Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data

PubMed Central

Goto, Takahiro; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results. PMID:29337999

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

Enhancement of electrical signaling in neural networks on graphene films.

PubMed

Tang, Mingliang; Song, Qin; Li, Ning; Jiang, Ziyun; Huang, Rong; Cheng, Guosheng

2013-09-01

One of the key challenges for neural tissue engineering is to exploit supporting materials with robust functionalities not only to govern cell-specific behaviors, but also to form functional neural network. The unique electrical and mechanical properties of graphene imply it as a promising candidate for neural interfaces, but little is known about the details of neural network formation on graphene as a scaffold material for tissue engineering. Therapeutic regenerative strategies aim to guide and enhance the intrinsic capacity of the neurons to reorganize by promoting plasticity mechanisms in a controllable manner. Here, we investigated the impact of graphene on the formation and performance in the assembly of neural networks in neural stem cell (NSC) culture. Using calcium imaging and electrophysiological recordings, we demonstrate the capabilities of graphene to support the growth of functional neural circuits, and improve neural performance and electrical signaling in the network. These results offer a better understanding of interactions between graphene and NSCs, also they clearly present the great potentials of graphene as neural interface in tissue engineering. Copyright © 2013 Elsevier Ltd. All rights reserved.

Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

PubMed Central

Bhowmik, David; Shanahan, Murray

2013-01-01

Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain. PMID:23614040

Trait Approach and Avoidance Motivation: Lateralized Neural Activity Associated with Executive Function

PubMed Central

Spielberg, Jeffrey M.; Miller, Gregory A.; Engels, Anna S.; Herrington, John D.; Sutton, Bradley P.; Banich, Marie T.; Heller, Wendy

2010-01-01

Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals. PMID:20728552

Trait approach and avoidance motivation: lateralized neural activity associated with executive function.

PubMed

Spielberg, Jeffrey M; Miller, Gregory A; Engels, Anna S; Herrington, John D; Sutton, Bradley P; Banich, Marie T; Heller, Wendy

2011-01-01

Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals. Copyright © 2010 Elsevier Inc. All rights reserved.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18-88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. Copyright © 2016 Tsvetanov et al.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

PubMed Central

Henson, Richard N.A.; Tyler, Lorraine K.; Razi, Adeel; Geerligs, Linda; Ham, Timothy E.; Rowe, James B.

2016-01-01

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18–88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. PMID:26985024

Stress and sodium intake in neural control of renal function in hypertension.

PubMed

DiBona, G F

1991-04-01

The interaction between genetic and environmental factors is important in the pathophysiology of hypertension. By examining the effects of two environmental factors--acute psychoemotional stress and dietary sodium intake--in rats with genetic hypertension, an important influence on central neural mechanisms governing the renal sympathetic neural control of renal function has been demonstrated. Additional studies of the central opioid systems have demonstrated an important role of opioid peptides in modulating the renal functional responses to acute psychoemotional stress. The observed renal functional alterations--antidiuresis, antinatriuresis, and renal vasoconstriction--are known to be capable of contributing to the initiation, development, and maintenance of the hypertensive process.

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

Working memory overload: fronto-limbic interactions and effects on subsequent working memory function.

PubMed

Yun, Richard J; Krystal, John H; Mathalon, Daniel H

2010-03-01

The human working memory system provides an experimentally useful model for examination of neural overload effects on subsequent functioning of the overloaded system. This study employed functional magnetic resonance imaging in conjunction with a parametric working memory task to characterize the behavioral and neural effects of cognitive overload on subsequent cognitive performance, with particular attention to cognitive-limbic interactions. Overloading the working memory system was associated with varying degrees of subsequent decline in performance accuracy and reduced activation of brain regions central to both task performance and suppression of negative affect. The degree of performance decline was independently predicted by three separate factors operating during the overload condition: the degree of task failure, the degree of amygdala activation, and the degree of inverse coupling between the amygdala and dorsolateral prefrontal cortex. These findings suggest that vulnerability to overload effects in cognitive functioning may be mediated by reduced amygdala suppression and subsequent amygdala-prefrontal interaction.

Integrative approaches for modeling regulation and function of the respiratory system.

PubMed

Ben-Tal, Alona; Tawhai, Merryn H

2013-01-01

Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. Copyright © 2013 Wiley Periodicals, Inc.

Stress, glucocorticoid hormones, and hippocampal neural progenitor cells: implications to mood disorders.

