R7-binding protein targets the G protein β5/R7-regulator of G protein signaling complex to lipid rafts in neuronal cells and brain

Directory of Open Access Journals (Sweden)

Zhang Jian-Hua

2007-09-01

Full Text Available Abstract Background Heterotrimeric guanine nucleotide-binding regulatory proteins (G proteins, composed of Gα, Gβ, and Gγ subunits, are positioned at the inner face of the plasma membrane and relay signals from activated G protein-coupled cell surface receptors to various signaling pathways. Gβ5 is the most structurally divergent Gβ isoform and forms tight heterodimers with regulator of G protein signalling (RGS proteins of the R7 subfamily (R7-RGS. The subcellular localization of Gβ 5/R7-RGS protein complexes is regulated by the palmitoylation status of the associated R7-binding protein (R7BP, a recently discovered SNARE-like protein. We investigate here whether R7BP controls the targeting of Gβ5/R7-RGS complexes to lipid rafts, cholesterol-rich membrane microdomains where conventional heterotrimeric G proteins and some effector proteins are concentrated in neurons and brain. Results We show that endogenous Gβ5/R7-RGS/R7BP protein complexes are present in native neuron-like PC12 cells and that a fraction is targeted to low-density, detergent-resistant membrane lipid rafts. The buoyant density of endogenous raft-associated Gβ5/R7-RGS protein complexes in PC12 cells was similar to that of lipid rafts containing the palmitoylated marker proteins PSD-95 and LAT, but distinct from that of the membrane microdomain where flotillin was localized. Overexpression of wild-type R7BP, but not its palmitoylation-deficient mutant, greatly enriched the fraction of endogenous Gβ5/R7-RGS protein complexes in the lipid rafts. In HEK-293 cells the palmitoylation status of R7BP also regulated the lipid raft targeting of co-expressed Gβ5/R7-RGS/R7BP proteins. A fraction of endogenous Gβ5/R7-RGS/R7BP complexes was also present in lipid rafts in mouse brain. Conclusion A fraction of Gβ5/R7-RGS/R7BP protein complexes is targeted to low-density, detergent-resistant membrane lipid rafts in PC12 cells and brain. In cultured cells, the palmitoylation status of

Preliminary study of Alzheimer's Disease diagnosis based on brain electrical signals using wireless EEG

Science.gov (United States)

Handayani, N.; Akbar, Y.; Khotimah, S. N.; Haryanto, F.; Arif, I.; Taruno, W. P.

2016-03-01

This research aims to study brain's electrical signals recorded using EEG as a basis for the diagnosis of patients with Alzheimer's Disease (AD). The subjects consisted of patients with AD, and normal subjects are used as the control. Brain signals are recorded for 3 minutes in a relaxed condition and with eyes closed. The data is processed using power spectral analysis, brain mapping and chaos test to observe the level of complexity of EEG's data. The results show a shift in the power spectral in the low frequency band (delta and theta) in AD patients. The increase of delta and theta occurs in lobus frontal area and lobus parietal respectively. However, there is a decrease of alpha activity in AD patients where in the case of normal subjects with relaxed condition, brain alpha wave dominates the posterior area. This is confirmed by the results of brain mapping. While the results of chaos analysis show that the average value of MMLE is lower in AD patients than in normal subjects. The level of chaos associated with neural complexity in AD patients with lower neural complexity is due to neuronal damage caused by the beta amyloid plaques and tau protein in neurons.

Silent communication: toward using brain signals.

Science.gov (United States)

Pei, Xiaomei; Hill, Jeremy; Schalk, Gerwin

2012-01-01

From the 1980s movie Firefox to the more recent Avatar, popular science fiction has speculated about the possibility of a persons thoughts being read directly from his or her brain. Such braincomputer interfaces (BCIs) might allow people who are paralyzed to communicate with and control their environment, and there might also be applications in military situations wherever silent user-to-user communication is desirable. Previous studies have shown that BCI systems can use brain signals related to movements and movement imagery or attention-based character selection. Although these systems have successfully demonstrated the possibility to control devices using brain function, directly inferring which word a person intends to communicate has been elusive. A BCI using imagined speech might provide such a practical, intuitive device. Toward this goal, our studies to date addressed two scientific questions: (1) Can brain signals accurately characterize different aspects of speech? (2) Is it possible to predict spoken or imagined words or their components using brain signals?

Hyaluronan activates Hyal-2/WWOX/Smad4 signaling and causes bubbling cell death when the signaling complex is overexpressed.

Science.gov (United States)

Hsu, Li-Jin; Hong, Qunying; Chen, Shur-Tzu; Kuo, Hsiang-Lin; Schultz, Lori; Heath, John; Lin, Sing-Ru; Lee, Ming-Hui; Li, Dong-Zhang; Li, Zih-Ling; Cheng, Hui-Ching; Armand, Gerard; Chang, Nan-Shan

2017-03-21

Malignant cancer cells frequently secrete significant amounts of transforming growth factor beta (TGF-β), hyaluronan (HA) and hyaluronidases to facilitate metastasizing to target organs. In a non-canonical signaling, TGF-β binds membrane hyaluronidase Hyal-2 for recruiting tumor suppressors WWOX and Smad4, and the resulting Hyal-2/WWOX/Smad4 complex is accumulated in the nucleus to enhance SMAD-promoter dependent transcriptional activity. Yeast two-hybrid analysis showed that WWOX acts as a bridge to bind both Hyal-2 and Smad4. When WWOX-expressing cells were stimulated with high molecular weight HA, an increased formation of endogenous Hyal-2/WWOX/Smad4 complex occurred rapidly, followed by relocating to the nuclei in 20-40 min. In WWOX-deficient cells, HA failed to induce Smad2/3/4 relocation to the nucleus. To prove the signaling event, we designed a real time tri-molecular FRET analysis and revealed that HA induces the signaling pathway from ectopic Smad4 to WWOX and finally to p53, as well as from Smad4 to Hyal-2 and then to WWOX. An increased binding of the Smad4/Hyal-2/WWOX complex occurs with time in the nucleus that leads to bubbling cell death. In contrast, HA increases the binding of Smad4/WWOX/p53, which causes membrane blebbing but without cell death. In traumatic brain injury-induced neuronal death, the Hyal-2/WWOX complex was accumulated in the apoptotic nuclei of neurons in the rat brains in 24 hr post injury, as determined by immunoelectron microscopy. Together, HA activates the Hyal-2/WWOX/Smad4 signaling and causes bubbling cell death when the signaling complex is overexpressed.

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping

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Bin Wang

2017-11-01

Full Text Available Alzheimer's disease (AD is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs, 33 early MCI (EMCI, 32 late MCI (LMCI, and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ scores and global Clinical Dementia Rating (CDR scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE

Hyaluronan activates Hyal-2/WWOX/Smad4 signaling and causes bubbling cell death when the signaling complex is overexpressed

Science.gov (United States)

Hsu, Li-Jin; Hong, Qunying; Chen, Shur-Tzu; Kuo, Hsiang-Lin; Schultz, Lori; Heath, John; Lin, Sing-Ru; Lee, Ming-Hui; Li, Dong-Zhang; Li, Zih-Ling; Cheng, Hui-Ching; Armand, Gerard; Chang, Nan-Shan

2017-01-01

Malignant cancer cells frequently secrete significant amounts of transforming growth factor beta (TGF-β), hyaluronan (HA) and hyaluronidases to facilitate metastasizing to target organs. In a non-canonical signaling, TGF-β binds membrane hyaluronidase Hyal-2 for recruiting tumor suppressors WWOX and Smad4, and the resulting Hyal-2/WWOX/Smad4 complex is accumulated in the nucleus to enhance SMAD-promoter dependent transcriptional activity. Yeast two-hybrid analysis showed that WWOX acts as a bridge to bind both Hyal-2 and Smad4. When WWOX-expressing cells were stimulated with high molecular weight HA, an increased formation of endogenous Hyal-2/WWOX/Smad4 complex occurred rapidly, followed by relocating to the nuclei in 20-40 min. In WWOX-deficient cells, HA failed to induce Smad2/3/4 relocation to the nucleus. To prove the signaling event, we designed a real time tri-molecular FRET analysis and revealed that HA induces the signaling pathway from ectopic Smad4 to WWOX and finally to p53, as well as from Smad4 to Hyal-2 and then to WWOX. An increased binding of the Smad4/Hyal-2/WWOX complex occurs with time in the nucleus that leads to bubbling cell death. In contrast, HA increases the binding of Smad4/WWOX/p53, which causes membrane blebbing but without cell death. In traumatic brain injury-induced neuronal death, the Hyal-2/WWOX complex was accumulated in the apoptotic nuclei of neurons in the rat brains in 24 hr post injury, as determined by immunoelectron microscopy. Together, HA activates the Hyal-2/WWOX/Smad4 signaling and causes bubbling cell death when the signaling complex is overexpressed. PMID:27845895

Cerebral insulin, insulin signaling pathway, and brain angiogenesis.

Science.gov (United States)

Zeng, Yi; Zhang, Le; Hu, Zhiping

2016-01-01

Insulin performs unique non-metabolic functions within the brain. Broadly speaking, two major areas of these functions are those related to brain endothelial cells and the blood-brain barrier (BBB) function, and those related to behavioral effects, like cognition in disease states (Alzheimer's disease, AD) and in health. Recent studies showed that both these functions are associated with brain angiogenesis. These findings raise interesting questions such as how they are linked to each other and whether modifying brain angiogenesis by targeting certain insulin signaling pathways could be an effective strategy to treat dementia as in AD, or even to help secure healthy longevity. The two canonical downstream pathways involved in mediating the insulin signaling pathway, the phosphoinositide-3 kinase (PI3K), and mitogen-activated protein kinase (MAPK) cascades, in the brain are supposed to be similar to those in the periphery. PI3K and MAPK pathways play important roles in angiogenesis. Both are involved in stimulating hypoxia inducible factor (HIF) in angiogenesis and could be activated by the insulin signaling pathway. This suggests that PI3K and MAPK pathways might act as cross-talk between the insulin signaling pathway and the angiogenesis pathway in brain. But the cerebral insulin, insulin signaling pathway, and the detailed mechanism in the connection of insulin signaling pathway, brain angiogenesis pathway, and healthy aging or dementias are still mostly not clear and need further studies.

FGF signaling is required for brain left-right asymmetry and brain midline formation.

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Neugebauer, Judith M; Yost, H Joseph

2014-02-01

Early disruption of FGF signaling alters left-right (LR) asymmetry throughout the embryo. Here we uncover a role for FGF signaling that specifically disrupts brain asymmetry, independent of normal lateral plate mesoderm (LPM) asymmetry. When FGF signaling is inhibited during mid-somitogenesis, asymmetrically expressed LPM markers southpaw and lefty2 are not affected. However, asymmetrically expressed brain markers lefty1 and cyclops become bilateral. We show that FGF signaling controls expression of six3b and six7, two transcription factors required for repression of asymmetric lefty1 in the brain. We found that Z0-1, atypical PKC (aPKC) and β-catenin protein distribution revealed a midline structure in the forebrain that is dependent on a balance of FGF signaling. Ectopic activation of FGF signaling leads to overexpression of six3b, loss of organized midline adherins junctions and bilateral loss of lefty1 expression. Reducing FGF signaling leads to a reduction in six3b and six7 expression, an increase in cell boundary formation in the brain midline, and bilateral expression of lefty1. Together, these results suggest a novel role for FGF signaling in the brain to control LR asymmetry, six transcription factor expressions, and a midline barrier structure. Copyright © 2013 Elsevier Inc. All rights reserved.

Sapphire implant based neuro-complex for deep-lying brain tumors phototheranostics

Science.gov (United States)

Sharova, A. S.; Maklygina, YU S.; Yusubalieva, G. M.; Shikunova, I. A.; Kurlov, V. N.; Loschenov, V. B.

2018-01-01

The neuro-complex as a combination of sapphire implant optical port and osteoplastic biomaterial "Collapan" as an Aluminum phthalocyanine nanoform photosensitizer (PS) depot was developed within the framework of this study. The main goals of such neuro-complex are to provide direct access of laser radiation to the brain tissue depth and to transfer PS directly to the pathological tissue location that will allow multiple optical phototheranostics of the deep-lying tumor region without repeated surgical intervention. The developed complex spectral-optical properties research was carried out by photodiagnostics method using the model sample: a brain tissue phantom. The optical transparency of sapphire implant allows obtaining a fluorescent signal with high accuracy, comparable to direct measurement "in contact" with the tissue.

GABAergic interneuron to astrocyte signalling: a neglected form of cell communication in the brain.

Science.gov (United States)

Losi, Gabriele; Mariotti, Letizia; Carmignoto, Giorgio

2014-10-19

GABAergic interneurons represent a minority of all cortical neurons and yet they efficiently control neural network activities in all brain areas. In parallel, glial cell astrocytes exert a broad control of brain tissue homeostasis and metabolism, modulate synaptic transmission and contribute to brain information processing in a dynamic interaction with neurons that is finely regulated in time and space. As most studies have focused on glutamatergic neurons and excitatory transmission, our knowledge of functional interactions between GABAergic interneurons and astrocytes is largely defective. Here, we critically discuss the currently available literature that hints at a potential relevance of this specific signalling in brain function. Astrocytes can respond to GABA through different mechanisms that include GABA receptors and transporters. GABA-activated astrocytes can, in turn, modulate local neuronal activity by releasing gliotransmitters including glutamate and ATP. In addition, astrocyte activation by different signals can modulate GABAergic neurotransmission. Full clarification of the reciprocal signalling between different GABAergic interneurons and astrocytes will improve our understanding of brain network complexity and has the potential to unveil novel therapeutic strategies for brain disorders. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Close relationship between fMRI signals and transient heart rate changes accompanying K-complex. Simultaneous EEG/fMRI study

International Nuclear Information System (INIS)

Kan, Shigeyuki; Koike, Takahiko; Miyauchi, Satoru; Misaki, Masaya

2009-01-01

Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) allows the investigation of spontaneous activities in the human brain. Recently, by using this technique, increases in fMRI signal accompanying transient EEG activities such as sleep spindles and slow waves were reported. Although these fMRI signal increases appear to arise as a result of the neural activities being reflected in the EEG, when the influence of physiological activities upon fMRI signals are taken into consideration, it is highly controversial that fMRI signal increases accompanying transient EEG activities reflect actual neural activities. In the present study, we conducted simultaneous fMRI and polysomnograph recording of 18 normal adults, to study the effect of transient heart rate changes after a K-complex on fMRI signals. Significant fMRI signal increase was observed in the cerebellum, the ventral thalamus, the dorsal part of the brainstem, the periventricular white matter and the ventricle (quadrigeminal cistern). On the other hand, significant fMRI signal decrease was observed only in the right insula. Moreover, intensities of fMRI signal increase that was accompanied by a K-complex correlated positively with the magnitude of heart rate changes after a K-complex. Previous studies have reported that K-complex is closely related with sympathetic nervous activity and that the attributes of perfusion regulation in the brain differ during wakefulness and sleep. By taking these findings into consideration, our present results indicate that a close relationship exists between a K-complex and the changes in cardio- and neurovascular regulations that are mediated by the autonomic nervous system during sleep; further, these results indicate that transient heart rate changes after a K-complex can affect the fMRI signal generated in certain brain regions. (author)

Preliminary study of Alzheimer's Disease diagnosis based on brain electrical signals using wireless EEG

International Nuclear Information System (INIS)

Handayani, N; Akbar, Y; Khotimah, S N; Haryanto, F; Arif, I; Taruno, W P

2016-01-01

This research aims to study brain's electrical signals recorded using EEG as a basis for the diagnosis of patients with Alzheimer's Disease (AD). The subjects consisted of patients with AD, and normal subjects are used as the control. Brain signals are recorded for 3 minutes in a relaxed condition and with eyes closed. The data is processed using power spectral analysis, brain mapping and chaos test to observe the level of complexity of EEG's data. The results show a shift in the power spectral in the low frequency band (delta and theta) in AD patients. The increase of delta and theta occurs in lobus frontal area and lobus parietal respectively. However, there is a decrease of alpha activity in AD patients where in the case of normal subjects with relaxed condition, brain alpha wave dominates the posterior area. This is confirmed by the results of brain mapping. While the results of chaos analysis show that the average value of MMLE is lower in AD patients than in normal subjects. The level of chaos associated with neural complexity in AD patients with lower neural complexity is due to neuronal damage caused by the beta amyloid plaques and tau protein in neurons. (paper)

Bio-Signal Complexity Analysis in Epileptic Seizure Monitoring: A Topic Review

Directory of Open Access Journals (Sweden)

Zhenning Mei

2018-05-01

Full Text Available Complexity science has provided new perspectives and opportunities for understanding a variety of complex natural or social phenomena, including brain dysfunctions like epilepsy. By delving into the complexity in electrophysiological signals and neuroimaging, new insights have emerged. These discoveries have revealed that complexity is a fundamental aspect of physiological processes. The inherent nonlinearity and non-stationarity of physiological processes limits the methods based on simpler underlying assumptions to point out the pathway to a more comprehensive understanding of their behavior and relation with certain diseases. The perspective of complexity may benefit both the research and clinical practice through providing novel data analytics tools devoted for the understanding of and the intervention about epilepsies. This review aims to provide a sketchy overview of the methods derived from different disciplines lucubrating to the complexity of bio-signals in the field of epilepsy monitoring. Although the complexity of bio-signals is still not fully understood, bundles of new insights have been already obtained. Despite the promising results about epileptic seizure detection and prediction through offline analysis, we are still lacking robust, tried-and-true real-time applications. Multidisciplinary collaborations and more high-quality data accessible to the whole community are needed for reproducible research and the development of such applications.

Analysis of the Influence of Complexity and Entropy of Odorant on Fractal Dynamics and Entropy of EEG Signal

OpenAIRE

Hamidreza Namazi; Amin Akrami; Sina Nazeri; Vladimir V. Kulish

2016-01-01

An important challenge in brain research is to make out the relation between the features of olfactory stimuli and the electroencephalogram (EEG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the EEG signal. This study investigates the relation between the structures of EEG signal and the olfactory stimulus (odorant). We show that the complexity of the EEG signal is coupled with the molecular complexity of the odorant, where more structurally ...

The sleeping brain as a complex system.

Science.gov (United States)

Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas

2011-10-13

'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.

BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology.

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Matthew Caldwell

Full Text Available Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time.

Brain-computer interfaces increase whole-brain signal to noise.

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Papageorgiou, T Dorina; Lisinski, Jonathan M; McHenry, Monica A; White, Jason P; LaConte, Stephen M

2013-08-13

Brain-computer interfaces (BCIs) can convert mental states into signals to drive real-world devices, but it is not known if a given covert task is the same when performed with and without BCI-based control. Using a BCI likely involves additional cognitive processes, such as multitasking, attention, and conflict monitoring. In addition, it is challenging to measure the quality of covert task performance. We used whole-brain classifier-based real-time functional MRI to address these issues, because the method provides both classifier-based maps to examine the neural requirements of BCI and classification accuracy to quantify the quality of task performance. Subjects performed a covert counting task at fast and slow rates to control a visual interface. Compared with the same task when viewing but not controlling the interface, we observed that being in control of a BCI improved task classification of fast and slow counting states. Additional BCI control increased subjects' whole-brain signal-to-noise ratio compared with the absence of control. The neural pattern for control consisted of a positive network comprised of dorsal parietal and frontal regions and the anterior insula of the right hemisphere as well as an expansive negative network of regions. These findings suggest that real-time functional MRI can serve as a platform for exploring information processing and frontoparietal and insula network-based regulation of whole-brain task signal-to-noise ratio.

Brain Network Analysis from High-Resolution EEG Signals

Science.gov (United States)

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

On a possible mechanism of the brain for responding to dynamical features extracted from input signals

International Nuclear Information System (INIS)

Liu Zengrong; Chen Guanrong

2003-01-01

Based on the general theory of nonlinear dynamical systems, a possible mechanism for responding to some dynamical features extracted from input signals in brain activities is described and discussed. This mechanism is first converted to a nonlinear dynamical configuration--a generalized synchronization of complex dynamical systems. Then, some general conditions for achieving such synchronizations are derived. It is shown that dynamical systems have potentials of producing different responses for different features extracted from various input signals, which may be used to describe brain activities. For illustration, some numerical examples are given with simulation figures

Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan

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Jianxin Dong

2018-02-01

Full Text Available Exploring functional information among various brain regions across time enables understanding of healthy aging process and holds great promise for age-related brain disease diagnosis. This paper proposed a method to explore fractal complexity of the resting-state functional magnetic resonance imaging (rs-fMRI signal in the human brain across the adult lifespan using Hurst exponent (HE. We took advantage of the examined rs-fMRI data from 116 adults 19 to 85 years of age (44.3 ± 19.4 years, 49 females from NKI/Rockland sample. Region-wise and voxel-wise analyses were performed to investigate the effects of age, gender, and their interaction on complexity. In region-wise analysis, we found that the healthy aging is accompanied by a loss of complexity in frontal and parietal lobe and increased complexity in insula, limbic, and temporal lobe. Meanwhile, differences in HE between genders were found to be significant in parietal lobe (p = 0.04, corrected. However, there was no interaction between gender and age. In voxel-wise analysis, the significant complexity decrease with aging was found in frontal and parietal lobe, and complexity increase was found in insula, limbic lobe, occipital lobe, and temporal lobe with aging. Meanwhile, differences in HE between genders were found to be significant in frontal, parietal, and limbic lobe. Furthermore, we found age and sex interaction in right parahippocampal gyrus (p = 0.04, corrected. Our findings reveal HE variations of the rs-fMRI signal across the human adult lifespan and show that HE may serve as a new parameter to assess healthy aging process.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

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

Science.gov (United States)

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.

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

2017-01-01

aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

Science.gov (United States)

Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi

2017-10-01

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A Signal-Interleaving Complex Bandpass Sigma-Delta Converter

DEFF Research Database (Denmark)

Wad, Paul Emmanuel

1997-01-01

Complex or quadrature Sigma-Delta converters operate on complex signals, i.e. signals consisting of a real and an imaginary component, whereas conventional converters operate only on real signals. The advantage of complex signal processing in the discrete-time domain is that the entire sampling...

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

Science.gov (United States)

Eugster, Manuel J. A.; Ruotsalo, Tuukka; Spapé, Michiel M.; Barral, Oswald; Ravaja, Niklas; Jacucci, Giulio; Kaski, Samuel

2016-01-01

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications. PMID:27929077

Fast attainment of computer cursor control with noninvasively acquired brain signals

Science.gov (United States)

Bradberry, Trent J.; Gentili, Rodolphe J.; Contreras-Vidal, José L.

2011-06-01

Brain-computer interface (BCI) systems are allowing humans and non-human primates to drive prosthetic devices such as computer cursors and artificial arms with just their thoughts. Invasive BCI systems acquire neural signals with intracranial or subdural electrodes, while noninvasive BCI systems typically acquire neural signals with scalp electroencephalography (EEG). Some drawbacks of invasive BCI systems are the inherent risks of surgery and gradual degradation of signal integrity. A limitation of noninvasive BCI systems for two-dimensional control of a cursor, in particular those based on sensorimotor rhythms, is the lengthy training time required by users to achieve satisfactory performance. Here we describe a novel approach to continuously decoding imagined movements from EEG signals in a BCI experiment with reduced training time. We demonstrate that, using our noninvasive BCI system and observational learning, subjects were able to accomplish two-dimensional control of a cursor with performance levels comparable to those of invasive BCI systems. Compared to other studies of noninvasive BCI systems, training time was substantially reduced, requiring only a single session of decoder calibration (~20 min) and subject practice (~20 min). In addition, we used standardized low-resolution brain electromagnetic tomography to reveal that the neural sources that encoded observed cursor movement may implicate a human mirror neuron system. These findings offer the potential to continuously control complex devices such as robotic arms with one's mind without lengthy training or surgery.

Chansporter complexes in cell signaling.

Science.gov (United States)

Abbott, Geoffrey W

2017-09-01

Ion channels facilitate diffusion of ions across cell membranes for such diverse purposes as neuronal signaling, muscular contraction, and fluid homeostasis. Solute transporters often utilize ionic gradients to move aqueous solutes up their concentration gradient, also fulfilling a wide variety of tasks. Recently, an increasing number of ion channel-transporter ('chansporter') complexes have been discovered. Chansporter complex formation may overcome what could otherwise be considerable spatial barriers to rapid signal integration and feedback between channels and transporters, the ions and other substrates they transport, and environmental factors to which they must respond. Here, current knowledge in this field is summarized, covering both heterologous expression structure/function findings and potential mechanisms by which chansporter complexes fulfill contrasting roles in cell signaling in vivo. © 2017 Federation of European Biochemical Societies.

Molecular Mechanisms of Cannabis Signaling in the Brain.

Science.gov (United States)

Ronan, Patrick J; Wongngamnit, Narin; Beresford, Thomas P

2016-01-01

Cannabis has been cultivated and used by humans for thousands of years. Research for decades was focused on understanding the mechanisms of an illegal/addictive drug. This led to the discovery of the vast endocannabinoid system. Research has now shifted to understanding fundamental biological questions related to one of the most widespread signaling systems in both the brain and the body. Our understanding of cannabinoid signaling has advanced significantly in the last two decades. In this review, we discuss the state of knowledge on mechanisms of Cannabis signaling in the brain and the modulation of key brain neurotransmitter systems involved in both brain reward/addiction and psychiatric disorders. It is highly probable that various cannabinoids will be found to be efficacious in the treatment of a number of psychiatric disorders. However, while there is clearly much potential, marijuana has not been properly vetted by the medical-scientific evaluation process and there are clearly a range of potentially adverse side-effects-including addiction. We are at crossroads for research on endocannabinoid function and therapeutics (including the use of exogenous treatments such as Cannabis). With over 100 cannabinoid constituents, the majority of which have not been studied, there is much Cannabis research yet to be done. With more states legalizing both the medicinal and recreational use of marijuana the rigorous scientific investigation into cannabinoid signaling is imperative. Copyright © 2016. Published by Elsevier Inc.

Neuron-astrocyte signaling is preserved in the aging brain.

Science.gov (United States)

Gómez-Gonzalo, Marta; Martin-Fernandez, Mario; Martínez-Murillo, Ricardo; Mederos, Sara; Hernández-Vivanco, Alicia; Jamison, Stephanie; Fernandez, Ana P; Serrano, Julia; Calero, Pilar; Futch, Hunter S; Corpas, Rubén; Sanfeliu, Coral; Perea, Gertrudis; Araque, Alfonso

2017-04-01

Astrocytes play crucial roles in brain homeostasis and are emerging as regulatory elements of neuronal and synaptic physiology by responding to neurotransmitters with Ca 2+ elevations and releasing gliotransmitters that activate neuronal receptors. Aging involves neuronal and astrocytic alterations, being considered risk factor for neurodegenerative diseases. Most evidence of the astrocyte-neuron signaling is derived from studies with young animals; however, the features of astrocyte-neuron signaling in adult and aging brain remain largely unknown. We have investigated the existence and properties of astrocyte-neuron signaling in physiologically and pathologically aging mouse hippocampal and cortical slices at different lifetime points (0.5 to 20 month-old animals). We found that astrocytes preserved their ability to express spontaneous and neurotransmitter-dependent intracellular Ca 2+ signals from juvenile to aging brains. Likewise, resting levels of gliotransmission, assessed by neuronal NMDAR activation by glutamate released from astrocytes, were largely preserved with similar properties in all tested age groups, but DHPG-induced gliotransmission was reduced in aged mice. In contrast, gliotransmission was enhanced in the APP/PS1 mouse model of Alzheimer's disease, indicating a dysregulation of astrocyte-neuron signaling in pathological conditions. Disruption of the astrocytic IP 3 R2 mediated-signaling, which is required for neurotransmitter-induced astrocyte Ca 2+ signals and gliotransmission, boosted the progression of amyloid plaque deposits and synaptic plasticity impairments in APP/PS1 mice at early stages of the disease. Therefore, astrocyte-neuron interaction is a fundamental signaling, largely conserved in the adult and aging brain of healthy animals, but it is altered in Alzheimer's disease, suggesting that dysfunctions of astrocyte Ca 2+ physiology may contribute to this neurodegenerative disease. GLIA 2017 GLIA 2017;65:569-580. © 2017 Wiley

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms.

Science.gov (United States)

Liu, Rensong; Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K -nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance.

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

Science.gov (United States)

Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K-nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance. PMID:28874909

Canonical TGF-β Signaling Negatively Regulates Neuronal Morphogenesis through TGIF/Smad Complex-Mediated CRMP2 Suppression.

Science.gov (United States)

Nakashima, Hideyuki; Tsujimura, Keita; Irie, Koichiro; Ishizu, Masataka; Pan, Miao; Kameda, Tomonori; Nakashima, Kinichi

2018-05-16

Functional neuronal connectivity requires proper neuronal morphogenesis and its dysregulation causes neurodevelopmental diseases. Transforming growth factor-β (TGF-β) family cytokines play pivotal roles in development, but little is known about their contribution to morphological development of neurons. Here we show that the Smad-dependent canonical signaling of TGF-β family cytokines negatively regulates neuronal morphogenesis during brain development. Mechanistically, activated Smads form a complex with transcriptional repressor TG-interacting factor (TGIF), and downregulate the expression of a neuronal polarity regulator, collapsin response mediator protein 2. We also demonstrate that TGF-β family signaling inhibits neurite elongation of human induced pluripotent stem cell-derived neurons. Furthermore, the expression of TGF-β receptor 1, Smad4, or TGIF, which have mutations found in patients with neurodevelopmental disorders, disrupted neuronal morphogenesis in both mouse (male and female) and human (female) neurons. Together, these findings suggest that the regulation of neuronal morphogenesis by an evolutionarily conserved function of TGF-β signaling is involved in the pathogenesis of neurodevelopmental diseases. SIGNIFICANCE STATEMENT Canonical transforming growth factor-β (TGF-β) signaling plays a crucial role in multiple organ development, including brain, and mutations in components of the signaling pathway associated with several human developmental disorders. In this study, we found that Smads/TG-interacting factor-dependent canonical TGF-β signaling regulates neuronal morphogenesis through the suppression of collapsin response mediator protein-2 (CRMP2) expression during brain development, and that function of this signaling is evolutionarily conserved in the mammalian brain. Mutations in canonical TGF-β signaling factors identified in patients with neurodevelopmental disorders disrupt the morphological development of neurons. Thus, our

Discovering Patterns in Brain Signals Using Decision Trees

Directory of Open Access Journals (Sweden)

Narusci S. Bastos

2016-01-01

Full Text Available Even with emerging technologies, such as Brain-Computer Interfaces (BCI systems, understanding how our brains work is a very difficult challenge. So we propose to use a data mining technique to help us in this task. As a case of study, we analyzed the brain’s behaviour of blind people and sighted people in a spatial activity. There is a common belief that blind people compensate their lack of vision using the other senses. If an object is given to sighted people and we asked them to identify this object, probably the sense of vision will be the most determinant one. If the same experiment was repeated with blind people, they will have to use other senses to identify the object. In this work, we propose a methodology that uses decision trees (DT to investigate the difference of how the brains of blind people and people with vision react against a spatial problem. We choose the DT algorithm because it can discover patterns in the brain signal, and its presentation is human interpretable. Our results show that using DT to analyze brain signals can help us to understand the brain’s behaviour.

Generate the scale-free brain music from BOLD signals.

Science.gov (United States)

Lu, Jing; Guo, Sijia; Chen, Mingming; Wang, Weixia; Yang, Hua; Guo, Daqing; Yao, Dezhong

2018-01-01

Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

Lactate transport and signaling in the brain

DEFF Research Database (Denmark)

Bergersen, Linda Hildegard

2015-01-01

AMP. The localization and function of HCAR1 and the three MCTs (MCT1, MCT2, and MCT4) expressed in brain constitute the focus of this review. They are possible targets for new therapeutic drugs and interventions. The author proposes that lactate actions in the brain through MCTs and the lactate receptor underlie part......Lactate acts as a ‘buffer’ between glycolysis and oxidative metabolism. In addition to being exchanged as a fuel by the monocarboxylate transporters (MCTs) between cells and tissues with different glycolytic and oxidative rates, lactate may be a ‘volume transmitter’ of brain signals. According...... to some, lactate is a preferred fuel for brain metabolism. Immediately after brain activation, the rate of glycolysis exceeds oxidation, leading to net production of lactate. At physical rest, there is a net efflux of lactate from the brain into the blood stream. But when blood lactate levels rise...

Astrocyte calcium signal and gliotransmission in human brain tissue.

Science.gov (United States)

Navarrete, Marta; Perea, Gertrudis; Maglio, Laura; Pastor, Jesús; García de Sola, Rafael; Araque, Alfonso

2013-05-01

Brain function is recognized to rely on neuronal activity and signaling processes between neurons, whereas astrocytes are generally considered to play supportive roles for proper neuronal function. However, accumulating evidence indicates that astrocytes sense and control neuronal and synaptic activity, indicating that neuron and astrocytes reciprocally communicate. While this evidence has been obtained in experimental animal models, whether this bidirectional signaling between astrocytes and neurons occurs in human brain remains unknown. We have investigated the existence of astrocyte-neuron communication in human brain tissue, using electrophysiological and Ca(2+) imaging techniques in slices of the cortex and hippocampus obtained from biopsies from epileptic patients. Cortical and hippocampal human astrocytes displayed spontaneous Ca(2+) elevations that were independent of neuronal activity. Local application of transmitter receptor agonists or nerve electrical stimulation transiently elevated Ca(2+) in astrocytes, indicating that human astrocytes detect synaptic activity and respond to synaptically released neurotransmitters, suggesting the existence of neuron-to-astrocyte communication in human brain tissue. Electrophysiological recordings in neurons revealed the presence of slow inward currents (SICs) mediated by NMDA receptor activation. The frequency of SICs increased after local application of ATP that elevated astrocyte Ca(2+). Therefore, human astrocytes are able to release the gliotransmitter glutamate, which affect neuronal excitability through activation of NMDA receptors in neurons. These results reveal the existence of reciprocal signaling between neurons and astrocytes in human brain tissue, indicating that astrocytes are relevant in human neurophysiology and are involved in human brain function.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

Science.gov (United States)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Early Life Experience and Gut Microbiome: The Brain-Gut-Microbiota Signaling System.

Science.gov (United States)

Cong, Xiaomei; Henderson, Wendy A; Graf, Joerg; McGrath, Jacqueline M

2015-10-01

Over the past decades, advances in neonatal care have led to substantial increases in survival among preterm infants. With these gains, recent concerns have focused on increases in neurodevelopment morbidity related to the interplay between stressful early life experiences and the immature neuroimmune systems. This interplay between these complex mechanisms is often described as the brain-gut signaling system. The role of the gut microbiome and the brain-gut signaling system have been found to be remarkably related to both short- and long-term stress and health. Recent evidence supports that microbial species, ligands, and/or products within the developing intestine play a key role in early programming of the central nervous system and regulation of the intestinal innate immunity. The purpose of this state-of-the-science review is to explore the supporting evidence demonstrating the importance of the brain-gut-microbiota axis in regulation of early life experience. We also discuss the role of gut microbiome in modulating stress and pain responses in high-risk infants. A conceptual framework has been developed to illustrate the regulation mechanisms involved in early life experience. The science in this area is just beginning to be uncovered; having a fundamental understanding of these relationships will be important as new discoveries continue to change our thinking, leading potentially to changes in practice and targeted interventions.

Regulation of brain insulin signaling: A new function for tau.

Science.gov (United States)

Gratuze, Maud; Planel, Emmanuel

2017-08-07

In this issue of JEM, Marciniak et al. (https://doi.org/10.1084/jem.20161731) identify a putative novel function of tau protein as a regulator of insulin signaling in the brain. They find that tau deletion impairs hippocampal response to insulin through IRS-1 and PTEN dysregulation and suggest that, in Alzheimer's disease, impairment of brain insulin signaling might occur via tau loss of function. © 2017 Gratuze and Planel.

Astrocyte Ca2+ signalling: an unexpected complexity

OpenAIRE

Volterra, Andrea; Liaudet, Nicolas; Savtchouk, Iaroslav

2014-01-01

Astrocyte Ca(2+) signalling has been proposed to link neuronal information in different spatial-temporal dimensions to achieve a higher level of brain integration. However, some discrepancies in the results of recent studies challenge this view and highlight key insufficiencies in our current understanding. In parallel, new experimental approaches that enable the study of astrocyte physiology at higher spatial-temporal resolution in intact brain preparations are beginning to reveal an unexpec...

Spontaneous brain network activity: Analysis of its temporal complexity

Directory of Open Access Journals (Sweden)

Mangor Pedersen

2017-06-01

Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

Prenatal Alcohol Exposure Damages Brain Signal Transduction Systems

National Research Council Canada - National Science Library

Caldwell, Kevin

2001-01-01

.... One and twenty-four hours following fear conditioning this learning deficit is associated with altered brain signal transduction mechanisms that are dependent on an enzyme termed phosphatidylinositol...

Tutorial: Signal Processing in Brain-Computer Interfaces

NARCIS (Netherlands)

Garcia Molina, G.

2010-01-01

Research in Electroencephalogram (EEG) based Brain-Computer Interfaces (BCIs) has been considerably expanding during the last few years. Such an expansion owes to a large extent to the multidisciplinary and challenging nature of BCI research. Signal processing undoubtedly constitutes an essential

Brain Signal Variability Differentially Affects Cognitive Flexibility and Cognitive Stability.

Science.gov (United States)

Armbruster-Genç, Diana J N; Ueltzhöffer, Kai; Fiebach, Christian J

2016-04-06

Recent research yielded the intriguing conclusion that, in healthy adults, higher levels of variability in neuronal processes are beneficial for cognitive functioning. Beneficial effects of variability in neuronal processing can also be inferred from neurocomputational theories of working memory, albeit this holds only for tasks requiring cognitive flexibility. However, cognitive stability, i.e., the ability to maintain a task goal in the face of irrelevant distractors, should suffer under high levels of brain signal variability. To directly test this prediction, we studied both behavioral and brain signal variability during cognitive flexibility (i.e., task switching) and cognitive stability (i.e., distractor inhibition) in a sample of healthy human subjects and developed an efficient and easy-to-implement analysis approach to assess BOLD-signal variability in event-related fMRI task paradigms. Results show a general positive effect of neural variability on task performance as assessed by accuracy measures. However, higher levels of BOLD-signal variability in the left inferior frontal junction area result in reduced error rate costs during task switching and thus facilitate cognitive flexibility. In contrast, variability in the same area has a detrimental effect on cognitive stability, as shown in a negative effect of variability on response time costs during distractor inhibition. This pattern was mirrored at the behavioral level, with higher behavioral variability predicting better task switching but worse distractor inhibition performance. Our data extend previous results on brain signal variability by showing a differential effect of brain signal variability that depends on task context, in line with predictions from computational theories. Recent neuroscientific research showed that the human brain signal is intrinsically variable and suggested that this variability improves performance. Computational models of prefrontal neural networks predict differential

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

Science.gov (United States)

Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

2015-05-15

We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

Artifact suppression and analysis of brain activities with electroencephalography signals.

Science.gov (United States)

Rashed-Al-Mahfuz, Md; Islam, Md Rabiul; Hirose, Keikichi; Molla, Md Khademul Islam

2013-06-05

Brain-computer interface is a communication system that connects the brain with computer (or other devices) but is not dependent on the normal output of the brain (i.e., peripheral nerve and muscle). Electro-oculogram is a dominant artifact which has a significant negative influence on further analysis of real electroencephalography data. This paper presented a data adaptive technique for artifact suppression and brain wave extraction from electroencephalography signals to detect regional brain activities. Empirical mode decomposition based adaptive thresholding approach was employed here to suppress the electro-oculogram artifact. Fractional Gaussian noise was used to determine the threshold level derived from the analysis data without any training. The purified electroencephalography signal was composed of the brain waves also called rhythmic components which represent the brain activities. The rhythmic components were extracted from each electroencephalography channel using adaptive wiener filter with the original scale. The regional brain activities were mapped on the basis of the spatial distribution of rhythmic components, and the results showed that different regions of the brain are activated in response to different stimuli. This research analyzed the activities of a single rhythmic component, alpha with respect to different motor imaginations. The experimental results showed that the proposed method is very efficient in artifact suppression and identifying individual motor imagery based on the activities of alpha component.

Astrocyte Sodium Signalling and Panglial Spread of Sodium Signals in Brain White Matter.

Science.gov (United States)

Moshrefi-Ravasdjani, Behrouz; Hammel, Evelyn L; Kafitz, Karl W; Rose, Christine R

2017-09-01

In brain grey matter, excitatory synaptic transmission activates glutamate uptake into astrocytes, inducing sodium signals which propagate into neighboring astrocytes through gap junctions. These sodium signals have been suggested to serve an important role in neuro-metabolic coupling. So far, it is unknown if astrocytes in white matter-that is in brain regions devoid of synapses-are also able to undergo such intra- and intercellular sodium signalling. In the present study, we have addressed this question by performing quantitative sodium imaging in acute tissue slices of mouse corpus callosum. Focal application of glutamate induced sodium transients in SR101-positive astrocytes. These were largely unaltered in the presence of ionotropic glutamate receptors blockers, but strongly dampened upon pharmacological inhibition of glutamate uptake. Sodium signals induced in individual astrocytes readily spread into neighboring SR101-positive cells with peak amplitudes decaying monoexponentially with distance from the stimulated cell. In addition, spread of sodium was largely unaltered during pharmacological inhibition of purinergic and glutamate receptors, indicating gap junction-mediated, passive diffusion of sodium between astrocytes. Using cell-type-specific, transgenic reporter mice, we found that sodium signals also propagated, albeit less effectively, from astrocytes to neighboring oligodendrocytes and NG2 cells. Again, panglial spread was unaltered with purinergic and glutamate receptors blocked. Taken together, our results demonstrate that activation of sodium-dependent glutamate transporters induces sodium signals in white matter astrocytes, which spread within the astrocyte syncytium. In addition, we found a panglial passage of sodium signals from astrocytes to NG2 cells and oligodendrocytes, indicating functional coupling between these macroglial cells in white matter.

Complex brain networks: From topological communities to clustered

Indian Academy of Sciences (India)

Complex brain networks: From topological communities to clustered dynamics ... Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. ... Pramana – Journal of Physics | News.

Brain insulin signaling and Alzheimer's disease: current evidence and future directions.

Science.gov (United States)

Schiöth, Helgi B; Craft, Suzanne; Brooks, Samantha J; Frey, William H; Benedict, Christian

2012-08-01

Insulin receptors in the brain are found in high densities in the hippocampus, a region that is fundamentally involved in the acquisition, consolidation, and recollection of new information. Using the intranasal method, which effectively bypasses the blood-brain barrier to deliver and target insulin directly from the nose to the brain, a series of experiments involving healthy humans has shown that increased central nervous system (CNS) insulin action enhances learning and memory processes associated with the hippocampus. Since Alzheimer's disease (AD) is linked to CNS insulin resistance, decreased expression of insulin and insulin receptor genes and attenuated permeation of blood-borne insulin across the blood-brain barrier, impaired brain insulin signaling could partially account for the cognitive deficits associated with this disease. Considering that insulin mitigates hippocampal synapse vulnerability to amyloid beta and inhibits the phosphorylation of tau, pharmacological strategies bolstering brain insulin signaling, such as intranasal insulin, could have significant therapeutic potential to deter AD pathogenesis.

Deficient brain insulin signalling pathway in Alzheimer’s disease and diabetes

Science.gov (United States)

Liu, Ying; Liu, Fei; Grundke-Iqbal, Inge; Iqbal, Khalid; Gong, Cheng-Xin

2015-01-01

Brain glucose metabolism is impaired in Alzheimer’s disease (AD), the most common form of dementia. Type 2 diabetes mellitus (T2DM) is reported to increase the risk for dementia, including AD, but the underlying mechanism is not understood. Here, we investigated the brain insulin–PI3K–AKT signalling pathway in the autopsied frontal cortices from nine AD, 10 T2DM, eight T2DM–AD and seven control cases. We found decreases in the levels and activities of several components of the insulin–PI3K–AKT signalling pathway in AD and T2DM cases. The deficiency of insulin–PI3K–AKT signalling was more severe in individuals with both T2DM and AD (T2DM–AD). This decrease in insulin–PI3K–AKT signalling could lead to activation of glycogen synthase kinase-3β, the major tau kinase. The levels and the activation of the insulin–PI3K–AKT signalling components correlated negatively with the level of tau phosphorylation and positively with protein O-GlcNAcylation, suggesting that impaired insulin–PI3K–AKT signalling might contribute to neurodegeneration in AD through down-regulation of O-GlcNAcylation and the consequent promotion of abnormal tau hyperphosphorylation and neurodegeneration. The decrease in brain insulin–PI3K–AKT signalling also correlated with the activation of calpain I in the brain, suggesting that the decrease might be caused by calpain over-activation. Our findings provide novel insight into the molecular mechanism by which type 2 diabetes mellitus increases the risk for developing cognitive impairment and dementia in Alzheimer’s disease. PMID:21598254

Does Global Astrocytic Calcium Signaling Participate in Awake Brain State Transitions and Neuronal Circuit Function?

DEFF Research Database (Denmark)

Kjaerby, Celia; Rasmussen, Rune; Andersen, Mie

2017-01-01

of the neuromodulators, noradrenaline and acetylcholine. Astrocytes have emerged as a new player participating in the regulation of brain activity, and have recently been implicated in brain state shifts. Astrocytes display global Ca(2+) signaling in response to activation of the noradrenergic system, but whether...... astrocytic Ca(2+) signaling is causative or correlative for shifts in brain state and neural activity patterns is not known. Here we review the current available literature on astrocytic Ca(2+) signaling in awake animals in order to explore the role of astrocytic signaling in brain state shifts. Furthermore......We continuously need to adapt to changing conditions within our surrounding environment, and our brain needs to quickly shift between resting and working activity states in order to allow appropriate behaviors. These global state shifts are intimately linked to the brain-wide release...

The role of insulin receptor signaling in the brain.

Science.gov (United States)

Plum, Leona; Schubert, Markus; Brüning, Jens C

2005-03-01

The insulin receptor (IR) is expressed in various regions of the developing and adult brain, and its functions have become the focus of recent research. Insulin enters the central nervous system (CNS) through the blood-brain barrier by receptor-mediated transport to regulate food intake, sympathetic activity and peripheral insulin action through the inhibition of hepatic gluconeogenesis and reproductive endocrinology. On a molecular level, some of the effects of insulin converge with those of the leptin signaling machinery at the point of activation of phosphatidylinositol 3-kinase (PI3K), resulting in the regulation of ATP-dependent potassium channels. Furthermore, insulin inhibits neuronal apoptosis via activation of protein kinase B in vitro, and it regulates phosphorylation of tau, metabolism of the amyloid precursor protein and clearance of beta-amyloid from the brain in vivo. These findings indicate that neuronal IR signaling has a direct role in the link between energy homeostasis, reproduction and the development of neurodegenerative diseases.

Emotion Walking for Humanoid Avatars Using Brain Signals

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Ahmad Hoirul Basori

2013-01-01

Full Text Available Interaction between humans and humanoid avatar representations is very important in virtual reality and robotics, since the humanoid avatar can represent either a human or a robot in a virtual environment. Many researchers have focused on providing natural interactions for humanoid avatars or even for robots with the use of camera tracking, gloves, giving them the ability to speak, brain interfaces and other devices. This paper provides a new multimodal interaction control for avatars by combining brain signals, facial muscle tension recognition and glove tracking to change the facial expression of humanoid avatars according to the user's emotional condition. The signals from brain activity and muscle movements are used as the emotional stimulator, while the glove acts as emotion intensity control for the avatar. This multimodal interface can determine when the humanoid avatar needs to change their facial expression or their walking power. The results show that humanoid avatar have different timelines of walking and facial expressions when the user stimulates them with different emotions. This finding is believed to provide new knowledge on controlling robots' and humanoid avatars' facial expressions and walking.

Unsupervised classification of operator workload from brain signals

Science.gov (United States)

Schultze-Kraft, Matthias; Dähne, Sven; Gugler, Manfred; Curio, Gabriel; Blankertz, Benjamin

2016-06-01

Objective. In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Approach. Subjects executed a task on a touch screen that required continuous effort of visual and motor processing with alternating difficulty. We first employed classical approaches for workload state classification that operate on the sensor space of EEG and compared those to the performance of three state-of-the-art spatial filtering methods: common spatial patterns (CSPs) analysis, which requires binary label information; source power co-modulation (SPoC) analysis, which uses the subjects’ error rate as a target function; and canonical SPoC (cSPoC) analysis, which solely makes use of cross-frequency power correlations induced by different states of workload and thus represents an unsupervised approach. Finally, we investigated the effects of fusing brain signals and peripheral physiological measures (PPMs) and examined the added value for improving classification performance. Main results. Mean classification accuracies of 94%, 92% and 82% were achieved with CSP, SPoC, cSPoC, respectively. These methods outperformed the approaches that did not use spatial filtering and they extracted physiologically plausible components. The performance of the unsupervised cSPoC is significantly increased by augmenting it with PPM features. Significance. Our analyses ensured that the signal sources used for classification were of cortical origin and not contaminated with artifacts. Our findings show that workload states can be successfully differentiated from brain signals, even when less and less information from the experimental paradigm is used, thus paving the way for real-world applications in which label information may be noisy or entirely unavailable.

