Random Forest Tree (RFT) model was constructed to predict brain progression. A total of 73 patients were included; median age at diagnosis was 58 years, 60.3% were female, and 93.2% had adenocarcinoma. Eighty-nine percent of patients were never smokers/former smokers, 71.1% had ≥2 sites of metastasis, and 20.5% had brain metastases at diagnosis. The median PFS on first-line crizotinib was 7.07 months (95% CI 3.77-12.37) and the overall response rate was 52%. Of those who discontinued crizotinib, 55.9% progressed in the central nervous system (CNS). The RFT model reached a sensitivity of 100% and a specificity of 88% for prediction of CNS progression. The overall response rate and the PFS observed in Hispanic patients with ALK-positive NSCLC treated with first-line crizotinib were similar to those in previous reports. An RFT model is helpful in predicting CNS progression and can help clinicians tailor treatments in a resource-limited practice. © 2018 S. Karger AG, Basel.

Right medial thalamic lesion causes isolated retrograde amnesia.

PubMed

Miller, L A; Caine, D; Harding, A; Thompson, E J; Large, M; Watson, J D

2001-01-01

Pervasive retrograde amnesia without anterograde memory impairment has rarely been described as a consequence of circumscribed brain damage. We report this phenomenon in a 33 yr-old, right-handed man (JG) in association with the extension in the right thalamus of a previously small, bilateral thalamic lesion. JG presented with a dense amnesia for autobiographical material more than a few years old, with some sparing of recent memories. Furthermore, he was completely unable to recognise famous people or world events. Many other aspects of semantic knowledge were intact and there was no evidence of general intellectual impairment, executive dysfunction or loss of visual imagery. Magnetic resonance imaging revealed an acute lesion in the right thalamus and two small, symmetrical, bilateral non-acute thalamic lesions. Follow-up neuropsychological assessment indicated a stable pattern of impaired retrograde and spared anterograde memory over 18 months and psychiatric assessments yielded no evidence of confabulation, malingering or other symptoms to suggest psychogenic amnesia. JG's profile indicates that the division of declarative memory into just two categories - episodic and semantic - is inadequate. Rather, his case adds to the growing body evidence to suggest that world knowledge pertaining to people and events is stored or accessed similarly to autobiographical information and differently from other types of more general factual knowledge. We hypothesize that the right mediodorsal thalamic nucleus and immediately surrounding regions comprise the central processing mechanism referred to by McClelland (Revue Neurologique, 150 (1994) 570) and Markowitsch (Brain Research Review, 21 (1995) 117) as responsible for inducing and co-ordinating the recall of these sorts of cortically stored memory engrams.

Bringing the Brain into Assessment.

ERIC Educational Resources Information Center

Caine, Geoffrey; Caine, Renate Nummela

1999-01-01

Brain research explains why testing for surface knowledge (memorization) reveals relatively little about real, usable knowledge. Assessment must contribute to real-world experience, relate to real-world performance, can never be fully translated into representative symbols or numbers, and can induce both helplessness (interference with meaningful…

Mapping the Alzheimer’s Brain with Connectomics

PubMed Central

Xie, Teng; He, Yong

2012-01-01

Alzheimer’s disease (AD) is the most common form of dementia. As an incurable, progressive, and neurodegenerative disease, it causes cognitive and memory deficits. However, the biological mechanisms underlying the disease are not thoroughly understood. In recent years, non-invasive neuroimaging and neurophysiological techniques [e.g., structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, and EEG/MEG] and graph theory based network analysis have provided a new perspective on structural and functional connectivity patterns of the human brain (i.e., the human connectome) in health and disease. Using these powerful approaches, several recent studies of patients with AD exhibited abnormal topological organization in both global and regional properties of neuronal networks, indicating that AD not only affects specific brain regions, but also alters the structural and functional associations between distinct brain regions. Specifically, disruptive organization in the whole-brain networks in AD is involved in the loss of small-world characters and the re-organization of hub distributions. These aberrant neuronal connectivity patterns were associated with cognitive deficits in patients with AD, even with genetic factors in healthy aging. These studies provide empirical evidence to support the existence of an aberrant connectome of AD. In this review we will summarize recent advances discovered in large-scale brain network studies of AD, mainly focusing on graph theoretical analysis of brain connectivity abnormalities. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis and monitoring. PMID:22291664

New World Tryptamine Hallucinogens and the Neuroscience of Ayahuasca.

PubMed

McKenna, Dennis; Riba, Jordi

2018-01-01

New World indigenous peoples are noted for their sophisticated use of psychedelic plants in shamanic and ethnomedical practices. The use of psychedelic plant preparations among New World tribes is far more prevalent than in the Old World. Yet, although these preparations are botanically diverse, almost all are chemically similar in that their active principles are tryptamine derivatives, either DMT or related constituents. Part 1 of this paper provides an ethnopharmacological overview of the major tryptamine-containing New World hallucinogens. Part 2 focuses on ayahuasca and its effects on the human brain. Using complementary neurophysiological and neuroimaging techniques, we have identified brain areas involved in the cognitive effects induced by this complex botanical preparation. Initial SPECT data showed that ayahuasca modulated activity in higher order association areas of the brain. Increased blood perfusion was observed mainly in anterior brain regions encompassing the frontomedial and anterior cingulate cortices of the frontal lobes, and in the medial regions of the temporal lobes. On the other hand, applying spectral analysis and source location techniques to cortical electrical signals, we found changes in neuronal activity that predominated in more posterior sensory-selective areas of the brain. Now, using functional connectivity analysis of brain oscillations we have been able to reconcile these seemingly contradictory findings. By measuring transfer entropy, a metric based on information theory, we have shown that ayahuasca temporarily modifies the ordinary flow of information within the brain. We propose a model in which ayahuasca reduces top-down constraints and facilitates bottom-up information transfer. By simultaneously enhancing endogenous cortical excitability and reducing higher-order cognitive control, ayahuasca temporarily disrupts neural hierarchies allowing inner exploration and a new outlook on reality.

Brain microvascular endothelium induced-annexin A1 secretion contributes to small cell lung cancer brain metastasis.

PubMed

Liu, Yi; Liu, Yong-Shuo; Wu, Peng-Fei; Li, Qiang; Dai, Wu-Min; Yuan, Shuai; Xu, Zhi-Hua; Liu, Ting-Ting; Miao, Zi-Wei; Fang, Wen-Gang; Chen, Yu-Hua; Li, Bo

2015-09-01

Small cell lung cancer is the most aggressive histologic subtype of lung cancer, with a strong predilection for metastasizing to brain early. However, the cellular and molecular basis is poorly known. Here, we provided evidence to reveal the role of annexin A1 in small cell lung cancer metastasis to brain. Firstly, the elevated annexin A1 serum levels in small cell lung cancer patients were associated with brain metastasis. The levels of annexin A1 were also upregulated in NCI-H446 cells, a small cell lung cancer cell line, upon migration into the mice brain. More interestingly, annexin A1 was secreted by NCI-H446 cells in a time-dependent manner when co-culturing with human brain microvascular endothelial cells, which was identified with the detections of annexin A1 in the co-cultured cellular supernatants by ELISA and western blot. Further results showed that blockage of annexin A1 in the co-cultured cellular supernatants using a neutralized antibody significantly inhibited NCI-H446 cells adhesion to brain endothelium and its transendothelial migration. Conversely, the addition of Ac2-26, an annexin A1 mimic peptide, enhanced these effects. Furthermore, knockdown of annexin A1 in NCI-H446 cells prevented its transendothelial migration in vitro and metastasis to mice brain in vivo. Our data showed that small cell lung cancer cell in brain microvasculature microenvironment could express much more annexin A1 and release it outside, which facilitated small cell lung cancer cell to gain malignant properties of entry into brain. These findings provided a potential target for the management of SCLC brain metastasis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.

PubMed

Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong

2014-12-01

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.

Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study.

PubMed

Sun, Yu; Chen, Yu; Lee, Renick; Bezerianos, Anastasios; Collinson, Simon L; Sim, Kang

2016-03-01

Despite convergent neuroimaging evidence indicating a wide range of brain abnormalities in schizophrenia, our understanding of alterations in the topological architecture of brain anatomical networks and how they are modulated over time, is still rudimentary. Here, we employed graph theoretical analysis of longitudinal diffusion tensor imaging data (DTI) over a 5-year period to investigate brain network topology in schizophrenia and its relationship with clinical manifestations of the illness. Using deterministic tractography, weighted brain anatomical networks were constructed from 31 patients experiencing schizophrenia and 28 age- and gender-matched healthy control subjects. Although the overall small-world characteristics were observed at both baseline and follow-up, a scan-point independent significant deficit of global integration was found in patients compared to controls, suggesting dysfunctional integration of the brain and supporting the notion of schizophrenia as a disconnection syndrome. Specifically, several brain regions (e.g., the inferior frontal gyrus and the bilateral insula) that are crucial for cognitive and emotional integration were aberrant. Furthermore, a significant group-by-longitudinal scan interaction was revealed in the characteristic path length and global efficiency, attributing to a progressive aberration of global integration in patients compared to healthy controls. Moreover, the progressive disruptions of the brain anatomical network topology were associated with the clinical symptoms of the patients. Together, our findings provide insights into the substrates of anatomical dysconnectivity patterns for schizophrenia and highlight the potential for connectome-based metrics as neural markers of illness progression and clinical change with treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

Information processing in the vertebrate habenula.

PubMed

Fore, Stephanie; Palumbo, Fabrizio; Pelgrims, Robbrecht; Yaksi, Emre

2018-06-01

The habenula is a brain region that has gained increasing popularity over the recent years due to its role in processing value-related and experience-dependent information with a strong link to depression, addiction, sleep and social interactions. This small diencephalic nucleus is proposed to act as a multimodal hub or a switchboard, where inputs from different brain regions converge. These diverse inputs to the habenula carry information about the sensory world and the animal's internal state, such as reward expectation or mood. However, it is not clear how these diverse habenular inputs interact with each other and how such interactions contribute to the function of habenular circuits in regulating behavioral responses in various tasks and contexts. In this review, we aim to discuss how information processing in habenular circuits, can contribute to specific behavioral programs that are attributed to the habenula. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications.

PubMed

Hemakom, Apit; Goverdovsky, Valentin; Looney, David; Mandic, Danilo P

2016-04-13

An extension to multivariate empirical mode decomposition (MEMD), termed adaptive-projection intrinsically transformed MEMD (APIT-MEMD), is proposed to cater for power imbalances and inter-channel correlations in real-world multichannel data. It is shown that the APIT-MEMD exhibits similar or better performance than MEMD for a large number of projection vectors, whereas it outperforms MEMD for the critical case of a small number of projection vectors within the sifting algorithm. We also employ the noise-assisted APIT-MEMD within our proposed intrinsic multiscale analysis framework and illustrate the advantages of such an approach in notoriously noise-dominated cooperative brain-computer interface (BCI) based on the steady-state visual evoked potentials and the P300 responses. Finally, we show that for a joint cognitive BCI task, the proposed intrinsic multiscale analysis framework improves system performance in terms of the information transfer rate. © 2016 The Author(s).

High-resolution, high-throughput imaging with a multibeam scanning electron microscope

PubMed Central

EBERLE, AL; MIKULA, S; SCHALEK, R; LICHTMAN, J; TATE, ML KNOTHE; ZEIDLER, D

2015-01-01

Electron–electron interactions and detector bandwidth limit the maximal imaging speed of single-beam scanning electron microscopes. We use multiple electron beams in a single column and detect secondary electrons in parallel to increase the imaging speed by close to two orders of magnitude and demonstrate imaging for a variety of samples ranging from biological brain tissue to semiconductor wafers. Lay Description The composition of our world and our bodies on the very small scale has always fascinated people, making them search for ways to make this visible to the human eye. Where light microscopes reach their resolution limit at a certain magnification, electron microscopes can go beyond. But their capability of visualizing extremely small features comes at the cost of a very small field of view. Some of the questions researchers seek to answer today deal with the ultrafine structure of brains, bones or computer chips. Capturing these objects with electron microscopes takes a lot of time – maybe even exceeding the time span of a human being – or new tools that do the job much faster. A new type of scanning electron microscope scans with 61 electron beams in parallel, acquiring 61 adjacent images of the sample at the same time a conventional scanning electron microscope captures one of these images. In principle, the multibeam scanning electron microscope’s field of view is 61 times larger and therefore coverage of the sample surface can be accomplished in less time. This enables researchers to think about large-scale projects, for example in the rather new field of connectomics. A very good introduction to imaging a brain at nanometre resolution can be found within course material from Harvard University on http://www.mcb80x.org/# as featured media entitled ‘connectomics’. PMID:25627873

Identification of a Functional Connectome for Long-Term Fear Memory in Mice

PubMed Central

Wheeler, Anne L.; Teixeira, Cátia M.; Wang, Afra H.; Xiong, Xuejian; Kovacevic, Natasa; Lerch, Jason P.; McIntosh, Anthony R.; Parkinson, John; Frankland, Paul W.

2013-01-01

Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression. PMID:23300432

Frequency specific patterns of resting-state networks development from childhood to adolescence: A magnetoencephalography study.

PubMed

Meng, Lu; Xiang, Jing

2016-11-01

The present study investigated frequency dependent developmental patterns of the brain resting-state networks from childhood to adolescence. Magnetoencephalography (MEG) data were recorded from 20 healthy subjects at resting-state with eyes-open. The resting-state networks (RSNs) was analyzed at source-level. Brain network organization was characterized by mean clustering coefficient and average path length. The correlations between brain network measures and subjects' age during development from childhood to adolescence were statistically analyzed in delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), and beta (12-30Hz) frequency bands. A significant positive correlation between functional connectivity with age was found in alpha and beta frequency bands. A significant negative correlation between average path lengths with age was found in beta frequency band. The results suggest that there are significant developmental changes of resting-state networks from childhood to adolescence, which matures from a lattice network to a small-world network. Copyright © 2016 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

The Field Relevance of NHTSA's Oblique Research Moving Deformable Barrier Tests.

PubMed

Prasad, Priya; Dalmotas, Dainius; German, Alan

2014-11-01

A small overlap frontal crash test has been recently introduced by the Insurance Institute for Highway Safety in its frontal rating scheme. Another small overlap frontal crash test is under development by the National Highway Traffic Safety Administration (NHTSA). Whereas the IIHS test is conducted against a fixed rigid barrier, the NHTSA test is conducted with a moving deformable barrier that overlaps 35% of the vehicle being tested and the angle between the longitudinal axis of the barrier and the longitudinal axis of the test vehicle is 15 degrees. The field relevance of the IIHS test has been the subject of a paper by Prasad et al. (2014). The current study is aimed at examining the field relevance of the NHTSA test. The field relevance is indicated by the frequency of occurrence of real world crashes that are simulated by the test conditions, the proportion of serious-to-fatal real world injuries explained by the test condition, and rates of serious injury to the head, chest and other body regions in the real world crashes resembling the test condition. The database examined for real world crashes is NASS. Results of the study indicate that 1.4% of all frontal 11-to-1 o'clock crashes are simulated by the test conditions that account for 2.4% to 4.5% of all frontal serious-to-fatal (MAIS3+F) injuries. Injury rates of the head and the chest are substantially lower in far-side than in near-side frontal impacts. Crash test ATD rotational responses of the head in the tests overpredict the real world risk of serious-to-fatal brain injuries.

Brain shape convergence in the adaptive radiation of New World monkeys

PubMed Central

Aristide, Leandro; dos Reis, Sergio Furtado; Machado, Alessandra C.; Lima, Inaya; Lopes, Ricardo T.; Perez, S. Ivan

2016-01-01

Primates constitute one of the most diverse mammalian clades, and a notable feature of their diversification is the evolution of brain morphology. However, the evolutionary processes and ecological factors behind these changes are largely unknown. In this work, we investigate brain shape diversification of New World monkeys during their adaptive radiation in relation to different ecological dimensions. Our results reveal that brain diversification in this clade can be explained by invoking a model of adaptive peak shifts to unique and shared optima, defined by a multidimensional ecological niche hypothesis. Particularly, we show that the evolution of convergent brain phenotypes may be related to ecological factors associated with group size (e.g., social complexity). Together, our results highlight the complexity of brain evolution and the ecological significance of brain shape changes during the evolutionary diversification of a primate clade. PMID:26858427

Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI.

PubMed

Tyan, Yeu-Sheng; Liao, Jan-Ray; Shen, Chao-Yu; Lin, Yu-Chieh; Weng, Jun-Cheng

2017-01-01

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

Altered Brain Network Segregation in Fragile X Syndrome Revealed by Structural Connectomics.

PubMed

Bruno, Jennifer Lynn; Hosseini, S M Hadi; Saggar, Manish; Quintin, Eve-Marie; Raman, Mira Michelle; Reiss, Allan L

2017-03-01

Fragile X syndrome (FXS), the most common inherited cause of intellectual disability and autism spectrum disorder, is associated with significant behavioral, social, and neurocognitive deficits. Understanding structural brain network topology in FXS provides an important link between neurobiological and behavioral/cognitive symptoms of this disorder. We investigated the connectome via whole-brain structural networks created from group-level morphological correlations. Participants included 100 individuals: 50 with FXS and 50 with typical development, age 11-23 years. Results indicated alterations in topological properties of structural brain networks in individuals with FXS. Significantly reduced small-world index indicates a shift in the balance between network segregation and integration and significantly reduced clustering coefficient suggests that reduced local segregation shifted this balance. Caudate and amygdala were less interactive in the FXS network further highlighting the importance of subcortical region alterations in the neurobiological signature of FXS. Modularity analysis indicates that FXS and typically developing groups' networks decompose into different sets of interconnected sub networks, potentially indicative of aberrant local interconnectivity in individuals with FXS. These findings advance our understanding of the effects of fragile X mental retardation protein on large-scale brain networks and could be used to develop a connectome-level biological signature for FXS. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

PubMed

Jiang, Guihua; Wen, Xue; Qiu, Yingwei; Zhang, Ruibin; Wang, Junjing; Li, Meng; Ma, Xiaofen; Tian, Junzhang; Huang, Ruiwang

2013-01-01

Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

[Study on Abnormal Topological Properties of Structural Brain Networks of Patients with Depression Comorbid with Anxiety].

PubMed

Wu, Xiuyong; Wu, Xiaoming; Peng, Hongjun; Ning, Yuping; Wu, Kai

2016-06-01

This paper is aimed to analyze the topological properties of structural brain networks in depressive patients with and without anxiety and to explore the neuropath logical mechanisms of depression comorbid with anxiety.Diffusion tensor imaging and deterministic tractography were applied to map the white matter structural networks.We collected 20 depressive patients with anxiety(DPA),18 depressive patients without anxiety(DP),and 28 normal controls(NC)as comparative groups.The global and nodal properties of the structural brain networks in the three groups were analyzed with graph theoretical methods.The result showed that1 the structural brain networks in three groups showed small-world properties and highly connected global hubs predominately from association cortices;2DP group showed lower local efficiency and global efficiency compared to NC group,whereas DPA group showed higher local efficiency and global efficiency compared to NC group;3significant differences of network properties(clustering coefficient,characteristic path lengths,local efficiency,global efficiency)were found between DPA and DP groups;4DP group showed significant changes of nodal efficiency in the brain areas primarily in the temporal lobe and bilateral frontal gyrus,compared to DPA and NC groups.The analysis indicated that the DP and DPA groups showed nodal properties of the structural brain networks,compared to NC group.Moreover,the two diseased groups indicated an opposite trend in the network properties.The results of this study may provide a new imaging index for clinical diagnosis for depression comorbid with anxiety.

Communication efficiency and congestion of signal traffic in large-scale brain networks.

PubMed

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks

PubMed Central

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R.

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a “rich club” of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication. PMID:24415931

Extinction from a Rationalist Perspective

PubMed Central

Gallistel, C. R.

2012-01-01

The merging of the computational theory of mind and evolutionary thinking leads to a kind of rationalism, in which enduring truths about the world have become implicit in the computations that enable the brain to cope with the experienced world. The dead reckoning computation, for example, is implemented within the brains of animals as one of the mechanisms that enables them to learn where they are (Gallistel, 1990, 1995). It integrates a velocity signal with respect to a time signal. Thus, the manner in which position and velocity relate to one another in the world is reflected in the manner in which signals representing those variables are processed in the brain. I use principles of information theory and Bayesian inference to derive from other simple principles explanations for: 1) the failure of partial reinforcement to increase reinforcements to acquisition; 2) the partial reinforcement extinction effect; 3) spontaneous recovery; 4) renewal; 5) reinstatement; 6) resurgence (aka facilitated reacquisition). Like the principle underlying dead-reckoning, these principles are grounded in analytic considerations. They are the kind of enduring truths about the world that are likely to have shaped the brain's computations. PMID:22391153

Aberrant topological organization of the functional brain network associated with prior overt hepatic encephalopathy in cirrhotic patients.

PubMed

Chen, Hua-Jun; Chen, Qiu-Feng; Yang, Zhe-Ting; Shi, Hai-Bin

2018-05-30

A higher risk of cognitive impairments has been found after an overt hepatic encephalopathy (OHE) episode in cirrhotic patients. We investigated the effect of prior OHE episodes on the topological organization of the functional brain network and its association with the relevant cognitive impairments. Resting-state functional MRI data were acquired from 41 cirrhotic patients (19 with prior OHE (Prior-OHE) and 22 without (Non-Prior-OHE)) and 21 healthy controls (HC). A Psychometric Hepatic Encephalopathy Score (PHES) assessed cognition. The whole-brain functional network was constructed by thresholding functional correlation matrices of 90 brain regions (derived from the Automated Anatomic Labeling atlas). The topological properties of the brain network, including small-worldness, network efficiency, and nodal efficiency, were examined using graph theory-based analysis. Globally, the Prior-OHE group had a significantly decreased clustering coefficient and local efficiency, compared with the controls. Locally, the nodal efficiency in the bilateral medial superior frontal gyrus and the right postcentral gyrus decreased in the Prior-OHE group, while the nodal efficiency in the bilateral anterior cingulate/paracingulate gyri and right superior parietal gyrus increased in the Prior-OHE group. The alterations of global and regional network parameters progressed from Non-Prior-OHE to Prior-OHE and the clustering coefficient and local efficiency values were significantly correlated with PHES results. In conclusion, cirrhosis leads to the reduction of brain functional network efficiency, which could be aggravated by a prior OHE episode. Aberrant topological organization of the functional brain network may contribute to a higher risk of cognitive impairments in Prior-OHE patients.

Brain Structural Networks in Mouse Exposed to Chronic Maternal Undernutrition.

PubMed

Barbeito-Andrés, Jimena; Gleiser, Pablo M; Bernal, Valeria; Hallgrímsson, Benedikt; Gonzalez, Paula N

2018-06-01

Brain structural connectivity is known to be altered in cases of intrauterine growth restriction and premature birth, although the specific effect of maternal nutritional restriction, a common burden in human populations, has not been assessed yet. Here we analyze the effects of maternal undernutrition during pregnancy and lactation by establishing three experimental groups of female mice divided according to their diet: control (Co), moderate calorie-protein restriction (MCP) and severe protein restriction (SP). Nutritionally restricted dams gained relatively less weight during pregnancy and the body weight of the offspring was also affected by maternal undernutrition, showing global growth restriction. We performed magnetic resonance imaging (MRI) of the offspring's brains after weaning and analyzed their connectivity patterns using complex graph theory. In general, changes observed in the MCP group were more subtle than in SP. Results indicated that brain structures were not homogeneously affected by early nutritional stress. In particular, the growth of central brain regions, such as the temporo-parietal cortex, and long integrative myelinated tracts were relatively preserved, while the frequency of short tracts was relatively reduced. We also found a differential effect on network parameters: network degree, clustering, characteristic path length and small-worldness remained mainly unchanged, while the rich-club index was lower in nutritionally restricted animals. Rich-club decrease reflects an impairment in the structure by which brain regions with large number of connections tend to be more densely linked among themselves. Overall, the findings presented here support the hypothesis that chronic nutritional stress produces long-term changes in brain structural connectivity. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Connectome analysis for pre-operative brain mapping in neurosurgery

PubMed Central

Hart, Michael G.; Price, Stephen J.; Suckling, John

2016-01-01

Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756

Dynamic Reorganization of Functional Connectivity Reveals Abnormal Temporal Efficiency in Schizophrenia.

PubMed

Sun, Yu; Collinson, Simon L; Suckling, John; Sim, Kang

2018-06-07

Emerging evidence suggests that schizophrenia is associated with brain dysconnectivity. Nonetheless, the implicit assumption of stationary functional connectivity (FC) adopted in most previous resting-state functional magnetic resonance imaging (fMRI) studies raises an open question of schizophrenia-related aberrations in dynamic properties of resting-state FC. This study introduces an empirical method to examine the dynamic functional dysconnectivity in patients with schizophrenia. Temporal brain networks were estimated from resting-state fMRI of 2 independent datasets (patients/controls = 18/19 and 53/57 for self-recorded dataset and a publicly available replication dataset, respectively) by the correlation of sliding time-windowed time courses among regions of a predefined atlas. Through the newly introduced temporal efficiency approach and temporal random network models, we examined, for the first time, the 3D spatiotemporal architecture of the temporal brain network. We found that although prominent temporal small-world properties were revealed in both groups, temporal brain networks of patients with schizophrenia in both datasets showed a significantly higher temporal global efficiency, which cannot be simply attributable to head motion and sampling error. Specifically, we found localized changes of temporal nodal properties in the left frontal, right medial parietal, and subcortical areas that were associated with clinical features of schizophrenia. Our findings demonstrate that altered dynamic FC may underlie abnormal brain function and clinical symptoms observed in schizophrenia. Moreover, we provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network and highlight the potential of aberrant brain dynamic FC in unraveling the pathophysiologic mechanisms of the disease.

Disrupted topological organization of structural networks revealed by probabilistic diffusion tractography in Tourette syndrome children.

PubMed

Wen, Hongwei; Liu, Yue; Rekik, Islem; Wang, Shengpei; Zhang, Jishui; Zhang, Yue; Peng, Yun; He, Huiguang

2017-08-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. Although previous TS studies revealed structural abnormalities in distinct corticobasal ganglia circuits, the topological alterations of the whole-brain white matter (WM) structural networks remain poorly understood. Here, we used diffusion MRI probabilistic tractography and graph theoretical analysis to investigate the topological organization of WM networks in 44 drug-naive TS children and 41 age- and gender-matched healthy children. The WM networks were constructed by estimating inter-regional connectivity probability and the topological properties were characterized using graph theory. We found that both TS and control groups showed an efficient small-world organization in WM networks. However, compared to controls, TS children exhibited decreased global and local efficiency, increased shortest path length and small worldness, indicating a disrupted balance between local specialization and global integration in structural networks. Although both TS and control groups showed highly similar hub distributions, TS children exhibited significant decreased nodal efficiency, mainly distributed in the default mode, language, visual, and sensorimotor systems. Furthermore, two separate networks showing significantly decreased connectivity in TS group were identified using network-based statistical (NBS) analysis, primarily composed of the parieto-occipital cortex, precuneus, and paracentral lobule. Importantly, we combined support vector machine and multiple kernel learning frameworks to fuse multiple levels of network topological features for classification of individuals, achieving high accuracy of 86.47%. Together, our study revealed the disrupted topological organization of structural networks related to pathophysiology of TS, and the discriminative topological features for classification are potential quantitative neuroimaging biomarkers for clinical TS diagnosis. Hum Brain Mapp 38:3988-4008, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A large, single-center, real-world study of clinicopathological characteristics and treatment in advanced ALK-positive non-small-cell lung cancer.

PubMed

Chen, Gang; Chen, Xi; Zhang, Yaxiong; Yan, Fang; Fang, Wenfeng; Yang, Yunpeng; Hong, Shaodong; Miao, Siyu; Wu, Manli; Huang, Xiaodan; Luo, Youli; Zhou, Cong; Gong, Run; Huang, Yan; Zhou, Ningning; Zhao, Hongyun; Zhang, Li

2017-05-01

Crizotinib has achieved astonishing success in advanced non-small-cell lung cancer (NSCLC) patients harboring anaplastic lymphoma kinase (ALK) rearrangement. However, no real-world studies described the clinicopathological characteristics and treatment of such patients in China. Patients were consecutively collected from Sun Yat-sen University Cancer Center. Chi-square test was applied to explore the relationship between ALK fusion status and metastasis sites. Kaplan-Meier methods and multivariable analyses were used to estimate progression-free survival (PFS). A total of 291 advanced NSCLC patients (ALK (+), N = 97; both ALK & epidermal growth factor receptor (EGFR) (-), N = 194) were enrolled. The occurrence of brain metastasis in ALK-positive patients was significantly higher than double-negative ones both at baseline (26.5% vs. 16.5%, P = 0.038) and during treatment (25.8% vs. 11.9%, P = 0.003), but opposite for pleural effusion (6.2% vs. 26.9%, P < 0.001 at baseline; 3.1% vs. 10.3%, P = 0.031 during treatment). ALK-positive patients of 53.6% used crizotinib, whereas others only received chemotherapy (37.1%) or supportive care (9.3%). Usage of crizotinib prolonged PFS compared with chemotherapy in ALK-positive patients (median PFS 17.6 m vs. 4.8 m, P < 0.001). ALK-positive NSCLC had more brain metastasis and less pleural effusion than double-negative ones. Crizotinib showed better PFS than chemotherapy in advanced ALK-positive NSCLC at any line. However, half advanced ALK-positive patients never received crizotinib, which was grim and need improving. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Decreased functional connectivity in schizophrenia: The relationship between social functioning, social cognition and graph theoretical network measures.

PubMed

Erdeniz, Burak; Serin, Emin; İbadi, Yelda; Taş, Cumhur

2017-12-30

Schizophrenia is a complex disorder in which abnormalities in brain connectivity and social functioning play a central role. The aim of this study is to explore small-world network properties, and understand their relationship with social functioning and social cognition in the context of schizophrenia, by testing functional connectivity differences in network properties and its relation to clinical behavioral measures. Resting-state fMRI time series data were acquired from 23 patients diagnosed with schizophrenia and 23 healthy volunteers. The results revealed that patients with schizophrenia show significantly decreased connectivity between a range of brain regions, particularly involving connections among the right orbitofrontal cortex, bilateral putamen and left amygdala. Furthermore, topological properties of functional brain networks in patients with schizophrenia were characterized by reduced path length compared to healthy controls; however, no significant difference was found for clustering coefficient, local efficiency or global efficiency. Additionally, we found that nodal efficiency of the amygdala and the putamen were significantly correlated with the independence-performance subscale of social functioning scale (SFC), and Reading the Mind in the Eyes test; however, the correlations do not survive correction for multiple comparison. The current results help to clarify the relationship between social functioning deficits and topological brain measures in schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Brain structural network topological alterations of the left prefrontal and limbic cortex in psychogenic erectile dysfunction.

PubMed

Chen, Jianhuai; Chen, Yun; Gao, Qingqiang; Chen, Guotao; Dai, Yutian; Yao, Zhijian; Lu, Qing

2018-05-01

Despite increasing understanding of the cerebral functional changes and structural abnormalities in erectile dysfunction, alterations in the topological organization of brain networks underlying psychogenic erectile dysfunction remain unclear. Here, based on the diffusion tensor image data of 25 patients and 26 healthy controls, we investigated the topological organization of brain structural networks and its correlations with the clinical variables using the graph theoretical analysis. Patients displayed a preserved overall small-world organization and exhibited a less connectivity strength in the left inferior frontal gyrus, amygdale and the right inferior temporal gyrus. Moreover, an abnormal hub pattern was observed in patients, which might disturb the information interactions of the remaining brain network. Additionally, the clustering coefficient of the left hippocampus was positively correlated with the duration of patients and the normalized betweenness centrality of the right anterior cingulate gyrus and the left calcarine fissure were negatively correlated with the sum scores of the 17-item Hamilton Depression Rating Scale. These findings suggested that the damaged white matter and the abnormal hub distribution of the left prefrontal and limbic cortex might contribute to the pathogenesis of psychogenic erectile dysfunction and provided new insights into the understanding of the pathophysiological mechanisms of psychogenic erectile dysfunction.

Discriminating the Difference between Remote and Close Association with Relation to White-Matter Structural Connectivity

PubMed Central

Wu, Chinglin; Zhong, Suyu; Chen, Hsuehchih

2016-01-01

Remote association is a core ability that influences creative output. In contrast to close association, remote association is commonly agreed to be connected with more original and unique concepts. However, although existing studies have discovered that creativity is closely related to the white-matter structure of the brain, there are no studies that examine the relevance between the connectivity efficiencies and creativity of the brain regions from the perspective of networks. Consequently, this study constructed a brain white matter network structure that consisted of cerebral tissues and nerve fibers and used graph theory to analyze the connection efficiencies among the network nodes, further illuminating the differences between remote and close association in relation to the connectivity of the brain network. Researchers analyzed correlations between the scores of 35 healthy adults with regard to remote and close associations and the connectivity efficiencies of the white-matter network of the brain. Controlling for gender, age, and verbal intelligence, the remote association positively correlated with the global efficiency and negatively correlated with the levels of small-world. A close association negatively correlated with the global efficiency. Notably, the node efficiency in the middle temporal gyrus (MTG) positively correlated with remote association and negatively correlated with close association. To summarize, remote and close associations work differently as patterns in the brain network. Remote association requires efficient and convenient mutual connections between different brain regions, while close association emphasizes the limited connections that exist in a local region. These results are consistent with previous results, which indicate that creativity is based on the efficient integration and connection between different regions of the brain and that temporal lobes are the key regions for discriminating remote and close associations. PMID:27760177

Topological Isomorphisms of Human Brain and Financial Market Networks

PubMed Central

Vértes, Petra E.; Nicol, Ruth M.; Chapman, Sandra C.; Watkins, Nicholas W.; Robertson, Duncan A.; Bullmore, Edward T.

2011-01-01

Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets – the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular – more highly optimized for information processing – than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets. PMID:22007161

Brain Migration Revisited

ERIC Educational Resources Information Center

Vinokur, Annie

2006-01-01

The "brain drain/brain gain" debate has been going on for the past 40 years, with irresolvable theoretical disputes and unenforceable policy recommendations that economists commonly ascribe to the lack of reliable empirical data. The recent report of the World Bank, "International migration, remittances and the brain drain", documents the…

The Neurodynamics of Affect in the Laboratory Predicts Persistence of Real-World Emotional Responses.

PubMed

Heller, Aaron S; Fox, Andrew S; Wing, Erik K; McQuisition, Kaitlyn M; Vack, Nathan J; Davidson, Richard J

2015-07-22

Failure to sustain positive affect over time is a hallmark of depression and other psychopathologies, but the mechanisms supporting the ability to sustain positive emotional responses are poorly understood. Here, we investigated the neural correlates associated with the persistence of positive affect in the real world by conducting two experiments in humans: an fMRI task of reward responses and an experience-sampling task measuring emotional responses to a reward obtained in the field. The magnitude of DLPFC engagement to rewards administered in the laboratory predicted reactivity of real-world positive emotion following a reward administered in the field. Sustained ventral striatum engagement in the laboratory positively predicted the duration of real-world positive emotional responses. These results suggest that common pathways are associated with the unfolding of neural processes over seconds and with the dynamics of emotions experienced over minutes. Examining such dynamics may facilitate a better understanding of the brain-behavior associations underlying emotion. Significance statement: How real-world emotion, experienced over seconds, minutes, and hours, is instantiated in the brain over the course of milliseconds and seconds is unknown. We combined a novel, real-world experience-sampling task with fMRI to examine how individual differences in real-world emotion, experienced over minutes and hours, is subserved by affective neurodynamics of brain activity over the course of seconds. When winning money in the real world, individuals sustaining positive emotion the longest were those with the most prolonged ventral striatal activity. These results suggest that common pathways are associated with the unfolding of neural processes over seconds and with the dynamics of emotions experienced over minutes. Examining such dynamics may facilitate a better understanding of the brain-behavior associations underlying emotion. Copyright © 2015 the authors 0270-6474/15/3510503-07$15.00/0.

Tracking the Spatiotemporal Neural Dynamics of Real-world Object Size and Animacy in the Human Brain.

PubMed

Khaligh-Razavi, Seyed-Mahdi; Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2018-06-07

Animacy and real-world size are properties that describe any object and thus bring basic order into our perception of the visual world. Here, we investigated how the human brain processes real-world size and animacy. For this, we applied representational similarity to fMRI and MEG data to yield a view of brain activity with high spatial and temporal resolutions, respectively. Analysis of fMRI data revealed that a distributed and partly overlapping set of cortical regions extending from occipital to ventral and medial temporal cortex represented animacy and real-world size. Within this set, parahippocampal cortex stood out as the region representing animacy and size stronger than most other regions. Further analysis of the detailed representational format revealed differences among regions involved in processing animacy. Analysis of MEG data revealed overlapping temporal dynamics of animacy and real-world size processing starting at around 150 msec and provided the first neuromagnetic signature of real-world object size processing. Finally, to investigate the neural dynamics of size and animacy processing simultaneously in space and time, we combined MEG and fMRI with a novel extension of MEG-fMRI fusion by representational similarity. This analysis revealed partly overlapping and distributed spatiotemporal dynamics, with parahippocampal cortex singled out as a region that represented size and animacy persistently when other regions did not. Furthermore, the analysis highlighted the role of early visual cortex in representing real-world size. A control analysis revealed that the neural dynamics of processing animacy and size were distinct from the neural dynamics of processing low-level visual features. Together, our results provide a detailed spatiotemporal view of animacy and size processing in the human brain.

Trust: Need for an Improved Communication between the Public World and the Pharmaceutical Companies

PubMed Central

Heinemann, Lutz

2009-01-01

In the industrialized world, the negative image that many people (including politicians) have of pharmaceutical companies not only makes the life for those working in this field more difficult, in a sense it is a road block. Without an improvement in communication between the public world and the pharmaceutical industry, one can foresee this industry steadily becoming a more difficult environment to work in. There is a clear need for knowing more about all the work done inside these companies before a new drug is approved (it is not all about marketing…). That society has no understanding of the ever-increasing costs of new drugs is also related to this lack of understanding of how tricky and cumbersome the process is to take a new idea for treating a certain disease to production of a marketed drug. With a relatively small investment of money, but with an investment of much good will, brain power, and trust, it should be possible to bring all relevant parties together and make a change. PMID:20046667

RO4929097 and Whole-Brain Radiation Therapy or Stereotactic Radiosurgery in Treating Patients With Brain Metastases From Breast Cancer

ClinicalTrials.gov

2015-01-22

Estrogen Receptor-negative Breast Cancer; Extensive Stage Small Cell Lung Cancer; HER2-negative Breast Cancer; HER2-positive Breast Cancer; Male Breast Cancer; Recurrent Breast Cancer; Recurrent Melanoma; Recurrent Non-small Cell Lung Cancer; Recurrent Small Cell Lung Cancer; Stage IV Breast Cancer; Stage IV Melanoma; Stage IV Non-small Cell Lung Cancer; Tumors Metastatic to Brain; Unspecified Adult Solid Tumor, Protocol Specific

Issues of cultural diversity in acquired brain injury (ABI) rehabilitation.