PubMed

Kino, Tomoshige

2015-01-01

The hypothalamic-pituitary-adrenal (HPA) axis and its end-effectors glucocorticoid hormones play central roles in the adaptive response to numerous stressors that can be either internal or external. Thus, this system has a strong impact on the brain hippocampus and its major functions, such as cognition, memory as well as behavior, and mood. The hippocampal area of the adult brain contains neural stem cells or more committed neural progenitor cells, which retain throughout the human life the ability of self-renewal and to differentiate into multiple neural cell lineages, such as neurons, astrocytes, and oligodendrocytes. Importantly, these characteristic cells contribute significantly to the above-indicated functions of the hippocampus, while various stressors and glucocorticoids influence proliferation, differentiation, and fate of these cells. This review offers an overview of the current understanding on the interactions between the HPA axis/glucocorticoid stress-responsive system and hippocampal neural progenitor cells by focusing on the actions of glucocorticoids. Also addressed is a further discussion on the implications of such interactions to the pathophysiology of mood disorders.

Structure-function clustering in multiplex brain networks

NASA Astrophysics Data System (ADS)

Crofts, J. J.; Forrester, M.; O'Dea, R. D.

2016-10-01

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.

Conducting Polymers for Neural Prosthetic and Neural Interface Applications

PubMed Central

2015-01-01

Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

Adaptation to conflict via context-driven anticipatory signals in the dorsomedial prefrontal cortex.

PubMed

Horga, Guillermo; Maia, Tiago V; Wang, Pengwei; Wang, Zhishun; Marsh, Rachel; Peterson, Bradley S

2011-11-09

Behavioral interference elicited by competing response tendencies adapts to contextual changes. Recent nonhuman primate research suggests a key mnemonic role of distinct prefrontal cells in supporting such context-driven behavioral adjustments by maintaining conflict information across trials, but corresponding prefrontal functions have yet to be probed in humans. Using event-related functional magnetic resonance imaging, we investigated the human neural substrates of contextual adaptations to conflict. We found that a neural system comprising the rostral dorsomedial prefrontal cortex and portions of the dorsolateral prefrontal cortex specifically encodes the history of previously experienced conflict and influences subsequent adaptation to conflict on a trial-by-trial basis. This neural system became active in anticipation of stimulus onsets during preparatory periods and interacted with a second neural system engaged during the processing of conflict. Our findings suggest that a dynamic interaction between a system that represents conflict history and a system that resolves conflict underlies the contextual adaptation to conflict.

Adaptation to Conflict via Context-Driven Anticipatory Signals in the Dorsomedial Prefrontal Cortex

PubMed Central

Horga, Guillermo; Maia, Tiago V.; Wang, Pengwei; Wang, Zhishun; Marsh, Rachel; Peterson, Bradley S.

2011-01-01

Behavioral interference elicited by competing response tendencies adapts to contextual changes. Recent nonhuman primate research suggests a key mnemonic role of distinct prefrontal cells in supporting such context-driven behavioral adjustments by maintaining conflict information across trials, but corresponding prefrontal functions have yet to be probed in humans. Using event-related functional magnetic resonance imaging (fMRI), we investigated the human neural substrates of contextual adaptations to conflict. We found that a neural system comprising the rostral dorsomedial prefrontal cortex and portions of the dorsolateral prefrontal cortex specifically encodes the history of previously experienced conflict and influences subsequent adaptation to conflict on a trial-by-trial basis. This neural system became active in anticipation of stimulus onsets during preparatory periods and interacted with a second neural system engaged during the processing of conflict. Our findings suggest that a dynamic interaction between a system that represents conflict history and a system that resolves conflict underlies the contextual adaptation to conflict. PMID:22072672

Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

PubMed

Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang

2017-09-21

The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.

Neural coordination during reach-to-grasp

PubMed Central

Vaidya, Mukta; Kording, Konrad; Saleh, Maryam; Takahashi, Kazutaka

2015-01-01

When reaching to grasp, we coordinate how we preshape the hand with how we move it. To ask how motor cortical neurons participate in this coordination, we examined the interactions between reach- and grasp-related neuronal ensembles while monkeys reached to grasp a variety of different objects in different locations. By describing the dynamics of these two ensembles as trajectories in a low-dimensional state space, we examined their coupling in time. We found evidence for temporal compensation across many different reach-to-grasp conditions such that if one neural trajectory led in time the other tended to catch up, reducing the asynchrony between the trajectories. Granger causality revealed bidirectional interactions between reach and grasp neural trajectories beyond that which could be attributed to the joint kinematics that were consistently stronger in the grasp-to-reach direction. Characterizing cortical coordination dynamics provides a new framework for understanding the functional interactions between neural populations. PMID:26224773

At the interface: convergence of neural regeneration and neural prostheses for restoration of function.