Complex modular structure of large-scale brain networks

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Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

2009-06-01

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

Notching on cancer’s door: Notch signaling in brain tumors

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Marcin eTeodorczyk

2015-01-01

Full Text Available Notch receptors play an essential role in the regulation of central cellular processes during embryonic and postnatal development. The mammalian genome encodes for four Notch paralogs (Notch 1-4, which are activated by three Delta-like (Dll1/3/4 and two Serrate-like (Jagged1/2 ligands. Further, non-canonical Notch ligands such as EGFL7 have been identified and serve mostly as antagonists of Notch signaling. The Notch pathway prevents neuronal differentiation in the central nervous system by driving neural stem cell maintenance and commitment of neural progenitor cells into the glial lineage. Notch is therefore often implicated in the development of brain tumors, as tumor cells share various characteristics with neural stem and progenitor cells. Notch receptors are overexpressed in gliomas and their oncogenicity has been confirmed by gain- and loss-of-function studies in vitro and in vivo. To this end, special attention is paid to the impact of Notch signaling on stem-like brain tumor-propagating cells as these cells contribute to growth, survival, invasion and recurrence of brain tumors. Based on the outcome of ongoing studies in vivo, Notch-directed therapies such as γ secretase inhibitors and blocking antibodies have entered and completed various clinical trials. This review summarizes the current knowledge on Notch signaling in brain tumor formation and therapy.

Gut-Brain Glucose Signaling in Energy Homeostasis.

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Soty, Maud; Gautier-Stein, Amandine; Rajas, Fabienne; Mithieux, Gilles

2017-06-06

Intestinal gluconeogenesis is a recently identified function influencing energy homeostasis. Intestinal gluconeogenesis induced by specific nutrients releases glucose, which is sensed by the nervous system surrounding the portal vein. This initiates a signal positively influencing parameters involved in glucose control and energy management controlled by the brain. This knowledge has extended our vision of the gut-brain axis, classically ascribed to gastrointestinal hormones. Our work raises several questions relating to the conditions under which intestinal gluconeogenesis proceeds and may provide its metabolic benefits. It also leads to questions on the advantage conferred by its conservation through a process of natural selection. Copyright © 2017 Elsevier Inc. All rights reserved.

OPTIMAL REPRESENTATION OF MER SIGNALS APPLIED TO THE IDENTIFICATION OF BRAIN STRUCTURES DURING DEEP BRAIN STIMULATION

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Hernán Darío Vargas Cardona

2015-07-01

Full Text Available Identification of brain signals from microelectrode recordings (MER is a key procedure during deep brain stimulation (DBS applied in Parkinson’s disease patients. The main purpose of this research work is to identify with high accuracy a brain structure called subthalamic nucleus (STN, since it is the target structure where the DBS achieves the best therapeutic results. To do this, we present an approach for optimal representation of MER signals through method of frames. We obtain coefficients that minimize the Euclidean norm of order two. From optimal coefficients, we extract some features from signals combining the wavelet packet and cosine dictionaries. For a comparison frame with the state of the art, we also process the signals using the discrete wavelet transform (DWT with several mother functions. We validate the proposed methodology in a real data base. We employ simple supervised machine learning algorithms, as the K-Nearest Neighbors classifier (K-NN, a linear Bayesian classifier (LDC and a quadratic Bayesian classifier (QDC. Classification results obtained with the proposed method improves significantly the performance of the DWT. We achieve a positive identification of the STN superior to 97,6%. Identification outcomes achieved by the MOF are highly accurate, as we can potentially get a false positive rate of less than 2% during the DBS.

Causal Mathematical Logic as a guiding framework for the prediction of "Intelligence Signals" in brain simulations

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Lanzalaco, Felix; Pissanetzky, Sergio

2013-12-01

A recent theory of physical information based on the fundamental principles of causality and thermodynamics has proposed that a large number of observable life and intelligence signals can be described in terms of the Causal Mathematical Logic (CML), which is proposed to encode the natural principles of intelligence across any physical domain and substrate. We attempt to expound the current definition of CML, the "Action functional" as a theory in terms of its ability to possess a superior explanatory power for the current neuroscientific data we use to measure the mammalian brains "intelligence" processes at its most general biophysical level. Brain simulation projects define their success partly in terms of the emergence of "non-explicitly programmed" complex biophysical signals such as self-oscillation and spreading cortical waves. Here we propose to extend the causal theory to predict and guide the understanding of these more complex emergent "intelligence Signals". To achieve this we review whether causal logic is consistent with, can explain and predict the function of complete perceptual processes associated with intelligence. Primarily those are defined as the range of Event Related Potentials (ERP) which include their primary subcomponents; Event Related Desynchronization (ERD) and Event Related Synchronization (ERS). This approach is aiming for a universal and predictive logic for neurosimulation and AGi. The result of this investigation has produced a general "Information Engine" model from translation of the ERD and ERS. The CML algorithm run in terms of action cost predicts ERP signal contents and is consistent with the fundamental laws of thermodynamics. A working substrate independent natural information logic would be a major asset. An information theory consistent with fundamental physics can be an AGi. It can also operate within genetic information space and provides a roadmap to understand the live biophysical operation of the phenotype

Fasting and Systemic Insulin Signaling Regulate Phosphorylation of Brain Proteins That Modulate Cell Morphology and Link to Neurological Disorders*

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Li, Min; Quan, Chao; Toth, Rachel; Campbell, David G.; MacKintosh, Carol; Wang, Hong Yu; Chen, Shuai

2015-01-01

Diabetes is strongly associated with cognitive decline, but the molecular reasons are unknown. We found that fasting and peripheral insulin promote phosphorylation and dephosphorylation, respectively, of specific residues on brain proteins including cytoskeletal regulators such as slit-robo GTPase-activating protein 3 (srGAP3) and microtubule affinity-regulating protein kinases (MARKs), in which deficiency or dysregulation is linked to neurological disorders. Fasting activates protein kinase A (PKA) but not PKB/Akt signaling in the brain, and PKA can phosphorylate the purified srGAP3. The phosphorylation of srGAP3 and MARKs were increased when PKA signaling was activated in primary neurons. Knockdown of PKA decreased the phosphorylation of srGAP3. Furthermore, WAVE1, a protein kinase A-anchoring protein, formed a complex with srGAP3 and PKA in the brain of fasted mice to facilitate the phosphorylation of srGAP3 by PKA. Although brain cells have insulin receptors, our findings are inconsistent with the down-regulation of phosphorylation of target proteins being mediated by insulin signaling within the brain. Rather, our findings infer that systemic insulin, through a yet unknown mechanism, inhibits PKA or protein kinase(s) with similar specificity and/or activates an unknown phosphatase in the brain. Ser858 of srGAP3 was identified as a key regulatory residue in which phosphorylation by PKA enhanced the GAP activity of srGAP3 toward its substrate, Rac1, in cells, thereby inhibiting the action of this GTPase in cytoskeletal regulation. Our findings reveal novel mechanisms linking peripheral insulin sensitivity with cytoskeletal remodeling in neurons, which may help to explain the association of diabetes with neurological disorders such as Alzheimer disease. PMID:26499801

Modulation of EEG Theta Band Signal Complexity by Music Therapy

Science.gov (United States)

Bhattacharya, Joydeep; Lee, Eun-Jeong

The primary goal of this study was to investigate the impact of monochord (MC) sounds, a type of archaic sounds used in music therapy, on the neural complexity of EEG signals obtained from patients undergoing chemotherapy. The secondary goal was to compare the EEG signal complexity values for monochords with those for progressive muscle relaxation (PMR), an alternative therapy for relaxation. Forty cancer patients were randomly allocated to one of the two relaxation groups, MC and PMR, over a period of six months; continuous EEG signals were recorded during the first and last sessions. EEG signals were analyzed by applying signal mode complexity, a measure of complexity of neuronal oscillations. Across sessions, both groups showed a modulation of complexity of beta-2 band (20-29Hz) at midfrontal regions, but only MC group showed a modulation of complexity of theta band (3.5-7.5Hz) at posterior regions. Therefore, the neuronal complexity patterns showed different changes in EEG frequency band specific complexity resulting in two different types of interventions. Moreover, the different neural responses to listening to monochords and PMR were observed after regular relaxation interventions over a short time span.

mTOR signaling and its roles in normal and abnormal brain development.

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Nobuyuki eTakei

2014-04-01

Full Text Available Target of rapamycin (TOR was first identified in yeast as a target molecule of rapamycin, an anti-fugal and immunosuppressant macrolide compound. In mammals, its orthologue is called mTOR (mammalian TOR. mTOR is a serine/threonine kinase that converges different extracellular stimuli, such as nutrients and growth factors, and diverges into several biochemical reactions, including translation, autophagy, transcription, and lipid synthesis among others. These biochemical reactions govern cell growth and cause cells to attain an anabolic state. Thus, the disruption of mTOR signaling is implicated in a wide array of diseases such as cancer, diabetes, and obesity. In the central nervous system (CNS, the mTOR signaling cascade is activated by nutrients, neurotrophic factors, and neurotransmitters that enhances protein (and possibly lipid synthesis and suppresses autophagy. These processes contribute to normal neuronal growth by promoting their differentiation, neurite elongation and branching, and synaptic formation during development. Therefore, disruption of mTOR signaling may cause neuronal degeneration and abnormal neural development. While reduced mTOR signaling is associated with neurodegeneration, excess activation of mTOR signaling causes abnormal development of neurons and glia, leading to brain malformation. In this review, we first introduce the current state of molecular knowledge of mTOR complexes and signaling in general. We then describe mTOR activation in neurons, which leads to translational enhancement, and finally discuss the link between mTOR and normal/abnormal neuronal growth during development.

Approach of Complex Networks for the Determination of Brain Death

Institute of Scientific and Technical Information of China (English)

SUN Wei-Gang; CAO Jian-Ting; WANG Ru-Bin

2011-01-01

In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our Sndings might provide valuable insights on the determination of brain death.%@@ In clinical practice, brain death is the irreversible end of all brain activity.Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination.Brain functional networks constructed by correlation analysis axe derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated.Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state.Our findings might provide valuable insights on the determination of brain death.

A signaling network for patterning of neuronal connectivity in the Drosophila brain.

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Mohammed Srahna

2006-10-01

Full Text Available The precise number and pattern of axonal connections generated during brain development regulates animal behavior. Therefore, understanding how developmental signals interact to regulate axonal extension and retraction to achieve precise neuronal connectivity is a fundamental goal of neurobiology. We investigated this question in the developing adult brain of Drosophila and find that it is regulated by crosstalk between Wnt, fibroblast growth factor (FGF receptor, and Jun N-terminal kinase (JNK signaling, but independent of neuronal activity. The Rac1 GTPase integrates a Wnt-Frizzled-Disheveled axon-stabilizing signal and a Branchless (FGF-Breathless (FGF receptor axon-retracting signal to modulate JNK activity. JNK activity is necessary and sufficient for axon extension, whereas the antagonistic Wnt and FGF signals act to balance the extension and retraction required for the generation of the precise wiring pattern.

Restoring susceptibility induced MRI signal loss in rat brain at 9.4 T: A step towards whole brain functional connectivity imaging.

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Rupeng Li

Full Text Available The aural cavity magnetic susceptibility artifact leads to significant echo planar imaging (EPI signal dropout in rat deep brain that limits acquisition of functional connectivity fcMRI data. In this study, we provide a method that recovers much of the EPI signal in deep brain. Needle puncture introduction of a liquid-phase fluorocarbon into the middle ear allows acquisition of rat fcMRI data without signal dropout. We demonstrate that with seeds chosen from previously unavailable areas, including the amygdala and the insular cortex, we are able to acquire large scale networks, including the limbic system. This tool allows EPI-based neuroscience and pharmaceutical research in rat brain using fcMRI that was previously not feasible.

Aluminum complexing enhances amyloid beta protein penetration of blood-brain barrier.

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Banks, William A; Niehoff, Michael L; Drago, Denise; Zatta, Paolo

2006-10-20

A significant co-morbidity of Alzheimer's disease and cerebrovascular impairment suggests that cerebrovascular dysregulation is an important feature of dementia. Amyloid beta protein (Abeta), a relevant risk factor in Alzheimer's disease, has neurotoxic properties and is thought to play a critical role in the cognitive impairments. Previously, we demonstrated that the 42mer of Abeta (Abeta42) complexed with aluminum (Al-Abeta42) is much more cytotoxic than non-complexed Abeta42. The level of Abeta in the brain is a balance between synthesis, degradation, and fluxes across the blood-brain barrier (BBB). In the present paper, we determined whether complexing with aluminum affected the ability of radioactively iodinated Abeta to cross the in vivo BBB. We found that the rates of uptake of Al-Abeta42 and Abeta42 were similar, but that Al-Abeta42 was sequestered by brain endothelial cells much less than Abeta42 and so more readily entered the parenchymal space of the brain. Al-Abeta42 also had a longer half-life in blood and had increased permeation at the striatum and thalamus. Brain-to-blood transport was similar for Al-Abeta42 and Abeta42. In conclusion, complexing with aluminum affects some aspects of blood-to-brain permeability so that Al-Abeta42 would have more ready access to brain cells than Abeta42.

The Brain Prize 2014: complex human functions.

Science.gov (United States)

Grigaityte, Kristina; Iacoboni, Marco

2014-11-01

Giacomo Rizzolatti, Stanislas Dehaene, and Trevor Robbins were recently awarded the 2014 Grete Lundbeck European Brain Research Prize for their 'pioneering research on higher brain mechanisms underpinning such complex human functions as literacy, numeracy, motivated behavior and social cognition, and for their effort to understand cognitive and behavioral disorders'. Why was their work highlighted? Is there anything that links together these seemingly disparate lines of research? Copyright © 2014 Elsevier Ltd. All rights reserved.

ATP as a Multi-target Danger Signal in the Brain

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Ricardo J Rodrigues

2015-04-01

Full Text Available ATP is released in an activity-dependent manner from different cell types in the brain, fulfilling different roles as a neurotransmitter, neuromodulator, astrocyte-to-neuron communication, propagating astrocytic responses and formatting microglia responses. This involves the activation of different ATP P2 receptors (P2R as well as adenosine receptors upon extracellular ATP catabolism by ecto-nucleotidases. Notably, brain noxious stimuli trigger a sustained increase of extracellular ATP, which plays a key role as danger signal in the brain. This involves a combined action of extracellular ATP in different cell types, namely increasing the susceptibility of neurons to damage, promoting astrogliosis and recruiting and formatting microglia to mount neuroinflammatory responses. Such actions involve the activation of different receptors, as heralded by neuroprotective effects resulting from blockade mainly of P2X7R, P2Y1R and adenosine A2A receptors (A2AR, which hierarchy, cooperation and/or redundancy is still not resolved. These pleiotropic functions of ATP as a danger signal in brain damage prompt a therapeutic interest to multi-target different purinergic receptors to provide maximal opportunities for neuroprotection.

Electroencephalography(EEG)-based instinctive brain-control of a quadruped locomotion robot.

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Jia, Wenchuan; Huang, Dandan; Luo, Xin; Pu, Huayan; Chen, Xuedong; Bai, Ou

2012-01-01

Artificial intelligence and bionic control have been applied in electroencephalography (EEG)-based robot system, to execute complex brain-control task. Nevertheless, due to technical limitations of the EEG decoding, the brain-computer interface (BCI) protocol is often complex, and the mapping between the EEG signal and the practical instructions lack of logic associated, which restrict the user's actual use. This paper presents a strategy that can be used to control a quadruped locomotion robot by user's instinctive action, based on five kinds of movement related neurophysiological signal. In actual use, the user drives or imagines the limbs/wrists action to generate EEG signal to adjust the real movement of the robot according to his/her own motor reflex of the robot locomotion. This method is easy for real use, as the user generates the brain-control signal through the instinctive reaction. By adopting the behavioral control of learning and evolution based on the proposed strategy, complex movement task may be realized by instinctive brain-control.

Brain architecture and social complexity in modern and ancient birds.

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Burish, Mark J; Kueh, Hao Yuan; Wang, Samuel S-H

2004-01-01

Vertebrate brains vary tremendously in size, but differences in form are more subtle. To bring out functional contrasts that are independent of absolute size, we have normalized brain component sizes to whole brain volume. The set of such volume fractions is the cerebrotype of a species. Using this approach in mammals we previously identified specific associations between cerebrotype and behavioral specializations. Among primates, cerebrotypes are linked principally to enlargement of the cerebral cortex and are associated with increases in the complexity of social structure. Here we extend this analysis to include a second major vertebrate group, the birds. In birds the telencephalic volume fraction is strongly correlated with social complexity. This correlation accounts for almost half of the observed variation in telencephalic size, more than any other behavioral specialization examined, including the ability to learn song. A prominent exception to this pattern is owls, which are not social but still have very large forebrains. Interpolating the overall correlation for Archaeopteryx, an ancient bird, suggests that its social complexity was likely to have been on a par with modern domesticated chickens. Telencephalic volume fraction outperforms residuals-based measures of brain size at separating birds by social structure. Telencephalic volume fraction may be an anatomical substrate for social complexity, and perhaps cognitive ability, that can be generalized across a range of vertebrate brains, including dinosaurs. Copyright 2004 S. Karger AG, Basel

Permanency analysis on human electroencephalogram signals for pervasive Brain-Computer Interface systems.

Science.gov (United States)

Sadeghi, Koosha; Junghyo Lee; Banerjee, Ayan; Sohankar, Javad; Gupta, Sandeep K S

2017-07-01

Brain-Computer Interface (BCI) systems use some permanent features of brain signals to recognize their corresponding cognitive states with high accuracy. However, these features are not perfectly permanent, and BCI system should be continuously trained over time, which is tedious and time consuming. Thus, analyzing the permanency of signal features is essential in determining how often to repeat training. In this paper, we monitor electroencephalogram (EEG) signals, and analyze their behavior through continuous and relatively long period of time. In our experiment, we record EEG signals corresponding to rest state (eyes open and closed) from one subject everyday, for three and a half months. The results show that signal features such as auto-regression coefficients remain permanent through time, while others such as power spectral density specifically in 5-7 Hz frequency band are not permanent. In addition, eyes open EEG data shows more permanency than eyes closed data.

Identifying modular relations in complex brain networks

DEFF Research Database (Denmark)

Andersen, Kasper Winther; Mørup, Morten; Siebner, Hartwig

2012-01-01

We evaluate the infinite relational model (IRM) against two simpler alternative nonparametric Bayesian models for identifying structures in multi subject brain networks. The models are evaluated for their ability to predict new data and infer reproducible structures. Prediction and reproducibility...... and obtains comparable reproducibility and predictability. For resting state functional magnetic resonance imaging data from 30 healthy controls the IRM model is also superior to the two simpler alternatives, suggesting that brain networks indeed exhibit universal complex relational structure...

Fasting and Systemic Insulin Signaling Regulate Phosphorylation of Brain Proteins That Modulate Cell Morphology and Link to Neurological Disorders.

Science.gov (United States)

Li, Min; Quan, Chao; Toth, Rachel; Campbell, David G; MacKintosh, Carol; Wang, Hong Yu; Chen, Shuai

2015-12-11

Diabetes is strongly associated with cognitive decline, but the molecular reasons are unknown. We found that fasting and peripheral insulin promote phosphorylation and dephosphorylation, respectively, of specific residues on brain proteins including cytoskeletal regulators such as slit-robo GTPase-activating protein 3 (srGAP3) and microtubule affinity-regulating protein kinases (MARKs), in which deficiency or dysregulation is linked to neurological disorders. Fasting activates protein kinase A (PKA) but not PKB/Akt signaling in the brain, and PKA can phosphorylate the purified srGAP3. The phosphorylation of srGAP3 and MARKs were increased when PKA signaling was activated in primary neurons. Knockdown of PKA decreased the phosphorylation of srGAP3. Furthermore, WAVE1, a protein kinase A-anchoring protein, formed a complex with srGAP3 and PKA in the brain of fasted mice to facilitate the phosphorylation of srGAP3 by PKA. Although brain cells have insulin receptors, our findings are inconsistent with the down-regulation of phosphorylation of target proteins being mediated by insulin signaling within the brain. Rather, our findings infer that systemic insulin, through a yet unknown mechanism, inhibits PKA or protein kinase(s) with similar specificity and/or activates an unknown phosphatase in the brain. Ser(858) of srGAP3 was identified as a key regulatory residue in which phosphorylation by PKA enhanced the GAP activity of srGAP3 toward its substrate, Rac1, in cells, thereby inhibiting the action of this GTPase in cytoskeletal regulation. Our findings reveal novel mechanisms linking peripheral insulin sensitivity with cytoskeletal remodeling in neurons, which may help to explain the association of diabetes with neurological disorders such as Alzheimer disease. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

Science.gov (United States)

Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

Amphetamine modulates brain signal variability and working memory in younger and older adults.

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Garrett, Douglas D; Nagel, Irene E; Preuschhof, Claudia; Burzynska, Agnieszka Z; Marchner, Janina; Wiegert, Steffen; Jungehülsing, Gerhard J; Nyberg, Lars; Villringer, Arno; Li, Shu-Chen; Heekeren, Hauke R; Bäckman, Lars; Lindenberger, Ulman

2015-06-16

Better-performing younger adults typically express greater brain signal variability relative to older, poorer performers. Mechanisms for age and performance-graded differences in brain dynamics have, however, not yet been uncovered. Given the age-related decline of the dopamine (DA) system in normal cognitive aging, DA neuromodulation is one plausible mechanism. Hence, agents that boost systemic DA [such as d-amphetamine (AMPH)] may help to restore deficient signal variability levels. Furthermore, despite the standard practice of counterbalancing drug session order (AMPH first vs. placebo first), it remains understudied how AMPH may interact with practice effects, possibly influencing whether DA up-regulation is functional. We examined the effects of AMPH on functional-MRI-based blood oxygen level-dependent (BOLD) signal variability (SD(BOLD)) in younger and older adults during a working memory task (letter n-back). Older adults expressed lower brain signal variability at placebo, but met or exceeded young adult SD(BOLD) levels in the presence of AMPH. Drug session order greatly moderated change-change relations between AMPH-driven SD(BOLD) and reaction time means (RT(mean)) and SDs (RT(SD)). Older adults who received AMPH in the first session tended to improve in RT(mean) and RT(SD) when SD(BOLD) was boosted on AMPH, whereas younger and older adults who received AMPH in the second session showed either a performance improvement when SD(BOLD) decreased (for RT(mean)) or no effect at all (for RT(SD)). The present findings support the hypothesis that age differences in brain signal variability reflect aging-induced changes in dopaminergic neuromodulation. The observed interactions among AMPH, age, and session order highlight the state- and practice-dependent neurochemical basis of human brain dynamics.

Lactate in the brain: from metabolic end-product to signalling molecule

KAUST Repository

Magistretti, Pierre J.

2018-03-08

Lactate in the brain has long been associated with ischaemia; however, more recent evidence shows that it can be found there under physiological conditions. In the brain, lactate is formed predominantly in astrocytes from glucose or glycogen in response to neuronal activity signals. Thus, neurons and astrocytes show tight metabolic coupling. Lactate is transferred from astrocytes to neurons to match the neuronal energetic needs, and to provide signals that modulate neuronal functions, including excitability, plasticity and memory consolidation. In addition, lactate affects several homeostatic functions. Overall, lactate ensures adequate energy supply, modulates neuronal excitability levels and regulates adaptive functions in order to set the \\'homeostatic tone\\' of the nervous system.

Hemorrhagic brain metastases with high signal intensity on diffusion-weighted MR images. A case report

Energy Technology Data Exchange (ETDEWEB)

Mori, H.; Abe, O.; Aoki, S.; Masumoto, T.; Yoshikawa, T.; Kunimatsu, A; Hayashi, N.; Ohtomo, K. [Graduate School of Medicine, Univ. of Tokyo (Japan). Dept. of Radiology

2002-11-01

Diffusion-weighted MR imaging has been applicable to the differential diagnosis of abscesses and necrotic or cystic brain tumors. However, restricted water diffusion is not necessarily specific for brain abscess. We describe ring-enhancing metastases of lung carcinoma characterized by high signal intensity on diffusion-weighted MR images. The signal pattern probably reflected intralesional hemorrhage. The present report adds to the growing literature regarding the differential diagnosis of ring-enhancing brain lesions.

ALFY-Controlled DVL3 Autophagy Regulates Wnt Signaling, Determining Human Brain Size.

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Rotem Kadir

2016-03-01

Full Text Available Primary microcephaly is a congenital neurodevelopmental disorder of reduced head circumference and brain volume, with fewer neurons in the cortex of the developing brain due to premature transition between symmetrical and asymmetrical cellular division of the neuronal stem cell layer during neurogenesis. We now show through linkage analysis and whole exome sequencing, that a dominant mutation in ALFY, encoding an autophagy scaffold protein, causes human primary microcephaly. We demonstrate the dominant effect of the mutation in drosophila: transgenic flies harboring the human mutant allele display small brain volume, recapitulating the disease phenotype. Moreover, eye-specific expression of human mutant ALFY causes rough eye phenotype. In molecular terms, we demonstrate that normally ALFY attenuates the canonical Wnt signaling pathway via autophagy-dependent removal specifically of aggregates of DVL3 and not of Dvl1 or Dvl2. Thus, autophagic attenuation of Wnt signaling through removal of Dvl3 aggregates by ALFY acts in determining human brain size.

Design principles of nuclear receptor signaling: how complex networking improves signal transduction

Science.gov (United States)

Kolodkin, Alexey N; Bruggeman, Frank J; Plant, Nick; Moné, Martijn J; Bakker, Barbara M; Campbell, Moray J; van Leeuwen, Johannes P T M; Carlberg, Carsten; Snoep, Jacky L; Westerhoff, Hans V

2010-01-01

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of ‘design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic ‘nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. PMID:21179018

Effects of Bisphenol A on glucose homeostasis and brain insulin signaling pathways in male mice.

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Fang, Fangfang; Chen, Donglong; Yu, Pan; Qian, Wenyi; Zhou, Jing; Liu, Jingli; Gao, Rong; Wang, Jun; Xiao, Hang

2015-02-01

The potential effects of Bisphenol A (BPA) on peripheral insulin resistance have recently gained more attention, however, its functions on brain insulin resistance are still unknown. The aim of the present study was to investigate the effects of BPA on insulin signaling and glucose transport in mouse brain. The male mice were administrated of 100 μg/kg/day BPA or vehicle for 15 days then challenged with glucose and insulin tolerance tests. The insulin levels were detected with radioimmunoassay (RIA), and the insulin signaling pathways were investigated by Western blot. Our results revealed that BPA significantly increased peripheral plasma insulin levels, and decreased the insulin signals including phosphorylated insulin receptor (p-IR), phosphorylated insulin receptor substrate 1 (p-IRS1), phosphorylated protein kinase B (p-AKT), phosphorylated glycogen synthase kinase 3β (p-GSK3β) and phosphorylated extracellular regulated protein kinases (p-ERK1/2) in the brain, though insulin expression in both hippocampus and profrontal cortex was increased. In parallel, BPA exposure might contribute to glucose transport disturbance in the brain since the expression of glucose transporters were markedly decreased. In conclusion, BPA exposure perturbs the insulin signaling and glucose transport in the brain, therefore, it might be a risk factor for brain insulin resistance. Copyright © 2015 Elsevier Inc. All rights reserved.

Activation of Brain Somatostatin Signaling Suppresses CRF Receptor-Mediated Stress Response

OpenAIRE

Andreas Stengel; Yvette F. Taché; Yvette F. Taché

2017-01-01

Corticotropin-releasing factor (CRF) is the hallmark brain peptide triggering the response to stress and mediates—in addition to the stimulation of the hypothalamus-pituitary-adrenal (HPA) axis—other hormonal, behavioral, autonomic and visceral components. Earlier reports indicate that somatostatin-28 injected intracerebroventricularly counteracts the acute stress-induced ACTH and catecholamine release. Mounting evidence now supports that activation of brain somatostatin signaling exerts a br...

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

International Nuclear Information System (INIS)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli

2007-01-01

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

Energy Technology Data Exchange (ETDEWEB)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli [Electrical Engineering Department, Federal University of Espirito Santo (UFES), Av. Fernando Ferrari, 514, Vitoria, 29075-910 (Brazil)

2007-11-15

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded.

The IGFBP7 homolog Imp-L2 promotes insulin signaling in distinct neurons of the Drosophila brain.

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Bader, R; Sarraf-Zadeh, L; Peters, M; Moderau, N; Stocker, H; Köhler, K; Pankratz, M J; Hafen, E

2013-06-15

In Drosophila, Insulin-like peptide 2 (Dilp-2) is expressed by insulin-producing cells in the brain, and is secreted into the hemolymph to activate insulin signaling systemically. Within the brain, however, a more local activation of insulin signaling may be required to couple behavioral and physiological traits to nutritional inputs. We show that a small subset of neurons in the larval brain has high Dilp-2-mediated insulin signaling activity. This local insulin signaling activation is accompanied by selective Dilp-2 uptake and depends on the expression of the Imaginal morphogenesis protein-late 2 (Imp-L2) in the target neurons. We suggest that Imp-L2 acts as a licensing factor for neuronal IIS activation through Dilp-2 to further increase the precision of insulin activity in the brain.

Complex network analysis of resting-state fMRI of the brain.

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Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

2016-08-01

Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

Brain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear model.

Science.gov (United States)

Hutka, Stefanie; Bidelman, Gavin M; Moreno, Sylvain

2013-12-30

There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity) that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain's processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV) analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer.

TGFβ signaling in the brain increases with aging and signals to astrocytes and innate immune cells in the weeks after stroke

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Buckwalter Marion S

2010-10-01

Full Text Available Abstract Background TGFβ is both neuroprotective and a key immune system modulator and is likely to be an important target for future stroke therapy. The precise function of increased TGF-β1 after stroke is unknown and its pleiotropic nature means that it may convey a neuroprotective signal, orchestrate glial scarring or function as an important immune system regulator. We therefore investigated the time course and cell-specificity of TGFβ signaling after stroke, and whether its signaling pattern is altered by gender and aging. Methods We performed distal middle cerebral artery occlusion strokes on 5 and 18 month old TGFβ reporter mice to get a readout of TGFβ responses after stroke in real time. To determine which cell type is the source of increased TGFβ production after stroke, brain sections were stained with an anti-TGFβ antibody, colocalized with markers for reactive astrocytes, neurons, and activated microglia. To determine which cells are responding to TGFβ after stroke, brain sections were double-labelled with anti-pSmad2, a marker of TGFβ signaling, and markers of neurons, oligodendrocytes, endothelial cells, astrocytes and microglia. Results TGFβ signaling increased 2 fold after stroke, beginning on day 1 and peaking on day 7. This pattern of increase was preserved in old animals and absolute TGFβ signaling in the brain increased with age. Activated microglia and macrophages were the predominant source of increased TGFβ after stroke and astrocytes and activated microglia and macrophages demonstrated dramatic upregulation of TGFβ signaling after stroke. TGFβ signaling in neurons and oligodendrocytes did not undergo marked changes. Conclusions We found that TGFβ signaling increases with age and that astrocytes and activated microglia and macrophages are the main cell types that undergo increased TGFβ signaling in response to post-stroke increases in TGFβ. Therefore increased TGFβ after stroke likely regulates glial

TGFβ signaling in the brain increases with aging and signals to astrocytes and innate immune cells in the weeks after stroke.

Science.gov (United States)

Doyle, Kristian P; Cekanaviciute, Egle; Mamer, Lauren E; Buckwalter, Marion S

2010-10-11

TGFβ is both neuroprotective and a key immune system modulator and is likely to be an important target for future stroke therapy. The precise function of increased TGF-β1 after stroke is unknown and its pleiotropic nature means that it may convey a neuroprotective signal, orchestrate glial scarring or function as an important immune system regulator. We therefore investigated the time course and cell-specificity of TGFβ signaling after stroke, and whether its signaling pattern is altered by gender and aging. We performed distal middle cerebral artery occlusion strokes on 5 and 18 month old TGFβ reporter mice to get a readout of TGFβ responses after stroke in real time. To determine which cell type is the source of increased TGFβ production after stroke, brain sections were stained with an anti-TGFβ antibody, colocalized with markers for reactive astrocytes, neurons, and activated microglia. To determine which cells are responding to TGFβ after stroke, brain sections were double-labelled with anti-pSmad2, a marker of TGFβ signaling, and markers of neurons, oligodendrocytes, endothelial cells, astrocytes and microglia. TGFβ signaling increased 2 fold after stroke, beginning on day 1 and peaking on day 7. This pattern of increase was preserved in old animals and absolute TGFβ signaling in the brain increased with age. Activated microglia and macrophages were the predominant source of increased TGFβ after stroke and astrocytes and activated microglia and macrophages demonstrated dramatic upregulation of TGFβ signaling after stroke. TGFβ signaling in neurons and oligodendrocytes did not undergo marked changes. We found that TGFβ signaling increases with age and that astrocytes and activated microglia and macrophages are the main cell types that undergo increased TGFβ signaling in response to post-stroke increases in TGFβ. Therefore increased TGFβ after stroke likely regulates glial scar formation and the immune response to stroke.

Delivery of circulating lipoproteins to specific neurons in the Drosophila brain regulates systemic insulin signaling.

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Brankatschk, Marko; Dunst, Sebastian; Nemetschke, Linda; Eaton, Suzanne

2014-10-02

The Insulin signaling pathway couples growth, development and lifespan to nutritional conditions. Here, we demonstrate a function for the Drosophila lipoprotein LTP in conveying information about dietary lipid composition to the brain to regulate Insulin signaling. When yeast lipids are present in the diet, free calcium levels rise in Blood Brain Barrier glial cells. This induces transport of LTP across the Blood Brain Barrier by two LDL receptor-related proteins: LRP1 and Megalin. LTP accumulates on specific neurons that connect to cells that produce Insulin-like peptides, and induces their release into the circulation. This increases systemic Insulin signaling and the rate of larval development on yeast-containing food compared with a plant-based food of similar nutritional content.

Sex-specific signaling in the blood-brain barrier is required for male courtship in Drosophila.

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Valbona Hoxha

Full Text Available Soluble circulating proteins play an important role in the regulation of mating behavior in Drosophila melanogaster. However, how these factors signal through the blood-brain barrier (bbb to interact with the sex-specific brain circuits that control courtship is unknown. Here we show that male identity of the blood-brain barrier is necessary and that male-specific factors in the bbb are physiologically required for normal male courtship behavior. Feminization of the bbb of adult males significantly reduces male courtship. We show that the bbb-specific G-protein coupled receptor moody and bbb-specific Go signaling in adult males are necessary for normal courtship. These data identify sex-specific factors and signaling processes in the bbb as important regulators of male mating behavior.

Approach of Complex Networks for the Determination of Brain Death

International Nuclear Information System (INIS)

Sun Wei-Gang; Cao Jian-Ting; Wang Ru-Bin

2011-01-01

In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death. (cross-disciplinary physics and related areas of science and technology)

Barrier mechanisms in the Drosophila blood-brain barrier

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Samantha Jane Hindle

2014-12-01

Full Text Available The invertebrate blood-brain barrier field is growing at a rapid pace and, in recent years, studies have shown a physiologic and molecular complexity that has begun to rival its vertebrate counterpart. Novel mechanisms of paracellular barrier maintenance through GPCR signaling were the first demonstrations of the complex adaptive mechanisms of barrier physiology. Building upon this work, the integrity of the invertebrate blood-brain barrier has recently been shown to require coordinated function of all layers of the compound barrier structure, analogous to signaling between the layers of the vertebrate neurovascular unit. These findings strengthen the notion that many blood-brain barrier mechanisms are conserved between vertebrates and invertebrates, and suggest that novel findings in invertebrate model organisms will have a significant impact on the understanding of vertebrate BBB functions. In this vein, important roles in coordinating localized and systemic signaling to dictate organism development and growth are beginning to show how the blood-brain barrier can govern whole animal physiologies. This includes novel functions of blood-brain barrier gap junctions in orchestrating synchronized neuroblast proliferation, and of blood-brain barrier secreted antagonists of insulin receptor signaling. These advancements and others are pushing the field forward in exciting new directions. In this review, we provide a synopsis of invertebrate blood-brain barrier anatomy and physiology, with a focus on insights from the past 5 years, and highlight important areas for future study.

Endocrinology and the brain: corticotropin-releasing hormone signaling.

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Inda, Carolina; Armando, Natalia G; Dos Santos Claro, Paula A; Silberstein, Susana

2017-08-01

Corticotropin-releasing hormone (CRH) is a key player of basal and stress-activated responses in the hypothalamic-pituitary-adrenal axis (HPA) and in extrahypothalamic circuits, where it functions as a neuromodulator to orchestrate humoral and behavioral adaptive responses to stress. This review describes molecular components and cellular mechanisms involved in CRH signaling downstream of its G protein-coupled receptors (GPCRs) CRHR1 and CRHR2 and summarizes recent findings that challenge the classical view of GPCR signaling and impact on our understanding of CRHRs function. Special emphasis is placed on recent studies of CRH signaling that revealed new mechanistic aspects of cAMP generation and ERK1/2 activation in physiologically relevant contexts of the neurohormone action. In addition, we present an overview of the pathophysiological role of the CRH system, which highlights the need for a precise definition of CRHRs signaling at molecular level to identify novel targets for pharmacological intervention in neuroendocrine tissues and specific brain areas involved in CRH-related disorders. © 2017 The authors.

Taurine-modified Ru(ii)-complex targets cancerous brain cells for photodynamic therapy.

Science.gov (United States)

Du, Enming; Hu, Xunwu; Roy, Sona; Wang, Peng; Deasy, Kieran; Mochizuki, Toshiaki; Zhang, Ye

2017-05-30

The precision and efficacy of photodynamic therapy (PDT) is essential for the treatment of brain tumors because the cancer cells are within or adjacent to the delicate nervous system. Taurine is an abundant amino acid in the brain that serves the central nervous system (CNS). A taurine-modified polypyridyl Ru-complex was shown to have optimized intracellular affinity in cancer cells through accumulation in lysosomes. Symmetrical modification of this Ru-complex by multiple taurine molecules enhanced the efficiency of molecular emission with boosted generation of reactive oxygen species. These characteristic features make the taurine-modified Ru-complex a potentially effective photosensitizer for PDT of target cancer cells, with outstanding efficacy in cancerous brain cells.

Neuronal LRP1 regulates glucose metabolism and insulin signaling in the brain.

Science.gov (United States)

Liu, Chia-Chen; Hu, Jin; Tsai, Chih-Wei; Yue, Mei; Melrose, Heather L; Kanekiyo, Takahisa; Bu, Guojun

2015-04-08

Alzheimer's disease (AD) is a neurological disorder characterized by profound memory loss and progressive dementia. Accumulating evidence suggests that Type 2 diabetes mellitus, a metabolic disorder characterized by insulin resistance and glucose intolerance, significantly increases the risk for developing AD. Whereas amyloid-β (Aβ) deposition and neurofibrillary tangles are major histological hallmarks of AD, impairment of cerebral glucose metabolism precedes these pathological changes during the early stage of AD and likely triggers or exacerbates AD pathology. However, the mechanisms linking disturbed insulin signaling/glucose metabolism and AD pathogenesis remain unclear. The low-density lipoprotein receptor-related protein 1 (LRP1), a major apolipoprotein E receptor, plays critical roles in lipoprotein metabolism, synaptic maintenance, and clearance of Aβ in the brain. Here, we demonstrate that LRP1 interacts with the insulin receptor β in the brain and regulates insulin signaling and glucose uptake. LRP1 deficiency in neurons leads to impaired insulin signaling as well as reduced levels of glucose transporters GLUT3 and GLUT4. Consequently, glucose uptake is reduced. By using an in vivo microdialysis technique sampling brain glucose concentration in freely moving mice, we further show that LRP1 deficiency in conditional knock-out mice resulted in glucose intolerance in the brain. We also found that hyperglycemia suppresses LRP1 expression, which further exacerbates insulin resistance, glucose intolerance, and AD pathology. As loss of LRP1 expression is seen in AD brains, our study provides novel insights into insulin resistance in AD. Our work also establishes new targets that can be explored for AD prevention or therapy. Copyright © 2015 the authors 0270-6474/15/355851-09$15.00/0.

The application of graph theoretical analysis to complex networks in the brain

NARCIS (Netherlands)

Reijneveld, Jaap C.; Ponten, Sophie C.; Berendse, Henk W.; Stam, Cornelis J.

2007-01-01

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in

Machines vs. ensembles: effective MAPK signaling through heterogeneous sets of protein complexes.

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Ryan Suderman

Full Text Available Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively

Assessing signal-driven mechanism in neonates: brain responses to temporally and spectrally different sounds

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Yasuyo eMinagawa-Kawai

2011-06-01

Full Text Available Past studies have found that in adults that acoustic properties of sound signals (such as fast vs. slow temporal features differentially activate the left and right hemispheres, and some have hypothesized that left-lateralization for speech processing may follow from left-lateralization to rapidly changing signals. Here, we tested whether newborns’ brains show some evidence of signal-specific lateralization responses using near-infrared spectroscopy (NIRS and auditory stimuli that elicits lateralized responses in adults, composed of segments that vary in duration and spectral diversity. We found significantly greater bilateral responses of oxygenated hemoglobin (oxy-Hb in the temporal areas for stimuli with a minimum segment duration of 21 ms, than stimuli with a minimum segment duration of 667 ms. However, we found no evidence for hemispheric asymmetries dependent on the stimulus characteristics. We hypothesize that acoustic-based functional brain asymmetries may develop throughout early infancy, and discuss their possible relationship with brain asymmetries for language.

MR spectroscopy detection of lactate and lipid signals in the brains of healthy elderly people

Energy Technology Data Exchange (ETDEWEB)

Sijens, P.E.; Heijboer, R.J.J.; Oudkerk, M. [Dept. of Radiology, Univ. Hospital Groningen (Netherlands); Heijer, T. den; Leeuw, F.E. de; Groot, J.C. de; Hofman, A.; Breteler, M.M.B. [Dept. of Epidemiology and Biostatistics, Erasmus University Medical School, Rotterdam (Netherlands); Achten, E. [Dept. of Magnetic Resonance, Gent University Hospital (Belgium)

2001-08-01

Magnetic resonance spectroscopy was used to assess the presence of brain lactate and lipid signals, frequently associated with the presence of pathology, in healthy persons of 60-90 years old (n=540). Lactate and lipid signals were observed in, respectively, 25 and 6% of women, and 18 and 2% of men. Upon adjustment for age, and for MRI-detected cerebral atrophy and white matter lesions, the gender differences in lactate and lipid remained the same (p=0.05 and p=0.03, respectively). Brain lactate and lipid signals appear to be intrinsic to aging. However, the presence of these metabolites in very focal areas only, rather than in any distributed fashion within the brain (the latter generally the case with cerebral atrophy and white matter lesions), strongly suggests the existence of asymptomatic focal pathology not shown on MRI. (orig.)

Brain signal variability as a window into the bidirectionality between music and language processing: Moving from a linear to a nonlinear model

Directory of Open Access Journals (Sweden)

Stefanie Andrea Hutka

2013-12-01

Full Text Available There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain’s processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer.

Defining nodes in complex brain networks

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Matthew Lawrence Stanley

2013-11-01

Full Text Available Network science holds great promise for expanding our understanding of the human brain in health, disease, development, and aging. Network analyses are quickly becoming the method of choice for analyzing functional MRI data. However, many technical issues have yet to be confronted in order to optimize results. One particular issue that remains controversial in functional brain network analyses is the definition of a network node. In functional brain networks a node represents some predefined collection of brain tissue, and an edge measures the functional connectivity between pairs of nodes. The characteristics of a node, chosen by the researcher, vary considerably in the literature. This manuscript reviews the current state of the art based on published manuscripts and highlights the strengths and weaknesses of three main methods for defining nodes. Voxel-wise networks are constructed by assigning a node to each, equally sized brain area (voxel. The fMRI time-series recorded from each voxel is then used to create the functional network. Anatomical methods utilize atlases to define the nodes based on brain structure. The fMRI time-series from all voxels within the anatomical area are averaged and subsequently used to generate the network. Functional activation methods rely on data from traditional fMRI activation studies, often from databases, to identify network nodes. Such methods identify the peaks or centers of mass from activation maps to determine the location of the nodes. Small (~10-20 millimeter diameter spheres located at the coordinates of the activation foci are then applied to the data being used in the network analysis. The fMRI time-series from all voxels in the sphere are then averaged, and the resultant time series is used to generate the network. We attempt to clarify the discussion and move the study of complex brain networks forward. While the correct method to be used remains an open, possibly unsolvable question that

Hypothalamic roles of mTOR complex I: integration of nutrient and hormone signals to regulate energy homeostasis.

Science.gov (United States)

Hu, Fang; Xu, Yong; Liu, Feng

2016-06-01

Mammalian or mechanistic target of rapamycin (mTOR) senses nutrient, energy, and hormone signals to regulate metabolism and energy homeostasis. mTOR activity in the hypothalamus, which is associated with changes in energy status, plays a critical role in the regulation of food intake and body weight. mTOR integrates signals from a variety of "energy balancing" hormones such as leptin, insulin, and ghrelin, although its action varies in response to these distinct hormonal stimuli as well as across different neuronal populations. In this review, we summarize and highlight recent findings regarding the functional roles of mTOR complex 1 (mTORC1) in the hypothalamus specifically in its regulation of body weight, energy expenditure, and glucose/lipid homeostasis. Understanding the role and underlying mechanisms behind mTOR-related signaling in the brain will undoubtedly pave new avenues for future therapeutics and interventions that can combat obesity, insulin resistance, and diabetes. Copyright © 2016 the American Physiological Society.

Insulin Regulates Hepatic Triglyceride Secretion and Lipid Content via Signaling in the Brain.

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Scherer, Thomas; Lindtner, Claudia; O'Hare, James; Hackl, Martina; Zielinski, Elizabeth; Freudenthaler, Angelika; Baumgartner-Parzer, Sabina; Tödter, Klaus; Heeren, Joerg; Krššák, Martin; Scheja, Ludger; Fürnsinn, Clemens; Buettner, Christoph

2016-06-01

Hepatic steatosis is common in obesity and insulin resistance and results from a net retention of lipids in the liver. A key mechanism to prevent steatosis is to increase secretion of triglycerides (TG) packaged as VLDLs. Insulin controls nutrient partitioning via signaling through its cognate receptor in peripheral target organs such as liver, muscle, and adipose tissue and via signaling in the central nervous system (CNS) to orchestrate organ cross talk. While hepatic insulin signaling is known to suppress VLDL production from the liver, it is unknown whether brain insulin signaling independently regulates hepatic VLDL secretion. Here, we show that in conscious, unrestrained male Sprague Dawley rats the infusion of insulin into the third ventricle acutely increased hepatic TG secretion. Chronic infusion of insulin into the CNS via osmotic minipumps reduced the hepatic lipid content as assessed by noninvasive (1)H-MRS and lipid profiling independent of changes in hepatic de novo lipogenesis and food intake. In mice that lack the insulin receptor in the brain, hepatic TG secretion was reduced compared with wild-type littermate controls. These studies identify brain insulin as an important permissive factor in hepatic VLDL secretion that protects against hepatic steatosis. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Intelligent Technique for Signal Processing to Identify the Brain Disorder for Epilepsy Captures Using Fuzzy Systems

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Gurumurthy Sasikumar

2016-01-01

Full Text Available The new direction of understand the signal that is created from the brain organization is one of the main chores in the brain signal processing. Amid all the neurological disorders the human brain epilepsy is measured as one of the extreme prevalent and then programmed artificial intelligence detection technique is an essential due to the crooked and unpredictable nature of happening of epileptic seizures. We proposed an Improved Fuzzy firefly algorithm, which would enhance the classification of the brain signal efficiently with minimum iteration. An important bunching technique created on fuzzy logic is the Fuzzy C means. Together in the feature domain with the spatial domain the features gained after multichannel EEG signals remained combined by means of fuzzy algorithms. And for better precision segmentation process the firefly algorithm is applied to optimize the Fuzzy C-means membership function. Simultaneously for the efficient clustering method the convergence criteria are set. On the whole the proposed technique yields more accurate results and that gives an edge over other techniques. This proposed algorithm result compared with other algorithms like fuzzy c means algorithm and PSO algorithm.

Insulin signaling disruption in male mice due to perinatal bisphenol A exposure: Role of insulin signaling in the brain.

