Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

NASA Astrophysics Data System (ADS)

Doronina-Amitonova, L. V.; Fedotov, I. V.; Ivashkina, O. I.; Zots, M. A.; Fedotov, A. B.; Anokhin, K. V.; Zheltikov, A. M.

2013-11-01

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.

PubMed

Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B

2014-03-19

Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Near-Infrared Fluorescent Nanoprobes for Revealing the Role of Dopamine in Drug Addiction.

PubMed

Feng, Peijian; Chen, Yulei; Zhang, Lei; Qian, Cheng-Gen; Xiao, Xuanzhong; Han, Xu; Shen, Qun-Dong

2018-02-07

Brain imaging techniques enable visualizing the activity of central nervous system without invasive neurosurgery. Dopamine is an important neurotransmitter. Its fluctuation in brain leads to a wide range of diseases and disorders, like drug addiction, depression, and Parkinson's disease. We designed near-infrared fluorescence dopamine-responsive nanoprobes (DRNs) for brain activity imaging during drug abuse and addiction process. On the basis of light-induced electron transfer between DRNs and dopamine and molecular wire effect of the DRNs, we can track the dynamical change of the neurotransmitter level in the physiological environment and the releasing of the neurotransmitter in living dopaminergic neurons in response to nicotine stimulation. The functional near-infrared fluorescence imaging can dynamically track the dopamine level in the mice midbrain under normal or drug-activated condition and evaluate the long-term effect of addictive substances to the brain. This strategy has the potential for studying neural activity under physiological condition.

Dynamic contrast-enhanced MR imaging pharmacokinetic parameters as predictors of treatment response of brain metastases in patients with lung cancer.

PubMed

Kuchcinski, Grégory; Le Rhun, Emilie; Cortot, Alexis B; Drumez, Elodie; Duhal, Romain; Lalisse, Maxime; Dumont, Julien; Lopes, Renaud; Pruvo, Jean-Pierre; Leclerc, Xavier; Delmaire, Christine

2017-09-01

To determine the diagnostic accuracy of pharmacokinetic parameters measured by dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in predicting the response of brain metastases to antineoplastic therapy in patients with lung cancer. Forty-four consecutive patients with lung cancer, harbouring 123 newly diagnosed brain metastases prospectively underwent conventional 3-T MRI at baseline (within 1 month before treatment), during the early (7-10 weeks) and midterm (5-7 months) post-treatment period. An additional DCE MRI sequence was performed during baseline and early post-treatment MRI to evaluate baseline pharmacokinetic parameters (K trans , k ep , v e , v p ) and their early variation (∆K trans , ∆k ep , ∆v e , ∆v p ). The objective response was judged by the volume variation of each metastasis from baseline to midterm MRI. ROC curve analysis determined the best DCE MRI parameter to predict the objective response. Baseline DCE MRI parameters were not associated with the objective response. Early ∆K trans , ∆v e and ∆v p were significantly associated with the objective response (p = 0.02, p = 0.001 and p = 0.02, respectively). The best predictor of objective response was ∆v e with an area under the curve of 0.93 [95% CI = 0.87, 0.99]. DCE MRI and early ∆v e may be a useful tool to predict the objective response of brain metastases in patients with lung cancer. • DCE MRI could predict the response of brain metastases from lung cancer • ∆v e was the best predictor of response • DCE MRI could be used to individualize patients' follow-up.

Dynamic Target Match Signals in Perirhinal Cortex Can Be Explained by Instantaneous Computations That Act on Dynamic Input from Inferotemporal Cortex

PubMed Central

Pagan, Marino

2014-01-01

Finding sought objects requires the brain to combine visual and target signals to determine when a target is in view. To investigate how the brain implements these computations, we recorded neural responses in inferotemporal cortex (IT) and perirhinal cortex (PRH) as macaque monkeys performed a delayed-match-to-sample target search task. Our data suggest that visual and target signals were combined within or before IT in the ventral visual pathway and then passed onto PRH, where they were reformatted into a more explicit target match signal over ∼10–15 ms. Accounting for these dynamics in PRH did not require proposing dynamic computations within PRH itself but, rather, could be attributed to instantaneous PRH computations performed upon an input representation from IT that changed with time. We found that the dynamics of the IT representation arose from two commonly observed features: individual IT neurons whose response preferences were not simply rescaled with time and variable response latencies across the population. Our results demonstrate that these types of time-varying responses have important consequences for downstream computation and suggest that dynamic representations can arise within a feedforward framework as a consequence of instantaneous computations performed upon time-varying inputs. PMID:25122904

Dynamic glucose enhanced (DGE) MRI for combined imaging of blood-brain barrier break down and increased blood volume in brain cancer.

PubMed

Xu, Xiang; Chan, Kannie W Y; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T; van Zijl, Peter C M

2015-12-01

Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared with contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (P < 0.005). Both CEST and relaxation effects contribute to the signal change. DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. © 2015 Wiley Periodicals, Inc.

Dynamic Glucose Enhanced (DGE) MRI for Combined Imaging of Blood Brain Barrier Break Down and Increased Blood Volume in Brain Cancer

PubMed Central

Xu, Xiang; Chan, Kannie WY; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T.; van Zijl, Peter C.M.

2015-01-01

Purpose Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Methods Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. Results DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared to contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (p<0.005). Both CEST and relaxation effects contribute to the signal change. Conclusion DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. PMID:26404120

Brain Research, Learning and Emotions: Implications for Education Research, Policy and Practice

ERIC Educational Resources Information Center

Hinton, Christina; Miyamoto, Koji; Della-Chiesa, Bruno

2008-01-01

Recent advancements in neuroscience heighten its relevance to education. Newly developed imaging technologies enable scientists to peer into the working brain for the first time, providing powerful insights into how we learn. Research reveals that the brain is not a stable and isolated entity, but a dynamic system that is keenly responsive to…

WINCS Harmoni: Closed-loop dynamic neurochemical control of therapeutic interventions

NASA Astrophysics Data System (ADS)

Lee, Kendall H.; Lujan, J. Luis; Trevathan, James K.; Ross, Erika K.; Bartoletta, John J.; Park, Hyung Ook; Paek, Seungleal Brian; Nicolai, Evan N.; Lee, Jannifer H.; Min, Hoon-Ki; Kimble, Christopher J.; Blaha, Charles D.; Bennet, Kevin E.

2017-04-01

There has been significant progress in understanding the role of neurotransmitters in normal and pathologic brain function. However, preclinical trials aimed at improving therapeutic interventions do not take advantage of real-time in vivo neurochemical changes in dynamic brain processes such as disease progression and response to pharmacologic, cognitive, behavioral, and neuromodulation therapies. This is due in part to a lack of flexible research tools that allow in vivo measurement of the dynamic changes in brain chemistry. Here, we present a research platform, WINCS Harmoni, which can measure in vivo neurochemical activity simultaneously across multiple anatomical targets to study normal and pathologic brain function. In addition, WINCS Harmoni can provide real-time neurochemical feedback for closed-loop control of neurochemical levels via its synchronized stimulation and neurochemical sensing capabilities. We demonstrate these and other key features of this platform in non-human primate, swine, and rodent models of deep brain stimulation (DBS). Ultimately, systems like the one described here will improve our understanding of the dynamics of brain physiology in the context of neurologic disease and therapeutic interventions, which may lead to the development of precision medicine and personalized therapies for optimal therapeutic efficacy.

Plasticity of brain wave network interactions and evolution across physiologic states

PubMed Central

Liu, Kang K. L.; Bartsch, Ronny P.; Lin, Aijing; Mantegna, Rosario N.; Ivanov, Plamen Ch.

2015-01-01

Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function. PMID:26578891

The measurement of intracranial pressure and brain displacement due to short-duration dynamic overpressure loading

NASA Astrophysics Data System (ADS)

Iwaskiw, A. S.; Ott, K. A.; Armiger, R. S.; Wickwire, A. C.; Alphonse, V. D.; Voo, L. M.; Carneal, C. M.; Merkle, A. C.

2018-01-01

The experimental measurement of biomechanical responses that correlate with blast-induced traumatic brain injury (bTBI) has proven challenging. These data are critical for both the development and validation of computational and physical head models, which are used to quantify the biomechanical response to blast as well as to assess fidelity of injury mitigation strategies, such as personal protective equipment. Therefore, foundational postmortem human surrogate (PMHS) experimental data capturing the biomechanical response are necessary for human model development. Prior studies have measured short-duration pressure transmission to the brain (Kinetic phase), but have failed to reproduce and measure the longer-duration inertial loading that can occur (Kinematic phase). Four fully instrumented PMHS were subjected to short-duration dynamic overpressure in front-facing and rear-facing orientations, where intracranial pressure (ICP), global head kinematics, and brain motion (as measured by high-speed X-ray) with respect to the skull were recorded. Peak ICP results generally increased with increased dose, and a mirrored pressure response was seen when comparing the polarity of frontal bone versus occipital bone ICP sensors. The head kinematics were delayed when compared to the pressure response and showed higher peak angles for front-facing tests as compared to rear-facing. Brain displacements were approximately 2-6 mm, and magnitudes did not change appreciably between front- and rear-facing tests. These data will be used to inform and validate models used to assess bTBI.

Dynamic range in the C. elegans brain network

NASA Astrophysics Data System (ADS)

Antonopoulos, Chris G.

2016-01-01

We study external electrical perturbations and their responses in the brain dynamic network of the Caenorhabditis elegans soil worm, given by the connectome of its large somatic nervous system. Our analysis is inspired by a realistic experiment where one stimulates externally specific parts of the brain and studies the persistent neural activity triggered in other cortical regions. In this work, we perturb groups of neurons that form communities, identified by the walktrap community detection method, by trains of stereotypical electrical Poissonian impulses and study the propagation of neural activity to other communities by measuring the corresponding dynamic ranges and Steven law exponents. We show that when one perturbs specific communities, keeping the rest unperturbed, the external stimulations are able to propagate to some of them but not to all. There are also perturbations that do not trigger any response. We found that this depends on the initially perturbed community. Finally, we relate our findings for the former cases with low neural synchronization, self-criticality, and large information flow capacity, and interpret them as the ability of the brain network to respond to external perturbations when it works at criticality and its information flow capacity becomes maximal.

A brief historical perspective on the advent of brain oscillations in the biological and psychological disciplines.

PubMed

Karakaş, Sirel; Barry, Robert J

2017-04-01

We aim to review the historical evolution that has led to the study of the brain (body)-mind relationship based on brain oscillations, to outline and illustrate the principles of neuro-oscillatory dynamics using research findings. The paper addresses the relevant developments in behavioral sciences after Wundt established the science of psychology, and developments in the neurosciences after alpha and gamma oscillations were discovered by Berger and Adrian, respectively. Basic neuroscientific studies have led to a number of principles: (1) spontaneous EEG is composed of a set of oscillatory components, (2) the brain responds with oscillatory activity, (3) poststimulus oscillatory activity is a function of prestimulus activity, (4) the brain response results from a superposition of oscillatory components, (5) there are multiplicities with regard to oscillations and functions, and (6) oscillations are spatially integrated. Findings of clinical studies suggest that oscillatory responses can serve as biomarkers for neuropsychiatric disorders. However, the field of psychology is still making limited use of neuro-oscillatory dynamics for a bio-behavioral understanding of cognitive-affective processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Human Nervous System: A Framework for Teaching and the Teaching Brain

ERIC Educational Resources Information Center

Rodriguez, Vanessa

2013-01-01

The teaching brain is a new concept that mirrors the complex, dynamic, and context-dependent nature of the learning brain. In this article, I use the structure of the human nervous system and its sensing, processing, and responding components as a framework for a re-conceptualized teaching system. This teaching system is capable of responses on an…

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

PubMed

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

2017-05-08

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

Dynamic musical communication of core affect

PubMed Central

Flaig, Nicole K.; Large, Edward W.

2013-01-01

Is there something special about the way music communicates feelings? Theorists since Meyer (1956) have attempted to explain how music could stimulate varied and subtle affective experiences by violating learned expectancies, or by mimicking other forms of social interaction. Our proposal is that music speaks to the brain in its own language; it need not imitate any other form of communication. We review recent theoretical and empirical literature, which suggests that all conscious processes consist of dynamic neural events, produced by spatially dispersed processes in the physical brain. Intentional thought and affective experience arise as dynamical aspects of neural events taking place in multiple brain areas simultaneously. At any given moment, this content comprises a unified “scene” that is integrated into a dynamic core through synchrony of neuronal oscillations. We propose that (1) neurodynamic synchrony with musical stimuli gives rise to musical qualia including tonal and temporal expectancies, and that (2) music-synchronous responses couple into core neurodynamics, enabling music to directly modulate core affect. Expressive music performance, for example, may recruit rhythm-synchronous neural responses to support affective communication. We suggest that the dynamic relationship between musical expression and the experience of affect presents a unique opportunity for the study of emotional experience. This may help elucidate the neural mechanisms underlying arousal and valence, and offer a new approach to exploring the complex dynamics of the how and why of emotional experience. PMID:24672492

Dynamic musical communication of core affect.

PubMed

Flaig, Nicole K; Large, Edward W

2014-01-01

Is there something special about the way music communicates feelings? Theorists since Meyer (1956) have attempted to explain how music could stimulate varied and subtle affective experiences by violating learned expectancies, or by mimicking other forms of social interaction. Our proposal is that music speaks to the brain in its own language; it need not imitate any other form of communication. We review recent theoretical and empirical literature, which suggests that all conscious processes consist of dynamic neural events, produced by spatially dispersed processes in the physical brain. Intentional thought and affective experience arise as dynamical aspects of neural events taking place in multiple brain areas simultaneously. At any given moment, this content comprises a unified "scene" that is integrated into a dynamic core through synchrony of neuronal oscillations. We propose that (1) neurodynamic synchrony with musical stimuli gives rise to musical qualia including tonal and temporal expectancies, and that (2) music-synchronous responses couple into core neurodynamics, enabling music to directly modulate core affect. Expressive music performance, for example, may recruit rhythm-synchronous neural responses to support affective communication. We suggest that the dynamic relationship between musical expression and the experience of affect presents a unique opportunity for the study of emotional experience. This may help elucidate the neural mechanisms underlying arousal and valence, and offer a new approach to exploring the complex dynamics of the how and why of emotional experience.

Changing Workplace.

ERIC Educational Resources Information Center

1998

This document contains four papers from a symposium on the changing workplace and its relationship to human resource development (HRD). In "Globalization, Immigration and Quality of Life Dynamics for Reverse Brain Drains" (Ben-Chieh Liu, Maw Lin Lee, Hau-Lien), the factors responsible for the brain drain from Taiwan to the United States…

Dynamic Functional Imaging of Brain Glucose Utilization using fPET-FDG

PubMed Central

Villien, Marjorie; Wey, Hsiao-Ying; Mandeville, Joseph B.; Catana, Ciprian; Polimeni, Jonathan R.; Sander, Christin Y.; Zürcher, Nicole R.; Chonde, Daniel B.; Fowler, Joanna S.; Rosen, Bruce R.; Hooker, Jacob M.

2014-01-01

Glucose is the principal source of energy for the brain and yet the dynamic response of glucose utilization to changes in brain activity is still not fully understood. Positron emission tomography (PET) allows quantitative measurement of glucose metabolism using 2-[18F]-fluorodeoxyglucose (FDG). However, FDG PET in its current form provides an integral (or average) of glucose consumption over tens of minutes and lacks the temporal information to capture physiological alterations associated with changes in brain activity induced by tasks or drug challenges. Traditionally, changes in glucose utilization are inferred by comparing two separate scans, which significantly limits the utility of the method. We report a novel method to track changes in FDG metabolism dynamically, with higher temporal resolution than exists to date and within a single session. Using a constant infusion of FDG, we demonstrate that our technique (termed fPET-FDG) can be used in an analysis pipeline similar to fMRI to define within-session differential metabolic responses. We use visual stimulation to demonstrate the feasibility of this method. This new method has a great potential to be used in research protocols and clinical settings since fPET-FDG imaging can be performed with most PET scanners and data acquisition and analysis is straightforward. fPET-FDG is a highly complementary technique to MRI and provides a rich new way to observe functional changes in brain metabolism. PMID:24936683

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

PubMed

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.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis.

PubMed

Zinchenko, Oksana; Yaple, Zachary A; Arsalidou, Marie

2018-01-01

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness

PubMed Central

Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-01-01

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly “domain general” conflict processing mechanisms, instead of conflict source specific effects. PMID:26169473

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness.

PubMed

Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-07-14

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly "domain general" conflict processing mechanisms, instead of conflict source specific effects.

A viscoelastic analysis of the P56 mouse brain under large-deformation dynamic indentation.

PubMed

MacManus, David B; Pierrat, Baptiste; Murphy, Jeremiah G; Gilchrist, Michael D

2017-01-15

The brain is a complex organ made up of many different functional and structural regions consisting of different types of cells such as neurons and glia, as well as complex anatomical geometries. It is hypothesized that the different regions of the brain exhibit significantly different mechanical properties which may be attributed to the diversity of cells within individual brain regions. The regional viscoelastic properties of P56 mouse brain tissue, up to 70μm displacement, are presented and discussed in the context of traumatic brain injury, particularly how the different regions of the brain respond to mechanical loads. Force-relaxation data obtained from micro-indentation measurements were fit to both linear and quasi-linear viscoelastic models to determine the time and frequency domain viscoelastic response of the pons, cortex, medulla oblongata, cerebellum, and thalamus. The damping ratio of each region was also determined. Each region was found to have a unique mechanical response to the applied displacement, with the pons and thalamus exhibiting the largest and smallest force-response, respectively. All brain regions appear to have an optimal frequency for the dissipation of energies which lies between 1 and 10Hz. We present the first mechanical characterization of the viscoelastic response for different regions of mouse brain. Force-relaxation tests are performed under large strain dynamic micro-indentation, and viscoelastic models are used subsequently, providing time-dependent mechanical properties of brain tissue under loading conditions comparable to what is experienced in TBI. The unique mechanical properties of different brain regions are highlighted, with substantial variations in the viscoelastic properties and damping ratio of each region. Cortex and pons were the stiffest regions, while the thalamus and medulla were most compliant. The cerebellum and thalamus had highest damping ratio values and those of the medulla were lowest. The reported material parameters can be implemented into finite element computer models of the mouse to investigate the effects of trauma on individual brain regions. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Time Course of Brain Network Reconfiguration Supporting Inhibitory Control.

PubMed

Popov, Tzvetan; Westner, Britta U; Silton, Rebecca L; Sass, Sarah M; Spielberg, Jeffrey M; Rockstroh, Brigitte; Heller, Wendy; Miller, Gregory A

2018-05-02

Hemodynamic research has recently clarified key nodes and links in brain networks implementing inhibitory control. Although fMRI methods are optimized for identifying the structure of brain networks, the relatively slow temporal course of fMRI limits the ability to characterize network operation. The latter is crucial for developing a mechanistic understanding of how brain networks shift dynamically to support inhibitory control. To address this critical gap, we applied spectrally resolved Granger causality (GC) and random forest machine learning tools to human EEG data in two large samples of adults (test sample n = 96, replication sample n = 237, total N = 333, both sexes) who performed a color-word Stroop task. Time-frequency analysis confirmed that recruitment of inhibitory control accompanied by slower behavioral responses was related to changes in theta and alpha/beta power. GC analyses revealed directionally asymmetric exchanges within frontal and between frontal and parietal brain areas: top-down influence of superior frontal gyrus (SFG) over both dorsal ACC (dACC) and inferior frontal gyrus (IFG), dACC control over middle frontal gyrus (MFG), and frontal-parietal exchanges (IFG, precuneus, MFG). Predictive analytics confirmed a combination of behavioral and brain-derived variables as the best set of predictors of inhibitory control demands, with SFG theta bearing higher classification importance than dACC theta and posterior beta tracking the onset of behavioral response. The present results provide mechanistic insight into the biological implementation of a psychological phenomenon: inhibitory control is implemented by dynamic routing processes during which the target response is upregulated via theta-mediated effective connectivity within key PFC nodes and via beta-mediated motor preparation. SIGNIFICANCE STATEMENT Hemodynamic neuroimaging research has recently clarified regional structures in brain networks supporting inhibitory control. However, due to inherent methodological constraints, much of this research has been unable to characterize the temporal dynamics of such networks (e.g., direction of information flow between nodes). Guided by fMRI research identifying the structure of brain networks supporting inhibitory control, results of EEG source analysis in a test sample ( n = 96) and replication sample ( n = 237) using effective connectivity and predictive analytics strategies advance a model of inhibitory control by characterizing the precise temporal dynamics by which this network operates and exemplify an approach by which mechanistic models can be developed for other key psychological processes. Copyright © 2018 the authors 0270-6474/18/384348-09$15.00/0.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior

PubMed Central

Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.

2014-01-01

Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252

Brain coordination dynamics: True and false faces of phase synchrony and metastability

PubMed Central

Tognoli, Emmanuelle; Kelso, J.A. Scott

2009-01-01

Understanding the coordination of multiple parts in a complex system such as the brain is a fundamental challenge. We present a theoretical model of cortical coordination dynamics that shows how brain areas may cooperate (integration) and at the same time retain their functional specificity (segregation). This model expresses a range of desirable properties that the brain is known to exhibit, including self-organization, multi-functionality, metastability and switching. Empirically, the model motivates a thorough investigation of collective phase relationships among brain oscillations in neurophysiological data. The most serious obstacle to interpreting coupled oscillations as genuine evidence of inter-areal coordination in the brain stems from volume conduction of electrical fields. Spurious coupling due to volume conduction gives rise to zero-lag (inphase) and antiphase synchronization whose magnitude and persistence obscure the subtle expression of real synchrony. Through forward modeling and the help of a novel colorimetric method, we show how true synchronization can be deciphered from continuous EEG patterns. Developing empirical efforts along the lines of continuous EEG analysis constitutes a major response to the challenge of understanding how different brain areas work together. Key predictions of cortical coordination dynamics can now be tested thereby revealing the essential modus operandi of the intact living brain. PMID:18938209

From phase transitions to the topological renaissance. Comment on "Topodynamics of metastable brains" by Arturo Tozzi et al.

NASA Astrophysics Data System (ADS)

Somogyvári, Zoltán; Érdi, Péter

2017-07-01

The neural topodynamics theory of Tozzi et al. [13] has two main foci: metastable brain dynamics and the topological approach based on the Borsuk-Ulam theorem (BUT). Briefly, metastable brain dynamics theory hypothesizes that temporary stable synchronization and desynchronization of large number of individual dynamical systems, formed by local neural circuits, are responsible for coding of complex concepts in the brain and sudden changes of these synchronization patterns correspond to operational steps. But what dynamical network could form the substrate for this metastable dynamics, capable of entering into a combinatorially high number of metastable synchronization patterns and exhibit rapid transient changes between them? The general problem is related to the discrimination between ;Black Swans; and ;Dragon Kings;. While BSs are related to the theory of self-organized criticality, and suggests that high-impact extreme events are unpredictable, Dragon-kings are associated with the occurrence of a phase transition, whose emergent organization is based on intermittent criticality [9]. Widening the limits of predictability is one of the big open problems in the theory and practice of complex systems (Sect. 9.3 of Érdi [2]).

The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

PubMed

Başar, Erol; Düzgün, Aysel

2016-05-01

Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Transcranial amelioration of inflammation and cell death after brain injury

NASA Astrophysics Data System (ADS)

Roth, Theodore L.; Nayak, Debasis; Atanasijevic, Tatjana; Koretsky, Alan P.; Latour, Lawrence L.; McGavern, Dorian B.

2014-01-01

Traumatic brain injury (TBI) is increasingly appreciated to be highly prevalent and deleterious to neurological function. At present, no effective treatment options are available, and little is known about the complex cellular response to TBI during its acute phase. To gain insights into TBI pathogenesis, we developed a novel murine closed-skull brain injury model that mirrors some pathological features associated with mild TBI in humans and used long-term intravital microscopy to study the dynamics of the injury response from its inception. Here we demonstrate that acute brain injury induces vascular damage, meningeal cell death, and the generation of reactive oxygen species (ROS) that ultimately breach the glial limitans and promote spread of the injury into the parenchyma. In response, the brain elicits a neuroprotective, purinergic-receptor-dependent inflammatory response characterized by meningeal neutrophil swarming and microglial reconstitution of the damaged glial limitans. We also show that the skull bone is permeable to small-molecular-weight compounds, and use this delivery route to modulate inflammation and therapeutically ameliorate brain injury through transcranial administration of the ROS scavenger, glutathione. Our results shed light on the acute cellular response to TBI and provide a means to locally deliver therapeutic compounds to the site of injury.

Does my brain want what my eyes like? - How food liking and choice influence spatio-temporal brain dynamics of food viewing.

PubMed

Bielser, Marie-Laure; Crézé, Camille; Murray, Micah M; Toepel, Ulrike

2016-12-01

How food valuation and decision-making influence the perception of food is of major interest to better understand food intake behavior and, by extension, body weight management. Our study investigated behavioral responses and spatio-temporal brain dynamics by means of visual evoked potentials (VEPs) in twenty-two normal-weight participants when viewing pairs of food photographs. Participants rated how much they liked each food item (valuation) and subsequently chose between the two alternative food images. Unsurprisingly, strongly liked foods were also chosen most often. Foods were rated faster as strongly liked than as mildly liked or disliked irrespective of whether they were subsequently chosen over an alternative. Moreover, strongly liked foods were subsequently also chosen faster than the less liked alternatives. Response times during valuation and choice were positively correlated, but only when foods were liked; the faster participants rated foods as strongly liked, the faster they were in choosing the food item over an alternative. VEP modulations by the level of liking attributed as well as the subsequent choice were found as early as 135-180ms after food image onset. Analyses of neural source activity patterns over this time interval revealed an interaction between liking and the subsequent choice within the insula, dorsal frontal and superior parietal regions. The neural responses to food viewing were found to be modulated by the attributed level of liking only when foods were chosen, not when they were dismissed for an alternative. Therein, the responses to disliked foods were generally greater than those to foods that were liked more. Moreover, the responses to disliked but chosen foods were greater than responses to disliked foods which were subsequently dismissed for an alternative offer. Our findings show that the spatio-temporal brain dynamics to food viewing are immediately influenced both by how much foods are liked and by choices taken on them. These valuation and choice processes are subserved by brain regions involved in salience and reward attribution as well as in decision-making processes, which are likely to influence prospective dietary choices in everyday life. Copyright © 2015 Elsevier Inc. All rights reserved.

Self-organization, free energy minimization, and optimal grip on a field of affordances

PubMed Central

Bruineberg, Jelle; Rietveld, Erik

2014-01-01

In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system “brain-body-landscape of affordances.” Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients. PMID:25161615

Self-organization, free energy minimization, and optimal grip on a field of affordances.

PubMed

Bruineberg, Jelle; Rietveld, Erik

2014-01-01

In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system "brain-body-landscape of affordances." Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients.

Manipulating the content of dynamic natural scenes to characterize response in human MT/MST.

PubMed

Durant, Szonya; Wall, Matthew B; Zanker, Johannes M

2011-09-09

Optic flow is one of the most important sources of information for enabling human navigation through the world. A striking finding from single-cell studies in monkeys is the rapid saturation of response of MT/MST areas with the density of optic flow type motion information. These results are reflected psychophysically in human perception in the saturation of motion aftereffects. We began by comparing responses to natural optic flow scenes in human visual brain areas to responses to the same scenes with inverted contrast (photo negative). This changes scene familiarity while preserving local motion signals. This manipulation had no effect; however, the response was only correlated with the density of local motion (calculated by a motion correlation model) in V1, not in MT/MST. To further investigate this, we manipulated the visible proportion of natural dynamic scenes and found that areas MT and MST did not increase in response over a 16-fold increase in the amount of information presented, i.e., response had saturated. This makes sense in light of the sparseness of motion information in natural scenes, suggesting that the human brain is well adapted to exploit a small amount of dynamic signal and extract information important for survival.

Attenuation of the neural response to sad faces in major depression by antidepressant treatment: a prospective, event-related functional magnetic resonance imaging study.

PubMed

Fu, Cynthia H Y; Williams, Steven C R; Cleare, Anthony J; Brammer, Michael J; Walsh, Nicholas D; Kim, Jieun; Andrew, Chris M; Pich, Emilio Merlo; Williams, Pauline M; Reed, Laurence J; Mitterschiffthaler, Martina T; Suckling, John; Bullmore, Edward T

2004-09-01

Depression is associated with interpersonal difficulties related to abnormalities in affective facial processing. To map brain systems activated by sad facial affect processing in patients with depression and to identify brain functional correlates of antidepressant treatment and symptomatic response. Two groups underwent scanning twice using functional magnetic resonance imaging (fMRI) during an 8-week period. The event-related fMRI paradigm entailed incidental affect recognition of facial stimuli morphed to express discriminable intensities of sadness. Participants were recruited by advertisement from the local population; depressed subjects were treated as outpatients. We matched 19 medication-free, acutely symptomatic patients satisfying DSM-IV criteria for unipolar major depressive disorder by age, sex, and IQ with 19 healthy volunteers. Intervention After the baseline assessment, patients received fluoxetine hydrochloride, 20 mg/d, for 8 weeks. Average activation (capacity) and differential response to variable affective intensity (dynamic range) were estimated in each fMRI time series. We used analysis of variance to identify brain regions that demonstrated a main effect of group (depressed vs healthy subjects) and a group x time interaction (attributable to antidepressant treatment). Change in brain activation associated with reduction of depressive symptoms in the patient group was identified by means of regression analysis. Permutation tests were used for inference. Over time, depressed subjects showed reduced capacity for activation in the left amygdala, ventral striatum, and frontoparietal cortex and a negatively correlated increase of dynamic range in the prefrontal cortex. Symptomatic improvement was associated with reduction of dynamic range in the pregenual cingulate cortex, ventral striatum, and cerebellum. Antidepressant treatment reduces left limbic, subcortical, and neocortical capacity for activation in depressed subjects and increases the dynamic range of the left prefrontal cortex. Changes in anterior cingulate function associated with symptomatic improvement indicate that fMRI may be a useful surrogate marker of antidepressant treatment response.

Variability in Reward Responsivity and Obesity: Evidence from Brain Imaging Studies

PubMed Central

Burger, Kyle S.; Stice, Eric

2012-01-01

Advances in neuroimaging techniques have provided insight into the role of the brain in the regulation of food intake and weight. Growing evidence demonstrate that energy dense, palatable foods elicit similar responses in reward-related brain regions that mimic those of addictive substances. Currently, various models of obesity’s relation to reward from food have been theorized. There is evidence to support a theory of hypo-responsivity of reward regions to food, where individuals consume excess amounts to overcome this reward deficit. There is also data to support a theory of hyper-responsivity of reward regions, where individuals who experience greater reward from food intake are at risk for overeating. However, these seemingly discordant theories are static in nature and do not account for the possible effects of repeated overeating on brain responsivity to food and initial vulnerability factors. Here we review data that support these theories and propose a dynamic vulnerability model of obesity that appears to offer a parsimonious theory that accommodates extant findings. PMID:21999692

A close look at brain dynamics: cells and vessels seen by in vivo two-photon microscopy.

PubMed

Fumagalli, Stefano; Ortolano, Fabrizio; De Simoni, Maria-Grazia

2014-10-01

The cerebral vasculature has a unique role in providing a constant supply of oxygen and nutrients to ensure normal brain functions. Blood vessels that feed the brain are far from being simply channels for passive transportation of fluids. They form complex structures made up of different cell types. These structures regulate blood supply, local concentrations of O2 and CO2, transport of small molecules, trafficking of plasma cells and fine cerebral functions in normal and diseased brains. Until few years ago, analysis of these functions has been typically based on post mortem techniques, whose interpretation is limited by the need for tissue processing at specific times. For a reliable and effective picture of the dynamic processes in the central nervous system, real-time information in vivo is required. There are now few in vivo systems, among which two-photon microscopy (2-PM) is a truly innovative tool for studying the brain. 2-PM has been used to dissect specific aspects of vascular and immune cell dynamics in the context of neurological diseases, providing exciting results that could not have been obtained with conventional methods. This review summarizes the latest findings on vascular and immune system action in the brain, with particular focus on the dynamic responses after ischemic brain injury. 2-PM has helped define the hierarchical architecture of the brain vasculature, the dynamic interaction between the vasculature and immune cells recruited to lesion sites, the effects of blood flow on neuronal and microglial activity and the ability of cells of the neurovascular unit to regulate blood flow. Copyright © 2014 Elsevier Ltd. All rights reserved.

Event-Related Oscillations in Alcoholism Research: A Review

PubMed Central

Pandey, Ashwini K; Kamarajan, Chella; Rangaswamy, Madhavi; Porjesz, Bernice

2013-01-01

Alcohol dependence is characterized as a multi-factorial disorder caused by a complex interaction between genetic and environmental liabilities across development. A variety of neurocognitive deficits/dysfunctions involving impairments in different brain regions and/or neural circuitries have been associated with chronic alcoholism, as well as with a predisposition to develop alcoholism. Several neurobiological and neurobehavioral approaches and methods of analyses have been used to understand the nature of these neurocognitive impairments/deficits in alcoholism. In the present review, we have examined relatively novel methods of analyses of the brain signals that are collectively referred to as event-related oscillations (EROs) and show promise to further our understanding of human brain dynamics while performing various tasks. These new measures of dynamic brain processes have exquisite temporal resolution and allow the study of neural networks underlying responses to sensory and cognitive events, thus providing a closer link to the physiology underlying them. Here, we have reviewed EROs in the study of alcoholism, their usefulness in understanding dynamical brain functions/dysfunctions associated with alcoholism as well as their utility as effective endophenotypes to identify and understand genes associated with both brain oscillations and alcoholism. PMID:24273686

Common resting brain dynamics indicate a possible mechanism underlying zolpidem response in severe brain injury

PubMed Central

Williams, Shawniqua T; Conte, Mary M; Goldfine, Andrew M; Noirhomme, Quentin; Gosseries, Olivia; Thonnard, Marie; Beattie, Bradley; Hersh, Jennifer; Katz, Douglas I; Victor, Jonathan D; Laureys, Steven; Schiff, Nicholas D

2013-01-01

Zolpidem produces paradoxical recovery of speech, cognitive and motor functions in select subjects with severe brain injury but underlying mechanisms remain unknown. In three diverse patients with known zolpidem responses we identify a distinctive pattern of EEG dynamics that suggests a mechanistic model. In the absence of zolpidem, all subjects show a strong low frequency oscillatory peak ∼6–10 Hz in the EEG power spectrum most prominent over frontocentral regions and with high coherence (∼0.7–0.8) within and between hemispheres. Zolpidem administration sharply reduces EEG power and coherence at these low frequencies. The ∼6–10 Hz activity is proposed to arise from intrinsic membrane properties of pyramidal neurons that are passively entrained across the cortex by locally-generated spontaneous activity. Activation by zolpidem is proposed to arise from a combination of initial direct drug effects on cortical, striatal, and thalamic populations and further activation of underactive brain regions induced by restoration of cognitively-mediated behaviors. DOI: http://dx.doi.org/10.7554/eLife.01157.001 PMID:24252875

Self-Assembly of Gold Nanoparticles Shows Microenvironment-Mediated Dynamic Switching and Enhanced Brain Tumor Targeting

PubMed Central

Feng, Qishuai; Shen, Yajing; Fu, Yingjie; Muroski, Megan E.; Zhang, Peng; Wang, Qiaoyue; Xu, Chang; Lesniak, Maciej S.; Li, Gang; Cheng, Yu

2017-01-01

Inorganic nanoparticles with unique physical properties have been explored as nanomedicines for brain tumor treatment. However, the clinical applications of the inorganic formulations are often hindered by the biological barriers and failure to be bioeliminated. The size of the nanoparticle is an essential design parameter which plays a significant role to affect the tumor targeting and biodistribution. Here, we report a feasible approach for the assembly of gold nanoparticles into ~80 nm nanospheres as a drug delivery platform for enhanced retention in brain tumors with the ability to be dynamically switched into the single formulation for excretion. These nanoassemblies can target epidermal growth factor receptors on cancer cells and are responsive to tumor microenvironmental characteristics, including high vascular permeability and acidic and redox conditions. Anticancer drug release was controlled by a pH-responsive mechanism. Intracellular L-glutathione (GSH) triggered the complete breakdown of nanoassemblies to single gold nanoparticles. Furthermore, in vivo studies have shown that nanospheres display enhanced tumor-targeting efficiency and therapeutic effects relative to single-nanoparticle formulations. Hence, gold nanoassemblies present an effective targeting strategy for brain tumor treatment. PMID:28638474

Self-Assembly of Gold Nanoparticles Shows Microenvironment-Mediated Dynamic Switching and Enhanced Brain Tumor Targeting.

PubMed

Feng, Qishuai; Shen, Yajing; Fu, Yingjie; Muroski, Megan E; Zhang, Peng; Wang, Qiaoyue; Xu, Chang; Lesniak, Maciej S; Li, Gang; Cheng, Yu

2017-01-01

Inorganic nanoparticles with unique physical properties have been explored as nanomedicines for brain tumor treatment. However, the clinical applications of the inorganic formulations are often hindered by the biological barriers and failure to be bioeliminated. The size of the nanoparticle is an essential design parameter which plays a significant role to affect the tumor targeting and biodistribution. Here, we report a feasible approach for the assembly of gold nanoparticles into ~80 nm nanospheres as a drug delivery platform for enhanced retention in brain tumors with the ability to be dynamically switched into the single formulation for excretion. These nanoassemblies can target epidermal growth factor receptors on cancer cells and are responsive to tumor microenvironmental characteristics, including high vascular permeability and acidic and redox conditions. Anticancer drug release was controlled by a pH-responsive mechanism. Intracellular L-glutathione (GSH) triggered the complete breakdown of nanoassemblies to single gold nanoparticles. Furthermore, in vivo studies have shown that nanospheres display enhanced tumor-targeting efficiency and therapeutic effects relative to single-nanoparticle formulations. Hence, gold nanoassemblies present an effective targeting strategy for brain tumor treatment.

Dynamics of brain responses to phobic-related stimulation in specific phobia subtypes.

PubMed

Caseras, Xavier; Mataix-Cols, David; Trasovares, Maria Victoria; López-Solà, Marina; Ortriz, Hector; Pujol, Jesus; Soriano-Mas, Carles; Giampietro, Vincent; Brammer, Michael J; Torrubia, Rafael

2010-10-01

Very few studies have investigated to what extent different subtypes of specific phobia share the same underlying functional neuroanatomy. This study aims to investigate the potential differences in the anatomy and dynamics of the blood oxygen level-dependent (BOLD) responses associated with spider and blood-injection-injury phobias. We used an event-related paradigm in 14 untreated spider phobics, 15 untreated blood-injection-injury phobics and 17 controls. Phobic images successfully induced distress only in phobic participants. Both phobic groups showed a similar pattern of heart rate increase following the presentation of phobic stimuli, this being different from controls. The presentation of phobic images induced activity within the same brain network in all participants, although the intensity of brain responses was significantly higher in phobics. Only blood-injection-injury phobics showed greater activity in the ventral prefrontal cortex compared with controls. This phobia group also presented a lower activity peak in the left amygdala compared with spider phobics. Importantly, looking at the dynamics of BOLD responses, both phobia groups showed a quicker time-to-peak in the right amygdala than controls, but only spider phobics also differed from controls in this parameter within the left amygdala. Considering these and previous findings, both phobia subtypes show very similar responses regarding their immediate reaction to phobia-related images, but critical differences in their sustained responses to these stimuli. These results highlight the importance of considering complex mental processes potentially associated with coping and emotion regulation processes, rather than exclusively focusing on primary neural responses to threat, when investigating fear and phobias. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Resting state functional MRI in Parkinson’s disease: the impact of deep brain stimulation on ‘effective’ connectivity

PubMed Central

Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl

2014-01-01

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both ‘action’ and ‘resting’ motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the ‘effective’ connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network—disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses. PMID:24566670

Resting state functional MRI in Parkinson's disease: the impact of deep brain stimulation on 'effective' connectivity.

PubMed

Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl; Foltynie, Tom

2014-04-01

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.

Dynamic functional imaging of brain glucose utilization using fPET-FDG

DOE PAGES

Villien, Marjorie; Wey, Hsiao-Ying; Mandeville, Joseph B.; ...

2014-06-14

We report that glucose is the principal source of energy for the brain and yet the dynamic response of glucose utilization to changes in brain activity is still not fully understood. Positron emission tomography (PET) allows quantitative measurement of glucose metabolism using 2-[18F]-fluorodeoxyglucose (FDG). However, FDG PET in its current form provides an integral (or average) of glucose consumption over tens of minutes and lacks the temporal information to capture physiological alterations associated with changes in brain activity induced by tasks or drug challenges. Traditionally, changes in glucose utilization are inferred by comparing two separate scans, which significantly limits themore » utility of the method. We report a novel method to track changes in FDG metabolism dynamically, with higher temporal resolution than exists to date and within a single session. Using a constant infusion of FDG, we demonstrate that our technique (termed fPET-FDG) can be used in an analysis pipeline similar to fMRI to define within-session differential metabolic responses. We use visual stimulation to demonstrate the feasibility of this method. Ultimately, this new method has a great potential to be used in research protocols and clinical settings since fPET-FDG imaging can be performed with most PET scanners and data acquisition and analysis are straightforward. fPET-FDG is a highly complementary technique to MRI and provides a rich new way to observe functional changes in brain metabolism.« less

Neuronal Circuitry Mechanisms Regulating Adult Mammalian Neurogenesis

PubMed Central

Song, Juan; Olsen, Reid H.J.; Sun, Jiaqi; Ming, Guo-li; Song, Hongjun

2017-01-01

The adult mammalian brain is a dynamic structure, capable of remodeling in response to various physiological and pathological stimuli. One dramatic example of brain plasticity is the birth and subsequent integration of newborn neurons into the existing circuitry. This process, termed adult neurogenesis, recapitulates neural developmental events in two specialized adult brain regions: the lateral ventricles of the forebrain. Recent studies have begun to delineate how the existing neuronal circuits influence the dynamic process of adult neurogenesis, from activation of quiescent neural stem cells (NSCs) to the integration and survival of newborn neurons. Here, we review recent progress toward understanding the circuit-based regulation of adult neurogenesis in the hippocampus and olfactory bulb. PMID:27143698

Right mesial temporal lobe epilepsy impairs empathy-related brain responses to dynamic fearful faces.

PubMed

Toller, Gianina; Adhimoolam, Babu; Grunwald, Thomas; Huppertz, Hans-Jürgen; Kurthen, Martin; Rankin, Katherine P; Jokeit, Hennric

2015-03-01

Unilateral mesial temporal lobe epilepsy (MTLE) has been associated with reduced amygdala responsiveness to fearful faces. However, the effect of unilateral MTLE on empathy-related brain responses in extra-amygdalar regions has not been investigated. Using functional magnetic resonance imaging, we measured empathy-related brain responses to dynamic fearful faces in 34 patients with unilateral MTLE (18 right sided), in an epilepsy (extra-MTLE; n = 16) and in a healthy control group (n = 30). The primary finding was that right MTLE (RMTLE) was associated with decreased activity predominantly in the right amygdala and also in bilateral periaqueductal gray (PAG) but normal activity in the right anterior insula. The results of the extra-MTLE group demonstrate that these reduced amygdala and PAG responses go beyond the attenuation caused by antiepileptic and antidepressant medication. These findings clearly indicate that RMTLE affects the function of mesial temporal and midbrain structures that mediate basic interoceptive input necessary for the emotional awareness of empathic experiences of fear. Together with the decreased empathic concern found in the RMTLE group, this study provides neurobehavioral evidence that patients with RMTLE are at increased risk for reduced empathy towards others' internal states and sheds new light on the nature of social-cognitive impairments frequently accompanying MTLE.

An Examination of Dynamic Gene Expression Changes in the Mouse Brain During Pregnancy and the Postpartum Period.

PubMed

Ray, Surjyendu; Tzeng, Ruei-Ying; DiCarlo, Lisa M; Bundy, Joseph L; Vied, Cynthia; Tyson, Gary; Nowakowski, Richard; Arbeitman, Michelle N

2015-11-23

The developmental transition to motherhood requires gene expression changes that alter the brain to drive the female to perform maternal behaviors. We broadly examined the global transcriptional response in the mouse maternal brain, by examining four brain regions: hypothalamus, hippocampus, neocortex, and cerebellum, in virgin females, two pregnancy time points, and three postpartum time points. We find that overall there are hundreds of differentially expressed genes, but each brain region and time point shows a unique molecular signature, with only 49 genes differentially expressed in all four regions. Interestingly, a set of "early-response genes" is repressed in all brain regions during pregnancy and postpartum stages. Several genes previously implicated in underlying postpartum depression change expression. This study serves as an atlas of gene expression changes in the maternal brain, with the results demonstrating that pregnancy, parturition, and postpartum maternal experience substantially impact diverse brain regions. Copyright © 2016 Ray et al.

Brain talk: power and negotiation in children’s discourse about self, brain and behaviour

PubMed Central

Singh, Ilina

2013-01-01

This article examines children’s discourse about self, brain and behaviour, focusing on the dynamics of power, knowledge and responsibility articulated by children. The empirical data discussed in this article are drawn from the study of Voices on Identity, Childhood, Ethics and Stimulants, which included interviews with 151 US and UK children, a subset of whom had a diagnosis of attention deficit/hyperactivity disorder. Despite their contact with psychiatric explanations and psychotropic drugs for their behaviour, children’s discursive engagements with the brain show significant evidence of agency and negotiated responsibility. These engagements suggest the limitations of current concepts that describe a collapse of the self into the brain in an age of neurocentrism. Empirical investigation is needed in order to develop agent-centred conceptual and theoretical frameworks that describe and evaluate the harms and benefits of treating children with psychotropic drugs and other brain-based technologies. PMID:23094965

Neural dynamics during repetitive visual stimulation

NASA Astrophysics Data System (ADS)

Tsoneva, Tsvetomira; Garcia-Molina, Gary; Desain, Peter

2015-12-01

Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40-60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (15-30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline after approx. 500 ms. During the steady-state response, we observed alpha band desynchronization over occipital sites and after 500 ms also over frontal sites, while neighboring areas synchronized. The power in beta band over occipital sites increased during the stimulation period, possibly caused by increase in power at sub-harmonic frequencies of stimulation. Gamma power was also enhanced by the stimulation. Significance. These findings have direct implications on the use of RVS and SSVEPs for neural process investigation through steady-state topography, controlled entrainment of brain oscillations and BCIs. A deep understanding of SSVEP propagation in time and space and the link with ongoing brain rhythms is crucial for optimizing the typical SSVEP applications for studying, assisting, or augmenting human cognitive and sensorimotor function.

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Temporal dynamics of musical emotions examined through intersubject synchrony of brain activity

PubMed Central

Frühholz, Sascha; Cochrane, Tom; Cojan, Yann; Vuilleumier, Patrik

2015-01-01

To study emotional reactions to music, it is important to consider the temporal dynamics of both affective responses and underlying brain activity. Here, we investigated emotions induced by music using functional magnetic resonance imaging (fMRI) with a data-driven approach based on intersubject correlations (ISC). This method allowed us to identify moments in the music that produced similar brain activity (i.e. synchrony) among listeners under relatively natural listening conditions. Continuous ratings of subjective pleasantness and arousal elicited by the music were also obtained for the music outside of the scanner. Our results reveal synchronous activations in left amygdala, left insula and right caudate nucleus that were associated with higher arousal, whereas positive valence ratings correlated with decreases in amygdala and caudate activity. Additional analyses showed that synchronous amygdala responses were driven by energy-related features in the music such as root mean square and dissonance, while synchrony in insula was additionally sensitive to acoustic event density. Intersubject synchrony also occurred in the left nucleus accumbens, a region critically implicated in reward processing. Our study demonstrates the feasibility and usefulness of an approach based on ISC to explore the temporal dynamics of music perception and emotion in naturalistic conditions. PMID:25994970

Bayesian deconvolution of [corrected] fMRI data using bilinear dynamical systems.

PubMed

Makni, Salima; Beckmann, Christian; Smith, Steve; Woolrich, Mark

2008-10-01

In Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993], a particular case of the Linear Dynamical Systems (LDSs) was used to model the dynamic behavior of the BOLD response in functional MRI. This state-space model, called bilinear dynamical system (BDS), is used to deconvolve the fMRI time series in order to estimate the neuronal response induced by the different stimuli of the experimental paradigm. The BDS model parameters are estimated using an expectation-maximization (EM) algorithm proposed by Ghahramani and Hinton [Ghahramani, Z., Hinton, G.E. 1996. Parameter Estimation for Linear Dynamical Systems. Technical Report, Department of Computer Science, University of Toronto]. In this paper we introduce modifications to the BDS model in order to explicitly model the spatial variations of the haemodynamic response function (HRF) in the brain using a non-parametric approach. While in Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993] the relationship between neuronal activation and fMRI signals is formulated as a first-order convolution with a kernel expansion using basis functions (typically two or three), in this paper, we argue in favor of a spatially adaptive GLM in which a local non-parametric estimation of the HRF is performed. Furthermore, in order to overcome the overfitting problem typically associated with simple EM estimates, we propose a full Variational Bayes (VB) solution to infer the BDS model parameters. We demonstrate the usefulness of our model which is able to estimate both the neuronal activity and the haemodynamic response function in every voxel of the brain. We first examine the behavior of this approach when applied to simulated data with different temporal and noise features. As an example we will show how this method can be used to improve interpretability of estimates from an independent component analysis (ICA) analysis of fMRI data. We finally demonstrate its use on real fMRI data in one slice of the brain.

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

PubMed Central

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

2018-01-01

Abstract 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. PMID:29524274

Brain-wide neuronal dynamics during motor adaptation in zebrafish.

PubMed

Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

2012-05-09

A fundamental question in neuroscience is how entire neural circuits generate behaviour and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record the activity of large populations of neurons at the cellular level, throughout the brain of larval zebrafish expressing a genetically encoded calcium sensor, while the paralysed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neuronal response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioural adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behaviour.

Brain-wide neuronal dynamics during motor adaptation in zebrafish

PubMed Central

Ahrens, Misha B; Li, Jennifer M; Orger, Michael B; Robson, Drew N; Schier, Alexander F; Engert, Florian; Portugues, Ruben

2013-01-01

A fundamental question in neuroscience is how entire neural circuits generate behavior and adapt it to changes in sensory feedback. Here we use two-photon calcium imaging to record activity of large populations of neurons at the cellular level throughout the brain of larval zebrafish expressing a genetically-encoded calcium sensor, while the paralyzed animals interact fictively with a virtual environment and rapidly adapt their motor output to changes in visual feedback. We decompose the network dynamics involved in adaptive locomotion into four types of neural response properties, and provide anatomical maps of the corresponding sites. A subset of these signals occurred during behavioral adjustments and are candidates for the functional elements that drive motor learning. Lesions to the inferior olive indicate a specific functional role for olivocerebellar circuitry in adaptive locomotion. This study enables the analysis of brain-wide dynamics at single-cell resolution during behavior. PMID:22622571

Investigating Neuromagnetic Brain Responses against Chromatic Flickering Stimuli by Wavelet Entropies

PubMed Central

Bhagat, Mayank; Bhushan, Chitresh; Saha, Goutam; Shimjo, Shinsuke; Watanabe, Katsumi; Bhattacharya, Joydeep

2009-01-01

Background Photosensitive epilepsy is a type of reflexive epilepsy triggered by various visual stimuli including colourful ones. Despite the ubiquitous presence of colorful displays, brain responses against different colour combinations are not properly studied. Methodology/Principal Findings Here, we studied the photosensitivity of the human brain against three types of chromatic flickering stimuli by recording neuromagnetic brain responses (magnetoencephalogram, MEG) from nine adult controls, an unmedicated patient, a medicated patient, and two controls age-matched with patients. Dynamical complexities of MEG signals were investigated by a family of wavelet entropies. Wavelet entropy is a newly proposed measure to characterize large scale brain responses, which quantifies the degree of order/disorder associated with a multi-frequency signal response. In particular, we found that as compared to the unmedicated patient, controls showed significantly larger wavelet entropy values. We also found that Renyi entropy is the most powerful feature for the participant classification. Finally, we also demonstrated the effect of combinational chromatic sensitivity on the underlying order/disorder in MEG signals. Conclusions/Significance Our results suggest that when perturbed by potentially epileptic-triggering stimulus, healthy human brain manages to maintain a non-deterministic, possibly nonlinear state, with high degree of disorder, but an epileptic brain represents a highly ordered state which making it prone to hyper-excitation. Further, certain colour combination was found to be more threatening than other combinations. PMID:19779630

Investigating neuromagnetic brain responses against chromatic flickering stimuli by wavelet entropies.

PubMed

Bhagat, Mayank; Bhushan, Chitresh; Saha, Goutam; Shimjo, Shinsuke; Watanabe, Katsumi; Bhattacharya, Joydeep

2009-09-25

Photosensitive epilepsy is a type of reflexive epilepsy triggered by various visual stimuli including colourful ones. Despite the ubiquitous presence of colorful displays, brain responses against different colour combinations are not properly studied. Here, we studied the photosensitivity of the human brain against three types of chromatic flickering stimuli by recording neuromagnetic brain responses (magnetoencephalogram, MEG) from nine adult controls, an unmedicated patient, a medicated patient, and two controls age-matched with patients. Dynamical complexities of MEG signals were investigated by a family of wavelet entropies. Wavelet entropy is a newly proposed measure to characterize large scale brain responses, which quantifies the degree of order/disorder associated with a multi-frequency signal response. In particular, we found that as compared to the unmedicated patient, controls showed significantly larger wavelet entropy values. We also found that Renyi entropy is the most powerful feature for the participant classification. Finally, we also demonstrated the effect of combinational chromatic sensitivity on the underlying order/disorder in MEG signals. Our results suggest that when perturbed by potentially epileptic-triggering stimulus, healthy human brain manages to maintain a non-deterministic, possibly nonlinear state, with high degree of disorder, but an epileptic brain represents a highly ordered state which making it prone to hyper-excitation. Further, certain colour combination was found to be more threatening than other combinations.

Consequences of the dynamic triple peak impact factor in Traumatic Brain Injury as Measured with Numerical Simulation.

PubMed

von Holst, Hans; Li, Xiaogai

2013-01-01

There is a lack of knowledge about the direct neuromechanical consequences in traumatic brain injury (TBI) at the scene of accident. In this study we use a finite element model of the human head to study the dynamic response of the brain during the first milliseconds after the impact with velocities of 10, 6, and 2 meters/second (m/s), respectively. The numerical simulation was focused on the external kinetic energy transfer, intracranial pressure (ICP), strain energy density and first principal strain level, and their respective impacts to the brain tissue. We show that the oblique impacts of 10 and 6 m/s resulted in substantial high peaks for the ICP, strain energy density, and first principal strain levels, however, with different patterns and time frames. Also, the 2 m/s impact showed almost no increase in the above mentioned investigated parameters. More importantly, we show that there clearly exists a dynamic triple peak impact factor to the brain tissue immediately after the impact regardless of injury severity associated with different impact velocities. The dynamic triple peak impacts occurred in a sequential manner first showing strain energy density and ICP and then followed by first principal strain. This should open up a new dimension to better understand the complex mechanisms underlying TBI. Thus, it is suggested that the combination of the dynamic triple peak impacts to the brain tissue may interfere with the cerebral metabolism relative to the impact severity thereby having the potential to differentiate between severe and moderate TBI from mild TBI.

Advances in the Neuroscience of Intelligence: from Brain Connectivity to Brain Perturbation.

PubMed

Santarnecchi, Emiliano; Rossi, Simone

2016-12-06

Our view is that intelligence, as expression of the complexity of the human brain and of its evolutionary path, represents an intriguing example of "system level brain plasticity": tangible proofs of this assertion lie in the strong links intelligence has with vital brain capacities as information processing (i.e., pure, rough capacity to transfer information in an efficient way), resilience (i.e., the ability to cope with loss of efficiency and/or loss of physical elements in a network) and adaptability (i.e., being able to efficiently rearrange its dynamics in response to environmental demands). Current evidence supporting this view move from theoretical models correlating intelligence and individual response to systematic "lesions" of brain connectivity, as well as from the field of Noninvasive Brain Stimulation (NiBS). Perturbation-based approaches based on techniques as transcranial magnetic stimulation (TMS) and transcranial alternating current stimulation (tACS), are opening new in vivo scenarios which could allow to disclose more causal relationship between intelligence and brain plasticity, overcoming the limitations of brain-behavior correlational evidence.

Study on Brain Injury Biomechanics Based on the Real Pedestrian Traffic Accidents

NASA Astrophysics Data System (ADS)

Feng, Chengjian; Yin, Zhiyong

This paper aimed to research the dynamic response and injury mechanisms of head based on real pedestrian traffic accidents with video. The kinematics of head contact with the vehicle was reconstructed by using multi-body dynamics models. These calculated parameters such as head impact velocity and impact location and head orientation were applied to the THUMS-4 FE head model as initial conditions. The intracranial pressure and stress of brain were calculated from simulations of head contact with the vehicle. These results were consistent with that of others. It was proved that real traffic accidents combined with simulation analysis can be used to study head injury biomechanics. Increasing in the number of cases, a tolerance limit of brain injury will be put forward.

Identification of a novel dynamic red blindness in human by event-related brain potentials.

PubMed

Zhang, Jiahua; Kong, Weijia; Yang, Zhongle

2010-12-01

Dynamic color is an important carrier that takes information in some special occupations. However, up to the present, there are no available and objective tests to evaluate dynamic color processing. To investigate the characteristics of dynamic color processing, we adopted two patterns of visual stimulus called "onset-offset" which reflected static color stimuli and "sustained moving" without abrupt mode which reflected dynamic color stimuli to evoke event-related brain potentials (ERPs) in primary color amblyopia patients (abnormal group) and subjects with normal color recognition ability (normal group). ERPs were recorded by Neuroscan system. The results showed that in the normal group, ERPs in response to the dynamic red stimulus showed frontal positive amplitudes with a latency of about 180 ms, a negative peak at about 240 ms and a peak latency of the late positive potential (LPP) in a time window between 290 and 580 ms. In the abnormal group, ERPs in response to the dynamic red stimulus were fully lost and characterized by vanished amplitudes between 0 and 800 ms. No significant difference was noted in ERPs in response to the dynamic green and blue stimulus between the two groups (P>0.05). ERPs of the two groups in response to the static red, green and blue stimulus were not much different, showing a transient negative peak at about 170 ms and a peak latency of LPP in a time window between 350 and 650 ms. Our results first revealed that some subjects who were not identified as color blindness under static color recognition could not completely apperceive a sort of dynamic red stimulus by ERPs, which was called "dynamic red blindness". Furthermore, these results also indicated that low-frequency ERPs induced by "sustained moving" may be a good and new method to test dynamic color perception competence.