PubMed

Grill, W M; McDonald, J W; Peckham, P H; Heetderks, W; Kocsis, J; Weinrich, M

2001-01-01

The rapid pace of recent advances in development and application of electrical stimulation of the nervous system and in neural regeneration has created opportunities to combine these two approaches to restoration of function. This paper relates the discussion on this topic from a workshop at the International Functional Electrical Stimulation Society. The goals of this workshop were to discuss the current state of interaction between the fields of neural regeneration and neural prostheses and to identify potential areas of future research that would have the greatest impact on achieving the common goal of restoring function after neurological damage. Identified areas include enhancement of axonal regeneration with applied electric fields, development of hybrid neural interfaces combining synthetic silicon and biologically derived elements, and investigation of the role of patterned neural activity in regulating various neuronal processes and neurorehabilitation. Increased communication and cooperation between the two communities and recognition by each field that the other has something to contribute to their efforts are needed to take advantage of these opportunities. In addition, creative grants combining the two approaches and more flexible funding mechanisms to support the convergence of their perspectives are necessary to achieve common objectives.

Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions

PubMed Central

Hu, Kun; Meijer, Johanna H.; Shea, Steven A.; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A. J. L.

2012-01-01

The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ∼24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation. PMID:23185285

The interactive effect of social pain and executive functioning on aggression: an fMRI experiment.

PubMed

Chester, David S; Eisenberger, Naomi I; Pond, Richard S; Richman, Stephanie B; Bushman, Brad J; Dewall, C Nathan

2014-05-01

Social rejection often increases aggression, but the neural mechanisms underlying this effect remain unclear. This experiment tested whether neural activity in the dorsal anterior cingulate cortex (dACC) and anterior insula in response to social rejection predicted greater subsequent aggression. Additionally, it tested whether executive functioning moderated this relationship. Participants completed a behavioral measure of executive functioning, experienced social rejection while undergoing functional magnetic resonance imaging and then completed a task in which they could aggress against a person who rejected them using noise blasts . We found that dACC activation and executive functioning interacted to predict aggression. Specifically, participants with low executive functioning showed a positive association between dACC activation and aggression, whereas individuals with high executive functioning showed a negative association. Similar results were found for the left anterior insula. These findings suggest that social pain can increase or decrease aggression, depending on an individual's regulatory capability.

Feature to prototype transition in neural networks

NASA Astrophysics Data System (ADS)

Krotov, Dmitry; Hopfield, John

Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

Neural adaptation accounts for the dynamic resizing of peripersonal space: evidence from a psychophysical-computational approach.

PubMed

Noel, Jean-Paul; Blanke, Olaf; Magosso, Elisa; Serino, Andrea

2018-06-01

Interactions between the body and the environment occur within the peripersonal space (PPS), the space immediately surrounding the body. The PPS is encoded by multisensory (audio-tactile, visual-tactile) neurons that possess receptive fields (RFs) anchored on the body and restricted in depth. The extension in depth of PPS neurons' RFs has been documented to change dynamically as a function of the velocity of incoming stimuli, but the underlying neural mechanisms are still unknown. Here, by integrating a psychophysical approach with neural network modeling, we propose a mechanistic explanation behind this inherent dynamic property of PPS. We psychophysically mapped the size of participant's peri-face and peri-trunk space as a function of the velocity of task-irrelevant approaching auditory stimuli. Findings indicated that the peri-trunk space was larger than the peri-face space, and, importantly, as for the neurophysiological delineation of RFs, both of these representations enlarged as the velocity of incoming sound increased. We propose a neural network model to mechanistically interpret these findings: the network includes reciprocal connections between unisensory areas and higher order multisensory neurons, and it implements neural adaptation to persistent stimulation as a mechanism sensitive to stimulus velocity. The network was capable of replicating the behavioral observations of PPS size remapping and relates behavioral proxies of PPS size to neurophysiological measures of multisensory neurons' RF size. We propose that a biologically plausible neural adaptation mechanism embedded within the network encoding for PPS can be responsible for the dynamic alterations in PPS size as a function of the velocity of incoming stimuli. NEW & NOTEWORTHY Interactions between body and environment occur within the peripersonal space (PPS). PPS neurons are highly dynamic, adapting online as a function of body-object interactions. The mechanistic underpinning PPS dynamic properties are unexplained. We demonstrate with a psychophysical approach that PPS enlarges as incoming stimulus velocity increases, efficiently preventing contacts with faster approaching objects. We present a neurocomputational model of multisensory PPS implementing neural adaptation to persistent stimulation to propose a neurophysiological mechanism underlying this effect.

Aging and the interaction of sensory cortical function and structure.