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Fang, Fangfang; Gao, Yue; Wang, Tingwei; Chen, Donglong; Liu, Jingli; Qian, Wenyi; Cheng, Jie; Gao, Rong; Wang, Jun; Xiao, Hang

2016-03-14

Bisphenol A (BPA), an environmental estrogenic endocrine disruptor, is widely used for producing polycarbonate plastics and epoxy resins. Available data have shown that perinatal exposure to BPA contributes to peripheral insulin resistance, while in the present study, we aimed to investigate the effects of perinatal BPA exposure on insulin signaling and glucose transport in the cortex of offspring mice. The pregnant mice were administrated either vehicle or BPA (100 μg/kg/day) at three perinatal stages. Stage I: from day 6 of gestation until parturition (P6-PND0 fetus exposure); Stage II: from lactation until delactation (PND0-PND21 newborn exposure) and Stage III: from day 6 of pregnancy until delactation (P6-PND21 fetus and newborn exposure). At 8 months of age for the offspring mice, the insulin signaling pathways and glucose transporters (GLUTs) were detected. Our data indicated that the insulin signaling including insulin, phosphorylated insulin receptor (IR), phosphorylated protein kinase B (p-AKT), phosphorylated glycogen synthase kinase 3β (p-GSK3β) and phosphorylated extracellular signal regulated protein kinase (p-ERK) were significantly decreased in the brain. In parallel, GLUTs (GLUT1/3/4) were obviously decreased as well in BPA-treated group in mice brain. Noteworthily, the phosphorylated tau (p-tau) and amyloid precursor protein (APP) were markedly up-regulated in all BPA-treated groups. These results, taken together, suggest the adverse effects of BPA on insulin signaling and GLUTs, which might subsequently contribute to the increment of p-tau and APP in the brain of adult offspring. Therefore, perinatal BPA exposure might be a risk factor for the long-term neurodegenerative changes in offspring male mice. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Identification and analysis of signaling networks potentially involved in breast carcinoma metastasis to the brain.

Directory of Open Access Journals (Sweden)

Feng Li

Full Text Available Brain is a common site of breast cancer metastasis associated with significant neurologic morbidity, decreased quality of life, and greatly shortened survival. However, the molecular and cellular mechanisms underpinning brain colonization by breast carcinoma cells are poorly understood. Here, we used 2D-DIGE (Difference in Gel Electrophoresis proteomic analysis followed by LC-tandem mass spectrometry to identify the proteins differentially expressed in brain-targeting breast carcinoma cells (MB231-Br compared with parental MDA-MB-231 cell line. Between the two cell lines, we identified 12 proteins consistently exhibiting greater than 2-fold (p<0.05 difference in expression, which were associated by the Ingenuity Pathway Analysis (IPA with two major signaling networks involving TNFα/TGFβ-, NFκB-, HSP-70-, TP53-, and IFNγ-associated pathways. Remarkably, highly related networks were revealed by the IPA analysis of a list of 19 brain-metastasis-associated proteins identified recently by the group of Dr. A. Sierra using MDA-MB-435-based experimental system (Martin et al., J Proteome Res 2008 7:908-20, or a 17-gene classifier associated with breast cancer brain relapse reported by the group of Dr. J. Massague based on a microarray analysis of clinically annotated breast tumors from 368 patients (Bos et al., Nature 2009 459: 1005-9. These findings, showing that different experimental systems and approaches (2D-DIGE proteomics used on brain targeting cell lines or gene expression analysis of patient samples with documented brain relapse yield highly related signaling networks, suggest strongly that these signaling networks could be essential for a successful colonization of the brain by metastatic breast carcinoma cells.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

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Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping.

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Chen, Zikuan; Robinson, Jennifer; Calhoun, Vince

2018-01-01

To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization.

β-Adrenergic receptor signaling and modulation of long-term potentiation in the mammalian hippocampus

OpenAIRE

O'Dell, Thomas J.; Connor, Steven A.; Guglietta, Ryan; Nguyen, Peter V.

2015-01-01

Encoding new information in the brain requires changes in synaptic strength. Neuromodulatory transmitters can facilitate synaptic plasticity by modifying the actions and expression of specific signaling cascades, transmitter receptors and their associated signaling complexes, genes, and effector proteins. One critical neuromodulator in the mammalian brain is norepinephrine (NE), which regulates multiple brain functions such as attention, perception, arousal, sleep, learning, and memory. The m...

Hydrogen Exchange Differences between Chemoreceptor Signaling Complexes Localize to Functionally Important Subdomains

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2015-01-01

The goal of understanding mechanisms of transmembrane signaling, one of many key life processes mediated by membrane proteins, has motivated numerous studies of bacterial chemotaxis receptors. Ligand binding to the receptor causes a piston motion of an α helix in the periplasmic and transmembrane domains, but it is unclear how the signal is then propagated through the cytoplasmic domain to control the activity of the associated kinase CheA. Recent proposals suggest that signaling in the cytoplasmic domain involves opposing changes in dynamics in different subdomains. However, it has been difficult to measure dynamics within the functional system, consisting of extended arrays of receptor complexes with two other proteins, CheA and CheW. We have combined hydrogen exchange mass spectrometry with vesicle template assembly of functional complexes of the receptor cytoplasmic domain to reveal that there are significant signaling-associated changes in exchange, and these changes localize to key regions of the receptor involved in the excitation and adaptation responses. The methylation subdomain exhibits complex changes that include slower hydrogen exchange in complexes in a kinase-activating state, which may be partially consistent with proposals that this subdomain is stabilized in this state. The signaling subdomain exhibits significant protection from hydrogen exchange in complexes in a kinase-activating state, suggesting a tighter and/or larger interaction interface with CheA and CheW in this state. These first measurements of the stability of protein subdomains within functional signaling complexes demonstrate the promise of this approach for measuring functionally important protein dynamics within the various physiologically relevant states of multiprotein complexes. PMID:25420045

Synthesis of high-complexity rhythmic signals for closed-loop electrical neuromodulation.

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Zalay, Osbert C; Bardakjian, Berj L

2013-06-01

We propose an approach to synthesizing high-complexity rhythmic signals for closed-loop electrical neuromodulation using cognitive rhythm generator (CRG) networks, wherein the CRG is a hybrid oscillator comprised of (1) a bank of neuronal modes, (2) a ring device (clock), and (3) a static output nonlinearity (mapper). Networks of coupled CRGs have been previously implemented to simulate the electrical activity of biological neural networks, including in silico models of epilepsy, producing outputs of similar waveform and complexity to the biological system. This has enabled CRG network models to be used as platforms for testing seizure control strategies. Presently, we take the application one step further, envisioning therapeutic CRG networks as rhythmic signal generators creating neuromimetic signals for stimulation purposes, motivated by recent research indicating that stimulus complexity and waveform characteristics influence neuromodulation efficacy. To demonstrate this concept, an epileptiform CRG network generating spontaneous seizure-like events (SLEs) was coupled to a therapeutic CRG network, forming a closed-loop neuromodulation system. SLEs are associated with low-complexity dynamics and high phase coherence in the network. The tuned therapeutic network generated a high-complexity, multi-banded rhythmic stimulation signal with prominent theta and gamma-frequency power that suppressed SLEs and increased dynamic complexity in the epileptiform network, as measured by a relative increase in the maximum Lyapunov exponent and decrease in phase coherence. CRG-based neuromodulation outperformed both low and high-frequency periodic pulse stimulation, suggesting that neuromodulation using complex, biomimetic signals may provide an improvement over conventional electrical stimulation techniques for treating neurological disorders such as epilepsy. Copyright © 2013 Elsevier Ltd. All rights reserved.

EGFR Signaling in the Brain Is Necessary for Olfactory Learning in "Drosophila" Larvae

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Rahn, Tasja; Leippe, Matthias; Roeder, Thomas; Fedders, Henning

2013-01-01

Signaling via the epidermal growth factor receptor (EGFR) pathway has emerged as one of the key mechanisms in the development of the central nervous system in "Drosophila melanogaster." By contrast, little is known about the functions of EGFR signaling in the differentiated larval brain. Here, promoter-reporter lines of EGFR and its most prominent…

Reducing Brain Signal Noise in the Prediction of Economic Choices: A Case Study in Neuroeconomics

Directory of Open Access Journals (Sweden)

Raanju R. Sundararajan

2017-12-01

Full Text Available In order to reduce the noise of brain signals, neuroeconomic experiments typically aggregate data from hundreds of trials collected from a few individuals. This contrasts with the principle of simple and controlled designs in experimental and behavioral economics. We use a frequency domain variant of the stationary subspace analysis (SSA technique, denoted as DSSA, to filter out the noise (nonstationary sources in EEG brain signals. The nonstationary sources in the brain signal are associated with variations in the mental state that are unrelated to the experimental task. DSSA is a powerful tool for reducing the number of trials needed from each participant in neuroeconomic experiments and also for improving the prediction performance of an economic choice task. For a single trial, when DSSA is used as a noise reduction technique, the prediction model in a food snack choice experiment has an increase in overall accuracy by around 10% and in sensitivity and specificity by around 20% and in AUC by around 30%, respectively.

Activation of Brain Somatostatin Signaling Suppresses CRF Receptor-Mediated Stress Response.

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Stengel, Andreas; Taché, Yvette F

2017-01-01

Corticotropin-releasing factor (CRF) is the hallmark brain peptide triggering the response to stress and mediates-in addition to the stimulation of the hypothalamus-pituitary-adrenal (HPA) axis-other hormonal, behavioral, autonomic and visceral components. Earlier reports indicate that somatostatin-28 injected intracerebroventricularly counteracts the acute stress-induced ACTH and catecholamine release. Mounting evidence now supports that activation of brain somatostatin signaling exerts a broader anti-stress effect by blunting the endocrine, autonomic, behavioral (with a focus on food intake) and visceral gastrointestinal motor responses through the involvement of distinct somatostatin receptor subtypes.

Mapping glucose-mediated gut-to-brain signalling pathways in humans.

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Little, Tanya J; McKie, Shane; Jones, Richard B; D'Amato, Massimo; Smith, Craig; Kiss, Orsolya; Thompson, David G; McLaughlin, John T

2014-08-01

Previous fMRI studies have demonstrated that glucose decreases the hypothalamic BOLD response in humans. However, the mechanisms underlying the CNS response to glucose have not been defined. We recently demonstrated that the slowing of gastric emptying by glucose is dependent on activation of the gut peptide cholecystokinin (CCK1) receptor. Using physiological functional magnetic resonance imaging this study aimed to determine the whole brain response to glucose, and whether CCK plays a central role. Changes in blood oxygenation level-dependent (BOLD) signal were monitored using fMRI in 12 healthy subjects following intragastric infusion (250ml) of: 1M glucose+predosing with dexloxiglumide (CCK1 receptor antagonist), 1M glucose+placebo, or 0.9% saline (control)+placebo, in a single-blind, randomised fashion. Gallbladder volume, blood glucose, insulin, and GLP-1 and CCK concentrations were determined. Hunger, fullness and nausea scores were also recorded. Intragastric glucose elevated plasma glucose, insulin, and GLP-1, and reduced gall bladder volume (an in vivo assay for CCK secretion). Glucose decreased BOLD signal, relative to saline, in the brainstem and hypothalamus as well as the cerebellum, right occipital cortex, putamen and thalamus. The timing of the BOLD signal decrease was negatively correlated with the rise in blood glucose and insulin levels. The glucose+dex arm highlighted a CCK1-receptor dependent increase in BOLD signal only in the motor cortex. Glucose induces site-specific differences in BOLD response in the human brain; the brainstem and hypothalamus show a CCK1 receptor-independent reduction which is likely to be mediated by a circulatory effect of glucose and insulin, whereas the motor cortex shows an early dexloxiglumide-reversible increase in signal, suggesting a CCK1 receptor-dependent neural pathway. Copyright © 2014. Published by Elsevier Inc.

Mapping glucose-mediated gut-to-brain signalling pathways in humans☆

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Little, Tanya J.; McKie, Shane; Jones, Richard B.; D'Amato, Massimo; Smith, Craig; Kiss, Orsolya; Thompson, David G.; McLaughlin, John T.

2014-01-01

Objectives Previous fMRI studies have demonstrated that glucose decreases the hypothalamic BOLD response in humans. However, the mechanisms underlying the CNS response to glucose have not been defined. We recently demonstrated that the slowing of gastric emptying by glucose is dependent on activation of the gut peptide cholecystokinin (CCK1) receptor. Using physiological functional magnetic resonance imaging this study aimed to determine the whole brain response to glucose, and whether CCK plays a central role. Experimental design Changes in blood oxygenation level-dependent (BOLD) signal were monitored using fMRI in 12 healthy subjects following intragastric infusion (250 ml) of: 1 M glucose + predosing with dexloxiglumide (CCK1 receptor antagonist), 1 M glucose + placebo, or 0.9% saline (control) + placebo, in a single-blind, randomised fashion. Gallbladder volume, blood glucose, insulin, and GLP-1 and CCK concentrations were determined. Hunger, fullness and nausea scores were also recorded. Principal observations Intragastric glucose elevated plasma glucose, insulin, and GLP-1, and reduced gall bladder volume (an in vivo assay for CCK secretion). Glucose decreased BOLD signal, relative to saline, in the brainstem and hypothalamus as well as the cerebellum, right occipital cortex, putamen and thalamus. The timing of the BOLD signal decrease was negatively correlated with the rise in blood glucose and insulin levels. The glucose + dex arm highlighted a CCK1-receptor dependent increase in BOLD signal only in the motor cortex. Conclusions Glucose induces site-specific differences in BOLD response in the human brain; the brainstem and hypothalamus show a CCK1 receptor-independent reduction which is likely to be mediated by a circulatory effect of glucose and insulin, whereas the motor cortex shows an early dexloxiglumide-reversible increase in signal, suggesting a CCK1 receptor-dependent neural pathway. PMID:24685436

In vivo optical microprobe imaging for intracellular Ca2+ dynamics in response to dopaminergic signaling in deep brain evoked by cocaine

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Luo, Zhongchi; Pan, Yingtian; Du, Congwu

2012-02-01

Ca2+ plays a vital role as second messenger in signal transduction and the intracellular Ca2+ ([Ca2+]i) change is an important indicator of neuronal activity in the brain, including both cortical and subcortical brain regions. Due to the highly scattering and absorption of brain tissue, it is challenging to optically access the deep brain regions (e.g., striatum at >3mm under the brain surface) and image [Ca2+]i changes with cellular resolutions. Here, we present two micro-probe approaches (i.e., microlens, and micro-prism) integrated with a fluorescence microscope modified to permit imaging of neuronal [Ca2+]i signaling in the striatum using a calcium indicator Rhod2(AM). While a micro-prism probe provides a larger field of view to image neuronal network from cortex to striatum, a microlens probe enables us to track [Ca2+]i dynamic change in individual neurons within the brain. Both techniques are validated by imaging neuronal [Ca2+]i changes in transgenic mice with dopamine receptors (D1R, D2R) expressing EGFP. Our results show that micro-prism images can map the distribution of D1R- and D2R-expressing neurons in various brain regions and characterize their different mean [Ca2+]i changes induced by an intervention (e.g., cocaine administration, 8mg/kg., i.p). In addition, microlens images can characterize the different [Ca2+]i dynamics of D1 and D2 neurons in response to cocaine, including new mechanisms of these two types of neurons in striatum. These findings highlight the power of the optical micro-probe imaging for dissecting the complex cellular and molecular insights of cocaine in vivo.

Hand in glove: brain and skull in development and dysmorphogenesis

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Flaherty, Kevin

2013-01-01

The brain originates relatively early in development from differentiated ectoderm that forms a hollow tube and takes on an exceedingly complex shape with development. The skull is made up of individual bony elements that form from neural crest- and mesoderm-derived mesenchyme that unite to provide support and protection for soft tissues and spaces of the head. The meninges provide a protective and permeable membrane between brain and skull. Across evolutionary and developmental time, dynamic changes in brain and skull shape track one another so that their integration is evidenced in two structures that fit soundly regardless of changes in biomechanical and physiologic functions. Evidence for this tight correspondence is also seen in diseases of the craniofacial complex that are often classified as diseases of the skull (e.g., craniosynostosis) or diseases of the brain (e.g., holoprosencephaly) even when both tissues are affected. Our review suggests a model that links brain and skull morphogenesis through coordinated integration of signaling pathways (e.g., FGF, TGFβ, Wnt) via processes that are not currently understood, perhaps involving the meninges. Differences in the earliest signaling of biological structure establish divergent designs that will be enhanced during morphogenesis. Signaling systems that pattern the developing brain are also active in patterning required for growth and assembly of the skull and some members of these signaling families have been indicated as causal for craniofacial diseases. Because cells of early brain and skull are sensitive to similar signaling families, variation in the strength or timing of signals or shifts in patterning boundaries that affect one system (neural or skull) could also affect the other system and appropriate co-adjustments in development would be made. Interactions of these signaling systems and of the tissues that they pattern are fundamental to the consistent but labile functional and structural association

Managing Epileptic Seizures by Controlling the Brain Driver Nodes: A Complex Network View

Energy Technology Data Exchange (ETDEWEB)

Bakouie, Fatemeh, E-mail: fbakouie@aut.ac.ir [Neural and Cognitive Sciences Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Cybernetics and Modeling of Biological Systems Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Gharibzadeh, Shahriar, E-mail: fbakouie@aut.ac.ir [Neural and Cognitive Sciences Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Towhidkhah, Farzad [Cybernetics and Modeling of Biological Systems Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

2013-12-12

The brain is a complex biological organization. In its hierarchy, different components, from neurons to functional cognitive circuits are interacting with each other. As a result of cooperation between neurons in the lower levels of this hierarchy, high level cognitive functions emerge (Stam and Reijneveld, 2007). In order to uncover the complexity of these higher functions, understanding the interaction rules in the lower level may be useful. In this level, there are lots of components which connect to each other (with a special structure) and exchange their information (in a specific manner). In this regard, complex network approach will be an influential way to study brain organization. The brain connectivity structure is suggested as a basis for emergence of its complex functions (Rubinov et al., 2009). For example, brain network analysis shows that its connectivity has the “small-worldness” feature, i.e., low characteristic path length and high clustering coefficient (Sporns et al., 2004). It has been seen that “synchronization” (as a collective dynamical behavior) occurs more rapidly in networks with small-world structure (Watts and Strogatz, 1998). Hence, we are able to use structural information (i.e., the pattern of connectivity between elements of the system) for understanding the functional pattern of the organization. Moreover, it is suggested that synchronization is the main mechanism for information exchange between different brain regions (Womelsdorf et al.,).

Managing Epileptic Seizures by Controlling the Brain Driver Nodes: A Complex Network View

International Nuclear Information System (INIS)

Bakouie, Fatemeh; Gharibzadeh, Shahriar; Towhidkhah, Farzad

2013-01-01

The brain is a complex biological organization. In its hierarchy, different components, from neurons to functional cognitive circuits are interacting with each other. As a result of cooperation between neurons in the lower levels of this hierarchy, high level cognitive functions emerge (Stam and Reijneveld, 2007). In order to uncover the complexity of these higher functions, understanding the interaction rules in the lower level may be useful. In this level, there are lots of components which connect to each other (with a special structure) and exchange their information (in a specific manner). In this regard, complex network approach will be an influential way to study brain organization. The brain connectivity structure is suggested as a basis for emergence of its complex functions (Rubinov et al., 2009). For example, brain network analysis shows that its connectivity has the “small-worldness” feature, i.e., low characteristic path length and high clustering coefficient (Sporns et al., 2004). It has been seen that “synchronization” (as a collective dynamical behavior) occurs more rapidly in networks with small-world structure (Watts and Strogatz, 1998). Hence, we are able to use structural information (i.e., the pattern of connectivity between elements of the system) for understanding the functional pattern of the organization. Moreover, it is suggested that synchronization is the main mechanism for information exchange between different brain regions (Womelsdorf et al.,).

Free-running ADC- and FPGA-based signal processing method for brain PET using GAPD arrays

Energy Technology Data Exchange (ETDEWEB)

Hu, Wei [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Choi, Yong, E-mail: ychoi.image@gmail.com [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Hong, Key Jo [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Kang, Jihoon [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Jung, Jin Ho [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Huh, Youn Suk [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Lim, Hyun Keong; Kim, Sang Su [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Kim, Byung-Tae [Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Chung, Yonghyun [Department of Radiological Science, Yonsei University College of Health Science, 234 Meaji, Heungup Wonju, Kangwon-Do 220-710 (Korea, Republic of)

2012-02-01

then transferred to a host computer for coincidence sorting and image reconstruction. In order to evaluate the functionality of the developed signal processing method, energy and timing resolutions for brain PET were measured via the placement of a 6 {mu}Ci {sup 22}Na point source at the center of the PET scanner. Furthermore the PET image of the hot rod phantom (rod diameter: from 2.5 mm to 6.5 mm) with activity of 1 mCi was simulated, and then image acquisition experiment was performed using the brain PET. Measured average energy resolution for 1152 GAPD channels and system timing resolution were 19.5% (FWHM%) and 2.7 ns (FWHM), respectively. With regard to the acquisition of the hot rod phantom image, rods could be resolved down to a diameter of 2.5 mm, which was similar to simulated results. The experimental results demonstrated that the signal processing method developed herein was successfully implemented for brain PET. This reduced the complexity, cost and developing duration for PET system relative to normal PET electronics, and it will obviously be useful for the development of high-performance investigational PET systems.

Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning.

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Hearne, Luke J; Cocchi, Luca; Zalesky, Andrew; Mattingley, Jason B

2017-08-30

Our capacity for higher cognitive reasoning has a measurable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic "resting-state" network architecture. Here we combined resting-state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting-state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting-state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 × 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting-state and null-task demand conditions were associated with more segregated brain-network topology, whereas increases in reasoning complexity resulted in merging of resting-state modules. Further increments in task complexity did not change the established modular architecture, but affected selective patterns of connectivity between frontoparietal, subcortical, cingulo-opercular, and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity. SIGNIFICANCE STATEMENT Humans have clear limits in their ability to solve complex reasoning problems. It is thought that

Simultaneous recording of fluorescence and electrical signals by photometric patch electrode in deep brain regions in vivo.

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Hirai, Yasuharu; Nishino, Eri; Ohmori, Harunori

2015-06-01

Despite its widespread use, high-resolution imaging with multiphoton microscopy to record neuronal signals in vivo is limited to the surface of brain tissue because of limited light penetration. Moreover, most imaging studies do not simultaneously record electrical neural activity, which is, however, crucial to understanding brain function. Accordingly, we developed a photometric patch electrode (PME) to overcome the depth limitation of optical measurements and also enable the simultaneous recording of neural electrical responses in deep brain regions. The PME recoding system uses a patch electrode to excite a fluorescent dye and to measure the fluorescence signal as a light guide, to record electrical signal, and to apply chemicals to the recorded cells locally. The optical signal was analyzed by either a spectrometer of high light sensitivity or a photomultiplier tube depending on the kinetics of the responses. We used the PME in Oregon Green BAPTA-1 AM-loaded avian auditory nuclei in vivo to monitor calcium signals and electrical responses. We demonstrated distinct response patterns in three different nuclei of the ascending auditory pathway. On acoustic stimulation, a robust calcium fluorescence response occurred in auditory cortex (field L) neurons that outlasted the electrical response. In the auditory midbrain (inferior colliculus), both responses were transient. In the brain-stem cochlear nucleus magnocellularis, calcium response seemed to be effectively suppressed by the activity of metabotropic glutamate receptors. In conclusion, the PME provides a powerful tool to study brain function in vivo at a tissue depth inaccessible to conventional imaging devices. Copyright © 2015 the American Physiological Society.

Origin of hyperbolicity in brain-to-brain coordination networks

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Tadić, Bosiljka; Andjelković, Miroslav; Šuvakov, Milovan

2018-02-01

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are delta-hyperbolic with delta_max=1 and the graph diameter D=3 in each brain. While the emergent hyperbolicity in the two-brain networks satisfies delta_max/D/2 neuronal correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener’s self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

A functional TOC complex contributes to gravity signal transduction in Arabidopsis.

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Strohm, Allison K; Barrett-Wilt, Greg A; Masson, Patrick H

2014-01-01

Although plastid sedimentation has long been recognized as important for a plant's perception of gravity, it was recently shown that plastids play an additional function in gravitropism. The Translocon at the Outer envelope membrane of Chloroplasts (TOC) complex transports nuclear-encoded proteins into plastids, and a receptor of this complex, Toc132, was previously hypothesized to contribute to gravitropism either by directly functioning as a gravity signal transducer or by indirectly mediating the plastid localization of a gravity signal transducer. Here we show that mutations in multiple genes encoding TOC complex components affect gravitropism in a genetically sensitized background and that the cytoplasmic acidic domain of Toc132 is not required for its involvement in this process. Furthermore, mutations in TOC132 enhance the gravitropic defect of a mutant whose amyloplasts lack starch. Finally, we show that the levels of several nuclear-encoded root proteins are altered in toc132 mutants. These data suggest that the TOC complex indirectly mediates gravity signal transduction in Arabidopsis and support the idea that plastids are involved in gravitropism not only through their ability to sediment but also as part of the signal transduction mechanism.

Reduction of brain mitochondrial β-oxidation impairs complex I and V in chronic alcohol intake: the underlying mechanism for neurodegeneration.

Directory of Open Access Journals (Sweden)

James Haorah

Full Text Available Neuropathy and neurocognitive deficits are common among chronic alcohol users, which are believed to be associated with mitochondrial dysfunction in the brain. The specific type of brain mitochondrial respiratory chain complexes (mRCC that are adversely affected by alcohol abuse has not been studied. Thus, we examined the alterations of mRCC in freshly isolated mitochondria from mice brain that were pair-fed the ethanol (4% v/v and control liquid diets for 7-8 weeks. We observed that alcohol intake severely reduced the levels of complex I and V. A reduction in complex I was associated with a decrease in carnitine palmitoyltransferase 1 (cPT1 and cPT2 levels. The mitochondrial outer (cPT1 and inner (cPT2 membrane transporter enzymes are specialized in acylation of fatty acid from outer to inner membrane of mitochondria for ATP production. Thus, our results showed that alterations of cPT1 and cPT2 paralleled a decrease β-oxidation of palmitate and ATP production, suggesting that impairment of substrate entry step (complex I function can cause a negative impact on ATP production (complex V function. Disruption of cPT1/cPT2 was accompanied by an increase in cytochrome C leakage, while reduction of complex I and V paralleled a decrease in depolarization of mitochondrial membrane potential (ΔΨ, monitored by JC-1 fluorescence and ATP production in alcohol intake. We noted that acetyl-L-carnitine (ALC, a cofactor of cPT1 and cPT2 prevented the adverse effects of alcohol while coenzyme Q10 (CoQ10 was not very effective against alcohol insults. These results suggest that understanding the molecular, biochemical, and signaling mechanisms of the CNS mitochondrial β-oxidation such as ALC can mitigate alcohol related neurological disorders.

Reduction of brain mitochondrial β-oxidation impairs complex I and V in chronic alcohol intake: the underlying mechanism for neurodegeneration.

Science.gov (United States)

Haorah, James; Rump, Travis J; Xiong, Huangui

2013-01-01

Neuropathy and neurocognitive deficits are common among chronic alcohol users, which are believed to be associated with mitochondrial dysfunction in the brain. The specific type of brain mitochondrial respiratory chain complexes (mRCC) that are adversely affected by alcohol abuse has not been studied. Thus, we examined the alterations of mRCC in freshly isolated mitochondria from mice brain that were pair-fed the ethanol (4% v/v) and control liquid diets for 7-8 weeks. We observed that alcohol intake severely reduced the levels of complex I and V. A reduction in complex I was associated with a decrease in carnitine palmitoyltransferase 1 (cPT1) and cPT2 levels. The mitochondrial outer (cPT1) and inner (cPT2) membrane transporter enzymes are specialized in acylation of fatty acid from outer to inner membrane of mitochondria for ATP production. Thus, our results showed that alterations of cPT1 and cPT2 paralleled a decrease β-oxidation of palmitate and ATP production, suggesting that impairment of substrate entry step (complex I function) can cause a negative impact on ATP production (complex V function). Disruption of cPT1/cPT2 was accompanied by an increase in cytochrome C leakage, while reduction of complex I and V paralleled a decrease in depolarization of mitochondrial membrane potential (ΔΨ, monitored by JC-1 fluorescence) and ATP production in alcohol intake. We noted that acetyl-L-carnitine (ALC, a cofactor of cPT1 and cPT2) prevented the adverse effects of alcohol while coenzyme Q10 (CoQ10) was not very effective against alcohol insults. These results suggest that understanding the molecular, biochemical, and signaling mechanisms of the CNS mitochondrial β-oxidation such as ALC can mitigate alcohol related neurological disorders.

CD73 is a major regulator of adenosinergic signalling in mouse brain.

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Natalia Kulesskaya

Full Text Available CD73 (ecto-5'-nucleotidase is a cell surface enzyme that regulates purinergic signalling by desphosphorylating extracellular AMP to adenosine. 5'-nucleotidases are known to be expressed in brain, but the expression of CD73 and its putative physiological functions at this location remain elusive. Here we found, using immunohistochemistry of wild-type and CD73 deficient mice, that CD73 is prominently expressed in the basal ganglia core comprised of striatum (caudate nucleus and putamen and globus pallidus. Furthermore, meninges and the olfactory tubercle were found to specifically express CD73. Analysis of wild type (wt and CD73 deficient mice revealed that CD73 confers the majority of 5'-nucleotidase activity in several areas of the brain. In a battery of behavioural tests and in IntelliCage studies, the CD73 deficient mice demonstrated significantly enhanced exploratory locomotor activity, which probably reflects the prominent expression of CD73 in striatum and globus pallidus that are known to control locomotion. Furthermore, the CD73 deficient mice displayed altered social behaviour. Overall, our data provide a novel mechanistic insight into adenosinergic signalling in brain, which is implicated in the regulation of normal and pathological behaviour.

Activation of Brain Somatostatin Signaling Suppresses CRF Receptor-Mediated Stress Response

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Andreas Stengel

2017-04-01

Full Text Available Corticotropin-releasing factor (CRF is the hallmark brain peptide triggering the response to stress and mediates—in addition to the stimulation of the hypothalamus-pituitary-adrenal (HPA axis—other hormonal, behavioral, autonomic and visceral components. Earlier reports indicate that somatostatin-28 injected intracerebroventricularly counteracts the acute stress-induced ACTH and catecholamine release. Mounting evidence now supports that activation of brain somatostatin signaling exerts a broader anti-stress effect by blunting the endocrine, autonomic, behavioral (with a focus on food intake and visceral gastrointestinal motor responses through the involvement of distinct somatostatin receptor subtypes.

Entropy for the Complexity of Physiological Signal Dynamics.

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Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Lamotrigine blocks NMDA receptor-initiated arachidonic acid signalling in rat brain: Implications for its efficacy in bipolar disorder

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Ramadan, Epolia; Basselin, Mireille; Rao, Jagadeesh S.; Chang, Lisa; Chen, Mei; Ma, Kaizong; Rapoport, Stanley I.

2011-01-01

An upregulated brain arachidonic acid (AA) cascade and a hyperglutamatergic state characterize bipolar disorder (BD). Lamotrigine (LTG), a mood stabilizer approved for treating BD, is reported to interfere with glutamatergic neurotransmission involving N-methyl-D-aspartate receptors (NMDARs). NMDARs allow extracellular calcium into the cell, thereby stimulating calcium-dependent cytosolic phospholipase A2 (cPLA2) to release arachidonic acid (AA) from membrane phospholipid. We hypothesized that LTG, like other approved mood stabilizers, would reduce NMDAR-mediated AA signaling in rat brain. An acute subconvulsant dose of NMDA (25 mg/kg) or saline was administered intraperitoneally to unanesthetized rats that had been treated p.o. daily for 42 days with vehicle or a therapeutically relevant dose of LTG (10 mg/kg/.d). Regional brain AA incorporation coefficients k* and rates Jin, AA signals, were measured using quantitative autoradiography after intravenous [1-14C]AA infusion, as were other AA cascade markers. In chronic vehicle-treated rats, acute NMDA compared to saline increased k* and Jin in widespread regions of the brain, as well as prostaglandin (PG)E2 and thromboxane B2 concentrations. Chronic LTG treatment compared to vehicle reduced brain cyclooxygenase (COX) activity, PGE2 concentration, and DNA binding activity of the COX-2 transcription factor, NF-κB. Pretreatment with chronic LTG blocked the acute NMDA effects on AA cascade markers. In summary, chronic LTG like other mood stabilizers blocks NMDA-mediated signaling involving the AA metabolic cascade. Since markers of the AA cascade and of NMDAR signaling are up-regulated in the postmortem BD brain, mood stabilizers generally may be effective in BD by dampening NMDAR signalling and the AA cascade. PMID:21733229

Stochastic effects as a force to increase the complexity of signaling networks

KAUST Repository

Kuwahara, Hiroyuki; Gao, Xin

2013-01-01

Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism

Linking brain, mind and behavior.

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Makeig, Scott; Gramann, Klaus; Jung, Tzyy-Ping; Sejnowski, Terrence J; Poizner, Howard

2009-08-01

Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.

Exome localization of complex disease association signals

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Lewis Cathryn M

2011-02-01

Full Text Available Abstract Background Genome-wide association studies (GWAS of common diseases have had a tremendous impact on genetic research over the last five years; the field is now moving from microarray-based technology towards next-generation sequencing. To evaluate the potential of association studies for complex diseases based on exome sequencing we analysed the distribution of association signal with respect to protein-coding genes based on GWAS data for seven diseases from the Wellcome Trust Case Control Consortium. Results We find significant concentration of association signal in exons and genes for Crohn's Disease, Type 1 Diabetes and Bipolar Disorder, but also observe enrichment from up to 40 kilobases upstream to 40 kilobases downstream of protein-coding genes for Crohn's Disease and Type 1 Diabetes; the exact extent of the distribution is disease dependent. Conclusions Our work suggests that exome sequencing may be a feasible approach to find genetic variation associated with complex disease. Extending the exome sequencing to include flanking regions therefore promises further improvement of covering disease-relevant variants.

Beacon signal in transcranial color coded ultrasound: A sign for brain death

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Mehmet Akif Topçuoğlu

2014-04-01

Full Text Available A widely under-recognized brain-death confirming transcranial ultrasonography pattern resembling the red-blue beacon signal was demonstrated. Familiarity to this distinct and characteristic ultrasonic pattern seems to be important in the perspective of point-of-care neurological ultrasound use and knobology.

Dangerous mating systems: signal complexity, signal content and neural capacity in spiders.

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Herberstein, M E; Wignall, A E; Hebets, E A; Schneider, J M

2014-10-01

Spiders are highly efficient predators in possession of exquisite sensory capacities for ambushing prey, combined with machinery for launching rapid and determined attacks. As a consequence, any sexually motivated approach carries a risk of ending up as prey rather than as a mate. Sexual selection has shaped courtship to effectively communicate the presence, identity, motivation and/or quality of potential mates, which help ameliorate these risks. Spiders communicate this information via several sensory channels, including mechanical (e.g. vibrational), visual and/or chemical, with examples of multimodal signalling beginning to emerge in the literature. The diverse environments that spiders inhabit have further shaped courtship content and form. While our understanding of spider neurobiology remains in its infancy, recent studies are highlighting the unique and considerable capacities of spiders to process and respond to complex sexual signals. As a result, the dangerous mating systems of spiders are providing important insights into how ecology shapes the evolution of communication systems, with future work offering the potential to link this complex communication with its neural processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Alternate day fasting impacts the brain insulin-signaling pathway of young adult male C57BL/6 mice.

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Lu, Jianghua; E, Lezi; Wang, Wenfang; Frontera, Jennifer; Zhu, Hao; Wang, Wen-Tung; Lee, Phil; Choi, In Young; Brooks, William M; Burns, Jeffrey M; Aires, Daniel; Swerdlow, Russell H

2011-04-01

Dietary restriction (DR) has recognized health benefits that may extend to brain. We examined how DR affects bioenergetics-relevant enzymes and signaling pathways in the brains of C57BL/6 mice. Five-month-old male mice were placed in ad libitum or one of two repeated fasting and refeeding (RFR) groups, an alternate day (intermittent fed; IF) or alternate day plus antioxidants (blueberry, pomegranate, and green tea extracts) (IF + AO) fed group. During the 24-h fast blood glucose levels initially fell but stabilized within 6 h of starting the fast, thus avoiding frank hypoglycemia. DR in general appeared to enhance insulin sensitivity. After six weeks brain AKT and glycogen synthase kinase 3 beta phosphorylation were lower in the RFR mice, suggesting RFR reduced brain insulin-signaling pathway activity. Pathways that mediate mitochondrial biogenesis were not activated; AMP kinase phosphorylation, silent information regulator 2 phosphorylation, peroxisomal proliferator-activated receptor-gamma coactivator 1 alpha levels, and cytochrome oxidase subunit 4 levels did not change. ATP levels also did not decline, which suggests the RFR protocols did not directly impact brain bioenergetics. Antioxidant supplementation did not affect the brain parameters we evaluated. Our data indicate in young adult male C57BL/6 mice, RFR primarily affects brain energy metabolism by reducing brain insulin signaling, which potentially results indirectly as a consequence of reduced peripheral insulin production. © 2011 The Authors. Journal of Neurochemistry © 2011 International Society for Neurochemistry.

Estrogenic Endocrine Disrupting Chemicals Influencing NRF1 Regulated Gene Networks in the Development of Complex Human Brain Diseases.

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Preciados, Mark; Yoo, Changwon; Roy, Deodutta

2016-12-13

signaling pathways. Our findings suggest that in addition to estrogen signaling, EEDs influencing NRF1 regulated communities of genes across genomic and epigenomic multiple networks may contribute in the development of complex chronic human brain health disorders.

Estrogenic Endocrine Disrupting Chemicals Influencing NRF1 Regulated Gene Networks in the Development of Complex Human Brain Diseases

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Mark Preciados

2016-12-01

findings suggest that in addition to estrogen signaling, EEDs influencing NRF1 regulated communities of genes across genomic and epigenomic multiple networks may contribute in the development of complex chronic human brain health disorders.

Complexity and multifractality of neuronal noise in mouse and human hippocampal epileptiform dynamics

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Serletis, Demitre; Bardakjian, Berj L.; Valiante, Taufik A.; Carlen, Peter L.

2012-10-01

Fractal methods offer an invaluable means of investigating turbulent nonlinearity in non-stationary biomedical recordings from the brain. Here, we investigate properties of complexity (i.e. the correlation dimension, maximum Lyapunov exponent, 1/fγ noise and approximate entropy) and multifractality in background neuronal noise-like activity underlying epileptiform transitions recorded at the intracellular and local network scales from two in vitro models: the whole-intact mouse hippocampus and lesional human hippocampal slices. Our results show evidence for reduced dynamical complexity and multifractal signal features following transition to the ictal epileptiform state. These findings suggest that pathological breakdown in multifractal complexity coincides with loss of signal variability or heterogeneity, consistent with an unhealthy ictal state that is far from the equilibrium of turbulent yet healthy fractal dynamics in the brain. Thus, it appears that background noise-like activity successfully captures complex and multifractal signal features that may, at least in part, be used to classify and identify brain state transitions in the healthy and epileptic brain, offering potential promise for therapeutic neuromodulatory strategies for afflicted patients suffering from epilepsy and other related neurological disorders. This paper is based on chapter 5 of Serletis (2010 PhD Dissertation Department of Physiology, Institute of Biomaterials and Biomedical Engineering, University of Toronto).

Interleukin-6 (IL-6) receptor/IL-6 fusion protein (Hyper IL-6) effects on the neonatal mouse brain: possible role for IL-6 trans-signaling in brain development and functional neurobehavioral outcomes.

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Brunssen, Susan H; Moy, Sheryl S; Toews, Arrel D; McPherson, Christopher A; Harry, G Jean

2013-01-01

Adverse neurodevelopmental outcomes are linked to perinatal production of inflammatory mediators, including interleukin 6 (IL-6). While a pivotal role for maternal elevation in IL-6 has been established in determining neurobehavioral outcomes in the offspring and considered the primary target mediating the fetal inflammatory response, questions remain as to the specific actions of IL-6 on the developing brain. CD-1 male mice received a subdural injection of the bioactive fusion protein, hyper IL-6 (HIL-6) on postnatal-day (PND)4 and assessed from preweaning until adulthood. Immunohistochemical evaluation of astrocytes and microglia and mRNA levels for pro-inflammatory cytokines and host response genes indicated no evidence of an acute neuroinflammatory injury response. HIL-6 accelerated motor development and increased reactivity to stimulation and number of entries in a light/dark chamber, decreased ability to learn to withhold a response in passive avoidance, and effected deficits in social novelty behavior. No changes were observed in motor activity, pre-pulse startle inhibition, or learning and memory in the Morris water maze or radial arm maze, as have been reported for models of more severe developmental neuroinflammation. In young animals, mRNA levels for MBP and PLP/DM20 decreased and less complexity of MBP processes in the cortex was evident by immunohistochemistry. The non-hydroxy cerebroside fraction of cerebral lipids was increased. These results provide evidence for selective effects of IL-6 signaling, particularly trans-signaling, in the developing brain in the absence of a general neuroinflammatory response. These data contribute to our further understanding of the multiple aspects of IL-6 signaling in the developing brain. Published by Elsevier Inc.

Tobacco Smoke Exposure Impairs Brain Insulin/IGF Signaling: Potential Co-Factor Role in Neurodegeneration.

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Deochand, Chetram; Tong, Ming; Agarwal, Amit R; Cadenas, Enrique; de la Monte, Suzanne M

2016-01-01

Human studies suggest tobacco smoking is a risk factor for cognitive impairment and neurodegeneration, including Alzheimer's disease (AD). However, experimental data linking tobacco smoke exposures to underlying mediators of neurodegeneration, including impairments in brain insulin and insulin-like growth factor (IGF) signaling in AD are lacking. This study tests the hypothesis that cigarette smoke (CS) exposures can impair brain insulin/IGF signaling and alter expression of AD-associated proteins. Adult male A/J mice were exposed to air for 8 weeks (A8), CS for 4 or 8 weeks (CS4, CS8), or CS8 followed by 2 weeks recovery (CS8+R). Gene expression was measured by qRT-PCR analysis and proteins were measured by multiplex bead-based or direct binding duplex ELISAs. CS exposure effects on insulin/IGF and insulin receptor substrate (IRS) proteins and phosphorylated proteins were striking compared with the mRNA. The main consequences of CS4 or CS8 exposures were to significantly reduce insulin R, IGF-1R, IRS-1, and tyrosine phosphorylated insulin R and IGF-1R proteins. Paradoxically, these effects were even greater in the CS8+R group. In addition, relative levels of S312-IRS-1, which inhibits downstream signaling, were increased in the CS4, CS8, and CS8+R groups. Correspondingly, CS and CS8+R exposures inhibited expression of proteins and phosphoproteins required for signaling through Akt, PRAS40, and/or p70S6K, increased AβPP-Aβ, and reduced ASPH protein, which is a target of insulin/IGF-1 signaling. Secondhand CS exposures caused molecular and biochemical abnormalities in brain that overlap with the findings in AD, and many of these effects were sustained or worsened despite short-term CS withdrawal.

Frequency dependence of complex moduli of brain tissue using a fractional Zener model

International Nuclear Information System (INIS)

Kohandel, M; Sivaloganathan, S; Tenti, G; Darvish, K

2005-01-01

Brain tissue exhibits viscoelastic behaviour. If loading times are substantially short, static tests are not sufficient to determine the complete viscoelastic behaviour of the material, and dynamic test methods are more appropriate. The concept of complex modulus of elasticity is a powerful tool for characterizing the frequency domain behaviour of viscoelastic materials. On the other hand, it is well known that classical viscoelastic models can be generalized by means of fractional calculus to describe more complex viscoelastic behaviour of materials. In this paper, the fractional Zener model is investigated in order to describe the dynamic behaviour of brain tissue. The model is fitted to experimental data of oscillatory shear tests of bovine brain tissue to verify its behaviour and to obtain the material parameters

Imaging of endogenous exchangeable proton signals in the human brain using frequency labeled exchange transfer imaging.

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Yadav, Nirbhay N; Jones, Craig K; Hua, Jun; Xu, Jiadi; van Zijl, Peter C M

2013-04-01

To image endogenous exchangeable proton signals in the human brain using a recently reported method called frequency labeled exchange transfer (FLEX) MRI. As opposed to labeling exchangeable protons using saturation (i.e., chemical exchange saturation transfer, or CEST), FLEX labels exchangeable protons with their chemical shift evolution. The use of short high-power frequency pulses allows more efficient labeling of rapidly exchanging protons, while time domain acquisition allows removal of contamination from semi-solid magnetization transfer effects. FLEX-based exchangeable proton signals were detected in human brain over the 1-5 ppm frequency range from water. Conventional magnetization transfer contrast and the bulk water signal did not interfere in the FLEX spectrum. The information content of these signals differed from in vivo CEST data in that the average exchange rate of these signals was 350-400 s(-1) , much faster than the amide signal usually detected using direct saturation (∼30 s(-1) ). Similarly, fast exchanging protons could be detected in egg white in the same frequency range where amide and amine protons of mobile proteins and peptides are known to resonate. FLEX MRI in the human brain preferentially detects more rapidly exchanging amide/amine protons compared to traditional CEST experiments, thereby changing the information content of the exchangeable proton spectrum. This has the potential to open up different types of endogenous applications as well as more easy detection of rapidly exchanging protons in diaCEST agents or fast exchanging units such as water molecules in paracest agents without interference of conventional magnetization transfer contrast. Copyright © 2013 Wiley Periodicals, Inc.

SPATA2-Mediated Binding of CYLD to HOIP Enables CYLD Recruitment to Signaling Complexes

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Sebastian Kupka

2016-08-01

Full Text Available Recruitment of the deubiquitinase CYLD to signaling complexes is mediated by its interaction with HOIP, the catalytically active component of the linear ubiquitin chain assembly complex (LUBAC. Here, we identify SPATA2 as a constitutive direct binding partner of HOIP that bridges the interaction between CYLD and HOIP. SPATA2 recruitment to TNFR1- and NOD2-signaling complexes is dependent on HOIP, and loss of SPATA2 abolishes CYLD recruitment. Deficiency in SPATA2 exerts limited effects on gene activation pathways but diminishes necroptosis induced by tumor necrosis factor (TNF, resembling loss of CYLD. In summary, we describe SPATA2 as a previously unrecognized factor in LUBAC-dependent signaling pathways that serves as an adaptor between HOIP and CYLD, thereby enabling recruitment of CYLD to signaling complexes.

The alterations in biochemical signaling of hippocampal network activity in the autism brain The alterations in biochemical signaling of hippocampal network activity in the autism brain The alterations in biochemical signaling of hippocampal network activity in the autism brain

Institute of Scientific and Technical Information of China (English)

田允; 黄继云; 王锐; 陶蓉蓉; 卢应梅; 廖美华; 陆楠楠; 李静; 芦博; 韩峰

2012-01-01

Autism is a highly heritable neurodevelopmental condition characterized by impaired social interaction and communication. However, the role of synaptic dysfunction during development of autism remains unclear. In the present study, we address the alterations of biochemical signaling in hippocampal network following induction of the autism in experimental animals. Here, the an- imal disease model and DNA array being used to investigate the differences in transcriptome or- ganization between autistic and normal brain by gene co--expression network analysis.

Brain-Computer Interfaces in Medicine

Science.gov (United States)

Shih, Jerry J.; Krusienski, Dean J.; Wolpaw, Jonathan R.

2012-01-01

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. PMID:22325364

Simulation study on effects of signaling network structure on the developmental increase in complexity

Energy Technology Data Exchange (ETDEWEB)

Keranen, Soile V.E.

2003-04-02

The developmental increase in structural complexity in multicellular life forms depends on local, often non-periodic differences in gene expression. These depend on a network of gene-gene interactions coded within the organismal genome. To better understand how genomic information generates complex expression patterns, I have modeled the pattern forming behavior of small artificial genomes in virtual blastoderm embryos. I varied several basic properties of these genomic signaling networks, such as the number of genes, the distributions of positive (inductive) and negative (repressive) interactions, and the strengths of gene-gene interactions, and analyzed their effects on developmental pattern formation. The results show how even simple genomes can generate complex non-periodic patterns under suitable conditions. They also show how the frequency of complex patterns depended on the numbers and relative arrangements of positive and negative interactions. For example, negative co-regulation of signaling pathway components increased the likelihood of (complex) patterns relative to differential negative regulation of the pathway components. Interestingly, neither quantitative differences either in strengths of signaling interactions nor multiple response thresholds to signal concentration (as in morphogen gradients) were essential for formation of multiple, spatially unique cell types. Thus, with combinatorial code of gene regulation and hierarchical signaling interactions, it is theoretically possible to organize metazoan embryogenesis with just a small fraction of the metazoan genome. Because even small networks can generate complex patterns when they contain a suitable set of connections, evolution of metazoan complexity may have depended more on selection for favourable configurations of signaling interactions than on the increase in numbers of regulatory genes.