PubMed

Lequerica, Anthony; Krch, Denise

2014-01-01

With the general population in the United States becoming increasingly diverse, it is important for rehabilitation professionals to develop the capacity to provide culturally sensitive treatment. This is especially relevant when working with minority populations who have a higher risk for brain injury and poorer rehabilitation outcomes. This article presents a number of clinical vignettes to illustrate how cultural factors can influence behavior in patients recovering from brain injury, as well as rehabilitation staff. The main objectives are to raise awareness among clinicians and stimulate research ideas by highlighting some real world examples of situations where a specialized, patient-centered approach needs to consider factors of cultural diversity. Because one's own world view impacts the way we see the world and interpret behavior, it is important to understand one's own ethnocentrism when dealing with a diverse population of patients with brain injury where behavioral sequelae are often expected. Being able to see behavior after brain injury with an open mind and taking into account cultural and contextual factors is an important step in developing culturally competent rehabilitation practices.

Neurology in a globalizing world: World Congress of Neurology, Vienna, 2013.

PubMed

Hachinski, Vladimir

2013-06-11

The World Congress of Neurology (figure 1) theme "Neurology in a Globalizing World" acknowledges that science and increasingly medicine and neurology are becoming globalized. The best way to manage change is to shape it. It is becoming increasingly clear that brain diseases, particularly stroke and dementia, are projected to rise at a rate that could overwhelm our clinics and hospitals. Hence a new emphasis on prevention and the need to work across disciplines beyond our traditional roles. Neurologists are the guardians of the brain and need to take the lead role in advancing new approaches in stemming the tide of neurologic diseases.

Extinction from a rationalist perspective.

PubMed

Gallistel, C R

2012-05-01

The merging of the computational theory of mind and evolutionary thinking leads to a kind of rationalism, in which enduring truths about the world have become implicit in the computations that enable the brain to cope with the experienced world. The dead reckoning computation, for example, is implemented within the brains of animals as one of the mechanisms that enables them to learn where they are (Gallistel, 1990, 1995). It integrates a velocity signal with respect to a time signal. Thus, the manner in which position and velocity relate to one another in the world is reflected in the manner in which signals representing those variables are processed in the brain. I use principles of information theory and Bayesian inference to derive from other simple principles explanations for: (1) the failure of partial reinforcement to increase reinforcements to acquisition; (2) the partial reinforcement extinction effect; (3) spontaneous recovery; (4) renewal; (5) reinstatement; (6) resurgence (aka facilitated reacquisition). Like the principle underlying dead-reckoning, these principles are grounded in analytic considerations. They are the kind of enduring truths about the world that are likely to have shaped the brain's computations. Copyright © 2012 Elsevier B.V. All rights reserved.

The remarkable visual capacities of nocturnal insects: vision at the limits with small eyes and tiny brains

PubMed Central

2017-01-01

Nocturnal insects have evolved remarkable visual capacities, despite small eyes and tiny brains. They can see colour, control flight and land, react to faint movements in their environment, navigate using dim celestial cues and find their way home after a long and tortuous foraging trip using learned visual landmarks. These impressive visual abilities occur at light levels when only a trickle of photons are being absorbed by each photoreceptor, begging the question of how the visual system nonetheless generates the reliable signals needed to steer behaviour. In this review, I attempt to provide an answer to this question. Part of the answer lies in their compound eyes, which maximize light capture. Part lies in the slow responses and high gains of their photoreceptors, which improve the reliability of visual signals. And a very large part lies in the spatial and temporal summation of these signals in the optic lobe, a strategy that substantially enhances contrast sensitivity in dim light and allows nocturnal insects to see a brighter world, albeit a slower and coarser one. What is abundantly clear, however, is that during their evolution insects have overcome several serious potential visual limitations, endowing them with truly extraordinary night vision. This article is part of the themed issue ‘Vision in dim light’. PMID:28193808

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Growing trees in child brains: graph theoretical analysis of electroencephalography-derived minimum spanning tree in 5- and 7-year-old children reflects brain maturation.

PubMed

Boersma, Maria; Smit, Dirk J A; Boomsma, Dorret I; De Geus, Eco J C; Delemarre-van de Waal, Henriette A; Stam, Cornelis J

2013-01-01

The child brain is a small-world network, which is hypothesized to change toward more ordered configurations with development. In graph theoretical studies, comparing network topologies under different conditions remains a critical point. Constructing a minimum spanning tree (MST) might present a solution, since it does not require setting a threshold and uses a fixed number of nodes and edges. In this study, the MST method is introduced to examine developmental changes in functional brain network topology in young children. Resting-state electroencephalography was recorded from 227 children twice at 5 and 7 years of age. Synchronization likelihood (SL) weighted matrices were calculated in three different frequency bands from which MSTs were constructed, which represent constructs of the most important routes for information flow in a network. From these trees, several parameters were calculated to characterize developmental change in network organization. The MST diameter and eccentricity significantly increased, while the leaf number and hierarchy significantly decreased in the alpha band with development. Boys showed significant higher leaf number, betweenness, degree and hierarchy and significant lower SL, diameter, and eccentricity than girls in the theta band. The developmental changes indicate a shift toward more decentralized line-like trees, which supports the previously hypothesized increase toward regularity of brain networks with development. Additionally, girls showed more line-like decentralized configurations, which is consistent with the view that girls are ahead of boys in brain development. MST provides an elegant method sensitive to capture subtle developmental changes in network organization without the bias of network comparison.

Changes in functional brain networks following sports-related concussion in adolescents.

PubMed

Virji-Babul, Naznin; Hilderman, Courtney G E; Makan, Nadia; Liu, Aiping; Smith-Forrester, Jenna; Franks, Chris; Wang, Z J

2014-12-01

Sports-related concussion is a major public health issue; however, little is known about the underlying changes in functional brain networks in adolescents following injury. Our aim was to use the tools from graph theory to evaluate the changes in brain network properties following concussion in adolescent athletes. We recorded resting state electroencephalography (EEG) in 33 healthy adolescent athletes and 9 adolescent athletes with a clinical diagnosis of subacute concussion. Graph theory analysis was applied to these data to evaluate changes in brain networks. Global and local metrics of the structural properties of the graph were calculated for each group and correlated with Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) scores. Brain networks of both groups showed small-world topology with no statistically significant differences in the global metrics; however, significant differences were found in the local metrics. Specifically, in the concussed group, we noted: 1) increased values of betweenness and degree in frontal electrode sites corresponding to the (R) dorsolateral prefrontal cortex and the (R) inferior frontal gyrus and 2) decreased values of degree in the region corresponding to the (R) frontopolar prefrontal cortex. In addition, there was significant negative correlation between degree and hub value, with total symptom score at the electrode site corresponding to the (R) prefrontal cortex. This preliminary report in adolescent athletes shows for the first time that resting-state EEG combined with graph theoretical analysis may provide an objective method of evaluating changes in brain networks following concussion. This approach may be useful in identifying individuals at risk for future injury.

Characterization of the resting-state brain network topology in the 6-hydroxydopamine rat model of Parkinson’s disease

PubMed Central

Simmons, Camilla; Mesquita, Michel B.; Wood, Tobias C.; Williams, Steve C. R.; Vernon, Anthony C.; Cash, Diana

2017-01-01

Resting-state functional MRI (rsfMRI) is an imaging technology that has recently gained attention for its ability to detect disruptions in functional brain networks in humans, including in patients with Parkinson’s disease (PD), revealing early and widespread brain network abnormalities. This methodology is now readily applicable to experimental animals offering new possibilities for cross-species translational imaging. In this context, we herein describe the application of rsfMRI to the unilaterally-lesioned 6-hydroxydopamine (6-OHDA) rat, a robust experimental model of the dopamine depletion implicated in PD. Using graph theory to analyse the rsfMRI data, we were able to provide meaningful and translatable measures of integrity, influence and segregation of the underlying functional brain architecture. Specifically, we confirm that rats share a similar functional brain network topology as observed in humans, characterised by small-worldness and modularity. Interestingly, we observed significantly reduced functional connectivity in the 6-OHDA rats, primarily in the ipsilateral (lesioned) hemisphere as evidenced by significantly lower node degree, local efficiency and clustering coefficient in the motor, orbital and sensorimotor cortices. In contrast, we found significantly, and bilaterally, increased thalamic functional connectivity in the lesioned rats. The unilateral deficits in the cortex are consistent with the unilateral nature of this model and further support the validity of the rsfMRI technique in rodents. We thereby provide a methodological framework for the investigation of brain networks in other rodent experimental models of PD, as well as of animal models in general, for cross-comparison with human data. PMID:28249008

The Brain Adapts to Dishonesty

PubMed Central

Garrett, Neil; Lazzaro, Stephanie C.; Ariely, Dan; Sharot, Tali

2016-01-01

Dishonesty is an integral part of our social world, influencing domains ranging from finance and politics to personal relationships. Anecdotally, digressions from a moral code are often described as a series of small breaches that grow over time. Here, we provide empirical evidence for a gradual escalation of self-serving dishonesty and reveal a neural mechanism supporting it. Behaviorally, we show that the extent to which participants engage in self-serving dishonesty increases with repetition. Using fMRI we show that signal reduction in the amygdala is sensitive to the history of dishonest behavior, consistent with adaptation. Critically, the extent of amygdala BOLD reduction to dishonesty on a present decision relative to the last, predicts the magnitude of escalation of self-serving dishonesty on the next decision. The findings uncover a biological mechanism that supports a “slippery slope”: what begins as small acts of dishonesty can escalate into larger instances. PMID:27775721

Toward Developmental Connectomics of the Human Brain

PubMed Central

Cao, Miao; Huang, Hao; Peng, Yun; Dong, Qi; He, Yong

2016-01-01

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders. PMID:27064378

Frequency specific brain networks in Parkinson's disease and comorbid depression.

PubMed

Qian, Long; Zhang, Yi; Zheng, Li; Fu, Xuemei; Liu, Weiguo; Shang, Yuqing; Zhang, Yaoyu; Xu, Yuanyuan; Liu, Yijun; Zhu, Huaiqiu; Gao, Jia-Hong

2017-02-01

The topological organization underlying the human brain was extensively investigated using resting-state functional magnetic resonance imaging, focusing on a low frequency of signal oscillation from 0.01 to 0.1 Hz. However, the frequency specificities with regard to the topological properties of the brain networks have not been fully revealed. In this study, a novel complementary ensemble empirical mode decomposition (CEEMD) method was used to separate the fMRI time series into five characteristic oscillations with distinct frequencies. Then, the small world properties of brain networks were analyzed for each of these five oscillations in patients (n = 67) with depressed Parkinson's disease (DPD, n = 20) , non-depressed Parkinson's disease (NDPD, n = 47) and healthy controls (HC, n = 46). Compared with HC, the results showed decreased network efficiency in characteristic oscillations from 0.05 to 0.12 Hz and from 0.02 to 0.05 Hz for the DPD and NDPD patients, respectively. Furthermore, compared with HC, the most significant inter-group difference across five brain oscillations was found in the basal ganglia (0.01 to 0.05 Hz) and paralimbic-limbic network (0.02 to 0.22 Hz) for the DPD patients, and in the visual cortex (0.02 to 0.05 Hz) for the NDPD patients. Compared with NDPD, the DPD patients showed reduced efficiency of nodes in the basal ganglia network (0.01 to 0.05 Hz). Our results demonstrated that DPD is characterized by a disrupted topological organization in large-scale brain functional networks. Moreover, the CEEMD analysis suggested a prominent dissociation in the topological organization of brain networks between DPD and NDPD in both space and frequency domains. Our findings indicated that these characteristic oscillatory activities in different functional circuits may contribute to distinct motor and non-motor components of clinical impairments in Parkinson's disease.

The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

NASA Astrophysics Data System (ADS)

Yi, Guo-Sheng; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Li, Nuo

2013-02-01

Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world" network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

Topological Alterations of the Intrinsic Brain Network in Patients with Functional Dyspepsia.

PubMed

Nan, Jiaofen; Zhang, Li; Zhu, Fubao; Tian, Xiaorui; Zheng, Qian; Deneen, Karen M von; Liu, Jixin; Zhang, Ming

2016-01-31

Previous studies reported that integrated information in the brain ultimately determines the subjective experience of patients with chronic pain, but how the information is integrated in the brain connectome of functional dyspepsia (FD) patients remains largely unclear. The study aimed to quantify the topological changes of the brain network in FD patients. Small-world properties, network efficiency and nodal centrality were utilized to measure the changes in topological architecture in 25 FD patients and 25 healthy controls based on functional magnetic resonance imaging. Pearson's correlation assessed the relationship of each topological property with clinical symptoms. FD patients showed an increase of clustering coefficients and local efficiency relative to controls from the perspective of a whole network as well as elevated nodal centrality in the right orbital part of the inferior frontal gyrus, left anterior cingulate gyrus and left hippocampus, and decreased nodal centrality in the right posterior cingulate gyrus, left cuneus, right putamen, left middle occipital gyrus and right inferior occipital gyrus. Moreover, the centrality in the anterior cingulate gyrus was significantly associated with symptom severity and duration in FD patients. Nevertheless, the inclusion of anxiety and depression scores as covariates erased the group differences in nodal centralities in the orbital part of the inferior frontal gyrus and hippocampus. The results suggest topological disruption of the functional brain networks in FD patients, presumably in response to disturbances of sensory information integrated with emotion, memory, pain modulation, and selective attention in patients.

Free Will, Physics, Biology, and the Brain

NASA Astrophysics Data System (ADS)

Koch, Christof

This introduction reviews the traditionally conceived question of free will from the point of view of a physicist turned neurobiologist. I discuss the quantum mechanic evidence that has brought us to the view that the world, including our brains, is not completely determined by physics and that even very simple nervous systems are subject to deterministic chaos. However, it is unclear how consciousness or any other extra-physical agent could take advantage of this situation to effect a change in the world, except possibly by realizing one quantum possibility over another. While the brain is a highly nonlinear and stochastic system, it remains unclear to what extent individual quantum effects can affect its output behavior. Finally, I discuss several cognitive neuroscience experiments suggesting that in many instances, our brain decides prior to our conscious mind, and that we often ignorant of our brain's decisions.

Stereotactic radiosurgery for small brain metastases and implications regarding management with systemic therapy alone.

PubMed

Trifiletti, Daniel M; Hill, Colin; Cohen-Inbar, Or; Xu, Zhiyuan; Sheehan, Jason P

2017-09-01

While stereotactic radiosurgery (SRS) has been shown effective in the management of brain metastases, small brain metastases (≤10 mm) can pose unique challenges. Our aim was to investigate the efficacy of SRS in the treatment of small brain metastases, as well as elucidate clinically relevant factors impacting local failure (LF). We utilized a large, single-institution cohort to perform a retrospective analysis of patients with brain metastases up to 1 cm in maximal dimension. Clinical and radiosurgical parameters were investigated for an association with LF and compared using a competing risk model to calculate cumulative incidence functions, with death and whole brain radiotherapy serving as competing risks. 1596 small brain metastases treated with SRS among 424 patients were included. Among these tumors, 33 developed LF during the follow-up period (2.4% at 12 months following SRS). Competing risk analysis demonstrated that LF was dependent on tumor size (0.7% if ≤2 mm and 3.0% if 2-10 mm at 12 months, p = 0.016). Other factors associated with increasing risk of LF were the decreasing margin dose, increasing maximal tumor diameter, volume, and radioresistant tumors (each p < 0.01). 22 tumors (0.78%) developed radiographic radiation necrosis following SRS, and this incidence did not differ by tumor size (≤2 mm and 2-10 mm, p = 0.200). This large analysis confirms that SRS remains an effective modality in treatment of small brain metastases. In light of the excellent local control and relatively low risk of toxicity, patients with small brain metastases who otherwise have a reasonable expected survival should be considered for radiosurgical management.

Differential Modulation of Excitatory and Inhibitory Neurons during Periodic Stimulation

PubMed Central

Mahmud, Mufti; Vassanelli, Stefano

2016-01-01

Non-invasive transcranial neuronal stimulation, in addition to deep brain stimulation, is seen as a promising therapeutic and diagnostic approach for an increasing number of neurological diseases such as epilepsy, cluster headaches, depression, specific type of blindness, and other central nervous system disfunctions. Improving its effectiveness and widening its range of use may strongly rely on development of proper stimulation protocols that are tailored to specific brain circuits and that are based on a deep knowledge of different neuron types response to stimulation. To this aim, we have performed a simulation study on the behavior of excitatory and inhibitory neurons subject to sinusoidal stimulation. Due to the intrinsic difference in membrane conductance properties of excitatory and inhibitory neurons, we show that their firing is differentially modulated by the wave parameters. We analyzed the behavior of the two neuronal types for a broad range of stimulus frequency and amplitude and demonstrated that, within a small-world network prototype, parameters tuning allow for a selective enhancement or suppression of the excitation/inhibition ratio. PMID:26941602

A network of networks model to study phase synchronization using structural connection matrix of human brain

NASA Astrophysics Data System (ADS)

Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

2018-04-01

The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

Preservation of mitochondrial functional integrity in mitochondria isolated from small cryopreserved mouse brain areas.

PubMed

Valenti, Daniela; de Bari, Lidia; De Filippis, Bianca; Ricceri, Laura; Vacca, Rosa Anna

2014-01-01

Studies of mitochondrial bioenergetics in brain pathophysiology are often precluded by the need to isolate mitochondria immediately after tissue dissection from a large number of brain biopsies for comparative studies. Here we present a procedure of cryopreservation of small brain areas from which mitochondrial enriched fractions (crude mitochondria) with high oxidative phosphorylation efficiency can be isolated. Small mouse brain areas were frozen and stored in a solution containing glycerol as cryoprotectant. Crude mitochondria were isolated by differential centrifugation from both cryopreserved and freshly explanted brain samples and were compared with respect to their ability to generate membrane potential and produce ATP. Intactness of outer and inner mitochondrial membranes was verified by polarographic ascorbate and cytochrome c tests and spectrophotometric assay of citrate synthase activity. Preservation of structural integrity and oxidative phosphorylation efficiency was successfully obtained in crude mitochondria isolated from different areas of cryopreserved mouse brain samples. Long-term cryopreservation of small brain areas from which intact and phosphorylating mitochondria can be isolated for the study of mitochondrial bioenergetics will significantly expand the study of mitochondrial defects in neurological pathologies, allowing large comparative studies and favoring interlaboratory and interdisciplinary analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Brain control and information transfer.

PubMed

Tehovnik, Edward J; Chen, Lewis L

2015-12-01

In this review, we examine the importance of having a body as essential for the brain to transfer information about the outside world to generate appropriate motor responses. We discuss the context-dependent conditioning of the motor control neural circuits and its dependence on the completion of feedback loops, which is in close agreement with the insights of Hebb and colleagues, who have stressed that for learning to occur the body must be intact and able to interact with the outside world. Finally, we apply information theory to data from published studies to evaluate the robustness of the neuronal signals obtained by bypassing the body (as used for brain-machine interfaces) versus via the body to move in the world. We show that recording from a group of neurons that bypasses the body exhibits a vastly degraded level of transfer of information as compared to that of an entire brain using the body to engage in the normal execution of behaviour. We conclude that body sensations provide more than just feedback for movements; they sustain the necessary transfer of information as animals explore their environment, thereby creating associations through learning. This work has implications for the development of brain-machine interfaces used to move external devices.

A Penalized Likelihood Framework For High-Dimensional Phylogenetic Comparative Methods And An Application To New-World Monkeys Brain Evolution.

PubMed

Julien, Clavel; Leandro, Aristide; Hélène, Morlon

2018-06-19

Working with high-dimensional phylogenetic comparative datasets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits p approaches the number of species n and because some computational complications occur when p exceeds n. Alternative phylogenetic comparative methods have recently been proposed to deal with the large p small n scenario but their use and performances are limited. Here we develop a penalized likelihood framework to deal with high-dimensional comparative datasets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU) and Pagel's lambda models. We show using simulations that our penalized likelihood approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when p approaches n, and allows for their accurate estimation when p equals or exceeds n. In addition, we show that penalized likelihood models can be efficiently compared using Generalized Information Criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic PCA in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3-D dataset of brain shape in the New World monkeys. We find a clear support for an Early-burst model suggesting an early diversification of brain morphology during the ecological radiation of the clade. Penalized likelihood offers an efficient way to deal with high-dimensional multivariate comparative data.

Hoyeraal-Hreidarsson syndrome: magnetic resonance imaging findings.

PubMed

Kuwashima, Shigeko

2009-10-01

Hoyeraal-Hreidarsson syndrome (HH) has been defined as a severe variant of dyskeratosis congenita (DKC). We report here a case of a 6-year-old girl with HH who presented with bone marrow hypoplasia, skin pigmentation, nail dystrophy, growth retardation, and bilateral retinal hemorrhage. Brain MRI revealed cerebellar hypoplasia, hypoplasia of the corpus callosum, a small pituitary gland, a small brain stem, and focal long T2 lesions in the thalamus and brain stem. A brain computed tomography scan revealed intracranial calcification as well. To the best of our knowledge, a small pituitary gland and focal long T2 lesions in the thalamus and brain stem have never been reported as a feature of HH.

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats.

PubMed

De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro

2017-01-01

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

A simpler primate brain: the visual system of the marmoset monkey

PubMed Central

Solomon, Samuel G.; Rosa, Marcello G. P.

2014-01-01

Humans are diurnal primates with high visual acuity at the center of gaze. Although primates share many similarities in the organization of their visual centers with other mammals, and even other species of vertebrates, their visual pathways also show unique features, particularly with respect to the organization of the cerebral cortex. Therefore, in order to understand some aspects of human visual function, we need to study non-human primate brains. Which species is the most appropriate model? Macaque monkeys, the most widely used non-human primates, are not an optimal choice in many practical respects. For example, much of the macaque cerebral cortex is buried within sulci, and is therefore inaccessible to many imaging techniques, and the postnatal development and lifespan of macaques are prohibitively long for many studies of brain maturation, plasticity, and aging. In these and several other respects the marmoset, a small New World monkey, represents a more appropriate choice. Here we review the visual pathways of the marmoset, highlighting recent work that brings these advantages into focus, and identify where additional work needs to be done to link marmoset brain organization to that of macaques and humans. We will argue that the marmoset monkey provides a good subject for studies of a complex visual system, which will likely allow an important bridge linking experiments in animal models to humans. PMID:25152716

Resting State Brain Network Disturbances Related to Hypomania and Depression in Medication-Free Bipolar Disorder

PubMed Central

Spielberg, Jeffrey M; Beall, Erik B; Hulvershorn, Leslie A; Altinay, Murat; Karne, Harish; Anand, Amit

2016-01-01

Research on resting functional brain networks in bipolar disorder (BP) has been unable to differentiate between disturbances related to mania or depression, which is necessary to understand the mechanisms leading to each state. Past research has also been unable to elucidate the impact of BP-related network disturbances on the organizational properties of the brain (eg, communication efficiency). Thus, the present work sought to isolate network disturbances related to BP, fractionate these into components associated with manic and depressive symptoms, and characterize the impact of disturbances on network function. Graph theory was used to analyze resting functional magnetic resonance imaging data from 60 medication-free patients meeting the criteria for BP and either a current hypomanic (n=30) or depressed (n=30) episode and 30 closely age/sex-matched healthy controls. Correction for multiple comparisons was carried out. Compared with controls, BP patients evidenced hyperconnectivity in a network involving right amygdala. Fractionation revealed that (hypo)manic symptoms were associated with hyperconnectivity in an overlapping network and disruptions in the brain's ‘small-world' network organization. Depressive symptoms predicted hyperconnectivity in a network involving orbitofrontal cortex along with a less resilient global network organization. Findings provide deeper insight into the differential pathophysiological processes associated with hypomania and depression, along with the particular impact these differential processes have on network function. PMID:27356764

Resting State Brain Network Disturbances Related to Hypomania and Depression in Medication-Free Bipolar Disorder.

PubMed

Spielberg, Jeffrey M; Beall, Erik B; Hulvershorn, Leslie A; Altinay, Murat; Karne, Harish; Anand, Amit

2016-12-01

Research on resting functional brain networks in bipolar disorder (BP) has been unable to differentiate between disturbances related to mania or depression, which is necessary to understand the mechanisms leading to each state. Past research has also been unable to elucidate the impact of BP-related network disturbances on the organizational properties of the brain (eg, communication efficiency). Thus, the present work sought to isolate network disturbances related to BP, fractionate these into components associated with manic and depressive symptoms, and characterize the impact of disturbances on network function. Graph theory was used to analyze resting functional magnetic resonance imaging data from 60 medication-free patients meeting the criteria for BP and either a current hypomanic (n=30) or depressed (n=30) episode and 30 closely age/sex-matched healthy controls. Correction for multiple comparisons was carried out. Compared with controls, BP patients evidenced hyperconnectivity in a network involving right amygdala. Fractionation revealed that (hypo)manic symptoms were associated with hyperconnectivity in an overlapping network and disruptions in the brain's 'small-world' network organization. Depressive symptoms predicted hyperconnectivity in a network involving orbitofrontal cortex along with a less resilient global network organization. Findings provide deeper insight into the differential pathophysiological processes associated with hypomania and depression, along with the particular impact these differential processes have on network function.

Early Development of Functional Network Segregation Revealed by Connectomic Analysis of the Preterm Human Brain.

PubMed

Cao, Miao; He, Yong; Dai, Zhengjia; Liao, Xuhong; Jeon, Tina; Ouyang, Minhui; Chalak, Lina; Bi, Yanchao; Rollins, Nancy; Dong, Qi; Huang, Hao

2017-03-01

Human brain functional networks are topologically organized with nontrivial connectivity characteristics such as small-worldness and densely linked hubs to support highly segregated and integrated information processing. However, how they emerge and change at very early developmental phases remains poorly understood. Here, we used resting-state functional MRI and voxel-based graph theory analysis to systematically investigate the topological organization of whole-brain networks in 40 infants aged around 31 to 42 postmenstrual weeks. The functional connectivity strength and heterogeneity increased significantly in primary motor, somatosensory, visual, and auditory regions, but much less in high-order default-mode and executive-control regions. The hub and rich-club structures in primary regions were already present at around 31 postmenstrual weeks and exhibited remarkable expansions with age, accompanied by increased local clustering and shortest path length, indicating a transition from a relatively random to a more organized configuration. Moreover, multivariate pattern analysis using support vector regression revealed that individual brain maturity of preterm babies could be predicted by the network connectivity patterns. Collectively, we highlighted a gradually enhanced functional network segregation manner in the third trimester, which is primarily driven by the rapid increases of functional connectivity of the primary regions, providing crucial insights into the topological development patterns prior to birth. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Accelerated recovery from acute brain injuries: clinical efficacy of neurotrophic treatment in stroke and traumatic brain injuries.

PubMed

Bornstein, N; Poon, W S

2012-04-01

Stroke is one of the most devastating vascular diseases in the world as it is responsible for almost five million deaths per year. Almost 90% of all strokes are ischemic and mainly due to atherosclerosis, cardiac embolism and small-vessel disease. Intracerebral or subarachnoid hemorrhage can lead to hemorrhagic stroke, which usually has the poorest prognosis. Cerebrolysin is a peptide preparation which mimics the action of a neurotrophic factor, protecting stroke-injured neurons and promoting neuroplasticity and neurogenesis. Cerebrolysin has been widely studied as a therapeutic tool for both ischemic and hemorrhagic stroke, as well as traumatic brain injury. In ischemic stroke, Cerebrolysin given as an adjuvant therapy to antiplatelet and rheologically active medication resulted in accelerated improvement in global, neurological and motor functions, cognitive performance and activities of daily living. Cerebrolysin was also safe and well tolerated when administered in patients suffering from hemorrhagic stroke. Traumatic brain injury leads to transient or chronic impairments in physical, cognitive, emotional and behavioral functions. This is associated with deficits in the recognition of basic emotions, the capacity to interpret the mental states of others, and executive functioning. Pilot clinical studies with adjuvant Cerebrolysin in the acute and postacute phases of the injury have shown faster recovery, which translates into an earlier onset of rehabilitation and shortened hospitalization time. Copyright 2012 Prous Science, S.A.U. or its licensors. All rights reserved.

Analysis of Time-Dependent Brain Network on Active and MI Tasks for Chronic Stroke Patients

PubMed Central

Chang, Won Hyuk; Kim, Yun-Hee; Lee, Seong-Whan; Kwon, Gyu Hyun

2015-01-01

Several researchers have analyzed brain activities by investigating brain networks. However, there is a lack of the research on the temporal characteristics of the brain network during a stroke by EEG and the comparative studies between motor execution and imagery, which became known to have similar motor functions and pathways. In this study, we proposed the possibility of temporal characteristics on the brain networks of a stroke. We analyzed the temporal properties of the brain networks for nine chronic stroke patients by the active and motor imagery tasks by EEG. High beta band has a specific role in the brain network during motor tasks. In the high beta band, for the active task, there were significant characteristics of centrality and small-worldness on bilateral primary motor cortices at the initial motor execution. The degree centrality significantly increased on the contralateral primary motor cortex, and local efficiency increased on the ipsilateral primary motor cortex. These results indicate that the ipsilateral primary motor cortex constructed a powerful subnetwork by influencing the linked channels as compensatory effect, although the contralateral primary motor cortex organized an inefficient network by using the connected channels due to lesions. For the MI task, degree centrality and local efficiency significantly decreased on the somatosensory area at the initial motor imagery. Then, there were significant correlations between the properties of brain networks and motor function on the contralateral primary motor cortex and somatosensory area for each motor execution/imagery task. Our results represented that the active and MI tasks have different mechanisms of motor acts. Based on these results, we indicated the possibility of customized rehabilitation according to different motor tasks. We expect these results to help in the construction of the customized rehabilitation system depending on motor tasks by understanding temporal functional characteristics on brain network for a stroke. PMID:26656269

Virtual reality and consciousness inference in dreaming.

PubMed

Hobson, J Allan; Hong, Charles C-H; Friston, Karl J

2014-01-01

This article explores the notion that the brain is genetically endowed with an innate virtual reality generator that - through experience-dependent plasticity - becomes a generative or predictive model of the world. This model, which is most clearly revealed in rapid eye movement (REM) sleep dreaming, may provide the theater for conscious experience. Functional neuroimaging evidence for brain activations that are time-locked to rapid eye movements (REMs) endorses the view that waking consciousness emerges from REM sleep - and dreaming lays the foundations for waking perception. In this view, the brain is equipped with a virtual model of the world that generates predictions of its sensations. This model is continually updated and entrained by sensory prediction errors in wakefulness to ensure veridical perception, but not in dreaming. In contrast, dreaming plays an essential role in maintaining and enhancing the capacity to model the world by minimizing model complexity and thereby maximizing both statistical and thermodynamic efficiency. This perspective suggests that consciousness corresponds to the embodied process of inference, realized through the generation of virtual realities (in both sleep and wakefulness). In short, our premise or hypothesis is that the waking brain engages with the world to predict the causes of sensations, while in sleep the brain's generative model is actively refined so that it generates more efficient predictions during waking. We review the evidence in support of this hypothesis - evidence that grounds consciousness in biophysical computations whose neuronal and neurochemical infrastructure has been disclosed by sleep research.

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

NASA Astrophysics Data System (ADS)

Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

2011-03-01

Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

Epidemics in interconnected small-world networks.

PubMed

Liu, Meng; Li, Daqing; Qin, Pengju; Liu, Chaoran; Wang, Huijuan; Wang, Feilong

2015-01-01

Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

Real-World Data on Prognostic Factors for Overall Survival in EGFR Mutation-Positive Advanced Non-Small Cell Lung Cancer Patients Treated with First-Line Gefitinib.

PubMed

Yao, Zong-Han; Liao, Wei-Yu; Ho, Chao-Chi; Chen, Kuan-Yu; Shih, Jin-Yuan; Chen, Jin-Shing; Lin, Zhong-Zhe; Lin, Chia-Chi; Chih-Hsin Yang, James; Yu, Chong-Jen

2017-09-01

This study aimed to identify independent prognostic factors for overall survival (OS) of patients with advanced non-small cell lung cancer (NSCLC) harboring an activating epidermal growth factor receptor (EGFR) mutation and receiving gefitinib as first-line treatment in real-world practice. We enrolled 226 patients from June 2011 to May 2013. During this period, gefitinib was the only EGFR-tyrosine kinase inhibitor reimbursed by the Bureau of National Health Insurance of Taiwan. The median progression-free survival and median OS were 11.9 months (95% confidence interval [CI]: 9.7-14.2) and 26.9 months (21.2-32.5), respectively. The Cox proportional hazards regression model revealed that postoperative recurrence, performance status (Eastern Cooperative Oncology Grade [ECOG] ≥2), smoking index (≥20 pack-years), liver metastasis at initial diagnosis, and chronic hepatitis C virus (HCV) infection were independent prognostic factors for OS (hazard ratio [95% CI] 0.3 [0.11-0.83], p  = .02; 2.69 [1.60-4.51], p  < .001; 1.92 [1.24-2.97], p  = .003; 2.26 [1.34-3.82], p  = .002; 3.38 [1.85-7.78], p  < .001, respectively). However, brain metastasis (BM) at initial diagnosis or intracranial progression during gefitinib treatment had no impact on OS (1.266 [0.83-1.93], p  = .275 and 0.75 [0.48-1.19], p  = .211, respectively). HCV infection, performance status (ECOG ≥2), newly diagnosed advanced NSCLC without prior operation, and liver metastasis predicted poor OS in EGFR mutation-positive advanced NSCLC patients treated with first-line gefitinib; however, neither BM at initial diagnosis nor intracranial progression during gefitinib treatment had an impact on OS. The finding that chronic hepatitis C virus (HCV) infection might predict poor overall survival (OS) in epidermal growth factor receptor mutation-positive advanced non-small cell lung cancer (NSCLC) patients treated with first-line gefitinib may raise awareness of benefit from anti-HCV treatment in this patient population. Brain metastasis in the initial diagnosis or intracranial progression during gefitinib treatment is not a prognostic factor for OS. This study, which enrolled a real-world population of NSCLC patients, including sicker patients who were not eligible for a clinical trial, may have impact on guiding usual clinical practice. © AlphaMed Press 2017.

A thermocouple thermode for small animals

NASA Technical Reports Server (NTRS)

Williams, B. A.

1972-01-01

Thermode composed of two thin-walled stainless steel hypodermic needles and cooper-constantan thermocouple or small thermistor to indicate temperature at point of perfusion is used to measure brain temperature in animals. Because of relatively small size of thermode, structural damage to brain is minimized.

Unique semantic space in the brain of each beholder predicts perceived similarity

PubMed Central

Charest, Ian; Kievit, Rogier A.; Schmitz, Taylor W.; Deca, Diana; Kriegeskorte, Nikolaus

2014-01-01

The unique way in which each of us perceives the world must arise from our brain representations. If brain imaging could reveal an individual’s unique mental representation, it could help us understand the biological substrate of our individual experiential worlds in mental health and disease. However, imaging studies of object vision have focused on commonalities between individuals rather than individual differences and on category averages rather than representations of particular objects. Here we investigate the individually unique component of brain representations of particular objects with functional MRI (fMRI). Subjects were presented with unfamiliar and personally meaningful object images while we measured their brain activity on two separate days. We characterized the representational geometry by the dissimilarity matrix of activity patterns elicited by particular object images. The representational geometry remained stable across scanning days and was unique in each individual in early visual cortex and human inferior temporal cortex (hIT). The hIT representation predicted perceived similarity as reflected in dissimilarity judgments. Importantly, hIT predicted the individually unique component of the judgments when the objects were personally meaningful. Our results suggest that hIT brain representational idiosyncrasies accessible to fMRI are expressed in an individual's perceptual judgments. The unique way each of us perceives the world thus might reflect the individually unique representation in high-level visual areas. PMID:25246586

"Grey matters".

PubMed

Rose, Katie

2014-01-01

It's common in this world, for diagnoses to be confused. This grey, oblique world is the "World of Brain Tumors" from which these narratives are written, a world I entered when a tangerine-sized tumor was found on my temporal lobe. Each narrative illustrates this world in which everything is covered in a thick film rendering things once obvious, now unknown. Parents are asked to choose treatment plans for their children, plans that will inevitably alter their child's quality of life but in ways they cannot determine or even imagine. Parents are asked to play God. Most of the parents who share their stories in this collection, parents of PBT (pediatric brain tumor) patients have to walk the line of trying to not disrupt their relationships with their physicians, wanting the best for their child, and facing the decision to follow their gut or go with advised treatment plans.

Functional Interplay between Small Non-Coding RNAs and RNA Modification in the Brain.

PubMed

Leighton, Laura J; Bredy, Timothy W

2018-06-07

Small non-coding RNAs are essential for transcription, translation and gene regulation in all cell types, but are particularly important in neurons, with known roles in neurodevelopment, neuroplasticity and neurological disease. Many small non-coding RNAs are directly involved in the post-transcriptional modification of other RNA species, while others are themselves substrates for modification, or are functionally modulated by modification of their target RNAs. In this review, we explore the known and potential functions of several distinct classes of small non-coding RNAs in the mammalian brain, focusing on the newly recognised interplay between the epitranscriptome and the activity of small RNAs. We discuss the potential for this relationship to influence the spatial and temporal dynamics of gene activation in the brain, and predict that further research in the field of epitranscriptomics will identify interactions between small RNAs and RNA modifications which are essential for higher order brain functions such as learning and memory.

Cediranib Maleate and Whole Brain Radiation Therapy in Patients With Brain Metastases From Non-Small Cell Lung Cancer

ClinicalTrials.gov

2013-03-07

Male Breast Cancer; Stage IV Breast Cancer; Stage IV Melanoma; Stage IV Non-small Cell Lung Cancer; Stage IV Renal Cell Cancer; Stage IVA Colon Cancer; Stage IVA Rectal Cancer; Stage IVB Colon Cancer; Stage IVB Rectal Cancer; Tumors Metastatic to Brain

Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes.

PubMed

Hosseini, S M Hadi; Mazaika, Paul; Mauras, Nelly; Buckingham, Bruce; Weinzimer, Stuart A; Tsalikian, Eva; White, Neil H; Reiss, Allan L

2016-11-01

Type 1 diabetes mellitus (T1D), one of the most frequent chronic diseases in children, is associated with glucose dysregulation that contributes to an increased risk for neurocognitive deficits. While there is a bulk of evidence regarding neurocognitive deficits in adults with T1D, little is known about how early-onset T1D affects neural networks in young children. Recent data demonstrated widespread alterations in regional gray matter and white matter associated with T1D in young children. These widespread neuroanatomical changes might impact the organization of large-scale brain networks. In the present study, we applied graph-theoretical analysis to test whether the organization of structural covariance networks in the brain for a cohort of young children with T1D (N = 141) is altered compared to healthy controls (HC; N = 69). While the networks in both groups followed a small world organization-an architecture that is simultaneously highly segregated and integrated-the T1D network showed significantly longer path length compared with HC, suggesting reduced global integration of brain networks in young children with T1D. In addition, network robustness analysis revealed that the T1D network model showed more vulnerability to neural insult compared with HC. These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. This is the first study to examine structural covariance networks in young children with T1D. Improving glycemic control for young children with T1D might help prevent alterations in brain networks in this population. Hum Brain Mapp 37:4034-4046, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A computational study of whole-brain connectivity in resting state and task fMRI

PubMed Central

Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

2014-01-01

Background We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition. PMID:24947491

TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE.