PubMed

Peiffer, Ann M; Hugenschmidt, Christina E; Maldjian, Joseph A; Casanova, Ramon; Srikanth, Ryali; Hayasaka, Satoru; Burdette, Jonathan H; Kraft, Robert A; Laurienti, Paul J

2009-01-01

Even the healthiest older adults experience changes in cognitive and sensory function. Studies show that older adults have reduced neural responses to sensory information. However, it is well known that sensory systems do not act in isolation but function cooperatively to either enhance or suppress neural responses to individual environmental stimuli. Very little research has been dedicated to understanding how aging affects the interactions between sensory systems, especially cross-modal deactivations or the ability of one sensory system (e.g., audition) to suppress the neural responses in another sensory system cortex (e.g., vision). Such cross-modal interactions have been implicated in attentional shifts between sensory modalities and could account for increased distractibility in older adults. To assess age-related changes in cross-modal deactivations, functional MRI studies were performed in 61 adults between 18 and 80 years old during simple auditory and visual discrimination tasks. Results within visual cortex confirmed previous findings of decreased responses to visual stimuli for older adults. Age-related changes in the visual cortical response to auditory stimuli were, however, much more complex and suggested an alteration with age in the functional interactions between the senses. Ventral visual cortical regions exhibited cross-modal deactivations in younger but not older adults, whereas more dorsal aspects of visual cortex were suppressed in older but not younger adults. These differences in deactivation also remained after adjusting for age-related reductions in brain volume of sensory cortex. Thus, functional differences in cortical activity between older and younger adults cannot solely be accounted for by differences in gray matter volume. (c) 2007 Wiley-Liss, Inc.

Induction of the neural crest state: Control of stem cell attributes by gene regulatory, post-transcriptional and epigenetic interactions

PubMed Central

Prasad, Maneeshi S.; Sauka-Spengler, Tatjana; LaBonne, Carole

2012-01-01

Neural crest cells are a population of multipotent stem cell-like progenitors that arise at the neural plate border in vertebrates, migrate extensively, and give rise to diverse derivatives such as melanocytes, craniofacial cartilage and bone, smooth muscle, peripheral and enteric neurons and glia. The neural crest gene regulatory network (NC-GRN) includes a number of key factors that are used reiteratively to control multiple steps in the development of neural crest cells, including the acquisition of stem cell attributes. It is therefore essential to understand the mechanisms that control the distinct functions of such reiteratively used factors in different cellular contexts. The context-dependent control of neural crest specification is achieved through combinatorial interaction with other factors, post-transcriptional and post-translational modifications, and the epigenetic status and chromatin state of target genes. Here we review the current understanding of the NC-GRN, including the role of the neural crest specifiers, their links to the control of “stemness,” and their dynamic context-dependent regulation during the formation of neural crest progenitors. PMID:22583479

Neuroticism modulates the effects of intranasal vasopressin treatment on the neural response to positive and negative social interactions.

PubMed

Feng, Chunliang; DeMarco, Ashley C; Haroon, Ebrahim; Rilling, James K

2015-07-01

Neuroticism is a fundamental personality trait associated with proneness to feel negative affect. Here we ask how Neuroticism influences the neural response to positive and negative social interactions and how Neuroticism modulates the effect of intranasal oxytocin (OT) and vasopressin (AVP) on the neural response to social interactions. In a double-blind, placebo-controlled study, 153 male participants were randomized to receive 24 IU intranasal OT, 20 IU AVP or placebo. Afterwards, they were imaged with fMRI while playing an iterated Prisoner's Dilemma Game. On a different day, subjects completed the NEO personality inventory to measure Neuroticism. Neuroticism was positively correlated with the neural response to negative social interactions in the anterior cingulate cortex/medial prefrontal cortex and with the neural response to positive social interactions in the insula, indicating that Neuroticism modulates neuropsychological processing of both negative and positive social interactions. Neuroticism did not modulate the effect of intranasal OT treatment on the neural response to either positive or negative social interactions. On the other hand, AVP treatment significantly interacted with Neuroticism to modulate the BOLD response to both positive and negative social interactions. Specifically, AVP increased anterior cingulate cortex/medial prefrontal cortex and lateral temporal lobe responses to negative social interactions to a greater extent in participants scoring high rather than low on Neuroticism. AVP also increased the insula response to positive social interactions to a greater extent in participants scoring high rather than low on Neuroticism. These results imply that AVP may increase emotion regulation in response to negative social interactions and the salience of positive social interactions to a greater extent in individuals high compared to low in Neuroticism. The current findings urge caution against uniform clinical application of nonapeptides and suggest that their efficacy may vary as a function of personality. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interaction between DISC1 and CHL1 in regulation of neurite outgrowth.