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Characterization of time dynamical evolution of electroencephalographic epileptic records

NASA Astrophysics Data System (ADS)

Rosso, Osvaldo A.; Mairal, María. Liliana

2002-09-01

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of the brain dynamics. The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The entropy defined from the wavelet functions is a measure of the order/disorder degree present in a time series. In consequence, this entropy evaluates over EEG time series gives information about the underlying dynamical process in the brain, more specifically of the synchrony of the group cells involved in the different neural responses. The total wavelet entropy results independent of the signal energy and becomes a good tool for detecting dynamical changes in the system behavior. In addition the total wavelet entropy has advantages over the Lyapunov exponents, because it is parameter free and independent of the stationarity of the time series. In this work we compared the results of the time evolution of the chaoticity (Lyapunov exponent as a function of time) with the corresponding time evolution of the total wavelet entropy in two different EEG records, one provide by depth electrodes and other by scalp ones.

Mind over motor mapping: Driver response to changing vehicle dynamics.

PubMed

Bruno, Jennifer L; Baker, Joseph M; Gundran, Andrew; Harbott, Lene K; Stuart, Zachary; Piccirilli, Aaron M; Hosseini, S M Hadi; Gerdes, J Christian; Reiss, Allan L

2018-06-08

Improvements in vehicle safety require understanding of the neural systems that support the complex, dynamic task of real-world driving. We used functional near infrared spectroscopy (fNIRS) and pupilometry to quantify cortical and physiological responses during a realistic, simulated driving task in which vehicle dynamics were manipulated. Our results elucidate compensatory changes in driver behavior in response to changes in vehicle handling. We also describe associated neural and physiological responses under different levels of mental workload. The increased cortical activation we observed during the late phase of the experiment may indicate motor learning in prefrontal-parietal networks. Finally, relationships among cortical activation, steering control, and individual personality traits suggest that individual brain states and traits may be useful in predicting a driver's response to changes in vehicle dynamics. Results such as these will be useful for informing the design of automated safety systems that facilitate safe and supportive driver-car communication. © 2018 Wiley Periodicals, Inc.

Do resting brain dynamics predict oddball evoked-potential?

PubMed Central

2011-01-01

Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection. PMID:22114868

Frontal Oscillatory Dynamics Predict Feedback Learning and Action Adjustment

ERIC Educational Resources Information Center

van de Vijver, Irene; Ridderinkhof, K. Richard; Cohen, Michael X.

2011-01-01

Frontal oscillatory dynamics in the theta (4-8 Hz) and beta (20-30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after…

The Dynamics of Integration and Separation: ERP, MEG, and Neural Network Studies of Immediate Repetition Effects

ERIC Educational Resources Information Center

Huber, David E.; Tian, Xing; Curran, Tim; O'Reilly, Randall C.; Woroch, Brion

2008-01-01

This article presents data and theory concerning the fundamental question of how the brain achieves a balance between integrating and separating perceptual information over time. This theory was tested in the domain of word reading by examining brain responses to briefly presented words that were either new or immediate repetitions. Critically,…

Near-instant automatic access to visually presented words in the human neocortex: neuromagnetic evidence.

PubMed

Shtyrov, Yury; MacGregor, Lucy J

2016-05-24

Rapid and efficient processing of external information by the brain is vital to survival in a highly dynamic environment. The key channel humans use to exchange information is language, but the neural underpinnings of its processing are still not fully understood. We investigated the spatio-temporal dynamics of neural access to word representations in the brain by scrutinising the brain's activity elicited in response to psycholinguistically, visually and phonologically matched groups of familiar words and meaningless pseudowords. Stimuli were briefly presented on the visual-field periphery to experimental participants whose attention was occupied with a non-linguistic visual feature-detection task. The neural activation elicited by these unattended orthographic stimuli was recorded using multi-channel whole-head magnetoencephalography, and the timecourse of lexically-specific neuromagnetic responses was assessed in sensor space as well as at the level of cortical sources, estimated using individual MR-based distributed source reconstruction. Our results demonstrate a neocortical signature of automatic near-instant access to word representations in the brain: activity in the perisylvian language network characterised by specific activation enhancement for familiar words, starting as early as ~70 ms after the onset of unattended word stimuli and underpinned by temporal and inferior-frontal cortices.

The dynamics of error processing in the human brain as reflected by high-gamma activity in noninvasive and intracranial EEG.

PubMed

Völker, Martin; Fiederer, Lukas D J; Berberich, Sofie; Hammer, Jiří; Behncke, Joos; Kršek, Pavel; Tomášek, Martin; Marusič, Petr; Reinacher, Peter C; Coenen, Volker A; Helias, Moritz; Schulze-Bonhage, Andreas; Burgard, Wolfram; Ball, Tonio

2018-06-01

Error detection in motor behavior is a fundamental cognitive function heavily relying on local cortical information processing. Neural activity in the high-gamma frequency band (HGB) closely reflects such local cortical processing, but little is known about its role in error processing, particularly in the healthy human brain. Here we characterize the error-related response of the human brain based on data obtained with noninvasive EEG optimized for HGB mapping in 31 healthy subjects (15 females, 16 males), and additional intracranial EEG data from 9 epilepsy patients (4 females, 5 males). Our findings reveal a multiscale picture of the global and local dynamics of error-related HGB activity in the human brain. On the global level as reflected in the noninvasive EEG, the error-related response started with an early component dominated by anterior brain regions, followed by a shift to parietal regions, and a subsequent phase characterized by sustained parietal HGB activity. This phase lasted for more than 1 s after the error onset. On the local level reflected in the intracranial EEG, a cascade of both transient and sustained error-related responses involved an even more extended network, spanning beyond frontal and parietal regions to the insula and the hippocampus. HGB mapping appeared especially well suited to investigate late, sustained components of the error response, possibly linked to downstream functional stages such as error-related learning and behavioral adaptation. Our findings establish the basic spatio-temporal properties of HGB activity as a neural correlate of error processing, complementing traditional error-related potential studies. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Brain-heart linear and nonlinear dynamics during visual emotional elicitation in healthy subjects.

PubMed

Valenza, G; Greco, A; Gentili, C; Lanata, A; Toschi, N; Barbieri, R; Sebastiani, L; Menicucci, D; Gemignani, A; Scilingo, E P

2016-08-01

This study investigates brain-heart dynamics during visual emotional elicitation in healthy subjects through linear and nonlinear coupling measures of EEG spectrogram and instantaneous heart rate estimates. To this extent, affective pictures including different combinations of arousal and valence levels, gathered from the International Affective Picture System, were administered to twenty-two healthy subjects. Time-varying maps of cortical activation were obtained through EEG spectral analysis, whereas the associated instantaneous heartbeat dynamics was estimated using inhomogeneous point-process linear models. Brain-Heart linear and nonlinear coupling was estimated through the Maximal Information Coefficient (MIC), considering EEG time-varying spectra and point-process estimates defined in the time and frequency domains. As a proof of concept, we here show preliminary results considering EEG oscillations in the θ band (4-8 Hz). This band, indeed, is known in the literature to be involved in emotional processes. MIC highlighted significant arousal-dependent changes, mediated by the prefrontal cortex interplay especially occurring at intermediate arousing levels. Furthermore, lower and higher arousing elicitations were associated to not significant brain-heart coupling changes in response to pleasant/unpleasant elicitations.

Synaptic multistability and network synchronization induced by the neuron-glial interaction in the brain

NASA Astrophysics Data System (ADS)

Lazarevich, I. A.; Stasenko, S. V.; Kazantsev, V. B.

2017-02-01

The dynamics of a synaptic contact between neurons that forms a feedback loop through the interaction with glial cells of the brain surrounding the neurons is studied. It is shown that, depending on the character of the neuron-glial interaction, the dynamics of the signal transmission frequency in the synaptic contact can be bistable with two stable steady states or spiking with the regular generation of spikes with various amplitudes and durations. It is found that such a synaptic contact at the network level is responsible for the appearance of quasisynchronous network bursts.

Spatiotemporal brain dynamics of emotional face processing modulations induced by the serotonin 1A/2A receptor agonist psilocybin.

PubMed

Bernasconi, Fosco; Schmidt, André; Pokorny, Thomas; Kometer, Michael; Seifritz, Erich; Vollenweider, Franz X

2014-12-01

Emotional face processing is critically modulated by the serotonergic system. For instance, emotional face processing is impaired by acute psilocybin administration, a serotonin (5-HT) 1A and 2A receptor agonist. However, the spatiotemporal brain mechanisms underlying these modulations are poorly understood. Here, we investigated the spatiotemporal brain dynamics underlying psilocybin-induced modulations during emotional face processing. Electrical neuroimaging analyses were applied to visual evoked potentials in response to emotional faces, following psilocybin and placebo administration. Our results indicate a first time period of strength (i.e., Global Field Power) modulation over the 168-189 ms poststimulus interval, induced by psilocybin. A second time period of strength modulation was identified over the 211-242 ms poststimulus interval. Source estimations over these 2 time periods further revealed decreased activity in response to both neutral and fearful faces within limbic areas, including amygdala and parahippocampal gyrus, and the right temporal cortex over the 168-189 ms interval, and reduced activity in response to happy faces within limbic and right temporo-occipital brain areas over the 211-242 ms interval. Our results indicate a selective and temporally dissociable effect of psilocybin on the neuronal correlates of emotional face processing, consistent with a modulation of the top-down control. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

PubMed Central

Falcon, Maria Inez; Riley, Jeffrey D.; Jirsa, Viktor; McIntosh, Anthony R.; Shereen, Ahmed D.; Chen, E. Elinor; Solodkin, Ana

2015-01-01

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual’s brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions. PMID:26579071

Brain talk: power and negotiation in children's discourse about self, brain and behaviour.

PubMed

Singh, Ilina

2013-07-01

This article examines children's discourse about self, brain and behaviour, focusing on the dynamics of power, knowledge and responsibility articulated by children. The empirical data discussed in this article are drawn from the study of Voices on Identity, Childhood, Ethics and Stimulants, which included interviews with 151 US and UK children, a subset of whom had a diagnosis of attention deficit/hyperactivity disorder. Despite their contact with psychiatric explanations and psychotropic drugs for their behaviour, children's discursive engagements with the brain show significant evidence of agency and negotiated responsibility. These engagements suggest the limitations of current concepts that describe a collapse of the self into the brain in an age of neurocentrism. Empirical investigation is needed in order to develop agent-centred conceptual and theoretical frameworks that describe and evaluate the harms and benefits of treating children with psychotropic drugs and other brain-based technologies. © 2012 The Author. Sociology of Health & Illness © 2012 Foundation for the Sociology of Health & Illness/John Wiley & Sons Ltd.

Spatiotemporal oscillatory dynamics of visual selective attention during a flanker task.

PubMed

McDermott, Timothy J; Wiesman, Alex I; Proskovec, Amy L; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2017-08-01

The flanker task is a test of visual selective attention that has been widely used to probe error monitoring, response conflict, and related constructs. However, to date, few studies have focused on the selective attention component of this task and imaged the underlying oscillatory dynamics serving task performance. In this study, 21 healthy adults successfully completed an arrow-based version of the Eriksen flanker task during magnetoencephalography (MEG). All MEG data were pre-processed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach, and voxel time series were extracted from the peak responses to identify the temporal dynamics. Across both congruent and incongruent flanker conditions, our results indicated robust decreases in alpha (9-12Hz) activity in medial and lateral occipital regions, bilateral parietal cortices, and cerebellar areas during task performance. In parallel, increases in theta (3-7Hz) oscillatory activity were detected in dorsal and ventral frontal regions, and the anterior cingulate. As per conditional effects, stronger alpha responses (i.e., greater desynchronization) were observed in parietal, occipital, and cerebellar cortices during incongruent relative to congruent trials, whereas the opposite pattern emerged for theta responses (i.e., synchronization) in the anterior cingulate, left dorsolateral prefrontal, and ventral prefrontal cortices. Interestingly, the peak latency of theta responses in these latter brain regions was significantly correlated with reaction time, and may partially explain the amplitude difference observed between congruent and incongruent trials. Lastly, whole-brain exploratory analyses implicated the frontal eye fields, right temporoparietal junction, and premotor cortices. These findings suggest that regions of both the dorsal and ventral attention networks contribute to visual selective attention processes during incongruent trials, and that such differential processes are transient and fully completed shortly after the behavioral response in most trials. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of the dynamics of human glymphatic system by near-infrared spectroscopy.

PubMed

Myllylä, Teemu; Harju, Markus; Korhonen, Vesa; Bykov, Alexander; Kiviniemi, Vesa; Meglinski, Igor

2017-08-12

Fluctuations in brain water content has attracted increasing interest, particularly as regards studies of the glymphatic system, which is connected with the complex organization of dural lymphatic vessels, responsible for cleaning tissue. Disturbances of glymphatic circulation are associated with several brain disorders, including dementia. This article introduces an approach to noninvasive measurement of water dynamics in the human brain utilizing near-infrared spectroscopy (NIRS). We demonstrate the possibility to sense dynamic variations of water content between the skull and grey matter, for instance, in the subarachnoid space. Measured fluctuations in water content, especially in the cerebrospinal fluid (CSF), are assumed to be correlated with the dynamics of glymphatic circulation. The sampling volume for the NIRS optode was estimated by Monte Carlo modelling for the wavelengths of 660, 740, 830 and 980 nm. In addition, using combinations of these wavelengths, this article presents the calculation models for quantifying water and haemodynamics. The presented NIRS technique allows long-term functional brain monitoring, including sleeping time. Furthermore, it is used in combination with different magnetic neuroimaging techniques, particularly magnetic resonance encephalography. Using the combined setup, we report the preliminary results on the interaction between CSF and blood oxygen level-dependent fluctuations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data.

PubMed

Calhoun, V D; Adali, T; Pearlson, G D; Kiehl, K A

2006-04-01

Event-related potential (ERP) studies of the brain's response to infrequent, target (oddball) stimuli elicit a sequence of physiological events, the most prominent and well studied being a complex, the P300 (or P3) peaking approximately 300 ms post-stimulus for simple stimuli and slightly later for more complex stimuli. Localization of the neural generators of the human oddball response remains challenging due to the lack of a single imaging technique with good spatial and temporal resolution. Here, we use independent component analyses to fuse ERP and fMRI modalities in order to examine the dynamics of the auditory oddball response with high spatiotemporal resolution across the entire brain. Initial activations in auditory and motor planning regions are followed by auditory association cortex and motor execution regions. The P3 response is associated with brainstem, temporal lobe, and medial frontal activity and finally a late temporal lobe "evaluative" response. We show that fusing imaging modalities with different advantages can provide new information about the brain.

Biothermal Model of Patient and Automatic Control System of Brain Temperature for Brain Hypothermia Treatment

NASA Astrophysics Data System (ADS)

Wakamatsu, Hidetoshi; Gaohua, Lu

Various surface-cooling apparatus such as the cooling cap, muffler and blankets have been commonly used for the cooling of the brain to provide hypothermic neuro-protection for patients of hypoxic-ischemic encephalopathy. The present paper is aimed at the brain temperature regulation from the viewpoint of automatic system control, in order to help clinicians decide an optimal temperature of the cooling fluid provided for these three types of apparatus. At first, a biothermal model characterized by dynamic ambient temperatures is constructed for adult patient, especially on account of the clinical practice of hypothermia and anesthesia in the brain hypothermia treatment. Secondly, the model is represented by the state equation as a lumped parameter linear dynamic system. The biothermal model is justified from their various responses corresponding to clinical phenomena and treatment. Finally, the optimal regulator is tentatively designed to give clinicians some suggestions on the optimal temperature regulation of the patient’s brain. It suggests the patient’s brain temperature could be optimally controlled to follow-up the temperature process prescribed by the clinicians. This study benefits us a great clinical possibility for the automatic hypothermia treatment.

Dynamic neural activity during stress signals resilient coping

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Constable, R. Todd; Seo, Dongju

2016-01-01

Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping. PMID:27432990

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Epicenters of dynamic connectivity in the adaptation of the ventral visual system.

PubMed

Prčkovska, Vesna; Huijbers, Willem; Schultz, Aaron; Ortiz-Teran, Laura; Peña-Gomez, Cleofe; Villoslada, Pablo; Johnson, Keith; Sperling, Reisa; Sepulcre, Jorge

2017-04-01

Neuronal responses adapt to familiar and repeated sensory stimuli. Enhanced synchrony across wide brain systems has been postulated as a potential mechanism for this adaptation phenomenon. Here, we used recently developed graph theory methods to investigate hidden connectivity features of dynamic synchrony changes during a visual repetition paradigm. Particularly, we focused on strength connectivity changes occurring at local and distant brain neighborhoods. We found that connectivity reorganization in visual modal cortex-such as local suppressed connectivity in primary visual areas and distant suppressed connectivity in fusiform areas-is accompanied by enhanced local and distant connectivity in higher cognitive processing areas in multimodal and association cortex. Moreover, we found a shift of the dynamic functional connections from primary-visual-fusiform to primary-multimodal/association cortex. These findings suggest that repetition-suppression is made possible by reorganization of functional connectivity that enables communication between low- and high-order areas. Hum Brain Mapp 38:1965-1976, 2017. © 2017 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-07-24

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150-200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300-350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual-motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions

PubMed Central

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-01-01

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150–200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300–350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual–motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions. PMID:26206708

Probing mechanobiology with laser-induced shockwaves

NASA Astrophysics Data System (ADS)

Carmona, Christopher; Preece, Daryl C.; Gomez-Godinez, Veronica; Shi, Linda Z.; Berns, Michael W.

2017-08-01

Traumatic Brain Injury (TBI) occurs when an external force injures the brain. While clinical outcomes of TBI can vary widely in severity, few mechanisms of neurodegeneration following TBI have been identified for treatment. We propose a model for studying TBI using laser-induced shockwaves (LISs). An optical system was developed that allows single cells to be studied in response to LISs. Our system utilizes an optically-coupled force measurement component that allows for the visualization of shockwave dynamics. Here, the force measurement system is characterized by imaging stages over the period of violent expansion and collapse of microbubbles responsible for shockwave generation.

Methodological aspects of EEG and body dynamics measurements during motion

PubMed Central

Reis, Pedro M. R.; Hebenstreit, Felix; Gabsteiger, Florian; von Tscharner, Vinzenz; Lochmann, Matthias

2014-01-01

EEG involves the recording, analysis, and interpretation of voltages recorded on the human scalp which originate from brain gray matter. EEG is one of the most popular methods of studying and understanding the processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements that are performed in response to the environment. However, there are methodological difficulties which can occur when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions on how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics, and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determinating real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks. PMID:24715858

Altered Brain Dynamics in Patients With Type 1 Diabetes During Working Memory Processing.

PubMed

Embury, Christine M; Wiesman, Alex I; Proskovec, Amy L; Heinrichs-Graham, Elizabeth; McDermott, Timothy J; Lord, Grace H; Brau, Kaitlin L; Drincic, Andjela T; Desouza, Cyrus V; Wilson, Tony W

2018-06-01

It is now generally accepted that diabetes increases the risk for cognitive impairment, but the precise mechanisms are poorly understood. A critical problem in linking diabetes to cognitive impairment is that patients often have multiple comorbidities (e.g., obesity, hypertension) that have been independently linked to cognitive deficits. In the study reported here we focused on young adults with and without type 1 diabetes who were virtually free of such comorbidities. The two groups were matched on major health and demographic factors, and all participants completed a verbal working memory task during magnetoencephalographic brain imaging. We hypothesized that patients would have altered neural dynamics in verbal working memory processing and that these differences would directly relate to clinical disease measures. Accordingly, we found that patients had significantly stronger neural responses in the superior parietal cortices during memory encoding and significantly weaker activity in parietal-occipital regions during maintenance compared with control subjects. Moreover, disease duration and glycemic control were both significantly correlated with neural responses in various brain regions. In conclusion, young healthy adults with type 1 diabetes already have aberrant neural processing relative to their peers without diabetes, using compensatory responses to perform the task, and glucose management and duration may play a central role. © 2018 by the American Diabetes Association.

Simulation of fMRI signals to validate dynamic causal modeling estimation

NASA Astrophysics Data System (ADS)

Anandwala, Mobin; Siadat, Mohamad-Reza; Hadi, Shamil M.

2012-03-01

Through cognitive tasks certain brain areas are activated and also receive increased blood to them. This is modeled through a state system consisting of two separate parts one that deals with the neural node stimulation and the other blood response during that stimulation. The rationale behind using this state system is to validate existing analysis methods such as DCM to see what levels of noise they can handle. Using the forward Euler's method this system was approximated in a series of difference equations. What was obtained was the hemodynamic response for each brain area and this was used to test an analysis tool to estimate functional connectivity between each brain area with a given amount of noise. The importance of modeling this system is to not only have a model for neural response but also to compare to actual data obtained through functional imaging scans.

Role of inflammation and its mediators in acute ischemic stroke

PubMed Central

Jin, Rong; Liu, Lin; Zhang, Shihao; Nanda, Anil; Li, Guohong

2013-01-01

Inflammation plays an important role in the pathogenesis of ischemic stroke and other forms of ischemic brain injury. Increasing evidence suggests that inflammatory response is a double-edged sword, as it not only exacerbates secondary brain injury in the acute stage of stroke but also beneficially contributes to brain recovery after stroke. In this article, we provide an overview on the role of inflammation and its mediators in acute ischemic stroke. We discuss various pro-inflammatory and anti-inflammatory responses in different phases after ischemic stroke and the possible reasons for their failures in clinical trials. Undoubtedly, there is still much to be done in order to translate promising pre-clinical findings into clinical practice. A better understanding of the dynamic balance between pro- and anti-inflammatory responses and identifying the discrepancies between pre-clinical studies and clinical trials may serve as a basis for designing effective therapies. PMID:24006091

Vulnerability of the developing brain to hypoxic-ischemic damage: contribution of the cerebral vasculature to injury and repair?

PubMed Central

Baburamani, Ana A.; Ek, C. Joakim; Walker, David W.; Castillo-Melendez, Margie

2012-01-01

As clinicians attempt to understand the underlying reasons for the vulnerability of different regions of the developing brain to injury, it is apparent that little is known as to how hypoxia-ischemia may affect the cerebrovasculature in the developing infant. Most of the research investigating the pathogenesis of perinatal brain injury following hypoxia-ischemia has focused on excitotoxicity, oxidative stress and an inflammatory response, with the response of the developing cerebrovasculature receiving less attention. This is surprising as the presentation of devastating and permanent injury such as germinal matrix-intraventricular haemorrhage (GM-IVH) and perinatal stroke are of vascular origin, and the origin of periventricular leukomalacia (PVL) may also arise from poor perfusion of the white matter. This highlights that cerebrovasculature injury following hypoxia could primarily be responsible for the injury seen in the brain of many infants diagnosed with hypoxic-ischemic encephalopathy (HIE). Interestingly the highly dynamic nature of the cerebral blood vessels in the fetus, and the fluctuations of cerebral blood flow and metabolic demand that occur following hypoxia suggest that the response of blood vessels could explain both regional protection and vulnerability in the developing brain. However, research into how blood vessels respond following hypoxia-ischemia have mostly been conducted in adult models of ischemia or stroke, further highlighting the need to investigate how the developing cerebrovasculature responds and the possible contribution to perinatal brain injury following hypoxia. This review discusses the current concepts on the pathogenesis of perinatal brain injury, the development of the fetal cerebrovasculature and the blood brain barrier (BBB), and key mediators involved with the response of cerebral blood vessels to hypoxia. PMID:23162470

Abnormal hemodynamic response to forepaw stimulation in rat brain after cocaine injection

NASA Astrophysics Data System (ADS)

Chen, Wei; Park, Kicheon; Choi, Jeonghun; Pan, Yingtian; Du, Congwu

2015-03-01

Simultaneous measurement of hemodynamics is of great importance to evaluate the brain functional changes induced by brain diseases such as drug addiction. Previously, we developed a multimodal-imaging platform (OFI) which combined laser speckle contrast imaging with multi-wavelength imaging to simultaneously characterize the changes in cerebral blood flow (CBF), oxygenated- and deoxygenated- hemoglobin (HbO and HbR) from animal brain. Recently, we upgraded our OFI system that enables detection of hemodynamic changes in response to forepaw electrical stimulation to study potential brain activity changes elicited by cocaine. The improvement includes 1) high sensitivity to detect the cortical response to single forepaw electrical stimulation; 2) high temporal resolution (i.e., 16Hz/channel) to resolve dynamic variations in drug-delivery study; 3) high spatial resolution to separate the stimulation-evoked hemodynamic changes in vascular compartments from those in tissue. The system was validated by imaging the hemodynamic responses to the forepaw-stimulations in the somatosensory cortex of cocaine-treated rats. The stimulations and acquisitions were conducted every 2min over 40min, i.e., from 10min before (baseline) to 30min after cocaine challenge. Our results show that the HbO response decreased first (at ~4min) followed by the decrease of HbR response (at ~6min) after cocaine, and both did not fully recovered for over 30min. Interestingly, while CBF decreased at 4min, it partially recovered at 18min after cocaine administration. The results indicate the heterogeneity of cocaine's effects on vasculature and tissue metabolism, demonstrating the unique capability of optical imaging for brain functional studies.

Distance-responsive genes found in dancing honey bees.

PubMed

Sen Sarma, M; Rodriguez-Zas, S L; Gernat, T; Nguyen, T; Newman, T; Robinson, G E

2010-10-01

We report that regions of the honey bee brain involved in visual processing and learning and memory show a specific genomic response to distance information. These results were obtained with an established method that separates effects of perceived distance from effects of actual distance flown. Individuals forced to shift from a short to perceived long distance to reach a feeding site showed gene expression differences in the optic lobes and mushroom bodies relative to individuals that continued to perceive a short distance, even though they all flew the same distance. Bioinformatic analyses suggest that the genomic response to distance information involves learning and memory systems associated with well-known signaling pathways, synaptic remodeling, transcription factors and protein metabolism. By showing distance-sensitive brain gene expression, our findings also significantly extend the emerging paradigm of the genome as a dynamic regulator of behavior, that is particularly responsive to stimuli important in social life. © 2010 The Authors. Genes, Brain and Behavior © 2010 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

Intracranial spectral amplitude dynamics of perceptual suppression in fronto-insular, occipito-temporal, and primary visual cortex

PubMed Central

Vidal, Juan R.; Perrone-Bertolotti, Marcela; Kahane, Philippe; Lachaux, Jean-Philippe

2015-01-01

If conscious perception requires global information integration across active distant brain networks, how does the loss of conscious perception affect neural processing in these distant networks? Pioneering studies on perceptual suppression (PS) described specific local neural network responses in primary visual cortex, thalamus and lateral prefrontal cortex of the macaque brain. Yet the neural effects of PS have rarely been studied with intracerebral recordings outside these cortices and simultaneously across distant brain areas. Here, we combined (1) a novel experimental paradigm in which we produced a similar perceptual disappearance and also re-appearance by using visual adaptation with transient contrast changes, with (2) electrophysiological observations from human intracranial electrodes sampling wide brain areas. We focused on broadband high-frequency (50–150 Hz, i.e., gamma) and low-frequency (8–24 Hz) neural activity amplitude modulations related to target visibility and invisibility. We report that low-frequency amplitude modulations reflected stimulus visibility in a larger ensemble of recording sites as compared to broadband gamma responses, across distinct brain regions including occipital, temporal and frontal cortices. Moreover, the dynamics of the broadband gamma response distinguished stimulus visibility from stimulus invisibility earlier in anterior insula and inferior frontal gyrus than in temporal regions, suggesting a possible role of fronto-insular cortices in top–down processing for conscious perception. Finally, we report that in primary visual cortex only low-frequency amplitude modulations correlated directly with perceptual status. Interestingly, in this sensory area broadband gamma was not modulated during PS but became positively modulated after 300 ms when stimuli were rendered visible again, suggesting that local networks could be ignited by top–down influences during conscious perception. PMID:25642199

A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

PubMed

Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

2014-01-01

Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

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

PubMed

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

2017-01-01

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

Clinical assessment of cerebrospinal fluid dynamics in hydrocephalus. Guide to interpretation based on observational study.

PubMed

Weerakkody, R A; Czosnyka, M; Schuhmann, M U; Schmidt, E; Keong, N; Santarius, T; Pickard, J D; Czosnyka, Z

2011-08-01

The term hydrocephalus encompasses a range of disorders characterised by clinical symptoms, abnormal brain imaging and derangement of cerebrospinal fluid (CSF) dynamics. The ability to elucidate which patients would benefit from CSF diversion (a shunt or third ventriculostomy) is often unclear. Similar difficulties are often encountered in shunted patients to predict the scope for improvement by shunt re-adjustment or revision. In this study we aimed to update our knowledge of how key quantitative parameters describing CSF dynamics may be used in diagnosis of shunt-responsive hydrocephalus and in the assessment of shunt function. A number of quantitative parameters [including resistance to CSF outflow (Rcsf), pulse amplitude of intracranial pressure waveform (AMP), RAP index and slow vasogenic waves] were studies in 1423 patients with 2665 CSF infusion tests and 305 overnight intracranial pressure (ICP)-monitoring sessions over a 17 year period. We demonstrate our observations for typical values of Pb, Rcsf, AMP, slow vasogenic waves derived from infusion studies or overnight ICP monitoring in differentiating atrophy from shunt-responsive normal pressure hydrocephalus or acute hydrocephalus. From the same variables tested on shunted patients we demonstrate a standardised approach to help differentiate a properly-functioning shunt from underdrainage or overdrainage. Quantitative variables derived from CSF dynamics allow differentiation between clinically overlapping entities such as shunt-responsive normal pressure hydrocephalus and brain atrophy (not shunt responsive) as well as allowing the detection of shunt malfunction (partial or complete blockage) or overdrainage. This observational study is intended to serve as an update for our understanding of quantitative testing of CSF dynamics. © 2011 John Wiley & Sons A/S.

Self-regulated learning in a dynamic coaching model for supporting college students with traumatic brain injury: two case reports.

PubMed

Kennedy, Mary R T; Krause, Miriam O

2011-01-01

To describe a program that integrates self-regulated learning theory with supported education for college students with traumatic brain injury using a dynamic coaching model; to demonstrate the feasibility of developing and implementing such a program; and to identify individualized outcomes. Case study comparisons. University setting. Two severely injured students with cognitive impairments. A dynamic coaching model of supported education which incorporated self-regulated learning was provided for students with traumatic brain injury while attending college. Outcomes were both short and long term including decontextualized standardized test scores, self-reported academic challenges, number and specificity of reported strategies, grades on assignments, number of credits completed versus attempted, and changes in academic status and campus life. Students improved on graded assignments after strategy instruction and reported using more strategies by the end of the year. Students completed most of the credits they attempted, were in good academic standing, and made positive academic decisions. Performance on decontextualized tests pre- and postintervention was variable. It is feasible to deliver a hybrid supported education program that is dynamically responsive to individual students' needs and learning styles. Reasons for including both functional and standardized test outcomes are discussed.

Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms.

PubMed

Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng

2017-08-21

Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

Altered predictive capability of the brain network EEG model in schizophrenia during cognition.

PubMed

Gomez-Pilar, Javier; Poza, Jesús; Gómez, Carlos; Northoff, Georg; Lubeiro, Alba; Cea-Cañas, Benjamín B; Molina, Vicente; Hornero, Roberto

2018-05-12

The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Engaged listeners: shared neural processing of powerful political speeches

PubMed Central

Häcker, Frank E. K.; Honey, Christopher J.; Hasson, Uri

2015-01-01

Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners’ brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages. PMID:25653012

Early auditory processing in musicians and dancers during a contemporary dance piece

PubMed Central

Poikonen, Hanna; Toiviainen, Petri; Tervaniemi, Mari

2016-01-01

The neural responses to simple tones and short sound sequences have been studied extensively. However, in reality the sounds surrounding us are spectrally and temporally complex, dynamic and overlapping. Thus, research using natural sounds is crucial in understanding the operation of the brain in its natural environment. Music is an excellent example of natural stimulation which, in addition to sensory responses, elicits vast cognitive and emotional processes in the brain. Here we show that the preattentive P50 response evoked by rapid increases in timbral brightness during continuous music is enhanced in dancers when compared to musicians and laymen. In dance, fast changes in brightness are often emphasized with a significant change in movement. In addition, the auditory N100 and P200 responses are suppressed and sped up in dancers, musicians and laymen when music is accompanied with a dance choreography. These results were obtained with a novel event-related potential (ERP) method for natural music. They suggest that we can begin studying the brain with long pieces of natural music using the ERP method of electroencephalography (EEG) as has already been done with functional magnetic resonance (fMRI), these two brain imaging methods complementing each other. PMID:27611929

Improved recovery of the hemodynamic response in Diffuse Optical Imaging using short optode separations and state-space modeling

PubMed Central

Gagnon, Louis; Perdue, Katherine; Greve, Douglas N.; Goldenholz, Daniel; Kaskhedikar, Gayatri; Boas, David A.

2011-01-01

Diffuse Optical Imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1 cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R2 coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p < 0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique. PMID:21385616

[Electrophysiological correlates of efficacy of nootropic drugs in the treatment of consequences of traumatic brain injury in adolescents].

PubMed

Iznak, E V; Iznak, A F; Pankratova, E A; Zavadenko, N N; Guzilova, L S; Guzilova, Iu I

2010-01-01

To assess objectively a dynamics of brain functional state, EEG spectral power and peak latency of the P300 component of cognitive auditory evoked potentials have been analyzed in adolescents during the course of nootropic therapy of residual asthenic consequences of traumatic brain injury (ICD-10 F07.2). The study included 76 adolescents, aged 12-18 years, who have undergone severe closed head trauma with brain commotion 1/2--5 years ago. Patients have been divided into 3 groups treated during one month with cerebrolysin, piracetam or magne-B6, respectively. After the end of the nootropic therapy, 77% of patients treated with cerebrolysin as well as 50% of patients treated with piracetam and magne-B6 have demonstrated the positive dynamics of their brain functional state that manifested itself in the appearance of occipital EEG alpha rhythm or in the increase of its spectral power; in the normalization of alpha rhythm frequency; in the decrease in the spectral power of slow wave (theta and delta) EEG activity, in the amount (up to the disappearance) of paroxysmal EEG activity, in the EEG response to hyperventilation and in the shortening of the P300 peak latency. Such positive changes of neurophysiological parameters have been associated with the improvement of clinical conditions of patients and correlated significantly with the dynamics of psychometric scores of attention and memory.

Neuroimaging of Human Balance Control: A Systematic Review

PubMed Central

Wittenberg, Ellen; Thompson, Jessica; Nam, Chang S.; Franz, Jason R.

2017-01-01

This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control. PMID:28443007

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

Infant brain activity while viewing facial movement of point-light displays as measured by near-infrared spectroscopy (NIRS).

PubMed

Ichikawa, Hiroko; Kanazawa, So; Yamaguchi, Masami K; Kakigi, Ryusuke

2010-09-27

Adult observers can quickly identify specific actions performed by an invisible actor from the points of lights attached to the actor's head and major joints. Infants are also sensitive to biological motion and prefer to see it depicted by a dynamic point-light display. In detecting biological motion such as whole body and facial movements, neuroimaging studies have demonstrated the involvement of the occipitotemporal cortex, including the superior temporal sulcus (STS). In the present study, we used the point-light display technique and near-infrared spectroscopy (NIRS) to examine infant brain activity while viewing facial biological motion depicted in a point-light display. Dynamic facial point-light displays (PLD) were made from video recordings of three actors making a facial expression of surprise in a dark room. As in Bassili's study, about 80 luminous markers were scattered over the surface of the actor's faces. In the experiment, we measured infant's hemodynamic responses to these displays using NIRS. We hypothesized that infants would show different neural activity for upright and inverted PLD. The responses were compared to the baseline activation during the presentation of individual still images, which were frames extracted from the dynamic PLD. We found that the concentration of oxy-Hb increased in the right temporal area during the presentation of the upright PLD compared to that of the baseline period. This is the first study to demonstrate that infant's brain activity in face processing is induced only by the motion cue of facial movement depicted by dynamic PLD. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Spatiotemporal dynamics of optogenetically induced and spontaneous seizure transitions in primary generalized epilepsy

PubMed Central

Truccolo, Wilson; Wang, Jing; Nurmikko, Arto V.

2014-01-01

Transitions into primary generalized epileptic seizures occur abruptly and synchronously across the brain. Their potential triggers remain unknown. We used optogenetics to causally test the hypothesis that rhythmic population bursting of excitatory neurons in a local neocortical region can rapidly trigger absence seizures. Most previous studies have been purely correlational, and it remains unclear whether epileptiform events induced by rhythmic stimulation (e.g., sensory/electrical) mimic actual spontaneous seizures, especially regarding their spatiotemporal dynamics. In this study, we used a novel combination of intracortical optogenetic stimulation and microelectrode array recordings in freely moving WAG/Rij rats, a model of absence epilepsy with a cortical focus in the somatosensory cortex (SI). We report three main findings: 1) Brief rhythmic bursting, evoked by optical stimulation of neocortical excitatory neurons at frequencies around 10 Hz, induced seizures consisting of self-sustained spike-wave discharges (SWDs) for about 10% of stimulation trials. The probability of inducing seizures was frequency-dependent, reaching a maximum at 10 Hz. 2) Local field potential power before stimulation and response amplitudes during stimulation both predicted seizure induction, demonstrating a modulatory effect of brain states and neural excitation levels. 3) Evoked responses during stimulation propagated as cortical waves, likely reaching the cortical focus, which in turn generated self-sustained SWDs after stimulation was terminated. Importantly, SWDs during induced and spontaneous seizures propagated with the same spatiotemporal dynamics. Our findings demonstrate that local rhythmic bursting of excitatory neurons in neocortex at particular frequencies, under susceptible ongoing brain states, is sufficient to trigger primary generalized seizures with stereotypical spatiotemporal dynamics. PMID:25552645

In vivo imaging of the neurovascular unit in CNS disease

PubMed Central

Merlini, Mario; Davalos, Dimitrios; Akassoglou, Katerina

2014-01-01

The neurovascular unit—comprised of glia, pericytes, neurons and cerebrovasculature—is a dynamic interface that ensures physiological central nervous system (CNS) functioning. In disease dynamic remodeling of the neurovascular interface triggers a cascade of responses that determine the extent of CNS degeneration and repair. The dynamics of these processes can be adequately captured by imaging in vivo, which allows the study of cellular responses to environmental stimuli and cell-cell interactions in the living brain in real time. This perspective focuses on intravital imaging studies of the neurovascular unit in stroke, multiple sclerosis (MS) and Alzheimer disease (AD) models and discusses their potential for identifying novel therapeutic targets. PMID:25197615

Beyond static measures: A review of functional magnetic resonance spectroscopy and its potential to investigate dynamic glutamatergic abnormalities in schizophrenia.

PubMed

Jelen, Luke A; King, Sinead; Mullins, Paul G; Stone, James M

2018-05-01

Abnormalities of the glutamate system are increasingly implicated in schizophrenia but their exact nature remains unknown. Proton magnetic resonance spectroscopy ( 1 H-MRS), while fundamental in revealing glutamatergic alterations in schizophrenia, has, until recently, been significantly limited and thought to only provide static measures. Functional magnetic resonance spectroscopy (fMRS), which uses sequential scans for dynamic measurement of a range of brain metabolites in activated brain areas, has lately been applied to a variety of task or stimulus conditions, producing interesting insights into neurometabolite responses to neural activation. Here, we summarise the existing 1 H-MRS studies of brain glutamate in schizophrenia. We then present a comprehensive review of research studies that have utilised fMRS, and lastly consider how fMRS methods might further the understanding of glutamatergic abnormalities in schizophrenia.

Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition

PubMed Central

Daitch, Amy L.; Foster, Brett L.; Schrouff, Jessica; Rangarajan, Vinitha; Kaşikçi, Itır; Gattas, Sandra; Parvizi, Josef

2016-01-01

Brain areas within the lateral parietal cortex (LPC) and ventral temporal cortex (VTC) have been shown to code for abstract quantity representations and for symbolic numerical representations, respectively. To explore the fast dynamics of activity within each region and the interaction between them, we used electrocorticography recordings from 16 neurosurgical subjects implanted with grids of electrodes over these two regions and tracked the activity within and between the regions as subjects performed three different numerical tasks. Although our results reconfirm the presence of math-selective hubs within the VTC and LPC, we report here a remarkable heterogeneity of neural responses within each region at both millimeter and millisecond scales. Moreover, we show that the heterogeneity of response profiles within each hub mirrors the distinct patterns of functional coupling between them. Our results support the existence of multiple bidirectional functional loops operating between discrete populations of neurons within the VTC and LPC during the visual processing of numerals and the performance of arithmetic functions. These findings reveal information about the dynamics of numerical processing in the brain and also provide insight into the fine-grained functional architecture and connectivity within the human brain. PMID:27821758

Down syndrome's brain dynamics: analysis of fractality in resting state.

PubMed

Hemmati, Sahel; Ahmadlou, Mehran; Gharib, Masoud; Vameghi, Roshanak; Sajedi, Firoozeh

2013-08-01

To the best knowledge of the authors there is no study on nonlinear brain dynamics of down syndrome (DS) patients, whereas brain is a highly complex and nonlinear system. In this study, fractal dimension of EEG, as a key characteristic of brain dynamics, showing irregularity and complexity of brain dynamics, was used for evaluation of the dynamical changes in the DS brain. The results showed higher fractality of the DS brain in almost all regions compared to the normal brain, which indicates less centrality and higher irregular or random functioning of the DS brain regions. Also, laterality analysis of the frontal lobe showed that the normal brain had a right frontal laterality of complexity whereas the DS brain had an inverse pattern (left frontal laterality). Furthermore, the high accuracy of 95.8 % obtained by enhanced probabilistic neural network classifier showed the potential of nonlinear dynamic analysis of the brain for diagnosis of DS patients. Moreover, the results showed that the higher EEG fractality in DS is associated with the higher fractality in the low frequencies (delta and theta), in broad regions of the brain, and the high frequencies (beta and gamma), majorly in the frontal regions.

Looking for sexual selection in the female brain.

PubMed

Cummings, Molly E

2012-08-19

Female mate choice behaviour has significant evolutionary consequences, yet its mechanistic origins are not fully understood. Recent studies of female sensory systems have made great strides in identifying internal mechanisms governing female preferences. Only recently, however, have we begun to identify the dynamic genomic response associated with mate choice behaviour. Poeciliids provide a powerful comparative system to examine genomic responses governing mate choice and female preference behaviour, given the great range of mating systems: from female mate choice taxa with ornamental courting males to species lacking male ornamentation and exhibiting only male coercion. Furthermore, they exhibit laboratory-tractable preference responses without sexual contact that are decoupled from reproductive state, allowing investigators to isolate mechanisms in the brain without physiological confounds. Early investigations with poeciliid species (Xiphophorus nigrensis and Gambusia affinis) have identified putative candidate genes associated with female preference response and highlight a possible genomic pathway underlying female social interactions with males linked functionally with synaptic plasticity and learning processes. This network is positively correlated with female preference behaviour in the female mate choice species, but appears inhibited in the male coercive species. This behavioural genomics approach provides opportunity to elucidate the fundamental building blocks, and evolutionary dynamics, of sexual selection.

Shifted dynamic interactions between subcortical nuclei and inferior frontal gyri during response preparation in persistent developmental stuttering.

PubMed

Metzger, F Luise; Auer, Tibor; Helms, Gunther; Paulus, Walter; Frahm, Jens; Sommer, Martin; Neef, Nicole E

2018-01-01

Persistent developmental stuttering is associated with basal ganglia dysfunction or dopamine dysregulation. Here, we studied whole-brain functional connectivity to test how basal ganglia structures coordinate and reorganize sensorimotor brain networks in stuttering. To this end, adults who stutter and fluent speakers (control participants) performed a response anticipation paradigm in the MRI scanner. The preparation of a manual Go/No-Go response reliably produced activity in the basal ganglia and thalamus and particularly in the substantia nigra. Strikingly, in adults who stutter, substantia nigra activity correlated positively with stuttering severity. Furthermore, functional connectivity analyses yielded altered task-related network formations in adults who stutter compared to fluent speakers. Specifically, in adults who stutter, the globus pallidus and the thalamus showed increased network synchronization with the inferior frontal gyrus. This implies dynamic shifts in the response preparation-related network organization through the basal ganglia in the context of a non-speech motor task in stuttering. Here we discuss current findings in the traditional framework of how D1 and D2 receptor activity shapes focused movement selection, thereby suggesting a disproportional involvement of the direct and the indirect pathway in stuttering.

Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601

Early alterations of social brain networks in young children with autism

PubMed Central

Kojovic, Nada; Rihs, Tonia Anahi; Jan, Reem Kais; Franchini, Martina; Plomp, Gijs; Vulliemoz, Serge; Eliez, Stephan; Michel, Christoph Martin; Schaer, Marie

2018-01-01

Social impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. We recorded the gaze patterns and brain activity of toddlers with ASD and their typically developing peers while they explored dynamic social scenes. Directed functional connectivity analyses based on electrical source imaging revealed frequency specific network atypicalities in the theta and alpha frequency bands, manifesting as alterations in both the driving and the connections from key nodes of the social brain associated with autism. Analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with less atypical gaze patterns and lower clinical impairment. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD. PMID:29482718

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

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

Farjam, Reza; Tsien, Christina I.; Lawrence, Theodore S.

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. Amore » DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.« less

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

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

Farjam, Reza; Tsien, Christina I.; Lawrence, Theodore S.

2014-01-15

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. Amore » DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.« less

Data-driven analysis of functional brain interactions during free listening to music and speech.

PubMed

Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming

2015-06-01

Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.

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

Villien, Marjorie; Wey, Hsiao-Ying; Mandeville, Joseph B.

We report that glucose is the principal source of energy for the brain and yet the dynamic response of glucose utilization to changes in brain activity is still not fully understood. Positron emission tomography (PET) allows quantitative measurement of glucose metabolism using 2-[18F]-fluorodeoxyglucose (FDG). However, FDG PET in its current form provides an integral (or average) of glucose consumption over tens of minutes and lacks the temporal information to capture physiological alterations associated with changes in brain activity induced by tasks or drug challenges. Traditionally, changes in glucose utilization are inferred by comparing two separate scans, which significantly limits themore » utility of the method. We report a novel method to track changes in FDG metabolism dynamically, with higher temporal resolution than exists to date and within a single session. Using a constant infusion of FDG, we demonstrate that our technique (termed fPET-FDG) can be used in an analysis pipeline similar to fMRI to define within-session differential metabolic responses. We use visual stimulation to demonstrate the feasibility of this method. Ultimately, this new method has a great potential to be used in research protocols and clinical settings since fPET-FDG imaging can be performed with most PET scanners and data acquisition and analysis are straightforward. fPET-FDG is a highly complementary technique to MRI and provides a rich new way to observe functional changes in brain metabolism.« less

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

PubMed Central

Havlicek, Martin; Friston, Karl J.; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2011-01-01

This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. PMID:21396454

Functional neural networks underlying response inhibition in adolescents and adults.

PubMed

Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2007-07-19

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

Functional neural networks underlying response inhibition in adolescents and adults

PubMed Central

Stevens, Michael C.; Kiehl, Kent A.; Pearlson, Godfrey D.; Calhoun, Vince D.

2008-01-01

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally-integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by frontostriatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development. PMID:17467816

Aberrant reward center response to partner reputation during a social exchange game in generalized social phobia.

PubMed

Sripada, Chandra; Angstadt, Michael; Liberzon, Israel; McCabe, Kevin; Phan, K Luan

2013-04-01

Generalized social anxiety disorder (GSAD) is characterized by excessive fear of public scrutiny and reticence in social engagement. Previous studies have probed the neural basis of GSAD often using static, noninteractive stimuli (e.g., face photographs) and have identified dysfunction in fear circuitry. We sought to investigate brain-based dysfunction in GSAD during more real-world, dynamic social interactions, focusing on the role of reward-related regions that are implicated in social decision-making. Thirty-six healthy individuals (healthy control [HC]) and 36 individuals with GSAD underwent functional magnetic resonance imaging (fMRI) scanning while participating in a behavioral economic game ("Trust Game") involving iterative exchanges with fictive partners who acquire differential reputations for reciprocity. We investigated brain responses to reciprocation of trust in one's social partner, and how these brain responses are modulated by partner reputation for repayment. In both HC and GSAD, receipt of reciprocity robustly engaged ventral striatum, a region implicated in reward. In HC, striatal responses to reciprocity were specific to partners who have consistently returned the investment ("cooperative partners"), and were absent for partners who lack a cooperative reputation. In GSAD, modulation of striatal responses by partner reputation was absent. Social anxiety severity predicted diminished responses to cooperative partners. These results suggest abnormalities in GSAD in reward-related striatal mechanisms that may be important for the initiation, valuation, and maintenance of cooperative social relationships. Moreover, this study demonstrates that dynamic, interactive task paradigms derived from economics can help illuminate novel mechanisms of pathology in psychiatric illnesses in which social dysfunction is a cardinal feature. © 2013 Wiley Periodicals, Inc.

Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD.

PubMed

Atasoy, Selen; Roseman, Leor; Kaelen, Mendel; Kringelbach, Morten L; Deco, Gustavo; Carhart-Harris, Robin L

2017-12-15

Recent studies have started to elucidate the effects of lysergic acid diethylamide (LSD) on the human brain but the underlying dynamics are not yet fully understood. Here we used 'connectome-harmonic decomposition', a novel method to investigate the dynamical changes in brain states. We found that LSD alters the energy and the power of individual harmonic brain states in a frequency-selective manner. Remarkably, this leads to an expansion of the repertoire of active brain states, suggestive of a general re-organization of brain dynamics given the non-random increase in co-activation across frequencies. Interestingly, the frequency distribution of the active repertoire of brain states under LSD closely follows power-laws indicating a re-organization of the dynamics at the edge of criticality. Beyond the present findings, these methods open up for a better understanding of the complex brain dynamics in health and disease.

Dynamics of brain activity in motor and frontal cortical areas during music listening: a magnetoencephalographic study.

PubMed

Popescu, Mihai; Otsuka, Asuka; Ioannides, Andreas A

2004-04-01

There are formidable problems in studying how 'real' music engages the brain over wide ranges of temporal scales extending from milliseconds to a lifetime. In this work, we recorded the magnetoencephalographic signal while subjects listened to music as it unfolded over long periods of time (seconds), and we developed and applied methods to correlate the time course of the regional brain activations with the dynamic aspects of the musical sound. We showed that frontal areas generally respond with slow time constants to the music, reflecting their more integrative mode; motor-related areas showed transient-mode responses to fine temporal scale structures of the sound. The study combined novel analysis techniques designed to capture and quantify fine temporal sequencing from the authentic musical piece (characterized by a clearly defined rhythm and melodic structure) with the extraction of relevant features from the dynamics of the regional brain activations. The results demonstrated that activity in motor-related structures, specifically in lateral premotor areas, supplementary motor areas, and somatomotor areas, correlated with measures of rhythmicity derived from the music. These correlations showed distinct laterality depending on how the musical performance deviated from the strict tempo of the music score, that is, depending on the musical expression.

Development, Validation and Parametric study of a 3-Year-Old Child Head Finite Element Model

NASA Astrophysics Data System (ADS)

Cui, Shihai; Chen, Yue; Li, Haiyan; Ruan, ShiJie

2015-12-01

Traumatic brain injury caused by drop and traffic accidents is an important reason for children's death and disability. Recently, the computer finite element (FE) head model has been developed to investigate brain injury mechanism and biomechanical responses. Based on CT data of a healthy 3-year-old child head, the FE head model with detailed anatomical structure was developed. The deep brain structures such as white matter, gray matter, cerebral ventricle, hippocampus, were firstly created in this FE model. The FE model was validated by comparing the simulation results with that of cadaver experiments based on reconstructing the child and adult cadaver experiments. In addition, the effects of skull stiffness on the child head dynamic responses were further investigated. All the simulation results confirmed the good biofidelity of the FE model.

Identification of the Upward Movement of Human CSF In Vivo and its Relation to the Brain Venous System.

PubMed

Dreha-Kulaczewski, Steffi; Joseph, Arun A; Merboldt, Klaus-Dietmar; Ludwig, Hans-Christoph; Gärtner, Jutta; Frahm, Jens

2017-03-01

CSF flux is involved in the pathophysiology of neurodegenerative diseases and cognitive impairment after traumatic brain injury, all hallmarked by the accumulation of cellular metabolic waste. Its effective disposal via various CSF routes has been demonstrated in animal models. In contrast, the CSF dynamics in humans are still poorly understood. Using novel real-time MRI, forced inspiration has been identified recently as a main driving force of CSF flow in the human brain. Exploiting technical advances toward real-time phase-contrast MRI, the current work analyzed directions, velocities, and volumes of human CSF flow within the brain aqueduct as part of the internal ventricular system and in the spinal canal during respiratory cycles. A consistent upward CSF movement toward the brain in response to forced inspiration was seen in all subjects at the aqueduct, in 11/12 subjects at thoracic level 2, and in 4/12 subjects at thoracic level 5. Concomitant analyses of CSF dynamics and cerebral venous blood flow, that is, in epidural veins at cervical level 3, uniquely demonstrated CSF and venous flow to be closely communicating cerebral fluid systems in which inspiration-induced downward flow of venous blood due to reduced intrathoracic pressure is counterbalanced by an upward movement of CSF. The results extend our understanding of human CSF flux and open important clinical implications, including concepts for drug delivery and new classifications and therapeutic options for various forms of hydrocephalus and idiopathic intracranial hypertension. SIGNIFICANCE STATEMENT Effective disposal of brain cellular waste products via CSF has been demonstrated repeatedly in animal models. However, CSF dynamics in humans are still poorly understood. A novel quantitative real-time MRI technique yielded in vivo CSF flow directions, velocities, and volumes in the human brain and upper spinal canal. CSF moved upward toward the head in response to forced inspiration. Concomitant analysis of brain venous blood flow indicated that CSF and venous flux act as closely communicating systems. The finding of a human CSF-venous network with upward CSF net movement opens new clinical concepts for drug delivery and new classifications and therapeutic options for various forms of hydrocephalus and ideopathic intracranial hypertension. Copyright © 2017 the authors 0270-6474/17/372395-08$15.00/0.

The MNESIS model: Memory systems and processes, identity and future thinking.

PubMed

Eustache, Francis; Viard, Armelle; Desgranges, Béatrice

2016-07-01

The Memory NEo-Structural Inter-Systemic model (MNESIS; Eustache and Desgranges, Neuropsychology Review, 2008) is a macromodel based on neuropsychological data which presents an interactive construction of memory systems and processes. Largely inspired by Tulving's SPI model, MNESIS puts the emphasis on the existence of different memory systems in humans and their reciprocal relations, adding new aspects, such as the episodic buffer proposed by Baddeley. The more integrative comprehension of brain dynamics offered by neuroimaging has contributed to rethinking the existence of memory systems. In the present article, we will argue that understanding the concept of memory by dividing it into systems at the functional level is still valid, but needs to be considered in the light of brain imaging. Here, we reinstate the importance of this division in different memory systems and illustrate, with neuroimaging findings, the links that operate between memory systems in response to task demands that constrain the brain dynamics. During a cognitive task, these memory systems interact transiently to rapidly assemble representations and mobilize functions to propose a flexible and adaptative response. We will concentrate on two memory systems, episodic and semantic memory, and their links with autobiographical memory. More precisely, we will focus on interactions between episodic and semantic memory systems in support of 1) self-identity in healthy aging and in brain pathologies and 2) the concept of the prospective brain during future projection. In conclusion, this MNESIS global framework may help to get a general representation of human memory and its brain implementation with its specific components which are in constant interaction during cognitive processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

Brain activity correlates with emotional perception induced by dynamic avatars.

PubMed

Goldberg, Hagar; Christensen, Andrea; Flash, Tamar; Giese, Martin A; Malach, Rafael

2015-11-15

An accurate judgment of the emotional state of others is a prerequisite for successful social interaction and hence survival. Thus, it is not surprising that we are highly skilled at recognizing the emotions of others. Here we aimed to examine the neuronal correlates of emotion recognition from gait. To this end we created highly controlled dynamic body-movement stimuli based on real human motion-capture data (Roether et al., 2009). These animated avatars displayed gait in four emotional (happy, angry, fearful, and sad) and speed-matched neutral styles. For each emotional gait and its equivalent neutral gait, avatars were displayed at five morphing levels between the two. Subjects underwent fMRI scanning while classifying the emotions and the emotional intensity levels expressed by the avatars. Our results revealed robust brain selectivity to emotional compared to neutral gait stimuli in brain regions which are involved in emotion and biological motion processing, such as the extrastriate body area (EBA), fusiform body area (FBA), superior temporal sulcus (STS), and the amygdala (AMG). Brain activity in the amygdala reflected emotional awareness: for visually identical stimuli it showed amplified stronger response when the stimulus was perceived as emotional. Notably, in avatars gradually morphed along an emotional expression axis there was a parametric correlation between amygdala activity and emotional intensity. This study extends the mapping of emotional decoding in the human brain to the domain of highly controlled dynamic biological motion. Our results highlight an extensive level of brain processing of emotional information related to body language, which relies mostly on body kinematics. Copyright © 2015. Published by Elsevier Inc.

Immunoadolescence: Neuroimmune development and adolescent behavior

PubMed Central

Brenhouse, Heather C.; Schwarz, Jaclyn M.

2016-01-01

The brain is increasingly appreciated to be a constantly rewired organ that yields age-specific behaviors and responses to the environment. Adolescence in particular is a unique period characterized by continued brain maturation, superimposed with transient needs of the organism to traverse a leap from parental dependence to independence. Here we describe how these needs require immune maturation, as well as brain maturation. Our immune system, which protects us from pathogens and regulates inflammation, is in constant communication with our nervous system. Together, neuro-immune signaling regulates our behavioral responses to the environment, making this interaction a likely substrate for adolescent development. We review here the identified as well as understudied components of neuro-immune interactions during adolescence. Synaptic pruning, neurite outgrowth, and neurotransmitter release during adolescence all regulate—and are regulated by—immune signals, which occur via blood-brain barrier dynamics and glial activity. We discuss these processes, as well as how immune signaling during this transitional period of development confers differential effects on behavior and vulnerability to mental illness. PMID:27260127

Neural response to working memory demand predicts neurocognitive deficits in HIV.