PubMed

Prasad, Gautam; Nir, Talia M; Toga, Arthur W; Thompson, Paul M

2013-04-01

Brain connectivity declines in Alzheimer's disease (AD), both functionally and structurally. Connectivity maps and networks derived from diffusion-based tractography offer new ways to track disease progression and to understand how AD affects the brain. Here we set out to identify (1) which fiber network measures show greatest differences between AD patients and controls, and (2) how these effects depend on the density of fibers extracted by the tractography algorithm. We computed brain networks from diffusion-weighted images (DWI) of the brain, in 110 subjects (28 normal elderly, 56 with early and 11 with late mild cognitive impairment, and 15 with AD). We derived connectivity matrices and network topology measures, for each subject, from whole-brain tractography and cortical parcellations. We used an ODF lookup table to speed up fiber extraction, and to exploit the full information in the orientation distribution function (ODF). This made it feasible to compute high density connectivity maps. We used accelerated tractography to compute a large number of fibers to understand what effect fiber density has on network measures and in distinguishing different disease groups in our data. We focused on global efficiency, transitivity, path length, mean degree, density, modularity, small world, and assortativity measures computed from weighted and binary undirected connectivity matrices. Of all these measures, the mean nodal degree best distinguished diagnostic groups. High-density fiber matrices were most helpful for picking up the more subtle clinical differences, e.g. between mild cognitively impaired (MCI) and normals, or for distinguishing subtypes of MCI (early versus late). Care is needed in clinical analyses of brain connectivity, as the density of extracted fibers may affect how well a network measure can pick up differences between patients and controls.

Individual diversity of functional brain network economy.

PubMed

Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Ganger, Sebastian; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-04-01

On average, brain network economy represents a trade-off between communication efficiency, robustness, and connection cost, although an analogous understanding on an individual level is largely missing. Evaluating resting-state networks of 42 healthy participants with seven Tesla functional magnetic resonance imaging and graph theory revealed that not even half of all possible connections were common across subjects. The strongest similarities among individuals were observed for interhemispheric and/or short-range connections, which may relate to the essential feature of the human brain to develop specialized systems within each hemisphere. Despite this marked variability in individual network architecture, all subjects exhibited equal small-world properties. Furthermore, interdependency between four major network economy metrics was observed across healthy individuals. The characteristic path length was associated with the clustering coefficient (peak correlation r=0.93), the response to network attacks (r=-0.97), and the physical connection cost in three-dimensional space (r=-0.62). On the other hand, clustering was negatively related to attack response (r=-0.75) and connection cost (r=-0.59). Finally, increased connection cost was associated with better response to attacks (r=0.65). This indicates that functional brain networks with high global information transfer also exhibit strong network resilience. However, it seems that these advantages come at the cost of decreased local communication efficiency and increased physical connection cost. Except for wiring length, the results were replicated on a subsample at three Tesla (n=20). These findings highlight the finely tuned interrelationships between different parameters of brain network economy. Moreover, the understanding of the individual diversity of functional brain network economy may provide further insights in the vulnerability to mental and neurological disorders.

Disrupted resting-state brain network properties in obesity: decreased global and putaminal cortico-striatal network efficiency.

PubMed

Baek, K; Morris, L S; Kundu, P; Voon, V

2017-03-01

The efficient organization and communication of brain networks underlie cognitive processing and their disruption can lead to pathological behaviours. Few studies have focused on whole-brain networks in obesity and binge eating disorder (BED). Here we used multi-echo resting-state functional magnetic resonance imaging (rsfMRI) along with a data-driven graph theory approach to assess brain network characteristics in obesity and BED. Multi-echo rsfMRI scans were collected from 40 obese subjects (including 20 BED patients) and 40 healthy controls and denoised using multi-echo independent component analysis (ME-ICA). We constructed a whole-brain functional connectivity matrix with normalized correlation coefficients between regional mean blood oxygenation level-dependent (BOLD) signals from 90 brain regions in the Automated Anatomical Labeling atlas. We computed global and regional network properties in the binarized connectivity matrices with an edge density of 5%-25%. We also verified our findings using a separate parcellation, the Harvard-Oxford atlas parcellated into 470 regions. Obese subjects exhibited significantly reduced global and local network efficiency as well as decreased modularity compared with healthy controls, showing disruption in small-world and modular network structures. In regional metrics, the putamen, pallidum and thalamus exhibited significantly decreased nodal degree and efficiency in obese subjects. Obese subjects also showed decreased connectivity of cortico-striatal/cortico-thalamic networks associated with putaminal and cortical motor regions. These findings were significant with ME-ICA with limited group differences observed with conventional denoising or single-echo analysis. Using this data-driven analysis of multi-echo rsfMRI data, we found disruption in global network properties and motor cortico-striatal networks in obesity consistent with habit formation theories. Our findings highlight the role of network properties in pathological food misuse as possible biomarkers and therapeutic targets.

PAGANI Toolkit: Parallel graph-theoretical analysis package for brain network big data.

PubMed

Du, Haixiao; Xia, Mingrui; Zhao, Kang; Liao, Xuhong; Yang, Huazhong; Wang, Yu; He, Yong

2018-05-01

The recent collection of unprecedented quantities of neuroimaging data with high spatial resolution has led to brain network big data. However, a toolkit for fast and scalable computational solutions is still lacking. Here, we developed the PArallel Graph-theoretical ANalysIs (PAGANI) Toolkit based on a hybrid central processing unit-graphics processing unit (CPU-GPU) framework with a graphical user interface to facilitate the mapping and characterization of high-resolution brain networks. Specifically, the toolkit provides flexible parameters for users to customize computations of graph metrics in brain network analyses. As an empirical example, the PAGANI Toolkit was applied to individual voxel-based brain networks with ∼200,000 nodes that were derived from a resting-state fMRI dataset of 624 healthy young adults from the Human Connectome Project. Using a personal computer, this toolbox completed all computations in ∼27 h for one subject, which is markedly less than the 118 h required with a single-thread implementation. The voxel-based functional brain networks exhibited prominent small-world characteristics and densely connected hubs, which were mainly located in the medial and lateral fronto-parietal cortices. Moreover, the female group had significantly higher modularity and nodal betweenness centrality mainly in the medial/lateral fronto-parietal and occipital cortices than the male group. Significant correlations between the intelligence quotient and nodal metrics were also observed in several frontal regions. Collectively, the PAGANI Toolkit shows high computational performance and good scalability for analyzing connectome big data and provides a friendly interface without the complicated configuration of computing environments, thereby facilitating high-resolution connectomics research in health and disease. © 2018 Wiley Periodicals, Inc.

Altered striatal activation predicting real-world positive affect in adolescent major depressive disorder.

PubMed

Forbes, Erika E; Hariri, Ahmad R; Martin, Samantha L; Silk, Jennifer S; Moyles, Donna L; Fisher, Patrick M; Brown, Sarah M; Ryan, Neal D; Birmaher, Boris; Axelson, David A; Dahl, Ronald E

2009-01-01

Alterations in reward-related brain function and phenomenological aspects of positive affect are increasingly examined in the development of major depressive disorder. The authors tested differences in reward-related brain function in healthy and depressed adolescents, and the authors examined direct links between reward-related brain function and positive mood that occurred in real-world contexts. Fifteen adolescents with major depressive disorder and 28 adolescents with no history of psychiatric disorder, ages 8-17 years, completed a functional magnetic resonance imaging guessing task involving monetary reward. Participants also reported their subjective positive affect in natural environments during a 4-day cell-phone-based ecological momentary assessment. Adolescents with major depressive disorder exhibited less striatal response than healthy comparison adolescents during reward anticipation and reward outcome, but more response in dorsolateral and medial prefrontal cortex. Diminished activation in a caudate region associated with this depression group difference was correlated with lower subjective positive affect in natural environments, particularly within the depressed group. Results support models of altered reward processing and related positive affect in young people with major depressive disorder and indicate that depressed adolescents' brain response to monetary reward is related to their affective experience in natural environments. Additionally, these results suggest that reward-processing paradigms capture brain function relevant to real-world positive affect.

Brain-Compatible Assessments. Second Edition

ERIC Educational Resources Information Center

Ronis, Diane L.

2007-01-01

Diane Ronis, a recognized expert in brain-compatible learning and assessment, goes beyond the world of standardized testing to show educators how to build and use targeted assessments based on the latest neuroscientific research. Updated to reflect recent findings about how the brain learns, this book provides readers with revised tools for…

With Boys and Girls in Mind

ERIC Educational Resources Information Center

Gurian, Michael; Stevens, Kathy

2004-01-01

New positron emission tomography (PET) and MRI technologies, which allow looking inside the brains, show that the brains of boys and girls differ both structurally and functionally that profoundly affect the human learning. These gender differences in the brain are corroborated in males and females throughout the world and do not differ…

Human factors involved in perception and action in a natural stereoscopic world: an up-to-date review with guidelines for stereoscopic displays and stereoscopic virtual reality (VR)

NASA Astrophysics Data System (ADS)

Perez-Bayas, Luis

2001-06-01

In stereoscopic perception of a three-dimensional world, binocular disparity might be thought of as the most important cue to 3D depth perception. Nevertheless, in reality there are many other factors involved before the 'final' conscious and subconscious stereoscopic perception, such as luminance, contrast, orientation, color, motion, and figure-ground extraction (pop-out phenomenon). In addition, more complex perceptual factors exist, such as attention and its duration (an equivalent of 'brain zooming') in relation to physiological central vision, In opposition to attention to peripheral vision and the brain 'top-down' information in relation to psychological factors like memory of previous experiences and present emotions. The brain's internal mapping of a pure perceptual world might be different from the internal mapping of a visual-motor space, which represents an 'action-directed perceptual world.' In addition, psychological factors (emotions and fine adjustments) are much more involved in a stereoscopic world than in a flat 2D-world, as well as in a world using peripheral vision (like VR, using a curved perspective representation, and displays, as natural vision does) as opposed to presenting only central vision (bi-macular stereoscopic vision) as in the majority of typical stereoscopic displays. Here is presented the most recent and precise information available about the psycho-neuro- physiological factors involved in the perception of stereoscopic three-dimensional world, with an attempt to give practical, functional, and pertinent guidelines for building more 'natural' stereoscopic displays.

Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom.

PubMed

Dikker, Suzanne; Wan, Lu; Davidesco, Ido; Kaggen, Lisa; Oostrik, Matthias; McClintock, James; Rowland, Jess; Michalareas, Georgios; Van Bavel, Jay J; Ding, Mingzhou; Poeppel, David

2017-05-08

The human brain has evolved for group living [1]. Yet we know so little about how it supports dynamic group interactions that the study of real-world social exchanges has been dubbed the "dark matter of social neuroscience" [2]. Recently, various studies have begun to approach this question by comparing brain responses of multiple individuals during a variety of (semi-naturalistic) tasks [3-15]. These experiments reveal how stimulus properties [13], individual differences [14], and contextual factors [15] may underpin similarities and differences in neural activity across people. However, most studies to date suffer from various limitations: they often lack direct face-to-face interaction between participants, are typically limited to dyads, do not investigate social dynamics across time, and, crucially, they rarely study social behavior under naturalistic circumstances. Here we extend such experimentation drastically, beyond dyads and beyond laboratory walls, to identify neural markers of group engagement during dynamic real-world group interactions. We used portable electroencephalogram (EEG) to simultaneously record brain activity from a class of 12 high school students over the course of a semester (11 classes) during regular classroom activities (Figures 1A-1C; Supplemental Experimental Procedures, section S1). A novel analysis technique to assess group-based neural coherence demonstrates that the extent to which brain activity is synchronized across students predicts both student class engagement and social dynamics. This suggests that brain-to-brain synchrony is a possible neural marker for dynamic social interactions, likely driven by shared attention mechanisms. This study validates a promising new method to investigate the neuroscience of group interactions in ecologically natural settings. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Algebraic approach to small-world network models

NASA Astrophysics Data System (ADS)

Rudolph-Lilith, Michelle; Muller, Lyle E.

2014-01-01

We introduce an analytic model for directed Watts-Strogatz small-world graphs and deduce an algebraic expression of its defining adjacency matrix. The latter is then used to calculate the small-world digraph's asymmetry index and clustering coefficient in an analytically exact fashion, valid nonasymptotically for all graph sizes. The proposed approach is general and can be applied to all algebraically well-defined graph-theoretical measures, thus allowing for an analytical investigation of finite-size small-world graphs.

[Progress of treatments in non-small cell lung cancer with brain metastases].

PubMed

Ma, Chunhua; Jiang, Rong

2012-05-01

Brain metastases is one of the most common complications of non-small cell lung cancer, whole brain radiotherapy (WBRT), stereotactic radiosurgery (SRS), surgery and chemotherapy are standard methods in the treatment of brain metastases. But the effect of those treatments are still sad. Comprehensive treatment can prolong the survival and improve the quality of life. Recently, the improvement of technology, targeted therapy, survival time and the quality of life are in increasingly concerned. The paper make a summary of current situation and progress for comprehensive therapy of brain metastases.

Relationship Between Large-Scale Functional and Structural Covariance Networks in Idiopathic Generalized Epilepsy

PubMed Central

Zhang, Zhiqiang; Mantini, Dante; Xu, Qiang; Wang, Zhengge; Chen, Guanghui; Jiao, Qing; Zang, Yu-Feng

2013-01-01

Abstract The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of the large-scale interregional functional covariance network (FCN) in the brain. Further, the relationship between the FCN and the structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures and 59 healthy controls. We estimated the FCN and the SCN by measuring amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small worldness and highly-connected hub regions. The patients had an altered overall topology compared to the controls, suggesting that epilepsy is primarily a disorder of the cerebral network organization. Further, the patients had altered nodal characteristics in the subcortical and medial temporal regions and default-mode regions, for both the FCN and SCN. Importantly, the correspondence between the FCN and SCN was significantly larger in patients than in the controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between the whole-brain network organization and pathology in generalized tonic–clonic seizures. PMID:23510272

Homeostatic structural plasticity can account for topology changes following deafferentation and focal stroke.

PubMed

Butz, Markus; Steenbuck, Ines D; van Ooyen, Arjen

2014-01-01

After brain lesions caused by tumors or stroke, or after lasting loss of input (deafferentation), inter- and intra-regional brain networks respond with complex changes in topology. Not only areas directly affected by the lesion but also regions remote from the lesion may alter their connectivity-a phenomenon known as diaschisis. Changes in network topology after brain lesions can lead to cognitive decline and increasing functional disability. However, the principles governing changes in network topology are poorly understood. Here, we investigated whether homeostatic structural plasticity can account for changes in network topology after deafferentation and brain lesions. Homeostatic structural plasticity postulates that neurons aim to maintain a desired level of electrical activity by deleting synapses when neuronal activity is too high and by providing new synaptic contacts when activity is too low. Using our Model of Structural Plasticity, we explored how local changes in connectivity induced by a focal loss of input affected global network topology. In accordance with experimental and clinical data, we found that after partial deafferentation, the network as a whole became more random, although it maintained its small-world topology, while deafferentated neurons increased their betweenness centrality as they rewired and returned to the homeostatic range of activity. Furthermore, deafferentated neurons increased their global but decreased their local efficiency and got longer tailed degree distributions, indicating the emergence of hub neurons. Together, our results suggest that homeostatic structural plasticity may be an important driving force for lesion-induced network reorganization and that the increase in betweenness centrality of deafferentated areas may hold as a biomarker for brain repair.

Slow Spatial Recruitment of Neocortex during Secondarily Generalized Seizures and Its Relation to Surgical Outcome

PubMed Central

Martinet, Louis-Emmanuel; Ahmed, Omar J.; Lepage, Kyle Q.; Cash, Sydney S.

2015-01-01

Understanding the spatiotemporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic mechanisms of brain dysfunction. Focal seizures with secondary generalization are traditionally considered to begin in a limited spatial region and spread to connected areas, which can include both pathological and normal brain tissue. The mechanisms underlying this spread are important to our understanding of seizures and to improve therapies for surgical intervention. Here we study the properties of seizure recruitment—how electrical brain activity transitions to large voltage fluctuations characteristic of spike-and-wave seizures. We do so using invasive subdural electrode arrays from a population of 16 patients with pharmacoresistant epilepsy. We find an average delay of ∼30 s for a broad area of cortex (8 × 8 cm) to be recruited into the seizure, at an estimated speed of ∼4 mm/s. The spatiotemporal characteristics of recruitment reveal two categories of patients: one in which seizure recruitment of neighboring cortical regions follows a spatially organized pattern consistent from seizure to seizure, and a second group without consistent spatial organization of activity during recruitment. The consistent, organized recruitment correlates with a more regular, compared with small-world, connectivity pattern in simulation and successful surgical treatment of epilepsy. We propose that an improved understanding of how the seizure recruits brain regions into large amplitude voltage fluctuations provides novel information to improve surgical treatment of epilepsy and highlights the slow spread of massive local activity across a vast extent of cortex during seizure. PMID:26109670

More randomized and resilient in the topological properties of functional brain networks in patients with major depressive disorder.

PubMed

Li, Huaizhou; Zhou, Haiyan; Yang, Yang; Wang, Haiyuan; Zhong, Ning

2017-10-01

Previous studies have reported the enhanced randomization of functional brain networks in patients with major depressive disorder (MDD). However, little is known about the changes of key nodal attributes for randomization, the resilience of network, and the clinical significance of the alterations. In this study, we collected the resting-state functional MRI data from 19 MDD patients and 19 healthy control (HC) individuals. Graph theory analysis showed that decreases were found in the small-worldness, clustering coefficient, local efficiency, and characteristic path length (i.e., increase of global efficiency) in the network of MDD group compared with HC group, which was consistent with previous findings and suggested the development toward randomization in the brain network in MDD. In addition, the greater resilience under the targeted attacks was also found in the network of patients with MDD. Furthermore, the abnormal nodal properties were found, including clustering coefficients and nodal efficiencies in the left orbital superior frontal gyrus, bilateral insula, left amygdala, right supramarginal gyrus, left putamen, left posterior cingulate cortex, left angular gyrus. Meanwhile, the correlation analysis showed that most of these abnormal areas were associated with the clinical status. The observed increased randomization and resilience in MDD might be related to the abnormal hub nodes in the brain networks, which were attacked by the disease pathology. Our findings provide new evidence to indicate that the weakening of specialized regions and the enhancement of whole brain integrity could be the potential endophenotype of the depressive pathology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysing Local Sparseness in the Macaque Brain Network

PubMed Central

Singh, Raghavendra; Nagar, Seema; Nanavati, Amit A.

2015-01-01

Understanding the network structure of long distance pathways in the brain is a necessary step towards developing an insight into the brain’s function, organization and evolution. Dense global subnetworks of these pathways have often been studied, primarily due to their functional implications. Instead we study sparse local subnetworks of the pathways to establish the role of a brain area in enabling shortest path communication between its non-adjacent topological neighbours. We propose a novel metric to measure the topological communication load on a vertex due to its immediate neighbourhood, and show that in terms of distribution of this local communication load, a network of Macaque long distance pathways is substantially different from other real world networks and random graph models. Macaque network contains the entire range of local subnetworks, from star-like networks to clique-like networks, while other networks tend to contain a relatively small range of subnetworks. Further, sparse local subnetworks in the Macaque network are not only found across topographical super-areas, e.g., lobes, but also within a super-area, arguing that there is conservation of even relatively short-distance pathways. To establish the communication role of a vertex we borrow the concept of brokerage from social science, and present the different types of brokerage roles that brain areas play, highlighting that not only the thalamus, but also cingulate gyrus and insula often act as “relays” for areas in the neocortex. These and other analysis of communication load and roles of the sparse subnetworks of the Macaque brain provide new insights into the organisation of its pathways. PMID:26437077

The remarkable visual capacities of nocturnal insects: vision at the limits with small eyes and tiny brains.

PubMed

Warrant, Eric J

2017-04-05

Nocturnal insects have evolved remarkable visual capacities, despite small eyes and tiny brains. They can see colour, control flight and land, react to faint movements in their environment, navigate using dim celestial cues and find their way home after a long and tortuous foraging trip using learned visual landmarks. These impressive visual abilities occur at light levels when only a trickle of photons are being absorbed by each photoreceptor, begging the question of how the visual system nonetheless generates the reliable signals needed to steer behaviour. In this review, I attempt to provide an answer to this question. Part of the answer lies in their compound eyes, which maximize light capture. Part lies in the slow responses and high gains of their photoreceptors, which improve the reliability of visual signals. And a very large part lies in the spatial and temporal summation of these signals in the optic lobe, a strategy that substantially enhances contrast sensitivity in dim light and allows nocturnal insects to see a brighter world, albeit a slower and coarser one. What is abundantly clear, however, is that during their evolution insects have overcome several serious potential visual limitations, endowing them with truly extraordinary night vision.This article is part of the themed issue 'Vision in dim light'. © 2017 The Author(s).

Impact of transient emotions on functional connectivity during subsequent resting state: a wavelet correlation approach.

PubMed

Eryilmaz, Hamdi; Van De Ville, Dimitri; Schwartz, Sophie; Vuilleumier, Patrik

2011-02-01

The functional properties of resting brain activity are poorly understood, but have generally been related to self-monitoring and introspective processes. Here we investigated how emotionally positive and negative information differentially influenced subsequent brain activity at rest. We acquired fMRI data in 15 participants during rest periods following fearful, joyful, and neutral movies. Several brain regions were more active during resting than during movie-watching, including posterior/anterior cingulate cortices (PCC, ACC), bilateral insula and inferior parietal lobules (IPL). Functional connectivity at different frequency bands was also assessed using a wavelet correlation approach and small-world network analysis. Resting activity in ACC and insula as well as their coupling were strongly enhanced by preceding emotions, while coupling between ventral-medial prefrontal cortex and amygdala was selectively reduced. These effects were more pronounced after fearful than joyful movies for higher frequency bands. Moreover, the initial suppression of resting activity in ACC and insula after emotional stimuli was followed by a gradual restoration over time. Emotions did not affect IPL average activity but increased its connectivity with other regions. These findings reveal specific neural circuits recruited during the recovery from emotional arousal and highlight the complex functional dynamics of default mode networks in emotionally salient contexts. Copyright © 2010 Elsevier Inc. All rights reserved.

Large-scale Cortical Network Properties Predict Future Sound-to-Word Learning Success

PubMed Central

Sheppard, John Patrick; Wang, Ji-Ping; Wong, Patrick C. M.

2013-01-01

The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants’ future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-to-word learning abilities among healthy, younger adults. PMID:22360625

Natural world physical, brain operational, and mind phenomenal space-time

NASA Astrophysics Data System (ADS)

Fingelkurts, Andrew A.; Fingelkurts, Alexander A.; Neves, Carlos F. H.

2010-06-01

Concepts of space and time are widely developed in physics. However, there is a considerable lack of biologically plausible theoretical frameworks that can demonstrate how space and time dimensions are implemented in the activity of the most complex life-system - the brain with a mind. Brain activity is organized both temporally and spatially, thus representing space-time in the brain. Critical analysis of recent research on the space-time organization of the brain's activity pointed to the existence of so-called operational space-time in the brain. This space-time is limited to the execution of brain operations of differing complexity. During each such brain operation a particular short-term spatio-temporal pattern of integrated activity of different brain areas emerges within related operational space-time. At the same time, to have a fully functional human brain one needs to have a subjective mental experience. Current research on the subjective mental experience offers detailed analysis of space-time organization of the mind. According to this research, subjective mental experience (subjective virtual world) has definitive spatial and temporal properties similar to many physical phenomena. Based on systematic review of the propositions and tenets of brain and mind space-time descriptions, our aim in this review essay is to explore the relations between the two. To be precise, we would like to discuss the hypothesis that via the brain operational space-time the mind subjective space-time is connected to otherwise distant physical space-time reality.

Human Fetal Brain Connectome: Structural Network Development from Middle Fetal Stage to Birth

PubMed Central

Song, Limei; Mishra, Virendra; Ouyang, Minhui; Peng, Qinmu; Slinger, Michelle; Liu, Shuwei; Huang, Hao

2017-01-01

Complicated molecular and cellular processes take place in a spatiotemporally heterogeneous and precisely regulated pattern in the human fetal brain, yielding not only dramatic morphological and microstructural changes, but also macroscale connectomic transitions. As the underlying substrate of the fetal brain structural network, both dynamic neuronal migration pathways and rapid developing fetal white matter (WM) fibers could fundamentally reshape early fetal brain connectome. Quantifying structural connectome development can not only shed light on the brain reconfiguration in this critical yet rarely studied developmental period, but also reveal alterations of the connectome under neuropathological conditions. However, transition of the structural connectome from the mid-fetal stage to birth is not yet known. The contribution of different types of neural fibers to the structural network in the mid-fetal brain is not known, either. In this study, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) of 10 fetal brain specimens at the age of 20 postmenstrual weeks (PMW), 12 in vivo brains at 35 PMW, and 12 in vivo brains at term (40 PMW) were acquired. The structural connectome of each brain was established with evenly parcellated cortical regions as network nodes and traced fiber pathways based on DTI tractography as network edges. Two groups of fibers were categorized based on the fiber terminal locations in the cerebral wall in the 20 PMW fetal brains. We found that fetal brain networks become stronger and more efficient during 20–40 PMW. Furthermore, network strength and global efficiency increase more rapidly during 20–35 PMW than during 35–40 PMW. Visualization of the whole brain fiber distribution by the lengths suggested that the network reconfiguration in this developmental period could be associated with a significant increase of major long association WM fibers. In addition, non-WM neural fibers could be a major contributor to the structural network configuration at 20 PMW and small-world network organization could exist as early as 20 PMW. These findings offer a preliminary record of the fetal brain structural connectome maturation from the middle fetal stage to birth and reveal the critical role of non-WM neural fibers in structural network configuration in the middle fetal stage. PMID:29081731

Radiological Society of North America

MedlinePlus

... Courses Electronic Education Exhibits RSNA Journals RSNA/AAPM Physics Modules RadioGraphics ABR Diagnostic Radiology Core Exam Study ... Brain Tumor Classification System In 2016, the World Health Organization (WHO) released an update to its brain ...

The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.

Trade-offs between robustness and small-world effect in complex networks

PubMed Central

Peng, Guan-Sheng; Tan, Suo-Yi; Wu, Jun; Holme, Petter

2016-01-01

Robustness and small-world effect are two crucial structural features of complex networks and have attracted increasing attention. However, little is known about the relation between them. Here we demonstrate that, there is a conflicting relation between robustness and small-world effect for a given degree sequence. We suggest that the robustness-oriented optimization will weaken the small-world effect and vice versa. Then, we propose a multi-objective trade-off optimization model and develop a heuristic algorithm to obtain the optimal trade-off topology for robustness and small-world effect. We show that the optimal network topology exhibits a pronounced core-periphery structure and investigate the structural properties of the optimized networks in detail. PMID:27853301

Collective dynamics of 'small-world' networks.

PubMed

Watts, D J; Strogatz, S H

1998-06-04

Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

Gamma Knife radiosurgery for brain metastases from pulmonary large cell neuroendocrine carcinoma: a Japanese multi-institutional cooperative study (JLGK1401).

PubMed

Kawabe, Takuya; Yamamoto, Masaaki; Sato, Yasunori; Yomo, Shoji; Kondoh, Takeshi; Nagano, Osamu; Serizawa, Toru; Tsugawa, Takahiko; Okamoto, Hisayo; Akabane, Atsuya; Aita, Kazuyasu; Sato, Manabu; Jokura, Hidefumi; Kawagishi, Jun; Shuto, Takashi; Kawai, Hideya; Moriki, Akihito; Kenai, Hiroyuki; Iwai, Yoshiyasu; Gondo, Masazumi; Hasegawa, Toshinori; Yasuda, Soichiro; Kikuchi, Yasuhiro; Nagatomo, Yasushi; Watanabe, Shinya; Hashimoto, Naoya

2016-12-01

OBJECTIVE In 1999, the World Health Organization categorized large cell neuroendocrine carcinoma (LCNEC) of the lung as a variant of large cell carcinoma, and LCNEC now accounts for 3% of all lung cancers. Although LCNEC is categorized among the non-small cell lung cancers, its biological behavior has recently been suggested to be very similar to that of a small cell pulmonary malignancy. The clinical outcome for patients with LCNEC is generally poor, and the optimal treatment for this malignancy has not yet been established. Little information is available regarding management of LCNEC patients with brain metastases (METs). This study aimed to evaluate the efficacy of Gamma Knife radiosurgery (GKRS) for patients with brain METs from LCNEC. METHODS The Japanese Leksell Gamma Knife Society planned this retrospective study in which 21 Gamma Knife centers in Japan participated. Data from 101 patients were reviewed for this study. Most of the patients with LCNEC were men (80%), and the mean age was 67 years (range 39-84 years). Primary lung tumors were reported as well controlled in one-third of the patients. More than half of the patients had extracranial METs. Brain metastasis and lung cancer had been detected simultaneously in 25% of the patients. Before GKRS, brain METs had manifested with neurological symptoms in 37 patients. Additionally, prior to GKRS, resection was performed in 17 patients and radiation therapy in 10. A small cell lung carcinoma-based chemotherapy regimen was chosen for 48 patients. The median lesion number was 3 (range 1-33). The median cumulative tumor volume was 3.5 cm 3 , and the median radiation dose was 20.0 Gy. For statistical analysis, the standard Kaplan-Meier method was used to determine post-GKRS survival. Competing risk analysis was applied to estimate GKRS cumulative incidences of maintenance of neurological function and death, local recurrence, appearance of new lesions, and complications. RESULTS The overall median survival time (MST) was 9.6 months. MSTs for patients classified according to the modified recursive partitioning analysis (RPA) system were 25.7, 11.0, and 5.9 months for Class 1+2a (20 patients), Class 2b (28), and Class 3 (46), respectively. At 12 months after GKRS, neurological death-free and deterioration-free survival rates were 93% and 87%, respectively. Follow-up imaging studies were available in 78 patients. The tumor control rate was 86% at 12 months after GKRS. CONCLUSIONS The present study suggests that GKRS is an effective treatment for LCNEC patients with brain METs, particularly in terms of maintaining neurological status.

The Influence of the Brain on Overpopulation, Ageing and Dependency.

ERIC Educational Resources Information Center

Cape, Ronald D. T.

1989-01-01

With time, an increasing number in the world population is becoming old, and changes in the aging brain mean that a significant proportion of the aged are likely to be dependent on others. The devotion of resources to research into the aging brain could bring benefits far outweighing the investment. (Author/CW)

Big Cat Coalitions: A Comparative Analysis of Regional Brain Volumes in Felidae.

PubMed

Sakai, Sharleen T; Arsznov, Bradley M; Hristova, Ani E; Yoon, Elise J; Lundrigan, Barbara L

2016-01-01

Broad-based species comparisons across mammalian orders suggest a number of factors that might influence the evolution of large brains. However, the relationship between these factors and total and regional brain size remains unclear. This study investigated the relationship between relative brain size and regional brain volumes and sociality in 13 felid species in hopes of revealing relationships that are not detected in more inclusive comparative studies. In addition, a more detailed analysis was conducted of four focal species: lions ( Panthera leo ), leopards ( Panthera pardus ), cougars ( Puma concolor ), and cheetahs ( Acinonyx jubatus ). These species differ markedly in sociality and behavioral flexibility, factors hypothesized to contribute to increased relative brain size and/or frontal cortex size. Lions are the only truly social species, living in prides. Although cheetahs are largely solitary, males often form small groups. Both leopards and cougars are solitary. Of the four species, leopards exhibit the most behavioral flexibility, readily adapting to changing circumstances. Regional brain volumes were analyzed using computed tomography. Skulls ( n = 75) were scanned to create three-dimensional virtual endocasts, and regional brain volumes were measured using either sulcal or bony landmarks obtained from the endocasts or skulls. Phylogenetic least squares regression analyses found that sociality does not correspond with larger relative brain size in these species. However, the sociality/solitary variable significantly predicted anterior cerebrum (AC) volume, a region that includes frontal cortex. This latter finding is despite the fact that the two social species in our sample, lions and cheetahs, possess the largest and smallest relative AC volumes, respectively. Additionally, an ANOVA comparing regional brain volumes in four focal species revealed that lions and leopards, while not significantly different from one another, have relatively larger AC volumes than are found in cheetahs or cougars. Further, female lions possess a significantly larger AC volume than conspecific males; female lion values were also larger than those of the other three species (regardless of sex). These results may reflect greater complexity in a female lion's social world, but additional studies are necessary. These data suggest that within family comparisons may reveal variations not easily detected by broad comparative analyses.

Big Cat Coalitions: A Comparative Analysis of Regional Brain Volumes in Felidae

PubMed Central

Sakai, Sharleen T.; Arsznov, Bradley M.; Hristova, Ani E.; Yoon, Elise J.; Lundrigan, Barbara L.

2016-01-01

Broad-based species comparisons across mammalian orders suggest a number of factors that might influence the evolution of large brains. However, the relationship between these factors and total and regional brain size remains unclear. This study investigated the relationship between relative brain size and regional brain volumes and sociality in 13 felid species in hopes of revealing relationships that are not detected in more inclusive comparative studies. In addition, a more detailed analysis was conducted of four focal species: lions (Panthera leo), leopards (Panthera pardus), cougars (Puma concolor), and cheetahs (Acinonyx jubatus). These species differ markedly in sociality and behavioral flexibility, factors hypothesized to contribute to increased relative brain size and/or frontal cortex size. Lions are the only truly social species, living in prides. Although cheetahs are largely solitary, males often form small groups. Both leopards and cougars are solitary. Of the four species, leopards exhibit the most behavioral flexibility, readily adapting to changing circumstances. Regional brain volumes were analyzed using computed tomography. Skulls (n = 75) were scanned to create three-dimensional virtual endocasts, and regional brain volumes were measured using either sulcal or bony landmarks obtained from the endocasts or skulls. Phylogenetic least squares regression analyses found that sociality does not correspond with larger relative brain size in these species. However, the sociality/solitary variable significantly predicted anterior cerebrum (AC) volume, a region that includes frontal cortex. This latter finding is despite the fact that the two social species in our sample, lions and cheetahs, possess the largest and smallest relative AC volumes, respectively. Additionally, an ANOVA comparing regional brain volumes in four focal species revealed that lions and leopards, while not significantly different from one another, have relatively larger AC volumes than are found in cheetahs or cougars. Further, female lions possess a significantly larger AC volume than conspecific males; female lion values were also larger than those of the other three species (regardless of sex). These results may reflect greater complexity in a female lion’s social world, but additional studies are necessary. These data suggest that within family comparisons may reveal variations not easily detected by broad comparative analyses. PMID:27812324

Altered small-world topology of structural brain networks in infants with intrauterine growth restriction and its association with later neurodevelopmental outcome.

PubMed

Batalle, Dafnis; Eixarch, Elisenda; Figueras, Francesc; Muñoz-Moreno, Emma; Bargallo, Nuria; Illa, Miriam; Acosta-Rojas, Ruthy; Amat-Roldan, Ivan; Gratacos, Eduard

2012-04-02

Intrauterine growth restriction (IUGR) due to placental insufficiency affects 5-10% of all pregnancies and it is associated with a wide range of short- and long-term neurodevelopmental disorders. Prediction of neurodevelopmental outcomes in IUGR is among the clinical challenges of modern fetal medicine and pediatrics. In recent years several studies have used magnetic resonance imaging (MRI) to demonstrate differences in brain structure in IUGR subjects, but the ability to use MRI for individual predictive purposes in IUGR is limited. Recent research suggests that MRI in vivo access to brain connectivity might have the potential to help understanding cognitive and neurodevelopment processes. Specifically, MRI based connectomics is an emerging approach to extract information from MRI data that exhaustively maps inter-regional connectivity within the brain to build a graph model of its neural circuitry known as brain network. In the present study we used diffusion MRI based connectomics to obtain structural brain networks of a prospective cohort of one year old infants (32 controls and 24 IUGR) and analyze the existence of quantifiable brain reorganization of white matter circuitry in IUGR group by means of global and regional graph theory features of brain networks. Based on global and regional analyses of the brain network topology we demonstrated brain reorganization in IUGR infants at one year of age. Specifically, IUGR infants presented decreased global and local weighted efficiency, and a pattern of altered regional graph theory features. By means of binomial logistic regression, we also demonstrated that connectivity measures were associated with abnormal performance in later neurodevelopmental outcome as measured by Bayley Scale for Infant and Toddler Development, Third edition (BSID-III) at two years of age. These findings show the potential of diffusion MRI based connectomics and graph theory based network characteristics for estimating differences in the architecture of neural circuitry and developing imaging biomarkers of poor neurodevelopment outcome in infants with prenatal diseases. Copyright © 2012 Elsevier Inc. All rights reserved.

Individual Morphological Brain Network Construction Based on Multivariate Euclidean Distances Between Brain Regions.

PubMed

Yu, Kaixin; Wang, Xuetong; Li, Qiongling; Zhang, Xiaohui; Li, Xinwei; Li, Shuyu

2018-01-01

Morphological brain network plays a key role in investigating abnormalities in neurological diseases such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, most of the morphological brain network construction methods only considered a single morphological feature. Each type of morphological feature has specific neurological and genetic underpinnings. A combination of morphological features has been proven to have better diagnostic performance compared with a single feature, which suggests that an individual morphological brain network based on multiple morphological features would be beneficial in disease diagnosis. Here, we proposed a novel method to construct individual morphological brain networks for two datasets by calculating the exponential function of multivariate Euclidean distance as the evaluation of similarity between two regions. The first dataset included 24 healthy subjects who were scanned twice within a 3-month period. The topological properties of these brain networks were analyzed and compared with previous studies that used different methods and modalities. Small world property was observed in all of the subjects, and the high reproducibility indicated the robustness of our method. The second dataset included 170 patients with MCI (86 stable MCI and 84 progressive MCI cases) and 169 normal controls (NC). The edge features extracted from the individual morphological brain networks were used to distinguish MCI from NC and separate MCI subgroups (progressive vs. stable) through the support vector machine in order to validate our method. The results showed that our method achieved an accuracy of 79.65% (MCI vs. NC) and 70.59% (stable MCI vs. progressive MCI) in a one-dimension situation. In a multiple-dimension situation, our method improved the classification performance with an accuracy of 80.53% (MCI vs. NC) and 77.06% (stable MCI vs. progressive MCI) compared with the method using a single feature. The results indicated that our method could effectively construct an individual morphological brain network based on multiple morphological features and could accurately discriminate MCI from NC and stable MCI from progressive MCI, and may provide a valuable tool for the investigation of individual morphological brain networks.

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

PubMed Central

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies. PMID:22412922

Plumbing the brain drain.

PubMed

Saravia, Nancy Gore; Miranda, Juan Francisco

2004-08-01

Opportunity is the driving force of migration. Unsatisfied demands for higher education and skills, which have been created by the knowledge-based global economy, have generated unprecedented opportunities in knowledge-intensive service industries. These multi-trillion dollar industries include information, communication, finance, business, education and health. The leading industrialized nations are also the focal points of knowledge-intensive service industries and as such constitute centres of research and development activity that proactively draw in talented individuals worldwide through selective immigration policies, employment opportunities and targeted recruitment. Higher education is another major conduit of talent from less-developed countries to the centres of the knowledge-based global economy. Together career and educational opportunities drive "brain drain and recirculation". The departure of a large proportion of the most competent and innovative individuals from developing nations slows the achievement of the critical mass needed to generate the enabling context in which knowledge creation occurs. To favourably modify the asymmetric movement and distribution of global talent, developing countries must implement bold and creative strategies that are backed by national policies to: provide world-class educational opportunities, construct knowledge-based research and development industries, and sustainably finance the required investment for these strategies. Brazil, China and India have moved in this direction, offering world-class education in areas crucial to national development, such as biotechnology and information technology, paralleled by investments in research and development. As a result, only a small proportion of the most highly educated individuals migrate from these countries, and research and development opportunities employ national talent and even attract immigrants.