Aliasing in the Complex Cepstrum of Linear-Phase Signals

DEFF Research Database (Denmark)

Bysted, Tommy Kristensen

1997-01-01

Assuming linear-phase of the associated time signal, this paper presents an approximated analytical description of the unavoidable aliasing in practical use of complex cepstrums. The linear-phase assumption covers two major applications of complex cepstrums which are linear- to minimum-phase FIR......-filter transformation and minimum-phase estimation from amplitude specifications. The description is made in the cepstrum domain, the Fourier transform of the complex cepstrum and in the frequency domain. Two examples are given, one for verification of the derived equations and one using the description to reduce...... aliasing in minimum-phase estimation...

Statistical complexity is maximized in a small-world brain.

Directory of Open Access Journals (Sweden)

Teck Liang Tan

Full Text Available In this paper, we study a network of Izhikevich neurons to explore what it means for a brain to be at the edge of chaos. To do so, we first constructed the phase diagram of a single Izhikevich excitatory neuron, and identified a small region of the parameter space where we find a large number of phase boundaries to serve as our edge of chaos. We then couple the outputs of these neurons directly to the parameters of other neurons, so that the neuron dynamics can drive transitions from one phase to another on an artificial energy landscape. Finally, we measure the statistical complexity of the parameter time series, while the network is tuned from a regular network to a random network using the Watts-Strogatz rewiring algorithm. We find that the statistical complexity of the parameter dynamics is maximized when the neuron network is most small-world-like. Our results suggest that the small-world architecture of neuron connections in brains is not accidental, but may be related to the information processing that they do.

Alteration of brain insulin and leptin signaling promotes energy homeostasis impairment and neurodegenerative diseases

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Taouis Mohammed

2011-09-01

Full Text Available The central nervous system (CNS controls vital functions, by efficiently coordinating peripheral and central cascades of signals and networks in a coordinated manner. Historically, the brain was considered to be an insulin-insensitive tissue. But, new findings demonstrating that insulin is present in different regions of themammalian brain, in particular the hypothalamus and the hippocampus. Insulin acts through specific receptors and dialogues with numerous peptides, neurotransmitters and adipokines such as leptin. The cross-talk between leptin and insulin signaling pathways at the hypothalamic level is clearly involved in the control of energy homeostasis. Both hormones are anorexigenic through their action on hypothalamic arcuate nucleus by inducing the expression of anorexigenic neuropetides such as POMC (pro-opiomelanocortin, the precursor of aMSH and reducing the expression of orexigenic neuropeptide such as NPY (Neuropeptide Y. Central defect of insulin and leptin signaling predispose to obesity (leptin-resistant state and type-2 diabetes (insulin resistant state. Obesity and type-2 diabetes are associated to deep alterations in energy homeostasis control but also to other alterations of CNS functions as the predisposition to neurodegenerative diseases such as Alzheimer’s disease (AD. AD is a neurodegenerative disorder characterized by distinct hallmarks within the brain. Postmortem observation of AD brains showed the presence of parenchymal plaques due to the accumulation of the amyloid beta (AB peptide and neurofibrillary tangles. These accumulations result from the hyperphosphorylation of tau (a mictrotubule-interacting protein. Both insulin and leptin have been described to modulate tau phosphorylation and therefore in leptin and insulin resistant states may contribute to AD. The concentrations of leptin and insulin cerebrospinal fluid are decreased type2 diabetes and obese patients. In addition, the concentration of insulin in the

Structure-function relationship in complex brain networks expressed by hierarchical synchronization

International Nuclear Information System (INIS)

Zhou Changsong; Zemanova, Lucia; Zamora-Lopez, Gorka; Hilgetag, Claus C; Kurths, Juergen

2007-01-01

The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks

Structure-function relationship in complex brain networks expressed by hierarchical synchronization

Energy Technology Data Exchange (ETDEWEB)

Zhou Changsong [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zemanova, Lucia [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zamora-Lopez, Gorka [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Hilgetag, Claus C [Jacobs University Bremen, Campus Ring 6, Rm 116, D-28759 Bremen (Germany); Kurths, Juergen [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany)

2007-06-15

The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.

Predict or classify: The deceptive role of time-locking in brain signal classification

Science.gov (United States)

Rusconi, Marco; Valleriani, Angelo

2016-06-01

Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

An automated approach towards detecting complex behaviours in deep brain oscillations.

Science.gov (United States)

Mace, Michael; Yousif, Nada; Naushahi, Mohammad; Abdullah-Al-Mamun, Khondaker; Wang, Shouyan; Nandi, Dipankar; Vaidyanathan, Ravi

2014-03-15

Extracting event-related potentials (ERPs) from neurological rhythms is of fundamental importance in neuroscience research. Standard ERP techniques typically require the associated ERP waveform to have low variance, be shape and latency invariant and require many repeated trials. Additionally, the non-ERP part of the signal needs to be sampled from an uncorrelated Gaussian process. This limits methods of analysis to quantifying simple behaviours and movements only when multi-trial data-sets are available. We introduce a method for automatically detecting events associated with complex or large-scale behaviours, where the ERP need not conform to the aforementioned requirements. The algorithm is based on the calculation of a detection contour and adaptive threshold. These are combined using logical operations to produce a binary signal indicating the presence (or absence) of an event with the associated detection parameters tuned using a multi-objective genetic algorithm. To validate the proposed methodology, deep brain signals were recorded from implanted electrodes in patients with Parkinson's disease as they participated in a large movement-based behavioural paradigm. The experiment involved bilateral recordings of local field potentials from the sub-thalamic nucleus (STN) and pedunculopontine nucleus (PPN) during an orientation task. After tuning, the algorithm is able to extract events achieving training set sensitivities and specificities of [87.5 ± 6.5, 76.7 ± 12.8, 90.0 ± 4.1] and [92.6 ± 6.3, 86.0 ± 9.0, 29.8 ± 12.3] (mean ± 1 std) for the three subjects, averaged across the four neural sites. Furthermore, the methodology has the potential for utility in real-time applications as only a single-trial ERP is required. Copyright © 2013 Elsevier B.V. All rights reserved.

Activation of stress signaling molecules in bat brain during arousal from hibernation.

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Lee, Moonyong; Choi, Inho; Park, Kyoungsook

2002-08-01

Induction of glucose-regulated proteins (GRPs) is a ubiquitous intracellular response to stresses such as hypoxia, glucose starvation and acidosis. The induction of GRPs offers some protection against these stresses in vitro, but the specific role of GRPs in vivo remains unclear. Hibernating bats present a good in vivo model to address this question. The bats must overcome local high oxygen demand in tissue by severe metabolic stress during arousal thermogenesis. We used brain tissue of a temperate bat Rhinolopus ferrumequinum to investigate GRP induction by high metabolic oxygen demand and to identify associated signaling molecules. We found that during 30 min of arousal, oxygen consumption increased from nearly zero to 11.9/kg/h, which was about 8.7-fold higher than its active resting metabolic rate. During this time, body temperature rose from 7 degrees C to 35 degrees C, and levels of TNF-alpha and lactate in brain tissue increased 2-2.5-fold, indicating a high risk of oxygen shortage. Concomitantly, levels of GRP75, GRP78 and GRP94 increased 1.5-1.7-fold. At the same time, c-Jun N-terminal protein kinase (JNK) activity increased 6.4-fold, and extracellular signal-regulated protein kinase (ERK) activity decreased to a similar degree (6.1-fold). p38 MAPK activity was very low and remained unchanged during arousal. In addition, survival signaling molecules protein kinase B (Akt) and protein kinase C (PKC) were activated 3- and 5-fold, respectively, during arousal. Taken together, our results showed that bat brain undergoes high oxygen demand during arousal from hibernation. Up-regulation of GRP proteins and activation of JNK, PKCgamma and Akt may be critical for neuroprotection and the survival of bats during the repeated process.

Labor Inhibits Placental Mechanistic Target of Rapamycin Complex 1 Signaling

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LAGER, Susanne; AYE, Irving L.M.H.; GACCIOLI, Francesca; RAMIREZ, Vanessa I.; JANSSON, Thomas; POWELL, Theresa L.

2014-01-01

Introduction Labor induces a myriad of changes in placental gene expression. These changes may represent a physiological adaptation inhibiting placental cellular processes associated with a high demand for oxygen and energy (e.g., protein synthesis and active transport) thereby promoting oxygen and glucose transfer to the fetus. We hypothesized that mechanistic target of rapamycin complex 1 (mTORC1) signaling, a positive regulator of trophoblast protein synthesis and amino acid transport, is inhibited by labor. Methods Placental tissue was collected from healthy, term pregnancies (n=15 no-labor; n=12 labor). Activation of Caspase-1, IRS1/Akt, STAT, mTOR, and inflammatory signaling pathways was determined by Western blot. NFκB p65 and PPARγ DNA binding activity was measured in isolated nuclei. Results Labor increased Caspase-1 activation and mTOR complex 2 signaling, as measured by phosphorylation of Akt (S473). However, mTORC1 signaling was inhibited in response to labor as evidenced by decreased phosphorylation of mTOR (S2448) and 4EBP1 (T37/46 and T70). Labor also decreased NFκB and PPARγ DNA binding activity, while having no effect on IRS1 or STAT signaling pathway. Discussion and conclusion Several placental signaling pathways are affected by labor, which has implications for experimental design in studies of placental signaling. Inhibition of placental mTORC1 signaling in response to labor may serve to down-regulate protein synthesis and amino acid transport, processes that account for a large share of placental oxygen and glucose consumption. We speculate that this response preserves glucose and oxygen for transfer to the fetus during the stressful events of labor. PMID:25454472

Curcumin ameliorates insulin signalling pathway in brain of Alzheimer's disease transgenic mice.

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Feng, Hui-Li; Dang, Hui-Zi; Fan, Hui; Chen, Xiao-Pei; Rao, Ying-Xue; Ren, Ying; Yang, Jin-Duo; Shi, Jing; Wang, Peng-Wen; Tian, Jin-Zhou

2016-12-01

Deficits in glucose, impaired insulin signalling and brain insulin resistance are common in the pathogenesis of Alzheimer's disease (AD); therefore, some scholars even called AD type 3 diabetes mellitus. Curcumin can reduce the amyloid pathology in AD. Moreover, it is a well-known fact that curcumin has anti-oxidant and anti-inflammatory properties. However, whether or not curcumin could regulate the insulin signal transduction pathway in AD remains unclear. In this study, we used APPswe/PS1dE9 double transgenic mice as the AD model to investigate the mechanisms and the effects of curcumin on AD. Immunohistochemical (IHC) staining and a western blot analysis were used to test the major proteins in the insulin signal transduction pathway. After the administration of curcumin for 6 months, the results showed that the expression of an insulin receptor (InR) and insulin receptor substrate (IRS)-1 decreased in the hippocampal CA1 area of the APPswe/PS1dE9 double transgenic mice, while the expression of phosphatidylinositol-3 kinase (PI3K), phosphorylated PI3K (p-PI3K), serine-threonine kinase (AKT) and phosphorylated AKT (p-AKT) increased. Among the curcumin groups, the medium-dose group was the most effective one. Thus, we believe that curcumin may be a potential therapeutic agent that can regulate the critical molecules in brain insulin signalling pathways. Furthermore, curcumin could be adopted as one of the AD treatments to improve a patient's learning and memory ability. © The Author(s) 2016.

Reduced Predictable Information in Brain Signals in Autism Spectrum Disorder

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Carlos eGomez

2014-02-01

Full Text Available Autism spectrum disorder (ASD is a common developmental disorder characterized by communication difficulties and impaired social interaction. Recent results suggest altered brain dynamics as a potential cause of symptoms in ASD. Here, we aim to describe potential information-processing consequences of these alterations by measuring active information storage (AIS – a key quantity in the theory of distributed computation in biological networks. AIS is defined as the mutual information between the semi-infinite past of a process and its next state. It measures the amount of stored information that is used for computation of the next time step of a process. AIS is high for rich but predictable dynamics. We recorded magnetoencephalography (MEG signals in 13 ASD patients and 14 matched control subjects in a visual task. After a beamformer source analysis, twelve task-relevant sources were obtained. For these sources, stationary baseline activity was analyzed using AIS. Our results showed a decrease of AIS values in the hippocampus of ASD patients in comparison with controls, meaning that brain signals in ASD were either less predictable, reduced in their dynamic richness or both. Our study suggests the usefulness of AIS to detect an abnormal type of dynamics in ASD. The observed changes in AIS are compatible with Bayesian theories of reduced use or precision of priors in ASD.

Brain alpha-ketoglutarate dehydrogenase complex: kinetic properties, regional distribution, and effects of inhibitors.

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Lai, J C; Cooper, A J

1986-11-01

The substrate and cofactor requirements and some kinetic properties of the alpha-ketoglutarate dehydrogenase complex (KGDHC; EC 1.2.4.2, EC 2.3.1.61, and EC 1.6.4.3) in purified rat brain mitochondria were studied. Brain mitochondrial KGDHC showed absolute requirement for alpha-ketoglutarate, CoA and NAD, and only partial requirement for added thiamine pyrophosphate, but no requirement for Mg2+ under the assay conditions employed in this study. The pH optimum was between 7.2 and 7.4, but, at pH values below 7.0 or above 7.8, KGDHC activity decreased markedly. KGDHC activity in various brain regions followed the rank order: cerebral cortex greater than cerebellum greater than or equal to midbrain greater than striatum = hippocampus greater than hypothalamus greater than pons and medulla greater than olfactory bulb. Significant inhibition of brain mitochondrial KGDHC was noted at pathological concentrations of ammonia (0.2-2 mM). However, the purified bovine heart KGDHC and KGDHC activity in isolated rat heart mitochondria were much less sensitive to inhibition. At 5 mM both beta-methylene-D,L-aspartate and D,L-vinylglycine (inhibitors of cerebral glucose oxidation) inhibited the purified heart but not the brain mitochondrial enzyme complex. At approximately 10 microM, calcium slightly stimulated (by 10-15%) the brain mitochondrial KGDHC. At concentrations above 100 microM, calcium (IC50 = 1 mM) inhibited both brain mitochondrial and purified heart KGDHC. The present results suggest that some of the kinetic properties of the rat brain mitochondrial KGDHC differ from those of the purified bovine heart and rat heart mitochondrial enzyme complexes. They also suggest that the inhibition of KGDHC by ammonia and the consequent effect on the citric acid cycle fluxes may be of pathophysiological and/or pathogenetic importance in hyperammonemia and in diseases (e.g., hepatic encephalopathy, inborn errors of urea metabolism, Reye's syndrome) where hyperammonemia is a

The E3 ubiquitin ligase protein associated with Myc (Pam) regulates mammalian/mechanistic target of rapamycin complex 1 (mTORC1) signaling in vivo through N- and C-terminal domains.

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Han, Sangyeul; Kim, Sun; Bahl, Samira; Li, Lin; Burande, Clara F; Smith, Nicole; James, Marianne; Beauchamp, Roberta L; Bhide, Pradeep; DiAntonio, Aaron; Ramesh, Vijaya

2012-08-31

Pam and its homologs (the PHR protein family) are large E3 ubiquitin ligases that function to regulate synapse formation and growth in mammals, zebrafish, Drosophila, and Caenorhabditis elegans. Phr1-deficient mouse models (Phr1(Δ8,9) and Phr1(Magellan), with deletions in the N-terminal putative guanine exchange factor region and the C-terminal ubiquitin ligase region, respectively) exhibit axon guidance/outgrowth defects and striking defects of major axon tracts in the CNS. Our earlier studies identified Pam to be associated with tuberous sclerosis complex (TSC) proteins, ubiquitinating TSC2 and regulating mammalian/mechanistic target of rapamycin (mTOR) signaling. Here, we examine the potential involvement of the TSC/mTOR complex 1(mTORC1) signaling pathway in Phr1-deficient mouse models. We observed attenuation of mTORC1 signaling in the brains of both Phr1(Δ8,9) and Phr1(Magellan) mouse models. Our results establish that Pam regulates TSC/mTOR signaling in vitro and in vivo through two distinct domains. To further address whether Pam regulates mTORC1 through two functionally independent domains, we undertook heterozygous mutant crossing between Phr1(Δ8,9) and Phr1(Magellan) mice to generate a compound heterozygous model to determine whether these two domains can complement each other. mTORC1 signaling was not attenuated in the brains of double mutants (Phr1(Δ8,9/Mag)), confirming that Pam displays dual regulation of the mTORC1 pathway through two functional domains. Our results also suggest that although dysregulation of mTORC1 signaling may be responsible for the corpus callosum defects, other neurodevelopmental defects observed with Phr1 deficiency are independent of mTORC1 signaling. The ubiquitin ligase complex containing Pam-Fbxo45 likely targets additional synaptic and axonal proteins, which may explain the overlapping neurodevelopmental defects observed in Phr1 and Fbxo45 deficiency.

Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals.

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Demanuele, Charmaine; James, Christopher J; Sonuga-Barke, Edmund Js

2007-12-10

It has been acknowledged that the frequency spectrum of measured electromagnetic (EM) brain signals shows a decrease in power with increasing frequency. This spectral behaviour may lead to difficulty in distinguishing event-related peaks from ongoing brain activity in the electro- and magnetoencephalographic (EEG and MEG) signal spectra. This can become an issue especially in the analysis of low frequency oscillations (LFOs) - below 0.5 Hz - which are currently being observed in signal recordings linked with specific pathologies such as epileptic seizures or attention deficit hyperactivity disorder (ADHD), in sleep studies, etc. In this work we propose a simple method that can be used to compensate for this 1/f trend hence achieving spectral normalisation. This method involves filtering the raw measured EM signal through a differentiator prior to further data analysis. Applying the proposed method to various exemplary datasets including very low frequency EEG recordings, epileptic seizure recordings, MEG data and Evoked Response data showed that this compensating procedure provides a flat spectral base onto which event related peaks can be clearly observed. Findings suggest that the proposed filter is a useful tool for the analysis of physiological data especially in revealing very low frequency peaks which may otherwise be obscured by the 1/f spectral activity inherent in EEG/MEG recordings.

Signal Sampling for Efficient Sparse Representation of Resting State FMRI Data

Science.gov (United States)

Ge, Bao; Makkie, Milad; Wang, Jin; Zhao, Shijie; Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhang, Shu; Zhang, Wei; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

As the size of brain imaging data such as fMRI grows explosively, it provides us with unprecedented and abundant information about the brain. How to reduce the size of fMRI data but not lose much information becomes a more and more pressing issue. Recent literature studies tried to deal with it by dictionary learning and sparse representation methods, however, their computation complexities are still high, which hampers the wider application of sparse representation method to large scale fMRI datasets. To effectively address this problem, this work proposes to represent resting state fMRI (rs-fMRI) signals of a whole brain via a statistical sampling based sparse representation. First we sampled the whole brain’s signals via different sampling methods, then the sampled signals were aggregate into an input data matrix to learn a dictionary, finally this dictionary was used to sparsely represent the whole brain’s signals and identify the resting state networks. Comparative experiments demonstrate that the proposed signal sampling framework can speed-up by ten times in reconstructing concurrent brain networks without losing much information. The experiments on the 1000 Functional Connectomes Project further demonstrate its effectiveness and superiority. PMID:26646924

Brain source localization: A new method based on MUltiple SIgnal Classification algorithm and spatial sparsity of the field signal for electroencephalogram measurements

Science.gov (United States)

Vergallo, P.; Lay-Ekuakille, A.

2013-08-01

Brain activity can be recorded by means of EEG (Electroencephalogram) electrodes placed on the scalp of the patient. The EEG reflects the activity of groups of neurons located in the head, and the fundamental problem in neurophysiology is the identification of the sources responsible of brain activity, especially if a seizure occurs and in this case it is important to identify it. The studies conducted in order to formalize the relationship between the electromagnetic activity in the head and the recording of the generated external field allow to know pattern of brain activity. The inverse problem, that is given the sampling field at different electrodes the underlying asset must be determined, is more difficult because the problem may not have a unique solution, or the search for the solution is made difficult by a low spatial resolution which may not allow to distinguish between activities involving sources close to each other. Thus, sources of interest may be obscured or not detected and known method in source localization problem as MUSIC (MUltiple SIgnal Classification) could fail. Many advanced source localization techniques achieve a best resolution by exploiting sparsity: if the number of sources is small as a result, the neural power vs. location is sparse. In this work a solution based on the spatial sparsity of the field signal is presented and analyzed to improve MUSIC method. For this purpose, it is necessary to set a priori information of the sparsity in the signal. The problem is formulated and solved using a regularization method as Tikhonov, which calculates a solution that is the better compromise between two cost functions to minimize, one related to the fitting of the data, and another concerning the maintenance of the sparsity of the signal. At the first, the method is tested on simulated EEG signals obtained by the solution of the forward problem. Relatively to the model considered for the head and brain sources, the result obtained allows to

Mitochondrial Complex 1 Activity Measured by Spectrophotometry Is Reduced across All Brain Regions in Ageing and More Specifically in Neurodegeneration.

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Pollard, Amelia Kate; Craig, Emma Louise; Chakrabarti, Lisa

2016-01-01

Mitochondrial function, in particular complex 1 of the electron transport chain (ETC), has been shown to decrease during normal ageing and in neurodegenerative disease. However, there is some debate concerning which area of the brain has the greatest complex 1 activity. It is important to identify the pattern of activity in order to be able to gauge the effect of age or disease related changes. We determined complex 1 activity spectrophotometrically in the cortex, brainstem and cerebellum of middle aged mice (70-71 weeks), a cerebellar ataxic neurodegeneration model (pcd5J) and young wild type controls. We share our updated protocol on the measurements of complex1 activity and find that mitochondrial fractions isolated from frozen tissues can be measured for robust activity. We show that complex 1 activity is clearly highest in the cortex when compared with brainstem and cerebellum (p<0.003). Cerebellum and brainstem mitochondria exhibit similar levels of complex 1 activity in wild type brains. In the aged brain we see similar levels of complex 1 activity in all three-brain regions. The specific activity of complex 1 measured in the aged cortex is significantly decreased when compared with controls (p<0.0001). Both the cerebellum and brainstem mitochondria also show significantly reduced activity with ageing (p<0.05). The mouse model of ataxia predictably has a lower complex 1 activity in the cerebellum, and although reductions are measured in the cortex and brain stem, the remaining activity is higher than in the aged brains. We present clear evidence that complex 1 activity decreases across the brain with age and much more specifically in the cerebellum of the pcd5j mouse. Mitochondrial impairment can be a region specific phenomenon in disease, but in ageing appears to affect the entire brain, abolishing the pattern of higher activity in cortical regions.

Evolution of brain-computer interfaces: going beyond classic motor physiology

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Leuthardt, Eric C.; Schalk, Gerwin; Roland, Jarod; Rouse, Adam; Moran, Daniel W.

2010-01-01

The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future. PMID:19569892

Effects of Cell Phone Radiofrequency Signal Exposure on Brain Glucose Metabolism

Science.gov (United States)

Volkow, Nora D.; Tomasi, Dardo; Wang, Gene-Jack; Vaska, Paul; Fowler, Joanna S.; Telang, Frank; Alexoff, Dave; Logan, Jean; Wong, Christopher

2011-01-01

Context The dramatic increase in use of cellular telephones has generated concern about possible negative effects of radiofrequency signals delivered to the brain. However, whether acute cell phone exposure affects the human brain is unclear. Objective To evaluate if acute cell phone exposure affects brain glucose metabolism, a marker of brain activity. Design, Setting, and Participants Randomized crossover study conducted between January 1 and December 31, 2009, at a single US laboratory among 47 healthy participants recruited from the community. Cell phones were placed on the left and right ears and positron emission tomography with (18F)fluorodeoxyglucose injection was used to measure brain glucose metabolism twice, once with the right cell phone activated (sound muted) for 50 minutes (“on” condition) and once with both cell phones deactivated (“off” condition). Statistical parametric mapping was used to compare metabolism between on and off conditions using paired t tests, and Pearson linear correlations were used to verify the association of metabolism and estimated amplitude of radiofrequency-modulated electromagnetic waves emitted by the cell phone. Clusters with at least 1000 voxels (volume >8 cm3) and P < .05 (corrected for multiple comparisons) were considered significant. Main Outcome Measure Brain glucose metabolism computed as absolute metabolism (µmol/100 g per minute) and as normalized metabolism (region/whole brain). Results Whole-brain metabolism did not differ between on and off conditions. In contrast, metabolism in the region closest to the antenna (orbitofrontal cortex and temporal pole) was significantly higher for on than off conditions (35.7 vs 33.3 µmol/100 g per minute; mean difference, 2.4 [95% confidence interval, 0.67–4.2]; P = .004). The increases were significantly correlated with the estimated electromagnetic field amplitudes both for absolute metabolism (R = 0.95, P < .001) and normalized metabolism (R = 0.89; P < .001

Effects of Cell Phone Radiofrequency Signal Exposure on Brain Glucos Metabolism

International Nuclear Information System (INIS)

Volkow, N.D.; Tomasi, D.; Wang, G.-J.; Vaska, P.; Fowler, J.S.; Telang, F.; Alexoff, D.; Logan, J.; Wong, C.

2011-01-01

The dramatic increase in use of cellular telephones has generated concern about possible negative effects of radiofrequency signals delivered to the brain. However, whether acute cell phone exposure affects the human brain is unclear. To evaluate if acute cell phone exposure affects brain glucose metabolism, a marker of brain activity. Randomized crossover study conducted between January 1 and December 31, 2009, at a single US laboratory among 47 healthy participants recruited from the community. Cell phones were placed on the left and right ears and positron emission tomography with ( 18 F)fluorodeoxyglucose injection was used to measure brain glucose metabolism twice, once with the right cell phone activated (sound muted) for 50 minutes ('on' condition) and once with both cell phones deactivated ('off' condition). Statistical parametric mapping was used to compare metabolism between on and off conditions using paired t tests, and Pearson linear correlations were used to verify the association of metabolism and estimated amplitude of radiofrequency-modulated electromagnetic waves emitted by the cell phone. Clusters with at least 1000 voxels (volume >8 cm 3 ) and P < .05 (corrected for multiple comparisons) were considered significant. Brain glucose metabolism computed as absolute metabolism ((micro)mol/100 g per minute) and as normalized metabolism (region/whole brain). Whole-brain metabolism did not differ between on and off conditions. In contrast, metabolism in the region closest to the antenna (orbitofrontal cortex and temporal pole) was significantly higher for on than off conditions (35.7 vs 33.3 (micro)mol/100 g per minute; mean difference, 2.4 (95% confidence interval, 0.67-4.2); P = .004). The increases were significantly correlated with the estimated electromagnetic field amplitudes both for absolute metabolism (R = 0.95, P < .001) and normalized metabolism (R = 0.89; P < .001). In healthy participants and compared with no exposure, 50-minute cell phone

ß-Adrenergic Receptor Signaling and Modulation of Long-Term Potentiation in the Mammalian Hippocampus

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O'Dell, Thomas J.; Connor, Steven A.; Guglietta, Ryan; Nguyen, Peter V.

2015-01-01

Encoding new information in the brain requires changes in synaptic strength. Neuromodulatory transmitters can facilitate synaptic plasticity by modifying the actions and expression of specific signaling cascades, transmitter receptors and their associated signaling complexes, genes, and effector proteins. One critical neuromodulator in the…

Preparation of new technetium-99m NNS/X complexes and selection for brain imaging agent

Institute of Scientific and Technical Information of China (English)

HE; Qiange; CHEN; Xiangji; MIAO; Yubin; LIU; Boli

2004-01-01

Based on excellent experiment results of 99mTcO-MPBDA-Cl, two new ligands MPTDA and MPDAA are synthesized. Then series of 99mTcO3+ complexes are prepared through adding different halide anions, followed by tests of physical chemistry qualities and biodistribution experiments. And results of these experiments show that complexes formed with MPTDA and MPDAA have better lipophilicity than those formed with MPBDA, still maintain the good brain retention ability of this type of compounds, but radioactivity uptake in blood is higher than that of 99mTcO-MPBDA and ratios of brain/blood are reduced. Obvious affections are fetched out on brain uptake and retention if fluoride, bromide or iodide anions are added. Results of experiments can be explained in reason with theoretic computation. It is confirmed that 99mTcO-MPBDA-Cl has potential to develop a new type of brain imaging agent considering integrated factors such as brain uptake, retention and toxicity.

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

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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.

Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.

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Sabherwal, Pooja; Singh, Latika; Agrawal, Monika

2018-03-30

In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.

Assembly of Oligomeric Death Domain Complexes during Toll Receptor Signaling*

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Moncrieffe, Martin C.; Grossmann, J. Günter; Gay, Nicholas J.

2008-01-01

The Drosophila Toll receptor is activated by the endogenous protein ligand Spätzle in response to microbial stimuli in immunity and spatial cues during embryonic development. Downstream signaling is mediated by the adaptor proteins Tube, the kinase Pelle, and the Drosophila homologue of myeloid differentiation primary response protein (dMyD88). Here we have characterized heterodimeric (dMyD88-Tube) and heterotrimeric (dMyD88-Tube-Pelle) death domain complexes. We show that both the heterodimeric and heterotrimeric complexes form kidney-shaped structures and that Tube is bivalent and has separate high affinity binding sites for dMyD88 and Pelle. Additionally we found no interaction between the isolated death domains of Pelle and dMyD88. These results indicate that the mode of assembly of the heterotrimeric dMyD88-Tube-Pelle complex downstream of the activated Toll receptor is unique. The measured dissociation constants for the interaction between the death domains of dMyD88 and Tube and of Pelle and a preformed dMyD88-Tube complex are used to propose a model of the early postreceptor events in Drosophila Toll receptor signaling. PMID:18829464

Assembly of oligomeric death domain complexes during Toll receptor signaling.

Science.gov (United States)

Moncrieffe, Martin C; Grossmann, J Günter; Gay, Nicholas J

2008-11-28

The Drosophila Toll receptor is activated by the endogenous protein ligand Spätzle in response to microbial stimuli in immunity and spatial cues during embryonic development. Downstream signaling is mediated by the adaptor proteins Tube, the kinase Pelle, and the Drosophila homologue of myeloid differentiation primary response protein (dMyD88). Here we have characterized heterodimeric (dMyD88-Tube) and heterotrimeric (dMyD88-Tube-Pelle) death domain complexes. We show that both the heterodimeric and heterotrimeric complexes form kidney-shaped structures and that Tube is bivalent and has separate high affinity binding sites for dMyD88 and Pelle. Additionally we found no interaction between the isolated death domains of Pelle and dMyD88. These results indicate that the mode of assembly of the heterotrimeric dMyD88-Tube-Pelle complex downstream of the activated Toll receptor is unique. The measured dissociation constants for the interaction between the death domains of dMyD88 and Tube and of Pelle and a preformed dMyD88-Tube complex are used to propose a model of the early postreceptor events in Drosophila Toll receptor signaling.

Complexity in neuronal noise depends on network interconnectivity.

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Serletis, Demitre; Zalay, Osbert C; Valiante, Taufik A; Bardakjian, Berj L; Carlen, Peter L

2011-06-01

"Noise," or noise-like activity (NLA), defines background electrical membrane potential fluctuations at the cellular level of the nervous system, comprising an important aspect of brain dynamics. Using whole-cell voltage recordings from fast-spiking stratum oriens interneurons and stratum pyramidale neurons located in the CA3 region of the intact mouse hippocampus, we applied complexity measures from dynamical systems theory (i.e., 1/f(γ) noise and correlation dimension) and found evidence for complexity in neuronal NLA, ranging from high- to low-complexity dynamics. Importantly, these high- and low-complexity signal features were largely dependent on gap junction and chemical synaptic transmission. Progressive neuronal isolation from the surrounding local network via gap junction blockade (abolishing gap junction-dependent spikelets) and then chemical synaptic blockade (abolishing excitatory and inhibitory post-synaptic potentials), or the reverse order of these treatments, resulted in emergence of high-complexity NLA dynamics. Restoring local network interconnectivity via blockade washout resulted in resolution to low-complexity behavior. These results suggest that the observed increase in background NLA complexity is the result of reduced network interconnectivity, thereby highlighting the potential importance of the NLA signal to the study of network state transitions arising in normal and abnormal brain dynamics (such as in epilepsy, for example).

Unraveling the Complexities of Androgen Receptor Signaling in Prostate Cancer Cells

OpenAIRE

Heemers, Hannelore V.; Tindall, Donald J.

2009-01-01

Androgen signaling is critical for proliferation of prostate cancer cells but cannot be fully inhibited by current androgen deprivation therapies. A study by Xu et al. in this issue of Cancer Cell provides insights into the complexities of androgen signaling in prostate cancer and suggests avenues to target a subset of androgen-sensitive genes.

Mechanisms and significance of brain glucose signaling in energy balance, glucose homeostasis, and food-induced reward.

Science.gov (United States)

Devarakonda, Kavya; Mobbs, Charles V

2016-12-15

The concept that hypothalamic glucose signaling plays an important role in regulating energy balance, e.g., as instantiated in the so-called "glucostat" hypothesis, is one of the oldest in the field of metabolism. However the mechanisms by which neurons in the hypothalamus sense glucose, and the function of glucose signaling in the brain, has been difficult to establish. Nevertheless recent studies probing mechanisms of glucose signaling have also strongly supported a role for glucose signaling in regulating energy balance, glucose homeostasis, and food-induced reward. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Insights into Brain Glycogen Metabolism: THE STRUCTURE OF HUMAN BRAIN GLYCOGEN PHOSPHORYLASE.

Science.gov (United States)

Mathieu, Cécile; Li de la Sierra-Gallay, Ines; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-08-26

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

A method for detecting nonlinear determinism in normal and epileptic brain EEG signals.

Science.gov (United States)

Meghdadi, Amir H; Fazel-Rezai, Reza; Aghakhani, Yahya

2007-01-01

A robust method of detecting determinism for short time series is proposed and applied to both healthy and epileptic EEG signals. The method provides a robust measure of determinism through characterizing the trajectories of the signal components which are obtained through singular value decomposition. Robustness of the method is shown by calculating proposed index of determinism at different levels of white and colored noise added to a simulated chaotic signal. The method is shown to be able to detect determinism at considerably high levels of additive noise. The method is then applied to both intracranial and scalp EEG recordings collected in different data sets for healthy and epileptic brain signals. The results show that for all of the studied EEG data sets there is enough evidence of determinism. The determinism is more significant for intracranial EEG recordings particularly during seizure activity.

Distinguishing low frequency oscillations within the 1/f spectral behaviour of electromagnetic brain signals

Directory of Open Access Journals (Sweden)

Sonuga-Barke Edmund JS

2007-12-01

Full Text Available Abstract Background It has been acknowledged that the frequency spectrum of measured electromagnetic (EM brain signals shows a decrease in power with increasing frequency. This spectral behaviour may lead to difficulty in distinguishing event-related peaks from ongoing brain activity in the electro- and magnetoencephalographic (EEG and MEG signal spectra. This can become an issue especially in the analysis of low frequency oscillations (LFOs – below 0.5 Hz – which are currently being observed in signal recordings linked with specific pathologies such as epileptic seizures or attention deficit hyperactivity disorder (ADHD, in sleep studies, etc. Methods In this work we propose a simple method that can be used to compensate for this 1/f trend hence achieving spectral normalisation. This method involves filtering the raw measured EM signal through a differentiator prior to further data analysis. Results Applying the proposed method to various exemplary datasets including very low frequency EEG recordings, epileptic seizure recordings, MEG data and Evoked Response data showed that this compensating procedure provides a flat spectral base onto which event related peaks can be clearly observed. Conclusion Findings suggest that the proposed filter is a useful tool for the analysis of physiological data especially in revealing very low frequency peaks which may otherwise be obscured by the 1/f spectral activity inherent in EEG/MEG recordings.

Region-specific expression of mitochondrial complex I genes during murine brain development.

Directory of Open Access Journals (Sweden)

Stefanie Wirtz

Full Text Available Mutations in the nuclear encoded subunits of mitochondrial complex I (NADH:ubiquinone oxidoreductase may cause circumscribed cerebral lesions ranging from degeneration of the striatal and brainstem gray matter (Leigh syndrome to leukodystrophy. We hypothesized that such pattern of regional pathology might be due to local differences in the dependence on complex I function. Using in situ hybridization we investigated the relative expression of 33 nuclear encoded complex I subunits in different brain regions of the mouse at E11.5, E17.5, P1, P11, P28 and adult (12 weeks. With respect to timing and relative intensity of complex I gene expression we found a highly variant pattern in different regions during development. High average expression levels were detected in periods of intense neurogenesis. In cerebellar Purkinje and in hippocampal CA1/CA3 pyramidal neurons we found a second even higher peak during the period of synaptogenesis and maturation. The extraordinary dependence of these structures on complex I gene expression during synaptogenesis is in accord with our recent findings that gamma oscillations--known to be associated with higher cognitive functions of the mammalian brain--strongly depend on the complex I activity. However, with the exception of the mesencephalon, we detected only average complex I expression levels in the striatum and basal ganglia, which does not explain the exquisite vulnerability of these structures in mitochondrial disorders.

Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

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Lorenza A D'Alessandro

2015-04-01

Full Text Available Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF stimulated phosphoinositide-3-kinase (PI3K and mitogen activated protein kinase (MAPK signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

Maturation of the auditory t-complex brain response across adolescence.

Science.gov (United States)

Mahajan, Yatin; McArthur, Genevieve

2013-02-01

Adolescence is a time of great change in the brain in terms of structure and function. It is possible to track the development of neural function across adolescence using auditory event-related potentials (ERPs). This study tested if the brain's functional processing of sound changed across adolescence. We measured passive auditory t-complex peaks to pure tones and consonant-vowel (CV) syllables in 90 children and adolescents aged 10-18 years, as well as 10 adults. Across adolescence, Na amplitude increased to tones and speech at the right, but not left, temporal site. Ta amplitude decreased at the right temporal site for tones, and at both sites for speech. The Tb remained constant at both sites. The Na and Ta appeared to mature later in the right than left hemisphere. The t-complex peaks Na and Tb exhibited left lateralization and Ta showed right lateralization. Thus, the functional processing of sound continued to develop across adolescence and into adulthood. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Tryptophan as an evolutionarily conserved signal to brain serotonin : Molecular evidence and psychiatric implications

NARCIS (Netherlands)

Russo, Sascha; Kema, Ido P.; Bosker, Fokko; Haavik, Jan; Korf, Jakob

2009-01-01

The role of serotonin (5-HT) in psychopathology has been investigated for decades. Among others, symptoms of depression, panic, aggression and suicidality have been associated with serotonergic dysfunction. Here we summarize the evidence that low brain 5-HT signals a metabolic imbalance that is

Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

Science.gov (United States)

Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

2011-08-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. Copyright © 2011 Elsevier Inc. All rights reserved.

EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

OpenAIRE

Blum, Sarah; Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G.

2017-01-01

Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI) on the sma...

Application of complex discrete wavelet transform in classification of Doppler signals using complex-valued artificial neural network.

Science.gov (United States)

Ceylan, Murat; Ceylan, Rahime; Ozbay, Yüksel; Kara, Sadik

2008-09-01

In biomedical signal classification, due to the huge amount of data, to compress the biomedical waveform data is vital. This paper presents two different structures formed using feature extraction algorithms to decrease size of feature set in training and test data. The proposed structures, named as wavelet transform-complex-valued artificial neural network (WT-CVANN) and complex wavelet transform-complex-valued artificial neural network (CWT-CVANN), use real and complex discrete wavelet transform for feature extraction. The aim of using wavelet transform is to compress data and to reduce training time of network without decreasing accuracy rate. In this study, the presented structures were applied to the problem of classification in carotid arterial Doppler ultrasound signals. Carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group included 22 males and 16 females with an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal (lower extremity) angiographies (mean age, 59 years; range, 48-72 years). Healthy volunteers were young non-smokers who seem to not bear any risk of atherosclerosis, including 28 males and 12 females (mean age, 23 years; range, 19-27 years). Sensitivity, specificity and average detection rate were calculated for comparison, after training and test phases of all structures finished. These parameters have demonstrated that training times of CVANN and real-valued artificial neural network (RVANN) were reduced using feature extraction algorithms without decreasing accuracy rate in accordance to our aim.

Notch Signaling and Brain Tumors

DEFF Research Database (Denmark)

Stockhausen, Marie; Kristoffersen, Karina; Poulsen, Hans Skovgaard

2011-01-01

Human brain tumors are a heterogenous group of neoplasms occurring inside the cranium and the central spinal cord. In adults and children, astrocytic glioma and medulloblastoma are the most common subtypes of primary brain tumors. These tumor types are thought to arise from cells in which Notch...

Effects of ionizing radiation on purinergic signaling modulation in rat brain nerve cells

International Nuclear Information System (INIS)

Stanojevic, I.; Milosevic, M.; Drakulic, D.; Horvat, A.; Stanojevic, I.)

2007-01-01

Purinergic signaling is composed of three modulatory components: a) source of extracellular nucleotides, b) specific receptor expression for these transmitter molecules and c) ectonucleotidase selection that dictate cell response gradually degradation extracellular nucleotides to nucleosides. ATP acts as a fast excitatory transmitter in the CNS. Postsynaptic actions of ATP are mediated by an extended family of purinergic, P2X receptors, widely expressed throughout the CNS. NTPDases hydrolyse extracellular ATP and ADP to AMP and are responsive for purinergfic termination. To investigate if ionizing irradiation could modulate CNS purinergic signalization we monitored activity of NTPDases and abundance of P2X7 receptor in synaptic plasma membranes after whole-body acute irradiation using low (0,5Gy) or therapeutic (2Gy) doses, 1h i 72h after irradiating juvenile (15-day old) and adult (90-day old) rats. Acute irradiation modulate purinergic system components investigated at the different ways in the rat development brain SPM and in the adult brain dependent of dose and time after irradiation [sr

Brain MRI signal abnormalities and right-to-left shunting in asymptomatic military divers.

Science.gov (United States)

Gempp, Emmanuel; Sbardella, Fabrice; Stephant, Eric; Constantin, Pascal; De Maistre, Sebastien; Louge, Pierre; Blatteau, Jean-Eric

2010-11-01

We conducted a controlled study to assess the prevalence of brain MRI hyperintense signals and their correlation with right-to-left shunting (RLS) in military divers. We prospectively enrolled 32 asymptomatic military divers under 41 yr of age and 32 non-diving healthy subjects matched with respect to age and vascular disease risk factors. We examined both groups with a 3-Tesla brain MRI; RLS was detected using transcranial pulsed Doppler in divers only. Hyperintense spots were observed in 43.7% of the divers and 21.8% of the control subjects. In particular, divers with significant shunting exhibited a higher prevalence of hyperintensities compared to those with slight or no RLS (75% vs. 25%, respectively). Linear trend analysis also revealed a positive correlation between focal white matter changes, determined using a validated visual rating scale and the RLS grade. Healthy military divers with a hemodynamically relevant RLS have an increased likelihood of cerebral hyperintense spots compared to age-matched normal subjects. The clinical relevance of these MRI signal abnormalities and their causal relationship with diving remain unclear.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

International Nuclear Information System (INIS)

Gutierrez, David

2008-01-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEG data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation

Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

Science.gov (United States)

Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

2016-01-01

Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Insights into Brain Glycogen Metabolism

Science.gov (United States)

Mathieu, Cécile; de la Sierra-Gallay, Ines Li; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-01-01

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. PMID:27402852

Generation of Long-time Complex Signals for Testing the Instruments for Detection of Voltage Quality Disturbances

Science.gov (United States)

Živanović, Dragan; Simić, Milan; Kokolanski, Zivko; Denić, Dragan; Dimcev, Vladimir

2018-04-01

Software supported procedure for generation of long-time complex test sentences, suitable for testing the instruments for detection of standard voltage quality (VQ) disturbances is presented in this paper. This solution for test signal generation includes significant improvements of computer-based signal generator presented and described in the previously published paper [1]. The generator is based on virtual instrumentation software for defining the basic signal parameters, data acquisition card NI 6343, and power amplifier for amplification of output voltage level to the nominal RMS voltage value of 230 V. Definition of basic signal parameters in LabVIEW application software is supported using Script files, which allows simple repetition of specific test signals and combination of more different test sequences in the complex composite test waveform. The basic advantage of this generator compared to the similar solutions for signal generation is the possibility for long-time test sequence generation according to predefined complex test scenarios, including various combinations of VQ disturbances defined in accordance with the European standard EN50160. Experimental verification of the presented signal generator capability is performed by testing the commercial power quality analyzer Fluke 435 Series II. In this paper are shown some characteristic complex test signals with various disturbances and logged data obtained from the tested power quality analyzer.

Fixed-Point Algorithms for the Blind Separation of Arbitrary Complex-Valued Non-Gaussian Signal Mixtures

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Douglas Scott C

2007-01-01

Full Text Available We derive new fixed-point algorithms for the blind separation of complex-valued mixtures of independent, noncircularly symmetric, and non-Gaussian source signals. Leveraging recently developed results on the separability of complex-valued signal mixtures, we systematically construct iterative procedures on a kurtosis-based contrast whose evolutionary characteristics are identical to those of the FastICA algorithm of Hyvarinen and Oja in the real-valued mixture case. Thus, our methods inherit the fast convergence properties, computational simplicity, and ease of use of the FastICA algorithm while at the same time extending this class of techniques to complex signal mixtures. For extracting multiple sources, symmetric and asymmetric signal deflation procedures can be employed. Simulations for both noiseless and noisy mixtures indicate that the proposed algorithms have superior finite-sample performance in data-starved scenarios as compared to existing complex ICA methods while performing about as well as the best of these techniques for larger data-record lengths.

Regulation of neurite morphogenesis by interaction between R7 regulator of G protein signaling complexes and G protein subunit Gα13.

Science.gov (United States)

Scherer, Stephanie L; Cain, Matthew D; Kanai, Stanley M; Kaltenbronn, Kevin M; Blumer, Kendall J

2017-06-16

The R7 regulator of G protein signaling family (R7-RGS) critically regulates nervous system development and function. Mice lacking all R7-RGS subtypes exhibit diverse neurological phenotypes, and humans bearing mutations in the retinal R7-RGS isoform RGS9-1 have vision deficits. Although each R7-RGS subtype forms heterotrimeric complexes with Gβ 5 and R7-RGS-binding protein (R7BP) that regulate G protein-coupled receptor signaling by accelerating deactivation of G i/o α-subunits, several neurological phenotypes of R7-RGS knock-out mice are not readily explained by dysregulated G i/o signaling. Accordingly, we used tandem affinity purification and LC-MS/MS to search for novel proteins that interact with R7-RGS heterotrimers in the mouse brain. Among several proteins detected, we focused on Gα 13 because it had not been linked to R7-RGS complexes before. Split-luciferase complementation assays indicated that Gα 13 in its active or inactive state interacts with R7-RGS heterotrimers containing any R7-RGS isoform. LARG (leukemia-associated Rho guanine nucleotide exchange factor (GEF)), PDZ-RhoGEF, and p115RhoGEF augmented interaction between activated Gα 13 and R7-RGS heterotrimers, indicating that these effector RhoGEFs can engage Gα 13 ·R7-RGS complexes. Because Gα 13 /R7-RGS interaction required R7BP, we analyzed phenotypes of neuronal cell lines expressing RGS7 and Gβ 5 with or without R7BP. We found that neurite retraction evoked by Gα 12/13 -dependent lysophosphatidic acid receptors was augmented in R7BP-expressing cells. R7BP expression blunted neurite formation evoked by serum starvation by signaling mechanisms involving Gα 12/13 but not Gα i/o These findings provide the first evidence that R7-RGS heterotrimers interact with Gα 13 to augment signaling pathways that regulate neurite morphogenesis. This mechanism expands the diversity of functions whereby R7-RGS complexes regulate critical aspects of nervous system development and function. © 2017 by

Isolation and structure–function characterization of a signaling-active rhodopsin–G protein complex

Science.gov (United States)

Gao, Yang; Westfield, Gerwin; Erickson, Jon W.; Cerione, Richard A.; Skiniotis, Georgios; Ramachandran, Sekar

2017-01-01

The visual photo-transduction cascade is a prototypical G protein–coupled receptor (GPCR) signaling system, in which light-activated rhodopsin (Rho*) is the GPCR catalyzing the exchange of GDP for GTP on the heterotrimeric G protein transducin (GT). This results in the dissociation of GT into its component αT–GTP and β1γ1 subunit complex. Structural information for the Rho*–GT complex will be essential for understanding the molecular mechanism of visual photo-transduction. Moreover, it will shed light on how GPCRs selectively couple to and activate their G protein signaling partners. Here, we report on the preparation of a stable detergent-solubilized complex between Rho* and a heterotrimer (GT*) comprising a GαT/Gαi1 chimera (αT*) and β1γ1. The complex was formed on native rod outer segment membranes upon light activation, solubilized in lauryl maltose neopentyl glycol, and purified with a combination of affinity and size-exclusion chromatography. We found that the complex is fully functional and that the stoichiometry of Rho* to GαT* is 1:1. The molecular weight of the complex was calculated from small-angle X-ray scattering data and was in good agreement with a model consisting of one Rho* and one GT*. The complex was visualized by negative-stain electron microscopy, which revealed an architecture similar to that of the β2-adrenergic receptor–GS complex, including a flexible αT* helical domain. The stability and high yield of the purified complex should allow for further efforts toward obtaining a high-resolution structure of this important signaling complex. PMID:28655769

Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

Science.gov (United States)

Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

2016-05-01

Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

Signals, processes, and systems an interactive multimedia introduction to signal processing

CERN Document Server

Karrenberg, Ulrich

2013-01-01

This is a very new concept for learning Signal Processing, not only from the physically-based scientific fundamentals, but also from the didactic perspective, based on modern results of brain research. The textbook together with the DVD form a learning system that provides investigative studies and enables the reader to interactively visualize even complex processes. The unique didactic concept is built on visualizing signals and processes on the one hand, and on graphical programming of signal processing systems on the other. The concept has been designed especially for microelectronics, computer technology and communication. The book allows to develop, modify, and optimize useful applications using DasyLab - a professional and globally supported software for metrology and control engineering. With the 3rd edition, the software is also suitable for 64 bit systems running on Windows 7. Real signals can be acquired, processed and played on the sound card of your computer. The book provides more than 200 pre-pr...