PubMed

Cohen, Ronald A; Siegel, S; Gullett, J M; Porges, E; Woods, A J; Huang, H; Zhu, Y; Tashima, K; Ding, M-Z

2018-06-01

Human immunodeficiency virus (HIV) continues to have adverse effects on cognition and the brain in many infected people, despite a reduced incidence of HIV-associated dementia with combined antiretroviral therapy (cART). Working memory is often affected, along with attention, executive control, and cognitive processing speed. Verbal working memory (VWM) requires the interaction of each of the cognitive component processes along with a phonological loop for verbal repetition and rehearsal. HIV-related functional brain response abnormalities during VWM are evident in functional MRI (fMRI), though the neural substrate underlying these neurocognitive deficits is not well understood. The current study addressed this by comparing 24 HIV+ to 27 demographically matched HIV-seronegative (HIV-) adults with respect to fMRI activation on a VWM paradigm (n-back) relative to performance on two standardized tests of executive control, attention and processing speed (Stroop and Trail Making A-B). As expected, the HIV+ group had deficits on these neurocognitive tests compared to HIV- controls, and also differed in neural response on fMRI relative to neuropsychological performance. Reduced activation in VWM task-related brain regions on the 2-back was associated with Stroop interference deficits in HIV+ but not with either Trail Making A or B performance. Activation of the posterior cingulate cortex (PCC) of the default mode network during rest was associated with Hopkins Verbal Learning Test-2 (HVLT-2) learning in HIV+. These effects were not observed in the HIV- controls. Reduced dynamic range of neural response was also evident in HIV+ adults when activation on the 2-back condition was compared to the extent of activation of the default mode network during periods of rest. Neural dynamic range was associated with both Stroop and HVLT-2 performance. These findings provide evidence that HIV-associated alterations in neural activation induced by VWM demands and during rest differentially predict executive-attention and verbal learning deficits. That the Stroop, but not Trail Making was associated with VWM activation suggests that attentional regulation difficulties in suppressing interference and/or conflict regulation are a component of working memory deficits in HIV+ adults. Alterations in neural dynamic range may be a useful index of the impact of HIV on functional brain response and as a fMRI metric in predicting cognitive outcomes.

Dynamic representation of partially occluded objects in primate prefrontal and visual cortex

PubMed Central

Choi, Hannah; Shea-Brown, Eric

2017-01-01

Successful recognition of partially occluded objects is presumed to involve dynamic interactions between brain areas responsible for vision and cognition, but neurophysiological evidence for the involvement of feedback signals is lacking. Here, we demonstrate that neurons in the ventrolateral prefrontal cortex (vlPFC) of monkeys performing a shape discrimination task respond more strongly to occluded than unoccluded stimuli. In contrast, neurons in visual area V4 respond more strongly to unoccluded stimuli. Analyses of V4 response dynamics reveal that many neurons exhibit two transient response peaks, the second of which emerges after vlPFC response onset and displays stronger selectivity for occluded shapes. We replicate these findings using a model of V4/vlPFC interactions in which occlusion-sensitive vlPFC neurons feed back to shape-selective V4 neurons, thereby enhancing V4 responses and selectivity to occluded shapes. These results reveal how signals from frontal and visual cortex could interact to facilitate object recognition under occlusion. PMID:28925354

Functional brain microstate predicts the outcome in a visuospatial working memory task.

PubMed

Muthukrishnan, Suriya-Prakash; Ahuja, Navdeep; Mehta, Nalin; Sharma, Ratna

2016-11-01

Humans have limited capacity of processing just up to 4 integrated items of information in the working memory. Thus, it is inevitable to commit more errors when challenged with high memory loads. However, the neural mechanisms that determine the accuracy of response at high memory loads still remain unclear. High temporal resolution of Electroencephalography (EEG) technique makes it the best tool to resolve the temporal dynamics of brain networks. EEG-defined microstate is the quasi-stable scalp electrical potential topography that represents the momentary functional state of brain. Thus, it has been possible to assess the information processing currently performed by the brain using EEG microstate analysis. We hypothesize that the EEG microstate preceding the trial could determine its outcome in a visuospatial working memory (VSWM) task. Twenty-four healthy participants performed a high memory load VSWM task, while their brain activity was recorded using EEG. Four microstate maps were found to represent the functional brain state prior to the trials in the VSWM task. One pre-trial microstate map was found to determine the accuracy of subsequent behavioural response. The intracranial generators of the pre-trial microstate map that determined the response accuracy were localized to the visuospatial processing areas at bilateral occipital, right temporal and limbic cortices. Our results imply that the behavioural outcome in a VSWM task could be determined by the intensity of activation of memory representations in the visuospatial processing brain regions prior to the trial. Copyright © 2016 Elsevier B.V. All rights reserved.

Neuroscience is awaiting for a breakthrough: an essay bridging the concepts of Descartes, Einstein, Heisenberg, Hebb and Hayek with the explanatory formulations in this special issue.

PubMed

Başar, Erol; Karakaş, Sirel

2006-05-01

The paper presents gedankenmodels which, based on the theories and models in the present special issue, describe the conditions for a breakthrough in brain sciences and neuroscience. The new model is based on contemporary findings which show that the brain and its cognitive processes show super-synchronization. Accordingly, understanding the brain/body-mind complex is possible only when these three are considered as a wholistic entity and not as discrete structures or functions. Such a breakthrough and the related perspectives to the brain/body-mind complex will involve a transition from the mechanistic Cartesian system to a nebulous Cartesian system, one that is basically characterized by parallel computing and is further parallel to quantum mechanics. This integrated outlook on the brain/body-mind, or dynamic functionality, will make the treatment of also the meta-cognitive processes and the greater part of the iceberg, the unconscious, possible. All this will be possible only through the adoption of a multidisciplinary approach that will bring together the knowledge and the technology of the four P's which consist of physics, physiology, psychology and philosophy. The genetic approach to the functional dynamics of the brain/body-mind, where the oscillatory responses were found to be laws of brain activity, is presented in this volume as one of the most recent perspectives of neuroscience.

Sleep Deprivation and Neurobehavioral Dynamics

PubMed Central

Basner, Mathias; Rao, Hengyi; Goel, Namni; Dinges, David F.

2013-01-01

Lifestyles involving sleep deprivation are common, despite mounting evidence that both acute total sleep deprivation and chronically restricted sleep degrade neurobehavioral functions associated with arousal, attention, memory and state stability. Current research suggests dynamic differences in the way the central nervous system responds to acute versus chronic sleep restriction, which is reflected in new models of sleep-wake regulation. Chronic sleep restriction likely induces long-term neuromodulatory changes in brain physiology that could explain why recovery from it may require more time than from acute sleep loss. High intraclass correlations in neurobehavioral responses to sleep loss suggest that these trait-like differences are phenotypic and may include genetic components. Sleep deprivation induces changes in brain metabolism and neural activation that involve distributed networks and connectivity. PMID:23523374

Dynamic functional connectivity and individual differences in emotions during social stress.

PubMed

Tobia, Michael J; Hayashi, Koby; Ballard, Grey; Gotlib, Ian H; Waugh, Christian E

2017-12-01

Exposure to acute stress induces multiple emotional responses, each with their own unique temporal dynamics. Dynamic functional connectivity (dFC) measures the temporal variability of network synchrony and captures individual differences in network neurodynamics. This study investigated the relationship between dFC and individual differences in emotions induced by an acute psychosocial stressor. Sixteen healthy adult women underwent fMRI scanning during a social evaluative threat (SET) task, and retrospectively completed questionnaires that assessed individual differences in subjectively experienced positive and negative emotions about stress and stress relief during the task. Group dFC was decomposed with parallel factor analysis (PARAFAC) into 10 components, each with a temporal signature, spatial network of functionally connected regions, and vector of participant loadings that captures individual differences in dFC. Participant loadings of two networks were positively correlated with stress-related emotions, indicating the existence of networks for positive and negative emotions. The emotion-related networks involved the ventromedial prefrontal cortex, cingulate cortex, anterior insula, and amygdala, among other distributed brain regions, and time signatures for these emotion-related networks were uncorrelated. These findings demonstrate that individual differences in stress-induced positive and negative emotions are each uniquely associated with large-scale brain networks, and suggest that dFC is a mechanism that generates individual differences in the emotional components of the stress response. Hum Brain Mapp 38:6185-6205, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

NASA Astrophysics Data System (ADS)

Romeira, Bruno; Figueiredo, José M. L.; Javaloyes, Julien

2017-11-01

With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing.

Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications.

PubMed

Romeira, Bruno; Figueiredo, José M L; Javaloyes, Julien

2017-11-01

With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing.

Dynamic Changes in Amygdala Psychophysiological Connectivity Reveal Distinct Neural Networks for Facial Expressions of Basic Emotions.

PubMed

Diano, Matteo; Tamietto, Marco; Celeghin, Alessia; Weiskrantz, Lawrence; Tatu, Mona-Karina; Bagnis, Arianna; Duca, Sergio; Geminiani, Giuliano; Cauda, Franco; Costa, Tommaso

2017-03-27

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.

In Silico Investigation of Intracranial Blast Mitigation with Relevance to Military Traumatic Brain Injury

DTIC Science & Technology

2010-09-01

how personal protective equipment affects the brain’s response to blasts. In this study we investigated the effect of the Advanced Combat...analyzing stress wave propagation, which is the main dynamic effect loading the brain tissue during a blast event. We consider two key metrics of stress ...Cauchy stress tensor, and sij ¼ σij − 13σkkδij are the compo- nents of the deviatoric stress tensor (24). Fig. 1 shows snapshots of the pressure

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

PubMed Central

Meyer-Bäse, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts. PMID:29051730

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

PubMed

Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts.

Calcium-dependent molecular fMRI using a magnetic nanosensor.

PubMed

Okada, Satoshi; Bartelle, Benjamin B; Li, Nan; Breton-Provencher, Vincent; Lee, Jiyoung J; Rodriguez, Elisenda; Melican, James; Sur, Mriganka; Jasanoff, Alan

2018-06-01

Calcium ions are ubiquitous signalling molecules in all multicellular organisms, where they mediate diverse aspects of intracellular and extracellular communication over widely varying temporal and spatial scales 1 . Though techniques to map calcium-related activity at a high resolution by optical means are well established, there is currently no reliable method to measure calcium dynamics over large volumes in intact tissue 2 . Here, we address this need by introducing a family of magnetic calcium-responsive nanoparticles (MaCaReNas) that can be detected by magnetic resonance imaging (MRI). MaCaReNas respond within seconds to [Ca 2+ ] changes in the 0.1-1.0 mM range, suitable for monitoring extracellular calcium signalling processes in the brain. We show that the probes permit the repeated detection of brain activation in response to diverse stimuli in vivo. MaCaReNas thus provide a tool for calcium-activity mapping in deep tissue and offer a precedent for the development of further nanoparticle-based sensors for dynamic molecular imaging with MRI.

Calcium-dependent molecular fMRI using a magnetic nanosensor

NASA Astrophysics Data System (ADS)

Okada, Satoshi; Bartelle, Benjamin B.; Li, Nan; Breton-Provencher, Vincent; Lee, Jiyoung J.; Rodriguez, Elisenda; Melican, James; Sur, Mriganka; Jasanoff, Alan

2018-06-01

Calcium ions are ubiquitous signalling molecules in all multicellular organisms, where they mediate diverse aspects of intracellular and extracellular communication over widely varying temporal and spatial scales1. Though techniques to map calcium-related activity at a high resolution by optical means are well established, there is currently no reliable method to measure calcium dynamics over large volumes in intact tissue2. Here, we address this need by introducing a family of magnetic calcium-responsive nanoparticles (MaCaReNas) that can be detected by magnetic resonance imaging (MRI). MaCaReNas respond within seconds to [Ca2+] changes in the 0.1-1.0 mM range, suitable for monitoring extracellular calcium signalling processes in the brain. We show that the probes permit the repeated detection of brain activation in response to diverse stimuli in vivo. MaCaReNas thus provide a tool for calcium-activity mapping in deep tissue and offer a precedent for the development of further nanoparticle-based sensors for dynamic molecular imaging with MRI.

Mapping and characterization of positive and negative BOLD responses to visual stimulation in multiple brain regions at 7T.

PubMed

Jorge, João; Figueiredo, Patrícia; Gruetter, Rolf; van der Zwaag, Wietske

2018-06-01

External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard stimulation, occurring in various brain regions within and beyond the visual cortex. Recently-proposed accelerated fMRI techniques were employed for data acquisition, and procedures for exclusion of large draining vein contributions, together with ICA-assisted denoising, were included in the analysis to improve response estimation. Besides the visual cortex, significant PBRs were found in the lateral geniculate nucleus and superior colliculus, as well as the pre-central sulcus; in these regions, response durations increased monotonically with stimulus duration, in tight covariation with the visual PBR duration. Significant NBRs were found in the visual cortex, auditory cortex, default-mode network (DMN) and superior parietal lobule; NBR durations also tended to increase with stimulus duration, but were significantly less sustained than the visual PBR, especially for the DMN and superior parietal lobule. Responses in visual and auditory cortex were further studied for checkerboard contrast dependence, and their amplitudes were found to increase monotonically with contrast, linearly correlated with the visual PBR amplitude. Overall, these findings suggest the presence of dynamic neuronal interactions across multiple brain regions, sensitive to stimulus intensity and duration, and demonstrate the richness of information obtainable when jointly mapping positive and negative BOLD responses at a whole-brain scale, with ultra-high field fMRI. © 2018 Wiley Periodicals, Inc.

Engaged listeners: shared neural processing of powerful political speeches.

PubMed

Schmälzle, Ralf; Häcker, Frank E K; Honey, Christopher J; Hasson, Uri

2015-08-01

Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners' brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Investigating the dynamics of the brain response to music: A central role of the ventral striatum/nucleus accumbens.

PubMed

Mueller, Karsten; Fritz, Thomas; Mildner, Toralf; Richter, Maxi; Schulze, Katrin; Lepsien, Jöran; Schroeter, Matthias L; Möller, Harald E

2015-08-01

Ventral striatal activity has been previously shown to correspond well to reward value mediated by music. Here, we investigate the dynamic brain response to music and manipulated counterparts using functional magnetic resonance imaging (fMRI). Counterparts of musical excerpts were produced by either manipulating the consonance/dissonance of the musical fragments or playing them backwards (or both). Results show a greater involvement of the ventral striatum/nucleus accumbens both when contrasting listening to music that is perceived as pleasant and listening to a manipulated version perceived as unpleasant (backward dissonant), as well as in a parametric analysis for increasing pleasantness. Notably, both analyses yielded a ventral striatal response that was strongest during an early phase of stimulus presentation. A hippocampal response to the musical stimuli was also observed, and was largely mediated by processing differences between listening to forward and backward music. This hippocampal involvement was again strongest during the early response to the music. Auditory cortex activity was more strongly evoked by the original (pleasant) music compared to its manipulated counterparts, but did not display a similar decline of activation over time as subcortical activity. These findings rather suggest that the ventral striatal/nucleus accumbens response during music listening is strongest in the first seconds and then declines. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional Polarity of Microvascular Brain Endothelial Cells Supported by Neurovascular Unit Computational Model of Large Neutral Amino Acid Homeostasis

PubMed Central

Taslimifar, Mehdi; Buoso, Stefano; Verrey, Francois; Kurtcuoglu, Vartan

2018-01-01

The homeostatic regulation of large neutral amino acid (LNAA) concentration in the brain interstitial fluid (ISF) is essential for proper brain function. LNAA passage into the brain is primarily mediated by the complex and dynamic interactions between various solute carrier (SLC) transporters expressed in the neurovascular unit (NVU), among which SLC7A5/LAT1 is considered to be the major contributor in microvascular brain endothelial cells (MBEC). The LAT1-mediated trans-endothelial transport of LNAAs, however, could not be characterized precisely by available in vitro and in vivo standard methods so far. To circumvent these limitations, we have incorporated published in vivo data of rat brain into a robust computational model of NVU-LNAA homeostasis, allowing us to evaluate hypotheses concerning LAT1-mediated trans-endothelial transport of LNAAs across the blood brain barrier (BBB). We show that accounting for functional polarity of MBECs with either asymmetric LAT1 distribution between membranes and/or intrinsic LAT1 asymmetry with low intraendothelial binding affinity is required to reproduce the experimentally measured brain ISF response to intraperitoneal (IP) L-tyrosine and L-phenylalanine injection. On the basis of these findings, we have also investigated the effect of IP administrated L-tyrosine and L-phenylalanine on the dynamics of LNAAs in MBECs, astrocytes and neurons. Finally, the computational model was shown to explain the trans-stimulation of LNAA uptake across the BBB observed upon ISF perfusion with a competitive LAT1 inhibitor. PMID:29593549

Submillisecond unmasked subliminal visual stimuli evoke electrical brain responses.

PubMed

Sperdin, Holger F; Spierer, Lucas; Becker, Robert; Michel, Christoph M; Landis, Theodor

2015-04-01

Subliminal perception is strongly associated to the processing of meaningful or emotional information and has mostly been studied using visual masking. In this study, we used high density 256-channel EEG coupled with an liquid crystal display (LCD) tachistoscope to characterize the spatio-temporal dynamics of the brain response to visual checkerboard stimuli (Experiment 1) or blank stimuli (Experiment 2) presented without a mask for 1 ms (visible), 500 µs (partially visible), and 250 µs (subliminal) by applying time-wise, assumption-free nonparametric randomization statistics on the strength and on the topography of high-density scalp-recorded electric field. Stimulus visibility was assessed in a third separate behavioral experiment. Results revealed that unmasked checkerboards presented subliminally for 250 µs evoked weak but detectable visual evoked potential (VEP) responses. When the checkerboards were replaced by blank stimuli, there was no evidence for the presence of an evoked response anymore. Furthermore, the checkerboard VEPs were modulated topographically between 243 and 296 ms post-stimulus onset as a function of stimulus duration, indicative of the engagement of distinct configuration of active brain networks. A distributed electrical source analysis localized this modulation within the right superior parietal lobule near the precuneus. These results show the presence of a brain response to submillisecond unmasked subliminal visual stimuli independently of their emotional saliency or meaningfulness and opens an avenue for new investigations of subliminal stimulation without using visual masking. © 2014 Wiley Periodicals, Inc.

The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan.

PubMed

Moran, Rosalyn J; Symmonds, Mkael; Dolan, Raymond J; Friston, Karl J

2014-01-01

The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses--including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects--from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.

Flexible, rapid and automatic neocortical word form acquisition mechanism in children as revealed by neuromagnetic brain response dynamics.

PubMed

Partanen, Eino; Leminen, Alina; de Paoli, Stine; Bundgaard, Anette; Kingo, Osman Skjold; Krøjgaard, Peter; Shtyrov, Yury

2017-07-15

Children learn new words and word forms with ease, often acquiring a new word after very few repetitions. Recent neurophysiological research on word form acquisition in adults indicates that novel words can be acquired within minutes of repetitive exposure to them, regardless of the individual's focused attention on the speech input. Although it is well-known that children surpass adults in language acquisition, the developmental aspects of such rapid and automatic neural acquisition mechanisms remain unexplored. To address this open question, we used magnetoencephalography (MEG) to scrutinise brain dynamics elicited by spoken words and word-like sounds in healthy monolingual (Danish) children throughout a 20-min repetitive passive exposure session. We found rapid neural dynamics manifested as an enhancement of early (~100ms) brain activity over the short exposure session, with distinct spatiotemporal patterns for different novel sounds. For novel Danish word forms, signs of such enhancement were seen in the left temporal regions only, suggesting reliance on pre-existing language circuits for acquisition of novel word forms with native phonology. In contrast, exposure both to novel word forms with non-native phonology and to novel non-speech sounds led to activity enhancement in both left and right hemispheres, suggesting that more wide-spread cortical networks contribute to the build-up of memory traces for non-native and non-speech sounds. Similar studies in adults have previously reported more sluggish (~15-25min, as opposed to 4min in the present study) or non-existent neural dynamics for non-native sound acquisition, which might be indicative of a higher degree of plasticity in the children's brain. Overall, the results indicate a rapid and highly plastic mechanism for a dynamic build-up of memory traces for novel acoustic information in the children's brain that operates automatically and recruits bilateral temporal cortical circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

The Role of Visual and Semantic Properties in the Emergence of Category-Specific Patterns of Neural Response in the Human Brain.

PubMed

Coggan, David D; Baker, Daniel H; Andrews, Timothy J

2016-01-01

Brain-imaging studies have found distinct spatial and temporal patterns of response to different object categories across the brain. However, the extent to which these categorical patterns of response reflect higher-level semantic or lower-level visual properties of the stimulus remains unclear. To address this question, we measured patterns of EEG response to intact and scrambled images in the human brain. Our rationale for using scrambled images is that they have many of the visual properties found in intact images, but do not convey any semantic information. Images from different object categories (bottle, face, house) were briefly presented (400 ms) in an event-related design. A multivariate pattern analysis revealed categorical patterns of response to intact images emerged ∼80-100 ms after stimulus onset and were still evident when the stimulus was no longer present (∼800 ms). Next, we measured the patterns of response to scrambled images. Categorical patterns of response to scrambled images also emerged ∼80-100 ms after stimulus onset. However, in contrast to the intact images, distinct patterns of response to scrambled images were mostly evident while the stimulus was present (∼400 ms). Moreover, scrambled images were able to account only for all the variance in the intact images at early stages of processing. This direct manipulation of visual and semantic content provides new insights into the temporal dynamics of object perception and the extent to which different stages of processing are dependent on lower-level or higher-level properties of the image.

Polarization and dynamical properties of VCSELs-based photonic neuron subject to optical pulse injection

NASA Astrophysics Data System (ADS)

Xiang, Shuiying; Wen, Aijun; Zhang, Hao; Li, Jiafu; Guo, Xingxing; Shang, Lei; Lin, Lin

2016-11-01

The polarization-resolved nonlinear dynamics of vertical-cavity surface-emitting lasers (VCSELs) subject to orthogonally polarized optical pulse injection are investigated numerically based on the spin flip model. By extensive numerical bifurcation analysis, the responses dynamics of photonic neuron based on VCSELs under the arrival of external stimuli of orthogonally polarized optical pulse injection are mainly discussed. It is found that, several neuron-like dynamics, such as phasic spiking of a single abrupt large amplitude pulse followed with or without subthreshold oscillation, and tonic spiking with multiple periodic pulses, are successfully reproduced in the numerical model of VCSELs. Besides, the effects of stimuli strength, pump current, frequency detuning, as well as the linewidth enhancement factor on the neuron-like response dynamics are examined carefully. The operating parameters ranges corresponding to different neuron-like dynamics are further identified. Thus, the numerical model and simulation results are very useful and interesting for the ultrafast brain-inspired neuromorphic photonics systems based on VCSELs.

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering.

PubMed

Havlicek, Martin; Friston, Karl J; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D

2011-06-15

This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Autonomic and brain responses associated with empathy deficits in autism spectrum disorder

PubMed Central

Eilam‐Stock, Tehila; Zhou, Thomas; Anagnostou, Evdokia; Kolevzon, Alexander; Soorya, Latha; Hof, Patrick R.; Friston, Karl J.

2015-01-01

Abstract Accumulating evidence suggests that autonomic signals and their cortical representations are closely linked to emotional processes, and that related abnormalities could lead to social deficits. Although socio‐emotional impairments are a defining feature of autism spectrum disorder (ASD), empirical evidence directly supporting the link between autonomic, cortical, and socio‐emotional abnormalities in ASD is still lacking. In this study, we examined autonomic arousal indexed by skin conductance responses (SCR), concurrent cortical responses measured by functional magnetic resonance imaging, and effective brain connectivity estimated by dynamic causal modeling in seventeen unmedicated high‐functioning adults with ASD and seventeen matched controls while they performed an empathy‐for‐pain task. Compared to controls, adults with ASD showed enhanced SCR related to empathetic pain, along with increased neural activity in the anterior insular cortex, although their behavioral empathetic pain discriminability was reduced and overall SCR was decreased. ASD individuals also showed enhanced correlation between SCR and neural activities in the anterior insular cortex. Importantly, significant group differences in effective brain connectivity were limited to greater reduction in the negative intrinsic connectivity of the anterior insular cortex in the ASD group, indicating a failure in attenuating anterior insular responses to empathetic pain. These results suggest that aberrant interoceptive precision, as indexed by abnormalities in autonomic activity and its central representations, may underlie empathy deficits in ASD. Hum Brain Mapp 36:3323–3338, 2015. © 2015 The Authors Human Brain Mapping Published byWiley Periodicals, Inc. PMID:25995134

Spatial Memory in the Morris Water Maze and Activation of Cyclic AMP Response Element-Binding (CREB) Protein within the Mouse Hippocampus

ERIC Educational Resources Information Center

Porte, Yves; Buhot, Marie Christine; Mons, Nicole E.

2008-01-01

We investigated the spatio-temporal dynamics of learning-induced cAMP response element-binding protein activation/phosphorylation (pCREB) in mice trained in a spatial reference memory task in the water maze. Using immunohistochemistry, we examined pCREB immunoreactivity (pCREB-ir) in hippocampal CA1 and CA3 and related brain structures. During the…

Temporal dynamics of lactate concentration in the human brain during acute inspiratory hypoxia

PubMed Central

Harris, Ashley D; Roberton, Victoria H; Huckle, Danielle L; Saxena, Neeraj; Evans, C John; Murphy, Kevin; Hall, Judith E; Bailey, Damian M; Mitsis, Georgios; Edden, Richard A E; Wise, Richard G

2012-01-01

Purpose To demonstrate the feasibility of measuring the temporal dynamics of cerebral lactate concentration and examine these dynamics in human subjects using MRS during hypoxia. Methods A respiratory protocol consisting of 10 min baseline normoxia, 20 min inspiratory hypoxia and ending with 10 min normoxic recovery was used, throughout which lactate-edited MRS was performed. This was repeated four times in three subjects. A separate session was performed to measure blood lactate. Impulse response functions using end-tidal oxygen and blood lactate as system inputs and cerebral lactate as the system output were examined to describe the dynamics of the cerebral lactate response to a hypoxic challenge. Results The average lactate increase was 20%±15% during the last half of the hypoxic challenge. Significant changes in cerebral lactate concentration were observed after 400s. The average relative increase in blood lactate was 188%±95%. The temporal dynamics of cerebral lactate concentration was reproducibly demonstrated with 200s time bins of MRS data (coefficient of variation 0.063±0.035 between time bins in normoxia). The across subject coefficient of variation was 0.333. Conclusions The methods for measuring the dynamics of the cerebral lactate response developed here would be useful to further investigate the brain’s response to hypoxia. PMID:23197421

Wavelet entropy: a new tool for analysis of short duration brain electrical signals.

PubMed

Rosso, O A; Blanco, S; Yordanova, J; Kolev, V; Figliola, A; Schürmann, M; Başar, E

2001-01-30

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. Here, new method based on orthogonal discrete wavelet transform (ODWT) is applied. It takes as a basic element the ODWT of the EEG signal, and defines the relative wavelet energy, the wavelet entropy (WE) and the relative wavelet entropy (RWE). The relative wavelet energy provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The WE carries information about the degree of order/disorder associated with a multi-frequency signal response, and the RWE measures the degree of similarity between different segments of the signal. In addition, the time evolution of the WE is calculated to give information about the dynamics in the EEG records. Within this framework, the major objective of the present work was to characterize in a quantitative way functional dynamics of order/disorder microstates in short duration EEG signals. For that aim, spontaneous EEG signals under different physiological conditions were analyzed. Further, specific quantifiers were derived to characterize how stimulus affects electrical events in terms of frequency synchronization (tuning) in the event related potentials.

Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD.

PubMed

McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Bar-Haim, Yair; Pine, Daniel S; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2016-12-01

Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group's data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca's area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4-8 Hz) during encoding and in the alpha band (9-12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.

Instantaneous brain dynamics mapped to a continuous state space.

PubMed

Billings, Jacob C W; Medda, Alessio; Shakil, Sadia; Shen, Xiaohong; Kashyap, Amrit; Chen, Shiyang; Abbas, Anzar; Zhang, Xiaodi; Nezafati, Maysam; Pan, Wen-Ju; Berman, Gordon J; Keilholz, Shella D

2017-11-15

Measures of whole-brain activity, from techniques such as functional Magnetic Resonance Imaging, provide a means to observe the brain's dynamical operations. However, interpretation of whole-brain dynamics has been stymied by the inherently high-dimensional structure of brain activity. The present research addresses this challenge through a series of scale transformations in the spectral, spatial, and relational domains. Instantaneous multispectral dynamics are first developed from input data via a wavelet filter bank. Voxel-level signals are then projected onto a representative set of spatially independent components. The correlation distance over the instantaneous wavelet-ICA state vectors is a graph that may be embedded onto a lower-dimensional space to assist the interpretation of state-space dynamics. Applying this procedure to a large sample of resting-state and task-active data (acquired through the Human Connectome Project), we segment the empirical state space into a continuum of stimulus-dependent brain states. Upon observing the local neighborhood of brain-states adopted subsequent to each stimulus, we may conclude that resting brain activity includes brain states that are, at times, similar to those adopted during tasks, but that are at other times distinct from task-active brain states. As task-active brain states often populate a local neighborhood, back-projection of segments of the dynamical state space onto the brain's surface reveals the patterns of brain activity that support many experimentally-defined states. Copyright © 2017 Elsevier Inc. All rights reserved.

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience

PubMed Central

Turm, Hagit; Mukherjee, Diptendu; Haritan, Doron; Tahor, Maayan; Citri, Ami

2014-01-01

The encoding of experiences in the brain and the consolidation of long-term memories depend on gene transcription. Identifying the function of specific genes in encoding experience is one of the main objectives of molecular neuroscience. Furthermore, the functional association of defined genes with specific behaviors has implications for understanding the basis of neuropsychiatric disorders. Induction of robust transcription programs has been observed in the brains of mice following various behavioral manipulations. While some genetic elements are utilized recurrently following different behavioral manipulations and in different brain nuclei, transcriptional programs are overall unique to the inducing stimuli and the structure in which they are studied1,2. In this publication, a protocol is described for robust and comprehensive transcriptional profiling from brain nuclei of mice in response to behavioral manipulation. The protocol is demonstrated in the context of analysis of gene expression dynamics in the nucleus accumbens following acute cocaine experience. Subsequent to a defined in vivo experience, the target neural tissue is dissected; followed by RNA purification, reverse transcription and utilization of microfluidic arrays for comprehensive qPCR analysis of multiple target genes. This protocol is geared towards comprehensive analysis (addressing 50-500 genes) of limiting quantities of starting material, such as small brain samples or even single cells. The protocol is most advantageous for parallel analysis of multiple samples (e.g. single cells, dynamic analysis following pharmaceutical, viral or behavioral perturbations). However, the protocol could also serve for the characterization and quality assurance of samples prior to whole-genome studies by microarrays or RNAseq, as well as validation of data obtained from whole-genome studies. PMID:25225819

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

Dynamic time warping-based averaging framework for functional near-infrared spectroscopy brain imaging studies

NASA Astrophysics Data System (ADS)

Zhu, Li; Najafizadeh, Laleh

2017-06-01

We investigate the problem related to the averaging procedure in functional near-infrared spectroscopy (fNIRS) brain imaging studies. Typically, to reduce noise and to empower the signal strength associated with task-induced activities, recorded signals (e.g., in response to repeated stimuli or from a group of individuals) are averaged through a point-by-point conventional averaging technique. However, due to the existence of variable latencies in recorded activities, the use of the conventional averaging technique can lead to inaccuracies and loss of information in the averaged signal, which may result in inaccurate conclusions about the functionality of the brain. To improve the averaging accuracy in the presence of variable latencies, we present an averaging framework that employs dynamic time warping (DTW) to account for the temporal variation in the alignment of fNIRS signals to be averaged. As a proof of concept, we focus on the problem of localizing task-induced active brain regions. The framework is extensively tested on experimental data (obtained from both block design and event-related design experiments) as well as on simulated data. In all cases, it is shown that the DTW-based averaging technique outperforms the conventional-based averaging technique in estimating the location of task-induced active regions in the brain, suggesting that such advanced averaging methods should be employed in fNIRS brain imaging studies.

Modeling and stochastic analysis of dynamic mechanisms of the perception

NASA Astrophysics Data System (ADS)

Pisarchik, A.; Bashkirtseva, I.; Ryashko, L.

2017-10-01

Modern studies in physiology and cognitive neuroscience consider a noise as an important constructive factor of the brain functionality. Under the adequate noise, the brain can rapidly access different ordered states, and provide decision-making by preventing deadlocks. Bistable dynamic models are often used for the study of the underlying mechanisms of the visual perception. In the present paper, we consider a bistable energy model subject to both additive and parametric noise. Using the catastrophe theory formalism and stochastic sensitivity functions technique, we analyze a response of the equilibria to noise, and study noise-induced transitions between equilibria. We demonstrate and analyse the effect of hysteresis squeezing when the intensity of noise is increased. Stochastic bifurcations connected with the suppression of oscillations by parametric noises are discussed.

An animal-to-human scaling law for blast-induced traumatic brain injury risk assessment.

PubMed

Jean, Aurélie; Nyein, Michelle K; Zheng, James Q; Moore, David F; Joannopoulos, John D; Radovitzky, Raúl

2014-10-28

Despite recent efforts to understand blast effects on the human brain, there are still no widely accepted injury criteria for humans. Recent animal studies have resulted in important advances in the understanding of brain injury due to intense dynamic loads. However, the applicability of animal brain injury results to humans remains uncertain. Here, we use advanced computational models to derive a scaling law relating blast wave intensity to the mechanical response of brain tissue across species. Detailed simulations of blast effects on the brain are conducted for different mammals using image-based biofidelic models. The intensity of the stress waves computed for different external blast conditions is compared across species. It is found that mass scaling, which successfully estimates blast tolerance of the thorax, fails to capture the brain mechanical response to blast across mammals. Instead, we show that an appropriate scaling variable must account for the mass of protective tissues relative to the brain, as well as their acoustic impedance. Peak stresses transmitted to the brain tissue by the blast are then shown to be a power function of the scaling parameter for a range of blast conditions relevant to TBI. In particular, it is found that human brain vulnerability to blast is higher than for any other mammalian species, which is in distinct contrast to previously proposed scaling laws based on body or brain mass. An application of the scaling law to recent experiments on rabbits furnishes the first physics-based injury estimate for blast-induced TBI in humans.

Quantitative assessment of brain glucose metabolic rates using in vivo deuterium magnetic resonance spectroscopy.

PubMed

Lu, Ming; Zhu, Xiao-Hong; Zhang, Yi; Mateescu, Gheorghe; Chen, Wei

2017-11-01

Quantitative assessment of cerebral glucose consumption rate (CMR glc ) and tricarboxylic acid cycle flux (V TCA ) is crucial for understanding neuroenergetics under physiopathological conditions. In this study, we report a novel in vivo Deuterium ( 2 H) MRS (DMRS) approach for simultaneously measuring and quantifying CMR glc and V TCA in rat brains at 16.4 Tesla. Following a brief infusion of deuterated glucose, dynamic changes of isotope-labeled glucose, glutamate/glutamine (Glx) and water contents in the brain can be robustly monitored from their well-resolved 2 H resonances. Dynamic DMRS glucose and Glx data were employed to determine CMR glc and V TCA concurrently. To test the sensitivity of this method in response to altered glucose metabolism, two brain conditions with different anesthetics were investigated. Increased CMR glc (0.46 vs. 0.28 µmol/g/min) and V TCA (0.96 vs. 0.6 µmol/g/min) were found in rats under morphine as compared to deeper anesthesia using 2% isoflurane. This study demonstrates the feasibility and new utility of the in vivo DMRS approach to assess cerebral glucose metabolic rates at high/ultrahigh field. It provides an alternative MRS tool for in vivo study of metabolic coupling relationship between aerobic and anaerobic glucose metabolisms in brain under physiopathological states.

Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain

PubMed Central

2016-01-01

Abstract When the brain is stimulated, for example, by sensory inputs or goal-oriented tasks, the brain initially responds with activities in specific areas. The subsequent pattern formation of functional networks is constrained by the structural connectivity (SC) of the brain. The extent to which information is processed over short- or long-range SC is unclear. Whole-brain models based on long-range axonal connections, for example, can partly describe measured functional connectivity dynamics at rest. Here, we study the effect of SC on the network response to stimulation. We use a human whole-brain network model comprising long- and short-range connections. We systematically activate each cortical or thalamic area, and investigate the network response as a function of its short- and long-range SC. We show that when the brain is operating at the edge of criticality, stimulation causes a cascade of network recruitments, collapsing onto a smaller space that is partly constrained by SC. We found both short- and long-range SC essential to reproduce experimental results. In particular, the stimulation of specific areas results in the activation of one or more resting-state networks. We suggest that the stimulus-induced brain activity, which may indicate information and cognitive processing, follows specific routes imposed by structural networks explaining the emergence of functional networks. We provide a lookup table linking stimulation targets and functional network activations, which potentially can be useful in diagnostics and treatments with brain stimulation. PMID:27752540

What does the interactive brain hypothesis mean for social neuroscience? A dialogue

PubMed Central

Di Paolo, Ezequiel; Adolphs, Ralph

2016-01-01

A recent framework inspired by phenomenological philosophy, dynamical systems theory, embodied cognition and robotics has proposed the interactive brain hypothesis (IBH). Whereas mainstream social neuroscience views social cognition as arising solely from events in the brain, the IBH argues that social cognition requires, in addition, causal relations between the brain and the social environment. We discuss, in turn, the foundational claims for the IBH in its strongest form; classical views of cognition that can be raised against the IBH; a defence of the IBH in the light of these arguments; and a response to this. Our goal is to initiate a dialogue between cognitive neuroscience and enactive views of social cognition. We conclude by suggesting some new directions and emphases that social neuroscience might take. PMID:27069056

What does the interactive brain hypothesis mean for social neuroscience? A dialogue.

PubMed

De Jaegher, Hanne; Di Paolo, Ezequiel; Adolphs, Ralph

2016-05-05

A recent framework inspired by phenomenological philosophy, dynamical systems theory, embodied cognition and robotics has proposed the interactive brain hypothesis (IBH). Whereas mainstream social neuroscience views social cognition as arising solely from events in the brain, the IBH argues that social cognition requires, in addition, causal relations between the brain and the social environment. We discuss, in turn, the foundational claims for the IBH in its strongest form; classical views of cognition that can be raised against the IBH; a defence of the IBH in the light of these arguments; and a response to this. Our goal is to initiate a dialogue between cognitive neuroscience and enactive views of social cognition. We conclude by suggesting some new directions and emphases that social neuroscience might take. © 2016 The Author(s).

Dynamic Brain Network Correlates of Spontaneous Fluctuations in Attention.

PubMed

Kucyi, Aaron; Hove, Michael J; Esterman, Michael; Hutchison, R Matthew; Valera, Eve M

2017-03-01

Human attention is intrinsically dynamic, with focus continuously shifting between elements of the external world and internal, self-generated thoughts. Communication within and between large-scale brain networks also fluctuates spontaneously from moment to moment. However, the behavioral relevance of dynamic functional connectivity and possible link with attentional state shifts is unknown. We used a unique approach to examine whether brain network dynamics reflect spontaneous fluctuations in moment-to-moment behavioral variability, a sensitive marker of attentional state. Nineteen healthy adults were instructed to tap their finger every 600 ms while undergoing fMRI. This novel, but simple, approach allowed us to isolate moment-to-moment fluctuations in behavioral variability related to attention, independent of common confounds in cognitive tasks (e.g., stimulus changes, response inhibition). Spontaneously increasing tap variance ("out-of-the-zone" attention) was associated with increasing activation in dorsal-attention and salience network regions, whereas decreasing tap variance ("in-the-zone" attention) was marked by increasing activation of default mode network (DMN) regions. Independent of activation, tap variance representing out-of-the-zone attention was also time-locked to connectivity both within DMN and between DMN and salience network regions. These results provide novel mechanistic data on the understudied neural dynamics of everyday, moment-to-moment attentional fluctuations, elucidating the behavioral importance of spontaneous, transient coupling within and between attention-relevant networks. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

State-space receptive fields of semicircular canal afferent neurons in the bullfrog

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

Receptive fields are commonly used to describe spatial characteristics of sensory neuron responses. They can be extended to characterize temporal or dynamical aspects by mapping neural responses in dynamical state spaces. The state-space receptive field of a neuron is the probability distribution of the dynamical state of the stimulus-generating system conditioned upon the occurrence of a spike. We have computed state-space receptive fields for semicircular canal afferent neurons in the bullfrog (Rana catesbeiana). We recorded spike times during broad-band Gaussian noise rotational velocity stimuli, computed the frequency distribution of head states at spike times, and normalized these to obtain conditional pdfs for the state. These state-space receptive fields quantify what the brain can deduce about the dynamical state of the head when a single spike arrives from the periphery. c2001 Elsevier Science B.V. All rights reserved.

Dynamic Alignment Models for Neural Coding

PubMed Central

Kollmorgen, Sepp; Hahnloser, Richard H. R.

2014-01-01

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

Psychosocial Stress and Brain Function in Adolescent Psychopathology.

PubMed

Quinlan, Erin Burke; Cattrell, Anna; Jia, Tianye; Artiges, Eric; Banaschewski, Tobias; Barker, Gareth; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Brühl, Rüdiger; Conrod, Patricia J; Desrivieres, Sylvane; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Martinot, Jean-Luc; Paillère Martinot, Marie-Laure; Nees, Frauke; Papadopoulos-Orfanos, Dimitri; Paus, Tomáš; Poustka, Luise; Smolka, Michael N; Vetter, Nora C; Walter, Henrik; Whelan, Robert; Glennon, Jeffrey C; Buitelaar, Jan K; Happé, Francesca; Loth, Eva; Barker, Edward D; Schumann, Gunter

2017-08-01

The authors sought to explore how conduct, hyperactivity/inattention, and emotional symptoms are associated with neural reactivity to social-emotional stimuli, and the extent to which psychosocial stress modulates these relationships. Participants were community adolescents recruited as part of the European IMAGEN study. Bilateral amygdala regions of interest were used to assess the relationship between the three symptom domains and functional MRI neural reactivity during passive viewing of dynamic angry and neutral facial expressions. Exploratory functional connectivity and whole brain multiple regression approaches were used to analyze how the symptoms and psychosocial stress relate to other brain regions. In response to the social-emotional stimuli, adolescents with high levels of conduct or hyperactivity/inattention symptoms who had also experienced a greater number of stressful life events showed hyperactivity of the amygdala and several regions across the brain. This effect was not observed with emotional symptoms. A cluster in the midcingulate was found to be common to both conduct problems and hyperactivity symptoms. Exploratory functional connectivity analyses suggested that amygdala-precuneus connectivity is associated with hyperactivity/inattention symptoms. The results link hyperactive amygdala responses and regions critical for top-down emotional processing with high levels of psychosocial stress in individuals with greater conduct and hyperactivity/inattention symptoms. This work highlights the importance of studying how psychosocial stress affects functional brain responses to social-emotional stimuli, particularly in adolescents with externalizing symptoms.

Imaging Alzheimer's disease pathophysiology with PET

PubMed Central

Schilling, Lucas Porcello; Zimmer, Eduardo R.; Shin, Monica; Leuzy, Antoine; Pascoal, Tharick A.; Benedet, Andréa L.; Borelli, Wyllians Vendramini; Palmini, André; Gauthier, Serge; Rosa-Neto, Pedro

2016-01-01

ABSTRACT Alzheimer's disease (AD) has been reconceptualised as a dynamic pathophysiological process characterized by preclinical, mild cognitive impairment (MCI), and dementia stages. Positron emission tomography (PET) associated with various molecular imaging agents reveals numerous aspects of dementia pathophysiology, such as brain amyloidosis, tau accumulation, neuroreceptor changes, metabolism abnormalities and neuroinflammation in dementia patients. In the context of a growing shift toward presymptomatic early diagnosis and disease-modifying interventions, PET molecular imaging agents provide an unprecedented means of quantifying the AD pathophysiological process, monitoring disease progression, ascertaining whether therapies engage their respective brain molecular targets, as well as quantifying pharmacological responses. In the present study, we highlight the most important contributions of PET in describing brain molecular abnormalities in AD. PMID:29213438

Inside out: a neuro-behavioral signature of free recall dynamics.

PubMed

Shapira-Lichter, Irit; Vakil, Eli; Glikmann-Johnston, Yifat; Siman-Tov, Tali; Caspi, Dan; Paran, Daphna; Hendler, Talma

2012-07-01

Free recall (FR) is a ubiquitous internally-driven retrieval operation that crucially affects our day-to-day life. The neural correlates of FR, however, are not sufficiently understood, partly due to the methodological challenges presented by its emerging property and endogenic nature. Using fMRI and performance measures, the neuro-behavioral correlates of FR were studied in 33 healthy participants who repeatedly encoded and retrieved word-lists. Retrieval was determined either overtly via verbal output (Experiment 1) or covertly via motor responses (Experiment 2). Brain activation during FR was characterized by two types of performance-based parametric analyses of retrieval changes over time. First was the elongation in inter response time (IRT) assumed to represent the prolongation of memory search over time, as increased effort was needed. Using a derivative of this parameter in whole brain analysis revealed the default mode network (DMN): longer IRT within FR blocks correlated with less deactivation of the DMN, representing its greater recruitment. Second was the increased number of words retrieved in repeated encoding-recall cycles, assumed to represent the learning process. Using this parameter in whole brain analysis revealed increased deactivation in the DMN (i.e., less recruitment). Together our results demonstrate the naturally occurring dynamics in the recruitment of the DMN during utilization of internally generated processes during FR. The contrasting effects of increased and decreased recruitment of the DMN following dynamics in memory search and learning, respectively, supports the idea that with learning FR is less dependent on neural operations of internally-generated processes such as those initially needed for memory search. Copyright © 2012 Elsevier Ltd. All rights reserved.

Neural correlates of motor learning in the vestibulo-ocular reflex: dynamic regulation of multimodal integration in the macaque vestibular system

PubMed Central

Sadeghi, Soroush G.; Minor, Lloyd B.; Cullen, Kathleen E.

2010-01-01

Motor learning is required for the reacquisition of skills that have been compromised as a result of brain lesion or disease, as well as for the acquisition of new skills. Behaviors with well-characterized anatomy and physiology are required to yield significant insight into changes that occur in the brain during motor learning. The vestibulo-ocular-reflex (VOR) is well suited to establish connections between neurons, neural circuits, and motor performance during learning. Here we examined the linkage between neuronal and behavioural VOR responses in alert behaving monkeys (macaca mulatta) during the impressive recovery that occurs after unilateral vestibular loss. We show, for the first time, that motor learning is characterized by the dynamic reweighting of inputs from different modalities (i.e., vestibular versus extra-vestibular) at the level of the single neurons which constitute the first central stage of vestibular processing. Specifically, two types of information, which did not influence neuronal responses prior to the lesion, had an important role during compensation. First, unmasked neck proprioceptive inputs played a critical role in the early stages of this process demonstrated by faster and more substantial recovery of vestibular responses in proprioceptive sensitive neurons. Second, neuronal and VOR responses were significantly enhanced during active relative to passive head motion later in the compensation process (>3 weeks). Taken together, our findings provide evidence linking the dynamic regulation of multimodal integration at the level of single neurons and behavioural recovery, suggesting a role for homeostatic mechanisms in VOR motor learning. PMID:20668199

Encoding of physics concepts: concreteness and presentation modality reflected by human brain dynamics.

PubMed

Lai, Kevin; She, Hsiao-Ching; Chen, Sheng-Chang; Chou, Wen-Chi; Huang, Li-Yu; Jung, Tzyy-Ping; Gramann, Klaus

2012-01-01

Previous research into working memory has focused on activations in different brain areas accompanying either different presentation modalities (verbal vs. non-verbal) or concreteness (abstract vs. concrete) of non-science concepts. Less research has been conducted investigating how scientific concepts are learned and further processed in working memory. To bridge this gap, the present study investigated human brain dynamics associated with encoding of physics concepts, taking both presentation modality and concreteness into account. Results of this study revealed greater theta and low-beta synchronization in the anterior cingulate cortex (ACC) during encoding of concrete pictures as compared to the encoding of both high and low imageable words. In visual brain areas, greater theta activity accompanying stimulus onsets was observed for words as compared to pictures while stronger alpha suppression was observed in responses to pictures as compared to words. In general, the EEG oscillation patterns for encoding words of different levels of abstractness were comparable but differed significantly from encoding of pictures. These results provide insights into the effects of modality of presentation on human encoding of scientific concepts and thus might help in developing new ways to better teach scientific concepts in class.

Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data.

PubMed

Grootswagers, Tijl; Wardle, Susan G; Carlson, Thomas A

2017-04-01

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

Depression and treatment response: dynamic interplay of signaling pathways and altered neural processes

PubMed Central

Duric, Vanja

2014-01-01

Since the 1960s, when the first tricyclic and monoamine oxidase inhibitor antidepressant drugs were introduced, most of the ensuing agents were designed to target similar brain pathways that elevate serotonin and/or norepinephrine signaling. Fifty years later, the main goal of the current depression research is to develop faster-acting, more effective therapeutic agents with fewer side effects, as currently available antidepressants are plagued by delayed therapeutic onset and low response rates. Clinical and basic science research studies have made significant progress towards deciphering the pathophysiological events within the brain involved in development, maintenance, and treatment of major depressive disorder. Imaging and postmortem brain studies in depressed human subjects, in combination with animal behavioral models of depression, have identified a number of different cellular events, intracellular signaling pathways, proteins, and target genes that are modulated by stress and are potentially vital mediators of antidepressant action. In this review, we focus on several neural mechanisms, primarily within the hippocampus and prefrontal cortex, which have recently been implicated in depression and treatment response. PMID:22585060

Rapid Postnatal Expansion of Neural Networks Occurs in an Environment of Altered Neurovascular and Neurometabolic Coupling.

PubMed

Kozberg, Mariel G; Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Hillman, Elizabeth M C

2016-06-22

In the adult brain, increases in neural activity lead to increases in local blood flow. However, many prior measurements of functional hemodynamics in the neonatal brain, including functional magnetic resonance imaging (fMRI) in human infants, have noted altered and even inverted hemodynamic responses to stimuli. Here, we demonstrate that localized neural activity in early postnatal mice does not evoke blood flow increases as in the adult brain, and elucidate the neural and metabolic correlates of these altered functional hemodynamics as a function of developmental age. Using wide-field GCaMP imaging, the development of neural responses to somatosensory stimulus is visualized over the entire bilaterally exposed cortex. Neural responses are observed to progress from tightly localized, unilateral maps to bilateral responses as interhemispheric connectivity becomes established. Simultaneous hemodynamic imaging confirms that spatiotemporally coupled functional hyperemia is not present during these early stages of postnatal brain development, and develops gradually as cortical connectivity is established. Exploring the consequences of this lack of functional hyperemia, measurements of oxidative metabolism via flavoprotein fluorescence suggest that neural activity depletes local oxygen to below baseline levels at early developmental stages. Analysis of hemoglobin oxygenation dynamics at the same age confirms oxygen depletion for both stimulus-evoked and resting-state neural activity. This state of unmet metabolic demand during neural network development poses new questions about the mechanisms of neurovascular development and its role in both normal and abnormal brain development. These results also provide important insights for the interpretation of fMRI studies of the developing brain. This work demonstrates that the postnatal development of neuronal connectivity is accompanied by development of the mechanisms that regulate local blood flow in response to neural activity. Novel in vivo imaging reveals that, in the developing mouse brain, strong and localized GCaMP neural responses to stimulus fail to evoke local blood flow increases, leading to a state in which oxygen levels become locally depleted. These results demonstrate that the development of cortical connectivity occurs in an environment of altered energy availability that itself may play a role in shaping normal brain development. These findings have important implications for understanding the pathophysiology of abnormal developmental trajectories, and for the interpretation of functional magnetic resonance imaging data acquired in the developing brain. Copyright © 2016 the authors 0270-6474/16/366704-14$15.00/0.

Changes in brain entropy are related to abstract temporal topology. Comment on "Topodynamics of metastable brains" by Arturo Tozzi et al.

NASA Astrophysics Data System (ADS)

Çankaya, Mehmet Niyazi; Déli, Eva

2017-07-01

It is a great aspiration to consider biological systems, especially the notoriously unpredictable brain, with mathematical tools, because of their reliable predictive power. The classic idea that the brain can be compartmentalized into operational modules, such as vision, movement, emotions or consciousness has come up empty. A new surge of publications sets out the mathematical analysis of this highly integrated, complex and self-regulating system. For example, the resting brain's recurring electromagnetic activities form a highly reproducible harmonic function [1], which permits the use of matrix formulation, borrowed from quantum mechanics, to assess the probabilities of measurable properties, or ;observables;. It has also been suggested that resting state electric activities might take the form of a hypersphere [2], and even the particle-like formalism of the self-regulatory nature of consciousness has even been proposed [3]. The 'TOPODYNAMICS OF METASTABLE BRAINS' by Tozzi et al. [4] is part of the growing wave of publications that seeks to explain the brain's global dynamics within a physical framework. This fast growing literature has uncovered that the oscillatory networks of local electromagnetic potential differences, which are highly responsive to the environment, formulate according to non-classical principles and can be best modeled by the mathematical framework of dynamic and complex physical systems. However, the ability to connect the oscillatory dynamics of the brain to the global cognitive processes of the mind has been difficult. The TOPODYNAMICS OF METASTABLE BRAINS is a pioneering attempt to approach these seemingly disparate areas and bridge their conceptual, methodological divide. Specifically, topodynamics examines how the changing electric signals of the brain form an abstract topology during evoked and resting potential, and give rise to cognitive processes. For example, rapid transitional periods intercept the stable, operational modules of the brain's electric activities that parallel changes in thoughts or evolution of concepts. Within the framework of operational architectonics, Tozzi et al. applied the methods of the Bursuk-Ulam theorem (BUT) to uncover the detailed dynamics of brain activities, such as dimensionality, entropy changes, and information accumulation. The authors find that ripples of rapid transitional periods, with sudden changes and reorganization of the information and entropy, parallels shifts both in dimensionality of temporal dynamics, as well as in cognitive processes. The method therefore can uncover how entropic and dimensionality changes are interconnected with emerging mental concepts. It also highlights the differences between lower conceptual processes, such as sensory processing, and higher cognitive synthesis, such as semantics, for example. In physical systems, information, dimensionality and entropy are related according to well-established formulas. In this direction, the entropy values of the volume and surface area are added into the evaluation of brain functionings [5-7]. If the same relationship is true in the wet and constantly changing biological complexity of the brain, then it would give us predictive capability toward the understanding of cognition, aid the treatment of mental problems and diseases in psychiatry and psychology, and facilitate the design of a new generation of artificial intelligent machines.

Solving the two-dimensional Fokker-Planck equation for strongly correlated neurons

NASA Astrophysics Data System (ADS)

Deniz, Taşkın; Rotter, Stefan

2017-01-01

Pairs of neurons in brain networks often share much of the input they receive from other neurons. Due to essential nonlinearities of the neuronal dynamics, the consequences for the correlation of the output spike trains are generally not well understood. Here we analyze the case of two leaky integrate-and-fire neurons using an approach which is nonperturbative with respect to the degree of input correlation. Our treatment covers both weakly and strongly correlated dynamics, generalizing previous results based on linear response theory.

Fluid dynamics vascular theory of brain and inner-ear function in traumatic brain injury: a translational hypothesis for diagnosis and treatment.

PubMed

Shulman, Abraham; Strashun, Arnold M

2009-01-01

It is hypothesized that in all traumatic brain injury (TBI) patients with a clinical history of closed or penetrating head injury, the initial head trauma is associated with a vibratory sensation and noise exposure, with resultant alteration in vascular supply to the structures and contents of the fluid compartments of brain and ear (i.e., the fluid dynamics vascular theory of brain-inner-ear function [FDVTBE]). The primary etiology-head trauma-results in an initial fluctuation, interference, or interaction in the normal fluid dynamics between brain and labyrinth of the inner ear, with a resultant clinical diversity of complaints varying in time of onset and severity. Normal function of the brain and ear is a reflection of a normal state of homeostasis between the fluid compartments in the brain of cerebrospinal fluid and perilymph-endolymph in the labyrinth of the ear. The normal homeostasis in the structures and contents between the two fluid compartment systems--intracerebral and intralabyrinthine--is controlled by mechanisms involved in the maintenance of normal pressures, water and electrolyte content, and neurotransmitter activities. The initial pathophysiology (a reflection of an alteration in the vascular supply to the brain-ear) is hypothesized to be an initial acute inflammatory response, persistence of which results in ischemia and an irreversible alteration in the involved neural substrates of brain-ear. Clinically, a chronic multisymptom complex becomes manifest. The multisymptom complex, individual for each TBI patient regardless of the diagnostic TBI category (i.e., mild, moderate, or severe), initially reflects processes of inflammation and ischemia which, in brain, result in brain volume loss identified as neurodegeneration and hydrocephalus ex vacuo or an alteration in cerebrospinal fluid production (i.e., pseudotumor cerebri) and, in ear, secondary endolymphatic hydrops with associated cochleovestibular complaints of hearing loss, tinnitus, vertigo, ear blockage, and hyperacusis. The FDVTBE integrates and translates a neurovascular hypothesis for Alzheimer's disease to TBI. This study presents an FDVTBE hypothesis of TBI to explain the clinical association of head trauma (TBI) and central nervous system neurodegeneration with multisensory complaints, highlighted by and focusing on cochleovestibular complaints. A clinical case report, previously published for demonstration of the cerebrovascular medical significance of a particular type of tinnitus, and evidence-based basic science and clinical medicine are cited to provide objective evidence in support and demonstration of the FDVTBE.

Neural dynamics underlying emotional transmissions between individuals

PubMed Central

Levit-Binnun, Nava; Hendler, Talma; Lerner, Yulia

2017-01-01

Abstract Emotional experiences are frequently shaped by the emotional responses of co-present others. Research has shown that people constantly monitor and adapt to the incoming social–emotional signals, even without face-to-face interaction. And yet, the neural processes underlying such emotional transmissions have not been directly studied. Here, we investigated how the human brain processes emotional cues which arrive from another, co-attending individual. We presented continuous emotional feedback to participants who viewed a movie in the scanner. Participants in the social group (but not in the control group) believed that the feedback was coming from another person who was co-viewing the same movie. We found that social–emotional feedback significantly affected the neural dynamics both in the core affect and in the medial pre-frontal regions. Specifically, the response time-courses in those regions exhibited increased similarity across recipients and increased neural alignment with the timeline of the feedback in the social compared with control group. Taken in conjunction with previous research, this study suggests that emotional cues from others shape the neural dynamics across the whole neural continuum of emotional processing in the brain. Moreover, it demonstrates that interpersonal neural alignment can serve as a neural mechanism through which affective information is conveyed between individuals. PMID:28575520

Is brain response to food rewards related to overeating? A test of the reward surfeit model of overeating in children.