Large-scale imaging in small brains

PubMed Central

Ahrens, Misha B.; Engert, Florian

2016-01-01

The dense connectivity in the brain and arrangements of cells into circuits means that one neuron’s activity can influence many others. To observe this interconnected system comprehensively, an aspiration within neuroscience is to record from as many neurons as possible at the same time. There are two useful routes toward this goal: one is to expand the spatial extent of functional imaging techniques, and the second is to use animals with small brains. Here we review recent progress toward imaging many neurons and complete populations of identified neurons in small vertebrates and invertebrates. PMID:25636154

Large-scale imaging in small brains.

PubMed

Ahrens, Misha B; Engert, Florian

2015-06-01

The dense connectivity in the brain means that one neuron's activity can influence many others. To observe this interconnected system comprehensively, an aspiration within neuroscience is to record from as many neurons as possible at the same time. There are two useful routes toward this goal: one is to expand the spatial extent of functional imaging techniques, and the second is to use animals with small brains. Here we review recent progress toward imaging many neurons and complete populations of identified neurons in small vertebrates and invertebrates. Copyright © 2015 Elsevier Ltd. All rights reserved.

"The Most Famous Brain in the World" Performance and Pedagogy on an Amnesiac's Brain

ERIC Educational Resources Information Center

Sweaney, Katherine W.

2012-01-01

Project H.M. was just the sort of thing one might expect the Internet to latch onto: it was a live streaming video of a frozen human brain being slowly sliced apart. Users who clicked the link on Twitter or Facebook between the 2nd and 4th of December 2009 were immediately confronted with a close-up shot of the brain's interior, which was…

Neural basis of processing threatening voices in a crowded auditory world

PubMed Central

Mothes-Lasch, Martin; Becker, Michael P. I.; Miltner, Wolfgang H. R.

2016-01-01

In real world situations, we typically listen to voice prosody against a background crowded with auditory stimuli. Voices and background can both contain behaviorally relevant features and both can be selectively in the focus of attention. Adequate responses to threat-related voices under such conditions require that the brain unmixes reciprocally masked features depending on variable cognitive resources. It is unknown which brain systems instantiate the extraction of behaviorally relevant prosodic features under varying combinations of prosody valence, auditory background complexity and attentional focus. Here, we used event-related functional magnetic resonance imaging to investigate the effects of high background sound complexity and attentional focus on brain activation to angry and neutral prosody in humans. Results show that prosody effects in mid superior temporal cortex were gated by background complexity but not attention, while prosody effects in the amygdala and anterior superior temporal cortex were gated by attention but not background complexity, suggesting distinct emotional prosody processing limitations in different regions. Crucially, if attention was focused on the highly complex background, the differential processing of emotional prosody was prevented in all brain regions, suggesting that in a distracting, complex auditory world even threatening voices may go unnoticed. PMID:26884543

Geometric Assortative Growth Model for Small-World Networks

PubMed Central

2014-01-01

It has been shown that both humanly constructed and natural networks are often characterized by small-world phenomenon and assortative mixing. In this paper, we propose a geometrically growing model for small-world networks. The model displays both tunable small-world phenomenon and tunable assortativity. We obtain analytical solutions of relevant topological properties such as order, size, degree distribution, degree correlation, clustering, transitivity, and diameter. It is also worth noting that the model can be viewed as a generalization for an iterative construction of Farey graphs. PMID:24578661

Brain tissue volumes in the general elderly population. The Rotterdam Scan Study.

PubMed

Ikram, M Arfan; Vrooman, Henri A; Vernooij, Meike W; van der Lijn, Fedde; Hofman, Albert; van der Lugt, Aad; Niessen, Wiro J; Breteler, Monique M B

2008-06-01

We investigated how volumes of cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) varied with age, sex, small vessel disease and cardiovascular risk factors in the Rotterdam Scan Study. Participants (n=490; 60-90 years) were non-demented and 51.0% had hypertension, 4.9% had diabetes mellitus, 17.8% were current smoker and 54.0% were former smoker. We segmented brain MR-images into GM, normal WM, white matter lesion (WML) and CSF. Brain infarcts were rated visually. Volumes were expressed as percentage of intra-cranial volume. With increasing age, volumes of total brain, normal WM and total WM decreased; that of GM remained unchanged; and that of WML increased, in both men and women. Excluding persons with infarcts did not alter these results. Persons with larger load of small vessel disease had smaller brain volume, especially normal WM volume. Diastolic blood pressure, diabetes mellitus and current smoking were also related to smaller brain volume. In the elderly, higher age, small vessel disease and cardiovascular risk factors are associated with smaller brain volume, especially WM volume.

Moebius Syndrome

MedlinePlus

... by small or absent brain stem nuclei that control the cranial nerves; Group II, characterized by loss and degeneration of neurons ... by small or absent brain stem nuclei that control the cranial nerves; Group II, characterized by loss and degeneration of neurons ...

Right-side-stretched multifractal spectra indicate small-worldness in networks

NASA Astrophysics Data System (ADS)

Oświȩcimka, Paweł; Livi, Lorenzo; Drożdż, Stanisław

2018-04-01

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several ;types; of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing multifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.

A new measure based on degree distribution that links information theory and network graph analysis

PubMed Central

2012-01-01

Background Detailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths. Results We captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system’s capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric. Conclusions The new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties. PMID:22726594

Pre-seizure architecture of the local connections of the epileptic focus examined via graph-theory.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Vollono, Catello; Fuggetta, Filomena; Bramanti, Placido; Cioni, Beatrice; Rossini, Paolo Maria

2016-10-01

Epilepsy is characterized by unpredictable and sudden paroxysmal neuronal firing occurrences and sometimes evolving in clinically evident seizure. To predict seizure event, small-world characteristic in nine minutes before seizure, divided in three 3-min periods (T0, T1, T2) were investigated. Intracerebral recordings were obtained from 10 patients with drug resistant focal epilepsy examined by means of stereotactically implanted electrodes; analysis was focused in a period of low spiking (Baseline) and during two seizures. Networks' architecture is undirected and weighted. Electrodes' contacts close to epileptic focus are the vertices, edges are weighted by mscohere (=magnitude squared coherence). Differences were observed between Baseline and T1 and between Baseline and T2 in theta band; and between Baseline and T1, Baseline and T2, and near-significant difference between T0 and T2 in Alpha 2 band. Moreover, an intra-band index was computed for small worldness as difference between Theta and Alpha 2. It was found a growing index trend from Baseline to T2. Cortical network features a specific pre-seizure architecture which could predict the incoming epileptic seizure. Through this study future researches could investigate brain connectivity modifications approximating a clinical seizure also in order to address a preventive therapy. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Brain Graph Topology Changes Associated with Anti-Epileptic Drug Use

PubMed Central

Levin, Harvey S.; Chiang, Sharon

2015-01-01

Abstract Neuroimaging studies of functional connectivity using graph theory have furthered our understanding of the network structure in temporal lobe epilepsy (TLE). Brain network effects of anti-epileptic drugs could influence such studies, but have not been systematically studied. Resting-state functional MRI was analyzed in 25 patients with TLE using graph theory analysis. Patients were divided into two groups based on anti-epileptic medication use: those taking carbamazepine/oxcarbazepine (CBZ/OXC) (n=9) and those not taking CBZ/OXC (n=16) as a part of their medication regimen. The following graph topology metrics were analyzed: global efficiency, betweenness centrality (BC), clustering coefficient, and small-world index. Multiple linear regression was used to examine the association of CBZ/OXC with graph topology. The two groups did not differ from each other based on epilepsy characteristics. Use of CBZ/OXC was associated with a lower BC. Longer epilepsy duration was also associated with a lower BC. These findings can inform graph theory-based studies in patients with TLE. The changes observed are discussed in relation to the anti-epileptic mechanism of action and adverse effects of CBZ/OXC. PMID:25492633

The Laplacian spectrum of neural networks

PubMed Central

de Lange, Siemon C.; de Reus, Marcel A.; van den Heuvel, Martijn P.

2014-01-01

The brain is a complex network of neural interactions, both at the microscopic and macroscopic level. Graph theory is well suited to examine the global network architecture of these neural networks. Many popular graph metrics, however, encode average properties of individual network elements. Complementing these “conventional” graph metrics, the eigenvalue spectrum of the normalized Laplacian describes a network's structure directly at a systems level, without referring to individual nodes or connections. In this paper, the Laplacian spectra of the macroscopic anatomical neuronal networks of the macaque and cat, and the microscopic network of the Caenorhabditis elegans were examined. Consistent with conventional graph metrics, analysis of the Laplacian spectra revealed an integrative community structure in neural brain networks. Extending previous findings of overlap of network attributes across species, similarity of the Laplacian spectra across the cat, macaque and C. elegans neural networks suggests a certain level of consistency in the overall architecture of the anatomical neural networks of these species. Our results further suggest a specific network class for neural networks, distinct from conceptual small-world and scale-free models as well as several empirical networks. PMID:24454286

An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

Evolution of brain region volumes during artificial selection for relative brain size.

PubMed

Kotrschal, Alexander; Zeng, Hong-Li; van der Bijl, Wouter; Öhman-Mägi, Caroline; Kotrschal, Kurt; Pelckmans, Kristiaan; Kolm, Niclas

2017-12-01

The vertebrate brain shows an extremely conserved layout across taxa. Still, the relative sizes of separate brain regions vary markedly between species. One interesting pattern is that larger brains seem associated with increased relative sizes only of certain brain regions, for instance telencephalon and cerebellum. Till now, the evolutionary association between separate brain regions and overall brain size is based on comparative evidence and remains experimentally untested. Here, we test the evolutionary response of brain regions to directional selection on brain size in guppies (Poecilia reticulata) selected for large and small relative brain size. In these animals, artificial selection led to a fast response in relative brain size, while body size remained unchanged. We use microcomputer tomography to investigate how the volumes of 11 main brain regions respond to selection for larger versus smaller brains. We found no differences in relative brain region volumes between large- and small-brained animals and only minor sex-specific variation. Also, selection did not change allometric scaling between brain and brain region sizes. Our results suggest that brain regions respond similarly to strong directional selection on relative brain size, which indicates that brain anatomy variation in contemporary species most likely stem from direct selection on key regions. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Hyperbrain features of team mental models within a juggling paradigm: a proof of concept

PubMed Central

Filho, Edson; Tamburro, Gabriella; Schinaia, Lorenzo; Chatel-Goldman, Jonas; di Fronso, Selenia; Robazza, Claudio

2016-01-01

Background Research on cooperative behavior and the social brain exists, but little research has focused on real-time motor cooperative behavior and its neural correlates. In this proof of concept study, we explored the conceptual notion of shared and complementary mental models through EEG mapping of two brains performing a real-world interactive motor task of increasing difficulty. We used the recently introduced participative “juggling paradigm,” and collected neuro-physiological and psycho-social data. We were interested in analyzing the between-brains coupling during a dyadic juggling task, and in exploring the relationship between the motor task execution, the jugglers’skill level and the task difficulty. We also investigated how this relationship could be mirrored in the coupled functional organization of the interacting brains. Methods To capture the neural schemas underlying the notion of shared and complementary mental models, we examined the functional connectivity patterns and hyperbrain features of a juggling dyad involved in cooperative motor tasks of increasing difficulty. Jugglers’ cortical activity was measured using two synchronized 32-channel EEG systems during dyadic juggling performed with 3, 4, 5 and 6 balls. Individual and hyperbrain functional connections were quantified through coherence maps calculated across all electrode pairs in the theta and alpha bands (4–8 and 8–12 Hz). Graph metrics were used to typify the global topology and efficiency of the functional networks for the four difficulty levels in the theta and alpha bands. Results Results indicated that, as task difficulty increased, the cortical functional organization of the more skilled juggler became progressively more segregated in both frequency bands, with a small-world organization in the theta band during easier tasks, indicative of a flow-like state in line with the neural efficiency hypothesis. Conversely, more integrated functional patterns were observed for the less skilled juggler in both frequency bands, possibly related to cognitive overload due to the difficulty of the task at hand (reinvestment hypothesis). At the hyperbrain level, a segregated functional organization involving areas of the visuo-attentional networks of both jugglers was observed in both frequency bands and for the easier task only. Discussion These results suggest that cooperative juggling is supported by integrated activity of specialized cortical areas from both brains only during easier tasks, whereas it relies on individual skills, mirrored in uncorrelated individual brain activations, during more difficult tasks. These findings suggest that task difficulty and jugglers’ personal skills may influence the features of the hyperbrain network in its shared/integrative and complementary/segregative tendencies. PMID:27688968

Virtual reality and consciousness inference in dreaming

PubMed Central

Hobson, J. Allan; Hong, Charles C.-H.; Friston, Karl J.

2014-01-01

This article explores the notion that the brain is genetically endowed with an innate virtual reality generator that – through experience-dependent plasticity – becomes a generative or predictive model of the world. This model, which is most clearly revealed in rapid eye movement (REM) sleep dreaming, may provide the theater for conscious experience. Functional neuroimaging evidence for brain activations that are time-locked to rapid eye movements (REMs) endorses the view that waking consciousness emerges from REM sleep – and dreaming lays the foundations for waking perception. In this view, the brain is equipped with a virtual model of the world that generates predictions of its sensations. This model is continually updated and entrained by sensory prediction errors in wakefulness to ensure veridical perception, but not in dreaming. In contrast, dreaming plays an essential role in maintaining and enhancing the capacity to model the world by minimizing model complexity and thereby maximizing both statistical and thermodynamic efficiency. This perspective suggests that consciousness corresponds to the embodied process of inference, realized through the generation of virtual realities (in both sleep and wakefulness). In short, our premise or hypothesis is that the waking brain engages with the world to predict the causes of sensations, while in sleep the brain’s generative model is actively refined so that it generates more efficient predictions during waking. We review the evidence in support of this hypothesis – evidence that grounds consciousness in biophysical computations whose neuronal and neurochemical infrastructure has been disclosed by sleep research. PMID:25346710

Small-World Network Spectra in Mean-Field Theory

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc

2012-05-01

Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean-field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering, and social science.

Alternations of White Matter Structural Networks in First Episode Untreated Major Depressive Disorder with Short Duration.

PubMed

Lu, Yi; Shen, Zonglin; Cheng, Yuqi; Yang, Hui; He, Bo; Xie, Yue; Wen, Liang; Zhang, Zhenguang; Sun, Xuejin; Zhao, Wei; Xu, Xiufeng; Han, Dan

2017-01-01

It is crucial to explore the pathogenesis of major depressive disorder (MDD) at the early stage for the better diagnostic and treatment strategies. It was suggested that MDD might be involving in functional or structural alternations at the brain network level. However, at the onset of MDD, whether the whole brain white matter (WM) alterations at network level are already evident still remains unclear. In the present study, diffusion MRI scanning was adopt to depict the unique WM structural network topology across the entire brain at the early stage of MDD. Twenty-one first episode, short duration (<1 year) and drug-naïve depression patients, and 25 healthy control (HC) subjects were recruited. To construct the WM structural network, atlas-based brain regions were used for nodes, and the value of multiplying fiber number by the mean fractional anisotropy along the fiber bundles connected a pair of brain regions were used for edges. The structural network was analyzed by graph theoretic and network-based statistic methods. Pearson partial correlation analysis was also performed to evaluate their correlation with the clinical variables. Compared with HCs, the MDD patients had a significant decrease in the small-worldness (σ). Meanwhile, the MDD patients presented a significantly decreased subnetwork, which mainly involved in the frontal-subcortical and limbic regions. Our results suggested that the abnormal structural network of the orbitofrontal cortex and thalamus, involving the imbalance with the limbic system, might be a key pathology in early stage drug-naive depression. And the structural network analysis might be potential in early detection and diagnosis of MDD.

Alternations of White Matter Structural Networks in First Episode Untreated Major Depressive Disorder with Short Duration

PubMed Central

Lu, Yi; Shen, Zonglin; Cheng, Yuqi; Yang, Hui; He, Bo; Xie, Yue; Wen, Liang; Zhang, Zhenguang; Sun, Xuejin; Zhao, Wei; Xu, Xiufeng; Han, Dan

2017-01-01

It is crucial to explore the pathogenesis of major depressive disorder (MDD) at the early stage for the better diagnostic and treatment strategies. It was suggested that MDD might be involving in functional or structural alternations at the brain network level. However, at the onset of MDD, whether the whole brain white matter (WM) alterations at network level are already evident still remains unclear. In the present study, diffusion MRI scanning was adopt to depict the unique WM structural network topology across the entire brain at the early stage of MDD. Twenty-one first episode, short duration (<1 year) and drug-naïve depression patients, and 25 healthy control (HC) subjects were recruited. To construct the WM structural network, atlas-based brain regions were used for nodes, and the value of multiplying fiber number by the mean fractional anisotropy along the fiber bundles connected a pair of brain regions were used for edges. The structural network was analyzed by graph theoretic and network-based statistic methods. Pearson partial correlation analysis was also performed to evaluate their correlation with the clinical variables. Compared with HCs, the MDD patients had a significant decrease in the small-worldness (σ). Meanwhile, the MDD patients presented a significantly decreased subnetwork, which mainly involved in the frontal–subcortical and limbic regions. Our results suggested that the abnormal structural network of the orbitofrontal cortex and thalamus, involving the imbalance with the limbic system, might be a key pathology in early stage drug-naive depression. And the structural network analysis might be potential in early detection and diagnosis of MDD. PMID:29118724

Time-dependence of graph theory metrics in functional connectivity analysis

PubMed Central

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.

2016-01-01

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632

Time-dependence of graph theory metrics in functional connectivity analysis.

PubMed

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

2016-01-15

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The development of functional network organization in early childhood and early adolescence: A resting-state fNIRS study.

PubMed

Cai, Lin; Dong, Qi; Niu, Haijing

2018-04-01

Early childhood (7-8 years old) and early adolescence (11-12 years old) constitute two landmark developmental stages that comprise considerable changes in neural cognition. However, very limited information from functional neuroimaging studies exists on the functional topological configuration of the human brain during specific developmental periods. In the present study, we utilized continuous resting-state functional near-infrared spectroscopy (rs-fNIRS) imaging data to examine topological changes in network organization during development from early childhood and early adolescence to adulthood. Our results showed that the properties of small-worldness and modularity were not significantly different across development, demonstrating the developmental maturity of important functional brain organization in early childhood. Intriguingly, young children had a significantly lower global efficiency than early adolescents and adults, which revealed that the integration of the distributed networks strengthens across the developmental stages underlying cognitive development. Moreover, local efficiency of young children and adolescents was significantly lower than that of adults, while there was no difference between these two younger groups. This finding demonstrated that functional segregation remained relatively steady from early childhood to early adolescence, and the brain in these developmental periods possesses no optimal network configuration. Furthermore, we found heterogeneous developmental patterns in the regional nodal properties in various brain regions, such as linear increased nodal properties in the frontal cortex, indicating increasing cognitive capacity over development. Collectively, our results demonstrated that significant topological changes in functional network organization occurred during these two critical developmental stages, and provided a novel insight into elucidating subtle changes in brain functional networks across development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Using Naturalistic Methods to Examine Real-World Driving Behavior in Individuals With TBI Upon Return to Driving: A Pilot Study.

PubMed

Hua, Phuong; Charlton, Judith L; Ponsford, Jennie L; Gooden, James R; Ross, Pamela E; Bédard, Michel; Marshall, Shawn; Gagnon, Sylvain; Stolwyk, Renerus J

2018-05-31

To characterize the real-world driving habits of individuals with traumatic brain injury (TBI) using naturalistic methods and to demonstrate the feasibility of such methods in exploring return to driving after TBI. After passing an on-road driving assessment, 8 participants with TBI and 23 matched controls had an in-vehicle device installed to record information regarding their driving patterns (distance, duration, and start/end times) for 90 days. The overall number of trips, distance and duration or percentage of trips during peak hour, above 15 km from home or on freeways/highways did not differ between groups. However, the TBI group drove significantly less at night, and more during the daytime, than controls. Exploratory analyses using geographic information system (GIS) also demonstrated significant within-group heterogeneity for the TBI group in terms of location of travel. The TBI and control groups were largely comparable in terms of driving exposure, except for when they drove, which may indicate small group differences in driving self-regulatory practices. However, the GIS evidence suggests driving patterns within the TBI group were heterogeneous. These findings provide evidence for the feasibility of employing noninvasive in-car recording devices to explore real-world driving behavior post-TBI.

Brain Aneurysm

MedlinePlus

A brain aneurysm is an abnormal bulge or "ballooning" in the wall of an artery in the brain. They are sometimes called berry aneurysms because they ... often the size of a small berry. Most brain aneurysms produce no symptoms until they become large, ...

Emerging Trends in the Management of Brain Metastases from Non-small Cell Lung Cancer.

PubMed

Churilla, Thomas M; Weiss, Stephanie E

2018-05-07

To summarize current approaches in the management of brain metastases from non-small cell lung cancer (NSCLC). Local treatment has evolved from whole-brain radiotherapy (WBRT) to increasing use of stereotactic radiosurgery (SRS) alone for patients with limited (1-4) brain metastases. Trials have established post-operative SRS as an alternative to adjuvant WBRT following resection of brain metastases. Second-generation TKIs for ALK rearranged NSCLC have demonstrated improved CNS penetration and activity. Current brain metastasis trials are focused on reducing cognitive toxicity: hippocampal sparing WBRT, SRS for 5-15 metastases, pre-operative SRS, and use of systemic targeted agents or immunotherapy. The role for radiotherapy in the management of brain metastases is becoming better defined with local treatment shifting from WBRT to SRS alone for limited brain metastases and post-operative SRS for resected metastases. Further trials are warranted to define the optimal integration of newer systemic agents with local therapies.

Lacunar infarction and small vessel disease: pathology and pathophysiology.

PubMed

Caplan, Louis R

2015-01-01

Two major vascular pathologies underlie brain damage in patients with disease of small size penetrating brain arteries and arterioles; 1) thickening of the arterial media and 2) obstruction of the origins of penetrating arteries by parent artery intimal plaques. The media of these small vessels may be thickened by fibrinoid deposition and hypertrophy of smooth muscle and other connective tissue elements that accompanies degenerative changes in patients with hypertension and or diabetes or can contain foreign deposits as in amyloid angiopathy and genetically mediated conditions such as cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. These pathological changes lead to 2 different pathophysiologies: 1) brain ischemia in regions supplied by the affected arteries. The resultant lesions are deep small infarcts, most often involving the basal ganglia, pons, thalami and cerebral white matter. And 2) leakage of fluid causing edema and later gliosis in white matter tracts. The changes in the media and adventitia effect metalloproteinases and other substances within the matrix of the vessels and lead to abnormal blood/brain barriers in these small vessels. and chronic gliosis and atrophy of cerebral white matter.

Six Degrees of Information Seeking: Stanley Milgram and the Small World of the Library

ERIC Educational Resources Information Center

James, Kathryn

2006-01-01

Stanley Milgram's 1967 "small world" social connectivity study is used to analyze information connectivity, or patron information-seeking behavior. The "small world" study, upon examination, offers a clear example of the failure of social connectivity. This failure is used to highlight the importance of the subjectivities of patron experience of…

Alkmaion's discovery that brain creates mind: a revolution in human knowledge comparable to that of Copernicus and of Darwin.

PubMed

Doty, Robert W

2007-07-13

Without special examination the brain offers no clue that it is the organ of the mind. From the dawn of time man thus either ignored the problem as to the source of thought, or attributed it to a variety of anatomical structures, usually the heart. The brain held no place in such intuitions, and in most languages it is analogized to bone marrow. Furthermore, nothing in early medical systems claimed any intellectual capacity for the brain; and the Egyptians, so fastidious in care for their afterlife, heedlessly discarded the brain in funerary practice. It was thus a unique event in world history when Alkmaion of Kroton (Alcmaeon, ca. 500 bc), based on anatomical evidence, proposed that the brain was essential for perception. Although no writings of Alkmaion survived, it was probably via a fortuitous linkage that his idea of the mental primacy of the brain was transmitted to, and preserved within, the teachings of the Hippocratic school. Nothing, of course, was secure as to mechanism, two millennia unfolding until the search for mind passed from the ventricles to the cerebral cortex. Nonetheless, Alkmaion was the beginning, and the ensuing understanding that he initiated is still transforming humanity's perception of the natural world, and their place within it.

Natural Learning for a Connected World: Education, Technology, and the Human Brain

ERIC Educational Resources Information Center

Caine, Renate N.; Caine, Geoffrey

2011-01-01

Why do video games fascinate kids so much that they will spend hours pursuing a difficult skill? Why don't they apply this kind of intensity to their schoolwork? These questions are answered by the authors who pioneered brain/mind learning with the publication of "Making Connections: Teaching and the Human Brain". In their new book, "Natural…

Cognitive world: Neuropsychology of individual differences.

PubMed

Ardila, Alfredo; Rosselli, Monica

2018-01-01

It is proposed that depending upon the specific pattern of cognitive abilities, each individual lives in an idiosyncratic "cognitive world." Brain pathology can be associated with some disturbed abilities, and frequently experiential changes (i.e., how the world is understood) are observed. Because these patients often are aware of their intellectual changes, they may represent excellent models to illustrate the diversity of cognitive interpretations an individual can have about the surrounding environmental conditions. Four neuropsychology cases are presented to illustrate this point: (a) prosopagnosia associated with spatial agnosia; (b) Gerstmann's syndrome; (c) dysexecutive syndrome due to a head injury; and, (d) patient with Capgras' syndrome associated with a left temporal cyst. It is further emphasized that non-brain damaged people present an enormous-but usually overlooked-dispersion in different cognitive domains, resulting in specific and idiosyncratic patterns of cognitive abilities. It is concluded that the concept of "cognitive world" in neuropsychology can parallel the concept of "perceptual world" introduced by von Uexküll in biology, which assumes that different animal species live in idiosyncratic perceptual worlds, available and knowable by the differences in their sensory system abilities. That is, different individuals live in idiosyncratic cognitive worlds, owing to their differences in cognitive abilities.

Structural network alterations and neurological dysfunction in cerebral amyloid angiopathy

PubMed Central

Reijmer, Yael D.; Fotiadis, Panagiotis; Martinez-Ramirez, Sergi; Salat, David H.; Schultz, Aaron; Shoamanesh, Ashkan; Ayres, Alison M.; Vashkevich, Anastasia; Rosas, Diana; Schwab, Kristin; Leemans, Alexander; Biessels, Geert-Jan; Rosand, Jonathan; Johnson, Keith A.; Viswanathan, Anand; Gurol, M. Edip

2015-01-01

Cerebral amyloid angiopathy is a common form of small-vessel disease and an important risk factor for cognitive impairment. The mechanisms linking small-vessel disease to cognitive impairment are not well understood. We hypothesized that in patients with cerebral amyloid angiopathy, multiple small spatially distributed lesions affect cognition through disruption of brain connectivity. We therefore compared the structural brain network in patients with cerebral amyloid angiopathy to healthy control subjects and examined the relationship between markers of cerebral amyloid angiopathy-related brain injury, network efficiency, and potential clinical consequences. Structural brain networks were reconstructed from diffusion-weighted magnetic resonance imaging in 38 non-demented patients with probable cerebral amyloid angiopathy (69 ± 10 years) and 29 similar aged control participants. The efficiency of the brain network was characterized using graph theory and brain amyloid deposition was quantified by Pittsburgh compound B retention on positron emission tomography imaging. Global efficiency of the brain network was reduced in patients compared to controls (0.187 ± 0.018 and 0.201 ± 0.015, respectively, P < 0.001). Network disturbances were most pronounced in the occipital, parietal, and posterior temporal lobes. Among patients, lower global network efficiency was related to higher cortical amyloid load (r = −0.52; P = 0.004), and to magnetic resonance imaging markers of small-vessel disease including increased white matter hyperintensity volume (P < 0.001), lower total brain volume (P = 0.02), and number of microbleeds (trend P = 0.06). Lower global network efficiency was also related to worse performance on tests of processing speed (r = 0.58, P < 0.001), executive functioning (r = 0.54, P = 0.001), gait velocity (r = 0.41, P = 0.02), but not memory. Correlations with cognition were independent of age, sex, education level, and other magnetic resonance imaging markers of small-vessel disease. These findings suggest that reduced structural brain network efficiency might mediate the relationship between advanced cerebral amyloid angiopathy and neurologic dysfunction and that such large-scale brain network measures may represent useful outcome markers for tracking disease progression. PMID:25367025

Usability of World Health Organization Disability Assessment Schedule in chronic traumatic brain injury.

PubMed

Tarvonen-Schröder, Sinikka; Tenovuo, Olli; Kaljonen, Anne; Laimi, Katri

2018-06-15

To investigate functioning measured with the 12-item World Health Organization Disability Assessment Schedule (WHODAS 2.0) in patients with mild, moderate and severe traumatic brain injury, and to compare patients' experiences with assessments made by their significant others and by consultant neurologists. A total of 112 consecutive patients with traumatic brain injury (29 mild, 43 moderate, 40 severe) and their significant others completed a 12-item WHODAS 2.0 survey. A neurologist assessed functioning with the International Classification of Functioning, Disability and Health minimal generic set. The total patient and proxy WHODAS 2.0 sum score was rated as severe, and impairments in household tasks, learning, community life, emotional functions, concentrating, dealing with strangers, maintaining friendships, and working ability as around moderate in all 3 severity groups. In standing, walking, washing, and dressing oneself the reported impairments increased from mild in mild traumatic brain injury to moderate in severe traumatic brain injury. A neurologist rated the overall functioning, working ability, and motor activities most impaired in severe traumatic brain injury, while there were no between-group differences in energy and drive functions and emotional functions. Patients with chronic traumatic brain injury perceive a diversity of significant difficulties in activities and participation irrespective of the severity of the injury. We recommend assessing disability in traumatic brain injury with the short and understandable WHODAS 2.0 scale, when planning client-oriented services.

Aggression in Women: Behavior, Brain and Hormones

PubMed Central

Denson, Thomas F.; O’Dean, Siobhan M.; Blake, Khandis R.; Beames, Joanne R.

2018-01-01

We review the literature on aggression in women with an emphasis on laboratory experimentation and hormonal and brain mechanisms. Women tend to engage in more indirect forms of aggression (e.g., spreading rumors) than other types of aggression. In laboratory studies, women are less aggressive than men, but provocation attenuates this difference. In the real world, women are just as likely to aggress against their romantic partner as men are, but men cause more serious physical and psychological harm. A very small minority of women are also sexually violent. Women are susceptible to alcohol-related aggression, but this type of aggression may be limited to women high in trait aggression. Fear of being harmed is a robust inhibitor of direct aggression in women. There are too few studies and most are underpowered to detect unique neural mechanisms associated with aggression in women. Testosterone shows the same small, positive relationship with aggression in women as in men. The role of cortisol is unclear, although some evidence suggests that women who are high in testosterone and low in cortisol show heightened aggression. Under some circumstances, oxytocin may increase aggression by enhancing reactivity to provocation and simultaneously lowering perceptions of danger that normally inhibit many women from retaliating. There is some evidence that high levels of estradiol and progesterone are associated with low levels of aggression. We highlight that more gender-specific theory-driven hypothesis testing is needed with larger samples of women and aggression paradigms relevant to women. PMID:29770113

Epidemiological Characteristics, EGFR Status and Management Patterns of Advanced Non-small Cell Lung Cancer Patients: The Greek REASON Observational Registry Study.

PubMed

Syrigos, Konstantinos N; Georgoulias, Vasilis; Zarogoulidis, Konstantinos; Makrantonakis, Paris; Charpidou, Andriani; Christodoulou, Christos

2018-06-01

Real-world evidence regarding the prevalence of epidermal growth factor receptor (EGFR) mutation-positive status (M+) and the clinicopathological characteristics associated with the presence of EGFR mutations in advanced non-small cell lung cancer (NSCLC) is scarce, especially among Caucasian populations. The present study aimed to bridge this gap, as well as to record treatment patterns and outcomes in routine-care settings. REASON (NCT01153399) was a prospective study of patients with stage IIIB/IV NSCLC and known EGFR mutation status. Clinicopathological, treatment characteristics and clinical outcomes were recorded and correlated with EGFR mutation testing results. Of 575 enrolled patients, EGFR mutations were detected in 15.7% of them. Male gender (p=0.008) and smoking (p<0.001), but not adenocarcinoma, were associated with EGFR M+ status. In the EGFR M+ subpopulation (n=88), absence of bone and/or brain metastasis and presence of exon 19 EGFR M+ status at diagnosis were independently associated with longer progression-free survival (PFS) (p=0.011 and p=0.040, respectively). In our population, males and smokers had decreased odds of harboring an EGFR mutation, while adenocarcinoma histology was not a significant predictor of EGFR M+ status. EGFR M+ patients with bone and/or brain metastases at diagnosis or mutations other than exon 19 deletions were at increased risk for earlier disease progression. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Aggression in Women: Behavior, Brain and Hormones.

PubMed

Denson, Thomas F; O'Dean, Siobhan M; Blake, Khandis R; Beames, Joanne R

2018-01-01

We review the literature on aggression in women with an emphasis on laboratory experimentation and hormonal and brain mechanisms. Women tend to engage in more indirect forms of aggression (e.g., spreading rumors) than other types of aggression. In laboratory studies, women are less aggressive than men, but provocation attenuates this difference. In the real world, women are just as likely to aggress against their romantic partner as men are, but men cause more serious physical and psychological harm. A very small minority of women are also sexually violent. Women are susceptible to alcohol-related aggression, but this type of aggression may be limited to women high in trait aggression. Fear of being harmed is a robust inhibitor of direct aggression in women. There are too few studies and most are underpowered to detect unique neural mechanisms associated with aggression in women. Testosterone shows the same small, positive relationship with aggression in women as in men. The role of cortisol is unclear, although some evidence suggests that women who are high in testosterone and low in cortisol show heightened aggression. Under some circumstances, oxytocin may increase aggression by enhancing reactivity to provocation and simultaneously lowering perceptions of danger that normally inhibit many women from retaliating. There is some evidence that high levels of estradiol and progesterone are associated with low levels of aggression. We highlight that more gender-specific theory-driven hypothesis testing is needed with larger samples of women and aggression paradigms relevant to women.

On the relation between the small world structure and scientific activities.

PubMed

Ebadi, Ashkan; Schiffauerova, Andrea

2015-01-01

The modern science has become more complex and interdisciplinary in its nature which might encourage researchers to be more collaborative and get engaged in larger collaboration networks. Various aspects of collaboration networks have been examined so far to detect the most determinant factors in knowledge creation and scientific production. One of the network structures that recently attracted much theoretical attention is called small world. It has been suggested that small world can improve the information transmission among the network actors. In this paper, using the data on 12 periods of journal publications of Canadian researchers in natural sciences and engineering, the co-authorship networks of the researchers are created. Through measuring small world indicators, the small worldiness of the mentioned network and its relation with researchers' productivity, quality of their publications, and scientific team size are assessed. Our results show that the examined co-authorship network strictly exhibits the small world properties. In addition, it is suggested that in a small world network researchers expand their team size through getting connected to other experts of the field. This team size expansion may result in higher productivity of the whole team as a result of getting access to new resources, benefitting from the internal referring, and exchanging ideas among the team members. Moreover, although small world network is positively correlated with the quality of the articles in terms of both citation count and journal impact factor, it is negatively related with the average productivity of researchers in terms of the number of their publications.

On the Relation between the Small World Structure and Scientific Activities

PubMed Central

Ebadi, Ashkan; Schiffauerova, Andrea

2015-01-01

The modern science has become more complex and interdisciplinary in its nature which might encourage researchers to be more collaborative and get engaged in larger collaboration networks. Various aspects of collaboration networks have been examined so far to detect the most determinant factors in knowledge creation and scientific production. One of the network structures that recently attracted much theoretical attention is called small world. It has been suggested that small world can improve the information transmission among the network actors. In this paper, using the data on 12 periods of journal publications of Canadian researchers in natural sciences and engineering, the co-authorship networks of the researchers are created. Through measuring small world indicators, the small worldiness of the mentioned network and its relation with researchers’ productivity, quality of their publications, and scientific team size are assessed. Our results show that the examined co-authorship network strictly exhibits the small world properties. In addition, it is suggested that in a small world network researchers expand their team size through getting connected to other experts of the field. This team size expansion may result in higher productivity of the whole team as a result of getting access to new resources, benefitting from the internal referring, and exchanging ideas among the team members. Moreover, although small world network is positively correlated with the quality of the articles in terms of both citation count and journal impact factor, it is negatively related with the average productivity of researchers in terms of the number of their publications. PMID:25780922

Cogito.org: A Website and Online Community for the World's Most Talented Youth

ERIC Educational Resources Information Center

Brody, Linda E.

2008-01-01

Students have used Cogito.org to pose and/or solve math problems and brain teasers, share their experiences in academic competitions, debate the pros and cons of using biofuels for energy, design an alien world based on sound scientific principles, and expand their cultural understanding by connecting with students from around the world.…

Iron Deficiency's Long-Term Effects: An Interview with Pediatrician Betsy Lozoff

ERIC Educational Resources Information Center

National Scientific Council on the Developing Child, 2006

2006-01-01

Betsy Lozoff is among the world's leading experts on iron deficiency and its effects on infant brain development and behavior. Iron deficiency is the most common single nutrient disorder in the world, affecting more than half of the world's infants and young children. Research by Lozoff and others has shown that there are long-lasting…

Investigating the effects of visual distractors on the performance of a motor imagery brain-computer interface.

PubMed

Emami, Zahra; Chau, Tom

2018-06-01

Brain-computer interfaces (BCIs) allow users to operate a device or application by means of cognitive activity. This technology will ultimately be used in real-world environments which include the presence of distractors. The purpose of the study was to determine the effect of visual distractors on BCI performance. Sixteen able-bodied participants underwent neurofeedback training to achieve motor imagery-guided BCI control in an online paradigm using electroencephalography (EEG) to measure neural signals. Participants then completed two sessions of the motor imagery EEG-BCI protocol in the presence of infrequent, small visual distractors. BCI performance was determined based on classification accuracy. The presence of distractors was found to affect motor imagery-specific patterns in mu and beta power. However, the distractors did not significantly affect the BCI classification accuracy; across participants, the mean classification accuracy was 81.5 ± 14% for non-distractor trials, and 78.3 ± 17% for distractor trials. This minimal consequence suggests that the BCI was robust to distractor effects, despite motor imagery-related brain activity being attenuated amid distractors. A BCI system that mitigates distraction-related effects may improve the ease of its use and ultimately facilitate the effective translation of the technology from the lab to the home. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Identification and classification of hubs in brain networks.

PubMed

Sporns, Olaf; Honey, Christopher J; Kötter, Rolf

2007-10-17

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.

A functional magnetic resonance imaging assessment of small animals' phobia using virtual reality as a stimulus.

PubMed

Clemente, Miriam; Rey, Beatriz; Rodriguez-Pujadas, Aina; Breton-Lopez, Juani; Barros-Loscertales, Alfonso; Baños, Rosa M; Botella, Cristina; Alcañiz, Mariano; Avila, Cesar

2014-06-27

To date, still images or videos of real animals have been used in functional magnetic resonance imaging protocols to evaluate the brain activations associated with small animals' phobia. The objective of our study was to evaluate the brain activations associated with small animals' phobia through the use of virtual environments. This context will have the added benefit of allowing the subject to move and interact with the environment, giving the subject the illusion of being there. We have analyzed the brain activation in a group of phobic people while they navigated in a virtual environment that included the small animals that were the object of their phobia. We have found brain activation mainly in the left occipital inferior lobe (P<.05 corrected, cluster size=36), related to the enhanced visual attention to the phobic stimuli; and in the superior frontal gyrus (P<.005 uncorrected, cluster size=13), which is an area that has been previously related to the feeling of self-awareness. In our opinion, these results demonstrate that virtual stimulus can enhance brain activations consistent with previous studies with still images, but in an environment closer to the real situation the subject would face in their daily lives.