PubMed

Ren, Jun; Zhao, Tian; Xu, Yiliang; Ye, Haihong

2016-10-01

Disrupted-in-schizophrenia 1 (DISC1), a gene susceptible for major mental illnesses, including schizophrenia, plays multiple roles in neural development, including neuronal proliferation, maturation, migration and neurite outgrowth. DISC1 regulates neurite length via interaction with several intracellular proteins, such as NDEL1, FEZ1 and dysbindin. However, the signal transduction mechanism upstream of DISC1 in regulating neurite outgrowth remains to be elucidated. Here we show that DISC1 interacts with the intracellular domain of close homolog of L1 (CHL1), a member of the L1 family of neural cell adhesion molecules. DISC1 and CHL1 proteins co-localize in growth cones of cortical neurons. Moreover, in neurite outgrowth assay, CHL1 rescues the inhibitory effect of DISC1 on the initial phase of neurite outgrowth. Considering the fact that CHL1 also plays crucial roles in neural development, and its coding gene is associated with schizophrenia, our findings indicate that DISC1 and CHL1 may engage in physical and functional interaction in neural development, supporting the notion that DISC1 regulates neurite outgrowth with a receptor belonging to the neural cell adhesion molecules, and disruption of such interaction may contribute to increased risk for schizophrenia. Copyright © 2016. Published by Elsevier B.V.

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.

Analysis of Power Laws, Shape Collapses, and Neural Complexity: New Techniques and MATLAB Support via the NCC Toolbox

PubMed Central

Marshall, Najja; Timme, Nicholas M.; Bennett, Nicholas; Ripp, Monica; Lautzenhiser, Edward; Beggs, John M.

2016-01-01

Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of “neural avalanches” (contiguous bursts of activity), but the fractal nature of avalanche shapes has recently emerged as another signature of criticality. On the other hand, neural complexity, an information theoretic measure, has been used to capture the interplay between the functional localization of brain regions and their integration for higher cognitive functions. Unfortunately, treatments of all three methods—power-law fitting, avalanche shape collapse, and neural complexity—have suffered from shortcomings. Empirical data often contain biases that introduce deviations from true power law in the tail and head of the distribution, but deviations in the tail have often been unconsidered; avalanche shape collapse has required manual parameter tuning; and the estimation of neural complexity has relied on small data sets or statistical assumptions for the sake of computational efficiency. In this paper we present technical advancements in the analysis of criticality and complexity in neural systems. We use maximum-likelihood estimation to automatically fit power laws with left and right cutoffs, present the first automated shape collapse algorithm, and describe new techniques to account for large numbers of neural variables and small data sets in the calculation of neural complexity. In order to facilitate future research in criticality and complexity, we have made the software utilized in this analysis freely available online in the MATLAB NCC (Neural Complexity and Criticality) Toolbox. PMID:27445842

Analysis of Power Laws, Shape Collapses, and Neural Complexity: New Techniques and MATLAB Support via the NCC Toolbox.

PubMed

Marshall, Najja; Timme, Nicholas M; Bennett, Nicholas; Ripp, Monica; Lautzenhiser, Edward; Beggs, John M

2016-01-01

Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of "neural avalanches" (contiguous bursts of activity), but the fractal nature of avalanche shapes has recently emerged as another signature of criticality. On the other hand, neural complexity, an information theoretic measure, has been used to capture the interplay between the functional localization of brain regions and their integration for higher cognitive functions. Unfortunately, treatments of all three methods-power-law fitting, avalanche shape collapse, and neural complexity-have suffered from shortcomings. Empirical data often contain biases that introduce deviations from true power law in the tail and head of the distribution, but deviations in the tail have often been unconsidered; avalanche shape collapse has required manual parameter tuning; and the estimation of neural complexity has relied on small data sets or statistical assumptions for the sake of computational efficiency. In this paper we present technical advancements in the analysis of criticality and complexity in neural systems. We use maximum-likelihood estimation to automatically fit power laws with left and right cutoffs, present the first automated shape collapse algorithm, and describe new techniques to account for large numbers of neural variables and small data sets in the calculation of neural complexity. In order to facilitate future research in criticality and complexity, we have made the software utilized in this analysis freely available online in the MATLAB NCC (Neural Complexity and Criticality) Toolbox.