PubMed

Adise, Shana; Geier, Charles F; Roberts, Nicole J; White, Corey N; Keller, Kathleen L

2018-06-08

The reward surfeit model of overeating suggests that heightened brain response to rewards contributes to overeating and subsequent weight gain. However, previous studies have not tested whether brain response to reward is associated with food intake, particularly during childhood, a period of dynamic development in reward and inhibitory control neurocircuitry. We conducted functional magnetic resonance imaging (fMRI) with 7-11-year-old children (n = 59; healthy weight, n = 31; overweight, n = 28; 54% female) while they played a modified card-guessing paradigm to examine blood-oxygen-level-dependent (BOLD) response to anticipating and winning rewards (food, money, neutral). Food intake was assessed at three separate meals that measured different facets of eating behavior: 1) typical consumption (baseline), 2) overindulgence (palatable buffet), and 3) eating in the absence of hunger (EAH). A priori regions of interest included regions implicated in both reward processing and inhibitory control. Multiple stepwise regressions were conducted to examine the relationship between intake and BOLD response to rewards. Corrected results showed that a greater BOLD response in the medial prefrontal cortex for anticipating food compared to money positively correlated with how much children ate at the baseline and palatable buffet meals. BOLD response in the dorsolateral prefrontal cortex for winning food compared to money was positively correlated with intake at the palatable buffet meal and EAH. All aforementioned relationships were independent of child weight status. Findings support the reward surfeit model by showing that increased brain response to food compared to money rewards positively correlates with laboratory measures of food intake in children. Copyright © 2018. Published by Elsevier Ltd.

Multimodal Approaches to Define Network Oscillations in Depression

PubMed Central

Smart, Otis Lkuwamy; Tiruvadi, Vineet Ravi; Mayberg, Helen S.

2018-01-01

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients. PMID:25681871

Visceral Inflammation and Immune Activation Stress the Brain

PubMed Central

Holzer, Peter; Farzi, Aitak; Hassan, Ahmed M.; Zenz, Geraldine; Jačan, Angela; Reichmann, Florian

2017-01-01

Stress refers to a dynamic process in which the homeostasis of an organism is challenged, the outcome depending on the type, severity, and duration of stressors involved, the stress responses triggered, and the stress resilience of the organism. Importantly, the relationship between stress and the immune system is bidirectional, as not only stressors have an impact on immune function, but alterations in immune function themselves can elicit stress responses. Such bidirectional interactions have been prominently identified to occur in the gastrointestinal tract in which there is a close cross-talk between the gut microbiota and the local immune system, governed by the permeability of the intestinal mucosa. External stressors disturb the homeostasis between microbiota and gut, these disturbances being signaled to the brain via multiple communication pathways constituting the gut–brain axis, ultimately eliciting stress responses and perturbations of brain function. In view of these relationships, the present article sets out to highlight some of the interactions between peripheral immune activation, especially in the visceral system, and brain function, behavior, and stress coping. These issues are exemplified by the way through which the intestinal microbiota as well as microbe-associated molecular patterns including lipopolysaccharide communicate with the immune system and brain, and the mechanisms whereby overt inflammation in the GI tract impacts on emotional-affective behavior, pain sensitivity, and stress coping. The interactions between the peripheral immune system and the brain take place along the gut–brain axis, the major communication pathways of which comprise microbial metabolites, gut hormones, immune mediators, and sensory neurons. Through these signaling systems, several transmitter and neuropeptide systems within the brain are altered under conditions of peripheral immune stress, enabling adaptive processes related to stress coping and resilience to take place. These aspects of the impact of immune stress on molecular and behavioral processes in the brain have a bearing on several disturbances of mental health and highlight novel opportunities of therapeutic intervention. PMID:29213271

Dynamic Connectivity Patterns in Conscious and Unconscious Brain

PubMed Central

Ma, Yuncong; Hamilton, Christina

2017-01-01

Abstract Brain functional connectivity undergoes dynamic changes from the awake to unconscious states. However, how the dynamics of functional connectivity patterns are linked to consciousness at the behavioral level remains elusive. In this study, we acquired resting-state functional magnetic resonance imaging data during wakefulness and graded levels of consciousness in rats. Data were analyzed using a dynamic approach combining the sliding window method and k-means clustering. Our results demonstrate that whole-brain networks contained several quasi-stable patterns that dynamically recurred from the awake state into anesthetized states. Remarkably, two brain connectivity states with distinct spatial similarity to the structure of anatomical connectivity were strongly biased toward high and low consciousness levels, respectively. These results provide compelling neuroimaging evidence linking the dynamics of whole-brain functional connectivity patterns and states of consciousness at the behavioral level. PMID:27846731

Managing health worker migration: a qualitative study of the Philippine response to nurse brain drain

PubMed Central

2012-01-01

Background The emigration of skilled nurses from the Philippines is an ongoing phenomenon that has impacted the quality and quantity of the nursing workforce, while strengthening the domestic economy through remittances. This study examines how the development of brain drain-responsive policies is driven by the effects of nurse migration and how such efforts aim to achieve mind-shifts among nurses, governing and regulatory bodies, and public and private institutions in the Philippines and worldwide. Methods Interviews and focus group discussions were conducted to elicit exploratory perspectives on the policy response to nurse brain drain. Interviews with key informants from the nursing, labour and immigration sectors explored key themes behind the development of policies and programmes that respond to nurse migration. Focus group discussions were held with practising nurses to understand policy recipients’ perspectives on nurse migration and policy. Results Using the qualitative data, a thematic framework was created to conceptualize participants’ perceptions of how nurse migration has driven the policy development process. The framework demonstrates that policymakers have recognised the complexity of the brain drain phenomenon and are crafting dynamic policies and programmes that work to shift domestic and global mindsets on nurse training, employment and recruitment. Conclusions Development of responsive policy to Filipino nurse brain drain offers a glimpse into a domestic response to an increasingly prominent global issue. As a major source of professionals migrating abroad for employment, the Philippines has formalised efforts to manage nurse migration. Accordingly, the Philippine paradigm, summarised by the thematic framework presented in this paper, may act as an example for other countries that are experiencing similar shifts in healthcare worker employment due to migration. PMID:23249411

A plastic corticostriatal circuit model of adaptation in perceptual decision making

PubMed Central

Hsiao, Pao-Yueh; Lo, Chung-Chuan

2013-01-01

The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA) system that modulates spike-timing dependent plasticity (STDP). We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject's preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment. PMID:24339814

Dynamic diaschisis: anatomically remote and context-sensitive human brain lesions.

PubMed

Price, C J; Warburton, E A; Moore, C J; Frackowiak, R S; Friston, K J

2001-05-15

Functional neuroimaging was used to investigate how lesions to the Broca's area impair neuronal responses in remote undamaged cortical regions. Four patients with speech output problems, but relatively preserved comprehension, were scanned while viewing words relative to consonant letter strings. In normal subjects, this results in left lateralized activation in the posterior inferior frontal, middle temporal, and posterior inferior temporal cortices. Each patient activated normally in the middle temporal region but abnormally in the damaged posterior inferior frontal cortex and the undamaged posterior inferior temporal cortex. In the damaged frontal region, activity was insensitive to the presence of words but in the undamaged posterior inferior temporal region, activity decreased in the presence of words rather than increasing as it did in the normal individuals. The reversal of responses in the left posterior inferior temporal region illustrate the context-sensitive nature of the abnormality and that failure to activate the left posterior temporal region could not simply be accounted for by insufficient demands on the underlying function. We propose that, in normal individuals, visual word presentation changes the effective connectivity among reading areas and, in patients, posterior temporal responses are abnormal when they depend upon inputs from the damaged inferior frontal cortex. Our results serve to introduce the concept of dynamic diaschisis; the anatomically remote and context-sensitive effects of focal brain lesions. Dynamic diaschisis reveals abnormalities of functional integration that may have profound implications for neuropsychological inference, functional anatomy and, vicariously, cognitive rehabilitation.

Higher-Order Activity beyond the Word Level: Cortical Dynamics of Simple Transitive Sentence Comprehension

ERIC Educational Resources Information Center

Martin-Loeches, M.; Casado, P.; Hinojosa, J.A.; Carretie, L.; Munoz, F.; Pozo, M.A.

2005-01-01

Slow electrophysiological effects, which fluctuate throughout the course of a sentence, independent of transient responses to individual words, have been reported. However, this type of activity has scarcely been studied, and with only limited use of electrophysiological information, so that the brain areas in which these variations originate have…

An Overview on Evaluation of E-Learning/Training Response Time Considering Artificial Neural Networks Modeling

ERIC Educational Resources Information Center

Mustafa, Hassan M. H.; Tourkia, Fadhel Ben; Ramadan, Ramadan Mohamed

2017-01-01

The objective of this piece of research is to interpret and investigate systematically an observed brain functional phenomenon which is associated with proceeding of e-learning processes. More specifically, this work addresses an interesting and challenging educational issue concerned with dynamical evaluation of elearning performance considering…

Aquaporin-4 Functionality and Virchow-Robin Space Water Dynamics: Physiological Model for Neurovascular Coupling and Glymphatic Flow

PubMed Central

Kwee, Ingrid L.

2017-01-01

The unique properties of brain capillary endothelium, critical in maintaining the blood-brain barrier (BBB) and restricting water permeability across the BBB, have important consequences on fluid hydrodynamics inside the BBB hereto inadequately recognized. Recent studies indicate that the mechanisms underlying brain water dynamics are distinct from systemic tissue water dynamics. Hydrostatic pressure created by the systolic force of the heart, essential for interstitial circulation and lymphatic flow in systemic circulation, is effectively impeded from propagating into the interstitial fluid inside the BBB by the tightly sealed endothelium of brain capillaries. Instead, fluid dynamics inside the BBB is realized by aquaporin-4 (AQP-4), the water channel that connects astrocyte cytoplasm and extracellular (interstitial) fluid. Brain interstitial fluid dynamics, and therefore AQP-4, are now recognized as essential for two unique functions, namely, neurovascular coupling and glymphatic flow, the brain equivalent of systemic lymphatics. PMID:28820467

Aquaporin-4 Functionality and Virchow-Robin Space Water Dynamics: Physiological Model for Neurovascular Coupling and Glymphatic Flow.

PubMed

Nakada, Tsutomu; Kwee, Ingrid L; Igarashi, Hironaka; Suzuki, Yuji

2017-08-18

The unique properties of brain capillary endothelium, critical in maintaining the blood-brain barrier (BBB) and restricting water permeability across the BBB, have important consequences on fluid hydrodynamics inside the BBB hereto inadequately recognized. Recent studies indicate that the mechanisms underlying brain water dynamics are distinct from systemic tissue water dynamics. Hydrostatic pressure created by the systolic force of the heart, essential for interstitial circulation and lymphatic flow in systemic circulation, is effectively impeded from propagating into the interstitial fluid inside the BBB by the tightly sealed endothelium of brain capillaries. Instead, fluid dynamics inside the BBB is realized by aquaporin-4 (AQP-4), the water channel that connects astrocyte cytoplasm and extracellular (interstitial) fluid. Brain interstitial fluid dynamics, and therefore AQP-4, are now recognized as essential for two unique functions, namely, neurovascular coupling and glymphatic flow, the brain equivalent of systemic lymphatics.

Decoding brain state transitions in the pedunculopontine nucleus: cooperative phasic and tonic mechanisms

PubMed Central

Petzold, Anne; Valencia, Miguel; Pál, Balázs; Mena-Segovia, Juan

2015-01-01

Cholinergic neurons of the pedunculopontine nucleus (PPN) are most active during the waking state. Their activation is deemed to cause a switch in the global brain activity from sleep to wakefulness, while their sustained discharge may contribute to upholding the waking state and enhancing arousal. Similarly, non-cholinergic PPN neurons are responsive to brain state transitions and their activation may influence some of the same targets of cholinergic neurons, suggesting that they operate in coordination. Yet, it is not clear how the discharge of distinct classes of PPN neurons organize during brain states. Here, we monitored the in vivo network activity of PPN neurons in the anesthetized rat across two distinct levels of cortical dynamics and their transitions. We identified a highly structured configuration in PPN network activity during slow-wave activity that was replaced by decorrelated activity during the activated state (AS). During the transition, neurons were predominantly excited (phasically or tonically), but some were inhibited. Identified cholinergic neurons displayed phasic and short latency responses to sensory stimulation, whereas the majority of non-cholinergic showed tonic responses and remained at high discharge rates beyond the state transition. In vitro recordings demonstrate that cholinergic neurons exhibit fast adaptation that prevents them from discharging at high rates over prolonged time periods. Our data shows that PPN neurons have distinct but complementary roles during brain state transitions, where cholinergic neurons provide a fast and transient response to sensory events that drive state transitions, whereas non-cholinergic neurons maintain an elevated firing rate during global activation. PMID:26582977

Dynamical properties of the brain tissue under oscillatory shear stresses at large strain range

NASA Astrophysics Data System (ADS)

Boudjema, F.; Khelidj, B.; Lounis, M.

2017-01-01

In this experimental work, we study the viscoelastic behaviour of in vitro brain tissue, particularly the white matter, under oscillatory shear strain. The selective vulnerability of this tissue is the anisotropic mechanical properties of theirs different regions lead to a sensitivity to the angular shear rate and magnitude of strain. For this aim, shear storage modulus (G‧) and loss modulus (G″) were measured over a range of frequencies (1 to 100 Hz), for different levels of strain (1 %, to 50 %). The mechanical responses of the brain matter samples showed a viscoelastic behaviour that depend on the correlated strain level and frequency range and old age sample. The samples have been showed evolution behaviour by increasing then decreasing the strain level. Also, the stiffness anisotropy of brain matter was showed between regions and species.

Neural Dynamics Underlying Target Detection in the Human Brain

PubMed Central

Bansal, Arjun K.; Madhavan, Radhika; Agam, Yigal; Golby, Alexandra; Madsen, Joseph R.

2014-01-01

Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses. PMID:24553944

Anatomical connectivity influences both intra- and inter-brain synchronizations.

PubMed

Dumas, Guillaume; Chavez, Mario; Nadel, Jacqueline; Martinerie, Jacques

2012-01-01

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

PubMed

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.

Brain Dynamics: Methodological Issues and Applications in Psychiatric and Neurologic Diseases

NASA Astrophysics Data System (ADS)

Pezard, Laurent

The human brain is a complex dynamical system generating the EEG signal. Numerical methods developed to study complex physical dynamics have been used to characterize EEG since the mid-eighties. This endeavor raised several issues related to the specificity of EEG. Firstly, theoretical and methodological studies should address the major differences between the dynamics of the human brain and physical systems. Secondly, this approach of EEG signal should prove to be relevant for dealing with physiological or clinical problems. A set of studies performed in our group is presented here within the context of these two problematic aspects. After the discussion of methodological drawbacks, we review numerical simulations related to the high dimension and spatial extension of brain dynamics. Experimental studies in neurologic and psychiatric disease are then presented. We conclude that if it is now clear that brain dynamics changes in relation with clinical situations, methodological problems remain largely unsolved.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

PubMed

Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

Deep Brain Stimulation Frequency—A Divining Rod for New and Novel Concepts of Nervous System Function and Therapy

PubMed Central

Montgomery, Erwin B.; He, Huang

2016-01-01

The efficacy of Deep Brain Stimulation (DBS) for an expanding array of neurological and psychiatric disorders demonstrates directly that DBS affects the basic electroneurophysiological mechanisms of the brain. The increasing array of active electrode configurations, stimulation currents, pulse widths, frequencies, and pulse patterns provides valuable tools to probe electroneurophysiological mechanisms. The extension of basic electroneurophysiological and anatomical concepts using sophisticated computational modeling and simulation has provided relatively straightforward explanations of all the DBS parameters except frequency. This article summarizes current thought about frequency and relevant observations. Current methodological and conceptual errors are critically examined in the hope that future work will not replicate these errors. One possible alternative theory is presented to provide a contrast to many current theories. DBS, conceptually, is a noisy discrete oscillator interacting with the basal ganglia–thalamic–cortical system of multiple re-entrant, discrete oscillators. Implications for positive and negative resonance, stochastic resonance and coherence, noisy synchronization, and holographic memory (related to movement generation) are presented. The time course of DBS neuronal responses demonstrates evolution of the DBS response consistent with the dynamics of re-entrant mechanisms. Finally, computational modeling demonstrates identical dynamics as seen by neuronal activities recorded from human and nonhuman primates, illustrating the differences of discrete from continuous harmonic oscillators and the power of conceptualizing the nervous system as composed on interacting discrete nonlinear oscillators. PMID:27548234

Haptic contents of a movie dynamically engage the spectator's sensorimotor cortex.

PubMed

Lankinen, Kaisu; Smeds, Eero; Tikka, Pia; Pihko, Elina; Hari, Riitta; Koskinen, Miika

2016-11-01

Observation of another person's actions and feelings activates brain areas that support similar functions in the observer, thereby facilitating inferences about the other's mental and bodily states. In real life, events eliciting this kind of vicarious brain activations are intermingled with other complex, ever-changing stimuli in the environment. One practical approach to study the neural underpinnings of real-life vicarious perception is to image brain activity during movie viewing. Here the goal was to find out how observed haptic events in a silent movie would affect the spectator's sensorimotor cortex. The functional state of the sensorimotor cortex was monitored by analyzing, in 16 healthy subjects, magnetoencephalographic (MEG) responses to tactile finger stimuli that were presented once per second throughout the session. Using canonical correlation analysis and spatial filtering, consistent single-trial responses across subjects were uncovered, and their waveform changes throughout the movie were quantified. The long-latency (85-175 ms) parts of the responses were modulated in concordance with the participants' average moment-by-moment ratings of own engagement in the haptic content of the movie (correlation r = 0.49; ratings collected after the MEG session). The results, obtained by using novel signal-analysis approaches, demonstrate that the functional state of the human sensorimotor cortex fluctuates in a fine-grained manner even during passive observation of temporally varying haptic events. Hum Brain Mapp 37:4061-4068, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Permutation auto-mutual information of electroencephalogram in anesthesia

NASA Astrophysics Data System (ADS)

Liang, Zhenhu; Wang, Yinghua; Ouyang, Gaoxiang; Voss, Logan J.; Sleigh, Jamie W.; Li, Xiaoli

2013-04-01

Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinical doctors and drug designers. To explore the dynamical features of brain activity in anesthesia, a permutation auto-mutual information (PAMI) method is proposed to measure the information coupling of electroencephalogram (EEG) time series obtained in anesthesia. Approach. The PAMI is developed and applied on EEG data collected from 19 patients under sevoflurane anesthesia. The results are compared with the traditional auto-mutual information (AMI), SynchFastSlow (SFS, derived from the BIS index), permutation entropy (PE), composite PE (CPE), response entropy (RE) and state entropy (SE). Performance of all indices is assessed by pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability. Main results. The PK/PD modeling and prediction probability analysis show that the PAMI index correlates closely with the anesthetic effect. The coefficient of determination R2 between PAMI values and the sevoflurane effect site concentrations, and the prediction probability Pk are higher in comparison with other indices. The information coupling in EEG series can be applied to indicate the effect of the anesthetic drug sevoflurane on the brain activity as well as other indices. The PAMI of the EEG signals is suggested as a new index to track drug concentration change. Significance. The PAMI is a useful index for analyzing the EEG dynamics during general anesthesia.

Functional Network Dynamics of the Language System.

PubMed

Chai, Lucy R; Mattar, Marcelo G; Blank, Idan Asher; Fedorenko, Evelina; Bassett, Danielle S

2016-10-17

During linguistic processing, a set of brain regions on the lateral surfaces of the left frontal, temporal, and parietal cortices exhibit robust responses. These areas display highly correlated activity while a subject rests or performs a naturalistic language comprehension task, suggesting that they form an integrated functional system. Evidence suggests that this system is spatially and functionally distinct from other systems that support high-level cognition in humans. Yet, how different regions within this system might be recruited dynamically during task performance is not well understood. Here we use network methods, applied to fMRI data collected from 22 human subjects performing a language comprehension task, to reveal the dynamic nature of the language system. We observe the presence of a stable core of brain regions, predominantly located in the left hemisphere, that consistently coactivate with one another. We also observe the presence of a more flexible periphery of brain regions, predominantly located in the right hemisphere, that coactivate with different regions at different times. However, the language functional ROIs in the angular gyrus and the anterior temporal lobe were notable exceptions to this trend. By highlighting the temporal dimension of language processing, these results suggest a trade-off between a region's specialization and its capacity for flexible network reconfiguration. © The Author 2016. Published by Oxford University Press.

Functional Network Dynamics of the Language System

PubMed Central

Chai, Lucy R.; Mattar, Marcelo G.; Blank, Idan Asher; Fedorenko, Evelina; Bassett, Danielle S.

2016-01-01

During linguistic processing, a set of brain regions on the lateral surfaces of the left frontal, temporal, and parietal cortices exhibit robust responses. These areas display highly correlated activity while a subject rests or performs a naturalistic language comprehension task, suggesting that they form an integrated functional system. Evidence suggests that this system is spatially and functionally distinct from other systems that support high-level cognition in humans. Yet, how different regions within this system might be recruited dynamically during task performance is not well understood. Here we use network methods, applied to fMRI data collected from 22 human subjects performing a language comprehension task, to reveal the dynamic nature of the language system. We observe the presence of a stable core of brain regions, predominantly located in the left hemisphere, that consistently coactivate with one another. We also observe the presence of a more flexible periphery of brain regions, predominantly located in the right hemisphere, that coactivate with different regions at different times. However, the language functional ROIs in the angular gyrus and the anterior temporal lobe were notable exceptions to this trend. By highlighting the temporal dimension of language processing, these results suggest a trade-off between a region's specialization and its capacity for flexible network reconfiguration. PMID:27550868

High-speed swept source optical coherence Doppler tomography for deep brain microvascular imaging

NASA Astrophysics Data System (ADS)

Chen, Wei; You, Jiang; Gu, Xiaochun; Du, Congwu; Pan, Yingtian

2016-12-01

Noninvasive microvascular imaging using optical coherence Doppler tomography (ODT) has shown great promise in brain studies; however, high-speed microcirculatory imaging in deep brain remains an open quest. A high-speed 1.3 μm swept-source ODT (SS-ODT) system is reported which was based on a 200 kHz vertical-cavity-surface-emitting laser. Phase errors induced by sweep-trigger desynchronization were effectively reduced by spectral phase encoding and instantaneous correlation among the A-scans. Phantom studies have revealed a significant reduction in phase noise, thus an enhancement of minimally detectable flow down to 268.2 μm/s. Further in vivo validation was performed, in which 3D cerebral-blood-flow (CBF) networks in mouse brain over a large field-of-view (FOV: 8.5 × 5 × 3.2 mm3) was scanned through thinned skull. Results showed that fast flows up to 3 cm/s in pial vessels and minute flows down to 0.3 mm/s in arterioles or venules were readily detectable at depths down to 3.2 mm. Moreover, the dynamic changes of the CBF networks elicited by acute cocaine such as heterogeneous responses in various vessel compartments and at different cortical layers as well as transient ischemic events were tracked, suggesting the potential of SS-ODT for brain functional imaging that requires high flow sensitivity and dynamic range, fast frame rate and a large FOV to cover different brain regions.

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

PubMed Central

Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro

2015-01-01

Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045

Learning to Estimate Dynamical State with Probabilistic Population Codes.

PubMed

Makin, Joseph G; Dichter, Benjamin K; Sabes, Philip N

2015-11-01

Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH)-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states.

Learning to Estimate Dynamical State with Probabilistic Population Codes

PubMed Central

Sabes, Philip N.

2015-01-01

Tracking moving objects, including one’s own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF), the parameters of which can be learned via latent-variable density estimation (the EM algorithm). The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, “probabilistic population codes.” We show that a recurrent neural network—a modified form of an exponential family harmonium (EFH)—that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts) to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states. PMID:26540152

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

The dynamic genome: transposons and environmental adaptation in the nervous system.

PubMed

Lapp, Hannah E; Hunter, Richard G

2016-02-01

Classically thought as genomic clutter, the functional significance of transposable elements (TEs) has only recently become a focus of attention in neuroscience. Increasingly, studies have demonstrated that the brain seems to have more retrotransposition and TE transcription relative to other somatic tissues, suggesting a unique role for TEs in the central nervous system. TE expression and transposition also appear to vary by brain region and change in response to environmental stimuli such as stress. TEs appear to serve a number of adaptive roles in the nervous system. The regulation of TE expression by steroid, epigenetic and other mechanisms in interplay with the environment represents a significant and novel avenue to understanding both normal brain function and disease.

Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia

PubMed Central

Yu, Qingbao; Erhardt, Erik B.; Sui, Jing; Du, Yuhui; He, Hao; Hjelm, Devon; Cetin, Mustafa S.; Rachakonda, Srinivas; Miller, Robyn L.; Pearlson, Godfrey; Calhoun, Vince D.

2014-01-01

Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations over time. Here we develop a new framework for accessing dynamic graph properties of time-varying functional brain connectivity in resting state fMRI data and apply it to healthy controls (HCs) and patients with schizophrenia (SZs). Specifically, nodes of brain graphs are defined by intrinsic connectivity networks (ICNs) identified by group independent component analysis (ICA). Dynamic graph metrics of the time-varying brain connectivity estimated by the correlation of sliding time-windowed ICA time courses of ICNs are calculated. First- and second-level connectivity states are detected based on the correlation of nodal connectivity strength between time-varying brain graphs. Our results indicate that SZs show decreased variance in the dynamic graph metrics. Consistent with prior stationary functional brain connectivity works, graph measures of identified first-level connectivity states show lower values in SZs. In addition, more first-level connectivity states are disassociated with the second-level connectivity state which resembles the stationary connectivity pattern computed by the entire scan. Collectively, the findings provide new evidence about altered dynamic brain graphs in schizophrenia which may underscore the abnormal brain performance in this mental illness. PMID:25514514

Enhanced emotional responses during social coordination with a virtual partner

PubMed Central

Dumas, Guillaume; Kelso, J.A. Scott; Tognoli, Emmanuelle

2016-01-01

Emotion and motion, though seldom studied in tandem, are complementary aspects of social experience. This study investigates variations in emotional responses during movement coordination between a human and a Virtual Partner (VP), an agent whose virtual finger movements are driven by the Haken-Kelso-Bunz (HKB) equations of Coordination Dynamics. Twenty-one subjects were instructed to coordinate finger movements with the VP in either inphase or antiphase patterns. By adjusting model parameters, we manipulated the ‘intention’ of VP as cooperative or competitive with the human's instructed goal. Skin potential responses (SPR) were recorded to quantify the intensity of emotional response. At the end of each trial, subjects rated the VP's intention and whether they thought their partner was another human being or a machine. We found greater emotional responses when subjects reported that their partner was human and when coordination was stable. That emotional responses are strongly influenced by dynamic features of the VP's behavior, has implications for mental health, brain disorders and the design of socially cooperative machines. PMID:27094374

Theta dynamics reveal domain-specific control over stimulus and response conflict.

PubMed

Nigbur, Roland; Cohen, Michael X; Ridderinkhof, K Richard; Stürmer, Birgit

2012-05-01

Cognitive control allows us to adjust to environmental changes. The medial frontal cortex (MFC) is thought to detect conflicts and recruit additional resources from other brain areas including the lateral prefrontal cortices. Here we investigated how the MFC acts in concert with visual, motor, and lateral prefrontal cortices to support adaptations of goal-directed behavior. Physiologically, these interactions may occur through local and long-range synchronized oscillation dynamics, particularly in the theta range (4-8 Hz). A speeded flanker task allowed us to investigate conflict-type-specific control networks for perceptual and response conflicts. Theta power over MFC was sensitive to both perceptual and response conflict. Interareal theta phase synchrony, however, indicated a selective enhancement specific for response conflicts between MFC and left frontal cortex as well as between MFC and the presumed motor cortex contralateral to the response hand. These findings suggest that MFC theta-band activity is both generally involved in conflict processing and specifically involved in linking a neural network controlling response conflict.

Patients with Chronic Visceral Pain Show Sex-Related Alterations in Intrinsic Oscillations of the Resting Brain

PubMed Central

Hong, Jui-Yang; Kilpatrick, Lisa A.; Labus, Jennifer; Gupta, Arpana; Jiang, Zhiguo; Ashe-McNalley, Cody; Stains, Jean; Heendeniya, Nuwanthi; Ebrat, Bahar; Smith, Suzanne; Tillisch, Kirsten; Naliboff, Bruce

2013-01-01

Abnormal responses of the brain to delivered and expected aversive gut stimuli have been implicated in the pathophysiology of irritable bowel syndrome (IBS), a visceral pain syndrome occurring more commonly in women. Task-free resting-state functional magnetic resonance imaging (fMRI) can provide information about the dynamics of brain activity that may be involved in altered processing and/or modulation of visceral afferent signals. Fractional amplitude of low-frequency fluctuation is a measure of the power spectrum intensity of spontaneous brain oscillations. This approach was used here to identify differences in the resting-state activity of the human brain in IBS subjects compared with healthy controls (HCs) and to identify the role of sex-related differences. We found that both the female HCs and female IBS subjects had a frequency power distribution skewed toward high frequency to a greater extent in the amygdala and hippocampus compared with male subjects. In addition, female IBS subjects had a frequency power distribution skewed toward high frequency in the insula and toward low frequency in the sensorimotor cortex to a greater extent than male IBS subjects. Correlations were observed between resting-state blood oxygen level-dependent signal dynamics and some clinical symptom measures (e.g., abdominal discomfort). These findings provide the first insight into sex-related differences in IBS subjects compared with HCs using resting-state fMRI. PMID:23864686

The visual cognitive network, but not the visual sensory network, is affected in amnestic mild cognitive impairment: a study of brain oscillatory responses.

PubMed

Yener, Görsev G; Emek-Savaş, Derya Durusu; Güntekin, Bahar; Başar, Erol

2014-10-17

Mild Cognitive Impairment (MCI) is considered in many as prodromal stage of Alzheimer's disease (AD). Event-related oscillations (ERO) reflect cognitive responses of brain whereas sensory-evoked oscillations (SEO) inform about sensory responses. For this study, we compared visual SEO and ERO responses in MCI to explore brain dynamics (BACKGROUND). Forty-three patients with MCI (mean age=74.0 year) and 41 age- and education-matched healthy-elderly controls (HC) (mean age=71.1 year) participated in the study. The maximum peak-to-peak amplitudes for each subject's averaged delta response (0.5-3.0 Hz) were measured from two conditions (simple visual stimulation and classical visual oddball paradigm target stimulation) (METHOD). Overall, amplitudes of target ERO responses were higher than SEO amplitudes. The preferential location for maximum amplitude values was frontal lobe for ERO and occipital lobe for SEO. The ANOVA for delta responses showed significant results for the group Xparadigm. Post-hoc tests indicated that (1) the difference between groups were significant for target delta responses, but not for SEO, (2) ERO elicited higher responses for HC than MCI patients, and (3) females had higher target ERO than males and this difference was pronounced in the control group (RESULTS). Overall, cognitive responses display almost double the amplitudes of sensory responses over frontal regions. The topography of oscillatory responses differs depending on stimuli: visualsensory responses are highest over occipitals and -cognitive responses over frontal regions. A group effect is observed in MCI indicating that visual sensory and cognitive circuits behave differently indicating preserved visual sensory responses, but decreased cognitive responses (CONCLUSION). Copyright © 2014 Elsevier B.V. All rights reserved.

The Kantian brain: brain dynamics from a neurophenomenological perspective.

PubMed

Fazelpour, Sina; Thompson, Evan

2015-04-01

Current research on spontaneous, self-generated brain rhythms and dynamic neural network coordination cast new light on Immanuel Kant's idea of the 'spontaneity' of cognition, that is, the mind's capacity to organize and synthesize sensory stimuli in novel, unprecedented ways. Nevertheless, determining the precise nature of the brain-cognition mapping remains an outstanding challenge. Neurophenomenology, which uses phenomenological information about the variability of subjective experience in order to illuminate the variability of brain dynamics, offers a promising method for addressing this challenge. Copyright © 2014 Elsevier Ltd. All rights reserved.

Brain response to empathy-eliciting scenarios involving pain in incarcerated psychopaths

PubMed Central

Decety, Jean; Skelly, Laurie R.; Kiehl, Kent A.

2013-01-01

Context A marked lack of empathy is a hallmark characteristic of individuals with psychopathy. However, neural response associated to empathic processing has not yet been directly examined in psychopathy especially in response to the perception of other people in pain and distress. Objective To identify potential differences in patterns of neural activity in incarcerated psychopaths and incarcerated controls during the perception of empathy-eliciting stimuli depicting other people in pain. Design In a case-control study, brain activation patterns elicited by dynamic stimuli depicting individuals being harmed and facial expression of pain were compared between incarcerated psychopaths and incarcerated controls. Setting Participants were scanned in on the grounds of a correctional facility using the Mind Research Network's mobile 1.5 T MRI system. Participants Eighty incarcerated males were classified according to scores on the Hare Psychopathy Checklist-Revised (PCL-R) as high (n = 27; PCL-R =30), intermediate (n = 28; PCL-R between 21–29), or low (n = 25; PCL-R ≤20) on psychopathy. Main Outcome Measure Neuro-hemodynamic response to empathy-eliciting dynamic scenarios revealed by functional magnetic resonance imaging. Results Psychopaths exhibited significantly less activation in the ventromedial prefrontal cortex, lateral orbitofrontal cortex, and periaqueductal gray relative to controls, but showed greater activation in the insula. Conclusion In response to pain cues expressed by others, psychopaths exhibit deficits in vmPFC and OFC regardless of stimulus type, but display selective impairment in processing facial cues of distress in regions associated with cognitive mentalizing. PMID:23615636

BrainBrowser: distributed, web-based neurological data visualization.

PubMed

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C

2014-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.

BrainBrowser: distributed, web-based neurological data visualization

PubMed Central

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C.

2015-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible. PMID:25628562

Haptic contents of a movie dynamically engage the spectator's sensorimotor cortex

PubMed Central

Smeds, Eero; Tikka, Pia; Pihko, Elina; Hari, Riitta; Koskinen, Miika

2016-01-01

Abstract Observation of another person's actions and feelings activates brain areas that support similar functions in the observer, thereby facilitating inferences about the other's mental and bodily states. In real life, events eliciting this kind of vicarious brain activations are intermingled with other complex, ever‐changing stimuli in the environment. One practical approach to study the neural underpinnings of real‐life vicarious perception is to image brain activity during movie viewing. Here the goal was to find out how observed haptic events in a silent movie would affect the spectator's sensorimotor cortex. The functional state of the sensorimotor cortex was monitored by analyzing, in 16 healthy subjects, magnetoencephalographic (MEG) responses to tactile finger stimuli that were presented once per second throughout the session. Using canonical correlation analysis and spatial filtering, consistent single‐trial responses across subjects were uncovered, and their waveform changes throughout the movie were quantified. The long‐latency (85–175 ms) parts of the responses were modulated in concordance with the participants’ average moment‐by‐moment ratings of own engagement in the haptic content of the movie (correlation r = 0.49; ratings collected after the MEG session). The results, obtained by using novel signal‐analysis approaches, demonstrate that the functional state of the human sensorimotor cortex fluctuates in a fine‐grained manner even during passive observation of temporally varying haptic events. Hum Brain Mapp 37:4061–4068, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:27364184

Feature extraction inspired by V1 in visual cortex

NASA Astrophysics Data System (ADS)

Lv, Chao; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Xin, Peng; Zhu, Mingning; Ma, Hongqiang

2018-04-01

Target feature extraction plays an important role in pattern recognition. It is the most complicated activity in the brain mechanism of biological vision. Inspired by high properties of primary visual cortex (V1) in extracting dynamic and static features, a visual perception model was raised. Firstly, 28 spatial-temporal filters with different orientations, half-squaring operation and divisive normalization were adopted to obtain the responses of V1 simple cells; then, an adjustable parameter was added to the output weight so that the response of complex cells was got. Experimental results indicate that the proposed V1 model can perceive motion information well. Besides, it has a good edge detection capability. The model inspired by V1 has good performance in feature extraction and effectively combines brain-inspired intelligence with computer vision.

Neural dynamics for landmark orientation and angular path integration

PubMed Central

Seelig, Johannes D.; Jayaraman, Vivek

2015-01-01

Summary Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed flies walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body — a toroidal structure in the center of the fly brain. The population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity — a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors — network structures proposed to support the function of navigational brain circuits. PMID:25971509

Neural markers of social and monetary rewards in children with Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder.

PubMed

Gonzalez-Gadea, Maria Luz; Sigman, Mariano; Rattazzi, Alexia; Lavin, Claudio; Rivera-Rei, Alvaro; Marino, Julian; Manes, Facundo; Ibanez, Agustin

2016-07-28

Recent theories of decision making propose a shared value-related brain mechanism for encoding monetary and social rewards. We tested this model in children with Attention-Deficit/Hyperactivity Disorder (ADHD), children with Autism Spectrum Disorder (ASD) and control children. We monitored participants' brain dynamics using high density-electroencephalography while they played a monetary and social reward tasks. Control children exhibited a feedback Error-Related Negativity (fERN) modulation and Anterior Cingulate Cortex (ACC) source activation during both tasks. Remarkably, although cooperation resulted in greater losses for the participants, the betrayal options generated greater fERN responses. ADHD subjects exhibited an absence of fERN modulation and reduced ACC activation during both tasks. ASD subjects exhibited normal fERN modulation during monetary choices and inverted fERN/ACC responses in social options than did controls. These results suggest that in neurotypicals, monetary losses and observed disloyal social decisions induced similar activity in the brain value system. In ADHD children, difficulties in reward processing affected early brain signatures of monetary and social decisions. Conversely, ASD children showed intact neural markers of value-related monetary mechanisms, but no brain modulation by prosociality in the social task. These results offer insight into the typical and atypical developments of neural correlates of monetary and social reward processing.

Brain function assessment in different conscious states.

PubMed

Ozgoren, Murat; Bayazit, Onur; Kocaaslan, Sibel; Gokmen, Necati; Oniz, Adile

2010-06-03

The study of brain functioning is a major challenge in neuroscience fields as human brain has a dynamic and ever changing information processing. Case is worsened with conditions where brain undergoes major changes in so-called different conscious states. Even though the exact definition of consciousness is a hard one, there are certain conditions where the descriptions have reached a consensus. The sleep and the anesthesia are different conditions which are separable from each other and also from wakefulness. The aim of our group has been to tackle the issue of brain functioning with setting up similar research conditions for these three conscious states. In order to achieve this goal we have designed an auditory stimulation battery with changing conditions to be recorded during a 40 channel EEG polygraph (Nuamps) session. The stimuli (modified mismatch, auditory evoked etc.) have been administered both in the operation room and the sleep lab via Embedded Interactive Stimulus Unit which was developed in our lab. The overall study has provided some results for three domains of consciousness. In order to be able to monitor the changes we have incorporated Bispectral Index Monitoring to both sleep and anesthesia conditions. The first stage results have provided a basic understanding in these altered states such that auditory stimuli have been successfully processed in both light and deep sleep stages. The anesthesia provides a sudden change in brain responsiveness; therefore a dosage dependent anesthetic administration has proved to be useful. The auditory processing was exemplified targeting N1 wave, with a thorough analysis from spectrogram to sLORETA. The frequency components were observed to be shifting throughout the stages. The propofol administration and the deeper sleep stages both resulted in the decreasing of N1 component. The sLORETA revealed similar activity at BA7 in sleep (BIS 70) and target propofol concentration of 1.2 microg/mL. The current study utilized similar stimulation and recording system and incorporated BIS dependent values to validate a common approach to sleep and anesthesia. Accordingly the brain has a complex behavior pattern, dynamically changing its responsiveness in accordance with stimulations and states.

Distinct fMRI Responses to Self-Induced versus Stimulus Motion during Free Viewing in the Macaque

PubMed Central

Kaneko, Takaaki; Saleem, Kadharbatcha S.; Berman, Rebecca A.; Leopold, David A.

2016-01-01

Visual motion responses in the brain are shaped by two distinct sources: the physical movement of objects in the environment and motion resulting from one's own actions. The latter source, termed visual reafference, stems from movements of the head and body, and in primates from the frequent saccadic eye movements that mark natural vision. To study the relative contribution of reafferent and stimulus motion during natural vision, we measured fMRI activity in the brains of two macaques as they freely viewed >50 hours of naturalistic video footage depicting dynamic social interactions. We used eye movements obtained during scanning to estimate the level of reafferent retinal motion at each moment in time. We also estimated the net stimulus motion by analyzing the video content during the same time periods. Mapping the responses to these distinct sources of retinal motion, we found a striking dissociation in the distribution of visual responses throughout the brain. Reafferent motion drove fMRI activity in the early retinotopic areas V1, V2, V3, and V4, particularly in their central visual field representations, as well as lateral aspects of the caudal inferotemporal cortex (area TEO). However, stimulus motion dominated fMRI responses in the superior temporal sulcus, including areas MT, MST, and FST as well as more rostral areas. We discuss this pronounced separation of motion processing in the context of natural vision, saccadic suppression, and the brain's utilization of corollary discharge signals. SIGNIFICANCE STATEMENT Visual motion arises not only from events in the external world, but also from the movements of the observer. For example, even if objects are stationary in the world, the act of walking through a room or shifting one's eyes causes motion on the retina. This “reafferent” motion propagates into the brain as signals that must be interpreted in the context of real object motion. The delineation of whole-brain responses to stimulus versus self-generated retinal motion signals is critical for understanding visual perception and is of pragmatic importance given the increasing use of naturalistic viewing paradigms. The present study uses fMRI to demonstrate that the brain exhibits a fundamentally different pattern of responses to these two sources of retinal motion. PMID:27629710

Aging alters the immunological response to ischemic stroke.

PubMed

Ritzel, Rodney M; Lai, Yun-Ju; Crapser, Joshua D; Patel, Anita R; Schrecengost, Anna; Grenier, Jeremy M; Mancini, Nickolas S; Patrizz, Anthony; Jellison, Evan R; Morales-Scheihing, Diego; Venna, Venugopal R; Kofler, Julia K; Liu, Fudong; Verma, Rajkumar; McCullough, Louise D

2018-05-11

The peripheral immune system plays a critical role in aging and in the response to brain injury. Emerging data suggest inflammatory responses are exacerbated in older animals following ischemic stroke; however, our understanding of these age-related changes is poor. In this work, we demonstrate marked differences in the composition of circulating and infiltrating leukocytes recruited to the ischemic brain of old male mice after stroke compared to young male mice. Blood neutrophilia and neutrophil invasion into the brain were increased in aged animals. Relative to infiltrating monocyte populations, brain-invading neutrophils had reduced phagocytic potential, and produced higher levels of reactive oxygen species and extracellular matrix-degrading enzymes (i.e., MMP-9), which were further exacerbated with age. Hemorrhagic transformation was more pronounced in aged versus young mice relative to infarct size. High numbers of myeloperoxidase-positive neutrophils were found in postmortem human brain samples of old (> 71 years) acute ischemic stroke subjects compared to non-ischemic controls. Many of these neutrophils were found in the brain parenchyma. A large proportion of these neutrophils expressed MMP-9 and positively correlated with hemorrhage and hyperemia. MMP-9 expression and hemorrhagic transformation after stroke increased with age. These changes in the myeloid response to stroke with age led us to hypothesize that the bone marrow response to stroke is altered with age, which could be important for the development of effective therapies targeting the immune response. We generated heterochronic bone marrow chimeras as a tool to determine the contribution of peripheral immune senescence to age- and stroke-induced inflammation. Old hosts that received young bone marrow (i.e., Young → Old) had attenuation of age-related reductions in bFGF and VEGF and showed improved locomotor activity and gait dynamics compared to isochronic (Old → Old) controls. Microglia in young heterochronic mice (Old → Young) developed a senescent-like phenotype. After stroke, aged animals reconstituted with young marrow had reduced behavioral deficits compared to isochronic controls, and had significantly fewer brain-infiltrating neutrophils. Increased rates of hemorrhagic transformation were seen in young mice reconstituted with aged bone marrow. This work suggests that age alters the immunological response to stroke, and that this can be reversed by manipulation of the peripheral immune cells in the bone marrow.

Distinct fMRI Responses to Self-Induced versus Stimulus Motion during Free Viewing in the Macaque.

PubMed

Russ, Brian E; Kaneko, Takaaki; Saleem, Kadharbatcha S; Berman, Rebecca A; Leopold, David A

2016-09-14

Visual motion responses in the brain are shaped by two distinct sources: the physical movement of objects in the environment and motion resulting from one's own actions. The latter source, termed visual reafference, stems from movements of the head and body, and in primates from the frequent saccadic eye movements that mark natural vision. To study the relative contribution of reafferent and stimulus motion during natural vision, we measured fMRI activity in the brains of two macaques as they freely viewed >50 hours of naturalistic video footage depicting dynamic social interactions. We used eye movements obtained during scanning to estimate the level of reafferent retinal motion at each moment in time. We also estimated the net stimulus motion by analyzing the video content during the same time periods. Mapping the responses to these distinct sources of retinal motion, we found a striking dissociation in the distribution of visual responses throughout the brain. Reafferent motion drove fMRI activity in the early retinotopic areas V1, V2, V3, and V4, particularly in their central visual field representations, as well as lateral aspects of the caudal inferotemporal cortex (area TEO). However, stimulus motion dominated fMRI responses in the superior temporal sulcus, including areas MT, MST, and FST as well as more rostral areas. We discuss this pronounced separation of motion processing in the context of natural vision, saccadic suppression, and the brain's utilization of corollary discharge signals. Visual motion arises not only from events in the external world, but also from the movements of the observer. For example, even if objects are stationary in the world, the act of walking through a room or shifting one's eyes causes motion on the retina. This "reafferent" motion propagates into the brain as signals that must be interpreted in the context of real object motion. The delineation of whole-brain responses to stimulus versus self-generated retinal motion signals is critical for understanding visual perception and is of pragmatic importance given the increasing use of naturalistic viewing paradigms. The present study uses fMRI to demonstrate that the brain exhibits a fundamentally different pattern of responses to these two sources of retinal motion. Copyright © 2016 the authors 0270-6474/16/369580-10$15.00/0.

Altered Dynamics of the fMRI Response to Faces in Individuals with Autism

ERIC Educational Resources Information Center

Kleinhans, Natalia M.; Richards, Todd; Greenson, Jessica; Dawson, Geraldine; Aylward, Elizabeth

2016-01-01

Abnormal fMRI habituation in autism spectrum disorders (ASDs) has been proposed as a critical component in social impairment. This study investigated habituation to fearful faces and houses in ASD and whether fMRI measures of brain activity discriminate between ASD and typically developing (TD) controls. Two identical fMRI runs presenting masked…

Stuck in a State of Inattention? Functional Hyperconnectivity as an Indicator of Disturbed Intrinsic Brain Dynamics in Adolescents With Concussion: A Pilot Study

PubMed Central

Virji-Babul, Naznin

2018-01-01

Sports-related concussion in youth is a major public health issue. Evaluating the diffuse and often subtle changes in structure and function that occur in the brain, particularly in this population, remains a significant challenge. The goal of this pilot study was to evaluate the relationship between the intrinsic dynamics of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) and relate these findings to structural brain correlates from diffusion tensor imaging in a group of adolescents with sports-related concussions (n = 6) and a group of healthy adolescent athletes (n = 6). We analyzed rs-fMRI data using a sliding windows approach and related the functional findings to structural brain correlates by applying graph theory analysis to the diffusion tensor imaging data. Within the resting-state condition, we extracted three separate brain states in both groups. Our analysis revealed that the brain dynamics in healthy adolescents was characterized by a dynamic pattern, shifting equally between three brain states; however, in adolescents with concussion, the pattern was more static with a longer time spent in one brain state. Importantly, this lack of dynamic flexibility in the concussed group was associated with increased nodal strength in the left middle frontal gyrus, suggesting reorganization in a region related to attention. This preliminary report shows that both the intrinsic brain dynamics and structural organization are altered in networks related to attention in adolescents with concussion. This first report in adolescents will be used to inform future studies in a larger cohort. PMID:29357675

Stuck in a State of Inattention? Functional Hyperconnectivity as an Indicator of Disturbed Intrinsic Brain Dynamics in Adolescents With Concussion: A Pilot Study.

PubMed

Muller, Angela M; Virji-Babul, Naznin

2018-01-01

Sports-related concussion in youth is a major public health issue. Evaluating the diffuse and often subtle changes in structure and function that occur in the brain, particularly in this population, remains a significant challenge. The goal of this pilot study was to evaluate the relationship between the intrinsic dynamics of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) and relate these findings to structural brain correlates from diffusion tensor imaging in a group of adolescents with sports-related concussions ( n = 6) and a group of healthy adolescent athletes ( n = 6). We analyzed rs-fMRI data using a sliding windows approach and related the functional findings to structural brain correlates by applying graph theory analysis to the diffusion tensor imaging data. Within the resting-state condition, we extracted three separate brain states in both groups. Our analysis revealed that the brain dynamics in healthy adolescents was characterized by a dynamic pattern, shifting equally between three brain states; however, in adolescents with concussion, the pattern was more static with a longer time spent in one brain state. Importantly, this lack of dynamic flexibility in the concussed group was associated with increased nodal strength in the left middle frontal gyrus, suggesting reorganization in a region related to attention. This preliminary report shows that both the intrinsic brain dynamics and structural organization are altered in networks related to attention in adolescents with concussion. This first report in adolescents will be used to inform future studies in a larger cohort.

Emotion regulation in social anxiety disorder: behavioral and neural responses to three socio-emotional tasks

PubMed Central

2013-01-01

Background Social anxiety disorder (SAD) is thought to involve deficits in emotion regulation, and more specifically, deficits in cognitive reappraisal. However, evidence for such deficits is mixed. Methods Using functional magnetic resonance imaging (fMRI) of blood oxygen-level dependent (BOLD) signal, we examined reappraisal-related behavioral and neural responses in 27 participants with generalized SAD and 27 healthy controls (HC) during three socio-emotional tasks: (1) looming harsh faces (Faces); (2) videotaped actors delivering social criticism (Criticism); and (3) written autobiographical negative self-beliefs (Beliefs). Results Behaviorally, compared to HC, participants with SAD had lesser reappraisal-related reduction in negative emotion in the Beliefs task. Neurally, compared to HC, participants with SAD had lesser BOLD responses in reappraisal-related brain regions when reappraising faces, in visual and attention related regions when reappraising criticism, and in the left superior temporal gyrus when reappraising beliefs. Examination of the temporal dynamics of BOLD responses revealed late reappraisal-related increased responses in HC, compared to SAD. In addition, the dorsomedial prefrontal cortex (DMPFC), which showed reappraisal-related increased activity in both groups, had similar temporal dynamics in SAD and HC during the Faces and Criticism tasks, but greater late response increases in HC, compared to SAD, during the Beliefs task. Reappraisal-related greater late DMPFC responses were associated with greater percent reduction in negative emotion ratings in SAD patients. Conclusions These results suggest a dysfunction of cognitive reappraisal in SAD patients, with overall reduced late brain responses in prefrontal regions, particularly when reappraising faces. Decreased late activity in the DMPFC might be associated with deficient reappraisal and greater negative reactivity. Trial registration ClinicalTrials.gov identifier: NCT00380731 PMID:24517388

Hyper-resting brain entropy within chronic smokers and its moderation by Sex.

PubMed

Li, Zhengjun; Fang, Zhuo; Hager, Nathan; Rao, Hengyi; Wang, Ze

2016-07-05

Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers' brains, however less is known about the temporal dynamics within smokers' brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking.

Complete Firing-Rate Response of Neurons with Complex Intrinsic Dynamics

PubMed Central

Puelma Touzel, Maximilian; Wolf, Fred

2015-01-01

The response of a neuronal population over a space of inputs depends on the intrinsic properties of its constituent neurons. Two main modes of single neuron dynamics–integration and resonance–have been distinguished. While resonator cell types exist in a variety of brain areas, few models incorporate this feature and fewer have investigated its effects. To understand better how a resonator’s frequency preference emerges from its intrinsic dynamics and contributes to its local area’s population firing rate dynamics, we analyze the dynamic gain of an analytically solvable two-degree of freedom neuron model. In the Fokker-Planck approach, the dynamic gain is intractable. The alternative Gauss-Rice approach lifts the resetting of the voltage after a spike. This allows us to derive a complete expression for the dynamic gain of a resonator neuron model in terms of a cascade of filters on the input. We find six distinct response types and use them to fully characterize the routes to resonance across all values of the relevant timescales. We find that resonance arises primarily due to slow adaptation with an intrinsic frequency acting to sharpen and adjust the location of the resonant peak. We determine the parameter regions for the existence of an intrinsic frequency and for subthreshold and spiking resonance, finding all possible intersections of the three. The expressions and analysis presented here provide an account of how intrinsic neuron dynamics shape dynamic population response properties and can facilitate the construction of an exact theory of correlations and stability of population activity in networks containing populations of resonator neurons. PMID:26720924

Fast fMRI can detect oscillatory neural activity in humans.

PubMed

Lewis, Laura D; Setsompop, Kawin; Rosen, Bruce R; Polimeni, Jonathan R

2016-10-25

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.

Promising application of dynamic nuclear polarization for in vivo (13)C MR imaging.

PubMed

Yen, Yi-Fen; Nagasawa, Kiyoshi; Nakada, Tsutomu

2011-01-01

Use of hyperpolarized (13)C in magnetic resonance (MR) imaging is a new technique that enhances signal tens of thousands-fold. Recent in vivo animal studies of metabolic imaging that used hyperpolarized (13)C demonstrated its potential in many applications for disease indication, metabolic profiling, and treatment monitoring. We review the basic physics for dynamic nuclear polarization (DNP) and in vivo studies reported in prostate cancer research, hepatocellular carcinoma research, diabetes and cardiac applications, brain metabolism, and treatment response as well as investigations of various DNP (13)C substrates.

Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach

PubMed Central

Teng, Santani

2017-01-01

In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research. This article is part of the themed issue ‘Auditory and visual scene analysis’. PMID:28044019

Abnormal Brain Dynamics Underlie Speech Production in Children with Autism Spectrum Disorder.

PubMed

Pang, Elizabeth W; Valica, Tatiana; MacDonald, Matt J; Taylor, Margot J; Brian, Jessica; Lerch, Jason P; Anagnostou, Evdokia

2016-02-01

A large proportion of children with autism spectrum disorder (ASD) have speech and/or language difficulties. While a number of structural and functional neuroimaging methods have been used to explore the brain differences in ASD with regards to speech and language comprehension and production, the neurobiology of basic speech function in ASD has not been examined. Magnetoencephalography (MEG) is a neuroimaging modality with high spatial and temporal resolution that can be applied to the examination of brain dynamics underlying speech as it can capture the fast responses fundamental to this function. We acquired MEG from 21 children with high-functioning autism (mean age: 11.43 years) and 21 age- and sex-matched controls as they performed a simple oromotor task, a phoneme production task and a phonemic sequencing task. Results showed significant differences in activation magnitude and peak latencies in primary motor cortex (Brodmann Area 4), motor planning areas (BA 6), temporal sequencing and sensorimotor integration areas (BA 22/13) and executive control areas (BA 9). Our findings of significant functional brain differences between these two groups on these simple oromotor and phonemic tasks suggest that these deficits may be foundational and could underlie the language deficits seen in ASD. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research.

Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach.

PubMed

Cichy, Radoslaw Martin; Teng, Santani

2017-02-19

In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research.This article is part of the themed issue 'Auditory and visual scene analysis'. © 2017 The Authors.

Single-Trial Regression Elucidates the Role of Prefrontal Theta Oscillations in Response Conflict

PubMed Central

Cohen, Michael X; Cavanagh, James F.

2011-01-01

In most cognitive neuroscience experiments there are many behavioral and experimental dynamics, and many indices of brain activity, that vary from trial to trial. For example, in studies of response conflict, conflict is usually treated as a binary variable (i.e., response conflict exists or does not in any given trial), whereas some evidence and intuition suggests that conflict may vary in intensity from trial to trial. Here we demonstrate that single-trial multiple regression of time–frequency electrophysiological activity reveals neural mechanisms of cognitive control that are not apparent in cross-trial averages. We also introduce a novel extension to oscillation phase coherence and synchronization analyses, based on “weighted” phase modulation, that has advantages over standard coherence measures in terms of linking electrophysiological dynamics to trial-varying behavior and experimental variables. After replicating previous response conflict findings using trial-averaged data, we extend these findings using single-trial analytic methods to provide novel evidence for the role of medial frontal–lateral prefrontal theta-band synchronization in conflict-induced response time dynamics, including a role for lateral prefrontal theta-band activity in biasing response times according to perceptual conflict. Given that these methods shed new light on the prefrontal mechanisms of response conflict, they are also likely to be useful for investigating other neurocognitive processes. PMID:21713190

Renewal Processes in the Critical Brain

NASA Astrophysics Data System (ADS)

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Gemignani, Angelo

We describe herein a multidisciplinary research, as it developes and applies concepts of the theory of complexity, in turn stemming from recent advancements of statistical physics, onto cognitive neuroscience. We discuss (define) complexity, and how the human brain is a paradigm of it. We discuss how the hypothesis of brain activity dynamically behaving as a critical system is taking momentum in literature, then we focus on a feature of critical systems (hence of the brain), which is the intermittent passage between metastable states, marked by events, locally resetting the memory, but giving rise to correlation functions with infinite correlation times. The events, extracted from multi-channel ElectroEncephaloGrams, mark (are interpreted as) a birth/death process of cooperation, namely of system elements being recruited into collective states. Finally we discuss a recently discovered form of control (in the form of a new Linear Response Theory), that allows an optimized information transmission between complex systems, named Complexity Matching.

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

PubMed

Thompson, William H; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

Complex function in the dynamic brain. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

NASA Astrophysics Data System (ADS)

Anderson, Michael L.

2014-09-01

There is much to commend in this excellent overview of the progress we've made toward-and the challenges that remain for-developing an empirical framework for neuroscience that is adequate to the dynamic complexity of the brain [17]. Here I will limit myself first to highlighting the concept of dynamic affiliation, which I take to be the central feature of the functional architecture of the brain, and second to clarifying Pessoa's brief discussion of the ontology of cognition, to be sure readers appreciate this crucial issue.

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.

PubMed

Fu, Zening; Tu, Yiheng; Di, Xin; Du, Yuhui; Pearlson, G D; Turner, J A; Biswal, Bharat B; Zhang, Zhiguo; Calhoun, V D

2017-09-20

The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2) dALFF and dFC were correlated in time and their correlations are altered in SZ. The overall results support and expand prior work on abnormalities of brain activity, static FC (sFC) and dFC in SZ, and provide new evidence on aberrant time-varying brain activity and its associations with brain connectivity in SZ, which might underscore the disrupted brain cognitive functions in this mental disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

New Therapeutic Drugs from Bioactive Natural Molecules: the Role of Gut Microbiota Metabolism in Neurodegenerative Diseases.