Astrocytic Insulin Signaling Couples Brain Glucose Uptake with Nutrient Availability.

Science.gov (United States)

García-Cáceres, Cristina; Quarta, Carmelo; Varela, Luis; Gao, Yuanqing; Gruber, Tim; Legutko, Beata; Jastroch, Martin; Johansson, Pia; Ninkovic, Jovica; Yi, Chun-Xia; Le Thuc, Ophelia; Szigeti-Buck, Klara; Cai, Weikang; Meyer, Carola W; Pfluger, Paul T; Fernandez, Ana M; Luquet, Serge; Woods, Stephen C; Torres-Alemán, Ignacio; Kahn, C Ronald; Götz, Magdalena; Horvath, Tamas L; Tschöp, Matthias H

2016-08-11

We report that astrocytic insulin signaling co-regulates hypothalamic glucose sensing and systemic glucose metabolism. Postnatal ablation of insulin receptors (IRs) in glial fibrillary acidic protein (GFAP)-expressing cells affects hypothalamic astrocyte morphology, mitochondrial function, and circuit connectivity. Accordingly, astrocytic IR ablation reduces glucose-induced activation of hypothalamic pro-opio-melanocortin (POMC) neurons and impairs physiological responses to changes in glucose availability. Hypothalamus-specific knockout of astrocytic IRs, as well as postnatal ablation by targeting glutamate aspartate transporter (GLAST)-expressing cells, replicates such alterations. A normal response to altering directly CNS glucose levels in mice lacking astrocytic IRs indicates a role in glucose transport across the blood-brain barrier (BBB). This was confirmed in vivo in GFAP-IR KO mice by using positron emission tomography and glucose monitoring in cerebral spinal fluid. We conclude that insulin signaling in hypothalamic astrocytes co-controls CNS glucose sensing and systemic glucose metabolism via regulation of glucose uptake across the BBB. Copyright © 2016 Elsevier Inc. All rights reserved.

Histone deacetylases control neurogenesis in embryonic brain by inhibition of BMP2/4 signaling.

Directory of Open Access Journals (Sweden)

Maya Shakèd

Full Text Available BACKGROUND: Histone-modifying enzymes are essential for a wide variety of cellular processes dependent upon changes in gene expression. Histone deacetylases (HDACs lead to the compaction of chromatin and subsequent silencing of gene transcription, and they have recently been implicated in a diversity of functions and dysfunctions in the postnatal and adult brain including ocular dominance plasticity, memory consolidation, drug addiction, and depression. Here we investigate the role of HDACs in the generation of neurons and astrocytes in the embryonic brain. PRINCIPAL FINDINGS: As a variety of HDACs are expressed in differentiating neural progenitor cells, we have taken a pharmacological approach to inhibit multiple family members. Inhibition of class I and II HDACs in developing mouse embryos with trichostatin A resulted in a dramatic reduction in neurogenesis in the ganglionic eminences and a modest increase in neurogenesis in the cortex. An identical effect was observed upon pharmacological inhibition of HDACs in in vitro-differentiating neural precursors derived from the same brain regions. A reduction in neurogenesis in ganglionic eminence-derived neural precursors was accompanied by an increase in the production of immature astrocytes. We show that HDACs control neurogenesis by inhibition of the bone morphogenetic protein BMP2/4 signaling pathway in radial glial cells. HDACs function at the transcriptional level by inhibiting and promoting, respectively, the expression of Bmp2 and Smad7, an intracellular inhibitor of BMP signaling. Inhibition of the BMP2/4 signaling pathway restored normal levels of neurogenesis and astrogliogenesis to both ganglionic eminence- and cortex-derived cultures in which HDACs were inhibited. CONCLUSIONS: Our results demonstrate a transcriptionally-based regulation of BMP2/4 signaling by HDACs both in vivo and in vitro that is critical for neurogenesis in the ganglionic eminences and that modulates cortical

Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes.

Science.gov (United States)

Daskalakis, Nikolaos P; Cohen, Hagit; Cai, Guiqing; Buxbaum, Joseph D; Yehuda, Rachel

2014-09-16

Delineating the molecular basis of individual differences in the stress response is critical to understanding the pathophysiology and treatment of posttraumatic stress disorder (PTSD). In this study, 7 d after predator-scent-stress (PSS) exposure, male and female rats were classified into vulnerable (i.e., "PTSD-like") and resilient (i.e., minimally affected) phenotypes on the basis of their performance on a variety of behavioral measures. Genome-wide expression profiling in blood and two limbic brain regions (amygdala and hippocampus), followed by quantitative PCR validation, was performed in these two groups of animals, as well as in an unexposed control group. Differentially expressed genes were identified in blood and brain associated with PSS-exposure and with distinct behavioral profiles postexposure. There was a small but significant between-tissue overlap (4-21%) for the genes associated with exposure-related individual differences, indicating convergent gene expression in both sexes. To uncover convergent signaling pathways across tissue and sex, upstream activated/deactivated transcription factors were first predicted for each tissue and then the respective pathways were identified. Glucocorticoid receptor (GR) signaling was the only convergent pathway associated with individual differences when using the most stringent statistical threshold. Corticosterone treatment 1 h after PSS-exposure prevented anxiety and hyperarousal 7 d later in both sexes, confirming the GR involvement in the PSS behavioral response. In conclusion, genes and pathways associated with extreme differences in the traumatic stress behavioral response can be distinguished from those associated with trauma exposure. Blood-based biomarkers can predict aspects of brain signaling. GR signaling is a convergent signaling pathway, associated with trauma-related individual differences in both sexes.

Cannabinoid-Induced Changes in the Activity of Electron Transport Chain Complexes of Brain Mitochondria.

Science.gov (United States)

Singh, Namrata; Hroudová, Jana; Fišar, Zdeněk

2015-08-01

The aim of this study was to investigate changes in the activity of individual mitochondrial respiratory chain complexes (I, II/III, IV) and citrate synthase induced by pharmacologically different cannabinoids. In vitro effects of selected cannabinoids on mitochondrial enzymes were measured in crude mitochondrial fraction isolated from pig brain. Both cannabinoid receptor agonists, Δ(9)-tetrahydrocannabinol, anandamide, and R-(+)-WIN55,212-2, and antagonist/inverse agonists of cannabinoid receptors, AM251, and cannabidiol were examined in pig brain mitochondria. Different effects of these cannabinoids on mitochondrial respiratory chain complexes and citrate synthase were found. Citrate synthase activity was decreased only by Δ(9)-tetrahydrocannabinol and AM251. Significant increase in the complex I activity was induced by anandamide. At micromolar concentration, all the tested cannabinoids inhibited the activity of electron transport chain complexes II/III and IV. Stimulatory effect of anandamide on activity of complex I may participate on distinct physiological effects of endocannabinoids compared to phytocannabinoids or synthetic cannabinoids. Common inhibitory effect of cannabinoids on activity of complex II/III and IV confirmed a non-receptor-mediated mechanism of cannabinoid action on individual components of system of oxidative phosphorylation.

Investigation of mental fatigue through EEG signal processing based on nonlinear analysis: Symbolic dynamics

International Nuclear Information System (INIS)

Azarnoosh, Mahdi; Motie Nasrabadi, Ali; Mohammadi, Mohammad Reza; Firoozabadi, Mohammad

2011-01-01

Highlights: Mental fatigue indices’ variation discussed during simple long-term attentive task. Symbolic dynamics of reaction time and EEG signal determine mental state variation. Nonlinear quantifiers such as entropy can display chaotic behaviors of the brain. Frontal and central lobes of the brain are effective in attention investigations. Mental fatigue causes a reduction in the complexity of the brain’s activity. Abstract: To investigate nonlinear analysis of attention physiological indices this study used a simple repetitive attentive task in four consecutive trials that resulted in mental fatigue. Traditional performance indices, such as reaction time, error responses, and EEG signals, were simultaneously recorded to evaluate differences between the trials. Performance indices analysis demonstrated that a selected task leads to mental fatigue. In addition, the study aimed to find a method to determine mental fatigue based on nonlinear analysis of EEG signals. Symbolic dynamics was selected as a qualitative method used to extract some quantitative qualifiers such as entropy. This method was executed on the reaction time of responses, and EEG signals to distinguish mental states. The results revealed that nonlinear analysis of reaction time, and EEG signals of the frontal and central lobes of the brain could differentiate between attention, and occurrence of mental fatigue in trials. In addition, the trend of entropy variation displayed a reduction in the complexity of mental activity as fatigue occurred.

Reelin signaling in the migration of ventral brain stem and spinal cord neurons

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Sandra eBlaess

2016-03-01

Full Text Available The extracellular matrix protein Reelin is an important orchestrator of neuronal migration during the development of the central nervous system. While its role and mechanism of action have been extensively studied and reviewed in the formation of dorsal laminar brain structures like the cerebral cortex, hippocampus, and cerebellum, its functions during the neuronal migration events that result in the nuclear organization of the ventral central nervous system are less well understood. In an attempt to delineate an underlying pattern of Reelin action in the formation of neuronal cell clusters, this review highlights the role of Reelin signaling in the migration of neuronal populations that originate in the ventral brain stem and the spinal cord.

Isolation and structure-function characterization of a signaling-active rhodopsin-G protein complex.

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Gao, Yang; Westfield, Gerwin; Erickson, Jon W; Cerione, Richard A; Skiniotis, Georgios; Ramachandran, Sekar

2017-08-25

The visual photo-transduction cascade is a prototypical G protein-coupled receptor (GPCR) signaling system, in which light-activated rhodopsin (Rho*) is the GPCR catalyzing the exchange of GDP for GTP on the heterotrimeric G protein transducin (G T ). This results in the dissociation of G T into its component α T -GTP and β 1 γ 1 subunit complex. Structural information for the Rho*-G T complex will be essential for understanding the molecular mechanism of visual photo-transduction. Moreover, it will shed light on how GPCRs selectively couple to and activate their G protein signaling partners. Here, we report on the preparation of a stable detergent-solubilized complex between Rho* and a heterotrimer (G T *) comprising a Gα T /Gα i1 chimera (α T *) and β 1 γ 1 The complex was formed on native rod outer segment membranes upon light activation, solubilized in lauryl maltose neopentyl glycol, and purified with a combination of affinity and size-exclusion chromatography. We found that the complex is fully functional and that the stoichiometry of Rho* to Gα T * is 1:1. The molecular weight of the complex was calculated from small-angle X-ray scattering data and was in good agreement with a model consisting of one Rho* and one G T *. The complex was visualized by negative-stain electron microscopy, which revealed an architecture similar to that of the β 2 -adrenergic receptor-G S complex, including a flexible α T * helical domain. The stability and high yield of the purified complex should allow for further efforts toward obtaining a high-resolution structure of this important signaling complex. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Opaque for the Reader but Transparent for the Brain: Neural Signatures of Morphological Complexity

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Meinzer, Marcus; Lahiri, Aditi; Flaisch, Tobias; Hannemann, Ronny; Eulitz, Carsten

2009-01-01

Within linguistics, words with a complex internal structure are commonly assumed to be decomposed into their constituent morphemes (e.g., un-help-ful). Nevertheless, an ongoing debate concerns the brain structures that subserve this process. Using functional magnetic resonance imaging, the present study varied the internal complexity of derived…

Information properties of morphologically complex words modulate brain activity during word reading.

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Hakala, Tero; Hultén, Annika; Lehtonen, Minna; Lagus, Krista; Salmelin, Riitta

2018-06-01

Neuroimaging studies of the reading process point to functionally distinct stages in word recognition. Yet, current understanding of the operations linked to those various stages is mainly descriptive in nature. Approaches developed in the field of computational linguistics may offer a more quantitative approach for understanding brain dynamics. Our aim was to evaluate whether a statistical model of morphology, with well-defined computational principles, can capture the neural dynamics of reading, using the concept of surprisal from information theory as the common measure. The Morfessor model, created for unsupervised discovery of morphemes, is based on the minimum description length principle and attempts to find optimal units of representation for complex words. In a word recognition task, we correlated brain responses to word surprisal values derived from Morfessor and from other psycholinguistic variables that have been linked with various levels of linguistic abstraction. The magnetoencephalography data analysis focused on spatially, temporally and functionally distinct components of cortical activation observed in reading tasks. The early occipital and occipito-temporal responses were correlated with parameters relating to visual complexity and orthographic properties, whereas the later bilateral superior temporal activation was correlated with whole-word based and morphological models. The results show that the word processing costs estimated by the statistical Morfessor model are relevant for brain dynamics of reading during late processing stages. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Patterns of cortical oscillations organize neural activity into whole-brain functional networks evident in the fMRI BOLD signal

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Jennifer C Whitman

2013-03-01

Full Text Available Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG / MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks.

Multi-signal Visualization of Physiology (MVP): a novel visualization dashboard for physiological monitoring of Traumatic Brain Injury patients.

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Sebastian, Kevin; Sari, Vivian; Loy, Liang Yu; Zhang, Feng; Zhang, Zhuo; Feng, Mengling

2012-01-01

To prevent Traumatic Brain Injury (TBI) patients from secondary brain injuries, patients' physiological readings are continuously monitored. However, the visualization dashboards of most existing monitoring devices cannot effectively present all physiological information of TBI patients and are also ineffective in facilitating neuro-clinicians for fast and accurate diagnosis. To address these shortcomings, we proposed a new visualization dashboard, namely the Multi-signal Visualization of Physiology (MVP). MVP makes use of multi-signal polygram to collate various physiological signals, and it also utilizes colors and the concept of "safe/danger zones" to assist neuro-clinicians to achieve fast and accurate diagnosis. Moreover, MVP allows neuro-clinicians to review historical physiological statuses of TBI patients, which can guide and optimize clinicians' diagnosis and prognosis decisions. The performance of MVP is tested and justified with an actual Philips monitoring device.

IGF-1: The Jekyll & Hyde of the aging brain.

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Gubbi, Sriram; Quipildor, Gabriela Farias; Barzilai, Nir; Huffman, Derek M; Milman, Sofiya

2018-05-08

The IGF-1 signaling pathway has emerged as a major regulator of the aging process, from rodents to humans. However, given the pleiotropic actions of IGF-1, its role in the aging brain remains complex and controversial. While IGF-1 is clearly essential for normal development of the central nervous system, conflicting evidence has emerged from preclinical and human studies regarding its relationship to cognitive function, as well as cerebrovascular and neurodegenerative disorders. This review delves into the current state of the evidence examining the role of IGF-1 in the aging brain, encompassing preclinical and clinical studies. A broad examination of the data indicates that IGF-1 may indeed play opposing roles in the aging brain, depending on the underlying pathology and context. Some evidence suggests that in the setting of neurodegenerative diseases that manifest with abnormal protein deposition in the brain, such as Alzheimer's disease, reducing IGF-1 signaling may serve a protective role by slowing disease progression and augmenting clearance of pathologic proteins to maintain cellular homeostasis. In contrast, inducing IGF-1 deficiency has also been implicated in dysregulated function of cognition and the neurovascular system, suggesting that some IGF-1 signaling may be necessary for normal brain function. Furthermore, states of acute neuronal injury, which necessitate growth, repair and survival signals to persevere, typically demonstrate salutary effects of IGF-1 in that context. Appreciating the dual, at times opposing "Dr. Jekyll" and "Mr. Hyde" characteristics of IGF-1 in the aging brain, will bring us closer to understanding its impact and devising more targeted IGF-1-related interventions.

The Effects of Peripheral and Central High Insulin on Brain Insulin Signaling and Amyloid-β in Young and Old APP/PS1 Mice.

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Stanley, Molly; Macauley, Shannon L; Caesar, Emily E; Koscal, Lauren J; Moritz, Will; Robinson, Grace O; Roh, Joseph; Keyser, Jennifer; Jiang, Hong; Holtzman, David M

2016-11-16

Hyperinsulinemia is a risk factor for late-onset Alzheimer's disease (AD). In vitro experiments describe potential connections between insulin, insulin signaling, and amyloid-β (Aβ), but in vivo experiments are needed to validate these relationships under physiological conditions. First, we performed hyperinsulinemic-euglycemic clamps with concurrent hippocampal microdialysis in young, awake, behaving APP swe /PS1 dE9 transgenic mice. Both a postprandial and supraphysiological insulin clamp significantly increased interstitial fluid (ISF) and plasma Aβ compared with controls. We could detect no increase in brain, ISF, or CSF insulin or brain insulin signaling in response to peripheral hyperinsulinemia, despite detecting increased signaling in the muscle. Next, we delivered insulin directly into the hippocampus of young APP/PS1 mice via reverse microdialysis. Brain tissue insulin and insulin signaling was dose-dependently increased, but ISF Aβ was unchanged by central insulin administration. Finally, to determine whether peripheral and central high insulin has differential effects in the presence of significant amyloid pathology, we repeated these experiments in older APP/PS1 mice with significant amyloid plaque burden. Postprandial insulin clamps increased ISF and plasma Aβ, whereas direct delivery of insulin to the hippocampus significantly increased tissue insulin and insulin signaling, with no effect on Aβ in old mice. These results suggest that the brain is still responsive to insulin in the presence of amyloid pathology but increased insulin signaling does not acutely modulate Aβ in vivo before or after the onset of amyloid pathology. Peripheral hyperinsulinemia modestly increases ISF and plasma Aβ in young and old mice, independent of neuronal insulin signaling. The transportation of insulin from blood to brain is a saturable process relevant to understanding the link between hyperinsulinemia and AD. In vitro experiments have found direct connections

Abnormal Brain Responses to Action Observation in Complex Regional Pain Syndrome.

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Hotta, Jaakko; Saari, Jukka; Koskinen, Miika; Hlushchuk, Yevhen; Forss, Nina; Hari, Riitta

2017-03-01

Patients with complex regional pain syndrome (CRPS) display various abnormalities in central motor function, and their pain is intensified when they perform or just observe motor actions. In this study, we examined the abnormalities of brain responses to action observation in CRPS. We analyzed 3-T functional magnetic resonance images from 13 upper limb CRPS patients (all female, ages 31-58 years) and 13 healthy, age- and sex-matched control subjects. The functional magnetic resonance imaging data were acquired while the subjects viewed brief videos of hand actions shown in the first-person perspective. A pattern-classification analysis was applied to characterize brain areas where the activation pattern differed between CRPS patients and healthy subjects. Brain areas with statistically significant group differences (q frontal gyrus, secondary somatosensory cortex, inferior parietal lobule, orbitofrontal cortex, and thalamus. Our findings indicate that CRPS impairs action observation by affecting brain areas related to pain processing and motor control. This article shows that in CRPS, the observation of others' motor actions induces abnormal neural activity in brain areas essential for sensorimotor functions and pain. These results build the cerebral basis for action-observation impairments in CRPS. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Lectures in Supercomputational Neurosciences Dynamics in Complex Brain Networks

CERN Document Server

Graben, Peter beim; Thiel, Marco; Kurths, Jürgen

2008-01-01

Computational Neuroscience is a burgeoning field of research where only the combined effort of neuroscientists, biologists, psychologists, physicists, mathematicians, computer scientists, engineers and other specialists, e.g. from linguistics and medicine, seem to be able to expand the limits of our knowledge. The present volume is an introduction, largely from the physicists' perspective, to the subject matter with in-depth contributions by system neuroscientists. A conceptual model for complex networks of neurons is introduced that incorporates many important features of the real brain, such as various types of neurons, various brain areas, inhibitory and excitatory coupling and the plasticity of the network. The computational implementation on supercomputers, which is introduced and discussed in detail in this book, will enable the readers to modify and adapt the algortihm for their own research. Worked-out examples of applications are presented for networks of Morris-Lecar neurons to model the cortical co...

Investigating Irregularly Patterned Deep Brain Stimulation Signal Design Using Biophysical Models

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Samantha Rose Summerson

2015-06-01

Full Text Available Parkinson’s disease (PD is a neurodegenerative disorder which follows from cell loss of dopaminergic neurons in the substantia nigra pars compacta (SNc, a nucleus in the basal ganglia (BG. Deep brain stimulation (DBS is an electrical therapy that modulates the pathological activity to treat the motor symptoms of PD. Although this therapy is currently used in clinical practice, the sufficient conditions for therapeutic efficacy are unknown. In this work we develop a model of critical motor circuit structures in the brain using biophysical cell models as the base components and then evaluate performance of different DBS signals in this model to perform comparative studies of their efficacy. Biological models are an important tool for gaining insights into neural function and, in this case, serve as effective tools for investigating innovative new DBS paradigms. Experiments were performed using the hemi-parkinsonian rodent model to test the same set of signals, verifying the obedience of the model to physiological trends. We show that antidromic spiking from DBS of the subthalamic nucleus (STN has a significant impact on cortical neural activity, which is frequency dependent and additionally modulated by the regularity of the stimulus pulse train used. Irregular spacing between stimulus pulses, where the amount of variability added is bounded, is shown to increase diversification of response of basal ganglia neurons and reduce entropic noise in cortical neurons, which may be fundamentally important to restoration of information flow in the motor circuit.

Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

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Pei-Feng Lin

Full Text Available The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG and a 19-channel eye-closed routine electroencephalography (EEG. Multiscale entropy (MSE analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS, and photic stimulation of slow frequencies (slow-PS of EEG in the 1-58 Hz frequency range, and three RR interval (RRI time series (awake-state, sleep and that concomitant with the EEG for each subject. The low-to-high frequency power (LF/HF ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse at Fp2, C4, T6 and T4; (b the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.

Maternal obesity alters brain derived neurotrophic factor (BDNF) signaling in the placenta in a sexually dimorphic manner.

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Prince, Calais S; Maloyan, Alina; Myatt, Leslie

2017-01-01

Obesity is a major clinical problem in obstetrics being associated with adverse pregnancy outcomes and fetal programming. Brain derived neurotrophic factor (BDNF), a validated miR-210 target, is necessary for placental development, fetal growth, glucose metabolism, and energy homeostasis. Plasma BDNF levels are reduced in obese individuals; however, placental BDNF has yet to be studied in the context of maternal obesity. In this study, we investigated the effect of maternal obesity and sexual dimorphism on placental BDNF signaling. BDNF signaling was measured in placentas from lean (pre-pregnancy BMI 30) women at term without medical complications that delivered via cesarean section without labor. MiRNA-210, BDNF mRNA, proBDNF, and mature BDNF were measured by RT - PCR, ELISA, and Western blot. Downstream signaling via TRKB (BDNF receptor) was measured using Western blot. Maternal obesity was associated with increased miRNA-210 and decreased BDNF mRNA in placentas from female fetuses, and decreased proBDNF in placentas from male fetuses. We also identified decreased mature BDNF in placentas from male fetuses when compared to female fetuses. Mir-210 expression was negatively correlated with mature BDNF protein. TRKB phosphorylated at tyrosine 817, not tyrosine 515, was increased in placentas from obese women. Maternal obesity was associated with increased phosphorylation of MAPK p38 in placentas from male fetuses, but not phosphorylation of ERK p42/44. BDNF regulation is complex and highly regulated. Pre-pregnancy/early maternal obesity adversely affects BDNF/TRKB signaling in the placenta in a sexually dimorphic manner. These data collectively suggest that induction of placental TRKB signaling could ameliorate the placental OB phenotype, thus improving perinatal outcome. Copyright © 2016 Elsevier Ltd. All rights reserved.

IMAGING BRAIN SIGNAL TRANSDUCTION AND METABOLISM VIA ARACHIDONIC AND DOCOSAHEXAENOIC ACID IN ANIMALS AND HUMANS

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Basselin, Mireille; Ramadan, Epolia; Rapoport, Stanley I.

2012-01-01

The polyunsaturated fatty acids (PUFAs), arachidonic acid (AA, 20:4n-6) and docosahexaenoic acid (DHA, 22:6n-3), important second messengers in brain, are released from membrane phospholipid following receptor-mediated activation of specific phospholipase A2 (PLA2) enzymes. We developed an in vivo method in rodents using quantitative autoradiography to image PUFA incorporation into brain from plasma, and showed that their incorporation rates equal their rates of metabolic consumption by brain. Thus, quantitative imaging of unesterified plasma AA or DHA incorporation into brain can be used as a biomarker of brain PUFA metabolism and neurotransmission. We have employed our method to image and quantify effects of mood stabilizers on brain AA/DHA incorporation during neurotransmission by muscarinic M1,3,5, serotonergic 5-HT2A/2C, dopaminergic D2-like (D2, D3, D4) or glutamatergic N-methyl-D-aspartic acid (NMDA) receptors, and effects of inhibition of acetylcholinesterase, of selective serotonin and dopamine reuptake transporter inhibitors, of neuroinflammation (HIV-1 and lipopolysaccharide) and excitotoxicity, and in genetically modified rodents. The method has been extended for the use with positron emission tomography (PET), and can be employed to determine how human brain AA/DHA signaling and consumption are influenced by diet, aging, disease and genetics. PMID:22178644

Use of multiple singular value decompositions to analyze complex intracellular calcium ion signals

KAUST Repository

Martinez, Josue G.; Huang, Jianhua Z.; Burghardt, Robert C.; Barhoumi, Rola; Carroll, Raymond J.

2009-01-01

) to extract the signals from such movies, in a way that is semi-automatic and tuned closely to the actual data and their many complexities. These complexities include the following. First, the images themselves are of no interest: all interest focuses

Suppressed neural complexity during ketamine- and propofol-induced unconsciousness.

Science.gov (United States)

Wang, Jisung; Noh, Gyu-Jeong; Choi, Byung-Moon; Ku, Seung-Woo; Joo, Pangyu; Jung, Woo-Sung; Kim, Seunghwan; Lee, Heonsoo

2017-07-13

Ketamine and propofol have distinctively different molecular mechanisms of action and neurophysiological features, although both induce loss of consciousness. Therefore, identifying a common feature of ketamine- and propofol-induced unconsciousness would provide insight into the underlying mechanism of losing consciousness. In this study we search for a common feature by applying the concept of type-II complexity, and argue that neural complexity is essential for a brain to maintain consciousness. To test this hypothesis, we show that complexity is suppressed during loss of consciousness induced by ketamine or propofol. We analyzed the randomness (type-I complexity) and complexity (type-II complexity) of electroencephalogram (EEG) signals before and after bolus injection of ketamine or propofol. For the analysis, we use Mean Information Gain (MIG) and Fluctuation Complexity (FC), which are information-theory-based measures that quantify disorder and complexity of dynamics respectively. Both ketamine and propofol reduced the complexity of the EEG signal, but ketamine increased the randomness of the signal and propofol decreased it. The finding supports our claim and suggests EEG complexity as a candidate for a consciousness indicator. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparative analysis of brain EEG signals generated from the right and left hand while writing

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Sardesai, Neha; Jamali Mahabadi, S. E.; Meng, Qinglei; Choa, Fow-Sen

2016-05-01

This paper provides a comparative analysis of right handed people and left handed people when they write with both their hands. Two left handed and one right handed subject were asked to write their respective names on a paper using both, their left and right handed, and their brain signals were measured using EEG. Similarly, they were asked to perform simple mathematical calculations using both their hand. The data collected from the EEG from writing with both hands is compared. It is observed that though it is expected that the right brain only would contribute to left handed writing and vice versa, it is not so. When a right handed person writes with his/her left hand, the initial instinct is to go for writing with the right hand. Hence, both parts of the brain are active when a subject writes with the other hand. However, when the activity is repeated, the brain learns to expect to write with the other hand as the activity is repeated and then only the expected part of the brain is active.

Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals

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Banerjee, Archi; Sanyal, Shankha; Patranabis, Anirban; Banerjee, Kaushik; Guhathakurta, Tarit; Sengupta, Ranjan; Ghosh, Dipak; Ghose, Partha

2016-02-01

Music has been proven to be a valuable tool for the understanding of human cognition, human emotion, and their underlying brain mechanisms. The objective of this study is to analyze the effect of Hindustani music on brain activity during normal relaxing conditions using electroencephalography (EEG). Ten male healthy subjects without special musical education participated in the study. EEG signals were acquired at the frontal (F3/F4) lobes of the brain while listening to music at three experimental conditions (rest, with music and without music). Frequency analysis was done for the alpha, theta and gamma brain rhythms. The finding shows that arousal based activities were enhanced while listening to Hindustani music of contrasting emotions (romantic/sorrow) for all the subjects in case of alpha frequency bands while no significant changes were observed in gamma and theta frequency ranges. It has been observed that when the music stimulus is removed, arousal activities as evident from alpha brain rhythms remain for some time, showing residual arousal. This is analogous to the conventional 'Hysteresis' loop where the system retains some 'memory' of the former state. This is corroborated in the non linear analysis (Detrended Fluctuation Analysis) of the alpha rhythms as manifested in values of fractal dimension. After an input of music conveying contrast emotions, withdrawal of music shows more retention as evidenced by the values of fractal dimension.

A potential neural substrate for processing functional classes of complex acoustic signals.

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Isabelle George

Full Text Available Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

Changes in Electroencephalography Complexity using a Brain Computer Interface-Motor Observation Training in Chronic Stroke Patients: A Fuzzy Approximate Entropy Analysis

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Rui Sun

2017-09-01

Full Text Available Entropy-based algorithms have been suggested as robust estimators of electroencephalography (EEG predictability or regularity. This study aimed to examine possible disturbances in EEG complexity as a means to elucidate the pathophysiological mechanisms in chronic stroke, before and after a brain computer interface (BCI-motor observation intervention. Eleven chronic stroke subjects and nine unimpaired subjects were recruited to examine the differences in their EEG complexity. The BCI-motor observation intervention was designed to promote functional recovery of the hand in stroke subjects. Fuzzy approximate entropy (fApEn, a novel entropy-based algorithm designed to evaluate complexity in physiological systems, was applied to assess the EEG signals acquired from unimpaired subjects and stroke subjects, both before and after training. The results showed that stroke subjects had significantly lower EEG fApEn than unimpaired subjects (p < 0.05 in the motor cortex area of the brain (C3, C4, FC3, FC4, CP3, and CP4 in both hemispheres before training. After training, motor function of the paretic upper limb, assessed by the Fugl-Meyer Assessment-Upper Limb (FMA-UL, Action Research Arm Test (ARAT, and Wolf Motor Function Test (WMFT improved significantly (p < 0.05. Furthermore, the EEG fApEn in stroke subjects increased considerably in the central area of the contralesional hemisphere after training (p < 0.05. A significant correlation was noted between clinical scales (FMA-UL, ARAT, and WMFT and EEG fApEn in C3/C4 in the contralesional hemisphere (p < 0.05. This finding suggests that the increase in EEG fApEn could be an estimator of the variance in upper limb motor function improvement. In summary, fApEn can be used to identify abnormal EEG complexity in chronic stroke, when used with BCI-motor observation training. Moreover, these findings based on the fApEn of EEG signals also expand the existing interpretation of training-induced functional

Brain serotonin signaling does not determine sexual preference in male mice.

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Mariana Angoa-Pérez

Full Text Available It was reported recently that male mice lacking brain serotonin (5-HT lose their preference for females (Liu et al., 2011, Nature, 472, 95-100, suggesting a role for 5-HT signaling in sexual preference. Regulation of sex preference by 5-HT lies outside of the well established roles in this behavior established for the vomeronasal organ (VNO and the main olfactory epithelium (MOE. Presently, mice with a null mutation in the gene for tryptophan hydroxylase 2 (TPH2, which are depleted of brain 5-HT, were tested for sexual preference. When presented with inanimate (urine scents from male or estrous female or animate (male or female mouse in estrus sexual stimuli, TPH2-/- males show a clear preference for female over male stimuli. When a TPH2-/- male is offered the simultaneous choice between an estrous female and a male mouse, no sexual preference is expressed. However, when confounding behaviors that are seen among 3 mice in the same cage are controlled, TPH2-/- mice, like their TPH2+/+ counterparts, express a clear preference for female mice. Female TPH2-/- mice are preferred by males over TPH2+/+ females but this does not lead to increased pregnancy success. In fact, if one or both partners in a mating pair are TPH2-/- in genotype, pregnancy success rates are significantly decreased. Finally, expression of the VNO-specific cation channel TRPC2 and of CNGA2 in the MOE of TPH2-/- mice is normal, consistent with behavioral findings that sexual preference of TPH2-/- males for females is intact. In conclusion, 5-HT signaling in brain does not determine sexual preference in male mice. The use of pharmacological agents that are non-selective for the 5-HT neuronal system and that have serious adverse effects may have contributed historically to the stance that 5-HT regulates sexual behavior, including sex partner preference.

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

Science.gov (United States)

Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

2018-06-01

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

Retardation of fetal dendritic development induced by gestational hyperglycemia is associated with brain insulin/IGF-I signals.

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Jing, Yu-Hong; Song, Yan-Feng; Yao, Ya-Ming; Yin, Jie; Wang, De-Gui; Gao, Li-Ping

2014-10-01

Hyperglycemia is an essential risk factor for mothers and fetuses in gestational diabetes. Clinical observation has indicated that the offspring of mothers with diabetes shows impaired somatosensory function and IQ. However, only a few studies have explored the effects of hyperglycemia on fetal brain development. Neurodevelopment is susceptible to environmental conditions. Thus, this study aims to investigate the effects of maternal hyperglycemia on fetal brain development and to evaluate insulin and insulin-like growth factor-I (IGF-I) signals in fetal brain under hyperglycemia or controlled hyperglycemia. At day 1 of pregnancy, gestational rats were intraperitoneally injected with streptozocin (60 mg/kg). Some of the hyperglycemic gestational rats were injected with insulin (20 IU, two times a day) to control hyperglycemia; the others were injected with saline of equal volume. The gestational rats were sacrificed at days 14, 16, and 18 of embryo development. The dendritic spines of subplate cortex neurons in the fetal brain were detected by Golgi-Cox staining. The mRNA levels of insulin receptors (IRs) and IGF-IR in the fetal brain were measured using qRT-PCR. The protein levels of synaptophysin, IR, and IGF-IR in the fetal brain were detected by western blot. No significant difference in fetal brain formation was observed between the maternal hyperglycemic group and insulin-treated group. By contrast, obvious retardation of dendritic development in the fetus was observed in the maternal hyperglycemic group. Similarly, synaptophysin expression was lower in the fetus of the maternal hyperglycemic group than in that of the insulin-treated group. The mRNA and protein expression levels of IRs in the fetal brain were higher in the hyperglycemic group than in the insulin-treated group. By contrast, the levels of IGF-IR in the brain were lower in the fetus of the maternal hyperglycemic group than in that of the insulin-treated group. These results suggested that

Edaravone attenuates neuronal apoptosis in hypoxic-ischemic brain damage rat model via suppression of TRAIL signaling pathway.

Science.gov (United States)

Li, Chunyi; Mo, Zhihuai; Lei, Junjie; Li, Huiqing; Fu, Ruying; Huang, Yanxia; Luo, Shijian; Zhang, Lei

2018-06-01

Edaravone is a new type of oxygen free radical scavenger and able to attenuate various brain damage including hypoxic-ischemic brain damage (HIBD). This study was aimed at investigating the neuroprotective mechanism of edaravone in rat hypoxic-ischemic brain damage model and its correlation with tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) signaling pathway. 75 seven-day-old Sprague-Dawley neonatal rats were equally divided into three groups: sham-operated group (sham), HIBD group and HIBD rats injected with edaravone (HIBD + EDA) group. Neurological severity and space cognitive ability of rats in each group were evaluated using Longa neurological severity score and Morris water maze testing. TUNEL assay and flow cytometry were used to determine brain cell apoptosis. Western blot was used to estimate the expression level of death receptor-5 (DR5), Fas-associated protein with death domain (FADD), caspase 8, B-cell lymphoma-2 (Bcl-2) and Bcl-2 associated X protein (Bax). In addition, immunofluorescence was performed to detect caspase 3. Edaravone reduced neurofunctional damage caused by HIBD and improved the cognitive capability of rats. The above experiment results suggested that edaravone could down-regulate the expression of active caspase 3 protein, thereby relieving neuronal apoptosis. Taken together, edaravone could attenuate neuronal apoptosis in rat hypoxic-ischemic brain damage model via suppression of TRAIL signaling pathway, which also suggested that edaravone might be an effective therapeutic strategy for HIBD clinical treatment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Age- and gender-related regional variations of human brain cortical thickness, complexity, and gradient in the third decade.

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Creze, Maud; Versheure, Leslie; Besson, Pierre; Sauvage, Chloe; Leclerc, Xavier; Jissendi-Tchofo, Patrice

2014-06-01

Brain functional and cytoarchitectural maturation continue until adulthood, but little is known about the evolution of the regional pattern of cortical thickness (CT), complexity (CC), and intensity or gradient (CG) in young adults. We attempted to detect global and regional age- and gender-related variations of brain CT, CC, and CG, in 28 healthy young adults (19-33 years) using a three-dimensional T1 -weighted magnetic resonance imaging sequence and surface-based methods. Whole brain interindividual variations of CT and CG were similar to that in the literature. As a new finding, age- and gender-related variations significantly affected brain complexity (P gender), all in the right hemisphere. Regions of interest analyses showed age and gender significant interaction (P left inferior parietal. In addition, we found significant inverse correlations between CT and CC and between CT and CG over the whole brain and markedly in precentral and occipital areas. Our findings differ in details from previous reports and may correlate with late brain maturation and learning plasticity in young adults' brain in the third decade. Copyright © 2013 Wiley Periodicals, Inc.

Neural Correlates of Temporal Complexity and Synchrony during Audiovisual Correspondence Detection.

Science.gov (United States)

Baumann, Oliver; Vromen, Joyce M G; Cheung, Allen; McFadyen, Jessica; Ren, Yudan; Guo, Christine C

2018-01-01

We often perceive real-life objects as multisensory cues through space and time. A key challenge for audiovisual integration is to match neural signals that not only originate from different sensory modalities but also that typically reach the observer at slightly different times. In humans, complex, unpredictable audiovisual streams lead to higher levels of perceptual coherence than predictable, rhythmic streams. In addition, perceptual coherence for complex signals seems less affected by increased asynchrony between visual and auditory modalities than for simple signals. Here, we used functional magnetic resonance imaging to determine the human neural correlates of audiovisual signals with different levels of temporal complexity and synchrony. Our study demonstrated that greater perceptual asynchrony and lower signal complexity impaired performance in an audiovisual coherence-matching task. Differences in asynchrony and complexity were also underpinned by a partially different set of brain regions. In particular, our results suggest that, while regions in the dorsolateral prefrontal cortex (DLPFC) were modulated by differences in memory load due to stimulus asynchrony, areas traditionally thought to be involved in speech production and recognition, such as the inferior frontal and superior temporal cortex, were modulated by the temporal complexity of the audiovisual signals. Our results, therefore, indicate specific processing roles for different subregions of the fronto-temporal cortex during audiovisual coherence detection.

Endothelial β-Catenin Signaling Is Required for Maintaining Adult Blood-Brain Barrier Integrity and Central Nervous System Homeostasis.

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Tran, Khiem A; Zhang, Xianming; Predescu, Dan; Huang, Xiaojia; Machado, Roberto F; Göthert, Joachim R; Malik, Asrar B; Valyi-Nagy, Tibor; Zhao, You-Yang

2016-01-12

The blood-brain barrier (BBB) formed by brain endothelial cells interconnected by tight junctions is essential for the homeostasis of the central nervous system. Although studies have shown the importance of various signaling molecules in BBB formation during development, little is known about the molecular basis regulating the integrity of the adult BBB. Using a mouse model with tamoxifen-inducible endothelial cell-restricted disruption of ctnnb1 (iCKO), we show here that endothelial β-catenin signaling is essential for maintaining BBB integrity and central nervous system homeostasis in adult mice. The iCKO mice developed severe seizures accompanied by neuronal injury, multiple brain petechial hemorrhages, and central nervous system inflammation, and all had postictal death. Disruption of endothelial β-catenin induced BBB breakdown and downregulation of the specific tight junction proteins claudin-1 and -3 in adult brain endothelial cells. The clinical relevance of the data is indicated by the observation of decreased expression of claudin-1 and nuclear β-catenin in brain endothelial cells of hemorrhagic lesions of hemorrhagic stroke patients. These results demonstrate the prerequisite role of endothelial β-catenin in maintaining the integrity of adult BBB. The results suggest that BBB dysfunction secondary to defective β-catenin transcription activity is a key pathogenic factor in hemorrhagic stroke, seizure activity, and central nervous system inflammation. © 2015 American Heart Association, Inc.

Transport of /sup 99m/Tc complexes through the blood-brain barrier

International Nuclear Information System (INIS)

Loberg, M.D.; Corder, E.H.; Fields, A.T.; Callery, P.S.

1979-01-01

Thirteen /sup 99m/Tc complexes have been synthesized and used to determine the relationships between protein binding, lipophilicity and membrane transport. The lipophilicity of the /sup 99m/Tc complexes was altered by adding substituents to either IDA, EDTA, DTPA or oxine; membrane transport was estimated using the brain uptake index (BUI) method. The BUI of the /sup 99m/Tc complexes was found to vary directly with lipophilicity and inversely with protein binding. These results demonstrated that /sup 99m/Tc-oxine derivatives are better suited for use in the development of intracellular tracers than are the /sup 99m/Tc derivatives of aminopolycarboxylates

Age-dependent complex noise fluctuations in the brain

International Nuclear Information System (INIS)

Mareš, Jan; Vyšata, Oldřich; Procházka, Aleš; Vališ, Martin

2013-01-01

We investigated the parameters of colored noise in EEG data of 17 722 professional drivers aged 18–70. The whole study is based upon experiments showing that biological neural networks may operate in the vicinity of the critical point and that the balance between excitation and inhibition in the human brain is important for the transfer of information. This paper is devoted to the study of EEG power spectrum which can be described best by a power function with 1/f λ distribution and colored noise corresponding to the critical point in the EEG signal has the value of λ = 1 (purple noise). The slow accumulation of energy and its quick release is a universal property of the 1/f distribution. The physiological mechanism causing energy dissipation in the brain seems to depend on the number and strength of the connections between clusters of neurons. With ageing, the number of connections between the neurons decreases. Learning ability and intellectual performance also decrease. Therefore, age-related changes in the λ coefficient can be anticipated. We found that absolute values of λ coefficients decrease significantly with increasing age. Deviations from this rule are related to age-dependent slowing of the dominant frequency in the alpha band. Age-dependent change in the parameter and colored noise may be indicative of age-related changes in the self-organization of brain activity. Results obtained include (i) the age-dependent decrease of the absolute values of the average λ coefficient with the regression coefficient 0.005 1/year, (ii) distribution of λ value changes related to EEG frequency bands and to localization of electrodes on the scalp, and (iii) relation of age-dependent changes of colored noise and EEG energy in separate frequency bands. (paper)

Psychobiotics and the Manipulation of Bacteria-Gut-Brain Signals.

Science.gov (United States)

Sarkar, Amar; Lehto, Soili M; Harty, Siobhán; Dinan, Timothy G; Cryan, John F; Burnet, Philip W J

2016-11-01

Psychobiotics were previously defined as live bacteria (probiotics) which, when ingested, confer mental health benefits through interactions with commensal gut bacteria. We expand this definition to encompass prebiotics, which enhance the growth of beneficial gut bacteria. We review probiotic and prebiotic effects on emotional, cognitive, systemic, and neural variables relevant to health and disease. We discuss gut-brain signalling mechanisms enabling psychobiotic effects, such as metabolite production. Overall, knowledge of how the microbiome responds to exogenous influence remains limited. We tabulate several important research questions and issues, exploration of which will generate both mechanistic insights and facilitate future psychobiotic development. We suggest the definition of psychobiotics be expanded beyond probiotics and prebiotics to include other means of influencing the microbiome. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Investigation of Resonance Effect Caused by Local Exposure of Extremely Low Frequency Magnetic Field on Brain Signals: A Randomize Clinical Trial

Directory of Open Access Journals (Sweden)

Rasul Zadeh Tabataba’ei K

2011-03-01

Full Text Available Background and Objectives: Some studies have investigated the effects of extremely low frequency magnetic fields (ELF-MFs on brain signals, but only few of them have reported that humans exposed to magnetic fields exhibit changes in brain signals at the frequency of stimulation, i.e. resonance effect. In most investigations, researchers usually take advantage of a uniform field which encompasses the head. The aim of present study was to expose different parts of the brain to ELF-MFs locally and to investigate variation of brain signal and resonance effect.Methods: The subjects consisting of 19 male-students with the mean age of 25.6±1.6 years participated in this study. Local ELF-MFs with 3, 5, 10, 17 and 45Hz frequencies and 240 μT intensity was applied on five points (T3, T4, Cz, F3 and F4 of participants scalp Separately in 10-20 system. In the end, relative power over this points in common frequency bands and at the frequency of magnetic fields was evaluated by paired t-test.Results: Exposure of Central area by local magnetic field caused significant change (p<0.05 in the forehead alpha band. Reduction in the alpha band over central area was observed when temporal area was exposed to ELF MF.Conclusion: The results showed that resonance effect in the brain signals caused by local magnetic field exposure was not observed and change in every part of the relative power spectrum might occur. The changes in the EEG bands were not limited necessarily to the exposure point.

A mechanism for vertebrate Hedgehog signaling: recruitment to cilia and dissociation of SuFu-Gli protein complexes.

Science.gov (United States)

Tukachinsky, Hanna; Lopez, Lyle V; Salic, Adrian

2010-10-18

In vertebrates, Hedgehog (Hh) signaling initiated in primary cilia activates the membrane protein Smoothened (Smo) and leads to activation of Gli proteins, the transcriptional effectors of the pathway. In the absence of signaling, Gli proteins are inhibited by the cytoplasmic protein Suppressor of Fused (SuFu). It is unclear how Hh activates Gli and whether it directly regulates SuFu. We find that Hh stimulation quickly recruits endogenous SuFu-Gli complexes to cilia, suggesting a model in which Smo activates Gli by relieving inhibition by SuFu. In support of this model, we find that Hh causes rapid dissociation of the SuFu-Gli complex, thus allowing Gli to enter the nucleus and activate transcription. Activation of protein kinase A (PKA), an inhibitor of Hh signaling, blocks ciliary localization of SuFu-Gli complexes, which in turn prevents their dissociation by signaling. Our results support a simple mechanism in which Hh signals at vertebrate cilia cause dissociation of inactive SuFu-Gli complexes, a process inhibited by PKA.

A mechanism for vertebrate Hedgehog signaling: recruitment to cilia and dissociation of SuFu–Gli protein complexes

Science.gov (United States)

Tukachinsky, Hanna; Lopez, Lyle V.

2010-01-01

In vertebrates, Hedgehog (Hh) signaling initiated in primary cilia activates the membrane protein Smoothened (Smo) and leads to activation of Gli proteins, the transcriptional effectors of the pathway. In the absence of signaling, Gli proteins are inhibited by the cytoplasmic protein Suppressor of Fused (SuFu). It is unclear how Hh activates Gli and whether it directly regulates SuFu. We find that Hh stimulation quickly recruits endogenous SuFu–Gli complexes to cilia, suggesting a model in which Smo activates Gli by relieving inhibition by SuFu. In support of this model, we find that Hh causes rapid dissociation of the SuFu–Gli complex, thus allowing Gli to enter the nucleus and activate transcription. Activation of protein kinase A (PKA), an inhibitor of Hh signaling, blocks ciliary localization of SuFu–Gli complexes, which in turn prevents their dissociation by signaling. Our results support a simple mechanism in which Hh signals at vertebrate cilia cause dissociation of inactive SuFu–Gli complexes, a process inhibited by PKA. PMID:20956384

New isatin derivative inhibits neurodegeneration by restoring insulin signaling in brain.