A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.

Egocentric and allocentric representations in auditory cortex

PubMed Central

Brimijoin, W. Owen; Bizley, Jennifer K.

2017-01-01

A key function of the brain is to provide a stable representation of an object’s location in the world. In hearing, sound azimuth and elevation are encoded by neurons throughout the auditory system, and auditory cortex is necessary for sound localization. However, the coordinate frame in which neurons represent sound space remains undefined: classical spatial receptive fields in head-fixed subjects can be explained either by sensitivity to sound source location relative to the head (egocentric) or relative to the world (allocentric encoding). This coordinate frame ambiguity can be resolved by studying freely moving subjects; here we recorded spatial receptive fields in the auditory cortex of freely moving ferrets. We found that most spatially tuned neurons represented sound source location relative to the head across changes in head position and direction. In addition, we also recorded a small number of neurons in which sound location was represented in a world-centered coordinate frame. We used measurements of spatial tuning across changes in head position and direction to explore the influence of sound source distance and speed of head movement on auditory cortical activity and spatial tuning. Modulation depth of spatial tuning increased with distance for egocentric but not allocentric units, whereas, for both populations, modulation was stronger at faster movement speeds. Our findings suggest that early auditory cortex primarily represents sound source location relative to ourselves but that a minority of cells can represent sound location in the world independent of our own position. PMID:28617796

Emergence of Rich-Club Topology and Coordinated Dynamics in Development of Hippocampal Functional Networks In Vitro

PubMed Central

Charlesworth, Paul; Kitzbichler, Manfred G.; Paulsen, Ole

2015-01-01

Recent studies demonstrated that the anatomical network of the human brain shows a “rich-club” organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called “hub neurons”). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a “rich-get-richer” growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. PMID:25855164

Cognitive performance in mid-stage Parkinson's disease: functional connectivity under chronic antiparkinson treatment.

PubMed

Vancea, Roxana; Simonyan, Kristina; Petracca, Maria; Brys, Miroslaw; Di Rocco, Alessandro; Ghilardi, Maria Felice; Inglese, Matilde

2017-09-23

Cognitive impairment in Parkinson's disease (PD) is related to the reorganization of brain topology. Although drug challenge studies have proven how levodopa treatment can modulate functional connectivity in brain circuits, the role of chronic dopaminergic therapy on cognitive status and functional connectivity has never been investigated. We sought to characterize brain functional topology in mid-stage PD patients under chronic antiparkinson treatment and explore the presence of correlation between reorganization of brain architecture and specific cognitive deficits. We explored networks topology and functional connectivity in 16 patients with PD and 16 matched controls through a graph theoretical analysis of resting state-functional MRI data, and evaluated the relationships between network metrics and cognitive performance. PD patients showed a preserved small-world network topology but a lower clustering coefficient in comparison with healthy controls. Locally, PD patients showed lower degree of connectivity and local efficiency in many hubs corresponding to functionally relevant areas. Four disconnected subnetworks were also identified in regions responsible for executive control, sensory-motor control and planning, motor coordination and visual elaboration. Executive functions and information processing speed were directly correlated with degree of connectivity and local efficiency in frontal, parietal and occipital areas. While functional reorganization appears in both motor and cognitive areas, the clinical expression of network imbalance seems to be partially compensated by the chronic levodopa treatment with regards to the motor but not to the cognitive performance. In a context of reduced network segregation, the presence of higher local efficiency in hubs regions correlates with a better cognitive performance.

Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

PubMed

Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

2016-02-01

Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

Altered gray matter organization in children and adolescents with ADHD: a structural covariance connectome study

PubMed Central

Griffiths, K R; Grieve, S M; Kohn, M R; Clarke, S; Williams, L M; Korgaonkar, M S

2016-01-01

Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome. PMID:27824356

Bevacizumab Plus Radiosurgery for Nonsquamous Non-Small Cell Lung Cancer Patients with Brain Metastases: Safe Combination?

PubMed

Guinde, Julien; Carron, Romain; Tomasini, Pascale; Greillier, Laurent; Régis, Jean; Barlesi, Fabrice

2017-11-01

In the context of bronchial cancers, the brain is one of the most frequent sites for metastases. Local treatments of these metastases have evolved and are often combined to obtain greater efficiency, while the main objective remains to reduce the symptoms. Radiosurgery is currently used as a primary option for patients harboring few numbers of small to middle-sized brain metastases. In nonsquamous non-small cell lung cancer (NSCLC), chemotherapy is often associated with bevacizumab. Our goal was to assess the safety of this early combination. Six patients with advanced nonsquamous NSCLC were treated with radiosurgery for the management of their brain metastases (n = 40), followed within <4 weeks by a treatment with bevacizumab. No systemic or cerebral adverse event of grade 3 (intratumoral or parenchymal hemorrhage) or unexpected toxicity secondary to bevacizumab has been indexed. Radiosurgery may be safely combined with bevacizumab quite early on for patients with nonsquamous NSCLC with brain metastases. Copyright © 2017 Elsevier Inc. All rights reserved.

Pulsed laser diode photoacoustic tomography (PLD-PAT) system for fast in vivo imaging of small animal brain

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Kalva, Sandeep Kumar; Moothanchery, Mohesh; Pramanik, Manojit

2017-03-01

In recent years, high-repetition rate pulsed laser diode (PLD) was used as an alternative to the Nd:YAG lasers for photoacoustic tomography (PAT). The use of PLD makes the overall PAT system, a low-cost, portable, and high frame rate imaging tool for preclinical applications. In this work, we will present a portable in vivo pulsed laser diode based photoacoustic tomography (PLD-PAT) system. The PLD is integrated inside a circular scanning geometry. The PLD can provide near-infrared ( 803 nm) pulses with pulse duration 136 ns, and pulse energy 1.4 mJ / pulse at 7 kHz repetition rate. The system will be demonstrated for in vivo fast imaging of small animal brain. To enhance the contrast of brain imaging, experiments will be carried out using contrast agents which have strong absorption around laser excitation wavelength. This low-cost, portable small animal brain imaging system could be very useful for brain tumor imaging and therapy.

Motor skill failure or flow-experience? Functional brain asymmetry and brain connectivity in elite and amateur table tennis players.

PubMed

Wolf, Sebastian; Brölz, Ellen; Keune, Philipp M; Wesa, Benjamin; Hautzinger, Martin; Birbaumer, Niels; Strehl, Ute

2015-02-01

Functional hemispheric asymmetry is assumed to constitute one underlying neurophysiological mechanism of flow-experience and skilled psycho-motor performance in table tennis athletes. We hypothesized that when initiating motor execution during motor imagery, elite table tennis players show higher right- than left-hemispheric temporal activity and stronger right temporal-premotor than left temporal-premotor theta coherence compared to amateurs. We additionally investigated, whether less pronounced left temporal cortical activity is associated with more world rank points and more flow-experience. To this aim, electroencephalographic data were recorded in 14 experts and 15 amateur table tennis players. Subjects watched videos of an opponent serving a ball and were instructed to imagine themselves responding with a specific table tennis stroke. Alpha asymmetry scores were calculated by subtracting left from right hemispheric 8-13 Hz alpha power. 4-7 Hz theta coherence was calculated between temporal (T3/T4) and premotor (Fz) cortex. Experts showed a significantly stronger shift towards lower relative left-temporal brain activity compared to amateurs and a significantly stronger right temporal-premotor coherence than amateurs. The shift towards lower relative left-temporal brain activity in experts was associated with more flow-experience and lower relative left temporal activity was correlated with more world rank points. The present findings suggest that skilled psycho-motor performance in elite table tennis players reflect less desynchronized brain activity at the left hemisphere and more coherent brain activity between fronto-temporal and premotor oscillations at the right hemisphere. This pattern probably reflect less interference of irrelevant communication of verbal-analytical with motor-control mechanisms which implies flow-experience and predict world rank in experts. Copyright © 2015 Elsevier B.V. All rights reserved.

Plumbing the brain drain.

PubMed Central

Saravia, Nancy Gore; Miranda, Juan Francisco

2004-01-01

Opportunity is the driving force of migration. Unsatisfied demands for higher education and skills, which have been created by the knowledge-based global economy, have generated unprecedented opportunities in knowledge-intensive service industries. These multi-trillion dollar industries include information, communication, finance, business, education and health. The leading industrialized nations are also the focal points of knowledge-intensive service industries and as such constitute centres of research and development activity that proactively draw in talented individuals worldwide through selective immigration policies, employment opportunities and targeted recruitment. Higher education is another major conduit of talent from less-developed countries to the centres of the knowledge-based global economy. Together career and educational opportunities drive "brain drain and recirculation". The departure of a large proportion of the most competent and innovative individuals from developing nations slows the achievement of the critical mass needed to generate the enabling context in which knowledge creation occurs. To favourably modify the asymmetric movement and distribution of global talent, developing countries must implement bold and creative strategies that are backed by national policies to: provide world-class educational opportunities, construct knowledge-based research and development industries, and sustainably finance the required investment for these strategies. Brazil, China and India have moved in this direction, offering world-class education in areas crucial to national development, such as biotechnology and information technology, paralleled by investments in research and development. As a result, only a small proportion of the most highly educated individuals migrate from these countries, and research and development opportunities employ national talent and even attract immigrants. PMID:15375451

Brain drain or links to the world: views on emigrants from Singapore.

PubMed

Yap, M T

1994-01-01

"This article will present a general picture of emigration and emigrants from Singapore, with specific references to Australia where the data permit. The first section presents some flow data on the magnitudes of emigration from Singapore.... It is necessary to place this outflow against the background of the constraints imposed by the country's small size. This is discussed in the second section, together with the economic policies and strategies adopted to overcome these constraints. The third section documents the public debate on emigration and the responses to the 'problem.' This is followed in the last section by a prognosis for the future, particularly with regard to the implications for Australia. The article ends with a discussion of the relationship between emigration and nation building, using Singapore as a case study." excerpt

Structurally Dynamic Spin Market Networks

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán

The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study.

PubMed

Sun, Yu; Lim, Julian; Dai, Zhongxiang; Wong, KianFoong; Taya, Fumihiko; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios

2017-05-15

Although rest breaks are commonly administered as a countermeasure to reduce mental fatigue and boost cognitive performance, the effects of taking a break on behavior are not consistent. Moreover, our understanding of the underlying neural mechanisms of rest breaks and how they modulate mental fatigue is still rudimentary. In this study, we investigated the effects of receiving a rest break on the topological properties of brain connectivity networks via a two-session experimental paradigm, in which one session comprised four successive blocks of a mentally demanding visual selective attention task (No-rest session), whereas the other contained a rest break between the second and third task blocks (Rest session). Functional brain networks were constructed using resting-state functional MRI data recorded from 20 healthy adults before and after the performance of the task blocks. Behaviorally, subjects displayed robust time-on-task (TOT) declines, as reflected by increasingly slower reaction time as the test progressed and lower post-task self-reported ratings of engagement. However, we did not find a significant effect on task performance due to administering a mid-task break. Compared to pre-task measurements, post-task functional brain networks demonstrated an overall decrease of optimal small-world properties together with lower global efficiency. Specifically, we found TOT-related reduced nodal efficiency in brain regions that mainly resided in the subcortical areas. More interestingly, a significant block-by-session interaction was revealed in local efficiency, attributing to a significant post-task decline in No-rest session and a preserved local efficiency when a mid-task break opportunity was introduced in the Rest session. Taken together, these findings augment our understanding of how the resting brain reorganizes following the accumulation of prolonged task, suggest dissociable processes between the neural mechanisms of fatigue and recovery, and provide some of the first quantitative insights into the cognitive neuroscience of work and rest. Copyright © 2017 Elsevier Inc. All rights reserved.

Pharmacokinetics of pericyte involvement in small-molecular drug transport across the blood-brain barrier.

PubMed

Mihajlica, Nebojsa; Betsholtz, Christer; Hammarlund-Udenaes, Margareta

2018-06-19

Pericytes are perivascular cells that play important roles in the regulation of the blood-brain barrier (BBB) properties. Pericyte-deficiency causes compromised BBB integrity and increase in permeability to different macromolecules mainly by upregulated transcytosis. The aim of the present study was to investigate pericyte involvement in the extent of small-molecular drug transport across the BBB. This was performed with five compounds: diazepam, digoxin, levofloxacin, oxycodone and paliperidone. Compounds were administered at low doses via subcutaneous injections as a cassette (simultaneously) to pericyte-deficient Pdgfb ret/ret mice and corresponding WT controls. Total drug partitioning across the BBB was calculated as the ratio of total drug exposures in brain tissue and plasma (K p,brain ). In addition, equilibrium dialysis experiments were performed to estimate unbound drug fractions in brain (f u,brain ) and plasma (f u,plasma ). This enabled estimation of unbound drug partitioning coefficients (K p,uu,brain ). The results indicated slight tendencies towards increase of total brain exposures in Pdgfb ret/ret mice as reflected in K p,brain values, which were within the 2-fold limit. Part of these differences could be explained by differences in plasma protein binding. No difference was found in brain tissue binding. The combined in vivo and in vitro data resulted in no differences in BBB transport in pericyte-deficiency, as described by similar K p,uu,brain values in Pdgfb ret/ret and control mice. In conclusion, these findings imply no influence of pericytes on the extent of BBB transport of small-molecular drugs, and suggest preserved BBB features relevant for handling of this type of molecules irrespective of pericyte presence at the brain endothelium. Copyright © 2018. Published by Elsevier B.V.

The integration processing of the visual and auditory information in videos of real-world events: an ERP study.

PubMed

Liu, Baolin; Wang, Zhongning; Jin, Zhixing

2009-09-11

In real life, the human brain usually receives information through visual and auditory channels and processes the multisensory information, but studies on the integration processing of the dynamic visual and auditory information are relatively few. In this paper, we have designed an experiment, where through the presentation of common scenario, real-world videos, with matched and mismatched actions (images) and sounds as stimuli, we aimed to study the integration processing of synchronized visual and auditory information in videos of real-world events in the human brain, through the use event-related potentials (ERPs) methods. Experimental results showed that videos of mismatched actions (images) and sounds would elicit a larger P400 as compared to videos of matched actions (images) and sounds. We believe that the P400 waveform might be related to the cognitive integration processing of mismatched multisensory information in the human brain. The results also indicated that synchronized multisensory information would interfere with each other, which would influence the results of the cognitive integration processing.

Cartoons and the Brain.

ERIC Educational Resources Information Center

Stouder, James A.

1979-01-01

This paper describes the mechanism of conceptual development by characterizing it as a cartooning process, which is a neurological mechanism which records a perceptual kind of sketch of the world in our brains. Its unique character, its biological basis, and its consequences for education are discussed. (Author/KC)

Incidence of Brain Metastases on Follow-up 18F-FDG PET/CT Scans of Non-Small Cell Lung Cancer Patients: Should We Include the Brain?

PubMed

Nia, Emily S; Garland, Linda L; Eshghi, Naghmehossadat; Nia, Benjamin B; Avery, Ryan J; Kuo, Phillip H

2017-09-01

The brain is the most common site of distant metastasis from lung cancer. Thus, MRI of the brain at initial staging is routinely performed, but if this examination is negative a follow-up examination is often not performed. This study evaluates the incidence of asymptomatic brain metastases in non-small cell lung cancer patients detected on follow-up 18 F-FDG PET/CT scans. Methods: In this Institutional Review Board-approved retrospective review, all vertex to thigh 18 F-FDG PET/CT scans in patients with all subtypes of lung cancer from August 2014 to August 2016 were reviewed. A total of 1,175 18 F-FDG PET/CT examinations in 363 patients were reviewed. Exclusion criteria included brain metastases on initial staging, histologic subtype of small-cell lung cancer, and no follow-up 18 F-FDG PET/CT examinations. After our exclusion criteria were applied, a total of 809 follow-up 18 F-FDG PET/CT scans in 227 patients were included in the final analysis. The original report of each 18 F-FDG PET/CT study was reviewed for the finding of brain metastasis. The finding of a new brain metastasis prompted a brain MRI, which was reviewed to determine the accuracy of the 18 F-FDG PET/CT. Results: Five of 227 patients with 809 follow-up 18 F-FDG PET/CT scans reviewed were found to have incidental brain metastases. The mean age of the patients with incidental brain metastasis was 68 y (range, 60-77 y). The mean time from initial diagnosis to time of detection of incidental brain metastasis was 36 mo (range, 15-66 mo). When MRI was used as the gold standard, our false-positive rate was zero. Conclusion: By including the entire head during follow-up 18 F-FDG PET/CT scans of patients with non-small cell lung cancer, brain metastases can be detected earlier while still asymptomatic. But, given the additional scan time, radiation, and low incidence of new brain metastases in asymptomatic patients, the cost-to-benefit ratio should be weighed by each institution. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Using Copula Distributions to Support More Accurate Imaging-Based Diagnostic Classifiers for Neuropsychiatric Disorders

PubMed Central

Bansal, Ravi; Hao, Xuejun; Liu, Jun; Peterson, Bradley S.

2014-01-01

Many investigators have tried to apply machine learning techniques to magnetic resonance images (MRIs) of the brain in order to diagnose neuropsychiatric disorders. Usually the number of brain imaging measures (such as measures of cortical thickness and measures of local surface morphology) derived from the MRIs (i.e., their dimensionality) has been large (e.g. >10) relative to the number of participants who provide the MRI data (<100). Sparse data in a high dimensional space increases the variability of the classification rules that machine learning algorithms generate, thereby limiting the validity, reproducibility, and generalizability of those classifiers. The accuracy and stability of the classifiers can improve significantly if the multivariate distributions of the imaging measures can be estimated accurately. To accurately estimate the multivariate distributions using sparse data, we propose to estimate first the univariate distributions of imaging data and then combine them using a Copula to generate more accurate estimates of their multivariate distributions. We then sample the estimated Copula distributions to generate dense sets of imaging measures and use those measures to train classifiers. We hypothesize that the dense sets of brain imaging measures will generate classifiers that are stable to variations in brain imaging measures, thereby improving the reproducibility, validity, and generalizability of diagnostic classification algorithms in imaging datasets from clinical populations. In our experiments, we used both computer-generated and real-world brain imaging datasets to assess the accuracy of multivariate Copula distributions in estimating the corresponding multivariate distributions of real-world imaging data. Our experiments showed that diagnostic classifiers generated using imaging measures sampled from the Copula were significantly more accurate and more reproducible than were the classifiers generated using either the real-world imaging measures or their multivariate Gaussian distributions. Thus, our findings demonstrate that estimated multivariate Copula distributions can generate dense sets of brain imaging measures that can in turn be used to train classifiers, and those classifiers are significantly more accurate and more reproducible than are those generated using real-world imaging measures alone. PMID:25093634

Brain/MINDS: brain-mapping project in Japan

PubMed Central

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-01-01

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872

Anatomy, technology, art, and culture: toward a realistic perspective of the brain.

PubMed

Cavalcanti, Daniel D; Feindel, William; Goodrich, James T; Dagi, T Forcht; Prestigiacomo, Charles J; Preul, Mark C

2009-09-01

In the 15th century, brain illustration began to change from a schematic system that involved scant objective rendering of the brain, to accurate depictions based on anatomical dissections that demanded significant artistic talent. Notable examples of this innovation are the drawings of Leonardo da Vinci (1498-1504), Andreas Vesalius' association with the bottega of Titian to produce the drawings of Vesalius' De humani corporis fabrica (1543), and Christopher Wren's illustrations for Thomas Willis' Cerebri Anatome (1664). These works appeared during the Renaissance and Age of Enlightenment, when advances in brain imaging, or really brain rendering, reflected not only the abilities and dedications of the artists, but also the influences of important cultural and scientific factors. Anatomy and human dissection became popular social phenomena as well as scholarly pursuits, linked with the world of the fine arts. The working philosophy of these artists involved active participation in both anatomical study and illustration, and the belief that their discoveries of the natural world could best be communicated by rendering them in objective form (that is, with realistic perspective). From their studies emerged the beginning of contemporary brain imaging. In this article, the authors examine how the brain began to be imaged in realism within a cultural and scientific milieu that witnessed the emergence of anatomical dissection, the geometry of linear perspective, and the closer confluence of art and science.

Childhood brain cancer and its psychosocial impact on survivors and their parents: A qualitative thematic synthesis.

PubMed

Woodgate, Roberta L; Tailor, Ketan; Yanofsky, Rochelle; Vanan, Magimairajan Issai

2016-02-01

The multiple late-effects experienced by survivors of childhood brain tumors, are not only a source of great distress for survivors, but also for their parents and siblings. The aim of this review is to systematically identify and synthesize qualitative evidence on how survivors of childhood brain tumors and their parents experience life after surviving childhood brain tumors. Based on literature search in seven databases, 10 qualitative studies, published between 2004 and 2014 were included. Surviving a childhood brain tumor was experienced as paradox for survivors and their parents. While parents and survivors celebrated making it through the cancer experience, they nonetheless encountered a world with loss and new challenges. In short, the experience of survival was a bittersweet experience for survivors and their parents. Survivors and their parents experienced change that included living with uncertainty, intensification of the parenting role, a changing social world, a different way of being, and the need for additional help. Results from this synthesis reinforce that surviving a childhood brain tumor should be viewed as a point on a continuum of living with a brain tumor. Psychosocial effects of surviving brain cancer affect the entire family unit. A need for psychosocial support is evident, although development of such supports necessitates a more full understanding of challenges face by the child affected, their parents, and siblings. The limitations noted in this synthesis reinforce that more qualitative research is needed in this subject area. Copyright © 2015 Elsevier Ltd. All rights reserved.

Movement: How the Brain Communicates with the World.

PubMed

Schwartz, Andrew B

2016-03-10

Voluntary movement is a result of signals transmitted through a communication channel that links the internal world in our minds to the physical world around us. Intention can be considered the desire to effect change on our environment, and this is contained in the signals from the brain, passed through the nervous system to converge on muscles that generate displacements and forces on our surroundings. The resulting changes in the world act to generate sensations that feed back to the nervous system, closing the control loop. This Perspective discusses the experimental and theoretical underpinnings of current models of movement generation and the way they are modulated by external information. Movement systems embody intentionality and prediction, two factors that are propelling a revolution in engineering. Development of movement models that include the complexities of the external world may allow a better understanding of the neuronal populations regulating these processes, as well as the development of solutions for autonomous vehicles and robots, and neural prostheses for those who are motor impaired. Copyright © 2016 Elsevier Inc. All rights reserved.

Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults.

PubMed

Ten Kate, Mara; Visser, Pieter Jelle; Bakardjian, Hovagim; Barkhof, Frederik; Sikkes, Sietske A M; van der Flier, Wiesje M; Scheltens, Philip; Hampel, Harald; Habert, Marie-Odile; Dubois, Bruno; Tijms, Betty M

2018-01-01

The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer's disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects ( n = 318, mean age 76.1 ± 3.5, 64% female, 28% amyloid positive). Degree, clustering, path length and small world properties were computed. Global and regional amyloid load was determined using [ 18 F]-Florbetapir PET. Associations between standardized uptake value ratio (SUVr) values and network measures were examined using linear regression models. We found that higher global SUVr was associated with lower clustering ( β = -0.12, p < 0.05), and small world values ( β = -0.16, p < 0.01). Associations were most prominent in orbito- and dorsolateral frontal and parieto-occipital regions. Local SUVr values showed less anatomical variability and did not convey additional information beyond global amyloid burden. In conclusion, we found that in cognitively normal elderly subjects, increased global amyloid pathology is associated with alterations in gray matter networks that are indicative of incipient network breakdown towards AD dementia.

2007 International Brain Mapping and Intraoperative Surgical Planning Society’s (IBMISPS) Annual World Congress

DTIC Science & Technology

2008-02-01

and Stroke Two Long Term Consequences of Penetrating Head Injuries : Exacerbated Decline and Post-Traumatic Stress Disorder Key Note speaker: Michael L...an intuitively obvious first principle that if modern medicine hopes to repair adult brains (damaged by war injuries , automobile accidents, stroke ...Imaging Animal Models of Brain Disease Background and Animal Model Quantization of Structure Cerebral Blood Flow Mini- Strokes Cancer Future

Belief in a just world is associated with activity in insula and somatosensory cortices as a response to the perception of norm violations.

PubMed

Denke, Claudia; Rotte, Michael; Heinze, Hans-Jochen; Schaefer, Michael

2014-01-01

Previous studies identified a network of brain regions involved in the perception of norm violations, including insula, anterior cingulate cortex (ACC), and right temporoparietal junction area (RTPJ). Activations in these regions are suggested to reflect the perception of norm violations and unfairness. The current study aimed to test this hypothesis by exploring whether a personal disposition to perceive the world as being just is related to neural responses to moral evaluations. The just-world-hypothesis describes a cognitive bias to believe in a just world in which everyone gets what he or she deserves and deserves what he or she gets. Since it has been demonstrated that ACC, RTPJ, and insula are involved in the perception of unfairness, we hypothesized that individual differences in the belief in a just world are reflected by different activations of these brain areas. Participants were confronted with scenarios describing norm-violating or -confirming behavior. FMRI results revealed an activation of dorsal ACC, RTPJ, and insula when perceiving norm violations, but only activity in insula/somatosensory cortex correlated with the belief in a just world. Thus, our results suggest a role for insula/somatosensory cortex for the belief in a just world.

Embodiment and Performance

ERIC Educational Resources Information Center

Bessell, Jacquelyn; Riddell, Patricia

2016-01-01

Evidence suggests that some cognitive processes are based on sensorimotor systems in the brain (embodied cognition). The premise of this is that "Biological brains are first and foremost the control systems for biological bodies". It has therefore been suggested that both online cognition (processing as we move through the world) and…

Small-world behaviour in a system of mobile elements

NASA Astrophysics Data System (ADS)

Manrubia, S. C.; Delgado, J.; Luque, B.

2001-03-01

We analyze the propagation of activity in a system of mobile automata. A number ρLd of elements move as random walkers on a lattice of dimension d, while with a small probability p they can jump to any empty site in the system. We show that this system behaves as a Dynamic Small World (DSW) and present analytic and numerical results for several quantities. Our analysis shows that the persistence time T* (equivalent to the persistence size L* of small-world networks) scales as T* ~ (ρp)-τ, with τ = 1/(d + 1).

Artificial selection on relative brain size in the guppy reveals costs and benefits of evolving a larger brain.

PubMed

Kotrschal, Alexander; Rogell, Björn; Bundsen, Andreas; Svensson, Beatrice; Zajitschek, Susanne; Brännström, Ioana; Immler, Simone; Maklakov, Alexei A; Kolm, Niclas

2013-01-21

The large variation in brain size that exists in the animal kingdom has been suggested to have evolved through the balance between selective advantages of greater cognitive ability and the prohibitively high energy demands of a larger brain (the "expensive-tissue hypothesis"). Despite over a century of research on the evolution of brain size, empirical support for the trade-off between cognitive ability and energetic costs is based exclusively on correlative evidence, and the theory remains controversial. Here we provide experimental evidence for costs and benefits of increased brain size. We used artificial selection for large and small brain size relative to body size in a live-bearing fish, the guppy (Poecilia reticulata), and found that relative brain size evolved rapidly in response to divergent selection in both sexes. Large-brained females outperformed small-brained females in a numerical learning assay designed to test cognitive ability. Moreover, large-brained lines, especially males, developed smaller guts, as predicted by the expensive-tissue hypothesis, and produced fewer offspring. We propose that the evolution of brain size is mediated by a functional trade-off between increased cognitive ability and reproductive performance and discuss the implications of these findings for vertebrate brain evolution. Copyright © 2013 Elsevier Ltd. All rights reserved.

Permeability and route of entry for lipid-insoluble molecules across brain barriers in developing Monodelphis domestica

PubMed Central

Ek, C Joakim; Habgood, Mark D; Dziegielewska, Katarzyna M; Potter, Ann; Saunders, Norman R

2001-01-01

We have studied the permeability of blood-brain barriers to small molecules such as [14C]sucrose, [3H]inulin, [14C]l-glucose and [3H]glycerol from early stages of development (postnatal day 6, P6) in South American opossums (Monodelphis domestica), using a litter-based method for estimating steady-state cerebrospinal fluid (CSF)/plasma and brain/plasma ratios of markers that were injected i.p.. Steady-state ratios for l-glucose, sucrose and inulin all showed progressive decreases during development. The rate of uptake of l-glucose into the brain and CSF, in short time course experiments (7–24 min) when age-related differences in CSF production can be considered negligible also decreased during development. These results indicate that there is a significant decrease in the permeability of brain barriers to small lipid-insoluble molecules during brain development. The steady-state blood/CSF ratio for 3000 Da lysine-fixable biotin-dextran following i.p. injection was shown to be consistent with diffusion from blood to CSF. It was therefore used to visualise the route of penetration for small lipid-insoluble molecules across brain barriers at P 0–30. The proportion of biotin-dextran-positive cells in the choroid plexuses declined in parallel with the age-related decline in permeability to the small-molecular-weight markers; the paracellular (tight junction) pathway for biotin-dextran appeared to be blocked, but biotin-dextran was easily detectable in the CSF. A transcellular route from blood to CSF was suggested by the finding that some choroid plexus epithelial cells contained biotin-dextran. Biotin-dextran was also taken up by cerebral endothelial cells in the youngest brains studied (P0), but in contrast to the CSF, could not be detected in the brain extracellular space (i.e. a significant blood-brain barrier to small-sized lipid-insoluble compounds was already present). However, in immature brains (P0–13) biotin-dextran was taken up by some cells in the brain. These cells generally had contact with the CSF, suggesting that it is likely to have been the 2source of their biotin-dextran. Since the quantitative permeability data suggest that biotin-dextran behaves similarly to the radiolabelled markers used in this study, it is suggested that these markers in the more immature brains were also present intracellularly. Thus, brain/plasma ratios may be a misleading indicator of blood-brain barrier permeability in very immature animals. The immunocytochemical staining for biotin-dextran in the CSF, in contrast to the lack of staining in the brain extracellular space, together with the quantitative permeability data showing that the radiolabelled markers penetrated more rapidly and to a much higher steady-state level in CSF than in the brain, suggests that lipid-insoluble molecules such as sucrose and inulin reach the immature brain predominantly via the CSF rather than directly across the very few blood vessels that are present at that time. PMID:11691876

[A study on the expression of anti-mitochondrial antibody in the brain of patients with MELAS syndrome].

PubMed

Qi, Xiao-Kun; Yao, Sheng; Wang, Hai-Yan; Piao, Yue-Shan; Lu, De-Hong; Yuan, Yun

2009-04-01

To investigate the pathological changes and pathogenesis of the MELAS syndrome (mitochondrial encephalopathy lactic acidosis stroke-like episodes) by using the method of immunohistochemical staining in the brain biopsy specimens with anti-mitochondrial antibody (AMA). We performed immunohistochemical staining in 3 confirmed MELAS patients' paraffin-imbued brain biopsy specimens. Small vessel proliferation and the uneven thickness of the wall were found in the 3 MELAS patients. A lot of brown deposits was shown in the wall of small vessels and also noted in neurons. The main pathological change in the MELAS brain biopsy immunohistochemical staining with AMA was the small vessel proliferation, indicating that abnormal mitochondria accumulated in the vascular smooth muscle, endothelial cell and neurons of the lesion sites. This finding was consistent with the electron microscopic discovery and valuable for the diagnosis of MELAS.

Brain anatomical networks in world class gymnasts: a DTI tractography study.

PubMed

Wang, Bin; Fan, Yuanyuan; Lu, Min; Li, Shumei; Song, Zheng; Peng, Xiaoling; Zhang, Ruibin; Lin, Qixiang; He, Yong; Wang, Jun; Huang, Ruiwang

2013-01-15

The excellent motor skills of world class gymnasts amaze everyone. People marvel at the way they precisely control their movements and wonder how the brain structure and function of these elite athletes differ from those of non-athletes. In this study, we acquired diffusion images from thirteen world class gymnasts and fourteen matched controls, constructed their anatomical networks, and calculated the topological properties of each network based on graph theory. From a connectivity-based analysis, we found that most of the edges with increased connection density in the champions were linked to brain regions that are located in the sensorimotor, attentional, and default-mode systems. From graph-based metrics, we detected significantly greater global and local efficiency but shorter characteristic path length in the anatomical networks of the champions compared with the controls. Moreover, in the champions we found a significantly higher nodal degree and greater regional efficiency in several brain regions that correspond to motor and attention functions. These included the left precentral gyrus, left postcentral gyrus, right anterior cingulate gyrus and temporal lobes. In addition, we revealed an increase in the mean fractional anisotropy of the corticospinal tract in the champions, possibly in response to long-term gymnastic training. Our study indicates that neuroanatomical adaptations and plastic changes occur in gymnasts' brain anatomical networks either in response to long-term intensive gymnastic training or as an innate predisposition or both. Our findings may help to explain gymnastic skills at the highest levels of performance and aid in understanding the neural mechanisms that distinguish expert gymnasts from novices. Copyright © 2012 Elsevier Inc. All rights reserved.

A Functional Magnetic Resonance Imaging Assessment of Small Animals’ Phobia Using Virtual Reality as a Stimulus

PubMed Central

Rey, Beatriz; Rodriguez-Pujadas, Aina; Breton-Lopez, Juani; Barros-Loscertales, Alfonso; Baños, Rosa M; Botella, Cristina; Alcañiz, Mariano; Avila, Cesar

2014-01-01

Background To date, still images or videos of real animals have been used in functional magnetic resonance imaging protocols to evaluate the brain activations associated with small animals’ phobia. Objective The objective of our study was to evaluate the brain activations associated with small animals’ phobia through the use of virtual environments. This context will have the added benefit of allowing the subject to move and interact with the environment, giving the subject the illusion of being there. Methods We have analyzed the brain activation in a group of phobic people while they navigated in a virtual environment that included the small animals that were the object of their phobia. Results We have found brain activation mainly in the left occipital inferior lobe (P<.05 corrected, cluster size=36), related to the enhanced visual attention to the phobic stimuli; and in the superior frontal gyrus (P<.005 uncorrected, cluster size=13), which is an area that has been previously related to the feeling of self-awareness. Conclusions In our opinion, these results demonstrate that virtual stimulus can enhance brain activations consistent with previous studies with still images, but in an environment closer to the real situation the subject would face in their daily lives. PMID:25654753

Cerebral volumetric asymmetries in non-human primates: A magnetic resonance imaging study

PubMed Central

Pilcher, Dawn L.; Hammock, Elizabeth A.D.; Hopkins, William D.

2007-01-01

Magnetic resonance images (MRI) were collected in a sample of 23 apes, 14 Old World monkeys, and 8 New World monkeys. The total area or volume of the anterior and posterior cerebral regions of each hemisphere of the brain was measured. The results indicated that a rightward frontal and leftward occipital pattern of asymmetry was present at a population level in the great ape sample. Population-level cerebral asymmetries were not revealed in the sample of New or Old World monkeys. The total area or volume of the planum temporale, which was localised only in the great apes, was also measured in both hemispheres. A leftward planum temporale asymmetry was evident at the population level in the great apes. It was hypothesised that the rightward frontal and leftward occipital asymmetries would correlate with leftward planum temporale asymmetries. This hypothesis was based on the assumption that, similar to development of the human brain, the non-human primate brain ‘‘torques’’ during development due to a growth gradient which progresses anterior to posterior, ventral to dorsal, and right to left. The results of this study confirmed the predicted relationship between cerebral volume and the planum temporale asymmetries. This supports the hypothesis that the great ape brain may develop in a ‘‘torquing’’ manner, producing similar anatomical asymmetries as reported in humans. PMID:15513168

The Myth of Pink and Blue Brains

ERIC Educational Resources Information Center

Eliot, Lise

2010-01-01

Eliot, a neuroscientist who has analyzed gender differences in children's brains, asserts that--contrary to the widely held idea that boys' and girls' brains are hardwired differently--few differences exist in the neural structures and neurochemistry of boys' and girls' brains. Actual ability differences between the genders are quite small as…

The Nature of Compensatory Response to Low Thyroid Hormone in Developing Brain.

EPA Science Inventory

Abstract Thyroid hormone is essential for normal brain development, but the degree to which the developing brain is sensitive to small perturbations in serum thyroxin is not clear. An important concept related to this is that the developing brain possesses potent mechanisms to co...

Investigation of global and local network properties of music perception with culturally different styles of music.

PubMed

Li, Yan; Rui, Xue; Li, Shuyu; Pu, Fang

2014-11-01

Graph theoretical analysis has recently become a popular research tool in neuroscience, however, there have been very few studies on brain responses to music perception, especially when culturally different styles of music are involved. Electroencephalograms were recorded from ten subjects listening to Chinese traditional music, light music and western classical music. For event-related potentials, phase coherence was calculated in the alpha band and then constructed into correlation matrices. Clustering coefficients and characteristic path lengths were evaluated for global properties, while clustering coefficients and efficiency were assessed for local network properties. Perception of light music and western classical music manifested small-world network properties, especially with a relatively low proportion of weights of correlation matrices. For local analysis, efficiency was more discernible than clustering coefficient. Nevertheless, there was no significant discrimination between Chinese traditional and western classical music perception. Perception of different styles of music introduces different network properties, both globally and locally. Research into both global and local network properties has been carried out in other areas; however, this is a preliminary investigation aimed at suggesting a possible new approach to brain network properties in music perception. Copyright © 2014 Elsevier Ltd. All rights reserved.

Binocular depth processing in the ventral visual pathway.

PubMed

Verhoef, Bram-Ernst; Vogels, Rufin; Janssen, Peter

2016-06-19

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

APOE/TOMM40 genetic loci, white matter hyperintensities, and cerebral microbleeds.

PubMed

Lyall, Donald M; Muñoz Maniega, Susana; Harris, Sarah E; Bastin, Mark E; Murray, Catherine; Lutz, Michael W; Saunders, Ann M; Roses, Allen D; Valdés Hernández, Maria del C; Royle, Natalie A; Starr, John M; Porteous, David J; Deary, Ian J; Wardlaw, Joanna M

2015-12-01

Two markers of cerebral small vessel disease are white matter hyperintensities and cerebral microbleeds, which commonly occur in people with Alzheimer's disease. To test for independent associations between two Alzheimer's disease-susceptibility gene loci--APOE ε and the TOMM40 '523' poly-T repeat--and white matter hyperintensities/cerebral microbleed burden in community-dwelling older adults. Participants in the Lothian Birth Cohort 1936 underwent genotyping for APOE ε and TOMM40 523, and detailed structural brain magnetic resonance imaging at a mean age of 72·70 years (standard deviation = 0·7; range = 71-74). No significant effects of APOE ε or TOMM40 523 genotypes on white matter hyperintensities or cerebral microbleed burden were found amongst 624 participants. Lack of association between two Alzheimer's disease susceptibility gene loci and markers of cerebral small vessel disease may reflect the relative health of this population compared with those in other studies in the literature. © 2015 The Authors. International Journal of Stroke published by John Wiley & Sons Ltd on behalf of World Stroke Organization.

Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders.