PubMed

Di Meo, Francesco; Donato, Stella; Di Pardo, Alba; Maglione, Vittorio; Filosa, Stefania; Crispi, Stefania

2018-04-03

The gut-brain axis is considered a neuroendocrine system, which connects brain and gastrointestinal tract and plays an important role in stress response. The homeostasis of gut-brain axis is important for healthy conditions and its alterations are associated to neurological disorders and neurodegenerative diseases. Gut microbiota is a dynamic ecosystem that can be altered by external factors such as diet composition, antibiotics or xenobiotics. Recent advances in gut microbiota analyses indicate that the gut bacterial community plays a key role in maintaining normal brain functions. Recent metagenomic analyses have elucidated that the relationship between gut and brain, either in normal or in pathological conditions, reflects the existence of a "microbiota-gut-brain" axis. Gut microbiota composition can be influenced by dietary ingestion of probiotics or natural bioactive molecules such as prebiotics and polyphenols. Their derivatives coming from microbiota metabolism can affect both gut bacterial composition and brain biochemistry. Modifications of microbiota composition by natural bioactive molecules could be used to restore the altered brain functions, which characterize neurodegenerative diseases, leading to consider these compounds as novel therapeutic strategies for the treatment of neuropathologies. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Application of a multicompartment dynamical model to multimodal optical imaging for investigating individual cerebrovascular properties

NASA Astrophysics Data System (ADS)

Desjardins, Michèle; Gagnon, Louis; Gauthier, Claudine; Hoge, Rick D.; Dehaes, Mathieu; Desjardins-Crépeau, Laurence; Bherer, Louis; Lesage, Frédéric

2009-02-01

Biophysical models of hemodynamics provide a tool for quantitative multimodal brain imaging by allowing a deeper understanding of the interplay between neural activity and blood oxygenation, volume and flow responses to stimuli. Multicompartment dynamical models that describe the dynamics and interactions of the vascular and metabolic components of evoked hemodynamic responses have been developed in the literature. In this work, multimodal data using near-infrared spectroscopy (NIRS) and diffuse correlation flowmetry (DCF) is used to estimate total baseline hemoglobin concentration (HBT0) in 7 adult subjects. A validation of the model estimate and investigation of the partial volume effect is done by comparing with time-resolved spectroscopy (TRS) measures of absolute HBT0. Simultaneous NIRS and DCF measurements during hypercapnia are then performed, but are found to be hardly reproducible. The results raise questions about the feasibility of an all-optical model-based estimation of individual vascular properties.

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

PubMed

Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

2017-11-01

Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

The metabolic response to excitotoxicity - lessons from single-cell imaging.

PubMed

Connolly, Niamh M C; Prehn, Jochen H M

2015-04-01

Excitotoxicity is a pathological process implicated in neuronal death during ischaemia, traumatic brain injuries and neurodegenerative diseases. Excitotoxicity is caused by excess levels of glutamate and over-activation of NMDA or calcium-permeable AMPA receptors on neuronal membranes, leading to ionic influx, energetic stress and potential neuronal death. The metabolic response of neurons to excitotoxicity is complex and plays a key role in the ability of the neuron to adapt and recover from such an insult. Single-cell imaging is a powerful experimental technique that can be used to study the neuronal metabolic response to excitotoxicity in vitro and, increasingly, in vivo. Here, we review some of the knowledge of the neuronal metabolic response to excitotoxicity gained from in vitro single-cell imaging, including calcium and ATP dynamics and their effects on mitochondrial function, along with the contribution of glucose metabolism, oxidative stress and additional neuroprotective signalling mechanisms. Future work will combine knowledge gained from single-cell imaging with data from biochemical and computational techniques to garner holistic information about the metabolic response to excitotoxicity at the whole brain level and transfer this knowledge to a clinical setting.

Brain network dysfunction in youth with obsessive-compulsive disorder induced by simple uni-manual behavior: The role of the dorsal anterior cingulate cortex

PubMed Central

Friedman, Amy L.; Burgess, Ashley; Ramaseshan, Karthik; Easter, Phil; Khatib, Dalal; Chowdury, Asadur; Arnold, Paul D.; Hanna, Gregory L.; Rosenberg, David R.; Diwadkar, Vaibhav A.

2017-01-01

In an effort to elucidate differences in functioning brain networks between youth with obsessive-compulsive disorder and controls, we used fMRI signals to analyze brain network interactions of the dorsal anterior cingulate cortex (dACC) during visually coordinated motor responses. Subjects made a uni-manual response to briefly presented probes, at periodic (allowing participants to maintain a “motor set”) or random intervals (demanding reactive responses). Network interactions were assessed using psycho-physiological interaction (PPI), a basic model of functional connectivity evaluating modulatory effects of the dACC in the context of each task condition. Across conditions, OCD were characterized by hyper-modulation by the dACC, with loci alternatively observed as both condition-general and condition-specific. Thus, dynamically driven task demands during simple uni-manual motor control induce compensatory network interactions in cortical-thalamic regions in OCD. These findings support previous research in OCD showing compensatory network interactions during complex memory tasks, but establish that these network effects are observed during basic sensorimotor processing. Thus, these patterns of network dysfunction may in fact be independent of the complexity of tasks used to induce brain network activity. Hypothesis-driven approaches coupled with sophisticated network analyses are a highly valuable approach in using fMRI to uncover mechanisms in disorders like OCD. PMID:27992792

Clinical study and numerical simulation of brain cancer dynamics under radiotherapy

NASA Astrophysics Data System (ADS)

Nawrocki, S.; Zubik-Kowal, B.

2015-05-01

We perform a clinical and numerical study of the progression of brain cancer tumor growth dynamics coupled with the effects of radiotherapy. We obtained clinical data from a sample of brain cancer patients undergoing radiotherapy and compare it to our numerical simulations to a mathematical model of brain tumor cell population growth influenced by radiation treatment. We model how the body biologically receives a physically delivered dose of radiation to the affected tumorous area in the form of a generalized LQ model, modified to account for the conversion process of sublethal lesions into lethal lesions at high radiation doses. We obtain good agreement between our clinical data and our numerical simulations of brain cancer progression given by the mathematical model, which couples tumor growth dynamics and the effect of irradiation. The correlation, spanning a wide dataset, demonstrates the potential of the mathematical model to describe the dynamics of brain tumor growth influenced by radiotherapy.

Neural dynamics and information representation in microcircuits of motor cortex.

PubMed

Tsubo, Yasuhiro; Isomura, Yoshikazu; Fukai, Tomoki

2013-01-01

The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves (PRCs) of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs), in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.

Neural dynamics of social tie formation in economic decision-making.

PubMed

Bault, Nadège; Pelloux, Benjamin; Fahrenfort, Johannes J; Ridderinkhof, K Richard; van Winden, Frans

2015-06-01

The disposition for prosocial conduct, which contributes to cooperation as arising during social interaction, requires cortical network dynamics responsive to the development of social ties, or care about the interests of specific interaction partners. Here, we formulate a dynamic computational model that accurately predicted how tie formation, driven by the interaction history, influences decisions to contribute in a public good game. We used model-driven functional MRI to test the hypothesis that brain regions key to social interactions keep track of dynamics in tie strength. Activation in the medial prefrontal cortex (mPFC) and posterior cingulate cortex tracked the individual's public good contributions. Activation in the bilateral posterior superior temporal sulcus (pSTS), and temporo-parietal junction was modulated parametrically by the dynamically developing social tie-as estimated by our model-supporting a role of these regions in social tie formation. Activity in these two regions further reflected inter-individual differences in tie persistence and sensitivity to behavior of the interaction partner. Functional connectivity between pSTS and mPFC activations indicated that the representation of social ties is integrated in the decision process. These data reveal the brain mechanisms underlying the integration of interaction dynamics into a social tie representation which in turn influenced the individual's prosocial decisions. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Cross-entropy optimization for neuromodulation.

PubMed

Brar, Harleen K; Yunpeng Pan; Mahmoudi, Babak; Theodorou, Evangelos A

2016-08-01

This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller. With insufficient gains, the internal controller cannot provide enough feedback to the brain dynamics causing an increase in correlation between different brain sites. This increase in synchronization results in the destabilization of the brain dynamics, which is representative of an epileptic seizure. To provide compensation for an insufficient internal controller an external controller is designed using proportional-integral feedback control strategy. A cross-entropy optimization algorithm is applied to the chaotic oscillator network model to learn the optimal feedback gains for the external controller instead of hand-tuning the gains to provide sufficient control to the pathological brain and prevent seizure generation. The correlation between the dynamics of neural activity within different brain sites is calculated for experimental data to show similar dynamics of epileptic neural activity as simulated by the network of chaotic oscillators.

Effects of maternal separation on dynamics of urocortin 1 and brain-derived neurotrophic factor in the rat non-preganglionic Edinger-Westphal nucleus.

PubMed

Gaszner, Balázs; Jensen, Kai-Ole; Farkas, József; Reglodi, Dóra; Csernus, Valér; Roubos, Eric W; Kozicz, Tamás

2009-08-01

Although mood disorders are frequently genetically determined and to some degree gender-dependent, the concept of early life 'programming', implying a relation between perinatal environmental events and adult mood disorders, has recently gained considerable attention. In particular, maternal separation (MS) markedly affects various stress-sensitive brain centers. Therefore, MS is considered as a suitable experimental paradigm to study how early life events affect brain plasticity and, hence, cause psychopathologies like major depression. In adult mammals, the classical hypothalamo-pituitary-adrenal (HPA-) axis and the urocortin 1 (Ucn1)-containing non-preganglionic Edinger-Westphal nucleus (npEW) respond in opposite ways to chronic stressors. This raises the hypothesis that MS, which is known to increase vulnerability for adult mood disorders via the dysregulation of the HPA-axis, will affect npEW dynamics as well. We have tested this hypothesis and, moreover, studied a possible role of brain-derived neurotrophic factor (BDNF) in such npEW plasticity. By triple immunocytochemistry we show that BDNF and Ucn1 coexist in rat npEW-neurons that are c-Fos-positive upon acute stress. Quantitative immunocytochemistry revealed that MS increases the contents of Ucn1 and BDNF in these cells. Furthermore, in males and females, the c-Fos response of npEW-Ucn1 neurons upon restraint stress was blunted in animals with MS history, a phenomenon that was concomitant with dampening of the HPA corticosterone response in females but not in males. Based on these data we suggest that the BDNF-containing npEW-Ucn1 system might be affected by MS in a sex-specific manner. This supports the idea that the npEW would play a role in the appearance of sex differences in the pathogenesis of stress-induced mood disorders.

Information flow dynamics in the brain

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Afraimovich, Valentin S.; Bick, Christian; Varona, Pablo

2012-03-01

Timing and dynamics of information in the brain is a hot field in modern neuroscience. The analysis of the temporal evolution of brain information is crucially important for the understanding of higher cognitive mechanisms in normal and pathological states. From the perspective of information dynamics, in this review we discuss working memory capacity, language dynamics, goal-dependent behavior programming and other functions of brain activity. In contrast with the classical description of information theory, which is mostly algebraic, brain flow information dynamics deals with problems such as the stability/instability of information flows, their quality, the timing of sequential processing, the top-down cognitive control of perceptual information, and information creation. In this framework, different types of information flow instabilities correspond to different cognitive disorders. On the other hand, the robustness of cognitive activity is related to the control of the information flow stability. We discuss these problems using both experimental and theoretical approaches, and we argue that brain activity is better understood considering information flows in the phase space of the corresponding dynamical model. In particular, we show how theory helps to understand intriguing experimental results in this matter, and how recent knowledge inspires new theoretical formalisms that can be tested with modern experimental techniques.

Longitudinal changes in zinc transport kinetics, metallothionein, and zinc transporter expression in a blood-brain barrier model in response to a moderately excessive zinc environment$

PubMed Central

Gauthier, Nicole A.; Karki, Shakun; Olley, Bryony J.; Thomas, W. Kelly

2008-01-01

A blood-brain barrier (BBB) model composed of porcine brain capillary endothelial cells (BCEC) was exposed to a moderately excessive zinc environment (50 µmol Zn/L) in cell culture and longitudinal measurements were made of zinc transport kinetics, ZnT-1 (SLC30A1) expression, and changes in the protein concentration of metallothionein (MT), ZnT-1, ZnT-2 (SLC30A2), and Zip1 (SLC39A1). Zinc release by cells of the BBB model was significantly increased after 12–24 h of exposure, but decreased back to control levels after 48–96 h, as indicated by transport across the BBB from both the ablumenal (brain) and lumenal (blood) directions. Expression of ZnT-1, the zinc export protein, increased 169% within 12 h, but was no longer different from controls after 24 h. Likewise, ZnT-1 protein content increased transiently after 12 h of exposure but returned to control levels by 24 h. Capacity for zinc uptake and retention increased from both the lumenal and ablumenal directions within 12–24 h of exposure and remained elevated. MT and ZnT-2 were elevated within 12 h and remained elevated throughout the study. Zip1 was unchanged by the treatment. The BBB’s response to a moderately high zinc environment was dynamic and involved multiple mechanisms. The initial response was to increase the cell’s capacity to sequester zinc with additional MT and increase zinc export with the ZnT-1 protein. But, the longer term strategy involved increasing ZnT-2 transporters, presumably to sequester zinc into intracellular vesicles as a mechanism to protect the brain and maintain brain zinc homeostasis. PMID:18061429

Brain aging and neurodegeneration: from a mitochondrial point of view.

PubMed

Grimm, Amandine; Eckert, Anne

2017-11-01

Aging is defined as a progressive time-related accumulation of changes responsible for or at least involved in the increased susceptibility to disease and death. The brain seems to be particularly sensitive to the aging process since the appearance of neurodegenerative diseases, including Alzheimer's disease, is exponential with the increasing age. Mitochondria were placed at the center of the 'free-radical theory of aging', because these paramount organelles are not only the main producers of energy in the cells, but also to main source of reactive oxygen species. Thus, in this review, we aim to look at brain aging processes from a mitochondrial point of view by asking: (i) What happens to brain mitochondrial bioenergetics and dynamics during aging? (ii) Why is the brain so sensitive to the age-related mitochondrial impairments? (iii) Is there a sex difference in the age-induced mitochondrial dysfunction? Understanding mitochondrial physiology in the context of brain aging may help identify therapeutic targets against neurodegeneration. This article is part of a series "Beyond Amyloid". © 2017 The Authors. Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of International Society for Neurochemistry.

Hierarchies in light sensing and dynamic interactions between ocular and extraocular sensory networks in a flatworm

PubMed Central

Shettigar, Nishan; Joshi, Asawari; Dalmeida, Rimple; Gopalkrishna, Rohini; Chakravarthy, Anirudh; Patnaik, Siddharth; Mathew, Manoj; Palakodeti, Dasaradhi; Gulyani, Akash

2017-01-01

Light sensing has independently evolved multiple times under diverse selective pressures but has been examined only in a handful among the millions of light-responsive organisms. Unsurprisingly, mechanistic insights into how differential light processing can cause distinct behavioral outputs are limited. We show how an organism can achieve complex light processing with a simple “eye” while also having independent but mutually interacting light sensing networks. Although planarian flatworms lack wavelength-specific eye photoreceptors, a 25 nm change in light wavelength is sufficient to completely switch their phototactic behavior. Quantitative photoassays, eye-brain confocal imaging, and RNA interference/knockdown studies reveal that flatworms are able to compare small differences in the amounts of light absorbed at the eyes through a single eye opsin and convert them into binary behavioral outputs. Because planarians can fully regenerate, eye-brain injury-regeneration studies showed that this acute light intensity sensing and processing are layered on simple light detection. Unlike intact worms, partially regenerated animals with eyes can sense light but cannot sense finer gradients. Planarians also show a “reflex-like,” eye-independent (extraocular/whole-body) response to low ultraviolet A light, apart from the “processive” eye-brain–mediated (ocular) response. Competition experiments between ocular and extraocular sensory systems reveal dynamic interchanging hierarchies. In intact worms, cerebral ocular response can override the reflex-like extraocular response. However, injury-regeneration again offers a time window wherein both responses coexist, but the dominance of the ocular response is reversed. Overall, we demonstrate acute light intensity–based behavioral switching and two evolutionarily distinct but interacting light sensing networks in a regenerating organism. PMID:28782018

From naturalistic neuroscience to modeling radical embodiment with narrative enactive systems

PubMed Central

Tikka, Pia; Kaipainen, Mauri Ylermi

2014-01-01

Mainstream cognitive neuroscience has begun to accept the idea of embodied mind, which assumes that the human mind is fundamentally constituted by the dynamical interactions of the brain, body, and the environment. In today’s paradigm of naturalistic neurosciences, subjects are exposed to rich contexts, such as video sequences or entire films, under relatively controlled conditions, against which researchers can interpret changes in neural responses within a time window. However, from the point of view of radical embodied cognitive neuroscience, the increasing complexity alone will not suffice as the explanatory apparatus for dynamical embodiment and situatedness of the mind. We suggest that narrative enactive systems with dynamically adaptive content as stimuli, may serve better to account for the embodied mind engaged with the surrounding world. Among the ensuing challenges for neuroimaging studies is how to interpret brain data against broad temporal contexts of previous experiences that condition the unfolding experience of nowness. We propose means to tackle this issue, as well as ways to limit the exponentially growing combinatoria of narrative paths to a controllable number. PMID:25339890

From embodied mind to embodied robotics: humanities and system theoretical aspects.

PubMed

Mainzer, Klaus

2009-01-01

After an introduction (1) the article analyzes the evolution of the embodied mind (2), the innovation of embodied robotics (3), and finally discusses conclusions of embodied robotics for human responsibility (4). Considering the evolution of the embodied mind (2), we start with an introduction of complex systems and nonlinear dynamics (2.1), apply this approach to neural self-organization (2.2), distinguish degrees of complexity of the brain (2.3), explain the emergence of cognitive states by complex systems dynamics (2.4), and discuss criteria for modeling the brain as complex nonlinear system (2.5). The innovation of embodied robotics (3) is a challenge of future technology. We start with the distinction of symbolic and embodied AI (3.1) and explain embodied robots as dynamical systems (3.2). Self-organization needs self-control of technical systems (3.3). Cellular neural networks (CNN) are an example of self-organizing technical systems offering new avenues for neurobionics (3.4). In general, technical neural networks support different kinds of learning robots (3.5). Finally, embodied robotics aim at the development of cognitive and conscious robots (3.6).

Dynamic causal modelling: a critical review of the biophysical and statistical foundations.

PubMed

Daunizeau, J; David, O; Stephan, K E

2011-09-15

The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Infants and adults have similar regional functional brain organization for the perception of emotions.

PubMed

Rotem-Kohavi, N; Oberlander, T F; Virji-Babul, N

2017-05-22

An infant's ability to perceive emotional facial expressions is critical for developing social skills. Infants are tuned to faces from early in life, however the functional organization of the brain that supports the processing of emotional faces in infants is still not well understood. We recorded electroencephalography (EEG) brain responses in 8-10 month old infants and adults and applied graph theory analysis on the functional connections to compare the network organization at the global and the regional levels underlying the perception of negative and positive dynamic facial expressions (happiness and sadness). We first show that processing of dynamic emotional faces occurs across multiple brain regions in both infants and adults. Across all brain regions, at the global level, network density was higher in the infant group in comparison with adults suggesting that the overall brain organization in relation to emotion perception is still immature in infancy. In contrast, at the regional levels, the functional characteristics of the frontal and parietal nodes were similar between infants and adults, suggesting that functional regional specialization for emotion perception is already established at this age. In addition, in both groups the occipital, parietal and temporal nodes appear to have the strongest influence on information flow within the network. These results suggest that while the global organization for the emotion perception of sad and happy emotions is still under development, the basic functional network organization at the regional level is already in place early in infancy. Copyright © 2017 Elsevier B.V. All rights reserved.

Diminished neural network dynamics after moderate and severe traumatic brain injury.

PubMed

Gilbert, Nicholas; Bernier, Rachel A; Calhoun, Vincent D; Brenner, Einat; Grossner, Emily; Rajtmajer, Sarah M; Hillary, Frank G

2018-01-01

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain's subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network "states" that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics.

Experiential, Autonomic, and Neural Responses During Threat Anticipation Vary as a Function of Threat Intensity and Neuroticism

PubMed Central

Drabant, Emily M; Kuo, Janice R; Ramel, Wiveka; Blechert, Jens; Edge, Michael D; Cooper, Jeff R; Goldin, Philippe R; Hariri, Ahmad R; Gross, James J

2011-01-01

Anticipatory emotional responses play a crucial role in preparing individuals for impending challenges. They do this by triggering a coordinated set of changes in behavioral, autonomic, and neural response systems. In the present study, we examined the biobehavioral impact of varying levels of anticipatory anxiety, using a shock anticipation task in which unpredictable electric shocks were threatened and delivered to the wrist at variable intervals and intensities (safe, medium, strong). This permitted investigation of a dynamic range of anticipatory anxiety responses. In two studies, 95 and 51 healthy female participants, respectively, underwent this shock anticipation task while providing continuous ratings of anxiety experience and electrodermal responding (Study 1) and during fMRI BOLD neuroimaging (Study 2). Results indicated a step-wise pattern of responding in anxiety experience and electrodermal responses. Several brain regions showed robust responses to shock anticipation relative to safe trials, including the hypothalamus, periaqueductal gray, caudate, precentral gyrus, thalamus, insula, ventrolateral PFC, dorsomedial PFC, and ACC. A subset of these regions demonstrated a linear pattern of increased responding from safe to medium to strong trials, including the bilateral insula, ACC, and inferior frontal gyrus. These responses were modulated by individual differences in neuroticism, such that those high in neuroticism showed exaggerated anxiety experience across the entire task, and reduced brain activation from medium to strong trials in a subset of brain regions. These findings suggest that individual differences in neuroticism may influence sensitivity to anticipatory threat and provide new insights into the mechanism through which neuroticism may confer risk for developing anxiety disorders via dysregulated anticipatory responses. PMID:21093595

Hyper-resting brain entropy within chronic smokers and its moderation by Sex

PubMed Central

Li, Zhengjun; Fang, Zhuo; Hager, Nathan; Rao, Hengyi; Wang, Ze

2016-01-01

Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking. PMID:27377552

Intraoperative video-rate hemodynamic response assessment in human cortex using snapshot hyperspectral optical imaging

PubMed Central

Pichette, Julien; Laurence, Audrey; Angulo, Leticia; Lesage, Frederic; Bouthillier, Alain; Nguyen, Dang Khoa; Leblond, Frederic

2016-01-01

Abstract. Using light, we are able to visualize the hemodynamic behavior of the brain to better understand neurovascular coupling and cerebral metabolism. In vivo optical imaging of tissue using endogenous chromophores necessitates spectroscopic detection to ensure molecular specificity as well as sufficiently high imaging speed and signal-to-noise ratio, to allow dynamic physiological changes to be captured, isolated, and used as surrogate of pathophysiological processes. An optical imaging system is introduced using a 16-bands on-chip hyperspectral camera. Using this system, we show that up to three dyes can be imaged and quantified in a tissue phantom at video-rate through the optics of a surgical microscope. In vivo human patient data are presented demonstrating brain hemodynamic response can be measured intraoperatively with molecular specificity at high speed. PMID:27752519

Dynamic neurotransmitter interactions measured with PET

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

Schiffer, W.K.; Dewey, S.L.

2001-04-02

Positron emission tomography (PET) has become a valuable interdisciplinary tool for understanding physiological, biochemical and pharmacological functions at a molecular level in living humans, whether in a healthy or diseased state. The utility of tracing chemical activity through the body transcends the fields of cardiology, oncology, neurology and psychiatry. In this, PET techniques span radiochemistry and radiopharmaceutical development to instrumentation, image analysis, anatomy and modeling. PET has made substantial contributions in each of these fields by providing a,venue for mapping dynamic functions of healthy and unhealthy human anatomy. As diverse as the disciplines it bridges, PET has provided insight intomore » an equally significant variety of psychiatric disorders. Using the unique quantitative ability of PET, researchers are now better able to non-invasively characterize normally occurring neurotransmitter interactions in the brain. With the knowledge that these interactions provide the fundamental basis for brain response, many investigators have recently focused their efforts on an examination of the communication between these chemicals in both healthy volunteers and individuals suffering from diseases classically defined as neurotransmitter specific in nature. In addition, PET can measure the biochemical dynamics of acute and sustained drug abuse. Thus, PET studies of neurotransmitter interactions enable investigators to describe a multitude of specific functional interactions in the human brain. This information can then be applied to understanding side effects that occur in response to acute and chronic drug therapy, and to designing new drugs that target multiple systems as opposed to single receptor types. Knowledge derived from PET studies can be applied to drug discovery, research and development (for review, see (Fowler et al., 1999) and (Burns et al., 1999)). Here, we will cover the most substantial contributions of PET to understanding biologically distinct neurochemical systems that interact to produce a variety of behaviors and disorders. Neurotransmitters are neither static nor isolated in their distribution. In fact, it is through interactions with other neurochemically distinct systems that the central nervous system (CNS) performs its vital role in sustaining life. Exclusive quantitative capabilities intrinsic to PET make this technology a suitable experimental tool to measure not only the regional distribution of specific receptors and their subtypes, but also the dynamic properties of neuroreceptors and their inherent influence on related neurotransmitter pathways. The ability to investigate dynamic properties in a non-invasive and reproducible manner provides a powerful tool that can extend our current knowledge of these interactions. Coupled with innovative paradigms including pharmacologic manipulations, physiologic models and reconstruction theories, knowledge derived from PET studies can greatly advance our understanding of normal and abnormal brain function.« less

Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.

PubMed

Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel

2018-06-01

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

Nonequilibrium landscape theory of neural networks.

PubMed

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-11-05

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

Nonequilibrium landscape theory of neural networks

PubMed Central

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-01-01

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis

NASA Astrophysics Data System (ADS)

Laksari, Kaveh; Kurt, Mehmet; Babaee, Hessam; Kleiven, Svein; Camarillo, David

2018-03-01

Although concussion is one of the greatest health challenges today, our physical understanding of the cause of injury is limited. In this Letter, we simulated football head impacts in a finite element model and extracted the most dominant modal behavior of the brain's deformation. We showed that the brain's deformation is most sensitive in low frequency regimes close to 30 Hz, and discovered that for most subconcussive head impacts, the dynamics of brain deformation is dominated by a single global mode. In this Letter, we show the existence of localized modes and multimodal behavior in the brain as a hyperviscoelastic medium. This dynamical phenomenon leads to strain concentration patterns, particularly in deep brain regions, which is consistent with reported concussion pathology.

A Computational Model of Major Depression: the Role of Glutamate Dysfunction on Cingulo-Frontal Network Dynamics

PubMed Central

Ramirez-Mahaluf, Juan P.; Roxin, Alexander; Mayberg, Helen S.; Compte, Albert

2017-01-01

Abstract Major depression disease (MDD) is associated with the dysfunction of multinode brain networks. However, converging evidence implicates the reciprocal interaction between midline limbic regions (typified by the ventral anterior cingulate cortex, vACC) and the dorso-lateral prefrontal cortex (dlPFC), reflecting interactions between emotions and cognition. Furthermore, growing evidence suggests a role for abnormal glutamate metabolism in the vACC, while serotonergic treatments (selective serotonin reuptake inhibitor, SSRI) effective for many patients implicate the serotonin system. Currently, no mechanistic framework describes how network dynamics, glutamate, and serotonin interact to explain MDD symptoms and treatments. Here, we built a biophysical computational model of 2 areas (vACC and dlPFC) that can switch between emotional and cognitive processing. MDD networks were simulated by slowing glutamate decay in vACC and demonstrated sustained vACC activation. This hyperactivity was not suppressed by concurrent dlPFC activation and interfered with expected dlPFC responses to cognitive signals, mimicking cognitive dysfunction seen in MDD. Simulation of clinical treatments (SSRI or deep brain stimulation) counteracted this aberrant vACC activity. Theta and beta/gamma oscillations correlated with network function, representing markers of switch-like operation in the network. The model shows how glutamate dysregulation can cause aberrant brain dynamics, respond to treatments, and be reflected in EEG rhythms as biomarkers of MDD. PMID:26514163

Responsibility modulates pain-matrix activation elicited by the expressions of others in pain

PubMed Central

Cui, Fang; Abdelgabar, Abdel-Rahman; Keysers, Christian; Gazzola, Valeria

2015-01-01

Here we examine whether brain responses to dynamic facial expressions of pain are influenced by our responsibility for the observed pain. Participants played a flanker task with a confederate. Whenever either erred, the confederate was seen to receive a noxious shock. Using functional magnetic resonance imaging, we found that regions of the functionally localized pain-matrix of the participants (the anterior insula in particular) were activated most strongly when seeing the confederate receive a noxious shock when only the participant had erred (and hence had full responsibility). When both or only the confederate had erred (i.e. participant's shared or no responsibility), significantly weaker vicarious pain-matrix activations were measured. PMID:25800210

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

PubMed

Cheng, Lin; Zhu, Yang; Sun, Junfeng; Deng, Lifu; He, Naying; Yang, Yang; Ling, Huawei; Ayaz, Hasan; Fu, Yi; Tong, Shanbao

2018-01-25

Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique insights in understanding how the brain reorganizes itself during rest and task states, and the ways in which the brain adaptively responds to the cognitive requirements of tasks.

Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions

NASA Astrophysics Data System (ADS)

Lin, Aijing; Liu, Kang K. L.; Bartsch, Ronny P.; Ivanov, Plamen Ch.

2016-05-01

Within the framework of `Network Physiology', we ask a fundamental question of how modulations in cardiac dynamics emerge from networked brain-heart interactions. We propose a generalized time-delay approach to identify and quantify dynamical interactions between physiologically relevant brain rhythms and the heart rate. We perform empirical analysis of synchronized continuous EEG and ECG recordings from 34 healthy subjects during night-time sleep. For each pair of brain rhythm and heart interaction, we construct a delay-correlation landscape (DCL) that characterizes how individual brain rhythms are coupled to the heart rate, and how modulations in brain and cardiac dynamics are coordinated in time. We uncover characteristic time delays and an ensemble of specific profiles for the probability distribution of time delays that underly brain-heart interactions. These profiles are consistently observed in all subjects, indicating a universal pattern. Tracking the evolution of DCL across different sleep stages, we find that the ensemble of time-delay profiles changes from one physiologic state to another, indicating a strong association with physiologic state and function. The reported observations provide new insights on neurophysiological regulation of cardiac dynamics, with potential for broad clinical applications. The presented approach allows one to simultaneously capture key elements of dynamic interactions, including characteristic time delays and their time evolution, and can be applied to a range of coupled dynamical systems.

Dexamethasone increases production of C-type natriuretic peptide in the sheep brain.

PubMed

Wilson, Michele O; McNeill, Bryony A; Barrell, Graham K; Prickett, Timothy C R; Espiner, Eric A

2017-10-01

Although C-type natriuretic peptide (CNP) has high abundance in brain tissues and cerebrospinal fluid (CSF), the source and possible factors regulating its secretion within the central nervous system (CNS) are unknown. Here we report the dynamic effects of a single IV bolus of dexamethasone or saline solution on plasma, CSF, CNS and pituitary tissue content of CNP products in adult sheep, along with changes in CNP gene expression in selected tissues. Both CNP and NTproCNP (the amino-terminal product of proCNP) in plasma and CSF showed dose-responsive increases lasting 12-16 h after dexamethasone, whereas other natriuretic peptides were unaffected. CNS tissue concentrations of CNP and NTproCNP were increased by dexamethasone in all of the 12 regions examined. Abundance was highest in limbic tissues, pons and medulla oblongata. Relative to controls, CNP gene expression ( NPPC ) was upregulated by dexamethasone in 5 of 7 brain tissues examined. Patterns of responses differed in pituitary tissue. Whereas the abundance of CNP in both lobes of the pituitary gland greatly exceeded that of brain tissues, neither CNP nor NTproCNP concentration was affected by dexamethasone, despite an increase in NPPC expression. This is the first report of enhanced production and secretion of CNP in brain tissues in response to a corticosteroid. Activation of CNP secretion within CNS tissues by dexamethasone, not exhibited by other natriuretic peptides, suggests an important role for CNP in settings of acute stress. Differential findings in pituitary tissues likely relate to altered processing of proCNP storage and secretion. © 2017 Society for Endocrinology.

Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

PubMed

Başar, Erol

2005-01-01

According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

The emergence of mind and emotion in the evolution of neocortex.

PubMed

Freeman, Walter J

2011-01-01

The most deeply transformative concept for the growth of 21st Century psychiatry is the constellation of the chaotic dynamics of the brain. Brains are no longer seen as rational systems that are plagued with emotional disorders reflecting primitives inherited from our animal ancestors. Brains are dynamical systems that continually create patterns by acting intentionally into the environment and shaping themselves in accord with the sensory consequences of their intended actions. Emotions are now seen not as reversions to animal behaviors but as the sources of force and energy that brains require for the actions they take to understand the world and themselves. Humans are unique in experiencing consciousness of their own actions, which they experience as conscience: guilt, shame, pride and joy. Chaotic brain dynamics strives always for unity and harmony, but as a necessary condition for adaptation to a changing world, it repeatedly lapses into disorder. The successes are seen in the normal unity of consciousness; the failures are seen in the disorders that we rightly label the schizophrenias and the less severe character disorders. The foundation for healthy unity is revealed by studies in the evolution of brains, in particular the way in which neocortex of mammals emerged from the primitive allocortex of reptiles. The amazing facts of brain dynamics are now falling into several places. The power-law connectivity of cortex supports the scale-free dynamics of the global workspace in brains ranging from mouse to whale. That dynamics in humans holds the secrets of speech and symbol utilization. By recursive interactions in vast areas of human neocortex the scale-free connectivity supports our unified consciousness. Here in this dynamics are to be sought the keys to understanding and treating the disorders that uniquely plague the human mind.

The neural basis of responsive caregiving behaviour: Investigating temporal dynamics within the parental brain.

PubMed

Young, Katherine S; Parsons, Christine E; Stein, Alan; Vuust, Peter; Craske, Michelle G; Kringelbach, Morten L

2017-05-15

Whether it is the sound of a distressed cry or the image of a cute face, infants capture our attention. Parents and other adults alike are drawn into interactions to engage in play, nurturance and provide care. Responsive caregiving behaviour is a key feature of the parent-infant relationship, forming the foundation upon which attachment is built. Infant cues are considered to be 'innate releasers' or 'motivational entities' eliciting responses in nearby adults (Lorenz 1943; Murray, 1979) [42,43]. Through the advent of modern neuroimaging, we are beginning to understand the initiation of this motivational state at the neurobiological level. In this review, we first describe a current model of the 'parental brain', based on functional MRI studies assessing neural responses to infant cues. Next, we discuss recent findings from temporally sensitive techniques (magneto- and electroencephalography) that illuminate the temporal dynamics of this neural network. We focus on converging evidence highlighting a specific role for the orbitofrontal cortex in supporting rapid orienting responses to infant cues. In addition, we consider to what extent these neural processes are tied to parenthood, or whether they might be present universally in all adults. We highlight important avenues for future research, including utilizing multiple levels of analysis for a comprehensive understanding of adaptive caregiving behaviour. Finally, we discuss how this research can help us understand disrupted parent-infant relationships, such as in situations where parents' contingent responding to infant cues is disrupted; for example, in parental depression or anxiety where cognitive attentional processes are disrupted. Copyright © 2016 Elsevier B.V. All rights reserved.

GSK-3 mediates the okadaic acid-induced modification of collapsin response mediator protein-2 in human SK-N-SH neuroblastoma cells.

PubMed

Ni, Mei-Hui; Wu, Chih-Ching; Chan, Wen-Hsiung; Chien, Kun-Yi; Yu, Jau-Song

2008-04-15

Collapsin response mediator protein-2 (CRMP-2), a phosphoprotein involved in axonal outgrowth and microtubule dynamics, is aberrantly phosphorylated in Alzheimer's disease (AD) brain. Alteration of glycogen synthase kinase-3 (GSK-3) activity is associated with the pathogenesis of AD. Here, we show that CRMP-2 is one of the major substrates for GSK-3 in pig brain extracts. Both GSK-3alpha and 3beta phosphorylate purified pig brain CRMP-2 and significantly alter its mobility in SDS-gels, resembling the CRMP-2 modification observed in AD brain. Interestingly, this modification can be detected in SK-N-SH neuroblastoma cells treated with a phosphatase inhibitor, okadaic acid (OA), and GSK-3 inhibitors completely block this OA-induced event. Knockdown of both GSK-3alpha and 3beta, but not either kinase alone, impairs OA-induced modification of CRMP-2. Mutation of Ser-518 or Ser-522 of CRMP-2, which are highly phosphorylated in AD brain, to Ala blocks the OA-induced modification of CRMP-2 in SK-N-SH cells. Ser-522 prephosphorylated by Cdk5 is required for subsequent GSK-3alpha-mediated phosphorylation of CRMP-2 in vitro. Collectively, our results demonstrate for the first time that OA can induce phosphorylation of CRMP-2 in SK-N-SH cells at sites aberrantly phosphorylated in AD brain, and both GSK-3alpha and 3beta and Ser-522 kinase(s) are involved in this process.

Continuous blood pressure recordings simultaneously with functional brain imaging: studies of the glymphatic system

NASA Astrophysics Data System (ADS)

Zienkiewicz, Aleksandra; Huotari, Niko; Raitamaa, Lauri; Raatikainen, Ville; Ferdinando, Hany; Vihriälä, Erkki; Korhonen, Vesa; Myllylä, Teemu; Kiviniemi, Vesa

2017-03-01

The lymph system is responsible for cleaning the tissues of metabolic waste products, soluble proteins and other harmful fluids etc. Lymph flow in the body is driven by body movements and muscle contractions. Moreover, it is indirectly dependent on the cardiovascular system, where the heart beat and blood pressure maintain force of pressure in lymphatic channels. Over the last few years, studies revealed that the brain contains the so-called glymphatic system, which is the counterpart of the systemic lymphatic system in the brain. Similarly, the flow in the glymphatic system is assumed to be mostly driven by physiological pulsations such as cardiovascular pulses. Thus, continuous measurement of blood pressure and heart function simultaneously with functional brain imaging is of great interest, particularly in studies of the glymphatic system. We present our MRI compatible optics based sensing system for continuous blood pressure measurement and show our current results on the effects of blood pressure variations on cerebral brain dynamics, with a focus on the glymphatic system. Blood pressure was measured simultaneously with near-infrared spectroscopy (NIRS) combined with an ultrafast functional brain imaging (fMRI) sequence magnetic resonance encephalography (MREG, 3D brain 10 Hz sampling rate).

Predictive models for pressure-driven fluid infusions into brain parenchyma

NASA Astrophysics Data System (ADS)

Raghavan, Raghu; Brady, Martin

2011-10-01

Direct infusions into brain parenchyma of biological therapeutics for serious brain diseases have been, and are being, considered. However, individual brains, as well as distinct cytoarchitectural regions within brains, vary in their response to fluid flow and pressure. Further, the tissue responds dynamically to these stimuli, requiring a nonlinear treatment of equations that would describe fluid flow and drug transport in brain. We here report in detail on an individual-specific model and a comparison of its prediction with simulations for living porcine brains. Two critical features we introduced into our model—absent from previous ones, but requirements for any useful simulation—are the infusion-induced interstitial expansion and the backflow. These are significant determinants of the flow. Another feature of our treatment is the use of cross-property relations to obtain individual-specific parameters that are coefficients in the equations. The quantitative results are at least encouraging, showing a high fraction of overlap between the computed and measured volumes of distribution of a tracer molecule and are potentially clinically useful. Several improvements are called for; principally a treatment of the interstitial expansion more fundamentally based on poroelasticity and a better delineation of the diffusion tensor of a particle confined to the interstitial spaces.

In vitro models and systems for evaluating the dynamics of drug delivery to the healthy and diseased brain.

PubMed

Modarres, Hassan Pezeshgi; Janmaleki, Mohsen; Novin, Mana; Saliba, John; El-Hajj, Fatima; RezayatiCharan, Mahdi; Seyfoori, Amir; Sadabadi, Hamid; Vandal, Milène; Nguyen, Minh Dang; Hasan, Anwarul; Sanati-Nezhad, Amir

2018-03-10

The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis and transport of drugs to the brain. The conventional animal and Transwell BBB models along with emerging microfluidic-based BBB-on-chip systems have provided fundamental functionalities of the BBB and facilitated the testing of drug delivery to the brain tissue. However, developing biomimetic and predictive BBB models capable of reasonably mimicking essential characteristics of the BBB functions is still a challenge. In addition, detailed analysis of the dynamics of drug delivery to the healthy or diseased brain requires not only biomimetic BBB tissue models but also new systems capable of monitoring the BBB microenvironment and dynamics of barrier function and delivery mechanisms. This review provides a comprehensive overview of recent advances in microengineering of BBB models with different functional complexity and mimicking capability of healthy and diseased states. It also discusses new technologies that can make the next generation of biomimetic human BBBs containing integrated biosensors for real-time monitoring the tissue microenvironment and barrier function and correlating it with the dynamics of drug delivery. Such integrated system addresses important brain drug delivery questions related to the treatment of brain diseases. We further discuss how the combination of in vitro BBB systems, computational models and nanotechnology supports for characterization of the dynamics of drug delivery to the brain. Copyright © 2018 Elsevier B.V. All rights reserved.

Age-related changes in the ease of dynamical transitions in human brain activity.

PubMed

Ezaki, Takahiro; Sakaki, Michiko; Watanabe, Takamitsu; Masuda, Naoki

2018-06-01

Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks. © 2018 Wiley Periodicals, Inc.

Angular default mode network connectivity across working memory load.

PubMed

Vatansever, D; Manktelow, A E; Sahakian, B J; Menon, D K; Stamatakis, E A

2017-01-01

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Multiscale neural connectivity during human sensory processing in the brain

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir A.; Runnova, Anastasia E.; Frolov, Nikita S.; Makarov, Vladimir V.; Nedaivozov, Vladimir; Koronovskii, Alexey A.; Pisarchik, Alexander; Hramov, Alexander E.

2018-05-01

Stimulus-related brain activity is considered using wavelet-based analysis of neural interactions between occipital and parietal brain areas in alpha (8-12 Hz) and beta (15-30 Hz) frequency bands. We show that human sensory processing related to the visual stimuli perception induces brain response resulted in different ways of parieto-occipital interactions in these bands. In the alpha frequency band the parieto-occipital neuronal network is characterized by homogeneous increase of the interaction between all interconnected areas both within occipital and parietal lobes and between them. In the beta frequency band the occipital lobe starts to play a leading role in the dynamics of the occipital-parietal network: The perception of visual stimuli excites the visual center in the occipital area and then, due to the increase of parieto-occipital interactions, such excitation is transferred to the parietal area, where the attentional center takes place. In the case when stimuli are characterized by a high degree of ambiguity, we find greater increase of the interaction between interconnected areas in the parietal lobe due to the increase of human attention. Based on revealed mechanisms, we describe the complex response of the parieto-occipital brain neuronal network during the perception and primary processing of the visual stimuli. The results can serve as an essential complement to the existing theory of neural aspects of visual stimuli processing.

Neural markers of social and monetary rewards in children with Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder

PubMed Central

Gonzalez-Gadea, Maria Luz; Sigman, Mariano; Rattazzi, Alexia; Lavin, Claudio; Rivera-Rei, Alvaro; Marino, Julian; Manes, Facundo; Ibanez, Agustin

2016-01-01

Recent theories of decision making propose a shared value-related brain mechanism for encoding monetary and social rewards. We tested this model in children with Attention-Deficit/Hyperactivity Disorder (ADHD), children with Autism Spectrum Disorder (ASD) and control children. We monitored participants’ brain dynamics using high density-electroencephalography while they played a monetary and social reward tasks. Control children exhibited a feedback Error-Related Negativity (fERN) modulation and Anterior Cingulate Cortex (ACC) source activation during both tasks. Remarkably, although cooperation resulted in greater losses for the participants, the betrayal options generated greater fERN responses. ADHD subjects exhibited an absence of fERN modulation and reduced ACC activation during both tasks. ASD subjects exhibited normal fERN modulation during monetary choices and inverted fERN/ACC responses in social options than did controls. These results suggest that in neurotypicals, monetary losses and observed disloyal social decisions induced similar activity in the brain value system. In ADHD children, difficulties in reward processing affected early brain signatures of monetary and social decisions. Conversely, ASD children showed intact neural markers of value-related monetary mechanisms, but no brain modulation by prosociality in the social task. These results offer insight into the typical and atypical developments of neural correlates of monetary and social reward processing. PMID:27464551

Prototype of an opto-capacitive probe for non-invasive sensing cerebrospinal fluid circulation

NASA Astrophysics Data System (ADS)

Myllylä, Teemu; Vihriälä, Erkki; Pedone, Matteo; Korhonen, Vesa; Surazynski, Lukasz; Wróbel, Maciej; Zienkiewicz, Aleksandra; Hakala, Jaakko; Sorvoja, Hannu; Lauri, Janne; Fabritius, Tapio; Jedrzejewska-Szczerska, Małgorzata; Kiviniemi, Vesa; Meglinski, Igor

2017-03-01

In brain studies, the function of the cerebrospinal fluid (CSF) awakes growing interest, particularly related to studies of the glymphatic system in the brain, which is connected with the complex system of lymphatic vessels responsible for cleaning the tissues. The CSF is a clear, colourless liquid including water (H2O) approximately with a concentration of 99 %. In addition, it contains electrolytes, amino acids, glucose, and other small molecules found in plasma. The CSF acts as a cushion behind the skull, providing basic mechanical as well as immunological protection to the brain. Disturbances of the CSF circulation have been linked to several brain related medical disorders, such as dementia. Our goal is to develop an in vivo method for the non-invasive measurement of cerebral blood flow and CSF circulation by exploiting optical and capacitive sensing techniques simultaneously. We introduce a prototype of a wearable probe that is aimed to be used for long-term brain monitoring purposes, especially focusing on studies of the glymphatic system. In this method, changes in cerebral blood flow, particularly oxy- and deoxyhaemoglobin, are measured simultaneously and analysed with the response gathered by the capacitive sensor in order to distinct the dynamics of the CSF circulation behind the skull. Presented prototype probe is tested by measuring liquid flows inside phantoms mimicking the CSF circulation.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Analyzing the dynamics of brain circuits with temperature: design and implementation of a miniature thermoelectric device.

PubMed

Aronov, Dmitriy; Fee, Michale S

2011-04-15

Traditional lesion or inactivation methods are useful for determining if a given brain area is involved in the generation of a behavior, but not for determining if circuit dynamics in that area control the timing of the behavior. In contrast, localized mild cooling or heating of a brain area alters the speed of neuronal and circuit dynamics and can reveal the role of that area in the control of timing. It has been shown that miniaturized solid-state heat pumps based on the Peltier effect can be useful for analyzing brain dynamics in small freely behaving animals (Long and Fee, 2008). Here we present a theoretical analysis of these devices and a procedure for optimizing their design. We describe the construction and implementation of one device for cooling surface brain areas, such as cortex, and another device for cooling deep brain regions. We also present measurements of the magnitude and localization of the brain temperature changes produced by these two devices. Copyright © 2011 Elsevier B.V. All rights reserved.

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

PubMed Central

Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

2013-01-01

Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

Using the Detectability Index to Predict P300 Speller Performance

PubMed Central

Mainsah, B.O.; Collins, L.M.; Throckmorton, C.S.

2017-01-01

Objective The P300 speller is a popular brain-computer interface (BCI) system that has been investigated as a potential communication alternative for individuals with severe neuromuscular limitations. To achieve acceptable accuracy levels for communication, the system requires repeated data measurements in a given signal condition to enhance the signal-to-noise ratio of elicited brain responses. These elicited brain responses, which are used as control signals, are embedded in noisy electroencephalography (EEG) data. The discriminability between target and non-target EEG responses defines a user’s performance with the system. A previous P300 speller model has been proposed to estimate system accuracy given a certain amount of data collection. However, the approach was limited to a static stopping algorithm, i.e. averaging over a fixed number of measurements, and the row-column paradigm. A generalized method that is also applicable to dynamic stopping algorithms and other stimulus paradigms is desirable. Approach We developed a new probabilistic model-based approach to predicting BCI performance, where performance functions can be derived analytically or via Monte Carlo methods. Within this framework, we introduce a new model for the P300 speller with the Bayesian dynamic stopping (DS) algorithm, by simplifying a multi-hypothesis to a binary hypothesis problem using the likelihood ratio test. Under a normality assumption, the performance functions for the Bayesian algorithm can be parameterized with the detectability index, a measure which quantifies the discriminability between target and non-target EEG responses. Main results Simulations with synthetic and empirical data provided initial verification of the proposed method of estimating performance with Bayesian DS using the detectability index. Analysis of results from previous online studies validated the proposed method. Significance The proposed method could serve as a useful tool to initially asses BCI performance without extensive online testing, in order to estimate the amount of data required to achieve a desired accuracy level. PMID:27705956

Trajectories and phenotypes with estrogen exposures across the lifespan: What does Goldilocks have to do with it?

PubMed Central

Koebele, Stephanie V.; Bimonte-Nelson, Heather A.

2015-01-01

Estrogens impact the organization and activation of the mammalian brain in both sexes, with sex-specific critical windows. Throughout the female lifespan estrogens activate brain substrates previously organized by estrogens, and estrogens can induce non-transient brain and behavior changes into adulthood. Therefore, from early life through the transition to reproductive senescence and beyond, estrogens are potent modulators of the brain and behavior. Organizational, reorganizational, and activational hormone events likely impact the trajectory of brain profiles during aging. A “brain profile,” or quantitative brain measurement for research purposes, is typically a snapshot in time, but in life a brain profile is anything but static – it is in flux, variable, and dynamic. Akin to this, the only thing continuous and consistent about hormone exposures across a female's lifespan is that they are noncontinuous and inconsistent, building and rebuilding on past exposures to create a present brain and behavioral landscape. Thus, hormone variation is especially rich in females, and is likely the destiny for maximal responsiveness in the female brain. The magnitude and direction of estrogenic effects on the brain and its functions depend on a myriad of factors; a “Goldilocks” phenomenon exists for estrogens, whereby if the timing, dose, and regimen for an individual are just right, markedly efficacious effects present. Data indicate that exogenously-administered estrogens can bestow beneficial cognitive effects in some circumstances, especially when initiated in a window of opportunity such as the menopause transition. Could it be that the age-related reduction in efficacy of estrogens reflects the closure of a late-in-life critical window occurring around the menopause transition? Information from classic and contemporary works studying organizational/activational estrogen actions, in combination with acknowledging the tendency for maximal responsiveness to cyclicity, will elucidate ways to extend sensitivity and efficacy into post-menopause. PMID:26122297

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

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

The multi-modal responses of a physical head model subjected to various blast exposure conditions

NASA Astrophysics Data System (ADS)

Ouellet, S.; Philippens, M.

2018-01-01

The local and global biomechanical response of the body to a blast wave is the first step of a sequence that leads to the development of stresses and strains which can exceed the tolerance of brain tissue. These stresses and strains may then lead to neuro-physical changes in the brain and contribute to initiate a cascade of events leading to injury. The specific biomechanical pathways by which the blast energy is transmitted through the head structure are, however, not clearly understood. Multiple transmission mechanisms have been proposed to explain the generation of brain stresses following the impingement of a blast wave on the head. With the use of a physical head model, the work presented here aims at demonstrating that the proposed transmission mechanisms are not mutually exclusive. They are part of a continuum of head responses where, depending on the exposure conditions, a given mechanism may or may not dominate. This article presents the joint analysis of previous blast test results generated with the brain injury protection evaluation device (BIPED) headform under four significantly different exposure conditions. The focus of the analysis is to demonstrate how the nature of the recorded response is highly dependent on the exposure characteristics and consequently, on the method used to reproduce blast exposure in a laboratory environment. The timing and magnitude of the variations in intra-cranial pressures (ICP) were analysed relative to the external pressure field in order to better understand the wave dynamics occurring within the brain structure of the headform. ICP waveforms were also analysed in terms of their energy spectral density to better identify the energy partitioning between the different modes of response. It is shown that the BIPED response is multi-modal and that the energy partitioning between its different modes of response is greatly influenced by exposure characteristics such as external peak overpressure, impulse, blast wave structure, and direction of propagation. Convincing evidence of stresses generated from local skull deformation is presented along with evidence of stress transmission through relative brain-to-skull motion. These findings suggest that research aimed at defining exposure thresholds should not focus on a single stress transmission mechanism or use experimental designs unrepresentative of realistic blast loading conditions that may favour a given mechanism over another.

Principles of auditory processing differ between sensory and premotor structures of the songbird forebrain

PubMed Central

Vicario, David S.

2017-01-01

Sensory and motor brain structures work in collaboration during perception. To evaluate their respective contributions, the present study recorded neural responses to auditory stimulation at multiple sites simultaneously in both the higher-order auditory area NCM and the premotor area HVC of the songbird brain in awake zebra finches (Taeniopygia guttata). Bird’s own song (BOS) and various conspecific songs (CON) were presented in both blocked and shuffled sequences. Neural responses showed plasticity in the form of stimulus-specific adaptation, with markedly different dynamics between the two structures. In NCM, the response decrease with repetition of each stimulus was gradual and long-lasting and did not differ between the stimuli or the stimulus presentation sequences. In contrast, HVC responses to CON stimuli decreased much more rapidly in the blocked than in the shuffled sequence. Furthermore, this decrease was more transient in HVC than in NCM, as shown by differential dynamics in the shuffled sequence. Responses to BOS in HVC decreased more gradually than to CON stimuli. The quality of neural representations, computed as the mutual information between stimuli and neural activity, was higher in NCM than in HVC. Conversely, internal functional correlations, estimated as the coherence between recording sites, were greater in HVC than in NCM. The cross-coherence between the two structures was weak and limited to low frequencies. These findings suggest that auditory communication signals are processed according to very different but complementary principles in NCM and HVC, a contrast that may inform study of the auditory and motor pathways for human speech processing. NEW & NOTEWORTHY Neural responses to auditory stimulation in sensory area NCM and premotor area HVC of the songbird forebrain show plasticity in the form of stimulus-specific adaptation with markedly different dynamics. These two structures also differ in stimulus representations and internal functional correlations. Accordingly, NCM seems to process the individually specific complex vocalizations of others based on prior familiarity, while HVC responses appear to be modulated by transitions and/or timing in the ongoing sequence of sounds. PMID:28031398

The motivation to control and the origin of mind: exploring the life-mind joint point in the Tree of Knowledge System.

PubMed

Geary, David C

2005-01-01

The evolved function of brain, cognitive, affective, conscious-psychological, and behavioral systems is to enable animals to attempt to gain control of the social (e.g., mates), biological (e.g., prey), and physical (e.g., nesting spots) resources that have tended to covary with survival and reproductive outcomes during the species' evolutionary history. These resources generate information patterns that range from invariant to variant. Invariant information is consistent across generations and within lifetimes (e.g., the prototypical shape of a human face) and is associated with modular brain and cognitive systems that coalesce around the domains of folk psychology, folk biology, and folk physics. The processing of information in these domains is implicit and results in automatic bottom-up behavioral responses. Variant information varies across generations and within lifetimes (e.g., as in social dynamics) and is associated with plastic brain and cognitive systems and explicit, consciously driven top-down behavioral responses. The fundamentals of this motivation-to-control model are outlined and links are made to Henriques' (2004) Tree of Knowledge System and Behavioral Investment Theory.

Disrupted global metastability and static and dynamic brain connectivity across individuals in the Alzheimer’s disease continuum

NASA Astrophysics Data System (ADS)

Córdova-Palomera, Aldo; Kaufmann, Tobias; Persson, Karin; Alnæs, Dag; Doan, Nhat Trung; Moberget, Torgeir; Lund, Martina Jonette; Barca, Maria Lage; Engvig, Andreas; Brækhus, Anne; Engedal, Knut; Andreassen, Ole A.; Selbæk, Geir; Westlye, Lars T.

2017-01-01

As findings on the neuropathological and behavioral components of Alzheimer’s disease (AD) continue to accrue, converging evidence suggests that macroscale brain functional disruptions may mediate their association. Recent developments on theoretical neuroscience indicate that instantaneous patterns of brain connectivity and metastability may be a key mechanism in neural communication underlying cognitive performance. However, the potential significance of these patterns across the AD spectrum remains virtually unexplored. We assessed the clinical sensitivity of static and dynamic functional brain disruptions across the AD spectrum using resting-state fMRI in a sample consisting of AD patients (n = 80) and subjects with either mild (n = 44) or subjective (n = 26) cognitive impairment (MCI, SCI). Spatial maps constituting the nodes in the functional brain network and their associated time-series were estimated using spatial group independent component analysis and dual regression, and whole-brain oscillatory activity was analyzed both globally (metastability) and locally (static and dynamic connectivity). Instantaneous phase metrics showed functional coupling alterations in AD compared to MCI and SCI, both static (putamen, dorsal and default-mode) and dynamic (temporal, frontal-superior and default-mode), along with decreased global metastability. The results suggest that brains of AD patients display altered oscillatory patterns, in agreement with theoretical premises on cognitive dynamics.

Mathematical investigation of IP3-dependent calcium dynamics in astrocytes.

PubMed

Handy, Gregory; Taheri, Marsa; White, John A; Borisyuk, Alla

2017-06-01

We study evoked calcium dynamics in astrocytes, a major cell type in the mammalian brain. Experimental evidence has shown that such dynamics are highly variable between different trials, cells, and cell subcompartments. Here we present a qualitative analysis of a recent mathematical model of astrocyte calcium responses. We show how the major response types are generated in the model as a result of the underlying bifurcation structure. By varying key channel parameters, mimicking blockers used by experimentalists, we manipulate this underlying bifurcation structure and predict how the distributions of responses can change. We find that store-operated calcium channels, plasma membrane bound channels with little activity during calcium transients, have a surprisingly strong effect, underscoring the importance of considering these channels in both experiments and mathematical settings. Variation in the maximum flow in different calcium channels is also shown to determine the range of stable oscillations, as well as set the range of frequencies of the oscillations. Further, by conducting a randomized search through the parameter space and recording the resulting calcium responses, we create a database that can be used by experimentalists to help estimate the underlying channel distribution of their cells.