Science.gov (United States)

Aftab, Meha Fatima; Afridi, Shabbir Khan; Mughal, Uzma Rasool; Karim, Aneela; Haleem, Darakhshan Jabeen; Kabir, Nurul; Khan, Khalid M; Hafizur, Rahman M; Waraich, Rizwana S

2017-04-01

Diabetes is associated with neurodegeneration. Glycation ensues in diabetes and glycated proteins cause insulin resistance in brain resulting in amyloid plaques and NFTs. Also glycation enhances gliosis by promoting neuroinflammation. Currently there is no therapy available to target neurodegenration in brain therefore, development of new therapy that offers neuroprotection is critical. The objective of this study was to evaluate mechanistic effect of isatin derivative URM-II-81, an anti-glycation agent for improvement of insulin action in brain and inhibition of neurodegenration. Methylglyoxal induced stress was inhibited by treatment with URM-II-81. Also, Ser473 and Ser9 phosphorylation of Akt and GSK-3β respectively were restored by URM-II-81. Effect of URM-II-81 on axonal integrity was studied by differentiating Neuro2A using retinoic acid. URM-II-81 restored axonal length in MGO treated cells. Its effects were also studied in high fat and low dose streptozotocin induced diabetic mice where it reduced RBG levels and inhibited glycative stress by reducing HbA1c. URM-II-81 treatment also showed inhibition of gliosis in hippocampus. Histological analysis showed reduced NFTs in CA3 hippocampal region and restoration of insulin signaling in hippocampii of diabetic mice. Our findings suggest that URM-II-81 can be developed as a new therapeutic agent for treatment of neurodegenration. Copyright © 2017 Elsevier B.V. All rights reserved.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

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White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID

Complexity and competition in appetitive and aversive neural circuits

Directory of Open Access Journals (Sweden)

Crista L. Barberini

2012-11-01

Full Text Available Decision-making often involves using sensory cues to predict possible rewarding or punishing reinforcement outcomes before selecting a course of action. Recent work has revealed complexity in how the brain learns to predict rewards and punishments. Analysis of neural signaling during and after learning in the amygdala and orbitofrontal cortex, two brain areas that process appetitive and aversive stimuli, reveals a dynamic relationship between appetitive and aversive circuits. Specifically, the relationship between signaling in appetitive and aversive circuits in these areas shifts as a function of learning. Furthermore, although appetitive and aversive circuits may often drive opposite behaviors – approaching or avoiding reinforcement depending upon its valence – these circuits can also drive similar behaviors, such as enhanced arousal or attention; these processes also may influence choice behavior. These data highlight the formidable challenges ahead in dissecting how appetitive and aversive neural circuits interact to produce a complex and nuanced range of behaviors.

Improved Empirical Mode Decomposition Algorithm of Processing Complex Signal for IoT Application

OpenAIRE

Yang, Xianzhao; Cheng, Gengguo; Liu, Huikang

2015-01-01

Hilbert-Huang transform is widely used in signal analysis. However, due to its inadequacy in estimating both the maximum and the minimum values of the signals at both ends of the border, traditional HHT is easy to produce boundary error in empirical mode decomposition (EMD) process. To overcome this deficiency, this paper proposes an enhanced empirical mode decomposition algorithm for processing complex signal. Our work mainly focuses on two aspects. On one hand, we develop a technique to obt...

LC-MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices.

Science.gov (United States)

Choi, B K; Hercules, D M; Gusev, A I

2001-02-01

The application of LC separation and mobile phase additives in addressing LC-MS/MS matrix signal suppression effects for the analysis of pesticides in a complex environmental matrix was investigated. It was shown that signal suppression is most significant for analytes eluting early in the LC-MS analysis. Introduction of different buffers (e.g. ammonium formate, ammonium hydroxide, formic acid) into the LC mobile phase was effective in improving signal correlation between the matrix and standard samples. The signal improvement is dependent on buffer concentration as well as LC separation of the matrix components. The application of LC separation alone was not effective in addressing suppression effects when characterizing complex matrix samples. Overloading of the LC column by matrix components was found to significantly contribute to analyte-matrix co-elution and suppression of signal. This signal suppression effect can be efficiently compensated by 2D LC (LC-LC) separation techniques. The effectiveness of buffers and LC separation in improving signal correlation between standard and matrix samples is discussed.

Rapid anatomical brain imaging using spiral acquisition and an expanded signal model.

Science.gov (United States)

Kasper, Lars; Engel, Maria; Barmet, Christoph; Haeberlin, Maximilian; Wilm, Bertram J; Dietrich, Benjamin E; Schmid, Thomas; Gross, Simon; Brunner, David O; Stephan, Klaas E; Pruessmann, Klaas P

2018-03-01

We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B 0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute. A range of options is explored, including proton-density and T 2 * contrast, acceleration by parallel imaging, different readout orientations, and the extraction of phase images. Results are shown to exhibit competitive image quality along with high geometric consistency. Copyright © 2017 Elsevier Inc. All rights reserved.

Insulin action in brain regulates systemic metabolism and brain function.

Science.gov (United States)

Kleinridders, André; Ferris, Heather A; Cai, Weikang; Kahn, C Ronald

2014-07-01

Insulin receptors, as well as IGF-1 receptors and their postreceptor signaling partners, are distributed throughout the brain. Insulin acts on these receptors to modulate peripheral metabolism, including regulation of appetite, reproductive function, body temperature, white fat mass, hepatic glucose output, and response to hypoglycemia. Insulin signaling also modulates neurotransmitter channel activity, brain cholesterol synthesis, and mitochondrial function. Disruption of insulin action in the brain leads to impairment of neuronal function and synaptogenesis. In addition, insulin signaling modulates phosphorylation of tau protein, an early component in the development of Alzheimer disease. Thus, alterations in insulin action in the brain can contribute to metabolic syndrome, and the development of mood disorders and neurodegenerative diseases. © 2014 by the American Diabetes Association.

Use of multiple singular value decompositions to analyze complex intracellular calcium ion signals

KAUST Repository

Martinez, Josue G.

2009-12-01

We compare calcium ion signaling (Ca(2+)) between two exposures; the data are present as movies, or, more prosaically, time series of images. This paper describes novel uses of singular value decompositions (SVD) and weighted versions of them (WSVD) to extract the signals from such movies, in a way that is semi-automatic and tuned closely to the actual data and their many complexities. These complexities include the following. First, the images themselves are of no interest: all interest focuses on the behavior of individual cells across time, and thus, the cells need to be segmented in an automated manner. Second, the cells themselves have 100+ pixels, so that they form 100+ curves measured over time, so that data compression is required to extract the features of these curves. Third, some of the pixels in some of the cells are subject to image saturation due to bit depth limits, and this saturation needs to be accounted for if one is to normalize the images in a reasonably un-biased manner. Finally, the Ca(2+) signals have oscillations or waves that vary with time and these signals need to be extracted. Thus, our aim is to show how to use multiple weighted and standard singular value decompositions to detect, extract and clarify the Ca(2+) signals. Our signal extraction methods then lead to simple although finely focused statistical methods to compare Ca(2+) signals across experimental conditions.

Brain signal variability is modulated as a function of internal and external demand in younger and older adults.

Science.gov (United States)

Grady, Cheryl L; Garrett, Douglas D

2018-04-01

Variability in the Blood Oxygen-Level Dependent (BOLD) signal from fMRI is often associated with better cognitive performance and younger age. It has been proposed that neural variability enables flexible responding to uncertainty in a changing environment. However, signal variability reflecting environmental uncertainty may reduce to the extent that a task depends on internally-directed attention and is supported by neural "solutions" that are schematic and relatively stable within each individual. Accordingly, we examined the hypothesis that BOLD variability will be low at rest, higher during internally-directed tasks, and higher still during externally-directed tasks, and that this effect will be reduced with aging. Modulation of BOLD variability across conditions was consistent with these hypotheses, and was associated with faster and more stable behavioral performance in both young and older adults. These data support the idea that brain signal variability may modulate in response to environmental uncertainty, which is presumed to be greater in the external environment than in the internal milieu. Reduced flexibility of signal variability with age may indicate less ability to switch between internal and external brain states. Copyright © 2017 Elsevier Inc. All rights reserved.

Repeated intravenous administration of gadobutrol does not lead to increased signal intensity on unenhanced T1-weighted images - a voxel-based whole brain analysis

Energy Technology Data Exchange (ETDEWEB)

Langner, Soenke; Kromrey, Marie-Luise [University Medicine Greifswald, Institute of Diagnostic Radiology and Neuroradiology, Greifswald (Germany); Kuehn, Jens-Peter [University Medicine Greifswald, Institute of Diagnostic Radiology and Neuroradiology, Greifswald (Germany); University Hospital, Carl Gustav Carus University Dresden, Institute for Radiology, Dresden (Germany); Grothe, Matthias [University Medicine Greifswald, Department of Neurology, Greifswald (Germany); Domin, Martin [University Medicine Greifswald, Functional Imaging Unit, Institute of Diagnostic Radiology and Neuroradiology, Greifswald (Germany)

2017-09-15

To identify a possible association between repeated intravenous administration of gadobutrol and increased signal intensity in the grey and white matter using voxel-based whole-brain analysis. In this retrospective single-centre study, 217 patients with a clinically isolated syndrome underwent baseline brain magnetic resonance imaging and at least one annual follow-up examination with intravenous administration of 0.1 mmol/kg body weight of gadobutrol. Using the ''Diffeomorphic Anatomical Registration using Exponentiated Lie algebra'' (DARTEL) normalisation process, tissue templates for grey matter (GM), white matter (WM), and cerebrospinal fluid (CSF) were calculated, as were GM-CSF and WM-CSF ratios. Voxel-based whole-brain analysis was used to calculate the signal intensity for each voxel in each data set. Paired t-test was applied to test differences to baseline MRI for significance. Voxel-based whole-brain analysis demonstrated no significant changes in signal intensity of grey and white matter after up to five gadobutrol administrations. There was no significant change in GM-CSF and grey WM-CSF ratios. Voxel-based whole-brain analysis did not demonstrate increased signal intensity of GM and WM on unenhanced T1-weighted images after repeated gadobutrol administration. The molecular structure of gadolinium-based contrast agent preparations may be an essential factor causing SI increase on unenhanced T1-weighted images. (orig.)

The Hrs/Stam complex acts as a positive and negative regulator of RTK signaling during Drosophila development.

Directory of Open Access Journals (Sweden)

Hélène Chanut-Delalande

Full Text Available BACKGROUND: Endocytosis is a key regulatory step of diverse signalling pathways, including receptor tyrosine kinase (RTK signalling. Hrs and Stam constitute the ESCRT-0 complex that controls the initial selection of ubiquitinated proteins, which will subsequently be degraded in lysosomes. It has been well established ex vivo and during Drosophila embryogenesis that Hrs promotes EGFR down regulation. We have recently isolated the first mutations of stam in flies and shown that Stam is required for air sac morphogenesis, a larval respiratory structure whose formation critically depends on finely tuned levels of FGFR activity. This suggest that Stam, putatively within the ESCRT-0 complex, modulates FGF signalling, a possibility that has not been examined in Drosophila yet. PRINCIPAL FINDINGS: Here, we assessed the role of the Hrs/Stam complex in the regulation of signalling activity during Drosophila development. We show that stam and hrs are required for efficient FGFR signalling in the tracheal system, both during cell migration in the air sac primordium and during the formation of fine cytoplasmic extensions in terminal cells. We find that stam and hrs mutant cells display altered FGFR/Btl localisation, likely contributing to impaired signalling levels. Electron microscopy analyses indicate that endosome maturation is impaired at distinct steps by hrs and stam mutations. These somewhat unexpected results prompted us to further explore the function of stam and hrs in EGFR signalling. We show that while stam and hrs together downregulate EGFR signalling in the embryo, they are required for full activation of EGFR signalling during wing development. CONCLUSIONS/SIGNIFICANCE: Our study shows that the ESCRT-0 complex differentially regulates RTK signalling, either positively or negatively depending on tissues and developmental stages, further highlighting the importance of endocytosis in modulating signalling pathways during development.

Maternal Inflammation Contributes to Brain Overgrowth and Autism-Associated Behaviors through Altered Redox Signaling in Stem and Progenitor Cells

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Janel E. Le Belle

2014-11-01

Full Text Available A period of mild brain overgrowth with an unknown etiology has been identified as one of the most common phenotypes in autism. Here, we test the hypothesis that maternal inflammation during critical periods of embryonic development can cause brain overgrowth and autism-associated behaviors as a result of altered neural stem cell function. Pregnant mice treated with low-dose lipopolysaccharide at embryonic day 9 had offspring with brain overgrowth, with a more pronounced effect in PTEN heterozygotes. Exposure to maternal inflammation also enhanced NADPH oxidase (NOX-PI3K pathway signaling, stimulated the hyperproliferation of neural stem and progenitor cells, increased forebrain microglia, and produced abnormal autism-associated behaviors in affected pups. Our evidence supports the idea that a prenatal neuroinflammatory dysregulation in neural stem cell redox signaling can act in concert with underlying genetic susceptibilities to affect cellular responses to environmentally altered cellular levels of reactive oxygen species.

Precise signal amplitude retrieval for a non-homogeneous diagnostic beam using complex interferometry approach

Science.gov (United States)

Krupka, M.; Kalal, M.; Dostal, J.; Dudzak, R.; Juha, L.

2017-08-01

Classical interferometry became widely used method of active optical diagnostics. Its more advanced version, allowing reconstruction of three sets of data from just one especially designed interferogram (so called complex interferogram) was developed in the past and became known as complex interferometry. Along with the phase shift, which can be also retrieved using classical interferometry, the amplitude modifications of the probing part of the diagnostic beam caused by the object under study (to be called the signal amplitude) as well as the contrast of the interference fringes can be retrieved using the complex interferometry approach. In order to partially compensate for errors in the reconstruction due to imperfections in the diagnostic beam intensity structure as well as for errors caused by a non-ideal optical setup of the interferometer itself (including the quality of its optical components), a reference interferogram can be put to a good use. This method of interferogram analysis of experimental data has been successfully implemented in practice. However, in majority of interferometer setups (especially in the case of the ones employing the wavefront division) the probe and the reference part of the diagnostic beam would feature different intensity distributions over their respective cross sections. This introduces additional error into the reconstruction of the signal amplitude and the fringe contrast, which cannot be resolved using the reference interferogram only. In order to deal with this error it was found that additional separately recorded images of the intensity distribution of the probe and the reference part of the diagnostic beam (with no signal present) are needed. For the best results a sufficient shot-to-shot stability of the whole diagnostic system is required. In this paper, efficiency of the complex interferometry approach for obtaining the highest possible accuracy of the signal amplitude reconstruction is verified using the computer

Linking Genes and Brain Development of Honeybee Workers: A Whole-Transcriptome Approach.

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Christina Vleurinck

Full Text Available Honeybees live in complex societies whose capabilities far exceed those of the sum of their single members. This social synergism is achieved mainly by the worker bees, which form a female caste. The worker bees display diverse collaborative behaviors and engage in different behavioral tasks, which are controlled by the central nervous system (CNS. The development of the worker brain is determined by the female sex and the worker caste determination signal. Here, we report on genes that are controlled by sex or by caste during differentiation of the worker's pupal brain. We sequenced and compared transcriptomes from the pupal brains of honeybee workers, queens and drones. We detected 333 genes that are differently expressed and 519 genes that are differentially spliced between the sexes, and 1760 genes that are differentially expressed and 692 genes that are differentially spliced between castes. We further found that 403 genes are differentially regulated by both the sex and caste signals, providing evidence of the integration of both signals through differential gene regulation. In this gene set, we found that the molecular processes of restructuring the cell shape and cell-to-cell signaling are overrepresented. Our approach identified candidate genes that may be involved in brain differentiation that ensures the various social worker behaviors.

Simulation of Weak Signals of Nanotechnology Innovation in Complex System

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Sun Hi Yoo

2018-02-01

Full Text Available It is especially indispensable for new businesses or industries to predict the innovation of new technologies. This requires an understanding of how the complex process of innovation, which is accomplished through more efficient products, processes, services, technologies, or ideas, is adopted and diffused in the market, government, and society. Furthermore, detecting “weak signals” (signs of change in science and technology (S&T is also important to foretell events associated with innovations in technology. Thus, we explore the dynamic behavior of weak signals of a specific technological innovation using the agent-based simulating tool NetLogo. This study provides a deeper understanding of the early stages of complex technology innovation, and the models are capable of analyzing initial complex interaction structures between components of technologies and between agents engaged in collective invention.

Toll-like receptor 2 signaling in response to brain injury: an innate bridge to neuroinflammation

DEFF Research Database (Denmark)

Babcock, Alicia; Wirenfeldt, Martin; Holm, Thomas

2006-01-01

-mutant mice. Consistent with the fact that responses in knock-out mice had all returned to wild-type levels by 8 d, there was no evidence for effects on neuronal plasticity at 20 d. These results identify a role for TLR2 signaling in the early glial response to brain injury, acting as an innate bridge...

Heart and brain interaction in patients with heart failure: overview and proposal for a taxonomy. A position paper from the Study Group on Heart and Brain Interaction of the Heart Failure Association.

Science.gov (United States)

Doehner, Wolfram; Ural, Dilek; Haeusler, Karl Georg; Čelutkienė, Jelena; Bestetti, Reinaldo; Cavusoglu, Yuksel; Peña-Duque, Marco A; Glavas, Duska; Iacoviello, Massimo; Laufs, Ulrich; Alvear, Ricardo Marmol; Mbakwem, Amam; Piepoli, Massimo F; Rosen, Stuart D; Tsivgoulis, Georgios; Vitale, Cristiana; Yilmaz, M Birhan; Anker, Stefan D; Filippatos, Gerasimos; Seferovic, Petar; Coats, Andrew J S; Ruschitzka, Frank

2018-02-01

Heart failure (HF) is a complex clinical syndrome with multiple interactions between the failing myocardium and cerebral (dys-)functions. Bi-directional feedback interactions between the heart and the brain are inherent in the pathophysiology of HF: (i) the impaired cardiac function affects cerebral structure and functional capacity, and (ii) neuronal signals impact on the cardiovascular continuum. These interactions contribute to the symptomatic presentation of HF patients and affect many co-morbidities of HF. Moreover, neuro-cardiac feedback signals significantly promote aggravation and further progression of HF and are causal in the poor prognosis of HF. The diversity and complexity of heart and brain interactions make it difficult to develop a comprehensive overview. In this paper a systematic approach is proposed to develop a comprehensive atlas of related conditions, signals and disease mechanisms of the interactions between the heart and the brain in HF. The proposed taxonomy is based on pathophysiological principles. Impaired perfusion of the brain may represent one major category, with acute (cardio-embolic) or chronic (haemodynamic failure) low perfusion being sub-categories with mostly different consequences (i.e. ischaemic stroke or cognitive impairment, respectively). Further categories include impairment of higher cortical function (mood, cognition), of brain stem function (sympathetic over-activation, neuro-cardiac reflexes). Treatment-related interactions could be categorized as medical, interventional and device-related interactions. Also interactions due to specific diseases are categorized. A methodical approach to categorize the interdependency of heart and brain may help to integrate individual research areas into an overall picture. © 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.

The application of graph theoretical analysis to complex networks in the brain.

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Reijneveld, Jaap C; Ponten, Sophie C; Berendse, Henk W; Stam, Cornelis J

2007-11-01

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.

Preclinical chorioamnionitis dysregulates CXCL1/CXCR2 signaling throughout the placental-fetal-brain axis.

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Yellowhair, Tracylyn R; Noor, Shahani; Maxwell, Jessie R; Anstine, Christopher V; Oppong, Akosua Y; Robinson, Shenandoah; Milligan, Erin D; Jantzie, Lauren L

2018-03-01

In the United States, perinatal brain injury (PBI) is a major cause of infant mortality and childhood disability. For a large proportion of infants with PBI, central nervous system (CNS) injury begins in utero with inflammation (chorioamnionitis/CHORIO) and/or hypoxia-ischemia. While studies show CHORIO contributes to preterm CNS injury and is also a common independent risk factor for brain injury in term infants, the molecular mechanisms mediating inflammation in the placental-fetal-brain axis that result in PBI remain a gap in knowledge. The chemokine (C-X-C motif) ligand 1 (CXCL1), and its cognate receptor, CXCR2, have been clinically implicated in CHORIO and in mature CNS injury, although their specific role in PBI pathophysiology is poorly defined. Given CXCL1/CXCR2 signaling is essential to neural cell development and neutrophil recruitment, a key pathological hallmark of CHORIO, we hypothesized CHORIO would upregulate CXCL1/CXCR2 expression in the placenta and fetal circulation, concomitant with increased CXCL1/CXCR2 signaling in the developing brain, immune cell activation, neutrophilia, and microstructural PBI. On embryonic day 18 (E18), a laparotomy was performed in pregnant Sprague Dawley rats to induce CHORIO. Specifically, uterine arteries were occluded for 60min to induce placental transient systemic hypoxia-ischemia (TSHI), followed by intra-amniotic injection of lipopolysaccharide (LPS). Pups were born at E22. Placentae, serum and brain were collected along an extended time course from E19 to postnatal day (P)15 and analyzed using multiplex electrochemiluminescence (MECI), Western blot, qPCR, flow cytometry (FC) and diffusion tensor imaging (DTI). Results demonstrate that compared to sham, CHORIO increases placental CXCL1 and CXCR2 mRNA levels, concomitant with increased CXCR2 + neutrophils. Interestingly, pup serum CXCL1 expression in CHORIO parallels this increase, with sustained elevation through P15. Analyses of CHORIO brains reveal similarly

13 reasons why the brain is susceptible to oxidative stress

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James Nathan Cobley

2018-05-01

Full Text Available The human brain consumes 20% of the total basal oxygen (O2 budget to support ATP intensive neuronal activity. Without sufficient O2 to support ATP demands, neuronal activity fails, such that, even transient ischemia is neurodegenerative. While the essentiality of O2 to brain function is clear, how oxidative stress causes neurodegeneration is ambiguous. Ambiguity exists because many of the reasons why the brain is susceptible to oxidative stress remain obscure. Many are erroneously understood as the deleterious result of adventitious O2 derived free radical and non-radical species generation. To understand how many reasons underpin oxidative stress, one must first re-cast free radical and non-radical species in a positive light because their deliberate generation enables the brain to achieve critical functions (e.g. synaptic plasticity through redox signalling (i.e. positive functionality. Using free radicals and non-radical derivatives to signal sensitises the brain to oxidative stress when redox signalling goes awry (i.e. negative functionality. To advance mechanistic understanding, we rationalise 13 reasons why the brain is susceptible to oxidative stress. Key reasons include inter alia unsaturated lipid enrichment, mitochondria, calcium, glutamate, modest antioxidant defence, redox active transition metals and neurotransmitter auto-oxidation. We review RNA oxidation as an underappreciated cause of oxidative stress. The complex interplay between each reason dictates neuronal susceptibility to oxidative stress in a dynamic context and neural identity dependent manner. Our discourse sets the stage for investigators to interrogate the biochemical basis of oxidative stress in the brain in health and disease.

Radionuclide brain imaging in acquired immunodeficiency syndrome (AIDS)

International Nuclear Information System (INIS)

Costa, D.C.; Gacinovic, S.; Miller, R.F.

1995-01-01

Infection with the Human Immunodeficiency Virus type 1 (HIV-1) may produce a variety of central nervous system (CNS) symptoms and signs. CNS involvement in patients with the Acquired Immunodeficiency Syndrome (AIDS) includes AIDS dementia complex or HIV-1 associated cognitive/motor complex (widely known as HIV encephalopathy), progressive multifocal leucoencephalopathy (PML), opportunistic infections such as Toxoplasma gondii, TB, Cryptococcus and infiltration by non-Hodgkin's B cell lymphoma. High resolution structural imaging investigations, either X-ray Computed Tomography (CT scan) or Magnetic Resonance Imaging (MRI) have contributed to the understanding and definition of cerebral damage caused by HIV encephalopathy. Atrophy and mainly high signal scattered white matter abnormalities are commonly seen with MRI. PML produces focal white matter high signal abnormalities due to multiple foci of demyelination. However, using structural imaging techniques there are no reliable parameters to distinguish focal lesions due to opportunistic infection (Toxoplasma gondii abscess) from neoplasm (lymphoma infiltration). It is studied the use of radionuclide brain imaging techniques in the investigation of HIV infected patients. Brain perfusion Single Photon Emission Tomography (SPET), neuroreceptor and Positron Emission Tomography (PET) studies are reviewed. Greater emphasis is put on the potential of some radiopharmaceuticals, considered to be brain tumour markers, to distinguish intracerebral lymphoma infiltration from Toxoplasma infection. SPET with 201 Tl using quantification (tumour to non-tumour radioactivity ratios) appears a very promising technique to identify intracerebral lymphoma

Application of «Sensor signal analysis network» complex for distributed, time synchronized analysis of electromagnetic radiation

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Mochalov, Vladimir; Mochalova, Anastasia

2017-10-01

The paper considers a developing software-hardware complex «Sensor signal analysis network» for distributed and time synchronized analysis of electromagnetic radiations. The areas of application and the main features of the complex are described. An example of application of the complex to monitor natural electromagnetic radiation sources is considered based on the data recorded in VLF range. A generalized functional scheme of stream analysis of signals by a complex functional node is suggested and its application for stream detection of atmospherics, whistlers and tweaks is considered.

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

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Becerra, Lino; Sava, Simona; Simons, Laura E.; Drosos, Athena M.; Sethna, Navil; Berde, Charles; Lebel, Alyssa A.; Borsook, David

2014-01-01

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects. PMID:25379449

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

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Lino Becerra

2014-01-01

Full Text Available Pediatric complex regional pain syndrome (P-CRPS offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning. Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects. These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects.

Binding of Signal Recognition Particle Gives Ribosome/Nascent Chain Complexes a Competitive Advantage in Endoplasmic Reticulum Membrane Interaction

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Neuhof, Andrea; Rolls, Melissa M.; Jungnickel, Berit; Kalies, Kai-Uwe; Rapoport, Tom A.

1998-01-01

Most secretory and membrane proteins are sorted by signal sequences to the endoplasmic reticulum (ER) membrane early during their synthesis. Targeting of the ribosome-nascent chain complex (RNC) involves the binding of the signal sequence to the signal recognition particle (SRP), followed by an interaction of ribosome-bound SRP with the SRP receptor. However, ribosomes can also independently bind to the ER translocation channel formed by the Sec61p complex. To explain the specificity of membrane targeting, it has therefore been proposed that nascent polypeptide-associated complex functions as a cytosolic inhibitor of signal sequence- and SRP-independent ribosome binding to the ER membrane. We report here that SRP-independent binding of RNCs to the ER membrane can occur in the presence of all cytosolic factors, including nascent polypeptide-associated complex. Nontranslating ribosomes competitively inhibit SRP-independent membrane binding of RNCs but have no effect when SRP is bound to the RNCs. The protective effect of SRP against ribosome competition depends on a functional signal sequence in the nascent chain and is also observed with reconstituted proteoliposomes containing only the Sec61p complex and the SRP receptor. We conclude that cytosolic factors do not prevent the membrane binding of ribosomes. Instead, specific ribosome targeting to the Sec61p complex is provided by the binding of SRP to RNCs, followed by an interaction with the SRP receptor, which gives RNC–SRP complexes a selective advantage in membrane targeting over nontranslating ribosomes. PMID:9436994

Long-term music training tunes how the brain temporally binds signals from multiple senses

OpenAIRE

Lee, HweeLing; Noppeney, Uta

2011-01-01

Practicing a musical instrument is a rich multisensory experience involving the integration of visual, auditory, and tactile inputs with motor responses. This combined psychophysics–fMRI study used the musician's brain to investigate how sensory-motor experience molds temporal binding of auditory and visual signals. Behaviorally, musicians exhibited a narrower temporal integration window than nonmusicians for music but not for speech. At the neural level, musicians showed increased audiovisua...

Analysis of structural patterns in the brain with the complex network approach

Science.gov (United States)

Maksimenko, Vladimir A.; Makarov, Vladimir V.; Kharchenko, Alexander A.; Pavlov, Alexey N.; Khramova, Marina V.; Koronovskii, Alexey A.; Hramov, Alexander E.

2015-03-01

In this paper we study mechanisms of the phase synchronization in a model network of Van der Pol oscillators and in the neural network of the brain by consideration of macroscopic parameters of these networks. As the macroscopic characteristics of the model network we consider a summary signal produced by oscillators. Similar to the model simulations, we study EEG signals reflecting the macroscopic dynamics of neural network. We show that the appearance of the phase synchronization leads to an increased peak in the wavelet spectrum related to the dynamics of synchronized oscillators. The observed correlation between the phase relations of individual elements and the macroscopic characteristics of the whole network provides a way to detect phase synchronization in the neural networks in the cases of normal and pathological activity.

Global loss of acetylcholinesterase activity with mitochondrial complexes inhibition and inflammation in brain of hypercholesterolemic mice.

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Paul, Rajib; Borah, Anupom

2017-12-20

There exists an intricate relationship between hypercholesterolemia (elevated plasma cholesterol) and brain functions. The present study aims to understand the impact of hypercholesterolemia on pathological consequences in mouse brain. A chronic mouse model of hypercholesterolemia was induced by giving high-cholesterol diet for 12 weeks. The hypercholesterolemic mice developed cognitive impairment as evident from object recognition memory test. Cholesterol accumulation was observed in four discrete brain regions, such as cortex, striatum, hippocampus and substantia nigra along with significantly damaged blood-brain barrier by hypercholesterolemia. The crucial finding is the loss of acetylcholinesterase activity with mitochondrial dysfunction globally in the brain of hypercholesterolemic mice, which is related to the levels of cholesterol. Moreover, the levels of hydroxyl radical were elevated in the regions of brain where the activity of mitochondrial complexes was found to be reduced. Intriguingly, elevations of inflammatory stress markers in the cholesterol-rich brain regions were observed. As cognitive impairment, diminished brain acetylcholinesterase activity, mitochondrial dysfunctions, and inflammation are the prima facie pathologies of neurodegenerative diseases, the findings impose hypercholesterolemia as potential risk factor towards brain dysfunction.

Quantifying anisotropy and fiber orientation in human brain histological sections

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Matthew D Budde

2013-02-01

Full Text Available Diffusion weighted imaging (DWI has provided unparalleled insight into the microscopic structure and organization of the central nervous system. Diffusion tensor imaging (DTI and other models of the diffusion MRI signal extract microstructural properties of tissues with relevance to the normal and injured brain. Despite the prevalence of such techniques and applications, accurate and large-scale validation has proven difficult, particularly in the human brain. In this report, human brain sections obtained from a digital public brain bank were employed to quantify anisotropy and fiber orientation using structure tensor analysis. The derived maps depict the intricate complexity of white matter fibers at a resolution not attainable with current DWI experiments. Moreover, the effects of multiple fiber bundles (i.e. crossing fibers and intravoxel fiber dispersion were demonstrated. Examination of the cortex and hippocampal regions validated specific features of previous in vivo and ex vivo DTI studies of the human brain. Despite the limitation to two dimensions, the resulting images provide a unique depiction of white matter organization at resolutions currently unattainable with DWI. The method of analysis may be used to validate tissue properties derived from DTI and alternative models of the diffusion signal.

Monoaminergic integration of diet and social signals in the brains of juvenile spadefoot toads.

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Burmeister, Sabrina S; Rodriguez Moncalvo, Verónica G; Pfennig, Karin S

2017-09-01

Social behavior often includes the production of species-specific signals (e.g. mating calls or visual displays) that evoke context-dependent behavioral responses from conspecifics. Monoamines are important neuromodulators that have been implicated in context-dependent social behavior, yet we know little about the development of monoaminergic systems and whether they mediate the effects of early life experiences on adult behavior. We examined the effects of diet and social signals on monoamines early in development in the plains spadefoot toad ( Spea bombifrons ), a species in which diet affects the developmental emergence of species recognition and body condition affects the expression of adult mating preferences. To do so, we manipulated the diet of juveniles for 6 weeks following metamorphosis and collected their brains 40 min following the presentation of either a conspecific or a heterospecific call. We measured levels of monoamines and their metabolites using high pressure liquid chromatography from tissue punches of the auditory midbrain (i.e. torus semicircularis), hypothalamus and preoptic area. We found that call type affected dopamine and noradrenaline signaling in the auditory midbrain and that diet affected dopamine and serotonin in the hypothalamus. In the preoptic area, we detected an interaction between diet and call type, indicating that diet modulates how the preoptic area integrates social information. Our results suggest that the responsiveness of monoamine systems varies across the brain and highlight preoptic dopamine and noradrenaline as candidates for mediating effects of early diet experience on later expression of social preferences. © 2017. Published by The Company of Biologists Ltd.

Calcium Signaling in Taste Cells

Science.gov (United States)

Medler, Kathryn F.

2014-01-01

The sense of taste is a common ability shared by all organisms and is used to detect nutrients as well as potentially harmful compounds. Thus taste is critical to survival. Despite its importance, surprisingly little is known about the mechanisms generating and regulating responses to taste stimuli. All taste responses depend on calcium signals to generate appropriate responses which are relayed to the brain. Some taste cells have conventional synapses and rely on calcium influx through voltage-gated calcium channels. Other taste cells lack these synapses and depend on calcium release to formulate an output signal through a hemichannel. Beyond establishing these characteristics, few studies have focused on understanding how these calcium signals are formed. We identified multiple calcium clearance mechanisms that regulate calcium levels in taste cells as well as a calcium influx that contributes to maintaining appropriate calcium homeostasis in these cells. Multiple factors regulate the evoked taste signals with varying roles in different cell populations. Clearly, calcium signaling is a dynamic process in taste cells and is more complex than has previously been appreciated. PMID:25450977

Steroid Transport, Local Synthesis, and Signaling within the Brain: Roles in Neurogenesis, Neuroprotection, and Sexual Behaviors

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Nicolas Diotel

2018-02-01

Full Text Available Sex steroid hormones are synthesized from cholesterol and exert pleiotropic effects notably in the central nervous system. Pioneering studies from Baulieu and colleagues have suggested that steroids are also locally-synthesized in the brain. Such steroids, called neurosteroids, can rapidly modulate neuronal excitability and functions, brain plasticity, and behavior. Accumulating data obtained on a wide variety of species demonstrate that neurosteroidogenesis is an evolutionary conserved feature across fish, birds, and mammals. In this review, we will first document neurosteroidogenesis and steroid signaling for estrogens, progestagens, and androgens in the brain of teleost fish, birds, and mammals. We will next consider the effects of sex steroids in homeostatic and regenerative neurogenesis, in neuroprotection, and in sexual behaviors. In a last part, we will discuss the transport of steroids and lipoproteins from the periphery within the brain (and vice-versa and document their effects on the blood-brain barrier (BBB permeability and on neuroprotection. We will emphasize the potential interaction between lipoproteins and sex steroids, addressing the beneficial effects of steroids and lipoproteins, particularly HDL-cholesterol, against the breakdown of the BBB reported to occur during brain ischemic stroke. We will consequently highlight the potential anti-inflammatory, anti-oxidant, and neuroprotective properties of sex steroid and lipoproteins, these latest improving cholesterol and steroid ester transport within the brain after insults.

Signaling pathways of interleukin-1 actions in the brain: anatomical distribution of phospho-ERK1/2 in the brain of rat treated systemically with interleukin-1beta.

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Nadjar, A; Combe, C; Busquet, P; Dantzer, R; Parnet, P

2005-01-01

Interleukin-1beta is released at the periphery during infection and acts on the nervous system to induce fever, neuroendocrine activation, and behavioral changes. These effects are mediated by brain type I IL-1 receptors. In vitro studies have shown the ability of interleukin-1beta to activate mitogen-activated protein kinase signaling pathways including p38, c-Jun N-terminal kinase and extracellular signal-regulated protein kinase 1 and 2 (ERK1/2). In contrast to other mitogen-activated protein kinases, little is known about ERK1/2 activation in the rat brain in response to interleukin-1beta. The aim of the present study was therefore to investigate spatial and temporal activation of ERK1/2 in the rat brain after peripheral administration of interleukin-1beta using immunohistochemistry to detect the phosphorylated form of the kinase. In non-stimulated conditions, phosphorylated ERK1/2 immunoreactivity was observed in neurons throughout the brain. Administration of interleukin-1beta (60 microg/kg, i.p.) induced the phosphorylation of ERK1/2 in areas at the interface between brain and blood or cerebrospinal fluid: meninges, circumventricular organs, endothelial like cells of the blood vessels, and in brain nuclei involved in behavioral depression, fever and neuroendocrine activation: paraventricular nucleus of the hypothalamus, supraoptic nucleus, central amygdala and arcuate nucleus. Double labeling of phosphorylated ERK1/2 and cell markers revealed the expression of phosphorylated ERK1/2 in neurons, astrocytes and microglia. Since phosphorylated ERK1/2 was found in structures in which type I IL-1 receptor has already been identified as well as in structures lacking this receptor, activation of ERK1/2 is likely to occur in response to both direct and indirect action of interleukin-1beta on its target cells.

Nitric Oxide Synthase and Cyclooxygenase Pathways: A Complex Interplay in Cellular Signaling.

Science.gov (United States)

Sorokin, Andrey

2016-01-01

The cellular reaction to external challenges is a tightly regulated process consisting of integrated processes mediated by a variety of signaling molecules, generated as a result of modulation of corresponding biosynthetic systems. Both, nitric oxide synthase (NOS) and cyclooxygenase (COX) systems, consist of constitutive forms (NOS1, NOS3 and COX-1), which are mostly involved in housekeeping tasks, and inducible forms (NOS2 and COX-2), which shape the cellular response to stress and variety of bioactive agents. The complex interplay between NOS and COX pathways can be observed at least at three levels. Firstly, products of NOS and Cox systems can mediate the regulation and the expression of inducible forms (NOS2 and COX-2) in response of similar and dissimilar stimulus. Secondly, the reciprocal modulation of cyclooxygenase activity by nitric oxide and NOS activity by prostaglandins at the posttranslational level has been shown to occur. Mechanisms by which nitric oxide can modulate prostaglandin synthesis include direct S-nitrosylation of COX and inactivation of prostaglandin I synthase by peroxynitrite, product of superoxide reaction with nitric oxide. Prostaglandins, conversely, can promote an increased association of dynein light chain (DLC) (also known as protein inhibitor of neuronal nitric oxide synthase) with NOS1, thereby reducing its activity. The third level of interplay is provided by intracellular crosstalk of signaling pathways stimulated by products of NOS and COX which contributes significantly to the complexity of cellular signaling. Since modulation of COX and NOS pathways was shown to be principally involved in a variety of pathological conditions, the dissection of their complex relationship is needed for better understanding of possible therapeutic strategies. This review focuses on implications of interplay between NOS and COX for cellular function and signal integration.

Neuro-Glio-Vascular Complexes of the Brain After Acute Ischemia

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A. S. Stepanov

2017-01-01

Full Text Available The purpose of the study is to compare the structural and functional state of neuro-glio-vascular microstructural complexes of the somatosensory cortex (SSC, CA1 of the hippocampus and amygdala of the brain of white rats under normal conditions and after acute ischemia caused by a 20-minute occlusion of common carotid arteries.Materials and methods. In this experiment, neurons, astrocytes, endotheliocytes, pericytes, basal membrane of the microvessels were studied in the normal (n=5 and the reperfusion period (1, 3, 7, 14, 21 and 30 days, n=30 using electron and fluorescence microscopy (DAPI staining. The morphometric analysis was carried out using the ImageJ 1.46 software.Results. During the recovery period after ischemia was noted reactive (edema-swelling, tinctorial properties of cells and compensatory-restoration (hyperplasia, hypertrophy, proliferation, increased transcytosis changes in neuro-glia-vascular complexes. After ischemia, the number of neurons decreased (by 8.7%—55,3%, and the glial cell count 2—3 fold increased. Increasing neuroglial index (NGI was accompanied by: 1 the emergence of microvessels with numerous branched processes of pericytes, 2 the complication of the spatial organization of basal membranes, and 3 the structural features of activation of transcytosis processes (large number of caveolae, smooth and clathrin vesicles, large vesicles in pericytes and endothelial cells.Conclusion.These findings indicate the compensatory-restoration changes in the components of neuro-gliovascular complexes SSC, CA1 of the hippocampus and amygdala of white rat’s brain after a 20-minute occlusion of the common carotid arteries. The most complete implementation of mechanisms for the protection and repair of damaged neurons occurs in the SSC and amygdala exhibiting high NGI values.

n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals.

Science.gov (United States)

Zaylaa, Amira; Oudjemia, Souad; Charara, Jamal; Girault, Jean-Marc

2015-09-01

This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search for the optimal pattern size that maximized the similarity entropy. The second paradigm was based on the n-order similarity entropy that encompasses the 1-order similarity entropy. To improve the statistical stability, n-order fuzzy similarity entropy was proposed. Fractional Brownian motion was simulated to validate the different methods proposed, and fetal heart rate signals were used to discriminate normal from abnormal fetuses. In all cases, it was found that it was possible to discriminate time series of different complexity such as fractional Brownian motion and fetal heart rate signals. The best levels of performance in terms of sensitivity (90%) and specificity (90%) were obtained with the n-order fuzzy similarity entropy. However, it was shown that the optimal pattern size and the maximum similarity measurement were related to intrinsic features of the time series. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genome-wide analysis of brain and gonad transcripts reveals changes of key sex reversal-related genes expression and signaling pathways in three stages of Monopterus albus.

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Wei Chi

Full Text Available The natural sex reversal severely affects the sex ratio and thus decreases the productivity of the rice field eel (Monopterus albus. How to understand and manipulate this process is one of the major issues for the rice field eel stocking. So far the genomics and transcriptomics data available for this species are still scarce. Here we provide a comprehensive study of transcriptomes of brain and gonad tissue in three sex stages (female, intersex and male from the rice field eel to investigate changes in transcriptional level during the sex reversal process.Approximately 195 thousand unigenes were generated and over 44.4 thousand were functionally annotated. Comparative study between stages provided multiple differentially expressed genes in brain and gonad tissue. Overall 4668 genes were found to be of unequal abundance between gonad tissues, far more than that of the brain tissues (59 genes. These genes were enriched in several different signaling pathways. A number of 231 genes were found with different levels in gonad in each stage, with several reproduction-related genes included. A total of 19 candidate genes that could be most related to sex reversal were screened out, part of these genes' expression patterns were validated by RT-qPCR. The expression of spef2, maats1, spag6 and dmc1 were abundant in testis, but was barely detected in females, while the 17β-hsd12, zpsbp3, gal3 and foxn5 were only expressed in ovary.This study investigated the complexity of brain and gonad transcriptomes in three sex stages of the rice field eel. Integrated analysis of different gene expression and changes in signaling pathways, such as PI3K-Akt pathway, provided crucial data for further study of sex transformation mechanisms.

Sparse coding reveals greater functional connectivity in female brains during naturalistic emotional experience.

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Yudan Ren

Full Text Available Functional neuroimaging is widely used to examine changes in brain function associated with age, gender or neuropsychiatric conditions. FMRI (functional magnetic resonance imaging studies employ either laboratory-designed tasks that engage the brain with abstracted and repeated stimuli, or resting state paradigms with little behavioral constraint. Recently, novel neuroimaging paradigms using naturalistic stimuli are gaining increasing attraction, as they offer an ecologically-valid condition to approximate brain function in real life. Wider application of naturalistic paradigms in exploring individual differences in brain function, however, awaits further advances in statistical methods for modeling dynamic and complex dataset. Here, we developed a novel data-driven strategy that employs group sparse representation to assess gender differences in brain responses during naturalistic emotional experience. Comparing to independent component analysis (ICA, sparse coding algorithm considers the intrinsic sparsity of neural coding and thus could be more suitable in modeling dynamic whole-brain fMRI signals. An online dictionary learning and sparse coding algorithm was applied to the aggregated fMRI signals from both groups, which was subsequently factorized into a common time series signal dictionary matrix and the associated weight coefficient matrix. Our results demonstrate that group sparse representation can effectively identify gender differences in functional brain network during natural viewing, with improved sensitivity and reliability over ICA-based method. Group sparse representation hence offers a superior data-driven strategy for examining brain function during naturalistic conditions, with great potential for clinical application in neuropsychiatric disorders.

Brain-computer interfaces in neurological rehabilitation.

Science.gov (United States)

Daly, Janis J; Wolpaw, Jonathan R

2008-11-01

Recent advances in analysis of brain signals, training patients to control these signals, and improved computing capabilities have enabled people with severe motor disabilities to use their brain signals for communication and control of objects in their environment, thereby bypassing their impaired neuromuscular system. Non-invasive, electroencephalogram (EEG)-based brain-computer interface (BCI) technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment. By re-establishing some independence, BCI technologies can substantially improve the lives of people with devastating neurological disorders such as advanced amyotrophic lateral sclerosis. BCI technology might also restore more effective motor control to people after stroke or other traumatic brain disorders by helping to guide activity-dependent brain plasticity by use of EEG brain signals to indicate to the patient the current state of brain activity and to enable the user to subsequently lower abnormal activity. Alternatively, by use of brain signals to supplement impaired muscle control, BCIs might increase the efficacy of a rehabilitation protocol and thus improve muscle control for the patient.

Wireless brain-machine interface using EEG and EOG: brain wave classification and robot control

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Oh, Sechang; Kumar, Prashanth S.; Kwon, Hyeokjun; Varadan, Vijay K.

2012-04-01

A brain-machine interface (BMI) links a user's brain activity directly to an external device. It enables a person to control devices using only thought. Hence, it has gained significant interest in the design of assistive devices and systems for people with disabilities. In addition, BMI has also been proposed to replace humans with robots in the performance of dangerous tasks like explosives handling/diffusing, hazardous materials handling, fire fighting etc. There are mainly two types of BMI based on the measurement method of brain activity; invasive and non-invasive. Invasive BMI can provide pristine signals but it is expensive and surgery may lead to undesirable side effects. Recent advances in non-invasive BMI have opened the possibility of generating robust control signals from noisy brain activity signals like EEG and EOG. A practical implementation of a non-invasive BMI such as robot control requires: acquisition of brain signals with a robust wearable unit, noise filtering and signal processing, identification and extraction of relevant brain wave features and finally, an algorithm to determine control signals based on the wave features. In this work, we developed a wireless brain-machine interface with a small platform and established a BMI that can be used to control the movement of a robot by using the extracted features of the EEG and EOG signals. The system records and classifies EEG as alpha, beta, delta, and theta waves. The classified brain waves are then used to define the level of attention. The acceleration and deceleration or stopping of the robot is controlled based on the attention level of the wearer. In addition, the left and right movements of eye ball control the direction of the robot.

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

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Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Comparison of GFL–GFRα complexes: further evidence relating GFL bend angle to RET signalling

International Nuclear Information System (INIS)

Parkash, Vimal; Goldman, Adrian

2009-01-01

The second crystal structure of the GDNF-GFRα1 complex provides further evidence that GFL signalling through RET is determined by the bend angle in the GFL. Glial cell line-derived neurotrophic factor (GDNF) activates the receptor tyrosine kinase RET by binding to the GDNF-family receptor α1 (GFRα1) and forming the GDNF 2 –GFRα1 2 –RET 2 heterohexamer complex. A previous crystal structure of the GDNF 2 –GFRα1 2 complex suggested that differences in signalling in GDNF-family ligand (GFL) complexes might arise from differences in the bend angle between the two monomers in the GFL homodimer. Here, a 2.35 Å resolution structure of the GDNF 2 –GFRα1 2 complex crystallized with new cell dimensions is reported. The structure was refined to a final R factor of 22.5% (R free = 28%). The structures of both biological tetrameric complexes in the asymmetric unit are very similar to 2v5e and different from the artemin–GFRα3 structure, even though there is a small change in the structure of the GDNF. By comparison of all known GDNF and artemin structures, it is concluded that GDNF is more bent and more flexible than artemin and that this may be related to RET signalling. Comparisons also suggest that the differences between artemin and GDNF arise from the increased curvature of the artemin ‘fingers’, which both increases the buried surface area in the monomer–monomer interface and changes the intermonomer bend angle. From sequence comparison, it is suggested that neuturin (the second GFL) adopts an artemin-like conformation, while persephin has a different conformation to the other three

Microbiome-Derived Lipopolysaccharide Enriched in the Perinuclear Region of Alzheimer’s Disease Brain

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Yuhai Zhao

2017-09-01

Full Text Available Abundant clinical, epidemiological, imaging, genetic, molecular, and pathophysiological data together indicate that there occur an unusual inflammatory reaction and a disruption of the innate-immune signaling system in Alzheimer’s disease (AD brain. Despite many years of intense study, the origin and molecular mechanics of these AD-relevant pathogenic signals are still not well understood. Here, we provide evidence that an intensely pro-inflammatory bacterial lipopolysaccharide (LPS, part of a complex mixture of pro-inflammatory neurotoxins arising from abundant Gram-negative bacilli of the human gastrointestinal (GI tract, are abundant in AD-affected brain neocortex and hippocampus. For the first time, we provide evidence that LPS immunohistochemical signals appear to aggregate in clumps in the parenchyma in control brains, and in AD, about 75% of anti-LPS signals were clustered around the periphery of DAPI-stained nuclei. As LPS is an abundant secretory product of Gram-negative bacilli resident in the human GI-tract, these observations suggest (i that a major source of pro-inflammatory signals in AD brain may originate from internally derived noxious exudates of the GI-tract microbiome; (ii that due to aging, vascular deficits or degenerative disease these neurotoxic molecules may “leak” into the systemic circulation, cerebral vasculature, and on into the brain; and (iii that this internal source of microbiome-derived neurotoxins may play a particularly strong role in shaping the human immune system and contributing to neural degeneration, particularly in the aging CNS. This “Perspectives” paper will further highlight some very recent developments that implicate GI-tract microbiome-derived LPS as an important contributor to inflammatory-neurodegeneration in the AD brain.