Alcohol-Induced Molecular Dysregulation in Human Embryonic Stem Cell-Derived Neural Precursor Cells

PubMed Central

Kim, Yi Young; Roubal, Ivan; Lee, Youn Soo; Kim, Jin Seok; Hoang, Michael; Mathiyakom, Nathan; Kim, Yong

2016-01-01

Adverse effect of alcohol on neural function has been well documented. Especially, the teratogenic effect of alcohol on neurodevelopment during embryogenesis has been demonstrated in various models, which could be a pathologic basis for fetal alcohol spectrum disorders (FASDs). While the developmental defects from alcohol abuse during gestation have been described, the specific mechanisms by which alcohol mediates these injuries have yet to be determined. Recent studies have shown that alcohol has significant effect on molecular and cellular regulatory mechanisms in embryonic stem cell (ESC) differentiation including genes involved in neural development. To test our hypothesis that alcohol induces molecular alterations during neural differentiation we have derived neural precursor cells from pluripotent human ESCs in the presence or absence of ethanol treatment. Genome-wide transcriptomic profiling identified molecular alterations induced by ethanol exposure during neural differentiation of hESCs into neural rosettes and neural precursor cell populations. The Database for Annotation, Visualization and Integrated Discovery (DAVID) functional analysis on significantly altered genes showed potential ethanol’s effect on JAK-STAT signaling pathway, neuroactive ligand-receptor interaction, Toll-like receptor (TLR) signaling pathway, cytokine-cytokine receptor interaction and regulation of autophagy. We have further quantitatively verified ethanol-induced alterations of selected candidate genes. Among verified genes we further examined the expression of P2RX3, which is associated with nociception, a peripheral pain response. We found ethanol significantly reduced the level of P2RX3 in undifferentiated hESCs, but induced the level of P2RX3 mRNA and protein in hESC-derived NPCs. Our result suggests ethanol-induced dysregulation of P2RX3 along with alterations in molecules involved in neural activity such as neuroactive ligand-receptor interaction may be a molecular event associated with alcohol-related peripheral neuropathy of an enhanced nociceptive response. PMID:27682028

Short-term dynamics of causal information transfer in thalamocortical networks during natural inputs and microstimulation for somatosensory neuroprosthesis

PubMed Central

Semework, Mulugeta; DiStasio, Marcello

2014-01-01

Recording the activity of large populations of neurons requires new methods to analyze and use the large volumes of time series data thus created. Fast and clear methods for finding functional connectivity are an important step toward the goal of understanding neural processing. This problem presents itself readily in somatosensory neuroprosthesis (SSNP) research, which uses microstimulation (MiSt) to activate neural tissue to mimic natural stimuli, and has the capacity to potentiate, depotentiate, or even destroy functional connections. As the aim of SSNP engineering is artificially creating neural responses that resemble those observed during natural inputs, a central goal is describing the influence of MiSt on activity structure among groups of neurons, and how this structure may be altered to affect perception or behavior. In this paper, we demonstrate the concept of Granger causality, combined with maximum likelihood methods, applied to neural signals recorded before, during, and after natural and electrical stimulation. We show how these analyses can be used to evaluate the changing interactions in the thalamocortical somatosensory system in response to repeated perturbation. Using LFPs recorded from the ventral posterolateral thalamus (VPL) and somatosensory cortex (S1) in anesthetized rats, we estimated pair-wise functional interactions between functional microdomains. The preliminary results demonstrate input-dependent modulations in the direction and strength of information flow during and after application of MiSt. Cortico-cortical interactions during cortical MiSt and baseline conditions showed the largest causal influence differences, while there was no statistically significant difference between pre- and post-stimulation baseline causal activities. These functional connectivity changes agree with physiologically accepted communication patterns through the network, and their particular parameters have implications for both rehabilitation and brain—machine interface SSNP applications. PMID:25249973

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

PubMed Central

Soltoggio, Andrea; Lemme, Andre; Reinhart, Felix; Steil, Jochen J.

2013-01-01

Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms. PMID:23565092

Common capacity-limited neural mechanisms of selective attention and spatial working memory encoding

PubMed Central

Fusser, Fabian; Linden, David E J; Rahm, Benjamin; Hampel, Harald; Haenschel, Corinna; Mayer, Jutta S

2011-01-01

One characteristic feature of visual working memory (WM) is its limited capacity, and selective attention has been implicated as limiting factor. A possible reason why attention constrains the number of items that can be encoded into WM is that the two processes share limited neural resources. Functional magnetic resonance imaging (fMRI) studies have indeed demonstrated commonalities between the neural substrates of WM and attention. Here we investigated whether such overlapping activations reflect interacting neural mechanisms that could result in capacity limitations. To independently manipulate the demands on attention and WM encoding within one single task, we combined visual search and delayed discrimination of spatial locations. Participants were presented with a search array and performed easy or difficult visual search in order to encode one, three or five positions of target items into WM. Our fMRI data revealed colocalised activation for attention-demanding visual search and WM encoding in distributed posterior and frontal regions. However, further analysis yielded two patterns of results. Activity in prefrontal regions increased additively with increased demands on WM and attention, indicating regional overlap without functional interaction. Conversely, the WM load-dependent activation in visual, parietal and premotor regions was severely reduced during high attentional demand. We interpret this interaction as indicating the sites of shared capacity-limited neural resources. Our findings point to differential contributions of prefrontal and posterior regions to the common neural mechanisms that support spatial WM encoding and attention, providing new imaging evidence for attention-based models of WM encoding. PMID:21781193

Friend versus foe: Neural correlates of prosocial decisions for liked and disliked peers.