PubMed

Luan, Hemi; Wang, Xian; Cai, Zongwei

2017-11-12

Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies. © 2017 Wiley Periodicals, Inc.

Unsupervised MRI segmentation of brain tissues using a local linear model and level set.

PubMed

Rivest-Hénault, David; Cheriet, Mohamed

2011-02-01

Real-world magnetic resonance imaging of the brain is affected by intensity nonuniformity (INU) phenomena which makes it difficult to fully automate the segmentation process. This difficult task is accomplished in this work by using a new method with two original features: (1) each brain tissue class is locally modeled using a local linear region representative, which allows us to account for the INU in an implicit way and to more accurately position the region's boundaries; and (2) the region models are embedded in the level set framework, so that the spatial coherence of the segmentation can be controlled in a natural way. Our new method has been tested on the ground-truthed Internet Brain Segmentation Repository (IBSR) database and gave promising results, with Tanimoto indexes ranging from 0.61 to 0.79 for the classification of the white matter and from 0.72 to 0.84 for the gray matter. To our knowledge, this is the first time a region-based level set model has been used to perform the segmentation of real-world MRI brain scans with convincing results. Copyright © 2011 Elsevier Inc. All rights reserved.

Brain Activity on Navigation in Virtual Environments.

ERIC Educational Resources Information Center

Mikropoulos, Tassos A.

2001-01-01

Assessed the cognitive processing that takes place in virtual environments by measuring electrical brain activity using Fast Fourier Transform analysis. University students performed the same task in a real and a virtual environment, and eye movement measurements showed that all subjects were more attentive when navigating in the virtual world.…

Relationship of Temporal Lobe Volumes to Neuropsychological Test Performance in Healthy Children

ERIC Educational Resources Information Center

Wells, Carolyn T.; Mahone, E. Mark; Matson, Melissa A.; Kates, Wendy R.; Hay, Trisha; Horska, Alena

2008-01-01

Ecological validity of neuropsychological assessment includes the ability of tests to predict real-world functioning and/or covary with brain structures. Studies have examined the relationship between adaptive skills and test performance, with less focus on the association between regional brain volumes and neurobehavioral function in healthy…

Neuroscience, Education and Special Education

ERIC Educational Resources Information Center

Goswami, Usha

2004-01-01

The discipline of neuroscience draws from the fields of neurology, psychology, physiology and biology, but is best understood in the wider world as brain science. Of particular interest for education is the development of techniques for imaging the brain as it performs different cognitive functions. Cognitive neuroimaging has already led to…

The Brain's Versatile Toolbox.

ERIC Educational Resources Information Center

Pinker, Steven

1997-01-01

Considers the role of evolution and natural selection in the functioning of the modern human brain. Natural selection equipped humans with a mental toolbox of intuitive theories about the world which were used to master rocks, tools, plants, animals, and one another. The same toolbox is used today to master the intellectual challenges of modern…

MIT - Massachusetts Institute of Technology

Science.gov Websites

energy cancer diversity global industry public service Solve The MIT Campaign for a Better World give to produce electricity Drug-carrying nanoparticles could help fight brain cancer Drug-carrying nanoparticles could help fight brain cancer New dispatching approach optimizes a city's taxi fleet New dispatching

[Three Essential Shared Capabilities for Young Psychiatrists: Brain, Real-world, and Life-course Principles toward Values-based Psychiatry].

PubMed

Kasai, Kiyoto

2015-01-01

The discipline of psychiatry promotes well-being and recovery based on a comprehensive understanding of the patient from the perspectives of the brain, real-world, and life-course. Pursuant to efforts toward addressing social issues at a regional and national level, it is assumed that the psychiatrist can assist individuals based on an understanding of these three perspectives. This tripartite relationship goes beyond the history of extreme reductionism in neuroscience and the aftermath resulting from the anti-psychiatry movement to provide a foundation for the development of psychiatry and a theoretical groundwork for such basic psychiatric issues as what role pharmacotherapy plays in psychiatric treatment, just why the lives of people living in the community are thought to be important to an individual's well-being, and just what constitutes recovery. Humans have come to possess highly developed brain and mental functions as a result of the adaptation to the social environment that takes place as part of the evolutionary process. While mental functions are thus dictated in large part by evolution of the brain, they also consist of important features that are not attributable to reductionist models of the brain. That is, human mental functioning forms a foundation for metacognition and sophisticated language functions, and through interactions with others and society, one's mental functioning allows for further brain transformation and development (self-regulation of mental functions). Humans develop their own brain and mental functions through mutual exchanges with others, and their dealings with other people and society form their individual modes of living in the real-world. The human brain and mental functions have evolved in such a way as to provide for a better mode of living. Accordingly, for the individual, the makeup of his or her mode of living in the real-world is the source of the well-being that serves to support that individual's values. The scientific background that the human recovery process for those suffering from mental disease involves the combined support of work, school, marriage, and childrearing stems from this fact. Humans develop their own mental capital over their life-courses and utilize it in an effort to realize their well-beings. Humans utilize mental function self-regulation based on the emotional and interpersonal functions developed during childhood in order to formulate an image of themselves (the ego) as well as the type of person they want to become (values/needs). This is indeed the true essence of adolescence. The values that drive an individual's behavior by their very nature exist in the outside world and are shared by others as well as society. These are internalized as individual characteristics through the self-regulation process of adolescence. Regardless of life stage or type of mental illness, individual reflection, verbalization, and reorganization of adolescent ego and values formation are essential to the recovery process. Humans are born with both bodies and brains, and throughout the courses of their lives, they formulate and develop values. Based on an understanding of the tripartite relationship between the brain, real-world, and life courses, it can be argued that the supporting of individual values is the scientific basis for the so-called "patient-centered care" and "needs-based support" that serve as a psychiatrist's essential capabilities. Along with the patient's recovery, which is based on this values-based psychiatry, professional growth is the privilege enjoyed by those in the psychiatric field. Beginning with a foundation based on assisted recovery at the individual level, the psychiatrist can produce mental health changes at the regional level. The psychiatrist consequently possesses the national-level vision necessary to implement a community design model that combines mental health and preventive medicine.

Quantum probability, choice in large worlds, and the statistical structure of reality.

PubMed

Ross, Don; Ladyman, James

2013-06-01

Classical probability models of incentive response are inadequate in "large worlds," where the dimensions of relative risk and the dimensions of similarity in outcome comparisons typically differ. Quantum probability models for choice in large worlds may be motivated pragmatically - there is no third theory - or metaphysically: statistical processing in the brain adapts to the true scale-relative structure of the universe.

Small Worlds Week: Raising Curiosity and Contributing to STEM

NASA Astrophysics Data System (ADS)

Ng, C.; Mayo, L.; Stephenson, B. E.; Keck, A.; Cline, T. D.; Lewis, E. M.

2015-12-01

Dwarf planets, comets, asteroids, and icy moons took center stage in the years 2014-2015 as multiple spacecraft (New Horizons, Dawn, Rosetta, Cassini) and ground-based observing campaigns observed these small and yet amazing celestial bodies. Just prior to the historic New Horizons encounter with the Pluto system, NASA celebrated Small Worlds Week (July 6-10) as a fully online program to highlight small worlds mission discoveries. Small Worlds Week leveraged the infrastructure of Sun-Earth Days that included a robust web design, exemplary education materials, hands-on fun activities, multimedia resources, science and career highlights, and a culminating event. Each day from July 6-9, a new class of solar system small worlds was featured on the website: Monday-comets, Tuesday-asteroids, Wednesday-icy moons, and Thursday-dwarf planets. Then on Friday, July 10, nine scientists from Goddard Space Flight Center, Jet Propulsion Laboratory, Naval Research Laboratory, and Lunar and Planetary Institute gathered online for four hours to answer questions from the public via Facebook and Twitter. Throughout the afternoon the scientists worked closely with a social media expert and several summer interns to reply to inquirers and to archive their chats. By all accounts, Small Worlds Week was a huge success. The group plans to improve and replicate the program during the school year with a more classroom focus, and then to build and extend the program to be held every year. For more information, visit http:// sunearthday.nasa.gov or catch us on Twitter, #nasasww.

Is the ferret a suitable species for studying perinatal brain injury?

PubMed Central

Empie, Kristen; Rangarajan, Vijayeta; Juul, Sandra E.

2016-01-01

Complications of prematurity often disrupt normal brain development and/or cause direct damage to the developing brain, resulting in poor neurodevelopmental outcomes. Physiologically relevant animal models of perinatal brain injury can advance our understanding of these influences and thereby provide opportunities to develop therapies and improve long-term outcomes. While there are advantages to currently available small animal models, there are also significant drawbacks that have limited translation of research findings to humans. Large animal models such as newborn pig, sheep and nonhuman primates have complex brain development more similar to humans, but these animals are expensive, and developmental testing of sheep and piglets is limited. Ferrets (Mustela putorius furo) are born lissencephalic and undergo postnatal cortical folding to form complex gyrencephalic brains. This review examines whether ferrets might provide a novel intermediate animal model of neonatal brain disease that has the benefit of a gyrified, altricial brain in a small animal. It summarizes attributes of ferret brain growth and development that make it an appealing animal in which to model perinatal brain injury. We postulate that because of their innate characteristics, ferrets have great potential in neonatal neurodevelopmental studies. PMID:26102988

Drug transport across the blood–brain barrier

PubMed Central

Pardridge, William M

2012-01-01

The blood–brain barrier (BBB) prevents the brain uptake of most pharmaceuticals. This property arises from the epithelial-like tight junctions within the brain capillary endothelium. The BBB is anatomically and functionally distinct from the blood–cerebrospinal fluid barrier at the choroid plexus. Certain small molecule drugs may cross the BBB via lipid-mediated free diffusion, providing the drug has a molecular weight <400 Da and forms <8 hydrogen bonds. These chemical properties are lacking in the majority of small molecule drugs, and all large molecule drugs. Nevertheless, drugs can be reengineered for BBB transport, based on the knowledge of the endogenous transport systems within the BBB. Small molecule drugs can be synthesized that access carrier-mediated transport (CMT) systems within the BBB. Large molecule drugs can be reengineered with molecular Trojan horse delivery systems to access receptor-mediated transport (RMT) systems within the BBB. Peptide and antisense radiopharmaceuticals are made brain-penetrating with the combined use of RMT-based delivery systems and avidin–biotin technology. Knowledge on the endogenous CMT and RMT systems expressed at the BBB enable new solutions to the problem of BBB drug transport. PMID:22929442

Neurophysiology of the esophagus.

PubMed

Brock, Christina; Brokjaer, Anne; Drewes, Asbjørn Mohr; Farmer, Adam D; Frøkjaer, Jens Brøndum; Gregersen, Hans; Lottrup, Christian

2014-09-01

The following, from the 12th OESO World Conference: Cancers of the Esophagus, includes commentaries on the methods and characteristics of esophageal afferents in humans; the pitfalls in characterization of mechanosensitive afferents; the sensitization of esophageal afferents in human studies; the brain source modeling in the understanding of the esophagus-brain axis; the use of evoked brain potentials in the esophagus; and measuring descending inhibition in animal and human studies. © 2014 New York Academy of Sciences.

State-of-the-art considerations in small cell lung cancer brain metastases

PubMed Central

Lukas, Rimas V.; Gondi, Vinai; Kamson, David O.; Kumthekar, Priya; Salgia, Ravi

2017-01-01

Background Small cell lung cancer (SCLC) frequently leads to development of brain metastases. These unfortunately continue to be associated with short survival. Substantial advances have been made in our understanding of the underlying biology of disease. This understanding on the background of previously evaluated and currently utilized therapeutic treatments can help guide the next steps in investigations into this disease with the potential to influence future treatments. Design A comprehensive review of the literature covering epidemiology, pathophysiology, imaging characteristics, prognosis, and therapeutic management of SCLC brain metastases was performed. Results SCLC brain metastases continue to have a poor prognosis. Both unique aspects of SCLC brain metastases as well as features seen more universally across other solid tumor brain metastases are discussed. Systemic therapeutic studies and radiotherapeutic approaches are reviewed. Conclusions A clearer understanding of SCLC brain metastases will help lay the framework for studies which will hopefully translate into meaningful therapeutic options for these patients. PMID:29050358

Correlations between prefrontal neurons form a small-world network that optimizes the generation of multineuron sequences of activity

PubMed Central

Luongo, Francisco J.; Zimmerman, Chris A.; Horn, Meryl E.

2016-01-01

Sequential patterns of prefrontal activity are believed to mediate important behaviors, e.g., working memory, but it remains unclear exactly how they are generated. In accordance with previous studies of cortical circuits, we found that prefrontal microcircuits in young adult mice spontaneously generate many more stereotyped sequences of activity than expected by chance. However, the key question of whether these sequences depend on a specific functional organization within the cortical microcircuit, or emerge simply as a by-product of random interactions between neurons, remains unanswered. We observed that correlations between prefrontal neurons do follow a specific functional organization—they have a small-world topology. However, until now it has not been possible to directly link small-world topologies to specific circuit functions, e.g., sequence generation. Therefore, we developed a novel analysis to address this issue. Specifically, we constructed surrogate data sets that have identical levels of network activity at every point in time but nevertheless represent various network topologies. We call this method shuffling activity to rearrange correlations (SHARC). We found that only surrogate data sets based on the actual small-world functional organization of prefrontal microcircuits were able to reproduce the levels of sequences observed in actual data. As expected, small-world data sets contained many more sequences than surrogate data sets with randomly arranged correlations. Surprisingly, small-world data sets also outperformed data sets in which correlations were maximally clustered. Thus the small-world functional organization of cortical microcircuits, which effectively balances the random and maximally clustered regimes, is optimal for producing stereotyped sequential patterns of activity. PMID:26888108

Damage spreading in spatial and small-world random Boolean networks

NASA Astrophysics Data System (ADS)

Lu, Qiming; Teuscher, Christof

2014-02-01

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Information processing in micro and meso-scale neural circuits during normal and disease states

NASA Astrophysics Data System (ADS)

Luongo, Francisco

Neural computation can occur at multiple spatial and temporal timescales. The sum total of all of these processes is to guide optimal behaviors within the context of the constraints imposed by the physical world. How the circuits of the brain achieves this goal represents a central question in systems neuroscience. Here I explore the many ways in which the circuits of the brain can process information at both the micro and meso scale. Understanding the way information is represented and processed in the brain could shed light on the neuropathology underlying complex neuropsychiatric diseases such as autism and schizophrenia. Chapter 2 establishes an experimental paradigm for assaying patterns of microcircuit activity and examines the role of dopaminergic modulation on prefrontal microcircuits. We find that dopamine type 2 (D2) receptor activation results in an increase in spontaneous activity while dopamine type 1 (D1) activation does not. Chapter 3 of this dissertation presents a study that illustrates how cholingergic activation normally produces what has been suggested as a neural substrate of attention; pairwise decorrelation in microcircuit activity. This study also shows that in two etiologicall distinct mouse models of autism, FMR1 knockout mice and Valproic Acid exposed mice, this ability to decorrelate in the presence of cholinergic activation is lost. This represents a putative microcircuit level biomarker of autism. Chapter 4 examines the structure/function relationship within the prefrontal microcircuit. Spontaneous activity in prefrontal microcircuits is shown to be organized according to a small world architecture. Interestingly, this architecture is important for one concrete function of neuronal microcircuits; the ability to produce temporally stereotyped patterns of activation. In the final chapter, we identify subnetworks in chronic intracranial electrocorticographic (ECoG) recordings using pairwise electrode coherence and dimensionality reduction techniques. We show that we can further reduce the dimensionality of these networks by identifying 'key-interactions' that are informative of the overall subnetwork state at any given point in time. This study highlights that redundancy in ECoG data can be exploited to identify low-dimensional representation of brain-wide subnetworks. Taken together, these studies represent the development of multiple technological and analytical techniques aimed at understanding how information is processed and modulated at emergent circuit and network levels as well as understanding their dysfunction in a neuropsychiatric disease state.

Understanding the role of the perivascular space in cerebral small vessel disease.

PubMed

Brown, Rosalind; Benveniste, Helene; Black, Sandra E; Charpak, Serge; Dichgans, Martin; Joutel, Anne; Nedergaard, Maiken; Smith, Kenneth J; Zlokovic, Berislav V; Wardlaw, Joanna M

2018-05-02

Small vessel diseases are a group of disorders that result from pathological alteration of the small blood vessels in the brain, including the small arteries, capillaries and veins. Of the 35-36 million people that are estimated to suffer from dementia worldwide, up to 65% have an SVD component. Furthermore, SVD causes 20-25% of strokes, worsens outcome after stroke and is a leading cause of disability, cognitive impairment and poor mobility. Yet the underlying cause(s) of SVD are not fully understood.Magnetic resonance imaging (MRI) has confirmed enlarged perivascular spaces (PVS) as a hallmark feature of SVD. In healthy tissue, these spaces are proposed to form part of a complex brain fluid drainage system which supports interstitial fluid exchange and may also facilitate clearance of waste products from the brain. The pathophysiological signature of PVS, and what this infers about their function and interaction with cerebral microcirculation, plus subsequent downstream effects on lesion development in the brain has not been established. Here we discuss the potential of enlarged PVS to be a unique biomarker for SVD and related brain disorders with a vascular component. We propose that widening of PVS suggests presence of peri-vascular cell debris and other waste products that forms part of a vicious cycle involving impaired cerebrovascular reactivity (CVR), blood-brain barrier (BBB) dysfunction, perivascular inflammation and ultimately impaired clearance of waste proteins from the interstitial fluid (ISF) space, leading to accumulation of toxins, hypoxia and tissue damage.Here, we outline current knowledge, questions and hypotheses regarding understanding the brain fluid dynamics underpinning dementia and stroke through the common denominator of SVD.

The concentration of erlotinib in the cerebrospinal fluid of patients with brain metastasis from non-small-cell lung cancer

PubMed Central

DENG, YANMING; FENG, WEINENG; WU, JING; CHEN, ZECHENG; TANG, YICONG; ZHANG, HUA; LIANG, JIANMIAO; XIAN, HAIBING; ZHANG, SHUNDA

2014-01-01

It has been demonstrated that erlotinib is effective in treating patients with brain metastasis from non-small-cell lung cancer. However, the number of studies determining the erlotinib concentration in these patients is limited. The purpose of this study was to measure the concentration of erlotinib in the cerebrospinal fluid of patients with brain metastasis from non-small-cell lung carcinoma. Six patients were treated with the standard recommended daily dose of erlotinib (150 mg) for 4 weeks. All the patients had previously received chemotherapy, but no brain radiotherapy. At the end of the treatment period, blood plasma and cerebrospinal fluid samples were collected and the erlotinib concentration was determined by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The average erlotinib concentration in the blood plasma and the cerebrospinal fluid was 717.7±459.7 and 23.7±13.4 ng/ml, respectively. The blood-brain barrier permeation rate of erlotinib was found to be 4.4±3.2%. In patients with partial response (PR), stable disease (SD) and progressive disease (PD), the average concentrations of erlotinib in the cerebrospinal fluid were 35.5±19.0, 19.1±8.7 and 16.4±5.9 ng/ml, respectively. In addition, the efficacy rate of erlotinib for metastatic brain lesions was 33.3%, increasing to 50% in patients with EGFR mutations. However, erlotinib appeared to be ineffective in cases with wild-type EGFR. In conclusion, a relatively high concentration of erlotinib was detected in the cerebrospinal fluid of patients with brain metastases from non-small-cell lung cancer. Thus, erlotinib may be considered as a treatment option for this patient population. PMID:24649318

Efficacy and pharmacokinetics of a modified acid-labile docetaxel-PRINT(®) nanoparticle formulation against non-small-cell lung cancer brain metastases.

PubMed

Sambade, Maria; Deal, Allison; Schorzman, Allison; Luft, J Christopher; Bowerman, Charles; Chu, Kevin; Karginova, Olga; Swearingen, Amanda Van; Zamboni, William; DeSimone, Joseph; Anders, Carey K

2016-08-01

Particle Replication in Nonwetting Templates (PRINT(®)) PLGA nanoparticles of docetaxel and acid-labile C2-dimethyl-Si-Docetaxel were evaluated with small molecule docetaxel as treatments for non-small-cell lung cancer brain metastases. Pharmacokinetics, survival, tumor growth and mice weight change were efficacy measures against intracranial A549 tumors in nude mice. Treatments were administered by intravenous injection. Intracranial tumor concentrations of PRINT-docetaxel and PRINT-C2-docetaxel were 13- and sevenfold greater, respectively, than SM-docetaxel. C2-docetaxel conversion to docetaxel was threefold higher in intracranial tumor as compared with nontumor tissues. PRINT-C2-docetaxel increased median survival by 35% with less toxicity as compared with other treatments. The decreased toxicity of the PRINT-C2-docetaxel improved treatment efficacy against non-small-cell lung cancer brain metastasis.

An object-based approach for detecting small brain lesions: application to Virchow-Robin spaces.

PubMed

Descombes, Xavier; Kruggel, Frithjof; Wollny, Gert; Gertz, Hermann Josef

2004-02-01

This paper is concerned with the detection of multiple small brain lesions from magnetic resonance imaging (MRI) data. A model based on the marked point process framework is designed to detect Virchow-Robin spaces (VRSs). These tubular shaped spaces are due to retraction of the brain parenchyma from its supplying arteries. VRS are described by simple geometrical objects that are introduced as small tubular structures. Their radiometric properties are embedded in a data term. A prior model includes interactions describing the clustering property of VRS. A Reversible Jump Markov Chain Monte Carlo algorithm (RJMCMC) optimizes the proposed model, obtained by multiplying the prior and the data model. Example results are shown on T1-weighted MRI datasets of elderly subjects.

Targeted DNA sequencing of non-small cell lung cancer identifies mutations associated with brain metastases.

PubMed

Wilson, George D; Johnson, Matthew D; Ahmed, Samreen; Cardenas, Paola Yumpo; Grills, Inga S; Thibodeau, Bryan J

2018-05-25

This study explores the hypothesis that dominant molecular oncogenes in non-small cell lung cancer (NSCLC) are associated with metastatic spread to the brain. NSCLC patient groups with no evidence of metastasis, with metastatic disease to a non-CNS site, who developed brain metastasis after diagnosis, and patients with simultaneous diagnosis of NSCLC and metastatic brain lesions were studied using targeted sequencing. In patients with brain metastasis versus those without, only 2 variants (one each in BCL6 and NOTHC2) were identified that occurred in ≥ 4 NSCLC of patients with brain metastases but ≤ 1 of the NSCLC samples without brain metastases. At the gene level, 20 genes were found to have unique variants in more than 33% of the patients with brain metastases. When analyzed at the patient level, these 20 genes formed the basis of a predictive test to discriminate those with brain metastasis. Further analysis showed that PI3K/AKT signaling is altered in both the primary and metastases of NSCLC patients with brain lesions. While no single variant was associated with brain metastasis, this study describes a potential gene panel for the identification of patients at risk and implicates PI3K/AKT signaling as a therapeutic target.

Targeted DNA sequencing of non-small cell lung cancer identifies mutations associated with brain metastases

PubMed Central

Wilson, George D.; Johnson, Matthew D.; Ahmed, Samreen; Cardenas, Paola Yumpo; Grills, Inga S.; Thibodeau, Bryan J.

2018-01-01

Introduction This study explores the hypothesis that dominant molecular oncogenes in non-small cell lung cancer (NSCLC) are associated with metastatic spread to the brain. Methods NSCLC patient groups with no evidence of metastasis, with metastatic disease to a non-CNS site, who developed brain metastasis after diagnosis, and patients with simultaneous diagnosis of NSCLC and metastatic brain lesions were studied using targeted sequencing. Results In patients with brain metastasis versus those without, only 2 variants (one each in BCL6 and NOTHC2) were identified that occurred in ≥ 4 NSCLC of patients with brain metastases but ≤ 1 of the NSCLC samples without brain metastases. At the gene level, 20 genes were found to have unique variants in more than 33% of the patients with brain metastases. When analyzed at the patient level, these 20 genes formed the basis of a predictive test to discriminate those with brain metastasis. Further analysis showed that PI3K/AKT signaling is altered in both the primary and metastases of NSCLC patients with brain lesions. Conclusion While no single variant was associated with brain metastasis, this study describes a potential gene panel for the identification of patients at risk and implicates PI3K/AKT signaling as a therapeutic target. PMID:29899834

A fault-tolerant small world topology control model in ad hoc networks for search and rescue

NASA Astrophysics Data System (ADS)

Tan, Mian; Fang, Ling; Wu, Yue; Zhang, Bo; Chang, Bowen; Holme, Petter; Zhao, Jing

2018-02-01

Due to their self-organized, multi-hop and distributed characteristics, ad hoc networks are useful in search and rescue. Topology control models need to be designed for energy-efficient, robust and fast communication in ad hoc networks. This paper proposes a topology control model which specializes for search and rescue-Compensation Small World-Repeated Game (CSWRG)-which integrates mobility models, constructing small world networks and a game-theoretic approach to the allocation of resources. Simulation results show that our mobility models can enhance the communication performance of the constructed small-world networks. Our strategy, based on repeated game, can suppress selfish behavior and compensate agents that encounter selfish or faulty neighbors. This model could be useful for the design of ad hoc communication networks.

On the structural properties of small-world networks with range-limited shortcut links

NASA Astrophysics Data System (ADS)

Jia, Tao; Kulkarni, Rahul V.

2013-12-01

We explore a new variant of Small-World Networks (SWNs), in which an additional parameter (r) sets the length scale over which shortcuts are uniformly distributed. When r=0 we have an ordered network, whereas r=1 corresponds to the original Watts-Strogatz SWN model. These limited range SWNs have a similar degree distribution and scaling properties as the original SWN model. We observe the small-world phenomenon for r≪1, indicating that global shortcuts are not necessary for the small-world effect. For limited range SWNs, the average path length changes nonmonotonically with system size, whereas for the original SWN model it increases monotonically. We propose an expression for the average path length for limited range SWNs based on numerical simulations and analytical approximations.

The blind brain: how (lack of) vision shapes the morphological and functional architecture of the human brain.

PubMed

Ricciardi, Emiliano; Handjaras, Giacomo; Pietrini, Pietro

2014-11-01

Since the early days, how we represent the world around us has been a matter of philosophical speculation. Over the last few decades, modern neuroscience, and specifically the development of methodologies for the structural and the functional exploration of the brain have made it possible to investigate old questions with an innovative approach. In this brief review, we discuss the main findings from a series of brain anatomical and functional studies conducted in sighted and congenitally blind individuals by our's and others' laboratories. Historically, research on the 'blind brain' has focused mainly on the cross-modal plastic changes that follow sensory deprivation. More recently, a novel line of research has been developed to determine to what extent visual experience is truly required to achieve a representation of the surrounding environment. Overall, the results of these studies indicate that most of the brain fine morphological and functional architecture is programmed to develop and function independently from any visual experience. Distinct cortical areas are able to process information in a supramodal fashion, that is, independently from the sensory modality that carries that information to the brain. These observations strongly support the hypothesis of a modality-independent, i.e. more abstract, cortical organization, and may contribute to explain how congenitally blind individuals may interact efficiently with an external world that they have never seen. © 2014 by the Society for Experimental Biology and Medicine.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Brain Gain am Beispiel Österreich

NASA Astrophysics Data System (ADS)

Aschbacher, Christine; Gejguš, Mirko; Sablik, Jozef

2016-06-01

BrainGain is a common trend within the last ten years in Europe and all-over the world. Managers, key players and scientists are allowed to choose wherever they want to work in the world. As there is a lack of qualified individuals for companies and universities, BrainGain has become a necessity, and mostly - the higher educated individuals are moving away according to a better offer elsewhere in the world. Therefore, a lot of expats are moving around with their families. Many times, the lack of integration at the current place, country or city, is the critical success factor for staying or leaving. Furthermore, if the family does not feel happy in the current location, then the manager or scientist will move away or return home and the investment will be lost. Moreover, many students have received a good education in a state university, however afterwards they have not secured a satisfactory job in the country where they have studied, therefore they are moving away to utilise their know-how. Measures to retain the know-how include a common placement and a welcome-culture in the country, and also exchanges on an international level.

Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

2014-01-01

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

Aberrant brain functional connectome in patients with obstructive sleep apnea.

PubMed

Chen, Li-Ting; Fan, Xiao-Le; Li, Hai-Jun; Ye, Cheng-Long; Yu, Hong-Hui; Xin, Hui-Zhen; Gong, Hong-Han; Peng, De-Chang; Yan, Li-Ping

2018-01-01

Obstructive sleep apnea (OSA) is accompanied by widespread abnormal spontaneous regional activity related to cognitive deficits. However, little is known about the topological properties of the functional brain connectome of patients with OSA. This study aimed to use the graph theory approaches to investigate the topological properties and functional connectivity (FC) of the functional connectome in patients with OSA, based on resting-state functional magnetic resonance imaging (rs-fMRI). Forty-five male patients with newly diagnosed untreated severe OSA and 45 male good sleepers (GSs) underwent a polysomnography (PSG), clinical evaluations, and rs-fMRI scans. The automated anatomical labeling (AAL) atlas was used to construct the functional brain connectome. The topological organization and FC of brain functional networks in patients with OSA were characterized using graph theory methods and investigated the relationship between functional network topology and clinical variables. Both the patients with OSA and the GSs exhibited high-efficiency "small-world" network attributes. However, the patients with OSA exhibited decreased σ, γ, E glob ; increased Lp, λ; and abnormal nodal centralities in several default-mode network (DMN), salience network (SN), and central executive network (CEN) regions. However, the patients with OSA exhibited abnormal functional connections between the DMN, SN, and CEN. The disrupted FC was significantly positive correlations with the global network metrics γ and σ. The global network metrics were significantly correlated with the Epworth Sleepiness Scale (ESS) score, Montreal Cognitive Assessment (MoCA) score, and oxygen desaturation index. The findings suggest that the functional connectome of patients with OSA exhibited disrupted functional integration and segregation, and functional disconnections of the DMN, SN, and CEN. The aberrant topological attributes may be associated with disrupted FC and cognitive functions. These topological abnormalities and disconnections might be potential biomarkers of cognitive impairments in patients with OSA.

Differences in Aβ brain networks in Alzheimer's disease and healthy controls.

PubMed

Duan, Huoqiang; Jiang, Jiehui; Xu, Jun; Zhou, Hucheng; Huang, Zhemin; Yu, Zhihua; Yan, Zhuangzhi

2017-01-15

The prevailing β-amyloid (Aβ)-cascade hypothesis is the most classical Alzheimer's disease (AD) pathogenesis. In this hypothesis, excessive Aβ plaque deposition in human brain is considered to be the cause of AD. Carbon 11-labeled Pittsburgh compound B Positron emission tomography (11C-PiB PET) is the latest technology to detect Aβ plaques in vivo. Thus, it is possible to investigate the difference of Aβ brain networks between AD patients and Health Controls (HC) by analyzing 11C-PiB PET images. In this study, a graph-theoretical method was employed to investigate the topological properties of Aβ networks in 18 Chinese AD patients and 16 HC subjects from Huashan Hospital, Shanghai. The results showed that both groups demonstrated small-world property, and this property was more obvious in AD group. Additionally, the clustering coefficients and path lengths were significantly lower in AD group. The global efficiency was larger in AD than in HC. A direct comparison between with and without regression found that sex, age and weight had no significant effect on the Aβ network. Moreover, three altered regions in AD group were identified, including left cuneus (CUN.L), right caudate nucleus (CAU.R) and left superior frontal gyrus (SFGdor. L). A voxel-wise correlation analysis showed that in AD patients, the regions of strengthened connection with CUN.L were mainly located in frontal cortex and parietal cortex, the regions of strengthen connection with CAU.R were mainly located in temporal cortex. Finally, a machine learning based analysis demonstrated that the three regions could be better biomarkers than the whole brain for AD classification. Copyright © 2016 Elsevier B.V. All rights reserved.

Emergence of rich-club topology and coordinated dynamics in development of hippocampal functional networks in vitro.

PubMed

Schroeter, Manuel S; Charlesworth, Paul; Kitzbichler, Manfred G; Paulsen, Ole; Bullmore, Edward T

2015-04-08

Recent studies demonstrated that the anatomical network of the human brain shows a "rich-club" organization. This complex topological feature implies that highly connected regions, hubs of the large-scale brain network, are more densely interconnected with each other than expected by chance. Rich-club nodes were traversed by a majority of short paths between peripheral regions, underlining their potential importance for efficient global exchange of information between functionally specialized areas of the brain. Network hubs have also been described at the microscale of brain connectivity (so-called "hub neurons"). Their role in shaping synchronous dynamics and forming microcircuit wiring during development, however, is not yet fully understood. The present study aimed to investigate the role of hubs during network development, using multi-electrode arrays and functional connectivity analysis during spontaneous multi-unit activity (MUA) of dissociated primary mouse hippocampal neurons. Over the first 4 weeks in vitro, functional connectivity significantly increased in strength, density, and size, with mature networks demonstrating a robust modular and small-world topology. As expected by a "rich-get-richer" growth rule of network evolution, MUA graphs were found to form rich-clubs at an early stage in development (14 DIV). Later on, rich-club nodes were a consistent topological feature of MUA graphs, demonstrating high nodal strength, efficiency, and centrality. Rich-club nodes were also found to be crucial for MUA dynamics. They often served as broker of spontaneous activity flow, confirming that hub nodes and rich-clubs may play an important role in coordinating functional dynamics at the microcircuit level. Copyright © 2015 the authors 0270-6474/15/355459-12$15.00/0.

Cognitive mechanisms for the evolution of religious thought.

PubMed

Fondevila, Sabela; Martín-Loeches, Manuel

2013-09-01

The reasons behind the cultural persistence of religious beliefs throughout human history and prehistory still generate unanswered questions requiring scientific explanations. Within the framework of the cognitive science of religion, this article reviews experimental evidence supporting human predisposition for religious thinking and focuses on the hypothesis that a reason why religious beliefs are successful is their minimal counterintuitiveness. According to this hypothesis, religious concepts or stories would be characterized by containing only a small number of world-knowledge violations, which attracts attention while improving memorizability. We conclude this review by summarizing recent findings from our group using brain electrical activity and delving further into these questions. Our research suggests parallels between the natural tendency of the human cognitive system to use metaphors and the minimal counterintuitiveness of religious beliefs. © 2013 New York Academy of Sciences.

[Neurology of the arts].

PubMed

Chiu, Hou-Chang

2009-06-01

The brain is the window of the artistic mind. Brain activities lead to the understanding of the outside world by perception and cognition, and the enjoyment of the artistic wonders. This article will demonstrate how different brain areas are responsible for the creative abilities of painting, music, and literature. Due to the advancement in neuroscientic techniques such as functional MRI, brain electric activity mapping, etc, we explore and understand the brain areas that are responsible for cognition and artistic creation. We also understand the functional localization of mental activities from neurological patients with lesions in different brain areas. On the other hand, the artists had produced great works in a way similar to finding the related brain areas in the stimulation experiments. Therefore, many neuroscientists have praised that artists are outstanding neurologists.

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

PubMed Central

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-01-01

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

PubMed

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Torralba, Antonio; Oliva, Aude

2016-06-10

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

Walking and Talking Geography: A Small-World Approach

ERIC Educational Resources Information Center

Fertig, Gary; Silverman, Rick

2007-01-01

When teaching geography to students in the primary grades, teachers should provide firsthand experiences that young children need to make meaningful sense of their world. David Sobel, author of "Mapmaking with Children: Sense of Place Education for the Elementary Years," suggests that teachers in the early grades adopt a small-world approach to…

Brain Drain in Higher Education: Lost Hope or Opportunity?

ERIC Educational Resources Information Center

Odhiambo, George

2012-01-01

The flight of human capital is a phenomenon that has been of concern to academics and development practitioners for decades but unfortunately, there is no systematic record of the number of skilled professionals that many African countries have continued to lose to the developed world. Termed the "brain drain", it represents the loss of…

What's in a Name? How Different Languages Result in Different Brains in English and Chinese Speakers

ERIC Educational Resources Information Center

Liu, Chao

2010-01-01

The linguistic relativity hypothesis proposes that speakers of different languages perceive and conceptualize the world differently, but do their brains reflect these differences? In English, most nouns do not provide linguistic clues to their categories, whereas most Mandarin Chinese nouns provide explicit category information, either…

Who's Minding the Teenage Brain?

ERIC Educational Resources Information Center

Monastersky, Richard

2007-01-01

In this article, the author describes how researchers study the adolescent brain--a subject of inquiry that did not exist a generation ago. Any parent of a teenager knows that adolescents often have difficulty navigating through their world. Now scientists are starting to find out why. Peering into the minds of maturing youngsters, researchers are…

Genotyping and pathobiologic characterization of canine parvovirus circulating in Nanjing, China

PubMed Central

2013-01-01

Background Canine parvovirus (CPV) is an important pathogen that causes acute enteric disease in dogs. It has mutated and spread throughout the world in dog populations. We provide an update on the molecular characterization of CPV that circulated in Nanjing, a provincial capital in China between 2009 and 2012. Results Seventy rectal swab samples were collected from the dogs diagnosed with CPV infection in 8 animal hospitals of Nanjing. Sequence analysis of VP2 genes of 31 samples revealed that 29 viral strains belonged to CPV-2a subtype, while other two strains were classified into CPV-2b. To investigate the pathogenicity of the prevalent virus, we isolated CPV-2a and performed the animal experiment. Nine beagles were inoculated with 105.86 of 50% tissue culture infectious doses (TCID50) of the virus. All the experimentally infected beagles exhibited mild to moderate mucoid or watery diarrhea on day 4 post-infection (p.i.). On day 9 p.i., characteristic histopathological lesions were clearly observed in multiple organs of infected dogs, including liver, spleen, kidney, brain and all segments of the small and large intestines, while viral DNA and antigen staining could be detected in the sampled tissues. It is notable that canine parvovirus was isolated in one from two brain samples processed. Conclusion Our results indicated that CPV-2a is the predominant subtype in Nanjing of China. And this virus caused extensive lesions in a variety of tissues, including the brain. PMID:23988202

Genotyping and pathobiologic characterization of canine parvovirus circulating in Nanjing, China.

PubMed

Zhao, Yanbing; Lin, Yan; Zeng, Xujian; Lu, Chengping; Hou, Jiafa

2013-08-29

Canine parvovirus (CPV) is an important pathogen that causes acute enteric disease in dogs. It has mutated and spread throughout the world in dog populations. We provide an update on the molecular characterization of CPV that circulated in Nanjing, a provincial capital in China between 2009 and 2012. Seventy rectal swab samples were collected from the dogs diagnosed with CPV infection in 8 animal hospitals of Nanjing. Sequence analysis of VP2 genes of 31 samples revealed that 29 viral strains belonged to CPV-2a subtype, while other two strains were classified into CPV-2b. To investigate the pathogenicity of the prevalent virus, we isolated CPV-2a and performed the animal experiment. Nine beagles were inoculated with 105.86 of 50% tissue culture infectious doses (TCID50) of the virus. All the experimentally infected beagles exhibited mild to moderate mucoid or watery diarrhea on day 4 post-infection (p.i.). On day 9 p.i., characteristic histopathological lesions were clearly observed in multiple organs of infected dogs, including liver, spleen, kidney, brain and all segments of the small and large intestines, while viral DNA and antigen staining could be detected in the sampled tissues. It is notable that canine parvovirus was isolated in one from two brain samples processed. Our results indicated that CPV-2a is the predominant subtype in Nanjing of China. And this virus caused extensive lesions in a variety of tissues, including the brain.