Brain signaling and behavioral responses induced by exposure to (56)Fe-particle radiation

Science.gov (United States)

Denisova, N. A.; Shukitt-Hale, B.; Rabin, B. M.; Joseph, J. A.

2002-01-01

Previous experiments have demonstrated that exposure to 56Fe-particle irradiation (1.5 Gy, 1 GeV) produced aging-like accelerations in neuronal and behavioral deficits. Astronauts on long-term space flights will be exposed to similar heavy-particle radiations that might have similar deleterious effects on neuronal signaling and cognitive behavior. Therefore, the present study evaluated whether radiation-induced spatial learning and memory behavioral deficits are associated with region-specific brain signaling deficits by measuring signaling molecules previously found to be essential for behavior [pre-synaptic vesicle proteins, synaptobrevin and synaptophysin, and protein kinases, calcium-dependent PRKCs (also known as PKCs) and PRKA (PRKA RIIbeta)]. The results demonstrated a significant radiation-induced increase in reference memory errors. The increases in reference memory errors were significantly negatively correlated with striatal synaptobrevin and frontal cortical synaptophysin expression. Both synaptophysin and synaptobrevin are synaptic vesicle proteins that are important in cognition. Striatal PRKA, a memory signaling molecule, was also significantly negatively correlated with reference memory errors. Overall, our findings suggest that radiation-induced pre-synaptic facilitation may contribute to some previously reported radiation-induced decrease in striatal dopamine release and for the disruption of the central dopaminergic system integrity and dopamine-mediated behavior.

Stochastic effects as a force to increase the complexity of signaling networks

KAUST Repository

Kuwahara, Hiroyuki

2013-07-29

Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.

Discrimination of Rock Fracture and Blast Events Based on Signal Complexity and Machine Learning

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Zilong Zhou

2018-01-01

Full Text Available The automatic discrimination of rock fracture and blast events is complex and challenging due to the similar waveform characteristics. To solve this problem, a new method based on the signal complexity analysis and machine learning has been proposed in this paper. First, the permutation entropy values of signals at different scale factors are calculated to reflect complexity of signals and constructed into a feature vector set. Secondly, based on the feature vector set, back-propagation neural network (BPNN as a means of machine learning is applied to establish a discriminator for rock fracture and blast events. Then to evaluate the classification performances of the new method, the classifying accuracies of support vector machine (SVM, naive Bayes classifier, and the new method are compared, and the receiver operating characteristic (ROC curves are also analyzed. The results show the new method obtains the best classification performances. In addition, the influence of different scale factor q and number of training samples n on discrimination results is discussed. It is found that the classifying accuracy of the new method reaches the highest value when q = 8–15 or 8–20 and n=140.

Short- and long-term modulation of synaptic inputs to brain reward areas by nicotine

NARCIS (Netherlands)

Fagen, Z.M.; Mansvelder, H.D.; Keath, R.; McGehee, D.S.

2003-01-01

Dopamine signaling in brain reward areas is a key element in the development of drug abuse and dependence. Recent anatomical and electrophysiological research has begun to elucidate both complexity and specificity In synaptic connections between ventral tegmental neurons and their inputs.

The role of mitochondrial ROS in the aging brain.

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Stefanatos, Rhoda; Sanz, Alberto

2018-03-01

The brain is the most complex human organ, consuming more energy than any other tissue in proportion to its size. It relies heavily on mitochondria to produce energy and is made up of mitotic and postmitotic cells that need to closely coordinate their metabolism to maintain essential bodily functions. During aging, damaged mitochondria that produce less ATP and more reactive oxygen species (ROS) accumulate. The current consensus is that ROS cause oxidative stress, damaging mitochondria and resulting in an energetic crisis that triggers neurodegenerative diseases and accelerates aging. However, in model organisms, increasing mitochondrial ROS (mtROS) in the brain extends lifespan, suggesting that ROS may participate in signaling that protects the brain. Here, we summarize the mechanisms by which mtROS are produced at the molecular level, how different brain cells and regions produce different amounts of mtROS, and how mtROS levels change during aging. Finally, we critically discuss the possible roles of ROS in aging as signaling molecules and damaging agents, addressing whether age-associated increases in mtROS are a cause or a consequence of aging. © 2017 Federation of European Biochemical Societies.

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

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Dong-Sup Lee

2015-01-01

Full Text Available Independent Component Analysis (ICA, one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Anti-Inflammatory Effects of Omega-3 Fatty Acids in the Brain: Physiological Mechanisms and Relevance to Pharmacology.

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Layé, Sophie; Nadjar, Agnès; Joffre, Corinne; Bazinet, Richard P

2018-01-01

Classically, polyunsaturated fatty acids (PUFA) were largely thought to be relatively inert structural components of brain, largely important for the formation of cellular membranes. Over the past 10 years, a host of bioactive lipid mediators that are enzymatically derived from arachidonic acid, the main n-6 PUFA, and docosahexaenoic acid, the main n-3 PUFA in the brain, known to regulate peripheral immune function, have been detected in the brain and shown to regulate microglia activation. Recent advances have focused on how PUFA regulate the molecular signaling of microglia, especially in the context of neuroinflammation and behavior. Several active drugs regulate brain lipid signaling and provide proof of concept for targeting the brain. Because brain lipid metabolism relies on a complex integration of diet, peripheral metabolism, including the liver and blood, which supply the brain with PUFAs that can be altered by genetics, sex, and aging, there are many pathways that can be disrupted, leading to altered brain lipid homeostasis. Brain lipid signaling pathways are altered in neurologic disorders and may be viable targets for the development of novel therapeutics. In this study, we discuss in particular how n-3 PUFAs and their metabolites regulate microglia phenotype and function to exert their anti-inflammatory and proresolving activities in the brain. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

Complex Interplay of Hormonal Signals during Grape Berry Ripening

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Ana Margarida Fortes

2015-05-01

Full Text Available Grape and wine production and quality is extremely dependent on the fruit ripening process. Sensory and nutritional characteristics are important aspects for consumers and their development during fruit ripening involves complex hormonal control. In this review, we explored data already published on grape ripening and compared it with the hormonal regulation of ripening of other climacteric and non-climacteric fruits. The roles of abscisic acid, ethylene, and brassinosteroids as promoters of ripening are discussed, as well as the role of auxins, cytokinins, gibberellins, jasmonates, and polyamines as inhibitors of ripening. In particular, the recently described role of polyamine catabolism in grape ripening is discussed, together with its putative interaction with other hormones. Furthermore, other recent examples of cross-talk among the different hormones are presented, revealing a complex interplay of signals during grape development and ripening.

Persistency and flexibility of complex brain networks underlie dual-task interference.

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Alavash, Mohsen; Hilgetag, Claus C; Thiel, Christiane M; Gießing, Carsten

2015-09-01

Previous studies on multitasking suggest that performance decline during concurrent task processing arises from interfering brain modules. Here, we used graph-theoretical network analysis to define functional brain modules and relate the modular organization of complex brain networks to behavioral dual-task costs. Based on resting-state and task fMRI we explored two organizational aspects potentially associated with behavioral interference when human subjects performed a visuospatial and speech task simultaneously: the topological overlap between persistent single-task modules, and the flexibility of single-task modules in adaptation to the dual-task condition. Participants showed a significant decline in visuospatial accuracy in the dual-task compared with single visuospatial task. Global analysis of topological similarity between modules revealed that the overlap between single-task modules significantly correlated with the decline in visuospatial accuracy. Subjects with larger overlap between single-task modules showed higher behavioral interference. Furthermore, lower flexible reconfiguration of single-task modules in adaptation to the dual-task condition significantly correlated with larger decline in visuospatial accuracy. Subjects with lower modular flexibility showed higher behavioral interference. At the regional level, higher overlap between single-task modules and less modular flexibility in the somatomotor cortex positively correlated with the decline in visuospatial accuracy. Additionally, higher modular flexibility in cingulate and frontal control areas and lower flexibility in right-lateralized nodes comprising the middle occipital and superior temporal gyri supported dual-tasking. Our results suggest that persistency and flexibility of brain modules are important determinants of dual-task costs. We conclude that efficient dual-tasking benefits from a specific balance between flexibility and rigidity of functional brain modules. © 2015 Wiley

Oxytocin: parallel processing in the social brain?

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Dölen, Gül

2015-06-01

Early studies attempting to disentangle the network complexity of the brain exploited the accessibility of sensory receptive fields to reveal circuits made up of synapses connected both in series and in parallel. More recently, extension of this organisational principle beyond the sensory systems has been made possible by the advent of modern molecular, viral and optogenetic approaches. Here, evidence supporting parallel processing of social behaviours mediated by oxytocin is reviewed. Understanding oxytocinergic signalling from this perspective has significant implications for the design of oxytocin-based therapeutic interventions aimed at disorders such as autism, where disrupted social function is a core clinical feature. Moreover, identification of opportunities for novel technology development will require a better appreciation of the complexity of the circuit-level organisation of the social brain. © 2015 The Authors. Journal of Neuroendocrinology published by John Wiley & Sons Ltd on behalf of British Society for Neuroendocrinology.

β-Catenin destruction complex-independent regulation of Hippo–YAP signaling by APC in intestinal tumorigenesis

Science.gov (United States)

Cai, Jing; Maitra, Anirban; Anders, Robert A.; Taketo, Makoto M.; Pan, Duojia

2015-01-01

Mutations in Adenomatous polyposis coli (APC) underlie familial adenomatous polyposis (FAP), an inherited cancer syndrome characterized by the widespread development of colorectal polyps. APC is best known as a scaffold protein in the β-catenin destruction complex, whose activity is antagonized by canonical Wnt signaling. Whether other effector pathways mediate APC's tumor suppressor function is less clear. Here we report that activation of YAP, the downstream effector of the Hippo signaling pathway, is a general hallmark of tubular adenomas from FAP patients. We show that APC functions as a scaffold protein that facilitates the Hippo kinase cascade by interacting with Sav1 and Lats1. Consistent with the molecular link between APC and the Hippo signaling pathway, genetic analysis reveals that YAP is absolutely required for the development of APC-deficient adenomas. These findings establish Hippo–YAP signaling as a critical effector pathway downstream from APC, independent from its involvement in the β-catenin destruction complex. PMID:26193883

Neurotrophin Signaling via TrkB and TrkC Receptors Promotes the Growth of Brain Tumor-initiating Cells*

Science.gov (United States)

Lawn, Samuel; Krishna, Niveditha; Pisklakova, Alexandra; Qu, Xiaotao; Fenstermacher, David A.; Fournier, Michelle; Vrionis, Frank D.; Tran, Nam; Chan, Jennifer A.; Kenchappa, Rajappa S.; Forsyth, Peter A.

2015-01-01

Neurotrophins and their receptors are frequently expressed in malignant gliomas, yet their functions are largely unknown. Previously, we have shown that p75 neurotrophin receptor is required for glioma invasion and proliferation. However, the role of Trk receptors has not been examined. In this study, we investigated the importance of TrkB and TrkC in survival of brain tumor-initiating cells (BTICs). Here, we show that human malignant glioma tissues and also tumor-initiating cells isolated from fresh human malignant gliomas express the neurotrophin receptors TrkB and TrkC, not TrkA, and they also express neurotrophins NGF, BDNF, and neurotrophin 3 (NT3). Specific activation of TrkB and TrkC receptors by ligands BDNF and NT3 enhances tumor-initiating cell viability through activation of ERK and Akt pathways. Conversely, TrkB and TrkC knockdown or pharmacologic inhibition of Trk signaling decreases neurotrophin-dependent ERK activation and BTIC growth. Further, pharmacological inhibition of both ERK and Akt pathways blocked BDNF, and NT3 stimulated BTIC survival. Importantly, attenuation of BTIC growth by EGFR inhibitors could be overcome by activation of neurotrophin signaling, and neurotrophin signaling is sufficient for long term BTIC growth as spheres in the absence of EGF and FGF. Our results highlight a novel role for neurotrophin signaling in brain tumor and suggest that Trks could be a target for combinatorial treatment of malignant glioma. PMID:25538243

Neurotrophin signaling via TrkB and TrkC receptors promotes the growth of brain tumor-initiating cells.

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Lawn, Samuel; Krishna, Niveditha; Pisklakova, Alexandra; Qu, Xiaotao; Fenstermacher, David A; Fournier, Michelle; Vrionis, Frank D; Tran, Nam; Chan, Jennifer A; Kenchappa, Rajappa S; Forsyth, Peter A

2015-02-06

Neurotrophins and their receptors are frequently expressed in malignant gliomas, yet their functions are largely unknown. Previously, we have shown that p75 neurotrophin receptor is required for glioma invasion and proliferation. However, the role of Trk receptors has not been examined. In this study, we investigated the importance of TrkB and TrkC in survival of brain tumor-initiating cells (BTICs). Here, we show that human malignant glioma tissues and also tumor-initiating cells isolated from fresh human malignant gliomas express the neurotrophin receptors TrkB and TrkC, not TrkA, and they also express neurotrophins NGF, BDNF, and neurotrophin 3 (NT3). Specific activation of TrkB and TrkC receptors by ligands BDNF and NT3 enhances tumor-initiating cell viability through activation of ERK and Akt pathways. Conversely, TrkB and TrkC knockdown or pharmacologic inhibition of Trk signaling decreases neurotrophin-dependent ERK activation and BTIC growth. Further, pharmacological inhibition of both ERK and Akt pathways blocked BDNF, and NT3 stimulated BTIC survival. Importantly, attenuation of BTIC growth by EGFR inhibitors could be overcome by activation of neurotrophin signaling, and neurotrophin signaling is sufficient for long term BTIC growth as spheres in the absence of EGF and FGF. Our results highlight a novel role for neurotrophin signaling in brain tumor and suggest that Trks could be a target for combinatorial treatment of malignant glioma. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Oxidative stress and expression of insulin signaling proteins in the brain of diabetic rats: Role of Nigella sativa oil and antidiabetic drugs.

Science.gov (United States)

Balbaa, Mahmoud; Abdulmalek, Shaymaa A; Khalil, Sofia

2017-01-01

Insulin resistance of the brain is a specific form of type2-diabetes mellitus (T2DM) and the active insulin-signaling pathway plays a neuroprotective role against damaging conditions and Alzheimer's progression. The present study identifies the mediated emerging effects of the Nigella sativa oil (NSO) on the memory enhancing process, its anti-oxidative, acetylcholinestrase (AChE) inhibition, anti-brain insulin resistance and anti-amyloidogenic activities. In addition, the possible role of some anti-diabetic drugs in the neuro-protection processes and their effect in combination with NSO and/or the insulin receptor inhibitor IOMe-AG538 were investigated. T2DM-induced rats were orally and daily administrated 2.0 ml NSO, 100 mg metformin (MT), 0.8 mg glimepiride (GI) and different combinations (100 mg MT & 2.0 ml NSO, 0.8 mg GI & 2.0 ml NSO and 2.0 ml NSO & intraperitoneal injection of 1/100 LD50 of IOMe-AG538) per kg body weight for 21 days. A significant increase in the brain lipid peroxidation and decrease in the antioxidant status with peripheral and central production of pro-inflammatory mediators were observed in diabetes-induced rats. The brain AChE was activated and associated with diminished brain glucose level and cholinergic function. In addition, the brain insulin resistance and the attenuated insulin signaling pathway (p-IRS/ p-AKT/p-GSK-3β) were accompanied by an augmentation in GSK-3β level, which in turn may contribute in the extensive alterations of Tau phosphorylation along with changes in PP2A level. Furthermore, neuronal loss and elevation in Aβ-42 plaque formation were observed due to a low IDE formation and an increased expression of p53, BACE1 and APP with diminished ADAM10, SIRT1 and BDNF levels. The expression profile of AD-related miRNAs in sera and brain tissues displayed its neuro-protection role. The treatment of diabetes-induced rats with NSO and the anti-diabetic drugs alone and/or in combination have the potential to suppress the

MRI of the normal brain from early childhood to middle age. Pt. 2. Age dependence of signal intensity changes on T2-weighted images

International Nuclear Information System (INIS)

Autti, T.; Raininko, R.; Vanhanen, S.L.; Kallio, M.; Santavuori, P.

1994-01-01

We examined 66 healthy volunteers aged 4 to 50 years by magnetic resonance imaging (MRI) and the signal intensity was measured on T2-weighted images in numerous sites and correlated with age and sex. Using distilled water and cerebrospinal fluid (CSF) as references on each slice, we calculated the signal intensities of the brain structures. Calculated ratios between structures did not change with age, except for those of the globus pallidus and thalamus, in which the signal intensities decreased more rapidly. The signal intensities of other brain structures changed equally but this could not be discerned visually and quantitative measurements were required. The signal intensities in the white and deep grey matter decreased rapidly in the first decade and then gradually to reach a plateau after the age of 18 years. Maturation of the brain thus seems to continue until near the end of the second decade of life. No sex differences were found. Quantitative analysis requires intensity references. The CSF in the tips of the frontal horns seems to be as reliable as an external fluid reference for intensity, and can be used in routine examinations provided the frontal horns are large enough to avoid partial volume effect. (orig.)

Absence of Doppler signal in transcranial color-coded ultrasonography may be confirmatory for brain death: A case report

Directory of Open Access Journals (Sweden)

Mehmet Akif Topçuoğlu

2015-08-01

Full Text Available Transcranial Doppler ultrasonography (TCD is a valuable tool for demonstrating cerebral circulatory arrest (CCA in the setting of brain death. Complete reversal of diastolic flow (to-and-fro flow and systolic spikes in bilateral terminal internal carotid arteries and vertebrobasilar circulation are considered as specific sonogram configurations supporting the diagnosis of CCA. Because of the possibility of sonic bone window impermeability, absence of any waveform in TCD is not confirmatory for CCA unless there is documentation of disappearance of a previously well detected signal by the same recording settings. Transcranial color-coded sonography (TCCS with B-mode imaging can reliably detect adequacy of bone windows with clarity contralateral skull and ipsilateral planum temporale visualization. Therefore, absence of detectable intracranial Doppler signal along with available ultrasound window in TCCS can confirm clinical diagnosis of brain death. We herein discuss this entity from the frame of a representative case.

Optimal search strategies on complex networks

OpenAIRE

Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

2014-01-01

Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanism...

Fuzzy approximate entropy analysis of chaotic and natural complex systems: detecting muscle fatigue using electromyography signals.

Science.gov (United States)

Xie, Hong-Bo; Guo, Jing-Yi; Zheng, Yong-Ping

2010-04-01

In the present contribution, a complexity measure is proposed to assess surface electromyography (EMG) in the study of muscle fatigue during sustained, isometric muscle contractions. Approximate entropy (ApEn) is believed to provide quantitative information about the complexity of experimental data that is often corrupted with noise, short data length, and in many cases, has inherent dynamics that exhibit both deterministic and stochastic behaviors. We developed an improved ApEn measure, i.e., fuzzy approximate entropy (fApEn), which utilizes the fuzzy membership function to define the vectors' similarity. Tests were conducted on independent, identically distributed (i.i.d.) Gaussian and uniform noises, a chirp signal, MIX processes, Rossler equation, and Henon map. Compared with the standard ApEn, the fApEn showed better monotonicity, relative consistency, and more robustness to noise when characterizing signals with different complexities. Performance analysis on experimental EMG signals demonstrated that the fApEn significantly decreased during the development of muscle fatigue, which is a similar trend to that of the mean frequency (MNF) of the EMG signal, while the standard ApEn failed to detect this change. Moreover, fApEn of EMG demonstrated a better robustness to the length of the analysis window in comparison with the MNF of EMG. The results suggest that the fApEn of an EMG signal may potentially become a new reliable method for muscle fatigue assessment and be applicable to other short noisy physiological signal analysis.

The Blood-Brain Barrier: An Engineering Perspective

Directory of Open Access Journals (Sweden)

Andrew eWong

2013-08-01

Full Text Available It has been more than 100 years since Paul Ehrlich reported that various water-soluble dyes injected into the circulation did not enter the brain. Since Ehrlich’s first experiments, only a small number of molecules, such as alcohol and caffeine have been found to cross the blood-brain barrier, and it remains the major roadblock to treatment of many central nervous system diseases. At the same time, many central nervous system diseases are associated with disruption of the blood-brain barrier that can lead to changes in permeability, modulation of immune cell transport, and trafficking of pathogens into the brain. Therefore advances in our understanding of the structure and function of the blood-brain barrier are key to advances in treatment of a wide range of central nervous system diseases. Over the past 10 years it has become recognized that the blood-brain barrier is a complex dynamic system that involves biomechanical and biochemical signaling between the vascular system and the brain. Here we reconstruct the structure, function, and transport properties of the blood-brain barrier from an engineering perspective. New insight into the physics of the blood-brain barrier could ultimately lead to clinical advances in the treatment of central nervous system diseases.

Videogame training strategy-induced change in brain function during a complex visuomotor task.

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Lee, Hyunkyu; Voss, Michelle W; Prakash, Ruchika Shaurya; Boot, Walter R; Vo, Loan T K; Basak, Chandramallika; Vanpatter, Matt; Gratton, Gabriele; Fabiani, Monica; Kramer, Arthur F

2012-07-01

Although changes in brain function induced by cognitive training have been examined, functional plasticity associated with specific training strategies is still relatively unexplored. In this study, we examined changes in brain function during a complex visuomotor task following training using the Space Fortress video game. To assess brain function, participants completed functional magnetic resonance imaging (fMRI) before and after 30 h of training with one of two training regimens: Hybrid Variable-Priority Training (HVT), with a focus on improving specific skills and managing task priority, or Full Emphasis Training (FET), in which participants simply practiced the game to obtain the highest overall score. Control participants received only 6 h of FET. Compared to FET, HVT learners reached higher performance on the game and showed less brain activation in areas related to visuo-spatial attention and goal-directed movement after training. Compared to the control group, HVT exhibited less brain activation in right dorsolateral prefrontal cortex (DLPFC), coupled with greater performance improvement. Region-of-interest analysis revealed that the reduction in brain activation was correlated with improved performance on the task. This study sheds light on the neurobiological mechanisms of improved learning from directed training (HVT) over non-directed training (FET), which is related to visuo-spatial attention and goal-directed motor planning, while separating the practice-based benefit, which is related to executive control and rule management. Copyright © 2012 Elsevier B.V. All rights reserved.

Assembly of Slx4 signaling complexes behind DNA replication forks.

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Balint, Attila; Kim, TaeHyung; Gallo, David; Cussiol, Jose Renato; Bastos de Oliveira, Francisco M; Yimit, Askar; Ou, Jiongwen; Nakato, Ryuichiro; Gurevich, Alexey; Shirahige, Katsuhiko; Smolka, Marcus B; Zhang, Zhaolei; Brown, Grant W

2015-08-13

Obstructions to replication fork progression, referred to collectively as DNA replication stress, challenge genome stability. In Saccharomyces cerevisiae, cells lacking RTT107 or SLX4 show genome instability and sensitivity to DNA replication stress and are defective in the completion of DNA replication during recovery from replication stress. We demonstrate that Slx4 is recruited to chromatin behind stressed replication forks, in a region that is spatially distinct from that occupied by the replication machinery. Slx4 complex formation is nucleated by Mec1 phosphorylation of histone H2A, which is recognized by the constitutive Slx4 binding partner Rtt107. Slx4 is essential for recruiting the Mec1 activator Dpb11 behind stressed replication forks, and Slx4 complexes are important for full activity of Mec1. We propose that Slx4 complexes promote robust checkpoint signaling by Mec1 by stably recruiting Dpb11 within a discrete domain behind the replication fork, during DNA replication stress. © 2015 The Authors.

Kurtosis based blind source extraction of complex noncircular signals with application in EEG artifact removal in real-time

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Soroush eJavidi

2011-10-01

Full Text Available A new class of complex domain blind source extraction (BSE algorithms suitable for the extraction of both circular and noncircular complex signals is proposed. This is achieved through sequential extraction based on the degree of kurtosis and in the presence of noncircular measurement noise. The existence and uniqueness analysis of the solution is followed by a study of fast converging variants of the algorithm. The performance is first assessed through simulations on well understood benchmark signals, followed by a case study on real-time artifact removal from EEG signals, verified using both qualitative and quantitative metrics. The results illustrate the power of the proposed approach in real-time blind extraction of general complex-valued sources.

Ethylene Regulates Levels of Ethylene Receptor/CTR1 Signaling Complexes in Arabidopsis thaliana*

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Shakeel, Samina N.; Gao, Zhiyong; Amir, Madiha; Chen, Yi-Feng; Rai, Muneeza Iqbal; Haq, Noor Ul; Schaller, G. Eric

2015-01-01

The plant hormone ethylene is perceived by a five-member family of receptors in Arabidopsis thaliana. The receptors function in conjunction with the Raf-like kinase CTR1 to negatively regulate ethylene signal transduction. CTR1 interacts with multiple members of the receptor family based on co-purification analysis, interacting more strongly with receptors containing a receiver domain. Levels of membrane-associated CTR1 vary in response to ethylene, doing so in a post-transcriptional manner that correlates with ethylene-mediated changes in levels of the ethylene receptors ERS1, ERS2, EIN4, and ETR2. Interactions between CTR1 and the receptor ETR1 protect ETR1 from ethylene-induced turnover. Kinetic and dose-response analyses support a model in which two opposing factors control levels of the ethylene receptor/CTR1 complexes. Ethylene stimulates the production of new complexes largely through transcriptional induction of the receptors. However, ethylene also induces turnover of receptors, such that levels of ethylene receptor/CTR1 complexes decrease at higher ethylene concentrations. Implications of this model for ethylene signaling are discussed. PMID:25814663

Normalization of informatisation parameter on airfield light-signal bar at flights in complex meteorological conditions

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П.В. Попов

2005-03-01

Full Text Available  The technique of maintenance of the set level of flights safetivness is developed by normalization of informatisation parameters functional groups of light-signal lightings at technological stages of interaction of crew of the airplane with the airfield light-signals bar at flights in a complex weathercast conditions.

Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.

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McFarland, Dennis J; Krusienski, Dean J; Wolpaw, Jonathan R

2006-01-01

The Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.

Investigating long-range correlation properties in EEG during complex cognitive tasks

International Nuclear Information System (INIS)

Karkare, Siddharth; Saha, Goutam; Bhattacharya, Joydeep

2009-01-01

Previous work shows the presence of scale invariance and long-range correlations in ongoing and spontaneous activity of large scale brain responses (i.e. EEG), and such scaling behavior can also be modulated by simple sensory stimulus. However, little is known whether such alteration but not destruction in scaling properties also occurs during complex cognitive processing and if neuroplasticity plays any role in mediating such changes. In this study, we addressed these issues by investigating scaling properties of multivariate EEG signals obtained from two broad groups - artists and non-artists - while they performed complex tasks of perception and mental imagery of visual art objects. We found that brain regions showing increased correlation properties from rest were similar for both tasks, suggesting that brain networks responsible for visual perception are reactivated for mental imagery. Further, we observed that the two groups could be differentiated by scaling exponents and an artificial neural network based classifier achieved a classification efficiency of over 80%. These results altogether suggest that specific complex cognitive task demands and task-specific expertise can modify the temporal scale-free dynamics of brain responses.

Investigating long-range correlation properties in EEG during complex cognitive tasks

Energy Technology Data Exchange (ETDEWEB)

Karkare, Siddharth [Department of Electrical Engineering, Indian Institute of Technology, Kharagpur 721302 (India); Saha, Goutam [Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur 721302 (India); Bhattacharya, Joydeep [Department of Psychology, Goldsmiths College, University of London, New Cross, London SE14 6NW (United Kingdom); Commission for Scientific Visualization, Austrian Academy of Sciences, Vienna A1220 (Austria)], E-mail: j.bhattacharya@gold.ac.uk

2009-11-30

Previous work shows the presence of scale invariance and long-range correlations in ongoing and spontaneous activity of large scale brain responses (i.e. EEG), and such scaling behavior can also be modulated by simple sensory stimulus. However, little is known whether such alteration but not destruction in scaling properties also occurs during complex cognitive processing and if neuroplasticity plays any role in mediating such changes. In this study, we addressed these issues by investigating scaling properties of multivariate EEG signals obtained from two broad groups - artists and non-artists - while they performed complex tasks of perception and mental imagery of visual art objects. We found that brain regions showing increased correlation properties from rest were similar for both tasks, suggesting that brain networks responsible for visual perception are reactivated for mental imagery. Further, we observed that the two groups could be differentiated by scaling exponents and an artificial neural network based classifier achieved a classification efficiency of over 80%. These results altogether suggest that specific complex cognitive task demands and task-specific expertise can modify the temporal scale-free dynamics of brain responses.

Insulin Action in Brain Regulates Systemic Metabolism and Brain Function

OpenAIRE

Kleinridders, Andr?; Ferris, Heather A.; Cai, Weikang; Kahn, C. Ronald

2014-01-01

Insulin receptors, as well as IGF-1 receptors and their postreceptor signaling partners, are distributed throughout the brain. Insulin acts on these receptors to modulate peripheral metabolism, including regulation of appetite, reproductive function, body temperature, white fat mass, hepatic glucose output, and response to hypoglycemia. Insulin signaling also modulates neurotransmitter channel activity, brain cholesterol synthesis, and mitochondrial function. Disruption of insulin action in t...

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

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Laura Marchal-Crespo

2017-09-01

Full Text Available Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL, i.e., precuneus, and temporal cortex. These neuroimaging findings

Impact of Single or Repeated Dose Intranasal Zinc-free Insulin in Young and Aged F344 Rats on Cognition, Signaling, and Brain Metabolism.

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Anderson, Katie L; Frazier, Hilaree N; Maimaiti, Shaniya; Bakshi, Vikas V; Majeed, Zana R; Brewer, Lawrence D; Porter, Nada M; Lin, Ai-Ling; Thibault, Olivier

2017-02-01

Novel therapies have turned to delivering compounds to the brain using nasal sprays, bypassing the blood brain barrier, and enriching treatment options for brain aging and/or Alzheimer's disease. We conducted a series of in vivo experiments to test the impact of intranasal Apidra, a zinc-free insulin formulation, on the brain of young and aged F344 rats. Both single acute and repeated daily doses were compared to test the hypothesis that insulin could improve memory recall in aged memory-deficient animals. We quantified insulin signaling in different brain regions and at different times following delivery. We measured cerebral blood flow (CBF) using MRI and also characterized several brain metabolite levels using MR spectroscopy. We show that neither acute nor chronic Apidra improved memory or recall in young or aged animals. Within 2 hours of a single dose, increased insulin signaling was seen in ventral areas of the aged brains only. Although chronic Apidra was able to offset reduced CBF with aging, it also caused significant reductions in markers of neuronal integrity. Our data suggest that this zinc-free insulin formulation may actually hasten cognitive decline with age when used chronically. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Metal Dependence of Signal Transmission through MolecularQuantum-Dot Cellular Automata (QCA: A Theoretical Studyon Fe, Ru, and Os Mixed-Valence Complexes

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Ken Tokunaga

2010-08-01

Full Text Available Dynamic behavior of signal transmission through metal complexes [L5M-BL-ML5]5+ (M=Fe, Ru, Os, BL=pyrazine (py, 4,4’-bipyridine (bpy, L=NH3, which are simplified models of the molecular quantum-dot cellular automata (molecular QCA, is discussed from the viewpoint of one-electron theory, density functional theory. It is found that for py complexes, the signal transmission time (tst is Fe(0.6 fs < Os(0.7 fs < Ru(1.1 fs and the signal amplitude (A is Fe(0.05 e < Os(0.06 e < Ru(0.10 e. For bpy complexes, tst and A are Fe(1.4 fs < Os(1.7 fs < Ru(2.5 fs and Os(0.11 e < Ru(0.12 e complexes generally have stronger signal amplitude, but waste longer time for signal transmission than py complexes. Among all complexes, Fe complex with bpy BL shows the best result. These results are discussed from overlap integral and energy gap of molecular orbitals.

A System for True and False Memory Prediction Based on 2D and 3D Educational Contents and EEG Brain Signals.

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Bamatraf, Saeed; Hussain, Muhammad; Aboalsamh, Hatim; Qazi, Emad-Ul-Haq; Malik, Amir Saeed; Amin, Hafeez Ullah; Mathkour, Hassan; Muhammad, Ghulam; Imran, Hafiz Muhammad

2016-01-01

We studied the impact of 2D and 3D educational contents on learning and memory recall using electroencephalography (EEG) brain signals. For this purpose, we adopted a classification approach that predicts true and false memories in case of both short term memory (STM) and long term memory (LTM) and helps to decide whether there is a difference between the impact of 2D and 3D educational contents. In this approach, EEG brain signals are converted into topomaps and then discriminative features are extracted from them and finally support vector machine (SVM) which is employed to predict brain states. For data collection, half of sixty-eight healthy individuals watched the learning material in 2D format whereas the rest watched the same material in 3D format. After learning task, memory recall tasks were performed after 30 minutes (STM) and two months (LTM), and EEG signals were recorded. In case of STM, 97.5% prediction accuracy was achieved for 3D and 96.6% for 2D and, in case of LTM, it was 100% for both 2D and 3D. The statistical analysis of the results suggested that for learning and memory recall both 2D and 3D materials do not have much difference in case of STM and LTM.

Weak signal transmission in complex networks and its application in detecting connectivity.

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Liang, Xiaoming; Liu, Zonghua; Li, Baowen

2009-10-01

We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.

Assessing denoising strategies to increase signal to noise ratio in spinal cord and in brain cortical and subcortical regions

Science.gov (United States)

Maugeri, L.; Moraschi, M.; Summers, P.; Favilla, S.; Mascali, D.; Cedola, A.; Porro, C. A.; Giove, F.; Fratini, M.

2018-02-01

Functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygenation Level Dependent (BOLD) contrast has become one of the most powerful tools in neuroscience research. On the other hand, fMRI approaches have seen limited use in the study of spinal cord and subcortical brain regions (such as the brainstem and portions of the diencephalon). Indeed obtaining good BOLD signal in these areas still represents a technical and scientific challenge, due to poor control of physiological noise and to a limited overall quality of the functional series. A solution can be found in the combination of optimized experimental procedures at acquisition stage, and well-adapted artifact mitigation procedures in the data processing. In this framework, we studied two different data processing strategies to reduce physiological noise in cortical and subcortical brain regions and in the spinal cord, based on the aCompCor and RETROICOR denoising tools respectively. The study, performed in healthy subjects, was carried out using an ad hoc isometric motor task. We observed an increased signal to noise ratio in the denoised functional time series in the spinal cord and in the subcortical brain region.

Brain MRI findings of welders : high signal intensity in T1WI secondary to manganese exposure

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Kim, K. W.; Lim, M. A.; Shon, M. Y.; Lee, S. H.; Ha, D. G.; Kwon, K. R.; Kim, S. S.; Hong, Y. S.; Lee, Y. H. [Sunlin Presbyterian Hospital, Pohang (Korea, Republic of); Cheong, H. K. [Dongguk University, Seoul (Korea, Republic of)

1998-03-01

To evaluate the clinical and brain MRI findings of welders and to determine the utility of MRI in the assessment of occupational manganese exposure. All welders complained of fatigue, headache, anorexia, and decreased libido. The palmomental reflex was positive in five (28%), Myerson`s sign in four (22%), and intention tremor in three (17%). Mean blood Mn was 5.18 (range, 1.77-9.34) {mu}g/dl, mean urine Mn was 5.84 (range, 1.07 -22) {mu}g/l, serum Fe was elevated in one welder, and serum Cd in two. T1WI of brain MRI revealed high signal intensities in the globus pallidus, the putamen, the substantia nigra, the tectum, the caudate nucleus, the subthalamic nucleus, the hypothalamus and the pituitary gland. These intensities correlated closely with blood Mn levels, suggesting their potential role in estimating the accumulation of Mn in the brain. (author). 25 refs., 2 tabs., 5 figs.

Assembly of Oligomeric Death Domain Complexes during Toll Receptor Signaling*

OpenAIRE

Moncrieffe, Martin C.; Grossmann, J. Günter; Gay, Nicholas J.

2008-01-01

The Drosophila Toll receptor is activated by the endogenous protein ligand Spätzle in response to microbial stimuli in immunity and spatial cues during embryonic development. Downstream signaling is mediated by the adaptor proteins Tube, the kinase Pelle, and the Drosophila homologue of myeloid differentiation primary response protein (dMyD88). Here we have characterized heterodimeric (dMyD88-Tube) and heterotrimeric (dMyD88-Tube-Pelle) death domain complexes. We show ...

Simultaneous estimation of the in-mean and in-variance causal connectomes of the human brain.

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Duggento, A; Passamonti, L; Guerrisi, M; Toschi, N

2017-07-01

In recent years, the study of the human connectome (i.e. of statistical relationships between non spatially contiguous neurophysiological events in the human brain) has been enormously fuelled by technological advances in high-field functional magnetic resonance imaging (fMRI) as well as by coordinated world wide data-collection efforts like the Human Connectome Project (HCP). In this context, Granger Causality (GC) approaches have recently been employed to incorporate information about the directionality of the influence exerted by a brain region on another. However, while fluctuations in the Blood Oxygenation Level Dependent (BOLD) signal at rest also contain important information about the physiological processes that underlie neurovascular coupling and associations between disjoint brain regions, so far all connectivity estimation frameworks have focused on central tendencies, hence completely disregarding so-called in-variance causality (i.e. the directed influence of the volatility of one signal on the volatility of another). In this paper, we develop a framework for simultaneous estimation of both in-mean and in-variance causality in complex networks. We validate our approach using synthetic data from complex ensembles of coupled nonlinear oscillators, and successively employ HCP data to provide the very first estimate of the in-variance connectome of the human brain.

Final Report on LDRD project 130784 : functional brain imaging by tunable multi-spectral Event-Related Optical Signal (EROS).

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Speed, Ann Elizabeth; Spahn, Olga Blum; Hsu, Alan Yuan-Chun

2009-09-01

Functional brain imaging is of great interest for understanding correlations between specific cognitive processes and underlying neural activity. This understanding can provide the foundation for developing enhanced human-machine interfaces, decision aides, and enhanced cognition at the physiological level. The functional near infrared spectroscopy (fNIRS) based event-related optical signal (EROS) technique can provide direct, high-fidelity measures of temporal and spatial characteristics of neural networks underlying cognitive behavior. However, current EROS systems are hampered by poor signal-to-noise-ratio (SNR) and depth of measure, limiting areas of the brain and associated cognitive processes that can be investigated. We propose to investigate a flexible, tunable, multi-spectral fNIRS EROS system which will provide up to 10x greater SNR as well as improved spatial and temporal resolution through significant improvements in electronics, optoelectronics and optics, as well as contribute to the physiological foundation of higher-order cognitive processes and provide the technical foundation for miniaturized portable neuroimaging systems.

The mediator complex in genomic and non-genomic signaling in cancer.

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Weber, Hannah; Garabedian, Michael J

2018-05-01

Mediator is a conserved, multi-subunit macromolecular machine divided structurally into head, middle, and tail modules, along with a transiently associating kinase module. Mediator functions as an integrator of transcriptional regulatory activity by interacting with DNA-bound transcription factors and with RNA polymerase II (Pol II) to both activate and repress gene expression. Mediator has been shown to affect multiple steps in transcription, including chromatin looping between enhancers and promoters, pre-initiation complex formation, transcriptional elongation, and mRNA splicing. Individual Mediator subunits participate in regulation of gene expression by the estrogen and androgen receptors and are altered in a number of endocrine cancers, including breast and prostate cancer. In addition to its role in genomic signaling, MED12 has been implicated in non-genomic signaling by interacting with and activating TGF-beta receptor 2 in the cytoplasm. Recent structural studies have revealed extensive inter-domain interactions and complex architecture of the Mediator-Pol II complex, suggesting that Mediator is capable of reorganizing its conformation and composition to fit cellular needs. We propose that alterations in Mediator subunit expression that occur in various cancers could impact the organization and function of Mediator, resulting in changes in gene expression that promote malignancy. A better understanding of the role of Mediator in cancer could reveal new approaches to the diagnosis and treatment of Mediator-dependent endocrine cancers, especially in settings of therapy resistance. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of filtration of signals of brain activity on quality of recognition of brain activity patterns using artificial intelligence methods

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Hramov, Alexander E.; Frolov, Nikita S.; Musatov, Vyachaslav Yu.

2018-02-01

In present work we studied features of the human brain states classification, corresponding to the real movements of hands and legs. For this purpose we used supervised learning algorithm based on feed-forward artificial neural networks (ANNs) with error back-propagation along with the support vector machine (SVM) method. We compared the quality of operator movements classification by means of EEG signals obtained experimentally in the absence of preliminary processing and after filtration in different ranges up to 25 Hz. It was shown that low-frequency filtering of multichannel EEG data significantly improved accuracy of operator movements classification.

Preictal dynamics of EEG complexity in intracranially recorded epileptic seizure: a case report.

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Bob, Petr; Roman, Robert; Svetlak, Miroslav; Kukleta, Miloslav; Chladek, Jan; Brazdil, Milan

2014-11-01

Recent findings suggest that neural complexity reflecting a number of independent processes in the brain may characterize typical changes during epileptic seizures and may enable to describe preictal dynamics. With respect to previously reported findings suggesting specific changes in neural complexity during preictal period, we have used measure of pointwise correlation dimension (PD2) as a sensitive indicator of nonstationary changes in complexity of the electroencephalogram (EEG) signal. Although this measure of complexity in epileptic patients was previously reported by Feucht et al (Applications of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures. Med Biol Comput. 1999;37:208-217), it was not used to study changes in preictal dynamics. With this aim to study preictal changes of EEG complexity, we have examined signals from 11 multicontact depth (intracerebral) EEG electrodes located in 108 cortical and subcortical brain sites, and from 3 scalp EEG electrodes in a patient with intractable epilepsy, who underwent preoperative evaluation before epilepsy surgery. From those 108 EEG contacts, records related to 44 electrode contacts implanted into lesional structures and white matter were not included into the experimental analysis.The results show that in comparison to interictal period (at about 8-6 minutes before seizure onset), there was a statistically significant decrease in PD2 complexity in the preictal period at about 2 minutes before seizure onset in all 64 intracranial channels localized in various brain sites that were included into the analysis and in 3 scalp EEG channels as well. Presented results suggest that using PD2 in EEG analysis may have significant implications for research of preictal dynamics and prediction of epileptic seizures.

Hydrogen-Rich Saline Attenuates Brain Injury Induced by Cardiopulmonary Bypass and Inhibits Microvascular Endothelial Cell Apoptosis Via the PI3K/Akt/GSK3β Signaling Pathway in Rats

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Keyan Chen

2017-10-01

Full Text Available Background/Aims: Cardiopulmonary bypass (CPB is prone to inducing brain injury during open heart surgery. A hydrogen-rich solution (HRS can prevent oxidation and apoptosis, and inhibit inflammation. This study investigated effects of HRS on brain injury induced by CPB and regulatory mechanisms of the PI3K/Akt/GSK3β signaling pathway. Methods: A rat CPB model and an in vitro cell hypoxia model were established. After HRS treatment, Rat behavior was measured using neurological deficit score; Evans blue (EB was used to assess permeability of the blood-brain barrier (BBB; HE staining was used to observe pathological changes; Inflammatory factors and brain injury markers were detected by ELISA; the PI3K/Akt/GSK3β pathway-related proteins and apoptosis were assessed by western blot, immunohistochemistry and qRT –PCR analyses of brain tissue and neurons. Results: After CPB, brain tissue anatomy was disordered, and cell structure was abnormal. Brain tissue EB content increased. There was an increase in the number of apoptotic cells, an increase in expression of Bax and caspase-3, a decrease in expression of Bcl2, and increases in levels of Akt, GSK3β, P-Akt, and P-GSK3β in brain tissue. HRS treatment attenuated the inflammatory reaction ,brain tissue EB content was significantly reduced and significantly decreased expression levels of Bax, caspase-3, Akt, GSK3β, P-Akt, and P-GSK3β in the brain. After adding the PI3K signaling pathway inhibitor, LY294002, to rat cerebral microvascular endothelial cells (CMECs, HRS could reduce activated Akt expression and downstream regulatory gene phosphorylation of GSK3β expression, and inhibit CMEC apoptosis. Conclusion: The PI3K/Akt/GSK3β signaling pathway plays an important role in the mechanism of CPB-induced brain injury. HRS can reduce CPB-induced brain injury and inhibit CMEC apoptosis through the PI3K/Akt/GSK3β signaling pathway.

Cross Talk Between Brain Innate Immunity and Serotonin Signaling Underlies Depressive-Like Behavior Induced by Alzheimer's Amyloid-β Oligomers in Mice.

Science.gov (United States)

Ledo, Jose Henrique; Azevedo, Estefania P; Beckman, Danielle; Ribeiro, Felipe C; Santos, Luis E; Razolli, Daniela S; Kincheski, Grasielle C; Melo, Helen M; Bellio, Maria; Teixeira, Antonio L; Velloso, Licio A; Foguel, Debora; De Felice, Fernanda G; Ferreira, Sergio T

2016-11-30

Considerable clinical and epidemiological evidence links Alzheimer's disease (AD) and depression. However, the molecular mechanisms underlying this connection are largely unknown. We reported recently that soluble Aβ oligomers (AβOs), toxins that accumulate in AD brains and are thought to instigate synapse damage and memory loss, induce depressive-like behavior in mice. Here, we report that the mechanism underlying this action involves AβO-induced microglial activation, aberrant TNF-α signaling, and decreased brain serotonin levels. Inactivation or ablation of microglia blocked the increase in brain TNF-α and abolished depressive-like behavior induced by AβOs. Significantly, we identified serotonin as a negative regulator of microglial activation. Finally, AβOs failed to induce depressive-like behavior in Toll-like receptor 4-deficient mice and in mice harboring a nonfunctional TLR4 variant in myeloid cells. Results establish that AβOs trigger depressive-like behavior via a double impact on brain serotonin levels and microglial activation, unveiling a cross talk between brain innate immunity and serotonergic signaling as a key player in mood alterations in AD. Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the main cause of dementia in the world. Brain accumulation of amyloid-β oligomers (AβOs) is a major feature in the pathogenesis of AD. Although clinical and epidemiological data suggest a strong connection between AD and depression, the underlying mechanisms linking these two disorders remain largely unknown. Here, we report that aberrant activation of the brain innate immunity and decreased serotonergic tonus in the brain are key players in AβO-induced depressive-like behavior in mice. Our findings may open up new possibilities for the development of effective therapeutics for AD and depression aimed at modulating microglial function. Copyright © 2016 the authors 0270-6474/16/3612106-11$15.00/0.

Mutations in Subunits of the Activating Signal Cointegrator 1 Complex Are Associated with Prenatal Spinal Muscular Atrophy and Congenital Bone Fractures

Science.gov (United States)

Knierim, Ellen; Hirata, Hiromi; Wolf, Nicole I.; Morales-Gonzalez, Susanne; Schottmann, Gudrun; Tanaka, Yu; Rudnik-Schöneborn, Sabine; Orgeur, Mickael; Zerres, Klaus; Vogt, Stefanie; van Riesen, Anne; Gill, Esther; Seifert, Franziska; Zwirner, Angelika; Kirschner, Janbernd; Goebel, Hans Hilmar; Hübner, Christoph; Stricker, Sigmar; Meierhofer, David; Stenzel, Werner; Schuelke, Markus

2016-01-01

Transcriptional signal cointegrators associate with transcription factors or nuclear receptors and coregulate tissue-specific gene transcription. We report on recessive loss-of-function mutations in two genes (TRIP4 and ASCC1) that encode subunits of the nuclear activating signal cointegrator 1 (ASC-1) complex. We used autozygosity mapping and whole-exome sequencing to search for pathogenic mutations in four families. Affected individuals presented with prenatal-onset spinal muscular atrophy (SMA), multiple congenital contractures (arthrogryposis multiplex congenita), respiratory distress, and congenital bone fractures. We identified homozygous and compound-heterozygous nonsense and frameshift TRIP4 and ASCC1 mutations that led to a truncation or the entire absence of the respective proteins and cosegregated with the disease phenotype. Trip4 and Ascc1 have identical expression patterns in 17.5-day-old mouse embryos with high expression levels in the spinal cord, brain, paraspinal ganglia, thyroid, and submandibular glands. Antisense morpholino-mediated knockdown of either trip4 or ascc1 in zebrafish disrupted the highly patterned and coordinated process of α-motoneuron outgrowth and formation of myotomes and neuromuscular junctions and led to a swimming defect in the larvae. Immunoprecipitation of the ASC-1 complex consistently copurified cysteine and glycine rich protein 1 (CSRP1), a transcriptional cofactor, which is known to be involved in spinal cord regeneration upon injury in adult zebrafish. ASCC1 mutant fibroblasts downregulated genes associated with neurogenesis, neuronal migration, and pathfinding (SERPINF1, DAB1, SEMA3D, SEMA3A), as well as with bone development (TNFRSF11B, RASSF2, STC1). Our findings indicate that the dysfunction of a transcriptional coactivator complex can result in a clinical syndrome affecting the neuromuscular system. PMID:26924529

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

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Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

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Kyungsoo Kim

2016-06-01

Full Text Available Electroencephalograms (EEGs measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE schemes based on a joint maximum likelihood (ML criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°.