PubMed

Schreuders, Elisabeth; Klapwijk, Eduard T; Will, Geert-Jan; Güroğlu, Berna

2018-02-01

Although the majority of our social interactions are with people we know, few studies have investigated the neural correlates of sharing valuable resources with familiar others. Using an ecologically valid research paradigm, this functional magnetic resonance imaging study examined the neural correlates of prosocial and selfish behavior in interactions with real-life friends and disliked peers in young adults. Participants (N = 27) distributed coins between themselves and another person, where they could make selfish choices that maximized their own gains or prosocial choices that maximized outcomes of the other. Participants were more prosocial toward friends and more selfish toward disliked peers. Individual prosociality levels toward friends were associated negatively with supplementary motor area and anterior insula activity. Further preliminary analyses showed that prosocial decisions involving friends were associated with heightened activity in the bilateral posterior temporoparietal junction, and selfish decisions involving disliked peers were associated with heightened superior temporal sulcus activity, which are brain regions consistently shown to be involved in mentalizing and perspective taking in prior studies. Further, activation of the putamen was observed during prosocial choices involving friends and selfish choices involving disliked peers. These findings provide insights into the modulation of neural processes that underlie prosocial behavior as a function of a positive or negative relationship with the interaction partner.

In our own image? Emotional and neural processing differences when observing human–human vs human–robot interactions

PubMed Central

Wang, Yin

2015-01-01

Notwithstanding the significant role that human–robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human–human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal–parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots. PMID:25911418

A Model of Amygdala-Hippocampal-Prefrontal Interaction in Fear Conditioning and Extinction in Animals

ERIC Educational Resources Information Center

Moustafa, Ahmed A.; Gilbertson, Mark W.; Orr, Scott P.; Herzallah, Mohammad M.; Servatius, Richard J.; Myers, Catherine E.

2013-01-01

Empirical research has shown that the amygdala, hippocampus, and ventromedial prefrontal cortex (vmPFC) are involved in fear conditioning. However, the functional contribution of each brain area and the nature of their interactions are not clearly understood. Here, we extend existing neural network models of the functional roles of the hippocampus…

Neuroimaging in pedophilia.

PubMed

Wiebking, Christine; Northoff, Georg

2013-04-01

Paraphilia is a set of disorders characterized by abnormal sexual desires. Perhaps most discussed amongst them, pedophilia is a complex interaction of disturbances of the emotional, cognitive and sexual experience. Using new imaging techniques such as functional magnetic resonance imaging, neural correlates of emotional, sexual and cognitive abnormalities and interactions have been investigated. As described on the basis of current research, altered patterns of brain activity, especially in the frontal areas of the brain, are seen in pedophilia. Building on these results, the analysis of neural correlates of impaired psychological functions opens the opportunity to further explore sexual deviances, which may contribute ultimately to the development of tools for risk assessment, classification methods and new therapeutic approaches.

The interactive effect of social pain and executive functioning on aggression: an fMRI experiment

PubMed Central

Eisenberger, Naomi I.; Pond, Richard S.; Richman, Stephanie B.; Bushman, Brad J.; DeWall, C. Nathan

2014-01-01

Social rejection often increases aggression, but the neural mechanisms underlying this effect remain unclear. This experiment tested whether neural activity in the dorsal anterior cingulate cortex (dACC) and anterior insula in response to social rejection predicted greater subsequent aggression. Additionally, it tested whether executive functioning moderated this relationship. Participants completed a behavioral measure of executive functioning, experienced social rejection while undergoing functional magnetic resonance imaging and then completed a task in which they could aggress against a person who rejected them using noise blasts . We found that dACC activation and executive functioning interacted to predict aggression. Specifically, participants with low executive functioning showed a positive association between dACC activation and aggression, whereas individuals with high executive functioning showed a negative association. Similar results were found for the left anterior insula. These findings suggest that social pain can increase or decrease aggression, depending on an individual’s regulatory capability. PMID:23482622

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review

PubMed Central

McClelland, James L.

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered. PMID:23970868

Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review.

PubMed

McClelland, James L

2013-01-01

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.