Dynamic correlations between heart and brain rhythm during Autogenic meditation

PubMed Central

Kim, Dae-Keun; Lee, Kyung-Mi; Kim, Jongwha; Whang, Min-Cheol; Kang, Seung Wan

2013-01-01

This study is aimed to determine significant physiological parameters of brain and heart under meditative state, both in each activities and their dynamic correlations. Electrophysiological changes in response to meditation were explored in 12 healthy volunteers who completed 8 weeks of a basic training course in autogenic meditation. Heart coherence, representing the degree of ordering in oscillation of heart rhythm intervals, increased significantly during meditation. Relative EEG alpha power and alpha lagged coherence also increased. A significant slowing of parietal peak alpha frequency was observed. Parietal peak alpha power increased with increasing heart coherence during meditation, but no such relationship was observed during baseline. Average alpha lagged coherence also increased with increasing heart coherence during meditation, but weak opposite relationship was observed at baseline. Relative alpha power increased with increasing heart coherence during both meditation and baseline periods. Heart coherence can be a cardiac marker for the meditative state and also may be a general marker for the meditative state since heart coherence is strongly correlated with EEG alpha activities. It is expected that increasing heart coherence and the accompanying EEG alpha activations, heart brain synchronicity, would help recover physiological synchrony following a period of homeostatic depletion. PMID:23914165

Dynamic correlations between heart and brain rhythm during Autogenic meditation.

PubMed

Kim, Dae-Keun; Lee, Kyung-Mi; Kim, Jongwha; Whang, Min-Cheol; Kang, Seung Wan

2013-01-01

This study is aimed to determine significant physiological parameters of brain and heart under meditative state, both in each activities and their dynamic correlations. Electrophysiological changes in response to meditation were explored in 12 healthy volunteers who completed 8 weeks of a basic training course in autogenic meditation. Heart coherence, representing the degree of ordering in oscillation of heart rhythm intervals, increased significantly during meditation. Relative EEG alpha power and alpha lagged coherence also increased. A significant slowing of parietal peak alpha frequency was observed. Parietal peak alpha power increased with increasing heart coherence during meditation, but no such relationship was observed during baseline. Average alpha lagged coherence also increased with increasing heart coherence during meditation, but weak opposite relationship was observed at baseline. Relative alpha power increased with increasing heart coherence during both meditation and baseline periods. Heart coherence can be a cardiac marker for the meditative state and also may be a general marker for the meditative state since heart coherence is strongly correlated with EEG alpha activities. It is expected that increasing heart coherence and the accompanying EEG alpha activations, heart brain synchronicity, would help recover physiological synchrony following a period of homeostatic depletion.

An aberrant parasympathetic response: a new perspective linking chronic stress and itch.

PubMed

Kim, Hei Sung; Yosipovitch, Gil

2013-04-01

Perceived stress has long been known to alter the dynamic equilibrium established between the nervous, endocrine and immune system and is widely recognised to trigger or enhance pruritus. However, the exact mechanism of how the major stress response systems, such as the hypothalamus-pituitary adrenal (HPA) axis and the autonomic nervous system induce or aggravate chronic itch, has not been elucidated. The limbic regions of the brain such as the prefrontal cortex and hippocampus are deeply involved in the regulation of the stress response and intersect with circuits that are responsible for memory and reward. According to the 'Polyvagal Theory', certain limbic structures that serve as a 'higher brain equivalent of the parasympathetic nervous system' play a foremost role in maintaining body homoeostasis by functioning as an active vagal brake. In addition, the limbic system has been postulated to regulate two distinct, yet related aspects of itch: (i) the sensory-discriminative aspect; and (ii) the affective-cognitive aspect. Chronic stress-induced itch is hypothesised to be caused by stress-related changes in limbic structure with subsequent rewiring of both the peripheral and central pruriceptive circuits. Herein, we review data suggesting that a dysfunctional parasympathetic nervous system associated with chronic stress may play a critical role in the regulatory control of key candidate molecules, receptors and brain structures involved in chronic itch. © 2012 John Wiley & Sons A/S.

Neural Dynamics Underlying Event-Related Potentials

NASA Technical Reports Server (NTRS)

Shah, Ankoor S.; Bressler, Steven L.; Knuth, Kevin H.; Ding, Ming-Zhou; Mehta, Ashesh D.; Ulbert, Istvan; Schroeder, Charles E.

2003-01-01

There are two opposing hypotheses about the brain mechanisms underlying sensory event-related potentials (ERPs). One holds that sensory ERPs are generated by phase resetting of ongoing electroencephalographic (EEG) activity, and the other that they result from signal averaging of stimulus-evoked neural responses. We tested several contrasting predictions of these hypotheses by direct intracortical analysis of neural activity in monkeys. Our findings clearly demonstrate evoked response contributions to the sensory ERP in the monkey, and they suggest the likelihood that a mixed (Evoked/Phase Resetting) model may account for the generation of scalp ERPs in humans.

Keep Away from Danger: Dangerous Objects in Dynamic and Static Situations

PubMed Central

Anelli, Filomena; Nicoletti, Roberto; Bolzani, Roberto; Borghi, Anna M.

2013-01-01

Behavioral and neuroscience studies have shown that objects observation evokes specific affordances (i.e., action possibilities) and motor responses. Recent findings provide evidence that even dangerous objects can modulate the motor system evoking aversive affordances. This sounds intriguing since so far the majority of behavioral, brain imaging, and transcranial magnetic stimulation studies with painful and dangerous stimuli strictly concerned the domain of pain, with the exception of evidence suggesting sensitivity to objects’ affordances when neutral objects are located in participants’ peripersonal space. This study investigates whether the observation of a neutral or dangerous object in a static or dynamic situation differently influences motor responses, and the time-course of the dangerous objects’ processing. In three experiments we manipulated: object dangerousness (neutral vs. dangerous); object category (artifact vs. natural); manual response typology (press vs. release a key); object presentation (Experiment 1: dynamic, Experiments 2 and 3: static); object movement direction (Experiment 1: away vs. toward the participant) or size (Experiments 2 and 3: big vs. normal vs. small). The task required participants to decide whether the object was an artifact or a natural object, by pressing or releasing one key. Results showed a facilitation for neutral over dangerous objects in the static situation, probably due to an affordance effect. Instead, in the dynamic condition responses were modulated by the object movement direction, with a dynamic affordance effect elicited by neutral objects and an escape-avoidance effect provoked by dangerous objects (neutral objects were processed faster when they moved toward-approached the participant, whereas dangerous objects were processed faster when they moved away from the participant). Moreover, static stimuli influenced the manual response typology. These data indicate the emergence of dynamic affordance and escaping-avoidance effects. PMID:23847512

Keep away from danger: dangerous objects in dynamic and static situations.

PubMed

Anelli, Filomena; Nicoletti, Roberto; Bolzani, Roberto; Borghi, Anna M

2013-01-01

Behavioral and neuroscience studies have shown that objects observation evokes specific affordances (i.e., action possibilities) and motor responses. Recent findings provide evidence that even dangerous objects can modulate the motor system evoking aversive affordances. This sounds intriguing since so far the majority of behavioral, brain imaging, and transcranial magnetic stimulation studies with painful and dangerous stimuli strictly concerned the domain of pain, with the exception of evidence suggesting sensitivity to objects' affordances when neutral objects are located in participants' peripersonal space. This study investigates whether the observation of a neutral or dangerous object in a static or dynamic situation differently influences motor responses, and the time-course of the dangerous objects' processing. In three experiments we manipulated: object dangerousness (neutral vs. dangerous); object category (artifact vs. natural); manual response typology (press vs. release a key); object presentation (Experiment 1: dynamic, Experiments 2 and 3: static); object movement direction (Experiment 1: away vs. toward the participant) or size (Experiments 2 and 3: big vs. normal vs. small). The task required participants to decide whether the object was an artifact or a natural object, by pressing or releasing one key. Results showed a facilitation for neutral over dangerous objects in the static situation, probably due to an affordance effect. Instead, in the dynamic condition responses were modulated by the object movement direction, with a dynamic affordance effect elicited by neutral objects and an escape-avoidance effect provoked by dangerous objects (neutral objects were processed faster when they moved toward-approached the participant, whereas dangerous objects were processed faster when they moved away from the participant). Moreover, static stimuli influenced the manual response typology. These data indicate the emergence of dynamic affordance and escaping-avoidance effects.

Connexin channels provide a target to manipulate brain endothelial calcium dynamics and blood–brain barrier permeability

PubMed Central

De Bock, Marijke; Culot, Maxime; Wang, Nan; Bol, Mélissa; Decrock, Elke; De Vuyst, Elke; da Costa, Anaelle; Dauwe, Ine; Vinken, Mathieu; Simon, Alexander M; Rogiers, Vera; De Ley, Gaspard; Evans, William Howard; Bultynck, Geert; Dupont, Geneviève; Cecchelli, Romeo; Leybaert, Luc

2011-01-01

The cytoplasmic Ca2+ concentration ([Ca2+]i) is an important factor determining the functional state of blood–brain barrier (BBB) endothelial cells but little is known on the effect of dynamic [Ca2+]i changes on BBB function. We applied different agonists that trigger [Ca2+]i oscillations and determined the involvement of connexin channels and subsequent effects on endothelial permeability in immortalized and primary brain endothelial cells. The inflammatory peptide bradykinin (BK) triggered [Ca2+]i oscillations and increased endothelial permeability. The latter was prevented by buffering [Ca2+]i with BAPTA, indicating that [Ca2+]i oscillations are crucial in the permeability changes. Bradykinin-triggered [Ca2+]i oscillations were inhibited by interfering with connexin channels, making use of carbenoxolone, Gap27, a peptide blocker of connexin channels, and Cx37/43 knockdown. Gap27 inhibition of the oscillations was rapid (within minutes) and work with connexin hemichannel-permeable dyes indicated hemichannel opening and purinergic signaling in response to stimulation with BK. Moreover, Gap27 inhibited the BK-triggered endothelial permeability increase in in vitro and in vivo experiments. By contrast, [Ca2+]i oscillations provoked by exposure to adenosine 5′ triphosphate (ATP) were not affected by carbenoxolone or Gap27 and ATP did not disturb endothelial permeability. We conclude that interfering with endothelial connexin hemichannels is a novel approach to limiting BBB-permeability alterations. PMID:21654699

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

PubMed Central

Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

[In vivo measurement of rabbits brain impedance frequency response and the elementary imaging of EIT].

PubMed

Wu, Xiaoming; Dong, Xiuzhen; Qin, Mingxin; Fu, Feng; Wang, Yuemin; You, Fusheng; Xiang, Haiyan; Liu, Ruigang; Shi, Xuetao

2003-03-01

The in vivo measurements of rabbit brain tissue impedance were taken under both normal and ischemic conditions by using two-electrode measurement method in the frequency range from 0.1 Hz to 1 MHz. The dynamic images about the resistivity of cerebral ischemia were reconstructed based on a 16-electrode system. The results of in vivo measurement showed that the ratio of impedance increased can be as high as 75% at frequencies lower than 10 Hz. In the range from 1 KHz to 1 MHz, the ratio showed a constant value of 15%. The electrical impedance tomography (EIT) images obtained suggested that the regions of impedance changes highly correspond to the position of ischemia. It is confirmed that the brain function changes caused by local deficiency of blood can be detected and imaged by EIT method.

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance.

PubMed

Proskovec, Amy L; Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2018-05-31

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

Diminished neural network dynamics after moderate and severe traumatic brain injury

PubMed Central

Gilbert, Nicholas; Bernier, Rachel A.; Calhoun, Vincent D.; Brenner, Einat; Grossner, Emily; Rajtmajer, Sarah M.

2018-01-01

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain’s subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network “states” that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics. PMID:29883447

Effect of skull flexural properties on brain response during dynamic head loading - biomed 2013.

PubMed

Harrigan, T P; Roberts, J C; Ward, E E; Carneal, C M; Merkle, A C

2013-01-01

The skull-brain complex is typically modeled as an integrated structure, similar to a fluid-filled shell. Under dynamic loads, the interaction of the skull and the underlying brain, cerebrospinal fluid, and other tissue produces the pressure and strain histories that are the basis for many theories meant to describe the genesis of traumatic brain injury. In addition, local bone strains are of interest for predicting skull fracture in blunt trauma. However, the role of skull flexure in the intracranial pressure response to blunt trauma is complex. Since the relative time scales for pressure and flexural wave transmission across the skull are not easily separated, it is difficult to separate out the relative roles of the mechanical components in this system. This study uses a finite element model of the head, which is validated for pressure transmission to the brain, to assess the influence of skull table flexural stiffness on pressure in the brain and on strain within the skull. In a Human Head Finite Element Model, the skull component was modified by attaching shell elements to the inner and outer surfaces of the existing solid elements that modeled the skull. The shell elements were given the properties of bone, and the existing solid elements were decreased so that the overall stiffness along the surface of the skull was unchanged, but the skull table bending stiffness increased by a factor of 2.4. Blunt impact loads were applied to the frontal bone centrally, using LS-Dyna. The intracranial pressure predictions and the strain predictions in the skull were compared for models with and without surface shell elements, showing that the pressures in the mid-anterior and mid-posterior of the brain were very similar, but the strains in the skull under the loads and adjacent to the loads were decreased 15% with stiffer flexural properties. Pressure equilibration to nearly hydrostatic distributions occurred, indicating that the important frequency components for typical impact loading are lower than frequencies based on pressure wave propagation across the skull. This indicates that skull flexure has a local effect on intracranial pressures but that the integrated effect of a dome-like structure under load is a significant part of load transfer in the skull in blunt trauma.

Activation induced changes in GABA: Functional MRS at 7T with MEGA-sLASER.

PubMed

Chen, Chen; Sigurdsson, Hilmar P; Pépés, Sophia E; Auer, Dorothee P; Morris, Peter G; Morgan, Paul S; Gowland, Penny A; Jackson, Stephen R

2017-08-01

Functional magnetic resonance spectroscopy (fMRS) has been used to assess the dynamic metabolic responses of the brain to a physiological stimulus non-invasively. However, only limited information on the dynamic functional response of γ-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the brain, is available. We aimed to measure the activation-induced changes in GABA unambiguously using a spectral editing method, instead of the conventional direct detection techniques used in previous fMRS studies. The Mescher-Garwood-semi-localised by adiabatic selective refocusing (MEGA-sLASER) sequence was developed at 7T to obtain the time course of GABA concentration without macromolecular contamination. A significant decrease (-12±5%) in the GABA to total creatine ratio (GABA/tCr) was observed in the motor cortex during a period of 10min of hand-clenching, compared to an initial baseline level (GABA/tCr =0.11±0.02) at rest. An increase in the Glx (glutamate and glutamine) to tCr ratio was also found, which is in agreement with previous findings. In contrast, no significant changes in NAA/tCr and tCr were detected. With consistent and highly efficient editing performance for GABA detection and the advantage of visually identifying GABA resonances in the spectra, MEGA-sLASER is demonstrated to be an effective method for studying of dynamic changes in GABA at 7T. Copyright © 2017 Elsevier Inc. All rights reserved.

Imaging Live Drosophila Brain with Two-Photon Fluorescence Microscopy

NASA Astrophysics Data System (ADS)

Ahmed, Syeed Ehsan

Two-photon fluorescence microscopy is an imaging technique which delivers distinct benefits for in vivo cellular and molecular imaging. Cyclic adenosine monophosphate (cAMP), a second messenger molecule, is responsible for triggering many physiological changes in neural system. However, the mechanism by which this molecule regulates responses in neuron cells is not yet clearly understood. When cAMP binds to a target protein, it changes the structure of that protein. Therefore, studying this molecular structure change with fluorescence resonance energy transfer (FRET) imaging can shed light on the cAMP functioning mechanism. FRET is a non-radiative dipole-dipole coupling which is sensitive to small distance change in nanometer scale. In this study we have investigated the effect of dopamine in cAMP dynamics in vivo. In our study two-photon fluorescence microscope was used for imaging mushroom bodies inside live Drosophila melanogaster brain and we developed a method for studying the change in cyclic AMP level.

Calcium neuroimaging in behaving zebrafish larvae using a turn-key light field camera

NASA Astrophysics Data System (ADS)

Cruz Perez, Carlos; Lauri, Antonella; Symvoulidis, Panagiotis; Cappetta, Michele; Erdmann, Arne; Westmeyer, Gil Gregor

2015-09-01

Reconstructing a three-dimensional scene from multiple simultaneously acquired perspectives (the light field) is an elegant scanless imaging concept that can exceed the temporal resolution of currently available scanning-based imaging methods for capturing fast cellular processes. We tested the performance of commercially available light field cameras on a fluorescent microscopy setup for monitoring calcium activity in the brain of awake and behaving reporter zebrafish larvae. The plenoptic imaging system could volumetrically resolve diverse neuronal response profiles throughout the zebrafish brain upon stimulation with an aversive odorant. Behavioral responses of the reporter fish could be captured simultaneously together with depth-resolved neuronal activity. Overall, our assessment showed that with some optimizations for fluorescence microscopy applications, commercial light field cameras have the potential of becoming an attractive alternative to custom-built systems to accelerate molecular imaging research on cellular dynamics.

Calcium neuroimaging in behaving zebrafish larvae using a turn-key light field camera.

PubMed

Perez, Carlos Cruz; Lauri, Antonella; Symvoulidis, Panagiotis; Cappetta, Michele; Erdmann, Arne; Westmeyer, Gil Gregor

2015-09-01

Reconstructing a three-dimensional scene from multiple simultaneously acquired perspectives (the light field) is an elegant scanless imaging concept that can exceed the temporal resolution of currently available scanning-based imaging methods for capturing fast cellular processes. We tested the performance of commercially available light field cameras on a fluorescent microscopy setup for monitoring calcium activity in the brain of awake and behaving reporter zebrafish larvae. The plenoptic imaging system could volumetrically resolve diverse neuronal response profiles throughout the zebrafish brain upon stimulation with an aversive odorant. Behavioral responses of the reporter fish could be captured simultaneously together with depth-resolved neuronal activity. Overall, our assessment showed that with some optimizations for fluorescence microscopy applications, commercial light field cameras have the potential of becoming an attractive alternative to custom-built systems to accelerate molecular imaging research on cellular dynamics.

Imaging Plasmodium Immunobiology in Liver, Brain, and Lung

PubMed Central

Frevert, Ute; Nacer, Adéla; Cabrera, Mynthia; Movila, Alexandru; Leberl, Maike

2013-01-01

Plasmodium falciparum malaria is responsible for the deaths of over half a million African children annually. Until a decade ago, dynamic analysis of the malaria parasite was limited to in vitro systems with the typical limitations associated with 2D monocultures or entirely artificial surfaces. Due to extremely low parasite densities, the liver was considered a black box in terms of Plasmodium sporozoite invasion, liver stage development, and merozoite release into the blood. Further, nothing was known about the behavior of blood stage parasites in organs such as brain where clinical signs manifest and the ensuing immune response of the host that may ultimately result in a fatal outcome. The advent of fluorescent parasites, advances in imaging technology, and availability of an ever-increasing number of cellular and molecular probes have helped illuminate many steps along the pathogenetic cascade of this deadly tropical parasite. PMID:24076429

Quantitative complexity analysis in multi-channel intracranial EEG recordings form epilepsy brains

PubMed Central

Liu, Chang-Chia; Pardalos, Panos M.; Chaovalitwongse, W. Art; Shiau, Deng-Shan; Ghacibeh, Georges; Suharitdamrong, Wichai; Sackellares, J. Chris

2008-01-01

Epilepsy is a brain disorder characterized clinically by temporary but recurrent disturbances of brain function that may or may not be associated with destruction or loss of consciousness and abnormal behavior. Human brain is composed of more than 10 to the power 10 neurons, each of which receives electrical impulses known as action potentials from others neurons via synapses and sends electrical impulses via a sing output line to a similar (the axon) number of neurons. When neuronal networks are active, they produced a change in voltage potential, which can be captured by an electroencephalogram (EEG). The EEG recordings represent the time series that match up to neurological activity as a function of time. By analyzing the EEG recordings, we sought to evaluate the degree of underlining dynamical complexity prior to progression of seizure onset. Through the utilization of the dynamical measurements, it is possible to classify the state of the brain according to the underlying dynamical properties of EEG recordings. The results from two patients with temporal lobe epilepsy (TLE), the degree of complexity start converging to lower value prior to the epileptic seizures was observed from epileptic regions as well as non-epileptic regions. The dynamical measurements appear to reflect the changes of EEG’s dynamical structure. We suggest that the nonlinear dynamical analysis can provide a useful information for detecting relative changes in brain dynamics, which cannot be detected by conventional linear analysis. PMID:19079790

Brain stiffens post mortem.

PubMed

Weickenmeier, J; Kurt, M; Ozkaya, E; de Rooij, R; Ovaert, T C; Ehman, R L; Butts Pauly, K; Kuhl, E

2018-04-22

Alterations in brain rheology are increasingly recognized as a diagnostic marker for various neurological conditions. Magnetic resonance elastography now allows us to assess brain rheology repeatably, reproducibly, and non-invasively in vivo. Recent elastography studies suggest that brain stiffness decreases one percent per year during normal aging, and is significantly reduced in Alzheimer's disease and multiple sclerosis. While existing studies successfully compare brain stiffnesses across different populations, they fail to provide insight into changes within the same brain. Here we characterize rheological alterations in one and the same brain under extreme metabolic changes: alive and dead. Strikingly, the storage and loss moduli of the cerebrum increased by 26% and 60% within only three minutes post mortem and continued to increase by 40% and 103% within 45 minutes. Immediate post mortem stiffening displayed pronounced regional variations; it was largest in the corpus callosum and smallest in the brainstem. We postulate that post mortem stiffening is a manifestation of alterations in polarization, oxidation, perfusion, and metabolism immediately after death. Our results suggest that the stiffness of our brain-unlike any other organ-is a dynamic property that is highly sensitive to the metabolic environment. Our findings emphasize the importance of characterizing brain tissue in vivo and question the relevance of ex vivo brain tissue testing as a whole. Knowing the true stiffness of the living brain has important consequences in diagnosing neurological conditions, planning neurosurgical procedures, and modeling the brain's response to high impact loading. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Monocyte trafficking to the brain with stress and inflammation: a novel axis of immune-to-brain communication that influences mood and behavior

PubMed Central

Wohleb, Eric S.; McKim, Daniel B.; Sheridan, John F.; Godbout, Jonathan P.

2015-01-01

HIGHLIGHTS Psychological stress activates neuroendocrine pathways that alter immune responses.Stress-induced alterations in microglia phenotype and monocyte priming leads to aberrant peripheral and central inflammation.Elevated pro-inflammatory cytokine levels caused by microglia activation and recruitment of monocytes to the brain contribute to development and persistent anxiety-like behavior.Mechanisms that mediate interactions between microglia, endothelial cells, and macrophages and how these contribute to changes in behavior are discussed.Sensitization of microglia and re-distribution of primed monocytes are implicated in re-establishment of anxiety-like behavior. Psychological stress causes physiological, immunological, and behavioral alterations in humans and rodents that can be maladaptive and negatively affect quality of life. Several lines of evidence indicate that psychological stress disrupts key functional interactions between the immune system and brain that ultimately affects mood and behavior. For example, activation of microglia, the resident innate immune cells of the brain, has been implicated as a key regulator of mood and behavior in the context of prolonged exposure to psychological stress. Emerging evidence implicates a novel neuroimmune circuit involving microglia activation and sympathetic outflow to the peripheral immune system that further reinforces stress-related behaviors by facilitating the recruitment of inflammatory monocytes to the brain. Evidence from various rodent models, including repeated social defeat (RSD), revealed that trafficking of monocytes to the brain promoted the establishment of anxiety-like behaviors following prolonged stress exposure. In addition, new evidence implicates monocyte trafficking from the spleen to the brain as key regulator of recurring anxiety following exposure to prolonged stress. The purpose of this review is to discuss mechanisms that cause stress-induced monocyte re-distribution in the brain and how dynamic interactions between microglia, endothelial cells, and brain macrophages lead to maladaptive behavioral responses. PMID:25653581

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior.

PubMed

Hansen, Sofie Therese; Hansen, Lars Kai

2017-03-01

Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging connections exist in the brain than long ranging, arguing for spatially focal sources. Additionally, recent work (Delorme et al., 2012) argues that EEG can be decomposed into components having sparse source distributions. On the temporal side both short and long term stationarity of brain activation are seen. We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

Experiential, autonomic, and neural responses during threat anticipation vary as a function of threat intensity and neuroticism.

PubMed

Drabant, Emily M; Kuo, Janice R; Ramel, Wiveka; Blechert, Jens; Edge, Michael D; Cooper, Jeff R; Goldin, Philippe R; Hariri, Ahmad R; Gross, James J

2011-03-01

Anticipatory emotional responses play a crucial role in preparing individuals for impending challenges. They do this by triggering a coordinated set of changes in behavioral, autonomic, and neural response systems. In the present study, we examined the biobehavioral impact of varying levels of anticipatory anxiety, using a shock anticipation task in which unpredictable electric shocks were threatened and delivered to the wrist at variable intervals and intensities (safe, medium, strong). This permitted investigation of a dynamic range of anticipatory anxiety responses. In two studies, 95 and 51 healthy female participants, respectively, underwent this shock anticipation task while providing continuous ratings of anxiety experience and electrodermal responding (Study 1) and during fMRI BOLD neuroimaging (Study 2). Results indicated a step-wise pattern of responding in anxiety experience and electrodermal responses. Several brain regions showed robust responses to shock anticipation relative to safe trials, including the hypothalamus, periaqueductal gray, caudate, precentral gyrus, thalamus, insula, ventrolateral PFC, dorsomedial PFC, and ACC. A subset of these regions demonstrated a linear pattern of increased responding from safe to medium to strong trials, including the bilateral insula, ACC, and inferior frontal gyrus. These responses were modulated by individual differences in neuroticism, such that those high in neuroticism showed exaggerated anxiety experience across the entire task, and reduced brain activation from medium to strong trials in a subset of brain regions. These findings suggest that individual differences in neuroticism may influence sensitivity to anticipatory threat and provide new insights into the mechanism through which neuroticism may confer risk for developing anxiety disorders via dysregulated anticipatory responses. Copyright © 2010 Elsevier Inc. All rights reserved.

Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension.

PubMed

Brodbeck, Christian; Presacco, Alessandro; Simon, Jonathan Z

2018-05-15

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.

Natural Changes in Brain Temperature Underlie Variations in Song Tempo during a Mating Behavior

PubMed Central

Aronov, Dmitriy; Fee, Michale S.

2012-01-01

The song of a male zebra finch is a stereotyped motor sequence whose tempo varies with social context – whether or not the song is directed at a female bird – as well as with the time of day. The neural mechanisms underlying these changes in tempo are unknown. Here we show that brain temperature recorded in freely behaving male finches exhibits a global increase in response to the presentation of a female bird. This increase strongly correlates with, and largely explains, the faster tempo of songs directed at a female compared to songs produced in social isolation. Furthermore, we find that the observed diurnal variations in song tempo are also explained by natural variations in brain temperature. Our findings suggest that brain temperature is an important variable that can influence the dynamics of activity in neural circuits, as well as the temporal features of behaviors that some of these circuits generate. PMID:23112858

Taste quality decoding parallels taste sensations.

PubMed

Crouzet, Sébastien M; Busch, Niko A; Ohla, Kathrin

2015-03-30

In most species, the sense of taste is key in the distinction of potentially nutritious and harmful food constituents and thereby in the acceptance (or rejection) of food. Taste quality is encoded by specialized receptors on the tongue, which detect chemicals corresponding to each of the basic tastes (sweet, salty, sour, bitter, and savory [1]), before taste quality information is transmitted via segregated neuronal fibers [2], distributed coding across neuronal fibers [3], or dynamic firing patterns [4] to the gustatory cortex in the insula. In rodents, both hardwired coding by labeled lines [2] and flexible, learning-dependent representations [5] and broadly tuned neurons [6] seem to coexist. It is currently unknown how, when, and where taste quality representations are established in the cortex and whether these representations are used for perceptual decisions. Here, we show that neuronal response patterns allow to decode which of four tastants (salty, sweet, sour, and bitter) participants tasted in a given trial by using time-resolved multivariate pattern analyses of large-scale electrophysiological brain responses. The onset of this prediction coincided with the earliest taste-evoked responses originating from the insula and opercular cortices, indicating that quality is among the first attributes of a taste represented in the central gustatory system. These response patterns correlated with perceptual decisions of taste quality: tastes that participants discriminated less accurately also evoked less discriminated brain response patterns. The results therefore provide the first evidence for a link between taste-related decision-making and the predictive value of these brain response patterns. Copyright © 2015 Elsevier Ltd. All rights reserved.

A 3-dimensional DTI MRI-based model of GBM growth and response to radiation therapy.

PubMed

Hathout, Leith; Patel, Vishal; Wen, Patrick

2016-09-01

Glioblastoma (GBM) is both the most common and the most aggressive intra-axial brain tumor, with a notoriously poor prognosis. To improve this prognosis, it is necessary to understand the dynamics of GBM growth, response to treatment and recurrence. The present study presents a mathematical diffusion-proliferation model of GBM growth and response to radiation therapy based on diffusion tensor (DTI) MRI imaging. This represents an important advance because it allows 3-dimensional tumor modeling in the anatomical context of the brain. Specifically, tumor infiltration is guided by the direction of the white matter tracts along which glioma cells infiltrate. This provides the potential to model different tumor growth patterns based on location within the brain, and to simulate the tumor's response to different radiation therapy regimens. Tumor infiltration across the corpus callosum is simulated in biologically accurate time frames. The response to radiation therapy, including changes in cell density gradients and how these compare across different radiation fractionation protocols, can be rendered. Also, the model can estimate the amount of subthreshold tumor which has extended beyond the visible MR imaging margins. When combined with the ability of being able to estimate the biological parameters of invasiveness and proliferation of a particular GBM from serial MRI scans, it is shown that the model has potential to simulate realistic tumor growth, response and recurrence patterns in individual patients. To the best of our knowledge, this is the first presentation of a DTI-based GBM growth and radiation therapy treatment model.

Sex-Steroid Hormone Manipulation Reduces Brain Response to Reward.

PubMed

Macoveanu, Julian; Henningsson, Susanne; Pinborg, Anja; Jensen, Peter; Knudsen, Gitte M; Frokjaer, Vibe G; Siebner, Hartwig R

2016-03-01

Mood disorders are twice as frequent in women than in men. Risk mechanisms for major depression include adverse responses to acute changes in sex-steroid hormone levels, eg, postpartum in women. Such adverse responses may involve an altered processing of rewards. Here, we examine how women's vulnerability for mood disorders is linked to sex-steroid dynamics by investigating the effects of a pharmacologically induced fluctuation in ovarian sex steroids on the brain response to monetary rewards. In a double-blinded placebo controlled study, healthy women were randomized to receive either placebo or the gonadotropin-releasing hormone agonist (GnRHa) goserelin, which causes a net decrease in sex-steroid levels. Fifty-eight women performed a gambling task while undergoing functional MRI at baseline, during the mid-follicular phase, and again following the intervention. The gambling task enabled us to map regional brain activity related to the magnitude of risk during choice and to monetary reward. The GnRHa intervention caused a net reduction in ovarian sex steroids (estradiol and testosterone) and increased depression symptoms. Compared with placebo, GnRHa reduced amygdala's reactivity to high monetary rewards. There was a positive association between the individual changes in testosterone and changes in bilateral insula response to monetary rewards. Our data provide evidence for the involvement of sex-steroid hormones in reward processing. A blunted amygdala response to rewarding stimuli following a rapid decline in sex-steroid hormones may reflect a reduced engagement in positive experiences. Abnormal reward processing may constitute a neurobiological mechanism by which sex-steroid fluctuations provoke mood disorders in susceptible women.

What kind of noise is brain noise: anomalous scaling behavior of the resting brain activity fluctuations

PubMed Central

Fraiman, Daniel; Chialvo, Dante R.

2012-01-01

The study of spontaneous fluctuations of brain activity, often referred as brain noise, is getting increasing attention in functional magnetic resonance imaging (fMRI) studies. Despite important efforts, much of the statistical properties of such fluctuations remain largely unknown. This work scrutinizes these fluctuations looking at specific statistical properties which are relevant to clarify its dynamical origins. Here, three statistical features which clearly differentiate brain data from naive expectations for random processes are uncovered: First, the variance of the fMRI mean signal as a function of the number of averaged voxels remains constant across a wide range of observed clusters sizes. Second, the anomalous behavior of the variance is originated by bursts of synchronized activity across regions, regardless of their widely different sizes. Finally, the correlation length (i.e., the length at which the correlation strength between two regions vanishes) as well as mutual information diverges with the cluster's size considered, such that arbitrarily large clusters exhibit the same collective dynamics than smaller ones. These three properties are known to be exclusive of complex systems exhibiting critical dynamics, where the spatio-temporal dynamics show these peculiar type of fluctuations. Thus, these findings are fully consistent with previous reports of brain critical dynamics, and are relevant for the interpretation of the role of fluctuations and variability in brain function in health and disease. PMID:22934058

Psychotic Experiences, Working Memory, and the Developing Brain: A Multimodal Neuroimaging Study

PubMed Central

Fonville, Leon; Cohen Kadosh, Kathrin; Drakesmith, Mark; Dutt, Anirban; Zammit, Stanley; Mollon, Josephine; Reichenberg, Abraham; Lewis, Glyn; Jones, Derek K.; David, Anthony S.

2015-01-01

Psychotic experiences (PEs) occur in the general population, especially in children and adolescents, and are associated with poor psychosocial outcomes, impaired cognition, and increased risk of transition to psychosis. It is unknown how the presence and persistence of PEs during early adulthood affects cognition and brain function. The current study assessed working memory as well as brain function and structure in 149 individuals, with and without PEs, drawn from a population cohort. Observer-rated PEs were classified as persistent or transient on the basis of longitudinal assessments. Working memory was assessed using the n-back task during fMRI. Dynamic causal modeling (DCM) was used to characterize frontoparietal network configuration and voxel-based morphometry was utilized to examine gray matter. Those with persistent, but not transient, PEs performed worse on the n-back task, compared with controls, yet showed no significant differences in regional brain activation or brain structure. DCM analyses revealed greater emphasis on frontal connectivity within a frontoparietal network in those with PEs compared with controls. We propose that these findings portray an altered configuration of working memory function in the brain, potentially indicative of an adaptive response to atypical development associated with the manifestation of PEs. PMID:26286920

Cocaine-Induced Structural Plasticity in Input Regions to Distinct Cell Types in Nucleus Accumbens.

PubMed

Barrientos, Cindy; Knowland, Daniel; Wu, Mingche M J; Lilascharoen, Varoth; Huang, Kee Wui; Malenka, Robert C; Lim, Byung Kook

2018-05-09

The nucleus accumbens (NAc) is a brain region implicated in pathological motivated behaviors such as drug addiction and is composed predominantly of two discrete populations of neurons, dopamine receptor-1- and dopamine receptor-2-expressing medium spiny neurons (D1-MSNs and D2-MSNs, respectively). It is unclear whether these populations receive inputs from different brain areas and whether input regions to these cell types undergo distinct structural adaptations in response to the administration of addictive drugs such as cocaine. Using a modified rabies virus-mediated tracing method, we created a comprehensive brain-wide monosynaptic input map to NAc D1- and D2-MSNs. Next, we analyzed nearly 2000 dendrites and 125,000 spines of neurons across four input regions (the prelimbic cortex, medial orbitofrontal cortex, basolateral amygdala, and ventral hippocampus) at four separate time points during cocaine administration and withdrawal to examine changes in spine density in response to repeated intraperitoneal cocaine injection in mice. D1- and D2-MSNs display overall similar input profiles, with the exception that D1-MSNs receive significantly more input from the medial orbitofrontal cortex. We found that neurons in distinct brain areas projecting to D1- and D2-MSNs display different adaptations in dendritic spine density at different stages of cocaine administration and withdrawal. While NAc D1- and D2-MSNs receive input from similar brain structures, cocaine-induced spine density changes in input regions are quite distinct and dynamic. While previous studies have focused on input-specific postsynaptic changes within NAc MSNs in response to cocaine, these findings emphasize the dramatic changes that occur in the afferent input regions as well. Published by Elsevier Inc.

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Dynamic Multi-Coil Shimming of the Human Brain at 7 Tesla

PubMed Central

Juchem, Christoph; Nixon, Terence W.; McIntyre, Scott; Boer, Vincent O.; Rothman, Douglas L.; de Graaf, Robin A.

2011-01-01

High quality magnetic field homogenization of the human brain (i.e. shimming) for MR imaging and spectroscopy is a demanding task. The susceptibility differences between air and tissue are a longstanding problem as they induce complex field distortions in the prefrontal cortex and the temporal lobes. To date, the theoretical gains of high field MR have only been realized partially in the human brain due to limited magnetic field homogeneity. A novel shimming technique for the human brain is presented that is based on the combination of non-orthogonal basis fields from 48 individual, circular coils. Custom-built amplifier electronics enabled the dynamic application of the multi-coil shim fields in a slice-specific fashion. Dynamic multi-coil (DMC) shimming is shown to eliminate most of the magnetic field inhomogeneity apparent in the human brain at 7 Tesla and provided improved performance compared to state-of-the-art dynamic shim updating with zero through third order spherical harmonic functions. The novel technique paves the way for high field MR applications of the human brain for which excellent magnetic field homogeneity is a prerequisite. PMID:21824794

Sex-related differences in auditory processing in adolescents with fetal alcohol spectrum disorder: A magnetoencephalographic study.

PubMed

Tesche, Claudia D; Kodituwakku, Piyadasa W; Garcia, Christopher M; Houck, Jon M

2015-01-01

Children exposed to substantial amounts of alcohol in utero display a broad range of morphological and behavioral outcomes, which are collectively referred to as fetal alcohol spectrum disorders (FASDs). Common to all children on the spectrum are cognitive and behavioral problems that reflect central nervous system dysfunction. Little is known, however, about the potential effects of variables such as sex on alcohol-induced brain damage. The goal of the current research was to utilize magnetoencephalography (MEG) to examine the effect of sex on brain dynamics in adolescents and young adults with FASD during the performance of an auditory oddball task. The stimuli were short trains of 1 kHz "standard" tone bursts (80%) randomly interleaved with 1.5 kHz "target" tone bursts (10%) and "novel" digital sounds (10%). Participants made motor responses to the target tones. Results are reported for 44 individuals (18 males and 26 females) ages 12 through 22 years. Nine males and 13 females had a diagnosis of FASD and the remainder were typically-developing age- and sex-matched controls. The main finding was widespread sex-specific differential activation of the frontal, medial and temporal cortex in adolescents with FASD compared to typically developing controls. Significant differences in evoked-response and time-frequency measures of brain dynamics were observed for all stimulus types in the auditory cortex, inferior frontal sulcus and hippocampus. These results underscore the importance of considering the influence of sex when analyzing neurophysiological data in children with FASD.

Macromolecular networks and intelligence in microorganisms

PubMed Central

Westerhoff, Hans V.; Brooks, Aaron N.; Simeonidis, Evangelos; García-Contreras, Rodolfo; He, Fei; Boogerd, Fred C.; Jackson, Victoria J.; Goncharuk, Valeri; Kolodkin, Alexey

2014-01-01

Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity – particularly activity of the human brain – with a phenomenon we call “intelligence.” Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as “human” and “brain” out of the defining features of “intelligence,” all forms of life – from microbes to humans – exhibit some or all characteristics consistent with “intelligence.” We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo. PMID:25101076

Ketamine: differential neurophysiological dynamics in functional networks in the rat brain

PubMed Central

Ahnaou, A; Huysmans, H; Biermans, R; Manyakov, N V; Drinkenburg, W H I M

2017-01-01

Recently, the N-methyl-d-aspartate-receptor (NMDAR) antagonist ketamine has emerged as a fast-onset mechanism to achieve antidepressant activity, whereas its psychomimetic, dissociative and amnestic effects have been well documented to pharmacologically model schizophrenia features in rodents. Sleep–wake architecture, neuronal oscillations and network connectivity are key mechanisms supporting brain plasticity and cognition, which are disrupted in mood disorders such as depression and schizophrenia. In rats, we investigated the dynamic effects of acute and chronic subcutaneous administration of ketamine (2.5, 5 and 10 mg kg−1) on sleep–wake cycle, multichannels network interactions assessed by coherence and phase–amplitude cross-frequency coupling, locomotor activity (LMA), cognitive information processing as reflected by the mismatch negativity-like (MMN) component of event-related brain potentials (ERPs). Acute ketamine elicited a short, lasting inhibition of rapid eye movement (REM) sleep, increased coherence in higher gamma frequency oscillations independent of LMA, altered theta-gamma phase–amplitude coupling, increased MMN peak-amplitude response and evoked higher gamma oscillations. In contrast, chronic ketamine reduced large-scale communication among cortical regions by decreasing oscillations and coherent activity in the gamma frequency range, shifted networks activity towards slow alpha rhythm, decreased MMN peak response and enhanced aberrant higher gamma neuronal network oscillations. Altogether, our data show that acute and chronic ketamine elicited differential changes in network connectivity, ERPs and event-related oscillations (EROs), supporting possible underlying alterations in NMDAR–GABAergic signaling. The findings underscore the relevance of intermittent dosing of ketamine to accurately maintain the functional integrity of neuronal networks for long-term plastic changes and therapeutic effect. PMID:28926001

Ways of making-sense: Local gamma synchronization reveals differences between semantic processing induced by music and language.

PubMed

Barraza, Paulo; Chavez, Mario; Rodríguez, Eugenio

2016-01-01

Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing. Copyright © 2015 Elsevier Inc. All rights reserved.

A Brain-wide Circuit Model of Heat-Evoked Swimming Behavior in Larval Zebrafish.

PubMed

Haesemeyer, Martin; Robson, Drew N; Li, Jennifer M; Schier, Alexander F; Engert, Florian

2018-05-16

Thermosensation provides crucial information, but how temperature representation is transformed from sensation to behavior is poorly understood. Here, we report a preparation that allows control of heat delivery to zebrafish larvae while monitoring motor output and imaging whole-brain calcium signals, thereby uncovering algorithmic and computational rules that couple dynamics of heat modulation, neural activity and swimming behavior. This approach identifies a critical step in the transformation of temperature representation between the sensory trigeminal ganglia and the hindbrain: A simple sustained trigeminal stimulus representation is transformed into a representation of absolute temperature as well as temperature changes in the hindbrain that explains the observed motor output. An activity constrained dynamic circuit model captures the most prominent aspects of these sensori-motor transformations and predicts both behavior and neural activity in response to novel heat stimuli. These findings provide the first algorithmic description of heat processing from sensory input to behavioral output. Copyright © 2018 Elsevier Inc. All rights reserved.

Neuronal Representation of Social Information in the Medial Amygdala of Awake Behaving Mice.

PubMed

Li, Ying; Mathis, Alexander; Grewe, Benjamin F; Osterhout, Jessica A; Ahanonu, Biafra; Schnitzer, Mark J; Murthy, Venkatesh N; Dulac, Catherine

2017-11-16

The medial amygdala (MeA) plays a critical role in processing species- and sex-specific signals that trigger social and defensive behaviors. However, the principles by which this deep brain structure encodes social information is poorly understood. We used a miniature microscope to image the Ca 2+ dynamics of large neural ensembles in awake behaving mice and tracked the responses of MeA neurons over several months. These recordings revealed spatially intermingled subsets of MeA neurons with distinct temporal dynamics. The encoding of social information in the MeA differed between males and females and relied on information from both individual cells and neuronal populations. By performing long-term Ca 2+ imaging across different social contexts, we found that sexual experience triggers lasting and sex-specific changes in MeA activity, which, in males, involve signaling by oxytocin. These findings reveal basic principles underlying the brain's representation of social information and its modulation by intrinsic and extrinsic factors. Copyright © 2017 Elsevier Inc. All rights reserved.

Profiling neuronal ion channelopathies with non-invasive brain imaging and dynamic causal models: Case studies of single gene mutations

PubMed Central

Gilbert, Jessica R.; Symmonds, Mkael; Hanna, Michael G.; Dolan, Raymond J.; Friston, Karl J.; Moran, Rosalyn J.

2016-01-01

Clinical assessments of brain function rely upon visual inspection of electroencephalographic waveform abnormalities in tandem with functional magnetic resonance imaging. However, no current technology proffers in vivo assessments of activity at synapses, receptors and ion-channels, the basis of neuronal communication. Using dynamic causal modeling we compared electrophysiological responses from two patients with distinct monogenic ion channelopathies and a large cohort of healthy controls to demonstrate the feasibility of assaying synaptic-level channel communication non-invasively. Synaptic channel abnormality was identified in both patients (100% sensitivity) with assay specificity above 89%, furnishing estimates of neurotransmitter and voltage-gated ion throughput of sodium, calcium, chloride and potassium. This performance indicates a potential novel application as an adjunct for clinical assessments in neurological and psychiatric settings. More broadly, these findings indicate that biophysical models of synaptic channels can be estimated non-invasively, having important implications for advancing human neuroimaging to the level of non-invasive ion channel assays. PMID:26342528

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

PubMed

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

2018-06-07

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

Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain

PubMed Central

Kim, Christina K; Yang, Samuel J; Pichamoorthy, Nandini; Young, Noah P; Kauvar, Isaac; Jennings, Joshua H; Lerner, Talia N; Berndt, Andre; Lee, Soo Yeun; Ramakrishnan, Charu; Davidson, Thomas J; Inoue, Masatoshi; Bito, Haruhiko; Deisseroth, Karl

2017-01-01

Real-time activity measurements from multiple specific cell populations and projections are likely to be important for understanding the brain as a dynamical system. Here we developed frame-projected independent-fiber photometry (FIP), which we used to record fluorescence activity signals from many brain regions simultaneously in freely behaving mice. We explored the versatility of the FIP microscope by quantifying real-time activity relationships among many brain regions during social behavior, simultaneously recording activity along multiple axonal pathways during sensory experience, performing simultaneous two-color activity recording, and applying optical perturbation tuned to elicit dynamics that match naturally occurring patterns observed during behavior. PMID:26878381

A pilot study using dynamic contrast enhanced-MRI as a response biomarker of the radioprotective effect of memantine in patients receiving whole brain radiotherapy

PubMed Central

Wong, Philip; Leppert, Ilana R.; Roberge, David; Boudam, Karim; Brown, Paul D.; Muanza, Thierry; Pike, G. Bruce; Chankowsky, Jeffrey; Mihalcioiu, Catalin

2016-01-01

Purpose This pilot prospective study sought to determine whether dynamic contrast enhanced MRI (DCE-MRI) could be used as a clinical imaging biomarker of tissue toxicity from whole brain radiotherapy (WBRT). Method 14 patients who received WBRT were imaged using dynamic contrast enhanced DCE-MRI prior to and at 8-weeks, 16-weeks and 24-weeks after the initiation of WBRT. Twelve of the patients were also enrolled in the RTOG 0614 trial, which randomized patients to the use of placebo or memantine. After the unblinding of the treatments received by RTOG 0614 patients, DCE-MRI measures of tumor tissue and normal appearing white matter (NAWM) vascular permeability (Initial Area Under the Curve (AUC) Blood Adjusted) was analyzed. Cognitive, quality-of-life (QOL) assessment and blood samples were collected according to the patient's ability to tolerate the exams. Circulating endothelial cells (CEC) were measured using flow cytometry. Results Following WBRT, there was an increasing trend in the vascular permeability of tumors (p=0.09) and NAWM (p=0.06) with time. Memantine significantly (p=0.01) reduced NAWM AUC changes following radiotherapy. Patients on memantine retained (COWA p= 0.03) better cognitive functions than those on placebo. No association was observed between the level of CEC and DCE-MRI changes, time from radiotherapy or memantine use. Conclusions DCE-MRI can detect vascular damage secondary to WBRT. Our data suggests that memantine reduces WBRT-induced brain vasculature damages. PMID:27248467

Computational Approaches to Spatial Orientation: From Transfer Functions to Dynamic Bayesian Inference

PubMed Central

MacNeilage, Paul R.; Ganesan, Narayan; Angelaki, Dora E.

2008-01-01

Spatial orientation is the sense of body orientation and self-motion relative to the stationary environment, fundamental to normal waking behavior and control of everyday motor actions including eye movements, postural control, and locomotion. The brain achieves spatial orientation by integrating visual, vestibular, and somatosensory signals. Over the past years, considerable progress has been made toward understanding how these signals are processed by the brain using multiple computational approaches that include frequency domain analysis, the concept of internal models, observer theory, Bayesian theory, and Kalman filtering. Here we put these approaches in context by examining the specific questions that can be addressed by each technique and some of the scientific insights that have resulted. We conclude with a recent application of particle filtering, a probabilistic simulation technique that aims to generate the most likely state estimates by incorporating internal models of sensor dynamics and physical laws and noise associated with sensory processing as well as prior knowledge or experience. In this framework, priors for low angular velocity and linear acceleration can explain the phenomena of velocity storage and frequency segregation, both of which have been modeled previously using arbitrary low-pass filtering. How Kalman and particle filters may be implemented by the brain is an emerging field. Unlike past neurophysiological research that has aimed to characterize mean responses of single neurons, investigations of dynamic Bayesian inference should attempt to characterize population activities that constitute probabilistic representations of sensory and prior information. PMID:18842952

A pilot study using dynamic contrast enhanced-MRI as a response biomarker of the radioprotective effect of memantine in patients receiving whole brain radiotherapy.

PubMed

Wong, Philip; Leppert, Ilana R; Roberge, David; Boudam, Karim; Brown, Paul D; Muanza, Thierry; Pike, G Bruce; Chankowsky, Jeffrey; Mihalcioiu, Catalin

2016-08-09

This pilot prospective study sought to determine whether dynamic contrast enhanced MRI (DCE-MRI) could be used as a clinical imaging biomarker of tissue toxicity from whole brain radiotherapy (WBRT). 14 patients who received WBRT were imaged using dynamic contrast enhanced DCE-MRI prior to and at 8-weeks, 16-weeks and 24-weeks after the initiation of WBRT. Twelve of the patients were also enrolled in the RTOG 0614 trial, which randomized patients to the use of placebo or memantine. After the unblinding of the treatments received by RTOG 0614 patients, DCE-MRI measures of tumor tissue and normal appearing white matter (NAWM) vascular permeability (Initial Area Under the Curve (AUC) Blood Adjusted) was analyzed. Cognitive, quality-of-life (QOL) assessment and blood samples were collected according to the patient's ability to tolerate the exams. Circulating endothelial cells (CEC) were measured using flow cytometry. Following WBRT, there was an increasing trend in the vascular permeability of tumors (p=0.09) and NAWM (p=0.06) with time. Memantine significantly (p=0.01) reduced NAWM AUC changes following radiotherapy. Patients on memantine retained (COWA p= 0.03) better cognitive functions than those on placebo. No association was observed between the level of CEC and DCE-MRI changes, time from radiotherapy or memantine use. DCE-MRI can detect vascular damage secondary to WBRT. Our data suggests that memantine reduces WBRT-induced brain vasculature damages.

Neural dynamics in motor preparation: From phase-mediated global computation to amplitude-mediated local computation.

PubMed

Kajihara, Takafumi; Anwar, Muhammad Nabeel; Kawasaki, Masahiro; Mizuno, Yuji; Nakazawa, Kimitaka; Kitajo, Keiichi

2015-09-01

Oscillatory activity plays a critical role in the brain. Here, we illustrate the dynamics of neural oscillations in the motor system of the brain. We used a non-directional cue to instruct participants to prepare a motor response with either the left or the right hand and recorded electroencephalography during the preparation of the response. Consistent with previous findings, the amplitude of alpha-band (8-14Hz) oscillations significantly decreased over the motor region contralateral to the hand prepared for the response. Prior to this decrease, there were a number of inter-regional phase synchronies at lower frequencies (2-4Hz; delta band). Cross-frequency coupling was quantified to further explore the direct link between alpha amplitudes and delta synchrony. The cross-frequency coupling of showed response-specific modulation, whereby the motor region contralateral to the preparation hand exhibited an increase in coupling relative to the baseline. The amplitude of alpha oscillations had an unpreferred and a preferred delta phase, in which the amplitude was modulated negatively and positively, respectively. Given the amplitude of alpha-band oscillations decreased over the analyzed period, the alpha amplitude might be down-regulated by the phase-amplitude coupling, although we do not have direct evidence for that. Taken together, these results show global-to-local computation in the motor system, which started from inter-regional delta phase synchrony and ended at an effector-specific decrease in the amplitude of alpha-band oscillations, with phase-amplitude coupling connecting both computations. Copyright © 2015. Published by Elsevier Inc.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer.

PubMed

Roberts, James A; Friston, Karl J; Breakspear, Michael

2017-04-01

Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs). This article, Part I of a two-part series, offers a primer of SDMs and their application to large-scale neural systems in health and disease. The companion article, Part II, reviews the application of SDMs to brain disorders. SDMs generate a distribution of dynamic states, which (we argue) represent ideal candidates for modeling how the brain represents states of the world. When augmented with variational methods for model inversion, SDMs represent a powerful means of inferring neuronal dynamics from functional neuroimaging data in health and disease. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Why don't you like me? Midfrontal theta power in response to unexpected peer rejection feedback.

PubMed

van der Molen, M J W; Dekkers, L M S; Westenberg, P M; van der Veen, F M; van der Molen, M W

2017-02-01

Social connectedness theory posits that the brain processes social rejection as a threat to survival. Recent electrophysiological evidence suggests that midfrontal theta (4-8Hz) oscillations in the EEG provide a window on the processing of social rejection. Here we examined midfrontal theta dynamics (power and inter-trial phase synchrony) during the processing of social evaluative feedback. We employed the Social Judgment paradigm in which 56 undergraduate women (mean age=19.67 years) were asked to communicate their expectancies about being liked vs. disliked by unknown peers. Expectancies were followed by feedback indicating social acceptance vs. rejection. Results revealed a significant increase in EEG theta power to unexpected social rejection feedback. This EEG theta response could be source-localized to brain regions typically reported during activation of the saliency network (i.e., dorsal anterior cingulate cortex, insula, inferior frontal gyrus, frontal pole, and the supplementary motor area). Theta phase dynamics mimicked the behavior of the time-domain averaged feedback-related negativity (FRN) by showing stronger phase synchrony for feedback that was unexpected vs. expected. Theta phase, however, differed from the FRN by also displaying stronger phase synchrony in response to rejection vs. acceptance feedback. Together, this study highlights distinct roles for midfrontal theta power and phase synchrony in response to social evaluative feedback. Our findings contribute to the literature by showing that midfrontal theta oscillatory power is sensitive to social rejection but only when peer rejection is unexpected, and this theta response is governed by a widely distributed neural network implicated in saliency detection and conflict monitoring. Copyright © 2016 Elsevier Inc. All rights reserved.

[Effect of space flight factors simulated in ground-based experiments on the behavior, discriminant learning, and exchange of monoamines in different brain structures of rats].

PubMed

Shtemberg, A S; Lebedeva-Georgievskaia, K V; Matveeva, M I; Kudrin, V S; Narkevich, V B; Klodt, P M; Bazian, A S

2014-01-01

Experimental treatment (long-term fractionated γ-irradiation, antiorthostatic hypodynamia, and the combination of these factors) simulating the effect of space flight in ground-based experiments rapidly restored the motor and orienting-investigative activity of animals (rats) in "open-field" tests. The study of the dynamics of discriminant learning of rats of experimental groups did not show significant differences from the control animals. It was found that the minor effect of these factors on the cognitive performance of animals correlated with slight changes in the concentration ofmonoamines in the brain structures responsible for the cognitive, emotional, and motivational functions.

Neural predictors of emotional inertia in daily life.

PubMed

Waugh, Christian E; Shing, Elaine Z; Avery, Bradley M; Jung, Youngkyoo; Whitlow, Christopher T; Maldjian, Joseph A

2017-09-01

Assessing emotional dynamics in the brain offers insight into the fundamental neural and psychological mechanisms underlying emotion. One such dynamic is emotional inertia-the influence of one's emotional state at one time point on one's emotional state at a subsequent time point. Emotion inertia reflects emotional rigidity and poor emotion regulation as evidenced by its relationship to depression and neuroticism. In this study, we assessed changes in cerebral blood flow (CBF) from before to after an emotional task and used these changes to predict stress, positive and negative emotional inertia in daily life events. Cerebral blood flow changes in the lateral prefrontal cortex (lPFC) predicted decreased non-specific emotional inertia, suggesting that the lPFC may feature a general inhibitory mechanism responsible for limiting the impact that an emotional state from one event has on the emotional state of a subsequent event. CBF changes in the ventromedial prefrontal cortex and lateral occipital cortex were associated with positive emotional inertia and negative/stress inertia, respectively. These data advance the blossoming literature on the temporal dynamics of emotion in the brain and on the use of neural indices to predict mental health-relevant behavior in daily life. © The Author (2017). Published by Oxford University Press.

Neural predictors of emotional inertia in daily life

PubMed Central

Shing, Elaine Z.; Avery, Bradley M.; Jung, Youngkyoo; Whitlow, Christopher T.; Maldjian, Joseph A.

2017-01-01

Abstract Assessing emotional dynamics in the brain offers insight into the fundamental neural and psychological mechanisms underlying emotion. One such dynamic is emotional inertia—the influence of one’s emotional state at one time point on one’s emotional state at a subsequent time point. Emotion inertia reflects emotional rigidity and poor emotion regulation as evidenced by its relationship to depression and neuroticism. In this study, we assessed changes in cerebral blood flow (CBF) from before to after an emotional task and used these changes to predict stress, positive and negative emotional inertia in daily life events. Cerebral blood flow changes in the lateral prefrontal cortex (lPFC) predicted decreased non-specific emotional inertia, suggesting that the lPFC may feature a general inhibitory mechanism responsible for limiting the impact that an emotional state from one event has on the emotional state of a subsequent event. CBF changes in the ventromedial prefrontal cortex and lateral occipital cortex were associated with positive emotional inertia and negative/stress inertia, respectively. These data advance the blossoming literature on the temporal dynamics of emotion in the brain and on the use of neural indices to predict mental health-relevant behavior in daily life. PMID:28992272

From synthetic modeling of social interaction to dynamic theories of brain-body-environment-body-brain systems.

PubMed

Froese, Tom; Iizuka, Hiroyuki; Ikegami, Takashi

2013-08-01

Synthetic approaches to social interaction support the development of a second-person neuroscience. Agent-based models and psychological experiments can be related in a mutually informing manner. Models have the advantage of making the nonlinear brain-body-environment-body-brain system as a whole accessible to analysis by dynamical systems theory. We highlight some general principles of how social interaction can partially constitute an individual's behavior.

Large-scale coupling dynamics of instructed reversal learning.

PubMed

Mohr, Holger; Wolfensteller, Uta; Ruge, Hannes

2018-02-15

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of finite spatial resolution on quantitative CBF images from dynamic PET

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

Phelps, M.E.; Huang, S.C.; Mahoney, D.K.