Apo-ghrelin receptor (apo-GHSR1a Regulates Dopamine Signaling in the Brain

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Andras eKern

2014-08-01

Full Text Available The orexigenic peptide hormone ghrelin is synthesized in the stomach and its receptor growth hormone secretagogue receptor (GHSR1a is expressed mainly in the central nervous system (CNS. In this review we confine our discussion to the physiological role of GHSR1a in the brain. Paradoxically, despite broad expression of GHSR1a in the CNS, other than trace amounts in the hypothalamus, ghrelin is undetectable in the brain. In our efforts to elucidate the function of the ligand-free ghrelin receptor (apo-GHSR1a we identified subsets of neurons that co-express GHSR1a and dopamine receptors. In this review we focus on interactions between apo-GHSR1a and dopamine-2 receptor (DRD2 and formation of GHSR1a:DRD2 heteromers in hypothalamic neurons that regulate appetite, and discuss implications for the treatment of Prader-Willi syndrome. GHSR1a antagonists of distinct chemical structures, a quinazolinone and a triazole, respectively enhance and inhibit dopamine signaling through GHSR1a:DRD2 heteromers by an allosteric mechanism. This finding illustrates a potential strategy for designing the next generation of drugs for treating eating disorders as well as psychiatric disorders caused by abnormal dopamine signaling. Treatment with a GHSR1a antagonist that enhances dopamine/DRD2 activity in GHSR1a:DRD2 expressing hypothalamic neurons has the potential to inhibit the uncontrollable hyperphagia associated with Prader-Willi syndrome. DRD2 antagonists are prescribed for treating schizophrenia, but these block dopamine signaling in all DRD2 expressing neurons and are associated with adverse side effects, including enhanced appetite and excessive weight gain. A GHSR1a antagonist of structural class that allosterically blocks dopamine/DRD2 action in GHSR1a:DRD2 expressing neurons would have no effect on neurons expressing DRD2 alone; therefore, the side effects of DRD2 antagonists would potentially be reduced thereby enhancing patient compliance.

Enabling complex genetic circuits to respond to extrinsic environmental signals.

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Hoynes-O'Connor, Allison; Shopera, Tatenda; Hinman, Kristina; Creamer, John Philip; Moon, Tae Seok

2017-07-01

Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Brain entropy and human intelligence: A resting-state fMRI study

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Calderone, Daniel; Morales, Leah J.

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

Brain entropy and human intelligence: A resting-state fMRI study.

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Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

Complex motion of a vehicle through a series of signals controlled by power-law phase

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Nagatani, Takashi

2017-07-01

We study the dynamic motion of a vehicle moving through the series of traffic signals controlled by the position-dependent phase of power law. All signals are controlled by both cycle time and position-dependent phase. The dynamic model of the vehicular motion is described in terms of the nonlinear map. The vehicular motion varies in a complex manner by varying cycle time for various values of the power of the position-dependent phase. The vehicle displays the periodic motion with a long cycle for the integer power of the phase, while the vehicular motion exhibits the very complex behavior for the non-integer power of the phase.

Learning Predictive Statistics: Strategies and Brain Mechanisms.

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Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to

An Adaptive Noise Cancellation System Based on Linear and Widely Linear Complex Valued Least Mean Square Algorithms for Removing Electrooculography Artifacts from Electroencephalography Signals

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Engin Cemal MENGÜÇ

2018-03-01

Full Text Available In this study, an adaptive noise cancellation (ANC system based on linear and widely linear (WL complex valued least mean square (LMS algorithms is designed for removing electrooculography (EOG artifacts from electroencephalography (EEG signals. The real valued EOG and EEG signals (Fp1 and Fp2 given in dataset are primarily expressed as a complex valued signal in the complex domain. Then, using the proposed ANC system, the EOG artifacts are eliminated in the complex domain from the EEG signals. Expression of these signals in the complex domain allows us to remove EOG artifacts from two EEG channels simultaneously. Moreover, in this study, it has been shown that the complex valued EEG signal exhibits noncircular behavior, and in the case, the WL-CLMS algorithm enhances the performance of the ANC system compared to real-valued LMS and CLMS algorithms. Simulation results support the proposed approach.

Inhibition of VEGF Signaling Reduces Diabetes-Exacerbated Brain Swelling, but Not Infarct Size, in Large Cerebral Infarction in Mice.

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Kim, Eunhee; Yang, Jiwon; Park, Keun Woo; Cho, Sunghee

2017-12-30

In light of repeated translational failures with preclinical neuroprotection-based strategies, this preclinical study reevaluates brain swelling as an important pathological event in diabetic stroke and investigates underlying mechanism of the comorbidity-enhanced brain edema formation. Type 2 (mild), type 1 (moderate), and mixed type 1/2 (severe) diabetic mice were subjected to transient focal ischemia. Infarct volume, brain swelling, and IgG extravasation were assessed at 3 days post-stroke. Expression of vascular endothelial growth factor (VEGF)-A, endothelial-specific molecule-1 (Esm1), and the VEGF receptor 2 (VEGFR2) was determined in the ischemic brain. Additionally, SU5416, a VEGFR2 inhibitor, was treated in the type 1/2 diabetic mice, and stroke outcomes were determined. All diabetic groups displayed bigger infarct volume and brain swelling compared to nondiabetic mice, and the increased swelling was disproportionately larger relative to infarct enlargement. Diabetic conditions significantly increased VEGF-A, Esm1, and VEGFR2 expressions in the ischemic brain compared to nondiabetic mice. Notably, in diabetic mice, VEGFR2 mRNA levels were positively correlated with brain swelling, but not with infarct volume. Treatment with SU5416 in diabetic mice significantly reduced brain swelling. The study shows that brain swelling is a predominant pathological event in diabetic stroke and that an underlying event for diabetes-enhanced brain swelling includes the activation of VEGF signaling. This study suggests consideration of stroke therapies aiming at primarily reducing brain swelling for subjects with diabetes.

Tuning the brain for motherhood: prolactin-like central signalling in virgin, pregnant, and lactating female mice.

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Salais-López, Hugo; Lanuza, Enrique; Agustín-Pavón, Carmen; Martínez-García, Fernando

2017-03-01

Prolactin is fundamental for the expression of maternal behaviour. In virgin female rats, prolactin administered upon steroid hormone priming accelerates the onset of maternal care. By contrast, the role of prolactin in mice maternal behaviour remains unclear. This study aims at characterizing central prolactin activity patterns in female mice and their variation through pregnancy and lactation. This was revealed by immunoreactivity of phosphorylated (active) signal transducer and activator of transcription 5 (pSTAT5-ir), a key molecule in the signalling cascade of prolactin receptors. We also evaluated non-hypophyseal lactogenic activity during pregnancy by administering bromocriptine, which suppresses hypophyseal prolactin release. Late-pregnant and lactating females showed significantly increased pSTAT5-ir resulting in a widespread pattern of immunostaining with minor variations between pregnant and lactating animals, which comprises nuclei of the sociosexual and maternal brain, including telencephalic (septum, nucleus of the stria terminalis, and amygdala), hypothalamic (preoptic, paraventricular, supraoptic, and ventromedial), and midbrain (periaqueductal grey) regions. During late pregnancy, this pattern was not affected by the administration of bromocriptine, suggesting it to be elicited mostly by non-hypophyseal lactogenic agents, likely placental lactogens. Virgin females displayed, instead, a variable pattern of pSTAT5-ir restricted to a subset of the brain nuclei labelled in pregnant and lactating mice. A hormonal substitution experiment confirmed that estradiol and progesterone contribute to the variability found in virgin females. Our results reflect how the shaping of the maternal brain takes place prior to parturition and suggest that lactogenic agents are important candidates in the development of maternal behaviours already during pregnancy.

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain

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Prasad Shirvalkar

2018-03-01

Full Text Available Pain is a subjective experience that alerts an individual to actual or potential tissue damage. Through mechanisms that are still unclear, normal physiological pain can lose its adaptive value and evolve into pathological chronic neuropathic pain. Chronic pain is a multifaceted experience that can be understood in terms of somatosensory, affective, and cognitive dimensions, each with associated symptoms and neural signals. While there have been many attempts to treat chronic pain, in this article we will argue that feedback-controlled ‘closed-loop’ deep brain stimulation (DBS offers an urgent and promising route for treatment. Contemporary DBS trials for chronic pain use “open-loop” approaches in which tonic stimulation is delivered with fixed parameters to a single brain region. The impact of key variables such as the target brain region and the stimulation waveform is unclear, and long-term efficacy has mixed results. We hypothesize that chronic pain is due to abnormal synchronization between brain networks encoding the somatosensory, affective and cognitive dimensions of pain, and that multisite, closed-loop DBS provides an intuitive mechanism for disrupting that synchrony. By (1 identifying biomarkers of the subjective pain experience and (2 integrating these signals into a state-space representation of pain, we can create a predictive model of each patient's pain experience. Then, by establishing how stimulation in different brain regions influences individual neural signals, we can design real-time, closed-loop therapies tailored to each patient. While chronic pain is a complex disorder that has eluded modern therapies, rich historical data and state-of-the-art technology can now be used to develop a promising treatment.

Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI

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Galina V. Portnova

2018-01-01

Full Text Available Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

Cold stress-induced brain injury regulates TRPV1 channels and the PI3K/AKT signaling pathway.

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Liu, Ying; Liu, Yunen; Jin, Hongxu; Cong, Peifang; Zhang, Yubiao; Tong, Changci; Shi, Xiuyun; Liu, Xuelei; Tong, Zhou; Shi, Lin; Hou, Mingxiao

2017-09-01

Transient receptor potential vanilloid 1 (TRPV1) is a nonselective cation channel that interacts with several intracellular proteins in vivo, including calmodulin and Phosphatidylinositol-3-Kinase/Protein Kinase B (PI3K/Akt). TRPV1 activation has been reported to exert neuroprotective effects. The aim of this study was to examine the impact of cold stress on the mouse brain and the underlying mechanisms of TRPV1 involvement. Adult male C57BL/6 mice were subjected to cold stress (4°C for 8h per day for 2weeks). The behavioral deficits of the mice were then measured using the Morris water maze. Expression levels of brain injury-related proteins and mRNA were measured by western blot, immunofluorescence or RT-PCR analysis. The mice displayed behavioral deficits, inflammation and changes in brain injury markers following cold stress. As expected, upregulated TRPV1 expression levels and changes in PI3K/Akt expression were found. The TRPV1 inhibitor reduced the levels of brain injury-related proteins and inflammation. These data suggest that cold stress can induce brain injury, possibly through TRPV1 activation and the PI3K/Akt signaling pathway. Suppression of inflammation by inhibition of TRPV1 and the PI3K/Akt pathway may be helpful to prevent cold stress-induced brain injury. Copyright © 2017 Elsevier B.V. All rights reserved.

Combined Blockade of Interleukin-1α and -1β Signaling Protects Mice from Cognitive Dysfunction after Traumatic Brain Injury.

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Newell, Elizabeth A; Todd, Brittany P; Mahoney, Jolonda; Pieper, Andrew A; Ferguson, Polly J; Bassuk, Alexander G

2018-01-01

Diffuse activation of interleukin-1 inflammatory cytokine signaling after traumatic brain injury (TBI) elicits progressive neurodegeneration and neuropsychiatric dysfunction, and thus represents a potential opportunity for therapeutic intervention. Although interleukin (IL)-1α and IL-1β both activate the common type 1 IL-1 receptor (IL-1RI), they manifest distinct injury-specific roles in some models of neurodegeneration. Despite its potential relevance to treating patients with TBI, however, the individual contributions of IL-1α and IL-1β to TBI-pathology have not been previously investigated. To address this need, we applied genetic and pharmacologic approaches in mice to dissect the individual contributions of IL-1α, IL-β, and IL-1RI signaling to the pathophysiology of fluid percussion-mediated TBI, a model of mixed focal and diffuse TBI. IL-1RI ablation conferred a greater protective effect on brain cytokine expression and cognitive function after TBI than did individual IL-1α or IL-1β ablation. This protective effect was recapitulated by treatment with the drug anakinra, a recombinant naturally occurring IL-1RI antagonist. Our data thus suggest that broad targeting of IL-1RI signaling is more likely to reduce neuroinflammation and preserve cognitive function after TBI than are approaches that individually target IL-1α or IL-1β signaling.

Receptor density balances signal stimulation and attenuation in membrane-assembled complexes of bacterial chemotaxis signaling proteins

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Besschetnova, Tatiana Y.; Montefusco, David J.; Asinas, Abdalin E.; Shrout, Anthony L.; Antommattei, Frances M.; Weis, Robert M.

2008-01-01

All cells possess transmembrane signaling systems that function in the environment of the lipid bilayer. In the Escherichia coli chemotaxis pathway, the binding of attractants to a two-dimensional array of receptors and signaling proteins simultaneously inhibits an associated kinase and stimulates receptor methylation—a slower process that restores kinase activity. These two opposing effects lead to robust adaptation toward stimuli through a physical mechanism that is not understood. Here, we provide evidence of a counterbalancing influence exerted by receptor density on kinase stimulation and receptor methylation. Receptor signaling complexes were reconstituted over a range of defined surface concentrations by using a template-directed assembly method, and the kinase and receptor methylation activities were measured. Kinase activity and methylation rates were both found to vary significantly with surface concentration—yet in opposite ways: samples prepared at high surface densities stimulated kinase activity more effectively than low-density samples, whereas lower surface densities produced greater methylation rates than higher densities. FRET experiments demonstrated that the cooperative change in kinase activity coincided with a change in the arrangement of the membrane-associated receptor domains. The counterbalancing influence of density on receptor methylation and kinase stimulation leads naturally to a model for signal regulation that is compatible with the known logic of the E. coli pathway. Density-dependent mechanisms are likely to be general and may operate when two or more membrane-related processes are influenced differently by the two-dimensional concentration of pathway elements. PMID:18711126

Coherence and phase synchrony analyses of EEG signals in Mild Cognitive Impairment (MCI): A study of functional brain connectivity

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Handayani, Nita; Haryanto, Freddy; Khotimah, Siti Nurul; Arif, Idam; Taruno, Warsito Purwo

2018-03-01

This paper presents an EEG study for coherence and phase synchrony in mild cognitive impairment (MCI) subjects. MCI is characterized by cognitive decline, which is an early stage of Alzheimer's disease (AD). AD is a neurodegenerative disorder with symptoms such as memory loss and cognitive impairment. EEG coherence is a statistical measure of correlation between signals from electrodes spatially separated on the scalp. The magnitude of phase synchrony is expressed in the phase locking value (PLV), a statistical measure of neuronal connectivity in the human brain. Brain signals were recorded using an Emotiv Epoc 14-channel wireless EEG at a sampling frequency of 128 Hz. In this study, we used 22 elderly subjects consisted of 10 MCI subjects and 12 healthy subjects as control group. The coherence between each electrode pair was measured for all frequency bands (delta, theta, alpha and beta). In the MCI subjects, the value of coherence and phase synchrony was generally lower than in the healthy subjects especially in the beta frequency. A decline of intrahemisphere coherence in the MCI subjects occurred in the left temporo-parietal-occipital region. The pattern of decline in MCI coherence is associated with decreased cholinergic connectivity along the path that connects the temporal, occipital, and parietal areas of the brain to the frontal area of the brain. EEG coherence and phase synchrony are able to distinguish persons who suffer AD in the early stages from healthy elderly subjects.

Processing Functional Near Infrared Spectroscopy Signal with a Kalman Filter to Assess Working Memory during Simulated Flight.

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Gautier eDurantin

2016-01-01

Full Text Available Working memory is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor working memory as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces. We used functional near infrared spectroscopy as it has been already successfully tested to measure working memory capacity in complex environment with air traffic controllers, pilots or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with 9 participants involving a basic working memory task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with air traffic controller instructions (two levels of difficulty. The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in working

Metabolic Profiles of Brain Metastases

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Tone F. Bathen

2013-01-01

Full Text Available Metastasis to the brain is a feared complication of systemic cancer, associated with significant morbidity and poor prognosis. A better understanding of the tumor metabolism might help us meet the challenges in controlling brain metastases. The study aims to characterize the metabolic profile of brain metastases of different origin using high resolution magic angle spinning (HR-MAS magnetic resonance spectroscopy (MRS to correlate the metabolic profiles to clinical and pathological information. Biopsy samples of human brain metastases (n = 49 were investigated. A significant correlation between lipid signals and necrosis in brain metastases was observed (p < 0.01, irrespective of their primary origin. The principal component analysis (PCA showed that brain metastases from malignant melanomas cluster together, while lung carcinomas were metabolically heterogeneous and overlap with other subtypes. Metastatic melanomas have higher amounts of glycerophosphocholine than other brain metastases. A significant correlation between microscopically visible lipid droplets estimated by Nile Red staining and MR visible lipid signals was observed in metastatic lung carcinomas (p = 0.01, indicating that the proton MR visible lipid signals arise from cytoplasmic lipid droplets. MRS-based metabolomic profiling is a useful tool for exploring the metabolic profiles of metastatic brain tumors.

Thyroid hormone signaling in the hypothalamus

NARCIS (Netherlands)

Alkemade, Anneke; Visser, Theo J.; Fliers, Eric

2008-01-01

PURPOSE OF REVIEW: Proper thyroid hormone signaling is essential for brain development and adult brain function. Signaling can be disrupted at many levels due to altered thyroid hormone secretion, conversion or thyroid hormone receptor binding. RECENT FINDINGS: Mutated genes involved in thyroid

A map of brain neuropils and fiber systems in the ant Cardiocondyla obscurior

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Joris eBressan

2015-02-01

Full Text Available A wide spectrum of occupied ecological niches and spectacular morphological adaptations make social insects a prime object for comparative neuroanatomical studies. Eusocial insects have evolved complex societies based on caste polyphenism. A diverse behavioral repertoire of morphologically distinct castes of the same species requires a high degree of plasticity in the central nervous system. We have analyzed the central brain neuropils and fiber tract systems of the worker of the ant Cardiocondyla obscurior, a model for the study of social traits. Our analysis is based on whole mount preparations of adult brains labeled with an antibody against Drosophila-Synapsin, which cross-reacts strongly with synapses in Cardiocondyla. Neuropil compartments stand out as domains with a certain texture and intensity of the anti-Synapsin signal. By contrast, fiber tracts, which are composed of bundles of axons accompanied by glia and are devoid of synapses, appear as channels or sheaths with low anti-Synapsin signal. We have generated a digital 3D atlas of the Cardiocondyla brain neuropil. The atlas provides a reference for future studies of brain polymorphisms in distinct castes, brain development or localization of neurotransmitter systems.

A map of brain neuropils and fiber systems in the ant Cardiocondyla obscurior.

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Bressan, Joris M A; Benz, Martin; Oettler, Jan; Heinze, Jürgen; Hartenstein, Volker; Sprecher, Simon G

2014-01-01

A wide spectrum of occupied ecological niches and spectacular morphological adaptations make social insects a prime object for comparative neuroanatomical studies. Eusocial insects have evolved complex societies based on caste polyphenism. A diverse behavioral repertoire of morphologically distinct castes of the same species requires a high degree of plasticity in the central nervous system. We have analyzed the central brain neuropils and fiber tract systems of the worker of the ant Cardiocondyla obscurior, a model for the study of social traits. Our analysis is based on whole mount preparations of adult brains labeled with an antibody against Drosophila-Synapsin, which cross-reacts strongly with synapses in Cardiocondyla. Neuropil compartments stand out as domains with a certain texture and intensity of the anti-Synapsin signal. By contrast, fiber tracts, which are composed of bundles of axons accompanied by glia and are devoid of synapses, appear as channels or sheaths with low anti-Synapsin signal. We have generated a digital 3D atlas of the Cardiocondyla brain neuropil. The atlas provides a reference for future studies of brain polymorphisms in distinct castes, brain development or localization of neurotransmitter systems.

Convergent evolution of complex brains and high intelligence.

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Roth, Gerhard

2015-12-19

Within the animal kingdom, complex brains and high intelligence have evolved several to many times independently, e.g. among ecdysozoans in some groups of insects (e.g. blattoid, dipteran, hymenopteran taxa), among lophotrochozoans in octopodid molluscs, among vertebrates in teleosts (e.g. cichlids), corvid and psittacid birds, and cetaceans, elephants and primates. High levels of intelligence are invariantly bound to multimodal centres such as the mushroom bodies in insects, the vertical lobe in octopodids, the pallium in birds and the cerebral cortex in primates, all of which contain highly ordered associative neuronal networks. The driving forces for high intelligence may vary among the mentioned taxa, e.g. needs for spatial learning and foraging strategies in insects and cephalopods, for social learning in cichlids, instrumental learning and spatial orientation in birds and social as well as instrumental learning in primates. © 2015 The Author(s).

Requirement of the Mre11 complex and exonuclease 1 for activation of the Mec1 signaling pathway.

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Nakada, Daisuke; Hirano, Yukinori; Sugimoto, Katsunori

2004-11-01

The large protein kinases, ataxia-telangiectasia mutated (ATM) and ATM-Rad3-related (ATR), orchestrate DNA damage checkpoint pathways. In budding yeast, ATM and ATR homologs are encoded by TEL1 and MEC1, respectively. The Mre11 complex consists of two highly related proteins, Mre11 and Rad50, and a third protein, Xrs2 in budding yeast or Nbs1 in mammals. The Mre11 complex controls the ATM/Tel1 signaling pathway in response to double-strand break (DSB) induction. We show here that the Mre11 complex functions together with exonuclease 1 (Exo1) in activation of the Mec1 signaling pathway after DNA damage and replication block. Mec1 controls the checkpoint responses following UV irradiation as well as DSB induction. Correspondingly, the Mre11 complex and Exo1 play an overlapping role in activation of DSB- and UV-induced checkpoints. The Mre11 complex and Exo1 collaborate in producing long single-stranded DNA (ssDNA) tails at DSB ends and promote Mec1 association with the DSBs. The Ddc1-Mec3-Rad17 complex associates with sites of DNA damage and modulates the Mec1 signaling pathway. However, Ddc1 association with DSBs does not require the function of the Mre11 complex and Exo1. Mec1 controls checkpoint responses to stalled DNA replication as well. Accordingly, the Mre11 complex and Exo1 contribute to activation of the replication checkpoint pathway. Our results provide a model in which the Mre11 complex and Exo1 cooperate in generating long ssDNA tracts and thereby facilitate Mec1 association with sites of DNA damage or replication block.

Rictor/TORC2 mediates gut-to-brain signaling in the regulation of phenotypic plasticity in C. elegans.

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Michael P O'Donnell

2018-02-01

Full Text Available Animals integrate external cues with information about internal conditions such as metabolic state to execute the appropriate behavioral and developmental decisions. Information about food quality and quantity is assessed by the intestine and transmitted to modulate neuronal functions via mechanisms that are not fully understood. The conserved Target of Rapamycin complex 2 (TORC2 controls multiple processes in response to cellular stressors and growth factors. Here we show that TORC2 coordinates larval development and adult behaviors in response to environmental cues and feeding state in the bacterivorous nematode C. elegans. During development, pheromone, bacterial food, and temperature regulate expression of the daf-7 TGF-β and daf-28 insulin-like peptide in sensory neurons to promote a binary decision between reproductive growth and entry into the alternate dauer larval stage. We find that TORC2 acts in the intestine to regulate neuronal expression of both daf-7 and daf-28, which together reflect bacterial-diet dependent feeding status, thus providing a mechanism for integration of food signals with external cues in the regulation of neuroendocrine gene expression. In the adult, TORC2 similarly acts in the intestine to modulate food-regulated foraging behaviors via a PDF-2/PDFR-1 neuropeptide signaling-dependent pathway. We also demonstrate that genetic variation affects food-dependent larval and adult phenotypes, and identify quantitative trait loci (QTL associated with these traits. Together, these results suggest that TORC2 acts as a hub for communication of feeding state information from the gut to the brain, thereby contributing to modulation of neuronal function by internal state.

Physiological complexity of acute traumatic brain injury in patients treated with a brain oxygen protocol: utility of symbolic regression in predictive modeling of a dynamical system.

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Narotam, Pradeep K; Morrison, John F; Schmidt, Michael D; Nathoo, Narendra

2014-04-01

Predictive modeling of emergent behavior, inherent to complex physiological systems, requires the analysis of large complex clinical data streams currently being generated in the intensive care unit. Brain tissue oxygen protocols have yielded outcome benefits in traumatic brain injury (TBI), but the critical physiological thresholds for low brain oxygen have not been established for a dynamical patho-physiological system. High frequency, multi-modal clinical data sets from 29 patients with severe TBI who underwent multi-modality neuro-clinical care monitoring and treatment with a brain oxygen protocol were analyzed. The inter-relationship between acute physiological parameters was determined using symbolic regression (SR) as the computational framework. The mean patient age was 44.4±15 with a mean admission GCS of 6.6±3.9. Sixty-three percent sustained motor vehicle accidents and the most common pathology was intra-cerebral hemorrhage (50%). Hospital discharge mortality was 21%, poor outcome occurred in 24% of patients, and good outcome occurred in 56% of patients. Criticality for low brain oxygen was intracranial pressure (ICP) ≥22.8 mm Hg, for mortality at ICP≥37.1 mm Hg. The upper therapeutic threshold for cerebral perfusion pressure (CPP) was 75 mm Hg. Eubaric hyperoxia significantly impacted partial pressure of oxygen in brain tissue (PbtO2) at all ICP levels. Optimal brain temperature (Tbr) was 34-35°C, with an adverse effect when Tbr≥38°C. Survivors clustered at [Formula: see text] Hg vs. non-survivors [Formula: see text] 18 mm Hg. There were two mortality clusters for ICP: High ICP/low PbtO2 and low ICP/low PbtO2. Survivors maintained PbtO2 at all ranges of mean arterial pressure in contrast to non-survivors. The final SR equation for cerebral oxygenation is: [Formula: see text]. The SR-model of acute TBI advances new physiological thresholds or boundary conditions for acute TBI management: PbtO2≥25 mmHg; ICP≤22 mmHg; CPP≈60-75�

Electromagnetic brain imaging

International Nuclear Information System (INIS)

Sekihara, Kensuke

2008-01-01

Present imaging methods of cerebral neuro-activity like brain functional MRI and positron emission tomography (PET) secondarily measure only average activities within a time of the second-order (low time-resolution). In contrast, the electromagnetic brain imaging (EMBI) directly measures the faint magnetic field (10 -12 -10 -13 T) yielded by the cerebral activity with use of multiple arrayed sensors equipped on the head surface within a time of sub-millisecond order (high time-resolution). The sensor array technology to find the signal source from the measured data is common in wide areas like signal procession for radar, sonar, and epicenter detection by seismic wave. For estimating and reconstructing the active region in the brain in EMBI, the efficient method must be developed and this paper describes the direct and inverse problems concerned in signal and image processions of EMBI. The direct problem involves the cerebral magnetic field/lead field matrix and inverse problem for reconstruction of signal source, the MUSIC (multiple signal classification) algorithm, GLRT (generalized likelihood ratio test) scan, and adaptive beamformer. As an example, given are results of magnetic intensity changes (unit, fT) in the somatosensory cortex vs time (msec) measured by 160 sensors and of images reconstructed from EMBI and MRI during electric muscle afferent input from the hand. The real-time imaging is thus possible with EMBI and extremely, the EMBI image, the real-time cerebral signals, can inversely operate a machine, of which application directs toward the brain/machine interface development. (R.T.)

Insulin prevents mitochondrial generation of H₂O₂ in rat brain.

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Muller, Alexandre Pastoris; Haas, Clarissa Branco; Camacho-Pereira, Juliana; Brochier, Andressa Wigner; Gnoatto, Jussânia; Zimmer, Eduardo Rigon; de Souza, Diogo Onofre; Galina, Antonio; Portela, Luis Valmor

2013-09-01

The mitochondrial electron transport system (ETS) is a main source of cellular ROS, including hydrogen peroxide (H₂O₂). The production of H₂O₂ also involves the mitochondrial membrane potential (ΔΨm) and oxygen consumption. Impaired insulin signaling causes oxidative neuronal damage and places the brain at risk of neurodegeneration. We evaluated whether insulin signaling cross-talks with ETS components (complexes I and F₀F₁ATP synthase) and ΔΨm to regulate mitochondrial H₂O₂ production, in tissue preparations from rat brain. Insulin (50 to 100 ng/mL) decreased H₂O₂ production in synaptosomal preparations in high Na(+) buffer (polarized state), stimulated by glucose and pyruvate, without affecting the oxygen consumption. In addition, insulin (10 to 100 ng/mL) decreased H₂O₂ production induced by succinate in synaptosomes in high K(+) (depolarized state), whereas wortmannin and LY290042, inhibitors of the PI3K pathway, reversed this effect; heated insulin had no effect. Insulin decreased H₂O₂ production when complexes I and F₀F₁ATP synthase were inhibited by rotenone and oligomycin respectively suggesting a target effect on complex III. Also, insulin prevented the generation of maximum level of ∆Ψm induced by succinate. The PI3K inhibitors and heated insulin maintained the maximum level of ∆Ψm induced by succinate in synaptosomes in a depolarized state. Similarly, insulin decreased ROS production in neuronal cultures. In mitochondrial preparations, insulin neither modulated H2O2 production or oxygen consumption. In conclusion, the normal downstream insulin receptor signaling is necessary to regulate complex III of ETS avoiding the generation of maximal ∆Ψm and increased mitochondrial H2O2 production. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimization of parameter values for complex pulse sequences by simulated annealing: application to 3D MP-RAGE imaging of the brain.

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Epstein, F H; Mugler, J P; Brookeman, J R

1994-02-01

A number of pulse sequence techniques, including magnetization-prepared gradient echo (MP-GRE), segmented GRE, and hybrid RARE, employ a relatively large number of variable pulse sequence parameters and acquire the image data during a transient signal evolution. These sequences have recently been proposed and/or used for clinical applications in the brain, spine, liver, and coronary arteries. Thus, the need for a method of deriving optimal pulse sequence parameter values for this class of sequences now exists. Due to the complexity of these sequences, conventional optimization approaches, such as applying differential calculus to signal difference equations, are inadequate. We have developed a general framework for adapting the simulated annealing algorithm to pulse sequence parameter value optimization, and applied this framework to the specific case of optimizing the white matter-gray matter signal difference for a T1-weighted variable flip angle 3D MP-RAGE sequence. Using our algorithm, the values of 35 sequence parameters, including the magnetization-preparation RF pulse flip angle and delay time, 32 flip angles in the variable flip angle gradient-echo acquisition sequence, and the magnetization recovery time, were derived. Optimized 3D MP-RAGE achieved up to a 130% increase in white matter-gray matter signal difference compared with optimized 3D RF-spoiled FLASH with the same total acquisition time. The simulated annealing approach was effective at deriving optimal parameter values for a specific 3D MP-RAGE imaging objective, and may be useful for other imaging objectives and sequences in this general class.

CD25 and CD69 induction by α4β1 outside-in signalling requires TCR early signalling complex proteins

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Cimo, Ann-Marie; Ahmed, Zamal; McIntyre, Bradley W.; Lewis, Dorothy E.; Ladbury, John E.

2013-01-01

Distinct signalling pathways producing diverse cellular outcomes can utilize similar subsets of proteins. For example, proteins from the TCR (T-cell receptor) ESC (early signalling complex) are also involved in interferon-α receptor signalling. Defining the mechanism for how these proteins function within a given pathway is important in understanding the integration and communication of signalling networks with one another. We investigated the contributions of the TCR ESC proteins Lck (lymphocyte-specific kinase), ZAP-70 (ζ-chain-associated protein of 70 kDa), Vav1, SLP-76 [SH2 (Src homology 2)-domain-containing leukocyte protein of 76 kDa] and LAT (linker for activation of T-cells) to integrin outside-in signalling in human T-cells. Lck, ZAP-70, SLP-76, Vav1 and LAT were activated by α4β1 outside-in signalling, but in a manner different from TCR signalling. TCR stimulation recruits ESC proteins to activate the mitogen-activated protein kinase ERK (extracellular-signal-regulated kinase). α4β1 outside-in-mediated ERK activation did not require TCR ESC proteins. However, α4β1 outside-in signalling induced CD25 and co-stimulated CD69 and this was dependent on TCR ESC proteins. TCR and α4β1 outside-in signalling are integrated through the common use of TCR ESC proteins; however, these proteins display functionally distinct roles in these pathways. These novel insights into the cross-talk between integrin outside-in and TCR signalling pathways are highly relevant to the development of therapeutic strategies to overcome disease associated with T-cell deregulation. PMID:23758320

Contribution of altered signal transduction associated to glutamate receptors in brain to the neurological alterations of hepatic encephalopathy

Institute of Scientific and Technical Information of China (English)

Vicente Felipo

2006-01-01

Patients with liver disease may present hepatic encephalopathy (HE), a complex neuropsychiatric syndrome covering a wide range of neurological alterations,including cognitive and motor disturbances. HE reduces the quality of life of the patients and is associated with poor prognosis. In the worse cases HE may lead to coma or death.The mechanisms leading to HE which are not well known are being studied using animal models. The neurological alterations in HE are a consequence of impaired cerebral function mainly due to alterations in neurotransmission. We review here some studies indicating that alterations in neurotransmission associated to different types of glutamate receptors are responsible for some of the cognitive and motor alterations present in HE.These studies show that the function of the signal transduction pathway glutamate-nitric oxide-cGMP associated to the NMDA type of glutamate receptors is impaired in brain in vivo in HE animal models as well as in brain of patients died of HE. Activation of NMDA receptors in brain activates this pathway and increases cGMP. In animal models of HE this increase in cGMP induced by activation of NMDA receptors is reduced,which is responsible for the impairment in learning ability in these animal models. Increasing cGMP by pharmacological means restores learning ability in rats with HE and may be a new therapeutic approach to improve cognitive function in patients with HE.However, it is necessary to previously assess the possible secondary effects.Patients with HE may present psychomotor slowing,hypokinesia and bradykinesia. Animal models of HE also show hypolocomotion. It has been shown in rats with HE that hypolocomotion is due to excessive activation of metabotropic glutamate receptors (mGluRs) in substantia nigra pars reticulata. Blocking mGluR1 in this brain area normalizes motor activity in the rats, suggesting that a similar treatment for patients with HE could be useful to treat psychomotor slowing and

Wnt3a upregulates brain-derived insulin by increasing NeuroD1 via Wnt/β-catenin signaling in the hypothalamus.

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Lee, Jaemeun; Kim, Kyungchan; Yu, Seong-Woon; Kim, Eun-Kyoung

2016-03-08

Insulin plays diverse roles in the brain. Although insulin produced by pancreatic β-cells that crosses the blood-brain barrier is a major source of brain insulin, recent studies suggest that insulin is also produced locally within the brain. However, the mechanisms underlying the production of brain-derived insulin (BDI) are not yet known. Here, we examined the effect of Wnt3a on BDI production in a hypothalamic cell line and hypothalamic tissue. In N39 hypothalamic cells, Wnt3a treatment significantly increased the expression of the Ins2 gene, which encodes the insulin isoform predominant in the mouse brain, by activating Wnt/β-catenin signaling. The concentration of insulin was higher in culture medium of Wnt3a-treated cells than in that of untreated cells. Interestingly, neurogenic differentiation 1 (NeuroD1), a target of Wnt/β-catenin signaling and one of transcription factors for insulin, was also induced by Wnt3a treatment in a time- and dose-dependent manner. In addition, the treatment of BIO, a GSK3 inhibitor, also increased the expression of Ins2 and NeuroD1. Knockdown of NeuroD1 by lentiviral shRNAs reduced the basal expression of Ins2 and suppressed Wnt3a-induced Ins2 expression. To confirm the Wnt3a-induced increase in Ins2 expression in vivo, Wnt3a was injected into the hypothalamus of mice. Wnt3a increased the expression of NeuroD1 and Ins2 in the hypothalamus in a manner similar to that observed in vitro. Taken together, these results suggest that BDI production is regulated by the Wnt/β-catenin/NeuroD1 pathway in the hypothalamus. Our findings will help to unravel the regulation of BDI production in the hypothalamus.

Jasmonate signalling in Arabidopsis involves SGT1b-HSP70-HSP90 chaperone complexes.

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Zhang, Xue-Cheng; Millet, Yves A; Cheng, Zhenyu; Bush, Jenifer; Ausubel, Frederick M

Plant hormones play pivotal roles in growth, development and stress responses. Although it is essential to our understanding of hormone signalling, how plants maintain a steady state level of hormone receptors is poorly understood. We show that mutation of the Arabidopsis thaliana co-chaperone SGT1b impairs responses to the plant hormones jasmonate, auxin and gibberellic acid, but not brassinolide and abscisic acid, and that SGT1b and its homologue SGT1a are involved in maintaining the steady state levels of the F-box proteins COI1 and TIR1, receptors for jasmonate and auxin, respectively. The association of SGT1b with COI1 is direct and is independent of the Arabidopsis SKP1 protein, ASK1. We further show that COI1 is a client protein of SGT1b-HSP70-HSP90 chaperone complexes and that the complexes function in hormone signalling by stabilizing the COI1 protein. This study extends the SGT1b-HSP90 client protein list and broadens the functional scope of SGT1b-HSP70-HSP90 chaperone complexes.

Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis.

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Philipp S Orekhov

2015-10-01

Full Text Available Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors.

An Evolutionarily Conserved Network Mediates Development of the zona limitans intrathalamica, a Sonic Hedgehog-Secreting Caudal Forebrain Signaling Center

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Elena Sena

2016-10-01

Full Text Available Recent studies revealed new insights into the development of a unique caudal forebrain-signaling center: the zona limitans intrathalamica (zli. The zli is the last brain signaling center to form and the first forebrain compartment to be established. It is the only part of the dorsal neural tube expressing the morphogen Sonic Hedgehog (Shh whose activity participates in the survival, growth and patterning of neuronal progenitor subpopulations within the thalamic complex. Here, we review the gene regulatory network of transcription factors and cis-regulatory elements that underlies formation of a shh-expressing delimitated domain in the anterior brain. We discuss evidence that this network predates the origin of chordates. We highlight the contribution of Shh, Wnt and Notch signaling to zli development and discuss implications for the fact that the morphogen Shh relies on primary cilia for signal transduction. The network that underlies zli development also contributes to thalamus induction, and to its patterning once the zli has been set up. We present an overview of the brain malformations possibly associated with developmental defects in this gene regulatory network (GRN.

Synthesis characterization and biological evaluation of a novel mixed ligand 99mTc complex as potential brain imaging agent

International Nuclear Information System (INIS)

Rey, A.; Manta, E.; Leon, A.; Papadopoulos, M.; Pirmettis, Y.; Raptopoulou, C.; Chiotellis, E.; Leon, E.; Mallo, L.

1998-01-01

One approach in the design of neutral oxotechnetium complexes is based on the simultaneous substitution of a tridentate dianionic ligand and a monodentate monoanionic coligand on a [Tc(V)O] +3 precursor. Following this ''mixed ligand'' concept, a novel 99m Tc complex with N,N-bis(2-mercaptoethyl)-N'N'-diethylethylenediamine as ligand and 1-octanethiol as coligand is prepared and evaluated as potential brain radiopharmaceutical. Preparation of the complex at tracer level was accomplished by using 99m Tc-glucoheptonate as precursor. The substitution was optimized and a coligand/ligand ratio of 5 was selected. Under this conditions the labeling yield was over 80% and a major product (with radiochemical purity > 80%) was isolated by HPLC methods and used for biological evaluation. Chemical characterization at carrier level was developed using the corresponding rhenium complex as structural model. The Re complex was also prepared by substitution method and isolated as a crystalline product. The crystals were characterized by UV-vis and IR spectra and elemental analysis. Results were consistent with the expected ReOLC structure. X ray crystallographic study demonstrated that the complex adopts a distorted trigonal bipyramidal geometry. The basal plane is defined by the SS atoms of the ligand and the oxo group, while the N of the ligand and the S of the colligand occupy the two apical positions. All sulphur atoms underwent ionization leading to the formation of a neutral compound. 99 Tc complex was also prepared. Although it was not isolated due to the small amount of reagents employed, the HPLC profile was identical to the one observed for the rhenium complex suggesting the same chemical structure. Biodistribution in mice demonstrated early brain uptake, fast blood clearance, excretion through hepatobiliary system and a brain/blood ratio that increased significantly with time. (author)

Clear signals or mixed messages: inter-individual emotion congruency modulates brain activity underlying affective body perception

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de Gelder, B.

2016-01-01

The neural basis of emotion perception has mostly been investigated with single face or body stimuli. However, in daily life one may also encounter affective expressions by groups, e.g. an angry mob or an exhilarated concert crowd. In what way is brain activity modulated when several individuals express similar rather than different emotions? We investigated this question using an experimental design in which we presented two stimuli simultaneously, with same or different emotional expressions. We hypothesized that, in the case of two same-emotion stimuli, brain activity would be enhanced, while in the case of two different emotions, one emotion would interfere with the effect of the other. The results showed that the simultaneous perception of different affective body expressions leads to a deactivation of the amygdala and a reduction of cortical activity. It was revealed that the processing of fearful bodies, compared with different-emotion bodies, relied more strongly on saliency and action triggering regions in inferior parietal lobe and insula, while happy bodies drove the occipito-temporal cortex more strongly. We showed that this design could be used to uncover important differences between brain networks underlying fearful and happy emotions. The enhancement of brain activity for unambiguous affective signals expressed by several people simultaneously supports adaptive behaviour in critical situations. PMID:27025242

[The P300-based brain-computer interface: presentation of the complex "flash + movement" stimuli].

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Ganin, I P; Kaplan, A Ia

2014-01-01

The P300 based brain-computer interface requires the detection of P300 wave of brain event-related potentials. Most of its users learn the BCI control in several minutes and after the short classifier training they can type a text on the computer screen or assemble an image of separate fragments in simple BCI-based video games. Nevertheless, insufficient attractiveness for users and conservative stimuli organization in this BCI may restrict its integration into real information processes control. At the same time initial movement of object (motion-onset stimuli) may be an independent factor that induces P300 wave. In current work we checked the hypothesis that complex "flash + movement" stimuli together with drastic and compact stimuli organization on the computer screen may be much more attractive for user while operating in P300 BCI. In 20 subjects research we showed the effectiveness of our interface. Both accuracy and P300 amplitude were higher for flashing stimuli and complex "flash + movement" stimuli compared to motion-onset stimuli. N200 amplitude was maximal for flashing stimuli, while for "flash + movement" stimuli and motion-onset stimuli it was only a half of it. Similar BCI with complex stimuli may be embedded into compact control systems requiring high level of user attention under impact of negative external effects obstructing the BCI control.

Brain MR imaging in patients with hepatic cirrhosis: relationship between high intensity signal in basal ganglia on T1-weighted images and elemental concentrations in brain

International Nuclear Information System (INIS)

Maeda, H.; Sato, M.; Yoshikawa, A.; Kimura, M.; Sonomura, T.; Terada, M.; Kishi, K.

1997-01-01

In patients with hepatic cirrhosis, the globus pallidus and putamen show high intensity on T1-weighted MRI. While the causes of this high signal have been thought to include paramagnetic substances, especially manganese, no evidence for this has been presented. Autopsy in four cases of hepatic cirrhosis permitted measurement of metal concentrations in brain and histopathological examination. In three cases the globus pallidus showed high intensity on T1-weighted images. Mean manganese concentrations in globus pallidus, putamen and frontal white matter were 3.03 ± 0.38, 2.12 ± 0.37, and 1.38 ± 0.24 (μg/g wet weight), respectively, being approximately four- to almost ten-fold the normal values. Copper concentrations in globus pallidus and putamen were also high, 50 % more than normal. Calcium, iron, zinc and magnesium concentrations were all normal. The fourth case showed no abnormal intensity in the basal ganglia and brain metal concentrations were all normal. Histopathologically, cases with showing high signal remarkable atrophy, necrosis, and deciduation of nerve cells and proliferation of glial cells and microglia in globus pallidus. These findings were similar to those in chronic manganese poisoning. On T1-weighted images, copper deposition shows no abnormal intensity. It is therefore inferred that deposition of highly concentrations of manganese may caused high signal on T1-weighted images and nerve cell death in the globus pallidus. (orig.). With 2 figs., 2 tabs

Anatomical and functional assemblies of brain BOLD oscillations

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Baria, Alexis T.; Baliki, Marwan N.; Parrish, Todd; Apkarian, A. Vania

2011-01-01

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD). Resting state BOLD signal was transformed into frequency space (Welch’s method), averaged across subjects, and its spatial distribution studied as a function of four frequency bands, spanning the full bandwidth of BOLD. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann Areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), vs. complex properties (transmodal), are dominated by low frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking frequency properties of BOLD to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxel-wise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs. PMID:21613505

The winner takes it all: Event-related brain potentials reveal enhanced motivated attention toward athletes' nonverbal signals of leading.

Science.gov (United States)

Furley, Philip; Schnuerch, Robert; Gibbons, Henning

2017-08-01

Observers of sports can reliably estimate who is leading or trailing based on nonverbal cues. Most likely, this is due to an adaptive mechanism of detecting motivationally relevant signals such as high status, superiority, and dominance. We reasoned that the relevance of leading athletes should lead to a sustained attentional prioritization. To test this idea, we recorded electroencephalography while 45 participants saw brief stills of athletes and estimated whether they were leading or trailing. Based on these recordings, we assessed event-related potentials and focused on the late positive complex (LPC), a well-established signature of controlled attention to motivationally relevant visual stimuli. Confirming our expectation, we found that LPC amplitude was significantly enhanced for leading as compared to trailing athletes. Moreover, this modulation was significantly related to behavioral performance on the score-estimation task. The present data suggest that subtle cues related to athletic supremacy are reliably differentiated in the human brain, involving a strong attentional orienting toward leading athletes. This mechanism might be part of an adaptive cognitive strategy that guides human social behavior.

Wogonin improves histological and functional outcomes, and reduces activation of TLR4/NF-κB signaling after experimental traumatic brain injury.

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Chien-Cheng Chen

Full Text Available Traumatic brain injury (TBI initiates a neuroinflammatory cascade that contributes to neuronal damage and behavioral impairment. This study was undertaken to investigate the effects of wogonin, a flavonoid with potent anti-inflammatory properties, on functional and histological outcomes, brain edema, and toll-like receptor 4 (TLR4- and nuclear factor kappa B (NF-κB-related signaling pathways in mice following TBI.Mice subjected to controlled cortical impact injury were injected with wogonin (20, 40, or 50 mg·kg(-1 or vehicle 10 min after injury. Behavioral studies, histology analysis, and measurement of blood-brain barrier (BBB permeability and brain water content were carried out to assess the effects of wogonin. Levels of TLR4/NF-κB-related inflammatory mediators were also examined. Treatment with 40 mg·kg(-1 wogonin significantly improved functional recovery and reduced contusion volumes up to post-injury day 28. Wogonin also significantly reduced neuronal death, BBB permeability, and brain edema beginning at day 1. These changes were associated with a marked reduction in leukocyte infiltration, microglial activation, TLR4 expression, NF-κB translocation to nucleus and its DNA binding activity, matrix metalloproteinase-9 activity, and expression of inflammatory mediators, including interleukin-1β, interleukin-6, macrophage inflammatory protein-2, and cyclooxygenase-2.Our results show that post-injury wogonin treatment improved long-term functional and histological outcomes, reduced brain edema, and attenuated the TLR4/NF-κB-mediated inflammatory response in mouse TBI. The neuroprotective effects of wogonin may be related to modulation of the TLR4/NF-κB signaling pathway.

Pseudo-stokes vector from complex signal representation of a speckle pattern and its applications to micro-displacement measurement

DEFF Research Database (Denmark)

Wang, W.; Ishijima, R.; Matsuda, A.

2010-01-01

As an improvement of the intensity correlation used widely in conventional electronic speckle photography, we propose a new technique for displacement measurement based on correlating Stokes-like parameters derivatives for transformed speckle patterns. The method is based on a Riesz transform of ...... are presented that demonstrate the validity and advantage of the proposed pseudo-Stokes vector correlation technique over conventional intensity correlation technique....... of the intensity speckle pattern, which converts the original real-valued signal into a complex signal. In closest analogy to the polarisation of a vector wave, the Stokes-like vector constructed from the spatial derivative of the generated complex signal has been applied for correlation. Experimental results...

A lossless multichannel bio-signal compression based on low-complexity joint coding scheme for portable medical devices.

Science.gov (United States)

Kim, Dong-Sun; Kwon, Jin-San