Do all roads lead to Rome? A comparison of brain networks derived from inter-subject volumetric and metabolic covariance and moment-to-moment hemodynamic correlations in old individuals.

PubMed

Di, Xin; Gohel, Suril; Thielcke, Andre; Wehrl, Hans F; Biswal, Bharat B

2017-11-01

Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.

Multiple cortical thickness sub-networks and cognitive impairments in first episode, drug naïve patients with late life depression: A graph theory analysis.

PubMed

Shin, Jeong-Hyeon; Um, Yu Hyun; Lee, Chang Uk; Lim, Hyun Kook; Seong, Joon-Kyung

2018-03-15

Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients. Additionally, we investigated the structural sub-networks correlated with several clinical measurements including cognitive impairment and depression severity. We observed that small worldness, clustering coefficients, global and local efficiency, and hub structures in the brains of LLD patients were significantly different from healthy controls. We further found that a sub-network including the anterior cingulate, dorsolateral prefrontal cortex and superior prefrontal cortex is significantly associated with attention control and executive function. The severity of depression was associated with the sub-networks comprising the salience network, including the anterior cingulate and insula. We investigated cortico-cortical connectivity, but omitted the subcortical structures such as the striatum and thalamus. We report differences in patterns between several clinical measurements and sub-networks from large-scale and individual-level cortical thickness networks in LLD. Copyright © 2018 Elsevier B.V. All rights reserved.

Brain Death and Islam

PubMed Central

Ziad-Miller, Amna; Elamin, Elamin M.

2014-01-01

How one defines death may vary. It is important for clinicians to recognize those aspects of a patient’s religious beliefs that may directly influence medical care and how such practices may interface with local laws governing the determination of death. Debate continues about the validity and certainty of brain death criteria within Islamic traditions. A search of PubMed, Scopus, EMBASE, Web of Science, PsycNet, Sociological Abstracts, DIALOGUE ProQuest, Lexus Nexus, Google, and applicable religious texts was conducted to address the question of whether brain death is accepted as true death among Islamic scholars and clinicians and to discuss how divergent opinions may affect clinical care. The results of the literature review inform this discussion. Brain death has been acknowledged as representing true death by many Muslim scholars and medical organizations, including the Islamic Fiqh Academies of the Organization of the Islamic Conference and the Muslim World League, the Islamic Medical Association of North America, and other faith-based medical organizations as well as legal rulings by multiple Islamic nations. However, consensus in the Muslim world is not unanimous, and a sizable minority accepts death by cardiopulmonary criteria only. PMID:25287999

Culturally Appropriate Education: Insights from Educational Neuroscience

ERIC Educational Resources Information Center

Zhou, Jiaxian; Fischer, Kurt W.

2013-01-01

Culturally appropriate education focuses on educational competence needed in a global world and respect for different world views of learners and teachers from different cultural contexts. The relationship between gene, brain, and culture is complex and dynamical. Cultural experience and learning sculpts the anatomy and function of the human brain…

Consciously Thinking about Consciousness

ERIC Educational Resources Information Center

Tribus, Myron

2004-01-01

Merker hypothesized that because mobile creatures move around and must constantly readjust their map of the world and because the demands are so great for continually processing information for a map of the world, evolution has created a space in the brain where such preprocessing has been eliminated. This space he calls consciousness with the…

Battery-Less Electroencephalogram System Architecture Optimization

DTIC Science & Technology

2016-12-01

disorders, especially in real-world situations, such as when a Soldier is in theater. There are several methods to study the electrical activity in the brain...to measure the electrical activity in the brain that can still be used to study brain activity. Currently, most EEGs are recorded in highly controlled...base to build a larger system as its power consumption would allow it to operate from a AA battery for more than 72 h. While this might be acceptable

Safety and Efficacy of the BrainPort V100 Device in Individuals Blinded by Traumatic Injury

DTIC Science & Technology

2017-12-01

study was to investigate the impact of the BrainPort V200 on real-world functional task performance in persons who are profoundly blind (no better than...16 6. Products 16 7. Participants & Other Collaborating Organizations 16 8. Special Reporting Requirements 18 9. Appendix...environment. The purpose of this study was to evaluate the safety and effectiveness of the BrainPort V200 in individuals who have been medically

Jules and Augusta Dejerine, Pierre Marie, Joseph Babiński, Georges Guillain and their students during World War I.

PubMed

Walusinski, O

2017-03-01

World War I (1914-1918), however tragic, was nonetheless an "edifying school of nervous system experimental pathology" not only because of the various types of injuries, but also because their numbers were greater than any physician could have foreseen. The peripheral nervous system, the spine and the brain were all to benefit from the subsequent advances in clinical and anatomo-functional knowledge. Neurosurgeons took on nerve sutures, spinal injury exploration, and the localization and extraction of intracranial foreign bodies. Little by little, physical medicine and rehabilitation were established. A few of the most famous Parisian neurologists at the time-Jules and Augusta Dejerine, Pierre Marie, Joseph Babiński and Georges Guillain, who directed the military neurology centers-took up the physically and emotionally exhausting challenge of treating thousands of wounded soldiers. They not only cared for them, but also studied them scientifically, with the help of a small but devoted band of colleagues. The examples presented here reveal their courage and their efforts to make discoveries for which we remain grateful today. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

A Bayesian approach to in silico blood-brain barrier penetration modeling.

PubMed

Martins, Ines Filipa; Teixeira, Ana L; Pinheiro, Luis; Falcao, Andre O

2012-06-25

The human blood-brain barrier (BBB) is a membrane that protects the central nervous system (CNS) by restricting the passage of solutes. The development of any new drug must take into account its existence whether for designing new molecules that target components of the CNS or, on the other hand, to find new substances that should not penetrate the barrier. Several studies in the literature have attempted to predict BBB penetration, so far with limited success and few, if any, application to real world drug discovery and development programs. Part of the reason is due to the fact that only about 2% of small molecules can cross the BBB, and the available data sets are not representative of that reality, being generally biased with an over-representation of molecules that show an ability to permeate the BBB (BBB positives). To circumvent this limitation, the current study aims to devise and use a new approach based on Bayesian statistics, coupled with state-of-the-art machine learning methods to produce a robust model capable of being applied in real-world drug research scenarios. The data set used, gathered from the literature, totals 1970 curated molecules, one of the largest for similar studies. Random Forests and Support Vector Machines were tested in various configurations against several chemical descriptor set combinations. Models were tested in a 5-fold cross-validation process, and the best one tested over an independent validation set. The best fitted model produced an overall accuracy of 95%, with a mean square contingency coefficient (ϕ) of 0.74, and showing an overall capacity for predicting BBB positives of 83% and 96% for determining BBB negatives. This model was adapted into a Web based tool made available for the whole community at http://b3pp.lasige.di.fc.ul.pt.

Exploring the story, science, and adventure of small worlds

NASA Astrophysics Data System (ADS)

Swann, J. L.; Elkins-Tanton, L. T.; Anbar, A. D.; Klug Boonstra, S.; Tamer, A. J.; Mead, C.; Hunsley, D.

2017-12-01

Small worlds are a strategic focus at NASA, reflected by missions such as Osiris Rex and Psyche among others. The Infiniscope project, with funding from NASA SMD, is building on this scientific and public interest to teach formal and informal learners about asteroids and other small worlds. The digital learning experience, "Where are the small worlds?", and future Infiniscope experiences, incorporate a design theory that we describe as "education through exploration" (ETX) which is provided through an adaptive e-learning platform. This design ensures that learners actively engage in exploration and discovery, while receiving targeted feedback to push through challenges. To ensure that this and future experiences reach and meet the needs of as many educators as possible, Infiniscope includes a digital teaching network to host the experiences and support the reuse and adaptation of digital resources in new lessons. "Where are the small worlds?" puts learners in an interactive simulation of the solar system and provides a mission structure in which they hunt for "astrocaches" on near earth objects, main belt asteroids, and Kuiper-belt objects. These activities allow the learner to discover the locations of the small worlds in the solar system and develop an intuitive understanding for the relative motion of objects at various distances from the Sun. The experience is NGSS-aligned and accompanied by a lesson plan for integration into the classroom. In testing with more than 500 middle-school students, 83% of participants said they wanted to do more experiences like "Where are the small worlds?" They also found the experience both "fun" and "interesting" while being moderately difficult. "Where are the small worlds?" is one of many visualizations and lessons that is available within the Infiniscope teaching network. The network already has hundreds of members and is expected to grow in both numbers and engagement over time. Currently, educators can search and use pre-existing experiences, but as the visualization library expands and educators learn more about exploration-learning design, they may modify existing experiences and even build entirely new experiences to meet specific needs. In parallel, we are also developing a professional development program that builds understanding of the principles of ETX design.

Harmony in the small-world

NASA Astrophysics Data System (ADS)

Marchiori, Massimo; Latora, Vito

2000-10-01

The small-world phenomenon, popularly known as six degrees of separation, has been mathematically formalized by Watts and Strogatz in a study of the topological properties of a network. Small-world networks are defined in terms of two quantities: they have a high clustering coefficient C like regular lattices and a short characteristic path length L typical of random networks. Physical distances are of fundamental importance in applications to real cases; nevertheless, this basic ingredient is missing in the original formulation. Here, we introduce a new concept, the connectivity length D, that gives harmony to the whole theory. D can be evaluated on a global and on a local scale and plays in turn the role of L and 1/ C. Moreover, it can be computed for any metrical network and not only for the topological cases. D has a precise meaning in terms of information propagation and describes in a unified way, both the structural and the dynamical aspects of a network: small-worlds are defined by a small global and local D, i.e., by a high efficiency in propagating information both on a local and global scale. The neural system of the nematode C. elegans, the collaboration graph of film actors, and the oldest US subway system, can now be studied also as metrical networks and are shown to be small-worlds.

Eye movement-invariant representations in the human visual system.

PubMed

Nishimoto, Shinji; Huth, Alexander G; Bilenko, Natalia Y; Gallant, Jack L

2017-01-01

During natural vision, humans make frequent eye movements but perceive a stable visual world. It is therefore likely that the human visual system contains representations of the visual world that are invariant to eye movements. Here we present an experiment designed to identify visual areas that might contain eye-movement-invariant representations. We used functional MRI to record brain activity from four human subjects who watched natural movies. In one condition subjects were required to fixate steadily, and in the other they were allowed to freely make voluntary eye movements. The movies used in each condition were identical. We reasoned that the brain activity recorded in a visual area that is invariant to eye movement should be similar under fixation and free viewing conditions. In contrast, activity in a visual area that is sensitive to eye movement should differ between fixation and free viewing. We therefore measured the similarity of brain activity across repeated presentations of the same movie within the fixation condition, and separately between the fixation and free viewing conditions. The ratio of these measures was used to determine which brain areas are most likely to contain eye movement-invariant representations. We found that voxels located in early visual areas are strongly affected by eye movements, while voxels in ventral temporal areas are only weakly affected by eye movements. These results suggest that the ventral temporal visual areas contain a stable representation of the visual world that is invariant to eye movements made during natural vision.

Effects of Systemic Metabolic Fuels on Glucose and Lactate Levels in the Brain Extracellular Compartment of the Mouse

PubMed Central

Béland-Millar, Alexandria; Larcher, Jeremy; Courtemanche, Justine; Yuan, Tina; Messier, Claude

2017-01-01

Classic neuroenergetic research has emphasized the role of glucose, its transport and its metabolism in sustaining normal neural function leading to the textbook statement that it is the necessary and sole metabolic fuel of the mammalian brain. New evidence, including the Astrocyte-to-Neuron Lactate Shuttle hypothesis, suggests that the brain can use other metabolic substrates. To further study that possibility, we examined the effect of intraperitoneally administered metabolic fuels (glucose, fructose, lactate, pyruvate, ß-hydroxybutyrate, and galactose), and insulin, on blood, and extracellular brain levels of glucose and lactate in the adult male CD1 mouse. Primary motor cortex extracellular levels of glucose and lactate were monitored in freely moving mice with the use of electrochemical electrodes. Blood concentration of these same metabolites were obtained by tail vein sampling and measured with glucose and lactate meters. Blood and extracellular fluctuations of glucose and lactate were monitored for a 2-h period. We found that the systemic injections of glucose, fructose, lactate, pyruvate, and ß-hydroxybutyrate increased blood lactate levels. Apart for a small transitory rise in brain extracellular lactate levels, the main effect of the systemic injection of glucose, fructose, lactate, pyruvate, and ß-hydroxybutyrate was an increase in brain extracellular glucose levels. Systemic galactose injections produced a small rise in blood glucose and lactate but almost no change in brain extracellular lactate and glucose. Systemic insulin injections led to a decrease in blood glucose and a small rise in blood lactate; however brain extracellular glucose and lactate monotonically decreased at the same rate. Our results support the concept that the brain is able to use alternative fuels and the current experiments suggest some of the mechanisms involved. PMID:28154523

The detectability of brain metastases using contrast-enhanced spin-echo or gradient-echo images: a systematic review and meta-analysis.

PubMed

Suh, Chong Hyun; Jung, Seung Chai; Kim, Kyung Won; Pyo, Junhee

2016-09-01

This study aimed to compare the detectability of brain metastases using contrast-enhanced spin-echo (SE) and gradient-echo (GRE) T1-weighted images. The Ovid-MEDLINE and EMBASE databases were searched for studies on the detectability of brain metastases using contrast-enhanced SE or GRE images. The pooled proportions for the detectability of brain metastases were assessed using random-effects modeling. Heterogeneity among studies was determined using χ (2) statistics for the pooled estimates and the inconsistency index, I (2) . To overcome heterogeneity, subgroup analyses according to slice thickness and lesion size were performed. A total of eight eligible studies, which included a sample size of 252 patients and 1413 brain metastases, were included. The detectability of brain metastases using SE images (89.2 %) was higher than using GRE images (81.6 %; adjusted 84.0 %), but this difference was not statistically significant (p = 0.2385). In subgroup analysis of studies with 1-mm-thick slices and small metastases (<5 mm in diameter), 3-dimensional (3D) SE images demonstrated a higher detectability in comparison to 3D GRE images (93.7 % vs 73.1 % in 1-mm-thick slices; 89.5 % vs 59.4 % for small metastases) (p < 0.0001). Although both SE or GRE images are acceptable for detecting brain metastases, contrast-enhanced 3D SE images using 1-mm-thick slices are preferred for detecting brain metastases, especially small lesions (<5 mm in diameter).

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient formore » the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.« less

Rapid response of brain metastases to alectinib in a patient with non-small-cell lung cancer resistant to crizotinib.

PubMed

Ajimizu, Hitomi; Kim, Young Hak; Mishima, Michiaki

2015-02-01

Crizotinib is a potent and specific small-molecule inhibitor of both anaplastic lymphoma kinase (ALK) and c-MET tyrosine kinases, and patients with ALK rearrangement tumor benefit from crizotinib treatment; however, its penetration into calculated cerebrospinal fluid (CSF) is considered to be poor. Alectinib is a highly selective, next-generation ALK inhibitor, and both preclinical and clinical studies have indicated that alectinib is also effective in crizotinib-resistant tumors. A recent in vitro study demonstrated significant antitumor activity of alectinib for brain metastases using mouse models of ALK-positive non-small-cell lung cancer. In this paper, we report a first case alectinib was highly effective against brain metastases refractory to crizotinib. Further investigation of alectinib in this setting would be particularly valuable.

[Research of bornrol promote drugs through blood-brain barrier].

PubMed

Lv, Xuxiao; Sun, Mingjiang; Sun, Fengzhi

2012-04-01

Malignant tumor, epilepsy, dementia, cerebral ischemia and other brain diseases have very high rates of disability and mortality. Currently, many drugs are developed to treat such diseases and the effect is obviously. But they can not achieve the purpose to control these diseases because many of the drugs can not pass through the blood-brain barrier (BBB). Therefore, the treatment is not good. Borneol as the represent of the aromatic resuscitation medicine, it has strong fat-soluble active ingredients, small molecular weight, volatile and through the BBB quickly. It can also promote other therapeutic drugs through the BBB. It has two-ways regulations on BBB permeability and the damage of brain tissue is small, this have important theoretical significances and application values.

Brain Based Instruction in Correctional Settings: Strategies for Teachers.

ERIC Educational Resources Information Center

Becktold, Toni Hill

2001-01-01

Brain-based learning strategies (learner choice, movement, small groups) may be inappropriate in corrections for security reasons. Problems encountered in correctional education (attention deficit disorder, learned helplessness) complicate the use of these strategies. Incorporating brain-based instruction in these settings requires creativity and…

Ethics roundtable debate: Child with severe brain damage and an underlying brain tumour

PubMed Central

Gunn, Scott; Hashimoto, Satoru; Karakozov, Michael; Marx, Thomas; Tan, Ian KS; Thompson, Dan R; Vincent, Jean-Louis

2004-01-01

A young person presents with a highly malignant brain tumour with hemiparesis and limited prognosis after resection. She then suffers an iatrogenic cardiac and respiratory arrest that results in profound anoxic encephalopathy. A difference in opinion between the treatment team and the parent is based on a question of futile therapy. Opinions from five intensivists from around the world explore the differences in ethical and legal issues. A Physician-ethicist comments on the various approaches. PMID:15312199

Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion and action

PubMed Central

Grossberg, Stephen

2009-01-01

An intimate link exists between the predictive and learning processes in the brain. Perceptual/cognitive and spatial/motor processes use complementary predictive mechanisms to learn, recognize, attend and plan about objects in the world, determine their current value, and act upon them. Recent neural models clarify these mechanisms and how they interact in cortical and subcortical brain regions. The present paper reviews and synthesizes data and models of these processes, and outlines a unified theory of predictive brain processing. PMID:19528003

Longitudinal patterns of leukoaraiosis and brain atrophy in symptomatic small vessel disease.

PubMed

Lambert, Christian; Benjamin, Philip; Zeestraten, Eva; Lawrence, Andrew J; Barrick, Thomas R; Markus, Hugh S

2016-04-01

Cerebral small vessel disease is a common condition associated with lacunar stroke, cognitive impairment and significant functional morbidity. White matter hyperintensities and brain atrophy, seen on magnetic resonance imaging, are correlated with increasing disease severity. However, how the two are related remains an open question. To better define the relationship between white matter hyperintensity growth and brain atrophy, we applied a semi-automated magnetic resonance imaging segmentation analysis pipeline to a 3-year longitudinal cohort of 99 subjects with symptomatic small vessel disease, who were followed-up for ≥1 years. Using a novel two-stage warping pipeline with tissue repair step, voxel-by-voxel rate of change maps were calculated for each tissue class (grey matter, white matter, white matter hyperintensities and lacunes) for each individual. These maps capture both the distribution of disease and spatial information showing local rates of growth and atrophy. These were analysed to answer three primary questions: first, is there a relationship between whole brain atrophy and magnetic resonance imaging markers of small vessel disease (white matter hyperintensities or lacune volume)? Second, is there regional variation within the cerebral white matter in the rate of white matter hyperintensity progression? Finally, are there regionally specific relationships between the rates of white matter hyperintensity progression and cortical grey matter atrophy? We demonstrate that the rates of white matter hyperintensity expansion and grey matter atrophy are strongly correlated (Pearson's R = -0.69, P < 1 × 10(-7)), and significant grey matter loss and whole brain atrophy occurs annually (P < 0.05). Additionally, the rate of white matter hyperintensity growth was heterogeneous, occurring more rapidly within long association fasciculi. Using voxel-based quantification (family-wise error corrected P < 0.05), we show the rate of white matter hyperintensity progression is associated with increases in cortical grey matter atrophy rates, in the medial-frontal, orbito-frontal, parietal and occipital regions. Conversely, increased rates of global grey matter atrophy are significantly associated with faster white matter hyperintensity growth in the frontal and parietal regions. Together, these results link the progression of white matter hyperintensities with increasing rates of regional grey matter atrophy, and demonstrate that grey matter atrophy is the major contributor to whole brain atrophy in symptomatic cerebral small vessel disease. These measures provide novel insights into the longitudinal pathogenesis of small vessel disease, and imply that therapies aimed at reducing progression of white matter hyperintensities via end-arteriole damage may protect against secondary brain atrophy and consequent functional morbidity. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

Ex vivo micro-CT imaging of murine brain models using non-ionic iodinated contrast

NASA Astrophysics Data System (ADS)

Salas Bautista, N.; Martínez-Dávalos, A.; Rodríguez-Villafuerte, M.; Murrieta-Rodríguez, T.; Manjarrez-Marmolejo, J.; Franco-Pérez, J.; Calvillo-Velasco, M. E.

2014-11-01

Preclinical investigation of brain tumors is frequently carried out by means of intracranial implantation of brain tumor xenografts or allografts, with subsequent analysis of tumor growth using conventional histopathology. However, very little has been reported on the use contrast-enhanced techniques in micro-CT imaging for the study of malignant brain tumors in small animal models. The aim of this study has been to test a protocol for ex vivo imaging of murine brain models of glioblastoma multiforme (GBM) after treatment with non-ionic iodinated solution, using an in-house developed laboratory micro-CT. We have found that the best compromise between acquisition time and image quality is obtained using a 50 kVp, 0.5 mAs, 1° angular step on a 360 degree orbit acquisition protocol, with 70 μm reconstructed voxel size using the Feldkamp algorithm. With this parameters up to 4 murine brains can be scanned in tandem in less than 15 minutes. Image segmentation and analysis of three sample brains allowed identifying tumor volumes as small as 0.4 mm3.

The evolution of the complex sensory and motor systems of the human brain.

PubMed

Kaas, Jon H

2008-03-18

Inferences about how the complex sensory and motor systems of the human brain evolved are based on the results of comparative studies of brain organization across a range of mammalian species, and evidence from the endocasts of fossil skulls of key extinct species. The endocasts of the skulls of early mammals indicate that they had small brains with little neocortex. Evidence from comparative studies of cortical organization from small-brained mammals of the six major branches of mammalian evolution supports the conclusion that the small neocortex of early mammals was divided into roughly 20-25 cortical areas, including primary and secondary sensory fields. In early primates, vision was the dominant sense, and cortical areas associated with vision in temporal and occipital cortex underwent a significant expansion. Comparative studies indicate that early primates had 10 or more visual areas, and somatosensory areas with expanded representations of the forepaw. Posterior parietal cortex was also expanded, with a caudal half dominated by visual inputs, and a rostral half dominated by somatosensory inputs with outputs to an array of seven or more motor and visuomotor areas of the frontal lobe. Somatosensory areas and posterior parietal cortex became further differentiated in early anthropoid primates. As larger brains evolved in early apes and in our hominin ancestors, the number of cortical areas increased to reach an estimated 200 or so in present day humans, and hemispheric specializations emerged. The large human brain grew primarily by increasing neuron number rather than increasing average neuron size.

Multivariate Meta-Analysis of Brain-Mass Correlations in Eutherian Mammals

PubMed Central

Steinhausen, Charlene; Zehl, Lyuba; Haas-Rioth, Michaela; Morcinek, Kerstin; Walkowiak, Wolfgang; Huggenberger, Stefan

2016-01-01

The general assumption that brain size differences are an adequate proxy for subtler differences in brain organization turned neurobiologists toward the question why some groups of mammals such as primates, elephants, and whales have such remarkably large brains. In this meta-analysis, an extensive sample of eutherian mammals (115 species distributed in 14 orders) provided data about several different biological traits and measures of brain size such as absolute brain mass (AB), relative brain mass (RB; quotient from AB and body mass), and encephalization quotient (EQ). These data were analyzed by established multivariate statistics without taking specific phylogenetic information into account. Species with high AB tend to (1) feed on protein-rich nutrition, (2) have a long lifespan, (3) delayed sexual maturity, and (4) long and rare pregnancies with small litter sizes. Animals with high RB usually have (1) a short life span, (2) reach sexual maturity early, and (3) have short and frequent gestations. Moreover, males of species with high RB also have few potential sexual partners. In contrast, animals with high EQs have (1) a high number of potential sexual partners, (2) delayed sexual maturity, and (3) rare gestations with small litter sizes. Based on these correlations, we conclude that Eutheria with either high AB or high EQ occupy positions at the top of the network of food chains (high trophic levels). Eutheria of low trophic levels can develop a high RB only if they have small body masses. PMID:27746724

Reversal learning enhanced by lysergic acid diethylamide (LSD): concomitant rise in brain 5-hydroxytryptamine levels.

PubMed

King, A R; Martin, I L; Melville, K A

1974-11-01

1 Small doses of lysergic acid diethylamide (LSD) (12.5-50 mug/kg) consistently facilitated learning of a brightness discrimination reversal.2 2-Bromo-lysergic acid diethylamide (BOL-148), a structural analogue of LSD, with similar peripheral anti-5-hydroxytrypamine activity but no psychotomimetic properties, had no effect in this learning situation at a similar dose (25 mug/kg).3 LSD, but not BOL-148, caused a small but significant increase in brain 5-hydroxytryptamine levels, but had no effect on the levels of catecholamines in the brain at 25 mug/kg.

The intense world theory - a unifying theory of the neurobiology of autism.

PubMed

Markram, Kamila; Markram, Henry

2010-01-01

Autism covers a wide spectrum of disorders for which there are many views, hypotheses and theories. Here we propose a unifying theory of autism, the Intense World Theory. The proposed neuropathology is hyper-functioning of local neural microcircuits, best characterized by hyper-reactivity and hyper-plasticity. Such hyper-functional microcircuits are speculated to become autonomous and memory trapped leading to the core cognitive consequences of hyper-perception, hyper-attention, hyper-memory and hyper-emotionality. The theory is centered on the neocortex and the amygdala, but could potentially be applied to all brain regions. The severity on each axis depends on the severity of the molecular syndrome expressed in different brain regions, which could uniquely shape the repertoire of symptoms of an autistic child. The progression of the disorder is proposed to be driven by overly strong reactions to experiences that drive the brain to a hyper-preference and overly selective state, which becomes more extreme with each new experience and may be particularly accelerated by emotionally charged experiences and trauma. This may lead to obsessively detailed information processing of fragments of the world and an involuntarily and systematic decoupling of the autist from what becomes a painfully intense world. The autistic is proposed to become trapped in a limited, but highly secure internal world with minimal extremes and surprises. We present the key studies that support this theory of autism, show how this theory can better explain past findings, and how it could resolve apparently conflicting data and interpretations. The theory also makes further predictions from the molecular to the behavioral levels, provides a treatment strategy and presents its own falsifying hypothesis.

The Intense World Theory – A Unifying Theory of the Neurobiology of Autism

PubMed Central

Markram, Kamila; Markram, Henry

2010-01-01

Autism covers a wide spectrum of disorders for which there are many views, hypotheses and theories. Here we propose a unifying theory of autism, the Intense World Theory. The proposed neuropathology is hyper-functioning of local neural microcircuits, best characterized by hyper-reactivity and hyper-plasticity. Such hyper-functional microcircuits are speculated to become autonomous and memory trapped leading to the core cognitive consequences of hyper-perception, hyper-attention, hyper-memory and hyper-emotionality. The theory is centered on the neocortex and the amygdala, but could potentially be applied to all brain regions. The severity on each axis depends on the severity of the molecular syndrome expressed in different brain regions, which could uniquely shape the repertoire of symptoms of an autistic child. The progression of the disorder is proposed to be driven by overly strong reactions to experiences that drive the brain to a hyper-preference and overly selective state, which becomes more extreme with each new experience and may be particularly accelerated by emotionally charged experiences and trauma. This may lead to obsessively detailed information processing of fragments of the world and an involuntarily and systematic decoupling of the autist from what becomes a painfully intense world. The autistic is proposed to become trapped in a limited, but highly secure internal world with minimal extremes and surprises. We present the key studies that support this theory of autism, show how this theory can better explain past findings, and how it could resolve apparently conflicting data and interpretations. The theory also makes further predictions from the molecular to the behavioral levels, provides a treatment strategy and presents its own falsifying hypothesis. PMID:21191475

Want Success in School? Start with Babies!

ERIC Educational Resources Information Center

Lally, J. Ronald

2012-01-01

Much of what gets in the way of learning in elementary, middle, and high schools has to do with lessons missed, skills undeveloped, and experiences in the world that have shaped the early development of the brain. Neuroscience tells people that early experience, even experience in the womb, is the soil in which the young brain grows and that early…

Functional Connectivity between Brain Regions Involved in Learning Words of a New Language

ERIC Educational Resources Information Center

Veroude, Kim; Norris, David G.; Shumskaya, Elena; Gullberg, Marianne; Indefrey, Peter

2010-01-01

Previous studies have identified several brain regions that appear to be involved in the acquisition of novel word forms. Standard word-by-word presentation is often used although exposure to a new language normally occurs in a natural, real world situation. In the current experiment we investigated naturalistic language exposure and applied a…

Academic Brain Drain: Impact and Implications for Public Higher Education Quality in Kenya

ERIC Educational Resources Information Center

Odhiambo, George O.

2013-01-01

The flight of human capital is a phenomenon that has been of concern to academics and development practitioners for decades. Unfortunately, there is no systematic record of the number of skilled professionals that many African countries have continued to lose to the developed world. Termed the "brain drain", it represents the loss of…

Brain Friendly Techniques: Mind Mapping

ERIC Educational Resources Information Center

Goldberg, Cristine

2004-01-01

Mind Mapping can be called the Swiss Army Knife for the brain, a total visual thinking tool or a multi-handed thought catcher. Invented by Tony Buzan in the early 1970s and used by millions around the world, it is a method that can be a part of a techniques repertoire when teaching information literacy, planning, presenting, thinking, and so…

Classroom Strategies for Teaching Veterans with Post-Traumatic Stress Disorder and Traumatic Brain Injury

ERIC Educational Resources Information Center

Sinski, Jennifer Blevins

2012-01-01

Postsecondary institutions currently face the largest influx of veteran students since World War II. As the number of veteran students who may experience learning problems caused by Post-Traumatic Stress Disorder and/or Traumatic Brain Injury continues to rise, the need for instructional strategies that address their needs increases. Educators may…

The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

PubMed Central

Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

2018-01-01

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg). Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency. PMID:29497372

Graph properties of synchronized cortical networks during visual working memory maintenance.

PubMed

Palva, Satu; Monto, Simo; Palva, J Matias

2010-02-15

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI.

PubMed

Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

2018-01-01

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg) . Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

Neuropathology of supercentenarians - four autopsy case studies.

PubMed

Takao, Masaki; Hirose, Nobuyoshi; Arai, Yasumichi; Mihara, Ban; Mimura, Masaru

2016-09-02

Supercentenarians (aged 110 years old or more) are extremely rare in the world population (the number of living supercentenarians is estimated as 47 in the world), and details about their neuropathological information are limited. Based on previous studies, centenarians (aged 100-109 years old) exhibit several types of neuropathological changes, such as Alzheimer's disease and Lewy body disease pathology, primary age-related tauopathy, TDP-43 pathology, and hippocampal sclerosis. In the present study, we provide results from neuropathological analyses of four supercentenarian autopsy cases using conventional and immunohistochemical analysis for neurodegenerative disorders. In particular, we focused on the pathology of Alzheimer's disease and Lewy body disease, as well as the status of hippocampal sclerosis, TDP-43 pathology, aging-related tau astrogliopathy, and cerebrovascular diseases. Three cases were characterized as an "intermediate" level of Alzheimer's disease changes (NIA-AA guideline) and one was characterized as primary age-related tauopathy. TDP-43 deposits were present in the hippocampus in two cases. Neither Lewy body pathology nor hippocampal sclerosis was observed. Aging-related tau astrogliopathy was consistently observed, particularly in the basal forebrain. Small vessel diseases were also present, but they were relatively mild for cerebral amyloid-beta angiopathy and arteriolosclerosis. Although our study involved a small number of cases, the results provide a better understanding about human longevity. Neuropathological alterations associated with aging were mild to moderate in the supercentenarian brain, suggesting that these individuals might have some neuroprotective factors against aging. Future prospective studies and extensive molecular analyses are needed to determine the mechanisms of human longevity.

Brain Circulation: Unparalleled Opportunities, Underlying Challenges, and Outmoded Presumptions

ERIC Educational Resources Information Center

Teferra, Damtew

2005-01-01

An emerging global phenomenon of significant proportions, the mobility of high-level personnel affects the socioeconomic and sociocultural progress of a nation and the world. The information era has conquered the barriers of distance and space, opening up a whole array of opportunities and challenges affecting the mode in which the world interacts…

Enhanced learning of natural visual sequences in newborn chicks.

PubMed

Wood, Justin N; Prasad, Aditya; Goldman, Jason G; Wood, Samantha M W

2016-07-01

To what extent are newborn brains designed to operate over natural visual input? To address this question, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) show enhanced learning of natural visual sequences at the onset of vision. We took the same set of images and grouped them into either natural sequences (i.e., sequences showing different viewpoints of the same real-world object) or unnatural sequences (i.e., sequences showing different images of different real-world objects). When raised in virtual worlds containing natural sequences, newborn chicks developed the ability to recognize familiar images of objects. Conversely, when raised in virtual worlds containing unnatural sequences, newborn chicks' object recognition abilities were severely impaired. In fact, the majority of the chicks raised with the unnatural sequences failed to recognize familiar images of objects despite acquiring over 100 h of visual experience with those images. Thus, newborn chicks show enhanced learning of natural visual sequences at the onset of vision. These results indicate that newborn brains are designed to operate over natural visual input.

Brain anomalies in velo-cardio-facial syndrome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitnick, R.J.; Bello, J.A.; Shprintzen, R.J.

Magnetic resonance imaging of the brain in 11 consecutively referred patients with velo-cardio-facial syndrome (VCF) showed anomalies in nine cases including small vermis, cysts adjacent to the frontal horns, and small posterior fossa. Focal signal hyperintensities in the white matter on long TR images were also noted. The nine patients showed a variety of behavioral abnormalities including mild development delay, learning disabilities, and characteristic personality traits typical of this common multiple anomaly syndrome which has been related to a microdeletion at 22q11. Analysis of the behavorial findings showed no specific pattern related to the brain anomalies, and the patients withmore » VCF who did not have detectable brain lesions also had behavioral abnormalities consistent with VCF. The significance of the lesions is not yet known, but the high prevalence of anomalies in this sample suggests that structural brain abnormalities are probably common in VCF. 25 refs.« less

Permeabilization of brain tissue in situ enables multiregion analysis of mitochondrial function in a single mouse brain.

PubMed

Herbst, Eric A F; Holloway, Graham P

2015-02-15

Mitochondrial function in the brain is traditionally assessed through analysing respiration in isolated mitochondria, a technique that possesses significant tissue and time requirements while also disrupting the cooperative mitochondrial reticulum. We permeabilized brain tissue in situ to permit analysis of mitochondrial respiration with the native mitochondrial morphology intact, removing the need for isolation time and minimizing tissue requirements to ∼2 mg wet weight. The permeabilized brain technique was validated against the traditional method of isolated mitochondria and was then further applied to assess regional variation in the mouse brain with ischaemia-reperfusion injuries. A transgenic mouse model overexpressing catalase within mitochondria was applied to show the contribution of mitochondrial reactive oxygen species to ischaemia-reperfusion injuries in different brain regions. This technique enhances the accessibility of addressing physiological questions in small brain regions and in applying transgenic mouse models to assess mechanisms regulating mitochondrial function in health and disease. Mitochondria function as the core energy providers in the brain and symptoms of neurodegenerative diseases are often attributed to their dysregulation. Assessing mitochondrial function is classically performed in isolated mitochondria; however, this process requires significant isolation time, demand for abundant tissue and disruption of the cooperative mitochondrial reticulum, all of which reduce reliability when attempting to assess in vivo mitochondrial bioenergetics. Here we introduce a method that advances the assessment of mitochondrial respiration in the brain by permeabilizing existing brain tissue to grant direct access to the mitochondrial reticulum in situ. The permeabilized brain preparation allows for instant analysis of mitochondrial function with unaltered mitochondrial morphology using significantly small sample sizes (∼2 mg), which permits the analysis of mitochondrial function in multiple subregions within a single mouse brain. Here this technique was applied to assess regional variation in brain mitochondrial function with acute ischaemia-reperfusion injuries and to determine the role of reactive oxygen species in exacerbating dysfunction through the application of a transgenic mouse model overexpressing catalase within mitochondria. Through creating accessibility to small regions for the investigation of mitochondrial function, the permeabilized brain preparation enhances the capacity for examining regional differences in mitochondrial regulation within the brain, as the majority of genetic models used for unique approaches exist in the mouse model. © 2014 The Authors. The Journal of Physiology © 2014 The Physiological Society.

Preclinical Evaluation of 18F-JNJ64349311, a Novel PET Tracer for Tau Imaging.

PubMed

Declercq, Lieven; Rombouts, Frederik; Koole, Michel; Fierens, Katleen; Mariën, Jonas; Langlois, Xavier; Andrés, José Ignacio; Schmidt, Mark; Macdonald, Gregor; Moechars, Diederik; Vanduffel, Wim; Tousseyn, Thomas; Vandenberghe, Rik; Van Laere, Koen; Verbruggen, Alfons; Bormans, Guy

2017-06-01

In this study, we have synthesized and evaluated 18 F-JNJ64349311, a tracer with high affinity for aggregated tau (inhibition constant value, 8 nM) and high (≥500×) in vitro selectivity for tau over β-amyloid, in comparison with the benchmark compound 18 F-AV1451 ( 18 F-T807) in mice, rats, and a rhesus monkey. Methods: In vitro binding characteristics were determined for Alzheimer's disease, progressive supranuclear palsy, and corticobasal degeneration patient brain tissue slices using autoradiography studies. Ex vivo biodistribution studies were performed in mice. Radiometabolites were quantified in the brain and plasma of mice and in the plasma of a rhesus monkey using high-performance liquid chromatography. Dynamic small-animal PET studies were performed in rats and a rhesus monkey to evaluate tracer pharmacokinetics in the brain. Results: Mouse biodistribution studies showed moderate initial brain uptake and rapid brain washout. Radiometabolite analyses after injection of 18 F-JNJ64349311 in mice showed the presence of a polar radiometabolite in plasma, but not in the brain. Semiquantitative autoradiography studies on postmortem tissue sections of human Alzheimer's disease brains showed highly displaceable binding to tau-rich regions. No specific binding was, however, found on human progressive supranuclear palsy and corticobasal degeneration brain slices. Small-animal PET scans of Wistar rats revealed moderate initial brain uptake (SUV, ∼1.5 at 1 min after injection) and rapid brain washout. Gradual bone uptake was, however, also observed. Blocking and displacement did not affect brain time-activity curves, suggesting no off-target specific binding of the tracer in the healthy rat brain. A small-animal PET scan of a rhesus monkey revealed moderate initial brain uptake (SUV, 1.9 at 1 min after injection) with a rapid washout. In the monkey, no bone uptake was detected during the 120-min scan. Conclusion: This biologic evaluation suggests that 18 F-JNJ64349311 is a promising tau PET tracer candidate, with a favorable pharmacokinetic profile, as compared with 18 F-AV1451. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

The Brain Rotation and Brain Diffusion Strategies of Small Islanders: Considering "Movement" in Lieu of "Place"

ERIC Educational Resources Information Center

Baldacchino, Godfrey

2006-01-01

The "brain drain" phenomenon is typically seen as a zero-sum game, where one party's gain is presumed to be another's drain. This corresponds to deep-seated assumptions about what is "home" and what is "away". This article challenges the view, driven by much "brain drain" literature, that the dynamic is an…

Percolation and epidemics in a two-dimensional small world

NASA Astrophysics Data System (ADS)

Newman, M. E.; Jensen, I.; Ziff, R. M.