1985-05-01

The finite spatial resolution of PET causes the time-activity responses on pixels around the boundaries between gray and white matter regions to contain kinetic components from tissues of different CBF's. CBF values estimated from kinetics of such mixtures are underestimated because of the nonlinear relationship between the time-activity response and the estimated CBF. Computer simulation is used to investigate these effects on phantoms of circular structures and realistic brain slice in terms of object size and quantitative CBF values. The CBF image calculated is compared to the case of having resolution loss alone. Results show that the size of amore » high flow region in the CBF image is decreased while that of a low flow region is increased. For brain phantoms, the qualitative appearance of CBF images is not seriously affected, but the estimated CBF's are underestimated by 11 to 16 percent in local gray matter regions (of size 1 cm/sup 2/) with about 14 percent reduction in global CBF over the whole slice. It is concluded that the combined effect of finite spatial resolution and the nonlinearity in estimating CBF from dynamic PET is quite significant and must be considered in processing and interpreting quantitative CBF images.« less

Discontinuous Patterns of Brain Activation in the Psychotherapy Process of Obsessive-Compulsive Disorder: Converging Results from Repeated fMRI and Daily Self-Reports

PubMed Central

Schiepek, Günter; Tominschek, Igor; Heinzel, Stephan; Aigner, Martin; Dold, Markus; Unger, Annemarie; Lenz, Gerhard; Windischberger, Christian; Moser, Ewald; Plöderl, Martin; Lutz, Jürgen; Meindl, Thomas; Zaudig, Michael; Pogarell, Oliver; Karch, Susanne

2013-01-01

This study investigates neuronal activation patterns during the psychotherapeutic process, assuming that change dynamics undergo critical instabilities and discontinuous transitions. An internet-based system was used to collect daily self-assessments during inpatient therapies. A dynamic complexity measure was applied to the resulting time series. Critical phases of the change process were indicated by the maxima of the varying complexity. Repeated functional magnetic resonance imaging (fMRI) measurements were conducted over the course of the therapy. The study was realized with 9 patients suffering from obsessive-compulsive disorder (subtype: washing/contamination fear) and 9 matched healthy controls. For symptom-provocative stimulation individualized pictures from patients’ personal environments were used. The neuronal responses to these disease-specific pictures were compared to the responses during standardized disgust-provoking and neutral pictures. Considerably larger neuronal changes in therapy-relevant brain areas (cingulate cortex/supplementary motor cortex, bilateral dorsolateral prefrontal cortex, bilateral insula, bilateral parietal cortex, cuneus) were observed during critical phases (order transitions), as compared to non-critical phases, and also compared to healthy controls. The data indicate that non-stationary changes play a crucial role in the psychotherapeutic process supporting self-organization and complexity models of therapeutic change. PMID:23977168

Dynamics of the brain: Mathematical models and non-invasive experimental studies

NASA Astrophysics Data System (ADS)

Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.

2013-10-01

Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.

Maintenance of Gastrointestinal Glucose Homeostasis by the Gut-Brain Axis.

PubMed

Chen, Xiyue; Eslamfam, Shabnam; Fang, Luoyun; Qiao, Shiyan; Ma, Xi

2017-01-01

Gastrointestinal homeostasis is a dynamic balance under the interaction between the host, GI tract, nutrition and energy metabolism. Glucose is the main energy source in living cells. Thus, glucose metabolic disorders can impair normal cellular function and endanger organisms' health. Diseases that are associated with glucose metabolic disorders such as obesity, diabetes, hypertension, and other metabolic syndromes are in fact life threatening. Digestive system is responsible for food digestion and nutrient absorption. It is also involved in neuronal, immune, and endocrine pathways. In addition, the gut microbiota plays an essential role in initiating signal transduction, and communication between the enteric and central nervous system. Gut-brain axis is composed of enteric neural system, central neural system, and all the efferent and afferent neurons that are involved in signal transduction between the brain and gut-brain. Gut-brain axis is influenced by the gut-microbiota as well as numerous neurotransmitters. Properly regulated gut-brain axis ensures normal digestion, absorption, energy production, and subsequently maintenance of glucose homeostasis. Understanding the underlying regulatory mechanisms of gut-brain axis involved in gluose homeostasis would enable us develop more efficient means of prevention and management of metabolic disease such as diabetic, obesity, and hypertension. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Mother-infant interactions and regional brain volumes in infancy: an MRI study.

PubMed

Sethna, Vaheshta; Pote, Inês; Wang, Siying; Gudbrandsen, Maria; Blasi, Anna; McCusker, Caroline; Daly, Eileen; Perry, Emily; Adams, Kerrie P H; Kuklisova-Murgasova, Maria; Busuulwa, Paula; Lloyd-Fox, Sarah; Murray, Lynne; Johnson, Mark H; Williams, Steven C R; Murphy, Declan G M; Craig, Michael C; McAlonan, Grainne M

2017-07-01

It is generally agreed that the human brain is responsive to environmental influences, and that the male brain may be particularly sensitive to early adversity. However, this is largely based on retrospective studies of older children and adolescents exposed to extreme environments in childhood. Less is understood about how normative variations in parent-child interactions are associated with the development of the infant brain in typical settings. To address this, we used magnetic resonance imaging to investigate the relationship between observational measures of mother-infant interactions and regional brain volumes in a community sample of 3- to 6-month-old infants (N = 39). In addition, we examined whether this relationship differed in male and female infants. We found that lower maternal sensitivity was correlated with smaller subcortical grey matter volumes in the whole sample, and that this was similar in both sexes. However, male infants who showed greater levels of positive communication and engagement during early interactions had smaller cerebellar volumes. These preliminary findings suggest that variations in mother-infant interaction dimensions are associated with differences in infant brain development. Although the study is cross-sectional and causation cannot be inferred, the findings reveal a dynamic interaction between brain and environment that may be important when considering interventions to optimize infant outcomes.

[Disturbances of cerebral perfusion in patients with bacterial meningoencephalitis].

PubMed

Garlicki, Aleksander; Podsiadło-Kleinrok, Beata; Bociaga-Jasik, Monika; Kleinrok, Krzysztof; Tomik, Barbara

2003-01-01

The investigations were done in acute and reconvalescent phase in 34 patients with bacterial meningoencephalitis. Neurologic condition, degree of the brain injury on the basis of Glasgow Coma Scale (GCS), protein level and pleocytosis in cerebrospinal fluid (CSF), and regional cerebral blood flow on dynamic computed tomography (CT) were assessed. The brain blood flow was measured in the white matter of the frontal and occipital horns of lateral ventricles, symmetrically in both hemispheres. Statistically significant reduction of the brain perfusion in acute phase of illness was improved. In reconvalescent phase normalisation of the brain blood supply was observed. 56% of patients had changes of consciousness. There was no significant correlation between these symptoms and parameters describing blood supply. The rest of patients had neurologic abnormalities: seizure, pyramidal syndrome, injury of the central nerves due to the reduction of blood flow in selected regions of the brain. Patients who aggregated low GCS score had high inflow of the blood. In patients who were in better condition, inflow was smaller. High pleocytosis in CSF was associated with small blood inflow and perfusion in investigated regions of the brain. Whereas high protein concentration correlated with higher inflow and increase in regional perfusion. We consider, that the brain blood supply correlate with intensification of inflammatory response in CSF.

Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble.

PubMed

Jolivet, Renaud; Coggan, Jay S; Allaman, Igor; Magistretti, Pierre J

2015-02-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

EEG-Based Quantification of Cortical Current Density and Dynamic Causal Connectivity Generalized across Subjects Performing BCI-Monitored Cognitive Tasks

PubMed Central

Courellis, Hristos; Mullen, Tim; Poizner, Howard; Cauwenberghs, Gert; Iversen, John R.

2017-01-01

Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a “reach/saccade to spatial target” cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI. PMID:28566997

Robust Transient Dynamics and Brain Functions

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo

2011-01-01

In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques) has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc., have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework – heteroclinic sequential dynamics – to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i) within the same modality, (ii) among different modalities from the same family (like perception), and (iii) among modalities from different families (like emotion and cognition). The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory – a vital cognitive function –, and to find specific dynamical signatures – different kinds of instabilities – of several brain functions and mental diseases. PMID:21716642

Inflammation and white matter degeneration persist for years after a single traumatic brain injury.

PubMed

Johnson, Victoria E; Stewart, Janice E; Begbie, Finn D; Trojanowski, John Q; Smith, Douglas H; Stewart, William

2013-01-01

A single traumatic brain injury is associated with an increased risk of dementia and, in a proportion of patients surviving a year or more from injury, the development of hallmark Alzheimer's disease-like pathologies. However, the pathological processes linking traumatic brain injury and neurodegenerative disease remain poorly understood. Growing evidence supports a role for neuroinflammation in the development of Alzheimer's disease. In contrast, little is known about the neuroinflammatory response to brain injury and, in particular, its temporal dynamics and any potential role in neurodegeneration. Cases of traumatic brain injury with survivals ranging from 10 h to 47 years post injury (n = 52) and age-matched, uninjured control subjects (n = 44) were selected from the Glasgow Traumatic Brain Injury archive. From these, sections of the corpus callosum and adjacent parasaggital cortex were examined for microglial density and morphology, and for indices of white matter pathology and integrity. With survival of ≥3 months from injury, cases with traumatic brain injury frequently displayed extensive, densely packed, reactive microglia (CR3/43- and/or CD68-immunoreactive), a pathology not seen in control subjects or acutely injured cases. Of particular note, these reactive microglia were present in 28% of cases with survival of >1 year and up to 18 years post-trauma. In cases displaying this inflammatory pathology, evidence of ongoing white matter degradation could also be observed. Moreover, there was a 25% reduction in the corpus callosum thickness with survival >1 year post-injury. These data present striking evidence of persistent inflammation and ongoing white matter degeneration for many years after just a single traumatic brain injury in humans. Future studies to determine whether inflammation occurs in response to or, conversely, promotes white matter degeneration will be important. These findings may provide parallels for studying neurodegenerative disease, with traumatic brain injury patients serving as a model for longitudinal investigations, in particular with a view to identifying potential therapeutic interventions.

[Three-dimensional reconstruction of functional brain images].

PubMed

Inoue, M; Shoji, K; Kojima, H; Hirano, S; Naito, Y; Honjo, I

1999-08-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: 1) routine images by SPM, 2) three-dimensional static images, and 3) three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface model is the most common method of three-dimensional display. However, the volume rendering method may be more effective for imaging regions such as the brain.

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

PubMed

Hari, Riitta

2017-06-07

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

The dynamic development of the muzzle imprint by contact gunshot: high-speed documentation utilizing the "skin-skull-brain model".

PubMed

Thali, M J; Kneubuehl, B P; Dirnhofer, R; Zollinger, U

2002-07-17

Many contact gunshots produce a muzzle imprint in the skin of the victim. Different mechanisms have been discussed in literature as being responsible for the creation of the muzzle imprint. Experimenting upon the synthetic non biological skin-skull-brain model, our goal was to document and study the creation of the muzzle imprint with the aid of high-speed photography. In our experiments, we could document with our high-speed photography (at exposure rates in the range of nanoseconds) the bulging, the pressing against the muzzle, and the splitting of the artificial skin. Furthermore, it was possible to photographically record the back pattern of synthetic tissue particles. And, the soot and gunpowder cavity could be reproduced experimentally. In conclusion the experiments completed with the skin-skull-brain model, using high-speed photography for documentation, show the promising possibilities of experimental ballistics with body models.

Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

PubMed

Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

2014-01-01

Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.

Sleep is not just for the brain: transcriptional responses to sleep in peripheral tissues.

PubMed

Anafi, Ron C; Pellegrino, Renata; Shockley, Keith R; Romer, Micah; Tufik, Sergio; Pack, Allan I

2013-05-30

Many have assumed that the primary function of sleep is for the brain. We evaluated the molecular consequences of sleep and sleep deprivation outside the brain, in heart and lung. Using microarrays we compared gene expression in tissue from sleeping and sleep deprived mice euthanized at the same diurnal times. In each tissue, nearly two thousand genes demonstrated statistically significant differential expression as a function of sleep/wake behavioral state. To mitigate the influence of an artificial deprivation protocol, we identified a subset of these transcripts as specifically sleep-enhanced or sleep-repressed by requiring that their expression also change over the course of unperturbed sleep. 3% and 6% of the assayed transcripts showed "sleep specific" changes in the lung and heart respectively. Sleep specific transcripts in these tissues demonstrated highly significant overlap and shared temporal dynamics. Markers of cellular stress and the unfolded protein response were reduced during sleep in both tissues. These results mirror previous findings in brain. Sleep-enhanced pathways reflected the unique metabolic functions of each tissue. Transcripts related to carbohydrate and sulfur metabolic processes were enhanced by sleep in the lung, and collectively favor buffering from oxidative stress. DNA repair and protein metabolism annotations were significantly enriched among the sleep-enhanced transcripts in the heart. Our results also suggest that sleep may provide a Zeitgeber, or synchronizing cue, in the lung as a large cluster of transcripts demonstrated systematic changes in inter-animal variability as a function of both sleep duration and circadian time. Our data support the notion that the molecular consequences of sleep/wake behavioral state extend beyond the brain to include peripheral tissues. Sleep state induces a highly overlapping response in both heart and lung. We conclude that sleep enhances organ specific molecular functions and that it has a ubiquitous role in reducing cellular metabolic stress in both brain and peripheral tissues. Finally, our data suggest a novel role for sleep in synchronizing transcription in peripheral tissues.

Neural dynamics in Parkinsonian brain: The boundary between synchronized and nonsynchronized dynamics

NASA Astrophysics Data System (ADS)

Park, Choongseok; Worth, Robert M.; Rubchinsky, Leonid L.

2011-04-01

Synchronous oscillatory dynamics is frequently observed in the human brain. We analyze the fine temporal structure of phase-locking in a realistic network model and match it with the experimental data from Parkinsonian patients. We show that the experimentally observed intermittent synchrony can be generated just by moderately increased coupling strength in the basal ganglia circuits due to the lack of dopamine. Comparison of the experimental and modeling data suggest that brain activity in Parkinson's disease resides in the large boundary region between synchronized and nonsynchronized dynamics. Being on the edge of synchrony may allow for easy formation of transient neuronal assemblies.

Brain State Is a Major Factor in Preseizure Hippocampal Network Activity and Influences Success of Seizure Intervention

PubMed Central

Ewell, Laura A.; Liang, Liang; Armstrong, Caren; Soltész, Ivan; Leutgeb, Stefan

2015-01-01

Neural dynamics preceding seizures are of interest because they may shed light on mechanisms of seizure generation and could be predictive. In healthy animals, hippocampal network activity is shaped by behavioral brain state and, in epilepsy, seizures selectively emerge during specific brain states. To determine the degree to which changes in network dynamics before seizure are pathological or reflect ongoing fluctuations in brain state, dorsal hippocampal neurons were recorded during spontaneous seizures in a rat model of temporal lobe epilepsy. Seizures emerged from all brain states, but with a greater likelihood after REM sleep, potentially due to an observed increase in baseline excitability during periods of REM compared with other brains states also characterized by sustained theta oscillations. When comparing the firing patterns of the same neurons across brain states associated with and without seizures, activity dynamics before seizures followed patterns typical of the ongoing brain state, or brain state transitions, and did not differ until the onset of the electrographic seizure. Next, we tested whether disparate activity patterns during distinct brain states would influence the effectiveness of optogenetic curtailment of hippocampal seizures in a mouse model of temporal lobe epilepsy. Optogenetic curtailment was significantly more effective for seizures preceded by non-theta states compared with seizures that emerged from theta states. Our results indicate that consideration of behavioral brain state preceding a seizure is important for the appropriate interpretation of network dynamics leading up to a seizure and for designing effective seizure intervention. SIGNIFICANCE STATEMENT Hippocampal single-unit activity is strongly shaped by behavioral brain state, yet this relationship has been largely ignored when studying activity dynamics before spontaneous seizures in medial temporal lobe epilepsy. In light of the increased attention on using single-unit activity for the prediction of seizure onset and closed-loop seizure intervention, we show a need for monitoring brain state to interpret correctly whether changes in neural activity before seizure onset is pathological or normal. Moreover, we also find that the brain state preceding a seizure determines the success of therapeutic interventions to curtail seizure duration. Together, these findings suggest that seizure prediction and intervention will be more successful if tailored for the specific brain states from which seizures emerge. PMID:26609157

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition

PubMed Central

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A.

2016-01-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. PMID:26209846

Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model.

PubMed

Wang, Fang; Han, Yong; Wang, Bingyu; Peng, Qian; Huang, Xiaoqun; Miller, Karol; Wittek, Adam

2018-05-12

In this study, we investigate the effects of modelling choices for the brain-skull interface (layers of tissues between the brain and skull that determine boundary conditions for the brain) and the constitutive model of brain parenchyma on the brain responses under violent impact as predicted using computational biomechanics model. We used the head/brain model from Total HUman Model for Safety (THUMS)-extensively validated finite element model of the human body that has been applied in numerous injury biomechanics studies. The computations were conducted using a well-established nonlinear explicit dynamics finite element code LS-DYNA. We employed four approaches for modelling the brain-skull interface and four constitutive models for the brain tissue in the numerical simulations of the experiments on post-mortem human subjects exposed to violent impacts reported in the literature. The brain-skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney-Rivlin hyperviscoelastic, neo-Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain-skull interface and the constitutive model of the brain parenchyma tissues. The results suggest that accurate prediction of deformations within the brain and risk of brain injury due to violent impact using computational biomechanics models may require representation of the meninges and subarachnoidal space with cerebrospinal fluid in the model and application of hyperviscoelastic (preferably Ogden-type) constitutive model for the brain tissue.

Neuroenergetic Response to Prolonged Cerebral Glucose Depletion after Severe Brain Injury and the Role of Lactate.

PubMed

Patet, Camille; Quintard, Hervé; Suys, Tamarah; Bloch, Jocelyne; Daniel, Roy T; Pellerin, Luc; Magistretti, Pierre J; Oddo, Mauro

2015-10-15

Lactate may represent a supplemental fuel for the brain. We examined cerebral lactate metabolism during prolonged brain glucose depletion (GD) in acute brain injury (ABI) patients monitored with cerebral microdialysis (CMD). Sixty episodes of GD (defined as spontaneous decreases of CMD glucose from normal to low [<1.0 mmol/L] for at least 2 h) were identified among 26 patients. During GD, we found a significant increase of CMD lactate (from 4 ± 2.3 to 5.4 ± 2.9 mmol/L), pyruvate (126.9 ± 65.1 to 172.3 ± 74.1 μmol/L), and lactate/pyruvate ratio (LPR; 27 ± 6 to 35 ± 9; all, p < 0.005), while brain oxygen and blood lactate remained normal. Dynamics of lactate and glucose supply during GD were further studied by analyzing the relationships between blood and CMD samples. There was a strong correlation between blood and brain lactate when LPR was normal (r = 0.56; p < 0.0001), while an inverse correlation (r = -0.11; p = 0.04) was observed at elevated LPR >25. The correlation between blood and brain glucose also decreased from r = 0.62 to r = 0.45. These findings in ABI patients suggest increased cerebral lactate delivery in the absence of brain hypoxia when glucose availability is limited and support the concept that lactate acts as alternative fuel.

Dynamical Principles of Emotion-Cognition Interaction: Mathematical Images of Mental Disorders

PubMed Central

Rabinovich, Mikhail I.; Muezzinoglu, Mehmet K.; Strigo, Irina; Bystritsky, Alexander

2010-01-01

The key contribution of this work is to introduce a mathematical framework to understand self-organized dynamics in the brain that can explain certain aspects of itinerant behavior. Specifically, we introduce a model based upon the coupling of generalized Lotka-Volterra systems. This coupling is based upon competition for common resources. The system can be regarded as a normal or canonical form for any distributed system that shows self-organized dynamics that entail winnerless competition. Crucially, we will show that some of the fundamental instabilities that arise in these coupled systems are remarkably similar to endogenous activity seen in the brain (using EEG and fMRI). Furthermore, by changing a small subset of the system's parameters we can produce bifurcations and metastable sequential dynamics changing, which bear a remarkable similarity to pathological brain states seen in psychiatry. In what follows, we will consider the coupling of two macroscopic modes of brain activity, which, in a purely descriptive fashion, we will label as cognitive and emotional modes. Our aim is to examine the dynamical structures that emerge when coupling these two modes and relate them tentatively to brain activity in normal and non-normal states. PMID:20877723

Dynamical principles of emotion-cognition interaction: mathematical images of mental disorders.

PubMed

Rabinovich, Mikhail I; Muezzinoglu, Mehmet K; Strigo, Irina; Bystritsky, Alexander

2010-09-21

The key contribution of this work is to introduce a mathematical framework to understand self-organized dynamics in the brain that can explain certain aspects of itinerant behavior. Specifically, we introduce a model based upon the coupling of generalized Lotka-Volterra systems. This coupling is based upon competition for common resources. The system can be regarded as a normal or canonical form for any distributed system that shows self-organized dynamics that entail winnerless competition. Crucially, we will show that some of the fundamental instabilities that arise in these coupled systems are remarkably similar to endogenous activity seen in the brain (using EEG and fMRI). Furthermore, by changing a small subset of the system's parameters we can produce bifurcations and metastable sequential dynamics changing, which bear a remarkable similarity to pathological brain states seen in psychiatry. In what follows, we will consider the coupling of two macroscopic modes of brain activity, which, in a purely descriptive fashion, we will label as cognitive and emotional modes. Our aim is to examine the dynamical structures that emerge when coupling these two modes and relate them tentatively to brain activity in normal and non-normal states.

Brain Tissue Responses to Neural Implants Impact Signal Sensitivity and Intervention Strategies

PubMed Central

2015-01-01

Implantable biosensors are valuable scientific tools for basic neuroscience research and clinical applications. Neurotechnologies provide direct readouts of neurological signal and neurochemical processes. These tools are generally most valuable when performance capacities extend over months and years to facilitate the study of memory, plasticity, and behavior or to monitor patients’ conditions. These needs have generated a variety of device designs from microelectrodes for fast scan cyclic voltammetry (FSCV) and electrophysiology to microdialysis probes for sampling and detecting various neurochemicals. Regardless of the technology used, the breaching of the blood–brain barrier (BBB) to insert devices triggers a cascade of biochemical pathways resulting in complex molecular and cellular responses to implanted devices. Molecular and cellular changes in the microenvironment surrounding an implant include the introduction of mechanical strain, activation of glial cells, loss of perfusion, secondary metabolic injury, and neuronal degeneration. Changes to the tissue microenvironment surrounding the device can dramatically impact electrochemical and electrophysiological signal sensitivity and stability over time. This review summarizes the magnitude, variability, and time course of the dynamic molecular and cellular level neural tissue responses induced by state-of-the-art implantable devices. Studies show that insertion injuries and foreign body response can impact signal quality across all implanted central nervous system (CNS) sensors to varying degrees over both acute (seconds to minutes) and chronic periods (weeks to months). Understanding the underlying biological processes behind the brain tissue response to the devices at the cellular and molecular level leads to a variety of intervention strategies for improving signal sensitivity and longevity. PMID:25546652

A comparative study of event-related coupling patterns during an auditory oddball task in schizophrenia

NASA Astrophysics Data System (ADS)

Bachiller, Alejandro; Poza, Jesús; Gómez, Carlos; Molina, Vicente; Suazo, Vanessa; Hornero, Roberto

2015-02-01

Objective. The aim of this research is to explore the coupling patterns of brain dynamics during an auditory oddball task in schizophrenia (SCH). Approach. Event-related electroencephalographic (ERP) activity was recorded from 20 SCH patients and 20 healthy controls. The coupling changes between auditory response and pre-stimulus baseline were calculated in conventional EEG frequency bands (theta, alpha, beta-1, beta-2 and gamma), using three coupling measures: coherence, phase-locking value and Euclidean distance. Main results. Our results showed a statistically significant increase from baseline to response in theta coupling and a statistically significant decrease in beta-2 coupling in controls. No statistically significant changes were observed in SCH patients. Significance. Our findings support the aberrant salience hypothesis, since SCH patients failed to change their coupling dynamics between stimulus response and baseline when performing an auditory cognitive task. This result may reflect an impaired communication among neural areas, which may be related to abnormal cognitive functions.

The functional integration of the anterior cingulate cortex during conflict processing.

PubMed

Fan, Jin; Hof, Patrick R; Guise, Kevin G; Fossella, John A; Posner, Michael I

2008-04-01

Although functional activation of the anterior cingulate cortex (ACC) related to conflict processing has been studied extensively, the functional integration of the subdivisions of the ACC and other brain regions during conditions of conflict is still unclear. In this study, participants performed a task designed to elicit conflict processing by using flanker interference on target response while they were scanned using event-related functional magnetic resonance imaging. The physiological response of several brain regions in terms of an interaction between conflict processing and activity of the anterior rostral cingulate zone (RCZa) of the ACC, and the effective connectivity between this zone and other regions were examined using psychophysiological interaction analysis and dynamic causal modeling, respectively. There was significant integration of the RCZa with the caudal cingulate zone (CCZ) of the ACC and other brain regions such as the lateral prefrontal, primary, and supplementary motor areas above and beyond the main effect of conflict and baseline connectivity. The intrinsic connectivity from the RCZa to the CCZ was modulated by the context of conflict. These findings suggest that conflict processing is associated with the effective contribution of the RCZa to the neuronal activity of CCZ, as well as other cortical regions.

Brain-peripheral cell crosstalk in white matter damage and repair.

PubMed

Hayakawa, Kazuhide; Lo, Eng H

2016-05-01

White matter damage is an important part of cerebrovascular disease and may be a significant contributing factor in vascular mechanisms of cognitive dysfunction and dementia. It is well accepted that white matter homeostasis involves multifactorial interactions between all cells in the axon-glia-vascular unit. But more recently, it has been proposed that beyond cell-cell signaling within the brain per se, dynamic crosstalk between brain and systemic responses such as circulating immune cells and stem/progenitor cells may also be important. In this review, we explore the hypothesis that peripheral cells contribute to damage and repair after white matter damage. Depending on timing, phenotype and context, monocyte/macrophage can possess both detrimental and beneficial effects on oligodendrogenesis and white matter remodeling. Endothelial progenitor cells (EPCs) can be activated after CNS injury and the response may also influence white matter repair process. These emerging findings support the hypothesis that peripheral-derived cells can be both detrimental or beneficial in white matter pathology in cerebrovascular disease. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia, edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock. Copyright © 2015 Elsevier B.V. All rights reserved.

Dynamic adjustments of cognitive control: oscillatory correlates of the conflict adaptation effect.

PubMed

Pastötter, Bernhard; Dreisbach, Gesine; Bäuml, Karl-Heinz T

2013-12-01

It is a prominent idea that cognitive control mediates conflict adaptation, in that response conflict in a previous trial triggers control adjustments that reduce conflict in a current trial. In the present EEG study, we investigated the dynamics of cognitive control in a response-priming task by examining the effects of previous trial conflict on intertrial and current trial oscillatory brain activities, both on the electrode and the source level. Behavioral results showed conflict adaptation effects for RTs and response accuracy. Physiological results showed sustained intertrial effects in left parietal theta power, originating in the left inferior parietal cortex, and midcentral beta power, originating in the left and right (pre)motor cortex. Moreover, physiological analysis revealed a current trial conflict adaptation effect in midfrontal theta power, originating in the ACC. Correlational analyses showed that intertrial effects predicted conflict-induced midfrontal theta power in currently incongruent trials. In addition, conflict adaptation effects in midfrontal theta power and RTs were positively related. Together, these findings point to a dynamic cognitive control system that, as a function of previous trial type, up- and down-regulates attention and preparatory motor activities in anticipation of the next trial.

Cognitive cost as dynamic allocation of energetic resources

PubMed Central

Christie, S. Thomas; Schrater, Paul

2015-01-01

While it is widely recognized that thinking is somehow costly, involving cognitive effort and producing mental fatigue, these costs have alternatively been assumed to exist, treated as the brain's assessment of lost opportunities, or suggested to be metabolic but with implausible biological bases. We present a model of cognitive cost based on the novel idea that the brain senses and plans for longer-term allocation of metabolic resources by purposively conserving brain activity. We identify several distinct ways the brain might control its metabolic output, and show how a control-theoretic model that models decision-making with an energy budget can explain cognitive effort avoidance in terms of an optimal allocation of limited energetic resources. The model accounts for both subject responsiveness to reward and the detrimental effects of hypoglycemia on cognitive function. A critical component of the model is using astrocytic glycogen as a plausible basis for limited energetic reserves. Glycogen acts as an energy buffer that can temporarily support high neural activity beyond the rate supported by blood glucose supply. The published dynamics of glycogen depletion and repletion are consonant with a broad array of phenomena associated with cognitive cost. Our model thus subsumes both the “cost/benefit” and “limited resource” models of cognitive cost while retaining valuable contributions of each. We discuss how the rational control of metabolic resources could underpin the control of attention, working memory, cognitive look ahead, and model-free vs. model-based policy learning. PMID:26379482

Cognitive cost as dynamic allocation of energetic resources.

PubMed

Christie, S Thomas; Schrater, Paul

2015-01-01

While it is widely recognized that thinking is somehow costly, involving cognitive effort and producing mental fatigue, these costs have alternatively been assumed to exist, treated as the brain's assessment of lost opportunities, or suggested to be metabolic but with implausible biological bases. We present a model of cognitive cost based on the novel idea that the brain senses and plans for longer-term allocation of metabolic resources by purposively conserving brain activity. We identify several distinct ways the brain might control its metabolic output, and show how a control-theoretic model that models decision-making with an energy budget can explain cognitive effort avoidance in terms of an optimal allocation of limited energetic resources. The model accounts for both subject responsiveness to reward and the detrimental effects of hypoglycemia on cognitive function. A critical component of the model is using astrocytic glycogen as a plausible basis for limited energetic reserves. Glycogen acts as an energy buffer that can temporarily support high neural activity beyond the rate supported by blood glucose supply. The published dynamics of glycogen depletion and repletion are consonant with a broad array of phenomena associated with cognitive cost. Our model thus subsumes both the "cost/benefit" and "limited resource" models of cognitive cost while retaining valuable contributions of each. We discuss how the rational control of metabolic resources could underpin the control of attention, working memory, cognitive look ahead, and model-free vs. model-based policy learning.

Dynamic variation in forebrain estradiol levels during song learning

PubMed Central

Chao, Andrew; Paon, Ashley; Remage-Healey, Luke

2014-01-01

Estrogens shape brain circuits during development, and the capacity to synthesize estrogens locally has consequences for both sexual differentiation and the acute modulation of circuits during early learning. A recently-optimized method to detect and quantify fluctuations in brain estrogens in vivo provides a direct means to explore how brain estrogen production contributes to both differentiation and neuromodulation during development. Here, we use this method to test the hypothesis that neuroestrogens are sexually-differentiated as well as dynamically responsive to song tutoring (via passive video/audio playback) during the period of song learning in juvenile zebra finches. Our results show that baseline neuroestradiol levels in the caudal forebrain do not differ between males and females during an early critical masculinization window. Instead, we observe a prominent difference between males and females in baseline neuroestradiol that emerges during the subadult stage as animals approach sexual maturity. Second, we observe that fluctuating neuroestradiol levels during periods of passive song tutoring exhibit a markedly different profile in juveniles as compared to adults. Specifically, neuroestrogens in the caudal forebrain are elevated following (rather than during) tutor song exposure in both juvenile males and females, suggesting an important role for the early consolidation of tutor song memories. These results further reveal a circadian influence on the fluctuations in local neuroestrogens during sensory/cognitive tasks. Taken together, these findings uncover several unexpected features of brain estrogen synthesis in juvenile animals that may have implications for secondary masculinization as well as the consolidation of recent sensory experiences. PMID:25205304

Framework and Implications of Virtual Neurorobotics

PubMed Central

Goodman, Philip H.; Zou, Quan; Dascalu, Sergiu-Mihai

2008-01-01

Despite decades of societal investment in artificial learning systems, truly “intelligent” systems have yet to be realized. These traditional models are based on input-output pattern optimization and/or cognitive production rule modeling. One response has been social robotics, using the interaction of human and robot to capture important cognitive dynamics such as cooperation and emotion; to date, these systems still incorporate traditional learning algorithms. More recently, investigators are focusing on the core assumptions of the brain “algorithm” itself—trying to replicate uniquely “neuromorphic” dynamics such as action potential spiking and synaptic learning. Only now are large-scale neuromorphic models becoming feasible, due to the availability of powerful supercomputers and an expanding supply of parameters derived from research into the brain's interdependent electrophysiological, metabolomic and genomic networks. Personal computer technology has also led to the acceptance of computer-generated humanoid images, or “avatars”, to represent intelligent actors in virtual realities. In a recent paper, we proposed a method of virtual neurorobotics (VNR) in which the approaches above (social-emotional robotics, neuromorphic brain architectures, and virtual reality projection) are hybridized to rapidly forward-engineer and develop increasingly complex, intrinsically intelligent systems. In this paper, we synthesize our research and related work in the field and provide a framework for VNR, with wider implications for research and practical applications. PMID:18982115

Inter-subject phase synchronization for exploratory analysis of task-fMRI.

PubMed

Bolt, Taylor; Nomi, Jason S; Vij, Shruti G; Chang, Catie; Uddin, Lucina Q

2018-08-01

Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization approach for exploratory analysis of task-based fMRI data. Combining the tools of instantaneous phase synchronization and independent component analysis, we characterize whole-brain task-driven responses in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this framework to fMRI data collected during performance of a simple motor task and a social cognitive task. Analyses using an inter-subject phase synchronization approach revealed a large number of brain networks that dynamically synchronized to various features of the task, often not predicted by the hypothesized temporal structure of the task. We suggest that this methodological framework, along with readily available tools in the fMRI community, provides a powerful exploratory, data-driven approach for analysis of task-driven BOLD activity. Copyright © 2018 Elsevier Inc. All rights reserved.

Guiding the study of brain dynamics by using first-person data: Synchrony patterns correlate with ongoing conscious states during a simple visual task

PubMed Central

Lutz, Antoine; Lachaux, Jean-Philippe; Martinerie, Jacques; Varela, Francisco J.

2002-01-01

Even during well-calibrated cognitive tasks, successive brain responses to repeated identical stimulations are highly variable. The source of this variability is believed to reside mainly in fluctuations of the subject's cognitive “context” defined by his/her attentive state, spontaneous thought process, strategy to carry out the task, and so on … As these factors are hard to manipulate precisely, they are usually not controlled, and the variability is discarded by averaging techniques. We combined first-person data and the analysis of neural processes to reduce such noise. We presented the subjects with a three-dimensional illusion and recorded their electrical brain activity and their own report about their cognitive context. Trials were clustered according to these first-person data, and separate dynamical analyses were conducted for each cluster. We found that (i) characteristic patterns of endogenous synchrony appeared in frontal electrodes before stimulation. These patterns depended on the degree of preparation and the immediacy of perception as verbally reported. (ii) These patterns were stable for several recordings. (iii) Preparatory states modulate both the behavioral performance and the evoked and induced synchronous patterns that follow. (iv) These results indicated that first-person data can be used to detect and interpret neural processes. PMID:11805299

Habit strength is predicted by activity dynamics in goal-directed brain systems during training.

PubMed

Zwosta, Katharina; Ruge, Hannes; Goschke, Thomas; Wolfensteller, Uta

2018-01-15

Previous neuroscientific research revealed insights into the brain networks supporting goal-directed and habitual behavior, respectively. However, it remains unclear how these contribute to inter-individual differences in habit strength which is relevant for understanding not only normal behavior but also more severe dysregulations between these types of action control, such as in addiction. In the present fMRI study, we trained subjects on approach and avoidance behavior for an extended period of time before testing the habit strength of the acquired stimulus-response associations. We found that stronger habits were associated with a stronger decrease in inferior parietal lobule activity for approach and avoidance behavior and weaker vmPFC activity at the end of training for avoidance behavior, areas associated with the anticipation of outcome identity and value. VmPFC in particular showed markedly different activity dynamics during the training of approach and avoidance behavior. Furthermore, while ongoing training was accompanied by increasing functional connectivity between posterior putamen and premotor cortex, consistent with previous assumptions about the neural basis of increasing habitualization, this was not predictive of later habit strength. Together, our findings suggest that inter-individual differences in habitual behavior are driven by differences in the persistent involvement of brain areas supporting goal-directed behavior during training. Copyright © 2017. Published by Elsevier Inc.

Exploration and Modulation of Brain Network Interactions with Noninvasive Brain Stimulation in Combination with Neuroimaging

PubMed Central

Shafi, Mouhsin M.; Westover, M. Brandon; Fox, Michael D.; Pascual-Leone, Alvaro

2012-01-01

Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language, and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to noninvasively alter brain activity, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional MRI, PET and EEG, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner. PMID:22429242

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bayesian Mapping Reveals That Attention Boosts Neural Responses to Predicted and Unpredicted Stimuli.

PubMed

Garrido, Marta I; Rowe, Elise G; Halász, Veronika; Mattingley, Jason B

2018-05-01

Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between 2 alternative computational models. The "Opposition" model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the "Interaction" model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modeling showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.

Neural Computations in a Dynamical System with Multiple Time Scales.

PubMed

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Studies of pathological dynamics after microvascular injury using nonlinear optical methods

NASA Astrophysics Data System (ADS)

Rosidi, Nathanael L.

Microvascular lesions are a common feature in the aging brain and clinical evidence has correlated microvascular pathology with the development of neurodegenerative diseases such as Alzheimer's disease and dementia. Traditional animal models that replicate hemorrhagic and ischemic lesions in the brain typically affect large regions in the cortex and do not reproduce the small-scale lesions linked to neurodegeneration that likely stem from injuries to single microvessels. Due in part to this lack of small-scale injury animal models, there remains an incomplete understanding of the cellular and pathophysiological dynamics following small-scale vascular lesions, making progress on therapeutic strategies difficult. We used tightly focused femtosecond laser pulses to injure single penetrating arterioles (PA) (i.e., arterioles that plunge into the brain) in the cortex of live anesthetized rodents and used two-photon excited fluorescence (2PEF) imaging to quantify blood flow changes and to determine the time course of pathological consequences in the brain after injury. We find that after ischemic occlusion of a PA, nearby pial and penetrating arterioles do not actively compensate for the reduction of blood flow observed near the occluded blood vessel. We find that capillaries connected downstream to the clotted vessel dilate but other capillaries in the vicinity do not, suggesting that any compensatory signal that results in a physiological response travels vascularly. We ruptured individual PAs to induce microhemorrhages that resulted in extravasation of blood into the parenchyma. We find that tissue compression due to the hematoma does not collapse capillaries and cause acute ischemia. 2PEF imaging of mice expressing yellow fluorescent protein (YFP) in a subset of cortical neurons revealed no dendrite degeneration out to seven days after microhemorrhage. However, we did observe an inflammatory response by microglia/macrophages as quickly as 1.5-hrs after microhemorrhage which persisted past seven days. Lastly, we looked at spine (i.e., post-synaptic terminals on dendrites) dynamics on GFP fluorescent cortical dendrites and found a higher rate of spine loss and gain after a nearby microhemorrhage out to 14 days. This higher rate of spine turnover may help provide an understanding of the development of symptomatic dysfunction due to consequences in neuronal rewiring after a microhemorrhage. The work presented in this dissertation provides quantification of pathological consequences after both ischemic and hemorrhagic injury to a single blood vessel in the brain. We see that after a small-scale ischemic lesion, surrounding blood vessels do not elicit an active response to compensate for a lack of blood flow in the targeted blood vessel and surrounding tissue. After a hemorrhage to a single blood vessel, we do not observe any neuronal degeneration or death. These hemorrhagic lesions, however, do result in an inflammatory reaction that may lead to subtle changes in neuronal rewiring or seed the development of neurodegenerative diseases. The work presented in this dissertation can help provide new insights for the development of novel stroke therapeutics as well as provide cell specific observations about the development of pathological consequences in both ischemic and hemorrhagic lesions in the brain.

Neural Correlates of Facial Mimicry: Simultaneous Measurements of EMG and BOLD Responses during Perception of Dynamic Compared to Static Facial Expressions

PubMed Central

Rymarczyk, Krystyna; Żurawski, Łukasz; Jankowiak-Siuda, Kamila; Szatkowska, Iwona

2018-01-01

Facial mimicry (FM) is an automatic response to imitate the facial expressions of others. However, neural correlates of the phenomenon are as yet not well established. We investigated this issue using simultaneously recorded EMG and BOLD signals during perception of dynamic and static emotional facial expressions of happiness and anger. During display presentations, BOLD signals and zygomaticus major (ZM), corrugator supercilii (CS) and orbicularis oculi (OO) EMG responses were recorded simultaneously from 46 healthy individuals. Subjects reacted spontaneously to happy facial expressions with increased EMG activity in ZM and OO muscles and decreased CS activity, which was interpreted as FM. Facial muscle responses correlated with BOLD activity in regions associated with motor simulation of facial expressions [i.e., inferior frontal gyrus, a classical Mirror Neuron System (MNS)]. Further, we also found correlations for regions associated with emotional processing (i.e., insula, part of the extended MNS). It is concluded that FM involves both motor and emotional brain structures, especially during perception of natural emotional expressions. PMID:29467691

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients.

PubMed

Miller, Robyn L; Yaesoubi, Maziar; Turner, Jessica A; Mathalon, Daniel; Preda, Adrian; Pearlson, Godfrey; Adali, Tulay; Calhoun, Vince D

2016-01-01

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject's trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls.

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients

PubMed Central

Miller, Robyn L.; Yaesoubi, Maziar; Turner, Jessica A.; Mathalon, Daniel; Preda, Adrian; Pearlson, Godfrey; Adali, Tulay; Calhoun, Vince D.

2016-01-01

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject’s trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls. PMID:26981625

Plastic brain mechanisms for attaining auditory temporal order judgment proficiency.

PubMed

Bernasconi, Fosco; Grivel, Jeremy; Murray, Micah M; Spierer, Lucas

2010-04-15

Accurate perception of the order of occurrence of sensory information is critical for the building up of coherent representations of the external world from ongoing flows of sensory inputs. While some psychophysical evidence reports that performance on temporal perception can improve, the underlying neural mechanisms remain unresolved. Using electrical neuroimaging analyses of auditory evoked potentials (AEPs), we identified the brain dynamics and mechanism supporting improvements in auditory temporal order judgment (TOJ) during the course of the first vs. latter half of the experiment. Training-induced changes in brain activity were first evident 43-76 ms post stimulus onset and followed from topographic, rather than pure strength, AEP modulations. Improvements in auditory TOJ accuracy thus followed from changes in the configuration of the underlying brain networks during the initial stages of sensory processing. Source estimations revealed an increase in the lateralization of initially bilateral posterior sylvian region (PSR) responses at the beginning of the experiment to left-hemisphere dominance at its end. Further supporting the critical role of left and right PSR in auditory TOJ proficiency, as the experiment progressed, responses in the left and right PSR went from being correlated to un-correlated. These collective findings provide insights on the neurophysiologic mechanism and plasticity of temporal processing of sounds and are consistent with models based on spike timing dependent plasticity. Copyright 2010 Elsevier Inc. All rights reserved.

A self-organizing model of perisaccadic visual receptive field dynamics in primate visual and oculomotor system.

PubMed

Mender, Bedeho M W; Stringer, Simon M

2015-01-01

We propose and examine a model for how perisaccadic visual receptive field dynamics, observed in a range of primate brain areas such as LIP, FEF, SC, V3, V3A, V2, and V1, may develop through a biologically plausible process of unsupervised visually guided learning. These dynamics are associated with remapping, which is the phenomenon where receptive fields anticipate the consequences of saccadic eye movements. We find that a neural network model using a local associative synaptic learning rule, when exposed to visual scenes in conjunction with saccades, can account for a range of associated phenomena. In particular, our model demonstrates predictive and pre-saccadic remapping, responsiveness shifts around the time of saccades, and remapping from multiple directions.

A self-organizing model of perisaccadic visual receptive field dynamics in primate visual and oculomotor system

PubMed Central

Mender, Bedeho M. W.; Stringer, Simon M.

2015-01-01

We propose and examine a model for how perisaccadic visual receptive field dynamics, observed in a range of primate brain areas such as LIP, FEF, SC, V3, V3A, V2, and V1, may develop through a biologically plausible process of unsupervised visually guided learning. These dynamics are associated with remapping, which is the phenomenon where receptive fields anticipate the consequences of saccadic eye movements. We find that a neural network model using a local associative synaptic learning rule, when exposed to visual scenes in conjunction with saccades, can account for a range of associated phenomena. In particular, our model demonstrates predictive and pre-saccadic remapping, responsiveness shifts around the time of saccades, and remapping from multiple directions. PMID:25717301

Emergent dynamics of spiking neurons with fluctuating threshold

NASA Astrophysics Data System (ADS)

Bhattacharjee, Anindita; Das, M. K.

2017-05-01

Role of fluctuating threshold on neuronal dynamics is investigated. The threshold function is assumed to follow a normal probability distribution. Standard deviation of inter-spike interval of the response is computed as an indicator of irregularity in spike emission. It has been observed that, the irregularity in spiking is more if the threshold variation is more. A significant change in modal characteristics of Inter Spike Intervals (ISI) is seen to occur as a function of fluctuation parameter. Investigation is further carried out for coupled system of neurons. Cooperative dynamics of coupled neurons are discussed in view of synchronization. Total and partial synchronization regimes are depicted with the help of contour plots of synchrony measure under various conditions. Results of this investigation may provide a basis for exploring the complexities of neural communication and brain functioning.

Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans.

PubMed

Lohmann, Philipp; Stoffels, Gabriele; Ceccon, Garry; Rapp, Marion; Sabel, Michael; Filss, Christian P; Kamp, Marcel A; Stegmayr, Carina; Neumaier, Bernd; Shah, Nadim J; Langen, Karl-Josef; Galldiks, Norbert

2017-07-01

We investigated the potential of textural feature analysis of O-(2-[ 18 F]fluoroethyl)-L-tyrosine ( 18 F-FET) PET to differentiate radiation injury from brain metastasis recurrence. Forty-seven patients with contrast-enhancing brain lesions (n = 54) on MRI after radiotherapy of brain metastases underwent dynamic 18 F-FET PET. Tumour-to-brain ratios (TBRs) of 18 F-FET uptake and 62 textural parameters were determined on summed images 20-40 min post-injection. Tracer uptake kinetics, i.e., time-to-peak (TTP) and patterns of time-activity curves (TAC) were evaluated on dynamic PET data from 0-50 min post-injection. Diagnostic accuracy of investigated parameters and combinations thereof to discriminate between brain metastasis recurrence and radiation injury was compared. Diagnostic accuracy increased from 81 % for TBR mean alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBR max alone was 83 % and increased to 85 % after combination with the textural parameters Coarseness, Short-zone emphasis, or Correlation. Analysis of TACs resulted in an accuracy of 70 % for kinetic pattern alone and increased to 83 % when combined with TBR max . Textural feature analysis in combination with TBRs may have the potential to increase diagnostic accuracy for discrimination between brain metastasis recurrence and radiation injury, without the need for dynamic 18 F-FET PET scans. • Textural feature analysis provides quantitative information about tumour heterogeneity • Textural features help improve discrimination between brain metastasis recurrence and radiation injury • Textural features might be helpful to further understand tumour heterogeneity • Analysis does not require a more time consuming dynamic PET acquisition.

Stimulus and Response-Locked P3 Activity in a Dynamic Rapid Serial Visual Presentation (RSVP) Task

DTIC Science & Technology

2013-01-01

Perception and Psychophysics 1973, 14, 265–272. Touryan, J.; Gibson, L.; Horne, J. H.; Weber, P. Real-Time Classification of Neural Signals ...execution. 15. SUBJECT TERMS P300, RSVP, EEG, target recognition, reaction time, ERP 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT...applications and as an input signal in many brain computer interactive technologies (BCITs) for both patients and healthy individuals. ERPs are extracted

The Metastable Brain

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Neural ensembles oscillate across a broad range of frequencies and are transiently coupled or “bound” together when people attend to a stimulus, perceive, think and act. This is a dynamic, self-assembling process, with parts of the brain engaging and disengaging in time. But how is it done? The theory of Coordination Dynamics proposes a mechanism called metastability, a subtle blend of integration and segregation. Tendencies for brain regions to express their individual autonomy and specialized functions (segregation, modularity) coexist with tendencies to couple and coordinate globally for multiple functions (integration). Although metastability has garnered increasing attention, it has yet to be demonstrated and treated within a fully spatiotemporal perspective. Here, we illustrate metastability in continuous neural and behavioral recordings, and we discuss theory and experiments at multiple scales suggesting that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic cognitive, behavioral and social functions. PMID:24411730

Dynamic Responses in Brain Networks to Social Feedback: A Dual EEG Acquisition Study in Adolescent Couples

PubMed Central

Kuo, Ching-Chang; Ha, Thao; Ebbert, Ashley M.; Tucker, Don M.; Dishion, Thomas J.

2017-01-01

Adolescence is a sensitive period for the development of romantic relationships. During this period the maturation of frontolimbic networks is particularly important for the capacity to regulate emotional experiences. In previous research, both functional magnetic resonance imaging (fMRI) and dense array electroencephalography (dEEG) measures have suggested that responses in limbic regions are enhanced in adolescents experiencing social rejection. In the present research, we examined social acceptance and rejection from romantic partners as they engaged in a Chatroom Interact Task. Dual 128-channel dEEG systems were used to record neural responses to acceptance and rejection from both adolescent romantic partners and unfamiliar peers (N = 75). We employed a two-step temporal principal component analysis (PCA) and spatial independent component analysis (ICA) approach to statistically identify the neural components related to social feedback. Results revealed that the early (288 ms) discrimination between acceptance and rejection reflected by the P3a component was significant for the romantic partner but not the unfamiliar peer. In contrast, the later (364 ms) P3b component discriminated between acceptance and rejection for both partners and peers. The two-step approach (PCA then ICA) was better able than either PCA or ICA alone in separating these components of the brain's electrical activity that reflected both temporal and spatial phases of the brain's processing of social feedback. PMID:28620292

Cortical responses to dynamic emotional facial expressions generalize across stimuli, and are sensitive to task-relevance, in adults with and without Autism.

PubMed

Kliemann, Dorit; Richardson, Hilary; Anzellotti, Stefano; Ayyash, Dima; Haskins, Amanda J; Gabrieli, John D E; Saxe, Rebecca R

2018-06-01

Individuals with Autism Spectrum Disorders (ASD) report difficulties extracting meaningful information from dynamic and complex social cues, like facial expressions. The nature and mechanisms of these difficulties remain unclear. Here we tested whether that difficulty can be traced to the pattern of activity in "social brain" regions, when viewing dynamic facial expressions. In two studies, adult participants (male and female) watched brief videos of a range of positive and negative facial expressions, while undergoing functional magnetic resonance imaging (Study 1: ASD n = 16, control n = 21; Study 2: ASD n = 22, control n = 30). Patterns of hemodynamic activity differentiated among facial emotional expressions in left and right superior temporal sulcus, fusiform gyrus, and parts of medial prefrontal cortex. In both control participants and high-functioning individuals with ASD, we observed (i) similar responses to emotional valence that generalized across facial expressions and animated social events; (ii) similar flexibility of responses to emotional valence, when manipulating the task-relevance of perceived emotions; and (iii) similar responses to a range of emotions within valence. Altogether, the data indicate that there was little or no group difference in cortical responses to isolated dynamic emotional facial expressions, as measured with fMRI. Difficulties with real-world social communication and social interaction in ASD may instead reflect differences in initiating and maintaining contingent interactions, or in integrating social information over time or context. Copyright © 2018 Elsevier Ltd. All rights reserved.

The sleeping brain as a complex system.

PubMed

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.

Long-term neural and physiological phenotyping of a single human

PubMed Central

Poldrack, Russell A.; Laumann, Timothy O.; Koyejo, Oluwasanmi; Gregory, Brenda; Hover, Ashleigh; Chen, Mei-Yen; Gorgolewski, Krzysztof J.; Luci, Jeffrey; Joo, Sung Jun; Boyd, Ryan L.; Hunicke-Smith, Scott; Simpson, Zack Booth; Caven, Thomas; Sochat, Vanessa; Shine, James M.; Gordon, Evan; Snyder, Abraham Z.; Adeyemo, Babatunde; Petersen, Steven E.; Glahn, David C.; Reese Mckay, D.; Curran, Joanne E.; Göring, Harald H. H.; Carless, Melanie A.; Blangero, John; Dougherty, Robert; Leemans, Alexander; Handwerker, Daniel A.; Frick, Laurie; Marcotte, Edward M.; Mumford, Jeanette A.

2015-01-01

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders. PMID:26648521

Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics

PubMed Central

Sale, Martin V.; Lord, Anton; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B.

2015-01-01

Normal brain function depends on a dynamic balance between local specialization and large-scale integration. It remains unclear, however, how local changes in functionally specialized areas can influence integrated activity across larger brain networks. By combining transcranial magnetic stimulation with resting-state functional magnetic resonance imaging, we tested for changes in large-scale integration following the application of excitatory or inhibitory stimulation on the human motor cortex. After local inhibitory stimulation, regions encompassing the sensorimotor module concurrently increased their internal integration and decreased their communication with other modules of the brain. There were no such changes in modular dynamics following excitatory stimulation of the same area of motor cortex nor were there changes in the configuration and interactions between core brain hubs after excitatory or inhibitory stimulation of the same area. These results suggest the existence of selective mechanisms that integrate local changes in neural activity, while preserving ongoing communication between brain hubs. PMID:25717162

Investigating the Intersession Reliability of Dynamic Brain-State Properties.

PubMed

Smith, Derek M; Zhao, Yrian; Keilholz, Shella D; Schumacher, Eric H

2018-06-01

Dynamic functional connectivity metrics have much to offer to the neuroscience of individual differences of cognition. Yet, despite the recent expansion in dynamic connectivity research, limited resources have been devoted to the study of the reliability of these connectivity measures. To address this, resting-state functional magnetic resonance imaging data from 100 Human Connectome Project subjects were compared across 2 scan days. Brain states (i.e., patterns of coactivity across regions) were identified by classifying each time frame using k means clustering. This was done with and without global signal regression (GSR). Multiple gauges of reliability indicated consistency in the brain-state properties across days and GSR attenuated the reliability of the brain states. Changes in the brain-state properties across the course of the scan were investigated as well. The results demonstrate that summary metrics describing the clustering of individual time frames have adequate test/retest reliability, and thus, these patterns of brain activation may hold promise for individual-difference research.

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Traffic pollution exposure is associated with altered brain connectivity in school children.

PubMed

Pujol, Jesus; Martínez-Vilavella, Gerard; Macià, Dídac; Fenoll, Raquel; Alvarez-Pedrerol, Mar; Rivas, Ioar; Forns, Joan; Blanco-Hinojo, Laura; Capellades, Jaume; Querol, Xavier; Deus, Joan; Sunyer, Jordi

2016-04-01

Children are more vulnerable to the effects of environmental elements due to their active developmental processes. Exposure to urban air pollution has been associated with poorer cognitive performance, which is thought to be a result of direct interference with brain maturation. We aimed to assess the extent of such potential effects of urban pollution on child brain maturation using general indicators of vehicle exhaust measured in the school environment and a comprehensive imaging evaluation. A group of 263 children, aged 8 to 12 years, underwent MRI to quantify regional brain volumes, tissue composition, myelination, cortical thickness, neural tract architecture, membrane metabolites, functional connectivity in major neural networks and activation/deactivation dynamics during a sensory task. A combined measurement of elemental carbon and NO2 was used as a putative marker of vehicle exhaust. Air pollution exposure was associated with brain changes of a functional nature, with no evident effect on brain anatomy, structure or membrane metabolites. Specifically, a higher content of pollutants was associated with lower functional integration and segregation in key brain networks relevant to both inner mental processes (the default mode network) and stimulus-driven mental operations. Age and performance (motor response speed) both showed the opposite effect to that of pollution, thus indicating that higher exposure is associated with slower brain maturation. In conclusion, urban air pollution appears to adversely affect brain maturation in a critical age with changes specifically concerning the functional domain. Copyright © 2016 Elsevier Inc. All rights reserved.

Common and Distinct Neural Mechanisms of Attentional Switching and Response Conflict

PubMed Central

Kim, Chobok; Johnson, Nathan F.; Gold, Brian T.

2012-01-01

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. PMID:22750124

Genetic influences on phase synchrony of brain oscillations supporting response inhibition.

PubMed

Müller, Viktor; Anokhin, Andrey P; Lindenberger, Ulman

2017-05-01

Phase synchronization of neuronal oscillations is a fundamental mechanism underlying cognitive processing and behavior, including context-dependent response production and inhibition. Abnormalities in neural synchrony can lead to abnormal information processing and contribute to cognitive and behavioral deficits in neuropsychiatric disorders. However, little is known about genetic and environmental contributions to individual differences in cortical oscillatory dynamics underlying response inhibition. This study examined heritability of event-related phase synchronization of brain oscillations in 302 young female twins including 94 MZ and 57 DZ pairs performing a cued Go/No-Go version of the Continuous Performance Test (CPT). We used the Phase Locking Index (PLI) to assess inter-trial phase clustering (synchrony) in several frequency bands in two time intervals after stimulus onset (0-300 and 301-600ms). Response inhibition (i.e., successful response suppression in No-Go trials) was characterized by a transient increase in phase synchronization of delta- and theta-band oscillations in the fronto-central midline region. Genetic analysis showed significant heritability of the phase locking measures related to response inhibition, with 30 to 49% of inter-individual variability being accounted for by genetic factors. This is the first study providing evidence for heritability of task-related neural synchrony. The present results suggest that PLI can serve as an indicator of genetically transmitted individual differences in neural substrates of response inhibition. Copyright © 2016 Elsevier B.V. All rights reserved.

Common and distinct neural mechanisms of attentional switching and response conflict.

PubMed

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2012-08-21

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. Copyright © 2012 Elsevier B.V. All rights reserved.

Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

NASA Astrophysics Data System (ADS)

Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

2017-08-01

Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

Optogenetic Functional MRI

PubMed Central

Lin, Peter; Fang, Zhongnan; Liu, Jia; Lee, Jin Hyung

2016-01-01

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states. PMID:27167840

Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions

PubMed Central

Lin, Aijing; Liu, Kang K. L.; Bartsch, Ronny P.; Ivanov, Plamen Ch.

2016-01-01

Within the framework of ‘Network Physiology’, we ask a fundamental question of how modulations in cardiac dynamics emerge from networked brain–heart interactions. We propose a generalized time-delay approach to identify and quantify dynamical interactions between physiologically relevant brain rhythms and the heart rate. We perform empirical analysis of synchronized continuous EEG and ECG recordings from 34 healthy subjects during night-time sleep. For each pair of brain rhythm and heart interaction, we construct a delay-correlation landscape (DCL) that characterizes how individual brain rhythms are coupled to the heart rate, and how modulations in brain and cardiac dynamics are coordinated in time. We uncover characteristic time delays and an ensemble of specific profiles for the probability distribution of time delays that underly brain–heart interactions. These profiles are consistently observed in all subjects, indicating a universal pattern. Tracking the evolution of DCL across different sleep stages, we find that the ensemble of time-delay profiles changes from one physiologic state to another, indicating a strong association with physiologic state and function. The reported observations provide new insights on neurophysiological regulation of cardiac dynamics, with potential for broad clinical applications. The presented approach allows one to simultaneously capture key elements of dynamic interactions, including characteristic time delays and their time evolution, and can be applied to a range of coupled dynamical systems. PMID:27044991

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.

PubMed

Davison, Elizabeth N; Turner, Benjamin O; Schlesinger, Kimberly J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Carlson, Jean M

2016-11-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.

Does the regulation of local excitation-inhibition balance aid in recovery of functional connectivity? A computational account.

PubMed

Vattikonda, Anirudh; Surampudi, Bapi Raju; Banerjee, Arpan; Deco, Gustavo; Roy, Dipanjan

2016-08-01

Computational modeling of the spontaneous dynamics over the whole brain provides critical insight into the spatiotemporal organization of brain dynamics at multiple resolutions and their alteration to changes in brain structure (e.g. in diseased states, aging, across individuals). Recent experimental evidence further suggests that the adverse effect of lesions is visible on spontaneous dynamics characterized by changes in resting state functional connectivity and its graph theoretical properties (e.g. modularity). These changes originate from altered neural dynamics in individual brain areas that are otherwise poised towards a homeostatic equilibrium to maintain a stable excitatory and inhibitory activity. In this work, we employ a homeostatic inhibitory mechanism, balancing excitation and inhibition in the local brain areas of the entire cortex under neurological impairments like lesions to understand global functional recovery (across brain networks and individuals). Previous computational and empirical studies have demonstrated that the resting state functional connectivity varies primarily due to the location and specific topological characteristics of the lesion. We show that local homeostatic balance provides a functional recovery by re-establishing excitation-inhibition balance in all areas that are affected by lesion. We systematically compare the extent of recovery in the primary hub areas (e.g. default mode network (DMN), medial temporal lobe, medial prefrontal cortex) as well as other sensory areas like primary motor area, supplementary motor area, fronto-parietal and temporo-parietal networks. Our findings suggest that stability and richness similar to the normal brain dynamics at rest are achievable by re-establishment of balance. Copyright © 2016 Elsevier Inc. All rights reserved.

Hearing Scenes: A Neuromagnetic Signature of Auditory Source and Reverberant Space Separation

PubMed Central

Oliva, Aude

2017-01-01

Abstract Perceiving the geometry of surrounding space is a multisensory process, crucial to contextualizing object perception and guiding navigation behavior. Humans can make judgments about surrounding spaces from reverberation cues, caused by sounds reflecting off multiple interior surfaces. However, it remains unclear how the brain represents reverberant spaces separately from sound sources. Here, we report separable neural signatures of auditory space and source perception during magnetoencephalography (MEG) recording as subjects listened to brief sounds convolved with monaural room impulse responses (RIRs). The decoding signature of sound sources began at 57 ms after stimulus onset and peaked at 130 ms, while space decoding started at 138 ms and peaked at 386 ms. Importantly, these neuromagnetic responses were readily dissociable in form and time: while sound source decoding exhibited an early and transient response, the neural signature of space was sustained and independent of the original source that produced it. The reverberant space response was robust to variations in sound source, and vice versa, indicating a generalized response not tied to specific source-space combinations. These results provide the first neuromagnetic evidence for robust, dissociable auditory source and reverberant space representations in the human brain and reveal the temporal dynamics of how auditory scene analysis extracts percepts from complex naturalistic auditory signals. PMID:28451630

Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models

PubMed Central

Ou, Jinli; Xie, Li; Jin, Changfeng; Li, Xiang; Zhu, Dajiang; Jiang, Rongxin; Chen, Yaowu

2014-01-01

Functional connectivity measured from resting state fMRI (R-fMRI) data has been widely used to examine the brain’s functional activities and has been recently used to characterize and differentiate brain conditions. However, the dynamical transition patterns of the brain’s functional states have been less explored. In this work, we propose a novel computational framework to quantitatively characterize the brain state dynamics via hidden Markov models (HMMs) learned from the observations of temporally dynamic functional connectomics, denoted as functional connectome states. The framework has been applied to the R-fMRI dataset including 44 post-traumatic stress disorder (PTSD) patients and 51 normal control (NC) subjects. Experimental results show that both PTSD and NC brains were undergoing remarkable changes in resting state and mainly transiting amongst a few brain states. Interestingly, further prediction with the best-matched HMM demonstrates that PTSD would enter into, but could not disengage from, a negative mood state. Importantly, 84 % of PTSD patients and 86 % of NC subjects are successfully classified via multiple HMMs using majority voting. PMID:25331991

Evidence of a Conserved Molecular Response to Selection for Increased Brain Size in Primates

PubMed Central

Harrison, Peter W.; Caravas, Jason A.; Raghanti, Mary Ann; Phillips, Kimberley A.; Mundy, Nicholas I.

2017-01-01

The adaptive significance of human brain evolution has been frequently studied through comparisons with other primates. However, the evolution of increased brain size is not restricted to the human lineage but is a general characteristic of primate evolution. Whether or not these independent episodes of increased brain size share a common genetic basis is unclear. We sequenced and de novo assembled the transcriptome from the neocortical tissue of the most highly encephalized nonhuman primate, the tufted capuchin monkey (Cebus apella). Using this novel data set, we conducted a genome-wide analysis of orthologous brain-expressed protein coding genes to identify evidence of conserved gene–phenotype associations and species-specific adaptations during three independent episodes of brain size increase. We identify a greater number of genes associated with either total brain mass or relative brain size across these six species than show species-specific accelerated rates of evolution in individual large-brained lineages. We test the robustness of these associations in an expanded data set of 13 species, through permutation tests and by analyzing how genome-wide patterns of substitution co-vary with brain size. Many of the genes targeted by selection during brain expansion have glutamatergic functions or roles in cell cycle dynamics. We also identify accelerated evolution in a number of individual capuchin genes whose human orthologs are associated with human neuropsychiatric disorders. These findings demonstrate the value of phenotypically informed genome analyses, and suggest at least some aspects of human brain evolution have occurred through conserved gene–phenotype associations. Understanding these commonalities is essential for distinguishing human-specific selection events from general trends in brain evolution. PMID:28391320

The Role of Cell Volume in the Dynamics of Seizure, Spreading Depression, and Anoxic Depolarization

PubMed Central

Ullah, Ghanim; Wei, Yina; Dahlem, Markus A; Wechselberger, Martin; Schiff, Steven J

2015-01-01

Cell volume changes are ubiquitous in normal and pathological activity of the brain. Nevertheless, we know little of how cell volume affects neuronal dynamics. We here performed the first detailed study of the effects of cell volume on neuronal dynamics. By incorporating cell swelling together with dynamic ion concentrations and oxygen supply into Hodgkin-Huxley type spiking dynamics, we demonstrate the spontaneous transition between epileptic seizure and spreading depression states as the cell swells and contracts in response to changes in osmotic pressure. Our use of volume as an order parameter further revealed a dynamical definition for the experimentally described physiological ceiling that separates seizure from spreading depression, as well as predicted a second ceiling that demarcates spreading depression from anoxic depolarization. Our model highlights the neuroprotective role of glial K buffering against seizures and spreading depression, and provides novel insights into anoxic depolarization and the relevant cell swelling during ischemia. We argue that the dynamics of seizures, spreading depression, and anoxic depolarization lie along a continuum of the repertoire of the neuron membrane that can be understood only when the dynamic ion concentrations, oxygen homeostasis,and cell swelling in response to osmotic pressure are taken into consideration. Our results demonstrate the feasibility of a unified framework for a wide range of neuronal behaviors that may be of substantial importance in the understanding of and potentially developing universal intervention strategies for these pathological states. PMID:26273829

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

Theory of feedback controlled brain stimulations for Parkinson's disease

NASA Astrophysics Data System (ADS)

Sanzeni, A.; Celani, A.; Tiana, G.; Vergassola, M.

2016-01-01

Limb tremor and other debilitating symptoms caused by the neurodegenerative Parkinson's disease are currently treated by administering drugs and by fixed-frequency deep brain stimulation. The latter interferes directly with the brain dynamics by delivering electrical impulses to neurons in the subthalamic nucleus. While deep brain stimulation has shown therapeutic benefits in many instances, its mechanism is still unclear. Since its understanding could lead to improved protocols of stimulation and feedback control, we have studied a mathematical model of the many-body neural network dynamics controlling the dynamics of the basal ganglia. On the basis of the results obtained from the model, we propose a new procedure of active stimulation, that depends on the feedback of the network and that respects the constraints imposed by existing technology. We show by numerical simulations that the new protocol outperforms the standard ones for deep brain stimulation and we suggest future experiments that could further improve the feedback procedure.

A Stimulus-Locked Vector Autoregressive Model for Slow Event-Related fMRI Designs

PubMed Central

Siegle, Greg

2009-01-01

Summary Neuroscientists have become increasingly interested in exploring dynamic relationships among brain regions. Such a relationship, when directed from one region toward another, is denoted by “effective connectivity.” An fMRI experimental paradigm which is well-suited for examination of effective connectivity is the slow event-related design. This design presents stimuli at sufficient temporal spacing for determining within-trial trajectories of BOLD activation, allowing for the analysis of stimulus-locked temporal covariation of brain responses in multiple regions. This may be especially important for emotional stimuli processing, which can evolve over the course of several seconds, if not longer. However, while several methods have been devised for determining fMRI effective connectivity, few are adapted to event-related designs, which include non-stationary BOLD responses and multiple levels of nesting. We propose a model tailored for exploring effective connectivity of multiple brain regions in event-related fMRI designs - a semi-parametric adaptation of vector autoregressive (VAR) models, termed “stimulus-locked VAR” (SloVAR). Connectivity coefficients vary as a function of time relative to stimulus onset, are regularized via basis expansions, and vary randomly across subjects. SloVAR obtains flexible, data-driven estimates of effective connectivity and hence is useful for building connectivity models when prior information on dynamic regional relationships is sparse. Indices derived from the coefficient estimates can also be used to relate effective connectivity estimates to behavioral or clinical measures. We demonstrate the SloVAR model on a sample of clinically depressed and normal controls, showing that early but not late cortico-amygdala connectivity appears crucial to emotional control and early but not late cortico-cortico connectivity predicts depression severity in the depressed group, relationships that would have been missed in a more traditional VAR analysis. PMID:19236927

The Intracranial Volume Pressure Response in Increased Intracranial Pressure Patients: Clinical Significance of the Volume Pressure Indicator.

PubMed

Lai, Hung-Yi; Lee, Ching-Hsin; Lee, Ching-Yi

2016-01-01

For patients suffering from primary brain injury, monitoring intracranial pressure alone is not enough to reflect the dynamic intracranial condition. In our previous study, a segment of the pressure-volume curve can be expressed by the parabolic regression model with single indicator "a". The aim of this study is to evaluate if the indicator "a" can reflect intracranial conditions. Patients with traumatic brain injury, spontaneous intracranial hemorrhage, and/or hydrocephalus who had external ventricular drainage from January 2009 to February 2010 were included. The successive volume pressure response values were obtained by successive drainage of cerebral spinal fluid from intracranial pressure 20-25 mm Hg to 10 mm Hg. The relationship between withdrawn cerebral spinal fluid volume and intracranial pressure was analyzed by the parabolic regression model with single parameter "a". The overall mean for indicator "a" was 0.422 ± 0.046. The mean of "a" in hydrocephalus was 0.173 ± 0.024 and in severe intracranial mass with slender ventricle, it was 0.663 ± 0.062. The two extreme intracranial conditions had a statistical significant difference (p<0.001). The indicator "a" of a pressure-volume curve can reflect the dynamic intracranial condition and is comparable in different situations. A significantly larger indicator "a" with increased intracranial pressure is always observed in severe intracranial mass lesions with cerebral edema. A significantly smaller indicator "a" with increased intracranial pressure is observed in hydrocephalus. Brain computed tomography should be performed early if a rapid elevation of indicator "a" is detected, as it can reveal some ongoing intracranial pathology prior to clinical deterioration. Increased intracranial pressure was frequently observed in patients with intracranial pathology. The progression can be differentiated using the pattern of the volume pressure indicator.

Watching from a distance: A robotically controlled laser and real-time subject tracking software for the study of conditioned predator/prey-like interactions.

PubMed

Wilson, James C; Kesler, Mitch; Pelegrin, Sara-Lynn E; Kalvi, LeAnna; Gruber, Aaron; Steenland, Hendrik W

2015-09-30

The physical distance between predator and prey is a primary determinant of behavior, yet few paradigms exist to study this reliably in rodents. The utility of a robotically controlled laser for use in a predator-prey-like (PPL) paradigm was explored for use in rats. This involved the construction of a robotic two-dimensional gimbal to dynamically position a laser beam in a behavioral test chamber. Custom software was used to control the trajectory and final laser position in response to user input on a console. The software also detected the location of the laser beam and the rodent continuously so that the dynamics of the distance between them could be analyzed. When the animal or laser beam came within a fixed distance the animal would either be rewarded with electrical brain stimulation or shocked subcutaneously. Animals that received rewarding electrical brain stimulation could learn to chase the laser beam, while animals that received aversive subcutaneous shock learned to actively avoid the laser beam in the PPL paradigm. Mathematical computations are presented which describe the dynamic interaction of the laser and rodent. The robotic laser offers a neutral stimulus to train rodents in an open field and is the first device to be versatile enough to assess distance between predator and prey in real time. With ongoing behavioral testing this tool will permit the neurobiological investigation of predator/prey-like relationships in rodents, and may have future implications for prosthetic limb development through brain-machine interfaces. Copyright © 2015 Elsevier B.V. All rights reserved.

Abnormal rich club organization and functional brain dynamics in schizophrenia.

PubMed

van den Heuvel, Martijn P; Sporns, Olaf; Collin, Guusje; Scheewe, Thomas; Mandl, René C W; Cahn, Wiepke; Goñi, Joaquín; Hulshoff Pol, Hilleke E; Kahn, René S

2013-08-01

The human brain forms a large-scale structural network of regions and interregional pathways. Recent studies have reported the existence of a selective set of highly central and interconnected hub regions that may play a crucial role in the brain's integrative processes, together forming a central backbone for global brain communication. Abnormal brain connectivity may have a key role in the pathophysiology of schizophrenia. To examine the structure of the rich club in schizophrenia and its role in global functional brain dynamics. Structural diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed in patients with schizophrenia and matched healthy controls. Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. Forty-eight patients and 45 healthy controls participated in the study. An independent replication data set of 41 patients and 51 healthy controls was included to replicate and validate significant findings. MAIN OUTCOME(S) AND MEASURES: Measures of rich club organization, connectivity density of rich club connections and connections linking peripheral regions to brain hubs, measures of global brain network efficiency, and measures of coupling between brain structure and functional dynamics. Rich club organization between high-degree hub nodes was significantly affected in patients, together with a reduced density of rich club connections predominantly comprising the white matter pathways that link the midline frontal, parietal, and insular hub regions. This reduction in rich club density was found to be associated with lower levels of global communication capacity, a relationship that was absent for other white matter pathways. In addition, patients had an increase in the strength of structural connectivity-functional connectivity coupling. Our findings provide novel biological evidence that schizophrenia is characterized by a selective disruption of brain connectivity among central hub regions of the brain, potentially leading to reduced communication capacity and altered functional brain dynamics.

Frontal Theta Dynamics during Response Conflict in Long-Term Mindfulness Meditators

PubMed Central

Jo, Han-Gue; Malinowski, Peter; Schmidt, Stefan

2017-01-01

Mindfulness meditators often show greater efficiency in resolving response conflicts than non-meditators. However, the neural mechanisms underlying the improved behavioral efficiency are unclear. Here, we investigated frontal theta dynamics—a neural mechanism involved in cognitive control processes—in long-term mindfulness meditators. The dynamics of EEG theta oscillations (4–8 Hz) recorded over the medial frontal cortex (MFC) were examined in terms of their power (MFC theta power) and their functional connectivity with other brain areas (the MFC-centered theta network). Using a flanker-type paradigm, EEG data were obtained from 22 long-term mindfulness meditators and compared to those from 23 matched controls without meditation experience. Meditators showed more efficient cognitive control after conflicts, evidenced by fewer error responses irrespective of response timing. Furthermore, meditators exhibited enhanced conflict modulations of the MFC-centered theta network shortly before the response, in particular for the functional connection between the MFC and the motor cortex. In contrast, MFC theta power was comparable between groups. These results suggest that the higher behavioral efficiency after conflicts in mindfulness meditators could be a function of increased engagement to control the motor system in association with the MFC-centered theta network. PMID:28638334

Dynamic Brains and the Changing Rules of Neuroplasticity: Implications for Learning and Recovery

PubMed Central

Voss, Patrice; Thomas, Maryse E.; Cisneros-Franco, J. Miguel; de Villers-Sidani, Étienne

2017-01-01

A growing number of research publications have illustrated the remarkable ability of the brain to reorganize itself in response to various sensory experiences. A traditional view of this plastic nature of the brain is that it is predominantly limited to short epochs during early development. Although examples showing that neuroplasticity exists outside of these finite time-windows have existed for some time, it is only recently that we have started to develop a fuller understanding of the different regulators that modulate and underlie plasticity. In this article, we will provide several lines of evidence indicating that mechanisms of neuroplasticity are extremely variable across individuals and throughout the lifetime. This variability is attributable to several factors including inhibitory network function, neuromodulator systems, age, sex, brain disease, and psychological traits. We will also provide evidence of how neuroplasticity can be manipulated in both the healthy and diseased brain, including recent data in both young and aged rats demonstrating how plasticity within auditory cortex can be manipulated pharmacologically and by varying the quality of sensory inputs. We propose that a better understanding of the individual differences that exist within the various mechanisms that govern experience-dependent neuroplasticity will improve our ability to harness brain plasticity for the development of personalized translational strategies for learning and recovery following brain injury or disease. PMID:29085312

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

Hierarchical nonlinear dynamics of human attention.

PubMed

Rabinovich, Mikhail I; Tristan, Irma; Varona, Pablo

2015-08-01

Attention is the process of focusing mental resources on a specific cognitive/behavioral task. Such brain dynamics involves different partially overlapping brain functional networks whose interconnections change in time according to the performance stage, and can be stimulus-driven or induced by an intrinsically generated goal. The corresponding activity can be described by different families of spatiotemporal discrete patterns or sequential dynamic modes. Since mental resources are finite, attention modalities compete with each other at all levels of the hierarchy, from perception to decision making and behavior. Cognitive activity is a dynamical process and attention possesses some universal dynamical characteristics. Thus, it is time to apply nonlinear dynamical theory for the description and prediction of hierarchical attentional tasks. Such theory has to include the analyses of attentional control stability, the time cost of attention switching, the finite capacity of informational resources in the brain, and the normal and pathological bifurcations of attention sequential dynamics. In this paper we have integrated today's knowledge, models and results in these directions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamic perfusion CT in brain tumors.

PubMed

Yeung, Timothy Pok Chi; Bauman, Glenn; Yartsev, Slav; Fainardi, Enrico; Macdonald, David; Lee, Ting-Yim

2015-12-01

Dynamic perfusion CT (PCT) is an imaging technique for assessing the vascular supply and hemodynamics of brain tumors by measuring blood flow, blood volume, and permeability-surface area product. These PCT parameters provide information complementary to histopathologic assessments and have been used for grading brain tumors, distinguishing high-grade gliomas from other brain lesions, differentiating true progression from post-treatment effects, and predicting prognosis after treatments. In this review, the basic principles of PCT are described, and applications of PCT of brain tumors are discussed. The advantages and current challenges, along with possible solutions, of PCT are presented. Copyright © 2015. Published by Elsevier Ireland Ltd.

Exploiting neurovascular coupling: a Bayesian sequential Monte Carlo approach applied to simulated EEG fNIRS data

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Zappasodi, Filippo; Merla, Arcangelo; Chiarelli, Antonio Maria

2017-08-01

Objective. Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown. Approach. Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF). Main results. We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements. Significance. The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.

Brain function differences in language processing in children and adults with autism.

PubMed

Williams, Diane L; Cherkassky, Vladimir L; Mason, Robert A; Keller, Timothy A; Minshew, Nancy J; Just, Marcel Adam

2013-08-01

Comparison of brain function between children and adults with autism provides an understanding of the effects of the disorder and associated maturational differences on language processing. Functional imaging (functional magnetic resonance imaging) was used to examine brain activation and cortical synchronization during the processing of literal and ironic texts in 15 children with autism, 14 children with typical development, 13 adults with autism, and 12 adult controls. Both the children and adults with autism had lower functional connectivity (synchronization of brain activity among activated areas) than their age and ability comparison group in the left hemisphere language network during irony processing, and neither autism group had an increase in functional connectivity in response to increased task demands. Activation differences for the literal and irony conditions occurred in key language-processing regions (left middle temporal, left pars triangularis, left pars opercularis, left medial frontal, and right middle temporal). The children and adults with autism differed from each other in the use of some brain regions during the irony task, with the adults with autism having activation levels similar to those of the control groups. Overall, the children and adults with autism differed from the adult and child controls in (a) the degree of network coordination, (b) the distribution of the workload among member nodes, and (3) the dynamic recruitment of regions in response to text content. Moreover, the differences between the two autism age groups may be indicative of positive changes in the neural function related to language processing associated with maturation and/or educational experience. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

Brain Function Differences in Language Processing in Children and Adults with Autism

PubMed Central

Williams, Diane L.; Cherkassky, Vladimir L.; Mason, Robert A.; Keller, Timothy A.; Minshew, Nancy J.; Just, Marcel Adam

2015-01-01

Comparison of brain function between children and adults with autism provides an understanding of the effects of the disorder and associated maturational differences on language processing. Functional imaging (functional magnetic resonance imaging) was used to examine brain activation and cortical synchronization during the processing of literal and ironic texts in 15 children with autism, 14 children with typical development, 13 adults with autism, and 12 adult controls. Both the children and adults with autism had lower functional connectivity (synchronization of brain activity among activated areas) than their age and ability comparison group in the left hemisphere language network during irony processing, and neither autism group had an increase in functional connectivity in response to increased task demands. Activation differences for the literal and irony conditions occurred in key language-processing regions (left middle temporal, left pars triangularis, left pars opercularis, left medial frontal, and right middle temporal). The children and adults with autism differed from each other in the use of some brain regions during the irony task, with the adults with autism having activation levels similar to those of the control groups. Overall, the children and adults with autism differed from the adult and child controls in (a) the degree of network coordination, (b) the distribution of the workload among member nodes, and (3) the dynamic recruitment of regions in response to text content. Moreover, the differences between the two autism age groups may be indicative of positive changes in the neural function related to language processing associated with maturation and/or educational experience. PMID:23495230

Hypo-osmotic shock induces nuclear export and proteasome-dependent decrease of UBL5

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

Hatanaka, Ken; Precursory Research for Embryonic Science and Technology; Laboratory of Neurobiophysics, Graduate School of Pharmaceutical Sciences, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033

2006-11-24

The osmolarity of body fluid is strictly controlled through the action of diuretic hormones, which are secreted in the hypothalamus. In the mammalian brain, ubiquitin-like 5 (UBL5) is expressed in oxytocin- and vasopressin-positive neurons in the hypothalamus, and these neurons play a role in regulating osmolarity. We examined the dynamics of UBL5 levels in response to hyper- or hypo-osmotic conditions. Hypo-osmotic conditions led to significantly reduced levels of UBL5 both in brain slices from the hypothalamus and in NIH-3T3 cells. This decrease in UBL5 was transcription-independent and proteasome-dependent. Time-course immunocytochemical studies using exogenous UBL5 revealed that the protein was exportedmore » from the nucleus under hypo-osmotic conditions and decreased in a proteasome-dependent manner. This report is the first to describe changes in the intracellular and subcellular localization of UBL5 in response to hypo-osmotic conditions. Our results imply osmoregulation of UBL5.« less

Characterization of a time-resolved non-contact scanning diffuse optical imaging system exploiting fast-gated single-photon avalanche diode detection

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

Di Sieno, Laura, E-mail: laura.disieno@polimi.it; Dalla Mora, Alberto; Contini, Davide

2016-03-15

We present a system for non-contact time-resolved diffuse reflectance imaging, based on small source-detector distance and high dynamic range measurements utilizing a fast-gated single-photon avalanche diode. The system is suitable for imaging of diffusive media without any contact with the sample and with a spatial resolution of about 1 cm at 1 cm depth. In order to objectively assess its performances, we adopted two standardized protocols developed for time-domain brain imagers. The related tests included the recording of the instrument response function of the setup and the responsivity of its detection system. Moreover, by using liquid turbid phantoms with absorbingmore » inclusions, depth-dependent contrast and contrast-to-noise ratio as well as lateral spatial resolution were measured. To illustrate the potentialities of the novel approach, the characteristics of the non-contact system are discussed and compared to those of a fiber-based brain imager.« less

Brain penetration of telmisartan, a unique centrally acting angiotensin II type 1 receptor blocker, studied by PET in conscious rhesus macaques.

PubMed

Noda, Akihiro; Fushiki, Hiroshi; Murakami, Yoshihiro; Sasaki, Hiroshi; Miyoshi, Sosuke; Kakuta, Hirotoshi; Nishimura, Shintaro

2012-11-01

Telmisartan is a widely used, long-acting antihypertensive agent. Known to be a selective angiotensin II type 1 (AT(1)) receptor (AT(1)R) blocker (ARB), telmisartan acts as a partial agonist of peroxisome proliferator-activated receptor-gamma (PPAR-γ) and inhibits centrally mediated effects of angiotensin II in rats following peripheral administration, although the brain penetration of telmisartan remains unclear. We investigated the brain concentration and localization of telmisartan using (11)C-labeled telmisartan and positron emission tomography (PET) in conscious rhesus macaques. Three male rhesus macaques were bolus intravenously administered [(11)C]telmisartan either alone or as a mixture with unlabeled telmisartan (1mg/kg). Dynamic PET images were acquired for 95min following administration. Blood samples were collected for the analysis of plasma concentration and metabolites, and brain and plasma concentrations were calculated from detected radioactivity using the specific activity of the administered drug preparation, in which whole blood radioactivity was used for the correction of intravascular blood radioactivity in brain. Telmisartan penetrated into the brain little but enough to block AT(1)R and showed a consistently increasing brain/plasma ratio within the PET scanning period, suggesting slow clearance of the compound from the brain compared to the plasma clearance. Brain/plasma ratios at 30, 60, and 90min were 0.06, 0.13, and 0.18, respectively. No marked localization according to the AT(1)R distribution was noted over the entire brain, even on tracer alone dosing. Telmisartan penetrated into the brain enough to block AT(1)R and showed a slow clearance from the brain in conscious rhesus macaques, supporting the long-acting and central responses of telmisartan as a unique property among ARBs. Copyright © 2012 Elsevier Inc. All rights reserved.

In vivo measurement of apolipoprotein E from the brain interstitial fluid using microdialysis

PubMed Central

2013-01-01

Background The APOE4 allele variant is the strongest known genetic risk factor for developing late-onset Alzheimer’s disease. The link between apolipoprotein E (apoE) and Alzheimer’s disease is likely due in large part to the impact of apoE on the metabolism of amyloid β (Aβ) within the brain. Manipulation of apoE levels and lipidation within the brain has been proposed as a therapeutic target for the treatment of Alzheimer’s disease. However, we know little about the dynamic regulation of apoE levels and lipidation within the central nervous system. We have developed an assay to measure apoE levels in the brain interstitial fluid of awake and freely moving mice using large molecular weight cut-off microdialysis probes. Results We were able to recover apoE using microdialysis from human cerebrospinal fluid (CSF) in vitro and mouse brain parenchyma in vivo. Microdialysis probes were inserted into the hippocampus of wild-type mice and interstitial fluid was collected for 36 hours. Levels of apoE within the microdialysis samples were determined by ELISA. The levels of apoE were found to be relatively stable over 36 hours. No apoE was detected in microdialysis samples from apoE KO mice. Administration of the RXR agonist bexarotene increased ISF apoE levels while ISF Aβ levels were decreased. Extrapolation to zero-flow analysis allowed us to determine the absolute recoverable concentration of apoE3 in the brain ISF of apoE3 KI mice. Furthermore, analysis of microdialysis samples by non-denaturing gel electrophoresis determined lipidated apoE particles in microdialysis samples were consistent in size with apoE particles from CSF. Finally, we found that the concentration of apoE in the brain ISF was dependent upon apoE isoform in human apoE KI mice, following the pattern apoE2>apoE3>apoE4. Conclusions We are able to collect lipidated apoE from the brain of awake and freely moving mice and monitor apoE levels over the course of several hours from a single mouse. Our technique enables assessment of brain apoE dynamics under physiological and pathophysiological conditions and in response to therapeutic interventions designed to affect apoE levels and lipidation within the brain. PMID:23601557

[Brain function recovery after prolonged posttraumatic coma].

PubMed

Klimash, A V; Zhanaidarov, Z S

2016-01-01

To explore the characteristics of brain function recovery in patients after prolonged posttraumatic coma and with long-unconscious states. Eighty-seven patients after prolonged posttraumatic coma were followed-up for two years. An analysis of a clinical/neurological picture after a prolonged episode of coma was based on the dynamics of vital functions, neurological status and patient's reactions to external stimuli. Based on the dynamics of the clinical/neurological picture that shows the recovery of functions of the certain brain areas, three stages of brain function recovery after a prolonged episode of coma were singled out: brain stem areas, diencephalic areas and telencephalic areas. These functional/anatomic areas of brain function recovery after prolonged coma were compared to the present classifications.

The brain responses to different frequencies of binaural beat sounds on QEEG at cortical level.

PubMed

Jirakittayakorn, Nantawachara; Wongsawat, Yodchanan

2015-01-01

Beat phenomenon is occurred when two slightly different frequency waves interfere each other. The beat can also occur in the brain by providing two slightly different frequency waves separately each ear. This is called binaural beat. The brain responses to binaural beat are in discussion process whether the brain side and the brain area. Therefore, this study aims to figure out the brain responses to binaural beat by providing different binaural beat frequencies on 250 carrier tone continuously for 30 minutes to participants and using quantitative electroencephalography (QEEG) to interpret the data. The result shows that different responses appear in different beat frequency. Left hemisphere dominance occur in 3 Hz beat within 15 minutes and 15 Hz beat within 5 minutes. Right hemisphere dominance occurs in 10 Hz beat within 25 minute. 6 Hz beat enhances all area of the brain within 10 minutes. 8 Hz and 25 Hz beats have no clearly responses while 40 Hz beat enhances the responses in frontal lobe. These brain responses can be used for brain modulation application to induce the brain activity in further studies.

Spatial and temporal EEG dynamics of dual-task driving performance

PubMed Central

2011-01-01

Background Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions. Methods We designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains. Results Power increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA. Conclusions This study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations. PMID:21332977

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.

PubMed

Chennu, Srivas; Noreika, Valdas; Gueorguiev, David; Shtyrov, Yury; Bekinschtein, Tristan A; Henson, Richard

2016-08-10

There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future. Copyright © 2016 Chennu et al.

Correspondence of the brain's functional architecture during activation and rest.

PubMed

Smith, Stephen M; Fox, Peter T; Miller, Karla L; Glahn, David C; Fox, P Mickle; Mackay, Clare E; Filippini, Nicola; Watkins, Kate E; Toro, Roberto; Laird, Angela R; Beckmann, Christian F

2009-08-04

Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest." In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active" even when at "rest."

Dynamic studies of small animals with a four-color diffuse optical tomography imager

NASA Astrophysics Data System (ADS)

Schmitz, Christoph H.; Graber, Harry L.; Pei, Yaling; Farber, Mark; Stewart, Mark; Levina, Rita D.; Levin, Mikhail B.; Xu, Yong; Barbour, Randall L.

2005-09-01

We present newly developed instrumentation for full-tomographic four-wavelength, continuous wave, diffuse optical tomography (DOT) imaging on small animals. A small-animal imaging stage was constructed, from materials compatible with in-magnet studies, which offers stereotaxic fixation of the animal and precise, stable probe positioning. Instrument performance, based on calibration and phantom studies, demonstrates excellent long-term signal stability. DOT measurements of the functional rat brain response to electric paw stimulation are presented, and these demonstrate high data quality and excellent sensitivity to hemodynamic changes. A general linear model analysis on individual trials is used to localize and quantify the occurrence of functional behavior associated with the different hemoglobin state responses. Statistical evaluation of outcomes of individual trials is employed to identify significant regional response variations for different stimulation sites. Image results reveal a diffuse cortical response and a strong reaction of the thalamus, both indicative of activation of pain pathways by the stimulation. In addition, a weaker lateralized functional component is observed in the brain response, suggesting presence of motor activation. An important outcome of the experiment is that it shows that reactions to individual provocations can be monitored, without having to resort to signal averaging. Thus the described technology may be useful for studies of long-term trends in hemodynamic response, as would occur, for example, in behavioral studies involving freely moving animals.

Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome.

PubMed

Hellyer, Peter J; Scott, Gregory; Shanahan, Murray; Sharp, David J; Leech, Robert

2015-06-17

Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.

Assessment of Blood-Brain Barrier Permeability by Dynamic Contrast-Enhanced MRI in Transient Middle Cerebral Artery Occlusion Model after Localized Brain Cooling in Rats.

PubMed

Kim, Eun Soo; Lee, Seung-Koo; Kwon, Mi Jung; Lee, Phil Hye; Ju, Young-Su; Yoon, Dae Young; Kim, Hye Jeong; Lee, Kwan Seop

2016-01-01

The purpose of this study was to evaluate the effects of localized brain cooling on blood-brain barrier (BBB) permeability following transient middle cerebral artery occlusion (tMCAO) in rats, by using dynamic contrast-enhanced (DCE)-MRI. Thirty rats were divided into 3 groups of 10 rats each: control group, localized cold-saline (20℃) infusion group, and localized warm-saline (37℃) infusion group. The left middle cerebral artery (MCA) was occluded for 1 hour in anesthetized rats, followed by 3 hours of reperfusion. In the localized saline infusion group, 6 mL of cold or warm saline was infused through the hollow filament for 10 minutes after MCA occlusion. DCE-MRI investigations were performed after 3 hours and 24 hours of reperfusion. Pharmacokinetic parameters of the extended Tofts-Kety model were calculated for each DCE-MRI. In addition, rotarod testing was performed before tMCAO, and on days 1-9 after tMCAO. Myeloperoxidase (MPO) immunohisto-chemistry was performed to identify infiltrating neutrophils associated with the inflammatory response in the rat brain. Permeability parameters showed no statistical significance between cold and warm saline infusion groups after 3-hour reperfusion 0.09 ± 0.01 min(-1) vs. 0.07 ± 0.02 min(-1), p = 0.661 for K(trans); 0.30 ± 0.05 min(-1) vs. 0.37 ± 0.11 min(-1), p = 0.394 for kep, respectively. Behavioral testing revealed no significant difference among the three groups. However, the percentage of MPO-positive cells in the cold-saline group was significantly lower than those in the control and warm-saline groups (p < 0.05). Localized brain cooling (20℃) does not confer a benefit to inhibit the increase in BBB permeability that follows transient cerebral ischemia and reperfusion in an animal model, as compared with localized warm-saline (37℃) infusion group.

Assessment of Blood-Brain Barrier Permeability by Dynamic Contrast-Enhanced MRI in Transient Middle Cerebral Artery Occlusion Model after Localized Brain Cooling in Rats

PubMed Central

Kim, Eun Soo; Kwon, Mi Jung; Lee, Phil Hye; Ju, Young-Su; Yoon, Dae Young; Kim, Hye Jeong; Lee, Kwan Seop

2016-01-01

Objective The purpose of this study was to evaluate the effects of localized brain cooling on blood-brain barrier (BBB) permeability following transient middle cerebral artery occlusion (tMCAO) in rats, by using dynamic contrast-enhanced (DCE)-MRI. Materials and Methods Thirty rats were divided into 3 groups of 10 rats each: control group, localized cold-saline (20℃) infusion group, and localized warm-saline (37℃) infusion group. The left middle cerebral artery (MCA) was occluded for 1 hour in anesthetized rats, followed by 3 hours of reperfusion. In the localized saline infusion group, 6 mL of cold or warm saline was infused through the hollow filament for 10 minutes after MCA occlusion. DCE-MRI investigations were performed after 3 hours and 24 hours of reperfusion. Pharmacokinetic parameters of the extended Tofts-Kety model were calculated for each DCE-MRI. In addition, rotarod testing was performed before tMCAO, and on days 1-9 after tMCAO. Myeloperoxidase (MPO) immunohisto-chemistry was performed to identify infiltrating neutrophils associated with the inflammatory response in the rat brain. Results Permeability parameters showed no statistical significance between cold and warm saline infusion groups after 3-hour reperfusion 0.09 ± 0.01 min-1 vs. 0.07 ± 0.02 min-1, p = 0.661 for Ktrans; 0.30 ± 0.05 min-1 vs. 0.37 ± 0.11 min-1, p = 0.394 for kep, respectively. Behavioral testing revealed no significant difference among the three groups. However, the percentage of MPO-positive cells in the cold-saline group was significantly lower than those in the control and warm-saline groups (p < 0.05). Conclusion Localized brain cooling (20℃) does not confer a benefit to inhibit the increase in BBB permeability that follows transient cerebral ischemia and reperfusion in an animal model, as compared with localized warm-saline (37℃) infusion group. PMID:27587960

Long-Term Plasticity of Neurotransmitter Release: Emerging Mechanisms and Contributions to Brain Function and Disease.

PubMed

Monday, Hannah R; Younts, Thomas J; Castillo, Pablo E

2018-04-25

Long-lasting changes of brain function in response to experience rely on diverse forms of activity-dependent synaptic plasticity. Chief among them are long-term potentiation and long-term depression of neurotransmitter release, which are widely expressed by excitatory and inhibitory synapses throughout the central nervous system and can dynamically regulate information flow in neural circuits. This review article explores recent advances in presynaptic long-term plasticity mechanisms and contributions to circuit function. Growing evidence indicates that presynaptic plasticity may involve structural changes, presynaptic protein synthesis, and transsynaptic signaling. Presynaptic long-term plasticity can alter the short-term dynamics of neurotransmitter release, thereby contributing to circuit computations such as novelty detection, modifications of the excitatory/inhibitory balance, and sensory adaptation. In addition, presynaptic long-term plasticity underlies forms of learning and its dysregulation participates in several neuropsychiatric conditions, including schizophrenia, autism, intellectual disabilities, neurodegenerative diseases, and drug abuse. Expected final online publication date for the Annual Review of Neuroscience Volume 41 is July 8, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Dynamic cerebral autoregulation during brain activation paradigms.

PubMed

Panerai, Ronney B; Moody, Michelle; Eames, Penelope J; Potter, John F

2005-09-01

Dynamic cerebral autoregulation (CA) describes the transient response of cerebral blood flow (CBF) to rapid changes in arterial blood pressure (ABP). We tested the hypothesis that the efficiency of dynamic CA is increased by brain activation paradigms designed to induce hemispheric lateralization. CBF velocity [CBFV; bilateral, middle cerebral artery (MCA)], ABP, ECG, and end-tidal Pco(2) were continuously recorded in 14 right-handed healthy subjects (21-43 yr of age), in the seated position, at rest and during 10 repeated presentations (30 s on-off) of a word generation test and a constructional puzzle. Nonstationarities were not found during rest or activation. Transfer function analysis of the ABP-CBFV (i.e., input-output) relation was performed for the 10 separate 51.2-s segments of data during activation and compared with baseline data. During activation, the coherence function below 0.05 Hz was significantly increased for the right MCA recordings for the puzzle tasks compared with baseline values (0.36 +/- 0.16 vs. 0.26 +/- 0.13, P < 0.05) and for the left MCA recordings for the word paradigm (0.48 +/- 0.23 vs. 0.29 +/- 0.16, P < 0.05). In the same frequency range, significant increases in gain were observed during the puzzle paradigm for the right (0.69 +/- 0.37 vs. 0.46 +/- 0.32 cm.s(-1).mmHg(-1), P < 0.05) and left (0.61 +/- 0.29 vs. 0.45 +/- 0.24 cm.s(-1).mmHg(-1), P < 0.05) hemispheres and during the word tasks for the left hemisphere (0.66 +/- 0.31 vs. 0.39 +/- 0.15 cm.s(-1).mmHg(-1), P < 0.01). Significant reductions in phase were observed during activation with the puzzle task for the right (-0.04 +/- 1.01 vs. 0.80 +/- 0.86 rad, P < 0.01) and left (0.11 +/- 0.81 vs. 0.57 +/- 0.51 rad, P < 0.05) hemispheres and with the word paradigm for the right hemisphere (0.05 +/- 0.87 vs. 0.64 +/- 0.59 rad, P < 0.05). Brain activation also led to changes in the temporal pattern of the CBFV step response. We conclude that transfer function analysis suggests important changes in dynamic CA during mental activation tasks.

Neurobiology of dynamic psychotherapy: an integration possible?

PubMed

Mundo, Emanuela

2006-01-01

In the last decades, Kandel's innovative experiments have demonstrated that brain structures and synaptic connections are dynamic. Synapses can be modified by a wide variety of environmental factors, including learning and memory processes. The hypothesis that dynamic psychotherapy process involves memory and learning processes has opened the possibility of a dialogue between neuroscience and psychoanalysis and related psychotherapy techniques. The primary aim of the present article is to critically review the more recent data on neurobiological effects of dynamic psychotherapy in psychiatric disorders. Relevant literature has been selected using the databases currently available online (i.e., PubMed). The literature search has been limited to the past 10 years and to genetic, molecular biology, and neuroimaging studies that have addressed the issue of changes induced by psychotherapy. Most of the genetic studies on mental disorders have demonstrated that psychiatric conditions result from a complex interaction of genetic susceptibility and environmental effects. For none of the many psychiatric conditions investigated has a purely genetic background been found. Molecular biology studies have indicated that gene expression is influenced by several environmental factors, including early experiences, traumas, learning, and memory processes. Neuroimaging studies (using fMRI and PET) have found that not only cognitive but also dynamic psychotherapy has measurable effects on the brain. In addition, psychotherapy may modify brain function and metabolism in specific brain areas. Most of these studies have considered patients with major depressive disorders and compared the effects of psychotherapy with the effect of standard pharmacotherapy. In conclusion, recent results from neuroscience studies have suggested that dynamic psychotherapy has a significant impact on brain function and metabolism in specific brain areas. The possible applications and developments of this new area of research toward the conceptualization of an integrative approach to treatment of psychiatric disorders are discussed.

Three-dimensional organization of otolith-ocular reflexes in rhesus monkeys. III. Responses To translation

NASA Technical Reports Server (NTRS)

Angelaki, D. E.

1998-01-01

The three-dimensional (3-D) properties of the translational vestibulo-ocular reflexes (translational VORs) during lateral and fore-aft oscillations in complete darkness were studied in rhesus monkeys at frequencies between 0.16 and 25 Hz. In addition, constant velocity off-vertical axis rotations extended the frequency range to 0.02 Hz. During lateral motion, horizontal responses were in phase with linear velocity in the frequency range of 2-10 Hz. At both lower and higher frequencies, phase lags were introduced. Torsional response phase changed more than 180 degrees in the tested frequency range such that torsional eye movements, which could be regarded as compensatory to "an apparent roll tilt" at the lowest frequencies, became anticompensatory at all frequencies above approximately 1 Hz. These results suggest two functionally different frequency bandwidths for the translational VORs. In the low-frequency spectrum (<<0.5 Hz), horizontal responses compensatory to translation are small and high-pass-filtered whereas torsional response sensitivity is relatively frequency independent. At higher frequencies however, both horizontal and torsional response sensitivity and phase exhibit a similar frequency dependence, suggesting a common role during head translation. During up-down motion, vertical responses were in phase with translational velocity at 3-5 Hz but phase leads progressively increased for lower frequencies (>90 degrees at frequencies <0.2 Hz). No consistent dependence on static head orientation was observed for the vertical response components during up-down motion and the horizontal and torsional response components during lateral translation. The frequency response characteristics of the translational VORs were fitted by "periphery/brain stem" functions that related the linear acceleration input, transduced by primary otolith afferents, to the velocity signals providing the input to the velocity-to-position neural integrator and the oculomotor plant. The lowest-order, best-fit periphery/brain stem model that approximated the frequency dependence of the data consisted of a second order transfer function with two alternating poles (at 0.4 and 7.2 Hz) and zeros (at 0.035 and 3.4 Hz). In addition to clearly differentiator dynamics at low frequencies (less than approximately 0.5 Hz), there was no frequency bandwidth where the periphery/brain stem function could be approximated by an integrator, as previously suggested. In this scheme, the oculomotor plant dynamics are assumed to perform the necessary high-frequency integration as required by the reflex. The detailed frequency dependence of the data could only be precisely described by higher order functions with nonminimum phase characteristics that preclude simple filtering of afferent inputs and might be suggestive of distributed spatiotemporal processing of otolith signals in the translational VORs.

Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks

PubMed Central

Vanvinckenroye, Amaury; Vandewalle, Gilles; Chellappa, Sarah L.

2016-01-01

Functional and effective connectivity of cortical areas are essential for normal brain function under different behavioral states. Appropriate cortical activity during sleep and wakefulness is ensured by the balanced activity of excitatory and inhibitory circuits. Ultimately, fast, millisecond cortical rhythmic oscillations shape cortical function in time and space. On a much longer time scale, brain function also depends on prior sleep-wake history and circadian processes. However, much remains to be established on how the brain operates at the neuronal level in humans during sleep and wakefulness. A key limitation of human neuroscience is the difficulty in isolating neuronal excitation/inhibition drive in vivo. Therefore, computational models are noninvasive approaches of choice to indirectly access hidden neuronal states. In this review, we present a physiologically driven in silico approach, Dynamic Causal Modelling (DCM), as a means to comprehend brain function under different experimental paradigms. Importantly, DCM has allowed for the understanding of how brain dynamics underscore brain plasticity, cognition, and different states of consciousness. In a broader perspective, noninvasive computational approaches, such as DCM, may help to puzzle out the spatial and temporal dynamics of human brain function at different behavioural states. PMID:26885400

An information theory framework for dynamic functional domain connectivity.

PubMed

Vergara, Victor M; Miller, Robyn; Calhoun, Vince

2017-06-01

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan

PubMed Central

Davison, Elizabeth N.; Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2016-01-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism—hypergraph cardinality—we investigate individual variations in two separate, complementary data sets. The first data set (“multi-task”) consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set (“age-memory”), in which 95 individuals, aged 18–75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain. PMID:27880785

Effect of silhouetting and inversion on view invariance in the monkey inferotemporal cortex.

PubMed

Ratan Murty, N Apurva; Arun, S P

2017-07-01

We effortlessly recognize objects across changes in viewpoint, but we know relatively little about the features that underlie viewpoint invariance in the brain. Here, we set out to characterize how viewpoint invariance in monkey inferior temporal (IT) neurons is influenced by two image manipulations-silhouetting and inversion. Reducing an object into its silhouette removes internal detail, so this would reveal how much viewpoint invariance depends on the external contours. Inverting an object retains but rearranges features, so this would reveal how much viewpoint invariance depends on the arrangement and orientation of features. Our main findings are 1 ) view invariance is weakened by silhouetting but not by inversion; 2 ) view invariance was stronger in neurons that generalized across silhouetting and inversion; 3 ) neuronal responses to natural objects matched early with that of silhouettes and only later to that of inverted objects, indicative of coarse-to-fine processing; and 4 ) the impact of silhouetting and inversion depended on object structure. Taken together, our results elucidate the underlying features and dynamics of view-invariant object representations in the brain. NEW & NOTEWORTHY We easily recognize objects across changes in viewpoint, but the underlying features are unknown. Here, we show that view invariance in the monkey inferotemporal cortex is driven mainly by external object contours and is not specialized for object orientation. We also find that the responses to natural objects match with that of their silhouettes early in the response, and with inverted versions later in the response-indicative of a coarse-to-fine processing sequence in the brain. Copyright © 2017 the American Physiological Society.

The evolutionary dynamics of language.

PubMed

Steels, Luc; Szathmáry, Eörs

2018-02-01

The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort. Adopting this perspective has two major benefits. (i) It makes a bridge to neurobiological models of the brain that have also adopted an evolutionary dynamics point of view, thus opening a new horizon for studying how human brains achieve the remarkably complex competence for language. And (ii) it suggests a new foundation for studying cultural language change as an evolutionary dynamics process. The paper sketches this novel perspective, provides references to empirical data and computational experiments, and points to open problems. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

PubMed Central

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten

2013-01-01

A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g., fusiform gyrus), and frontal regions (e.g., ventromedial prefrontal cortex, medial and inferior frontal cortex) in early and again in later time windows. The present data support the view that dynamic facial displays trigger more information reflected in complex neural networks, in particular because of their changing features potentially triggering sustained activation related to a continuing evaluation of those faces. A combined fMRI and EEG approach thus provides an advanced insight to the spatio-temporal characteristics of emotional face processing, by also revealing additional neural generators, not identifiable by the only use of an fMRI approach. PMID:23818974

Abnormal early dynamic individual patterns of functional networks in low gamma band for depression recognition.

PubMed

Bi, Kun; Chattun, Mahammad Ridwan; Liu, Xiaoxue; Wang, Qiang; Tian, Shui; Zhang, Siqi; Lu, Qing; Yao, Zhijian

2018-06-13

The functional networks are associated with emotional processing in depression. The mapping of dynamic spatio-temporal brain networks is used to explore individual performance during early negative emotional processing. However, the dysfunctions of functional networks in low gamma band and their discriminative potentialities during early period of emotional face processing remain to be explored. Functional brain networks were constructed from the MEG recordings of 54 depressed patients and 54 controls in low gamma band (30-48 Hz). Dynamic connectivity regression (DCR) algorithm analyzed the individual change points of time series in response to emotional stimuli and constructed individualized spatio-temporal patterns. The nodal characteristics of patterns were calculated and fed into support vector machine (SVM). Performance of the classification algorithm in low gamma band was validated by dynamic topological characteristics of individual patterns in comparison to alpha and beta band. The best discrimination accuracy of individual spatio-temporal patterns was 91.01% in low gamma band. Individual temporal patterns had better results compared to group-averaged temporal patterns in all bands. The most important discriminative networks included affective network (AN) and fronto-parietal network (FPN) in low gamma band. The sample size is relatively small. High gamma band was not considered. The abnormal dynamic functional networks in low gamma band during early emotion processing enabled depression recognition. The individual information processing is crucial in the discovery of abnormal spatio-temporal patterns in depression during early negative emotional processing. Individual spatio-temporal patterns may reflect the real dynamic function of subjects while group-averaged data may neglect some individual information. Copyright © 2018. Published by Elsevier B.V.

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations

PubMed Central

Deco, Gustavo; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-01-01

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure–function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure–function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications. PMID:23825427

Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations.

PubMed

Deco, Gustavo; Ponce-Alvarez, Adrián; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-07-03

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics.

PubMed

Scifo, Enzo; Calza, Giulio; Fuhrmann, Martin; Soliymani, Rabah; Baumann, Marc; Lalowski, Maciej

2017-06-01

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

Altered retrieval of melodic information in congenital amusia: insights from dynamic causal modeling of MEG data.

PubMed

Albouy, Philippe; Mattout, Jérémie; Sanchez, Gaëtan; Tillmann, Barbara; Caclin, Anne

2015-01-01

Congenital amusia is a neuro-developmental disorder that primarily manifests as a difficulty in the perception and memory of pitch-based materials, including music. Recent findings have shown that the amusic brain exhibits altered functioning of a fronto-temporal network during pitch perception and short-term memory. Within this network, during the encoding of melodies, a decreased right backward frontal-to-temporal connectivity was reported in amusia, along with an abnormal connectivity within and between auditory cortices. The present study investigated whether connectivity patterns between these regions were affected during the short-term memory retrieval of melodies. Amusics and controls had to indicate whether sequences of six tones that were presented in pairs were the same or different. When melodies were different only one tone changed in the second melody. Brain responses to the changed tone in "Different" trials and to its equivalent (original) tone in "Same" trials were compared between groups using Dynamic Causal Modeling (DCM). DCM results confirmed that congenital amusia is characterized by an altered effective connectivity within and between the two auditory cortices during sound processing. Furthermore, right temporal-to-frontal message passing was altered in comparison to controls, with notably an increase in "Same" trials. An additional analysis in control participants emphasized that the detection of an unexpected event in the typically functioning brain is supported by right fronto-temporal connections. The results can be interpreted in a predictive coding framework as reflecting an abnormal prediction error sent by temporal auditory regions towards frontal areas in the amusic brain.

Impaired pitch perception and memory in congenital amusia: the deficit starts in the auditory cortex.

PubMed

Albouy, Philippe; Mattout, Jérémie; Bouet, Romain; Maby, Emmanuel; Sanchez, Gaëtan; Aguera, Pierre-Emmanuel; Daligault, Sébastien; Delpuech, Claude; Bertrand, Olivier; Caclin, Anne; Tillmann, Barbara

2013-05-01

Congenital amusia is a lifelong disorder of music perception and production. The present study investigated the cerebral bases of impaired pitch perception and memory in congenital amusia using behavioural measures, magnetoencephalography and voxel-based morphometry. Congenital amusics and matched control subjects performed two melodic tasks (a melodic contour task and an easier transposition task); they had to indicate whether sequences of six tones (presented in pairs) were the same or different. Behavioural data indicated that in comparison with control participants, amusics' short-term memory was impaired for the melodic contour task, but not for the transposition task. The major finding was that pitch processing and short-term memory deficits can be traced down to amusics' early brain responses during encoding of the melodic information. Temporal and frontal generators of the N100m evoked by each note of the melody were abnormally recruited in the amusic brain. Dynamic causal modelling of the N100m further revealed decreased intrinsic connectivity in both auditory cortices, increased lateral connectivity between auditory cortices as well as a decreased right fronto-temporal backward connectivity in amusics relative to control subjects. Abnormal functioning of this fronto-temporal network was also shown during the retention interval and the retrieval of melodic information. In particular, induced gamma oscillations in right frontal areas were decreased in amusics during the retention interval. Using voxel-based morphometry, we confirmed morphological brain anomalies in terms of white and grey matter concentration in the right inferior frontal gyrus and the right superior temporal gyrus in the amusic brain. The convergence between functional and structural brain differences strengthens the hypothesis of abnormalities in the fronto-temporal pathway of the amusic brain. Our data provide first evidence of altered functioning of the auditory cortices during pitch perception and memory in congenital amusia. They further support the hypothesis that in neurodevelopmental disorders impacting high-level functions (here musical abilities), abnormalities in cerebral processing can be observed in early brain responses.

Robotic gait assistive technology as means to aggressive mobilization strategy in acute rehabilitation following severe diffuse axonal injury: a case study.

PubMed

Stam, Daniel; Fernandez, Jennifer

2017-07-01

Diffuse axonal injury is a prominent cause of disablement post-traumatic brain injury. Utilization of the rapid expansion of our current scientific knowledge base combined with greater access to neurological and assistive technology as adjuncts to providing sensorimotor experience may yield innovative new approaches to rehabilitation based upon a dynamic model of brain response following injury. A 24-year-old female who sustained a traumatic brain injury, bilateral subdural hemorrhage, subarachnoid hemorrhage and severe diffuse axonal injury secondary to a motor vehicle collision. Evidence-based appraisal of present literature suggests a link between graded intensity of aerobic activity to facilitation of neuro-plastic change and up-regulation of neurotrophins essential to functional recovery post-diffuse axonal injury. Following resolution of paroxysmal autonomic instability with dystonia, aggressive early mobilization techniques were progressed utilizing robotic assistive gait technology in combination with conventional therapy. This approach allowed for arguably greater repetition and cardiovascular demands across a six-month inpatient rehabilitation stay. Outcomes in this case suggest that the use of assistive technology to adjunct higher level and intensity rehabilitation strategies may be a safe and effective means towards reduction of disablement following severe traumatic brain and neurological injury. Implications for Rehabilitation Functional recovery and neuroplasticity following diffuse neurological injury involves a complex process determined by the sensorimotor experience provided by rehabilitation clinicians. This process is in part modulated by intrinsic brain biochemical processes correlated to cardiovascular intensity of the activity provided. It is important that rehabilitation professionals monitor physiological response to higher intensity activities to provide an adaptive versus maladaptive response of central nervous system plasticity with activity. Identification of early mobilization parameters and skill acquisition may assist selection of gait assistive technology adjunct in progressing early optimal physical rehabilitation outcomes in the acute inpatient setting.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

PubMed

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A

2016-08-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A combination of an iron chelator with an antioxidant effectively diminishes the dendritic loss, tau-hyperphosphorylation, amyloids-β accumulation and brain mitochondrial dynamic disruption in rats with chronic iron-overload.

PubMed

Sripetchwandee, Jirapas; Wongjaikam, Suwakon; Krintratun, Warunsorn; Chattipakorn, Nipon; Chattipakorn, Siriporn C

2016-09-22

Iron-overload can cause cognitive impairment due to blood-brain barrier (BBB) breakdown and brain mitochondrial dysfunction. Although deferiprone (DFP) has been shown to exert neuroprotection, the head-to-head comparison among iron chelators used clinically on brain iron-overload has not been investigated. Moreover, since antioxidant has been shown to be beneficial in iron-overload condition, its combined effect with iron chelator has not been tested. Therefore, the hypothesis is that all chelators provide neuroprotection under iron-overload condition, and that a combination of an iron chelator with an antioxidant has greater efficacy than monotherapy. Male Wistar rats (n=42) were assigned to receive a normal diet (ND) or a high-iron diet (HFe) for 4months. At the 2nd month, HFe-fed rats were treated with a vehicle, deferoxamine (DFO), DFP, deferasirox (DFX), n-acetyl cysteine (NAC) or a combination of DFP with NAC, while ND-fed rats received vehicle. At the end of the experiment, rats were decapitated and brains were removed to determine brain iron level and deposition, brain mitochondrial function, BBB protein expression, brain mitochondrial dynamic, brain apoptosis, tau-hyperphosphorylation, amyloid-β (Aβ) accumulation and dendritic spine density. The results showed that iron-overload induced BBB breakdown, brain iron accumulation, brain mitochondrial dysfunction, impaired brain mitochondrial dynamics, tau-hyperphosphorylation, Aβ accumulation and dendritic spine reduction. All treatments, except DFX, attenuated these impairments. Moreover, combined therapy provided a greater efficacy than monotherapy. These findings suggested that iron-overload induced brain iron toxicity and a combination of an iron chelator with an antioxidant provided a greatest efficacy for neuroprotection than monotherapy. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Guo, Taomei; Xu, Yaqin; Zhao, Xiaojie; Yao, Li

2007-03-01

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.