2002-02-01

Percolation on two-dimensional small-world networks has been proposed as a model for the spread of plant diseases. In this paper we give an analytic solution of this model using a combination of generating function methods and high-order series expansion. Our solution gives accurate predictions for quantities such as the position of the percolation threshold and the typical size of disease outbreaks as a function of the density of ``shortcuts'' in the small-world network. Our results agree with scaling hypotheses and numerical simulations for the same model.

Potts Model in One-Dimension on Directed Small-World Networks

NASA Astrophysics Data System (ADS)

Aquino, Édio O.; Lima, F. W. S.; Araújo, Ascânio D.; Costa Filho, Raimundo N.

2018-06-01

The critical properties of the Potts model with q=3 and 8 states in one-dimension on directed small-world networks are investigated. This disordered system is simulated by updating it with the Monte Carlo heat bath algorithm. The Potts model on these directed small-world networks presents in fact a second-order phase transition with a new set of critical exponents for q=3 considering a rewiring probability p=0.1. For q=8 the system exhibits only a first-order phase transition independent of p.

Credit Assignment in Multiple Goal Embodied Visuomotor Behavior

PubMed Central

Rothkopf, Constantin A.; Ballard, Dana H.

2010-01-01

The intrinsic complexity of the brain can lead one to set aside issues related to its relationships with the body, but the field of embodied cognition emphasizes that understanding brain function at the system level requires one to address the role of the brain-body interface. It has only recently been appreciated that this interface performs huge amounts of computation that does not have to be repeated by the brain, and thus affords the brain great simplifications in its representations. In effect the brain's abstract states can refer to coded representations of the world created by the body. But even if the brain can communicate with the world through abstractions, the severe speed limitations in its neural circuitry mean that vast amounts of indexing must be performed during development so that appropriate behavioral responses can be rapidly accessed. One way this could happen would be if the brain used a decomposition whereby behavioral primitives could be quickly accessed and combined. This realization motivates our study of independent sensorimotor task solvers, which we call modules, in directing behavior. The issue we focus on herein is how an embodied agent can learn to calibrate such individual visuomotor modules while pursuing multiple goals. The biologically plausible standard for module programming is that of reinforcement given during exploration of the environment. However this formulation contains a substantial issue when sensorimotor modules are used in combination: The credit for their overall performance must be divided amongst them. We show that this problem can be solved and that diverse task combinations are beneficial in learning and not a complication, as usually assumed. Our simulations show that fast algorithms are available that allot credit correctly and are insensitive to measurement noise. PMID:21833235

The emergence of mind and emotion in the evolution of neocortex.

PubMed

Freeman, Walter J

2011-01-01

The most deeply transformative concept for the growth of 21st Century psychiatry is the constellation of the chaotic dynamics of the brain. Brains are no longer seen as rational systems that are plagued with emotional disorders reflecting primitives inherited from our animal ancestors. Brains are dynamical systems that continually create patterns by acting intentionally into the environment and shaping themselves in accord with the sensory consequences of their intended actions. Emotions are now seen not as reversions to animal behaviors but as the sources of force and energy that brains require for the actions they take to understand the world and themselves. Humans are unique in experiencing consciousness of their own actions, which they experience as conscience: guilt, shame, pride and joy. Chaotic brain dynamics strives always for unity and harmony, but as a necessary condition for adaptation to a changing world, it repeatedly lapses into disorder. The successes are seen in the normal unity of consciousness; the failures are seen in the disorders that we rightly label the schizophrenias and the less severe character disorders. The foundation for healthy unity is revealed by studies in the evolution of brains, in particular the way in which neocortex of mammals emerged from the primitive allocortex of reptiles. The amazing facts of brain dynamics are now falling into several places. The power-law connectivity of cortex supports the scale-free dynamics of the global workspace in brains ranging from mouse to whale. That dynamics in humans holds the secrets of speech and symbol utilization. By recursive interactions in vast areas of human neocortex the scale-free connectivity supports our unified consciousness. Here in this dynamics are to be sought the keys to understanding and treating the disorders that uniquely plague the human mind.

Scale-free networks which are highly assortative but not small world

NASA Astrophysics Data System (ADS)

Small, Michael; Xu, Xiaoke; Zhou, Jin; Zhang, Jie; Sun, Junfeng; Lu, Jun-An

2008-06-01

Uncorrelated scale-free networks are necessarily small world (and, in fact, smaller than small world). Nonetheless, for scale-free networks with correlated degree distribution this may not be the case. We describe a mechanism to generate highly assortative scale-free networks which are not small world. We show that it is possible to generate scale-free networks, with arbitrary degree exponent γ>1 , such that the average distance between nodes in the network is large. To achieve this, nodes are not added to the network with preferential attachment. Instead, we greedily optimize the assortativity of the network. The network generation scheme is physically motivated, and we show that the recently observed global network of Avian Influenza outbreaks arises through a mechanism similar to what we present here. Simulations show that this network exhibits very similar physical characteristics (very high assortativity, clustering, and path length).

Long-Term Survival in a Patient with Multiple Brain Metastases from Small-Cell Lung Cancer Treated with Gamma Knife Radiosurgery on Four Occasions: A Case Report

PubMed Central

Elaimy, Ameer L.; Thumma, Sudheer R.; Lamm, Andrew F.; Mackay, Alexander R.; Lamoreaux, Wayne T.; Fairbanks, Robert K.; Demakas, John J.; Cooke, Barton S.; Lee, Christopher M.

2012-01-01

Brain metastases are the most common cancerous neoplasm in the brain. The treatment of these lesions is challenging and often includes a multimodality management approach with whole-brain radiation therapy, stereotactic radiosurgery, and neurosurgery options. Although advances in biomedical imaging technologies and the treatment of extracranial cancer have led to the overall increase in the survival of brain metastases patients, the finding that select patients survive several years remains puzzling. For this reason, we present the case of a 70-year-old patient who was diagnosed with multiple brain metastases from small-cell lung cancer five years ago and is currently alive following treatment with chemotherapy for the primary cancer and whole-brain radiation therapy and Gamma Knife radiosurgery on four separate occasions for the neurological cancer. Since the diagnosis of brain metastases five years ago, the patient's primary cancer has remained controlled. Furthermore, multiple repeat GKRS procedures provided this patient with high levels of local tumor control, which in combination with a stable primary cancer led to an extended period of survival and a highly functional life. Further analysis and clinical research will be valuable in assessing the durability of multiple GKRS for brain metastases patients who experience long-term survival. PMID:23091748

White matter hyperintensities of presumed vascular origin: a population-based study in rural Ecuador (The Atahualpa Project).

PubMed

Del Brutto, Oscar H; Mera, Robertino M; Del Brutto, Victor J; Zambrano, Mauricio; Lama, Julio

2015-04-01

Cerebral small vessel disease is probably one of the most common pathogenetic mechanisms underlying stroke in Latin America. However, the importance of silent markers of small vessel disease, including white matter hyperintensities of presumed vascular origin, has not been assessed so far. The study aims to evaluate prevalence and correlates of white matter hyperintensities in community-dwelling elders living in Atahualpa (rural Ecuador). Atahualpa residents aged ≥ 60 years were identified during a door-to-door survey and invited to undergo brain magnetic resonance imaging for identification and grading white matter hyperintensities and other markers of small vessel disease. Using multivariate logistic regression models, we evaluated whether white matter hyperintensities is associated with demographics, cardiovascular health status, stroke, cerebral microbleeds, and cortical atrophy, after adjusting for the other variables. Out of 258 enrolled persons (mean age, 70 ± 8 years; 59% women), 172 (67%) had white matter hyperintensities, which were moderate to severe in 63. Analyses showed significant associations of white matter hyperintensities presence and severity with age and cardiovascular health status, as well as with overt and silent strokes, and a trend for association with cerebral microbleeds and cortical atrophy. Prevalence and correlates of white matter hyperintensities in elders living in rural Ecuador is almost comparable with that reported from industrialized nations, reinforcing the concept that the burden of small vessel disease is on the rise in underserved Latin American populations. © 2014 World Stroke Organization.

Stable functional networks exhibit consistent timing in the human brain.

PubMed

Chapeton, Julio I; Inati, Sara K; Zaghloul, Kareem A

2017-03-01

Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate that cortical regions exhibit functional relationships with well-defined and consistent timing, and the stability of these relationships over multiple time scales suggests that these stable pathways may be reliably and repeatedly used for large-scale cortical communication. Published by Oxford University Press on behalf of the Guarantors of Brain 2017. This work is written by US Government employees and is in the public domain in the United States.

Brain metabolite differences in one-year-old infants born small at term and association with neurodevelopmental outcome.

PubMed

Simões, Rui V; Cruz-Lemini, Mónica; Bargalló, Núria; Gratacós, Eduard; Sanz-Cortés, Magdalena

2015-08-01

We assessed brain metabolite levels by magnetic resonance spectroscopy (MRS) in 1-year-old infants born small at term, as compared with infants born appropriate for gestational age (AGA), and their association with neurodevelopment at 2 years of age. A total of 40 infants born small (birthweight <10th centile for gestational age) and 30 AGA infants underwent brain MRS at age 1 year on a 3-T scanner. Small-born infants were subclassified as late intrauterine growth restriction or as small for gestational age, based on the presence or absence of prenatal Doppler and birthweight predictors of an adverse perinatal outcome, respectively. Single-voxel proton magnetic resonance spectroscopy ((1)H-MRS) data were acquired from the frontal lobe at short echo time. Neurodevelopment was evaluated at 2 years of age using the Bayley Scales of Infant and Toddler Development, Third Edition, assessing cognitive, language, motor, social-emotional, and adaptive behavior scales. As compared with AGA controls, infants born small showed significantly higher levels of glutamate and total N-acetylaspartate (NAAt) to creatine (Cr) ratio at age 1 year, and lower Bayley Scales of Infant and Toddler Development, Third Edition scores at 2 years. The subgroup with late intrauterine growth restriction further showed lower estimated glutathione levels at age 1 year. Significant correlations were observed for estimated glutathione levels with adaptive scores, and for myo-inositol with language scores. Significant associations were also noticed for NAA/Cr with cognitive scores, and for glutamate/Cr with motor scores. Infants born small show brain metabolite differences at 1 year of age, which are correlated with later neurodevelopment. These results support further research on MRS to develop imaging biomarkers of abnormal neurodevelopment. Copyright © 2015 Elsevier Inc. All rights reserved.

Tau burden and the functional connectome in Alzheimer's disease and progressive supranuclear palsy.

PubMed

Cope, Thomas E; Rittman, Timothy; Borchert, Robin J; Jones, P Simon; Vatansever, Deniz; Allinson, Kieren; Passamonti, Luca; Vazquez Rodriguez, Patricia; Bevan-Jones, W Richard; O'Brien, John T; Rowe, James B

2018-02-01

Alzheimer's disease and progressive supranuclear palsy (PSP) represent neurodegenerative tauopathies with predominantly cortical versus subcortical disease burden. In Alzheimer's disease, neuropathology and atrophy preferentially affect 'hub' brain regions that are densely connected. It was unclear whether hubs are differentially affected by neurodegeneration because they are more likely to receive pathological proteins that propagate trans-neuronally, in a prion-like manner, or whether they are selectively vulnerable due to a lack of local trophic factors, higher metabolic demands, or differential gene expression. We assessed the relationship between tau burden and brain functional connectivity, by combining in vivo PET imaging using the ligand AV-1451, and graph theoretic measures of resting state functional MRI in 17 patients with Alzheimer's disease, 17 patients with PSP, and 12 controls. Strongly connected nodes displayed more tau pathology in Alzheimer's disease, independently of intrinsic connectivity network, validating the predictions of theories of trans-neuronal spread but not supporting a role for metabolic demands or deficient trophic support in tau accumulation. This was not a compensatory phenomenon, as the functional consequence of increasing tau burden in Alzheimer's disease was a progressive weakening of the connectivity of these same nodes, reducing weighted degree and local efficiency and resulting in weaker 'small-world' properties. Conversely, in PSP, unlike in Alzheimer's disease, those nodes that accrued pathological tau were those that displayed graph metric properties associated with increased metabolic demand and a lack of trophic support rather than strong functional connectivity. Together, these findings go some way towards explaining why Alzheimer's disease affects large scale connectivity networks throughout cortex while neuropathology in PSP is concentrated in a small number of subcortical structures. Further, we demonstrate that in PSP increasing tau burden in midbrain and deep nuclei was associated with strengthened cortico-cortical functional connectivity. Disrupted cortico-subcortical and cortico-brainstem interactions meant that information transfer took less direct paths, passing through a larger number of cortical nodes, reducing closeness centrality and eigenvector centrality in PSP, while increasing weighted degree, clustering, betweenness centrality and local efficiency. Our results have wide-ranging implications, from the validation of models of tau trafficking in humans to understanding the relationship between regional tau burden and brain functional reorganization. © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain.

An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy

PubMed Central

Cardona, Albert; Saalfeld, Stephan; Preibisch, Stephan; Schmid, Benjamin; Cheng, Anchi; Pulokas, Jim; Tomancak, Pavel; Hartenstein, Volker

2010-01-01

The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile. PMID:20957184

Enhancing the Teaching of Digital Processing of Remote Sensing Image Course through Geospatial Web Processing Services

NASA Astrophysics Data System (ADS)

di, L.; Deng, M.

2010-12-01

Remote sensing (RS) is an essential method to collect data for Earth science research. Huge amount of remote sensing data, most of them in the image form, have been acquired. Almost all geography departments in the world offer courses in digital processing of remote sensing images. Such courses place emphasis on how to digitally process large amount of multi-source images for solving real world problems. However, due to the diversity and complexity of RS images and the shortcomings of current data and processing infrastructure, obstacles for effectively teaching such courses still remain. The major obstacles include 1) difficulties in finding, accessing, integrating and using massive RS images by students and educators, and 2) inadequate processing functions and computing facilities for students to freely explore the massive data. Recent development in geospatial Web processing service systems, which make massive data, computing powers, and processing capabilities to average Internet users anywhere in the world, promises the removal of the obstacles. The GeoBrain system developed by CSISS is an example of such systems. All functions available in GRASS Open Source GIS have been implemented as Web services in GeoBrain. Petabytes of remote sensing images in NASA data centers, the USGS Landsat data archive, and NOAA CLASS are accessible transparently and processable through GeoBrain. The GeoBrain system is operated on a high performance cluster server with large disk storage and fast Internet connection. All GeoBrain capabilities can be accessed by any Internet-connected Web browser. Dozens of universities have used GeoBrain as an ideal platform to support data-intensive remote sensing education. This presentation gives a specific example of using GeoBrain geoprocessing services to enhance the teaching of GGS 588, Digital Remote Sensing taught at the Department of Geography and Geoinformation Science, George Mason University. The course uses the textbook "Introductory Digital Image Processing, A Remote Sensing Perspective" authored by John Jensen. The textbook is widely adopted in the geography departments around the world for training students on digital processing of remote sensing images. In the traditional teaching setting for the course, the instructor prepares a set of sample remote sensing images to be used for the course. Commercial desktop remote sensing software, such as ERDAS, is used for students to do the lab exercises. The students have to do the excurses in the lab and can only use the simple images. For this specific course at GMU, we developed GeoBrain-based lab excurses for the course. With GeoBrain, students now can explore petabytes of remote sensing images in the NASA, NOAA, and USGS data archives instead of dealing only with sample images. Students have a much more powerful computing facility available for their lab excurses. They can explore the data and do the excurses any time at any place they want as long as they can access the Internet through the Web Browser. The feedbacks from students are all very positive about the learning experience on the digital image processing with the help of GeoBrain web processing services. The teaching/lab materials and GeoBrain services are freely available to anyone at http://www.laits.gmu.edu.

Sex Differences in Intelligence and Brain Size: A Developmental Theory.

ERIC Educational Resources Information Center

Lynn, Richard

1999-01-01

Proposes a developmental theory of sex differences in intelligence that states that the faster maturation and brain size growth in girls up to age 15 compensates for their smaller brain size so that sex differences in intelligence are very small. Discusses evidence that supports this theory. (SLD)

Dual Benefit of TGFB Inhibition on Tumor Control in the Context of Radiotherapy for Breast Cancer Brain Metastases

DTIC Science & Technology

This project evaluates whether TGF beta inhibition during radiation therapy (RT) to breast cancer brain metastases (BCBM) provides greater...TNBC) brain metastasis. We provided image guided radiotherapy (IGRT) to murine BCBM using the small animal radiation research platform (SARRP) and

Feasibility of task-specific brain-machine interface training for upper-extremity paralysis in patients with chronic hemiparetic stroke.

PubMed

Nishimoto, Atsuko; Kawakami, Michiyuki; Fujiwara, Toshiyuki; Hiramoto, Miho; Honaga, Kaoru; Abe, Kaoru; Mizuno, Katsuhiro; Ushiba, Junichi; Liu, Meigen

2018-01-10

Brain-machine interface training was developed for upper-extremity rehabilitation for patients with severe hemiparesis. Its clinical application, however, has been limited because of its lack of feasibility in real-world rehabilitation settings. We developed a new compact task-specific brain-machine interface system that enables task-specific training, including reach-and-grasp tasks, and studied its clinical feasibility and effectiveness for upper-extremity motor paralysis in patients with stroke. Prospective beforeâ€"after study. Twenty-six patients with severe chronic hemiparetic stroke. Participants were trained with the brain-machine interface system to pick up and release pegs during 40-min sessions and 40 min of standard occupational therapy per day for 10 days. Fugl-Meyer upper-extremity motor (FMA) and Motor Activity Log-14 amount of use (MAL-AOU) scores were assessed before and after the intervention. To test its feasibility, 4 occupational therapists who operated the system for the first time assessed it with the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) 2.0. FMA and MAL-AOU scores improved significantly after brain-machine interface training, with the effect sizes being medium and large, respectively (p<0.01, d=0.55; p<0.01, d=0.88). QUEST effectiveness and safety scores showed feasibility and satisfaction in the clinical setting. Our newly developed compact brain-machine interface system is feasible for use in real-world clinical settings.

Consciousness weaves our internal view of the outside world.

PubMed

Gur, Moshe

2016-01-01

Low-level consciousness is fundamental to our understanding of the world. Within the conscious field, the constantly changing external visual information is transformed into stable, object-based percepts. Remarkably, holistic objects are perceived while we are cognizant of all of the spatial details comprising the objects and of the relationship between individual elements. This parallel conscious association is unique to the brain. Conscious contributions to motor activity come after our understanding of the world has been established.

Impaired behavior on real-world tasks following damage to the ventromedial prefrontal cortex.

PubMed

Tranel, Daniel; Hathaway-Nepple, Julie; Anderson, Steven W

2007-04-01

Patients with damage to the ventromedial prefrontal cortices (VMPC) commonly manifest blatant behavioral navigation defects in the real world, but it has been difficult to measure these impairments in the clinic or laboratory. Using a set of "strategy application" tasks, which were designed by Shallice and Burgess (1991) to be ecologically valid for detecting executive dysfunction, we investigated the hypothesis that VMPC damage would be associated with defective performance on such tasks, whereas damage outside the VMPC region would not. A group of 9 patients with bilateral VMPC damage was contrasted with comparison groups of participants with (a) prefrontal brain damage outside the VMPC region (n = 8); (b) nonprefrontal brain damage (n = 17); and (c) no brain damage (n = 20). We found support for the hypothesis: VMPC patients had more impaired performances on the strategy application tasks, especially on a Multiple Errands Test that required patients to execute a series of unstructured tasks in a real-world setting (shopping mall). The results are consistent with the notion that efficacious behavioral navigation is dependent on the VMPC region. However, the strategy application tasks were relatively time consuming and effortful, and their diagnostic yield over and above conventional executive functioning tests may not be sufficient to warrant their inclusion in standard clinical assessment.

The Human Factors and Ergonomics of P300-Based Brain-Computer Interfaces

PubMed Central

Powers, J. Clark; Bieliaieva, Kateryna; Wu, Shuohao; Nam, Chang S.

2015-01-01

Individuals with severe neuromuscular impairments face many challenges in communication and manipulation of the environment. Brain-computer interfaces (BCIs) show promise in presenting real-world applications that can provide such individuals with the means to interact with the world using only brain waves. Although there has been a growing body of research in recent years, much relates only to technology, and not to technology in use—i.e., real-world assistive technology employed by users. This review examined the literature to highlight studies that implicate the human factors and ergonomics (HFE) of P300-based BCIs. We assessed 21 studies on three topics to speak directly to improving the HFE of these systems: (1) alternative signal evocation methods within the oddball paradigm; (2) environmental interventions to improve user performance and satisfaction within the constraints of current BCI systems; and (3) measures and methods of measuring user acceptance. We found that HFE is central to the performance of P300-based BCI systems, although researchers do not often make explicit this connection. Incorporation of measures of user acceptance and rigorous usability evaluations, increased engagement of disabled users as test participants, and greater realism in testing will help progress the advancement of P300-based BCI systems in assistive applications. PMID:26266424

Impaired behavior on real-world tasks following damage to the ventromedial prefrontal cortex

PubMed Central

Tranel, Daniel; Hathaway-Nepple, Julie; Anderson, Steven W.

2008-01-01

Patients with damage to the ventromedial prefrontal cortices (VMPC) commonly manifest blatant behavioral navigation defects in the real world, but it has been difficult to measure these impairments in the clinic or laboratory. Using a set of “strategy application” tasks, which were designed by Shallice and Burgess (1991) to be ecologically valid for detecting executive dysfunction, we investigated the hypothesis that VMPC damage would be associated with defective performance on such tasks, whereas damage outside the VMPC region would not. A group of 9 patients with bilateral VMPC damage was contrasted with comparison groups of participants with (a) prefrontal brain damage outside the VMPC region (n=8); (b) nonprefrontal brain damage (n=17); and (c) no brain damage (n=20). We found support for the hypothesis: VMPC patients had more impaired performances on the strategy application tasks, especially on a Multiple Errands Test that required patients to execute a series of unstructured tasks in a real-world setting (shopping mall). The results are consistent with the notion that efficacious behavioral navigation is dependent on the VMPC region. However, the strategy application tasks were relatively time consuming and effortful, and their diagnostic yield over and above conventional executive functioning tests may not be sufficient to warrant their inclusion in standard clinical assessment. PMID:17454352

[On the "Brain is the House of Yuanshen" in "Bencao Gangmu"; from Li Shizhen to Zhang Xichun].

PubMed

Okuno, Shigeo

2011-03-01

The phrase the "Brain is the House of Yuanshen" is used in "Bencao Gangmu" in order to explain the reason why magnolia flower is good for sinus problems; however, the ideas on the relationship between the brain and the nose originate from "Huangdi Neijing" and those on the relationship between the brain and Yuanshen come from Taoism. It was "Bencao Beiyao" that combined the theory with the Western idea that "someone's memory is in the brain". The idea of the brain staying on as memory had great impact on "Leizheng Zhicai" and "Yilin Gaicuo", but again in "Yixue Zhongzhong Sanxilu" it claimed that "Yuanshen is in the brain" from Taoism's point of view, and it criticized the theory of the brain derived from the Western world. In this paper, the meaning of "Brain is the House of Yuanshen" in "Bencao Gangmu" is examined, along with the influence this idea had on the subsequent theories of medicine.

Unimodular lattice triangulations as small-world and scale-free random graphs

NASA Astrophysics Data System (ADS)

Krüger, B.; Schmidt, E. M.; Mecke, K.

2015-02-01

Real-world networks, e.g., the social relations or world-wide-web graphs, exhibit both small-world and scale-free behaviour. We interpret lattice triangulations as planar graphs by identifying triangulation vertices with graph nodes and one-dimensional simplices with edges. Since these triangulations are ergodic with respect to a certain Pachner flip, applying different Monte Carlo simulations enables us to calculate average properties of random triangulations, as well as canonical ensemble averages, using an energy functional that is approximately the variance of the degree distribution. All considered triangulations have clustering coefficients comparable with real-world graphs; for the canonical ensemble there are inverse temperatures with small shortest path length independent of system size. Tuning the inverse temperature to a quasi-critical value leads to an indication of scale-free behaviour for degrees k≥slant 5. Using triangulations as a random graph model can improve the understanding of real-world networks, especially if the actual distance of the embedded nodes becomes important.

Welcome to Molecular Brain

PubMed Central

Mei, Lin; Cho, Kei; Lee, C Justin; Li, Xiao-Jiang; Zhuo, Min; Kaang, Bong-Kiun

2008-01-01

We are delighted to announce the arrival of a brand new journal dedicated to the ever-expanding field of neuroscience. Molecular Brain is a peer-reviewed, open-access online journal that aims at publishing high quality articles as rapidly as possible. The journal will cover a broad spectrum of neuroscience ranging from molecular/cellular to behavioral/cognitive neuroscience and from basic to clinical research. Molecular Brain will publish not only research articles, but also methodology articles, editorials, reviews, and short reports. It will be a premier platform for neuroscientists to exchange their ideas with researchers from around the world to help improve our understanding of the molecular mechanisms of the brain and mind. PMID:18803854

SU-E-T-457: Design and Characterization of An Economical 192Ir Hemi-Brain Small Animal Irradiator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grams, M; Wilson, Z; Sio, T

Purpose: To describe the design and dosimetric characterization of a simple and economical small animal irradiator. Methods: A high dose rate 192Ir brachytherapy source from a commercially available afterloader was used with a 1.3 centimeter thick tungsten collimator to provide sharp beam penumbra suitable for hemi-brain irradiation of mice. The unit is equipped with continuous gas anesthesia to allow robust animal immobilization. Dosimetric characterization of the device was performed with Gafchromic film. The penumbra from the small animal irradiator was compared under similar collimating conditions to the penumbra from 6 MV photons, 6 MeV electrons, and 20 MeV electrons frommore » a linear accelerator as well as 300 kVp photons from an orthovoltage unit and Monte Carlo simulated 90 MeV protons. Results: The tungsten collimator provides a sharp penumbra suitable for hemi-brain irradiation, and dose rates on the order of 200 cGy/minute were achieved. The sharpness of the penumbra attainable with this device compares favorably to those measured experimentally for 6 MV photons, and 6 and 20 MeV electron beams from a linear accelerator. Additionally, the penumbra was comparable to those measured for a 300 kVp orthovoltage beam and a Monte Carlo simulated 90 MeV proton beam. Conclusions: The small animal irradiator described here can be built for under $1,000 and used in conjunction with any commercial brachytherapy afterloader to provide a convenient and cost-effective option for small animal irradiation experiments. The unit offers high dose rate delivery and sharp penumbra, which is ideal for hemi-brain irradiation of mice. With slight modifications to the design, irradiation of sites other than the brain could be accomplished easily. Due to its simplicity and low cost, the apparatus described is an attractive alternative for small animal irradiation experiments requiring a sharp penumbra.« less

Topographic distribution of brain iron deposition and small cerebrovascular lesions in amyotrophic lateral sclerosis and in frontotemporal lobar degeneration: a post-mortem 7.0-tesla magnetic resonance imaging study with neuropathological correlates.

PubMed

De Reuck, Jacques; Devos, David; Moreau, Caroline; Auger, Florent; Durieux, Nicolas; Deramecourt, Vincent; Pasquier, Florence; Maurage, Claude-Alain; Cordonnier, Charlotte; Leys, Didier; Bordet, Regis

2017-12-01

Amyotrophic lateral sclerosis (ALS) is associated with frontotemporal lobar degeneration (FTLD) in 15% of the cases. A neuropathological continuity between ALS and FTLD-TDP is suspected. The present post-mortem 7.0-tesla magnetic resonance imaging (MRI) study compares the topographic distribution of iron (Fe) deposition and the incidence of small cerebrovascular lesions in ALS and in FTLD brains. Seventy-eight post-mortem brains underwent 7.0-tesla MRI. The patients consisted of 12 with ALS, 38 with FTLD, and 28 controls. Three ALS brains had minor FTLD features. Three coronal sections of a cerebral hemisphere were submitted to T2 and T2* MRI sequences. The amount of Fe deposition in the deep brain structures and the number of small cerebrovascular lesions was determined in ALS and the subtypes of FTLD compared to control brains, with neuropathological correlates. A significant increase of Fe deposition was observed in the claustrum, caudate nucleus, globus pallidus, thalamus, and subthalamic nucleus of the FTLD-FUS and FTLD-TDP groups, while in the ALS one, the Fe increase was only observed in the caudate and the subthalamic nuclei. White matter changes were only significantly more severe in the FTLD compared to those in ALS and in controls brains. Cortical micro-bleeds were increased in the frontal and temporal lobes of FTLD as well as of ALS brains compared to controls. Cortical micro-infarcts were, on the other hand, more frequent in the control compared to the ALS and FTLD groups. The present study supports the assumption of a neuropathological continuity between ALS and FTLD and illustrates the favourable vascular risk profile in these diseases.

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

Evolution and development of brain networks: from Caenorhabditis elegans to Homo sapiens.

PubMed

Kaiser, Marcus; Varier, Sreedevi

2011-01-01

Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints.

Suppression of phase synchronisation in network based on cat's brain.

PubMed

Lameu, Ewandson L; Borges, Fernando S; Borges, Rafael R; Iarosz, Kelly C; Caldas, Iberê L; Batista, Antonio M; Viana, Ricardo L; Kurths, Jürgen

2016-04-01

We have studied the effects of perturbations on the cat's cerebral cortex. According to the literature, this cortex structure can be described by a clustered network. This way, we construct a clustered network with the same number of areas as in the cat matrix, where each area is described as a sub-network with a small-world property. We focus on the suppression of neuronal phase synchronisation considering different kinds of perturbations. Among the various controlling interventions, we choose three methods: delayed feedback control, external time-periodic driving, and activation of selected neurons. We simulate these interventions to provide a procedure to suppress undesired and pathological abnormal rhythms that can be associated with many forms of synchronisation. In our simulations, we have verified that the efficiency of synchronisation suppression by delayed feedback control is higher than external time-periodic driving and activation of selected neurons of the cat's cerebral cortex with the same coupling strengths.

Art and brain: insights from neuropsychology, biology and evolution.

PubMed

Zaidel, Dahlia W

2010-02-01

Art is a uniquely human activity associated fundamentally with symbolic and abstract cognition. Its practice in human societies throughout the world, coupled with seeming non-functionality, has led to three major brain theories of art. (1) The localized brain regions and pathways theory links art to multiple neural regions. (2) The display of art and its aesthetics theory is tied to the biological motivation of courtship signals and mate selection strategies in animals. (3) The evolutionary theory links the symbolic nature of art to critical pivotal brain changes in Homo sapiens supporting increased development of language and hierarchical social grouping. Collectively, these theories point to art as a multi-process cognition dependent on diverse brain regions and on redundancy in art-related functional representation.

Art and brain: insights from neuropsychology, biology and evolution

PubMed Central

Zaidel, Dahlia W

2010-01-01

Art is a uniquely human activity associated fundamentally with symbolic and abstract cognition. Its practice in human societies throughout the world, coupled with seeming non-functionality, has led to three major brain theories of art. (1) The localized brain regions and pathways theory links art to multiple neural regions. (2) The display of art and its aesthetics theory is tied to the biological motivation of courtship signals and mate selection strategies in animals. (3) The evolutionary theory links the symbolic nature of art to critical pivotal brain changes in Homo sapiens supporting increased development of language and hierarchical social grouping. Collectively, these theories point to art as a multi-process cognition dependent on diverse brain regions and on redundancy in art-related functional representation. PMID:19490399

Effects of Breast Cancer Chemotherapy Agents on Brain Activity in Rats: Functional Imaging Studies

DTIC Science & Technology

2011-04-29

and in a small region of the striatum. Visual stimulation produced bilateral activation of the superior colliculus, lateral geniculate and a small...pattern was seen in the lateral geniculate . These results demonstrate the feasibility of using brain activation by parametric sensory stimulation as...both the right and left lateral geniculate functional ROIs (25% and 29%, respectively). There were smaller but not statistically significant decreases

Rebooting the Brain: Using Early Childhood Education to Heal Trauma from Abuse and Neglect

ERIC Educational Resources Information Center

McLintock, Ben

2011-01-01

Abused and neglected children live in a world that usually includes some sort of violence, chaos, and tremendous physical and mental stress. This toxic environment wreaks havoc on a child's developing brain. This article discusses how to use early childhood education to heal trauma from abuse and neglect. It shares the story of two children, Bryce…

A Grounded Theory Study of the Process of Accessing Information on the World Wide Web by People with Mild Traumatic Brain Injury

ERIC Educational Resources Information Center

Blodgett, Cynthia S.

2008-01-01

The purpose of this grounded theory study was to examine the process by which people with Mild Traumatic Brain Injury (MTBI) access information on the web. Recent estimates include amateur sports and recreation injuries, non-hospital clinics and treatment facilities, private and public emergency department visits and admissions, providing…

Failures of Sustained Attention in Life, Lab, and Brain: Ecological Validity of the SART

ERIC Educational Resources Information Center

Smilek, Daniel; Carriere, Jonathan S. A.; Cheyne, J. Allan

2010-01-01

The Sustained Attention to Response Task (SART) is a widely used tool in cognitive neuroscience increasingly employed to identify brain regions associated with failures of sustained attention. An important claim of the SART is that it is significantly related to real-world problems of sustained attention such as those experienced by TBI and ADHD…

The neurotechnological revolution: unlocking the brain's secrets to develop innovative technologies as well as treatments for neurological diseases.

PubMed

Banks, Jim

2015-01-01

The brain contains all that makes us human, but its complexity is the source of both inspiration and frailty. Aging population is increasingly in need of effective care and therapies for brain diseases, including stroke, Parkinson's disease and Alzheimer's disease. The world's scientific community working hard to unravel the secrets of the brain's computing power and to devise technologies that can heal it when it fails and restore critical functions to patients with neurological conditions. Neurotechnology is the emerging field that brings together the development of technologies to study the brain and devices that improve and repair brain function. What is certain is the momentum behind neurotechnological research is building, and whether through implants, BCIs, or innovative computational systems inspired by the human brain, more light will be shed on our most complex and most precious organ, which will no doubt lead to effective treatment for many neurological conditions.

Nanotherapeutic approaches for brain cancer management.

PubMed

Saenz del Burgo, Laura; Hernández, Rosa María; Orive, Gorka; Pedraz, Jose Luis

2014-07-01

Around the world, cancer remains one of the most important causes of morbidity and mortality. Worldwide, approximately 238,000 new cases of brain and other central nervous system tumors are diagnosed every year. Nanotherapeutic approaches hold tremendous potential for diagnosis and treatment of brain cancer, including the ability to target complex molecular cargoes to the tumor sites and the capacity of crossing the blood-brain barrier and accessing to the brain after systemic administration. A new generation of "smart" nanoparticles has been designed as novel targeted delivery devices for new therapies including gene therapy, anti-angiogenic and thermotherapy. This review highlights the latest research, opportunities and challenges for developing novel nanotherapeutics for treating brain cancers. This comprehensive review highlights the latest research results, opportunities and challenges for developing novel nanotherapeutics for treating brain cancers, with a special focus on "smart" nanoparticles as novel targeted delivery devices for new therapies including gene therapy, anti-angiogenic therapy and localized thermotherapy. © 2014.

Brains studying brains: look before you think in vision

NASA Astrophysics Data System (ADS)

Zhaoping, Li

2016-06-01

Using our own brains to study our brains is extraordinary. For example, in vision this makes us naturally blind to our own blindness, since our impression of seeing our world clearly is consistent with our ignorance of what we do not see. Our brain employs its ‘conscious’ part to reason and make logical deductions using familiar rules and past experience. However, human vision employs many ‘subconscious’ brain parts that follow rules alien to our intuition. Our blindness to our unknown unknowns and our presumptive intuitions easily lead us astray in asking and formulating theoretical questions, as witnessed in many unexpected and counter-intuitive difficulties and failures encountered by generations of scientists. We should therefore pay a more than usual amount of attention and respect to experimental data when studying our brain. I show that this can be productive by reviewing two vision theories that have provided testable predictions and surprising insights.

Brains studying brains: look before you think in vision.

PubMed

Zhaoping, Li

2016-05-11

Using our own brains to study our brains is extraordinary. For example, in vision this makes us naturally blind to our own blindness, since our impression of seeing our world clearly is consistent with our ignorance of what we do not see. Our brain employs its 'conscious' part to reason and make logical deductions using familiar rules and past experience. However, human vision employs many 'subconscious' brain parts that follow rules alien to our intuition. Our blindness to our unknown unknowns and our presumptive intuitions easily lead us astray in asking and formulating theoretical questions, as witnessed in many unexpected and counter-intuitive difficulties and failures encountered by generations of scientists. We should therefore pay a more than usual amount of attention and respect to experimental data when studying our brain. I show that this can be productive by reviewing two vision theories that have provided testable predictions and surprising insights.

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Impact of Hypoglycemia on Brain Metabolism During Diabetes.

PubMed

Rehni, Ashish K; Dave, Kunjan R

2018-04-10

Diabetes is a metabolic disease afflicting millions of people worldwide. A substantial fraction of world's total healthcare expenditure is spent on treating diabetes. Hypoglycemia is a serious consequence of anti-diabetic drug therapy, because it induces metabolic alterations in the brain. Metabolic alterations are one of the central mechanisms mediating hypoglycemia-related functional changes in the brain. Acute, chronic, and/or recurrent hypoglycemia modulate multiple metabolic pathways, and exposure to hypoglycemia increases consumption of alternate respiratory substrates such as ketone bodies, glycogen, and monocarboxylates in the brain. The aim of this review is to discuss hypoglycemia-induced metabolic alterations in the brain in glucose counterregulation, uptake, utilization and metabolism, cellular respiration, amino acid and lipid metabolism, and the significance of other sources of energy. The present review summarizes information on hypoglycemia-induced metabolic changes in the brain of diabetic and non-diabetic subjects and the manner in which they may affect brain function.

ZIKV – CDB: A Collaborative Database to Guide Research Linking SncRNAs and ZIKA Virus Disease Symptoms

PubMed Central

Morais, Daniel Kumazawa; Cuadros-Orellana, Sara; Pais, Fabiano Sviatopolk-Mirsky; Medeiros, Julliane Dutra; Geraldo, Juliana Assis; Gilbert, Jack; Volpini, Angela Cristina; Fernandes, Gabriel Rocha

2016-01-01

Background In early 2015, a ZIKA Virus (ZIKV) infection outbreak was recognized in northeast Brazil, where concerns over its possible links with infant microcephaly have been discussed. Providing a causal link between ZIKV infection and birth defects is still a challenge. MicroRNAs (miRNAs) are small noncoding RNAs (sncRNAs) that regulate post-transcriptional gene expression by translational repression, and play important roles in viral pathogenesis and brain development. The potential for flavivirus-mediated miRNA signalling dysfunction in brain-tissue development provides a compelling hypothesis to test the perceived link between ZIKV and microcephaly. Methodology/Principal Findings Here, we applied in silico analyses to provide novel insights to understand how Congenital ZIKA Syndrome symptoms may be related to an imbalance in miRNAs function. Moreover, following World Health Organization (WHO) recommendations, we have assembled a database to help target investigations of the possible relationship between ZIKV symptoms and miRNA-mediated human gene expression. Conclusions/Significance We have computationally predicted both miRNAs encoded by ZIKV able to target genes in the human genome and cellular (human) miRNAs capable of interacting with ZIKV genomes. Our results represent a step forward in the ZIKV studies, providing new insights to support research in this field and identify potential targets for therapy. PMID:27332714