Long-range functional interactions of anterior insula and medial frontal cortex are differently modulated by visuospatial and inductive reasoning tasks.

PubMed

Ebisch, Sjoerd J H; Mantini, Dante; Romanelli, Roberta; Tommasi, Marco; Perrucci, Mauro G; Romani, Gian Luca; Colom, Roberto; Saggino, Aristide

2013-09-01

The brain is organized into functionally specific networks as characterized by intrinsic functional relationships within discrete sets of brain regions. However, it is poorly understood whether such functional networks are dynamically organized according to specific task-states. The anterior insular cortex (aIC)-dorsal anterior cingulate cortex (dACC)/medial frontal cortex (mFC) network has been proposed to play a central role in human cognitive abilities. The present functional magnetic resonance imaging (fMRI) study aimed at testing whether functional interactions of the aIC-dACC/mFC network in terms of temporally correlated patterns of neural activity across brain regions are dynamically modulated by transitory, ongoing task demands. For this purpose, functional interactions of the aIC-dACC/mFC network are compared during two distinguishable fluid reasoning tasks, Visualization and Induction. The results show an increased functional coupling of bilateral aIC with visual cortices in the occipital lobe during the Visualization task, whereas coupling of mFC with right anterior frontal cortex was enhanced during the Induction task. These task-specific modulations of functional interactions likely reflect ability related neural processing. Furthermore, functional connectivity strength between right aIC and right dACC/mFC reliably predicts general task performance. The findings suggest that the analysis of long-range functional interactions may provide complementary information about brain-behavior relationships. On the basis of our results, it is proposed that the aIC-dACC/mFC network contributes to the integration of task-common and task-specific information based on its within-network as well as its between-network dynamic functional interactions. Copyright © 2013 Elsevier Inc. All rights reserved.

Vestigial-like 3 is a novel Ets1 interacting partner and regulates trigeminal nerve formation and cranial neural crest migration

PubMed Central

Simon, Emilie; Thézé, Nadine; Fédou, Sandrine; Thiébaud, Pierre

2017-01-01

ABSTRACT Drosophila Vestigial is the founding member of a protein family containing a highly conserved domain, called Tondu, which mediates their interaction with members of the TEAD family of transcription factors (Scalloped in Drosophila). In Drosophila, the Vestigial/Scalloped complex controls wing development by regulating the expression of target genes through binding to MCAT sequences. In vertebrates, there are four Vestigial-like genes, the functions of which are still not well understood. Here, we describe the regulation and function of vestigial-like 3 (vgll3) during Xenopus early development. A combination of signals, including FGF8, Wnt8a, Hoxa2, Hoxb2 and retinoic acid, limits vgll3 expression to hindbrain rhombomere 2. We show that vgll3 regulates trigeminal placode and nerve formation and is required for normal neural crest development by affecting their migration and adhesion properties. At the molecular level, vgll3 is a potent activator of pax3, zic1, Wnt and FGF, which are important for brain patterning and neural crest cell formation. Vgll3 interacts in the embryo with Tead proteins but unexpectedly with Ets1, with which it is able to stimulate a MCAT driven luciferase reporter gene. Our findings highlight a critical function for vgll3 in vertebrate early development. PMID:28870996

Coordination dynamics in a socially situated nervous system

PubMed Central

Coey, Charles A.; Varlet, Manuel; Richardson, Michael J.

2012-01-01

Traditional theories of cognitive science have typically accounted for the organization of human behavior by detailing requisite computational/representational functions and identifying neurological mechanisms that might perform these functions. Put simply, such approaches hold that neural activity causes behavior. This same general framework has been extended to accounts of human social behavior via concepts such as “common-coding” and “co-representation” and much recent neurological research has been devoted to brain structures that might execute these social-cognitive functions. Although these neural processes are unquestionably involved in the organization and control of human social interactions, there is good reason to question whether they should be accorded explanatory primacy. Alternatively, we propose that a full appreciation of the role of neural processes in social interactions requires appropriately situating them in their context of embodied-embedded constraints. To this end, we introduce concepts from dynamical systems theory and review research demonstrating that the organization of human behavior, including social behavior, can be accounted for in terms of self-organizing processes and lawful dynamics of animal-environment systems. Ultimately, we hope that these alternative concepts can complement the recent advances in cognitive neuroscience and thereby provide opportunities to develop a complete and coherent account of human social interaction. PMID:22701413

Perceived live interaction modulates the developing social brain.

PubMed

Rice, Katherine; Moraczewski, Dustin; Redcay, Elizabeth

2016-09-01

Although children's social development is embedded in social interaction, most developmental neuroscience studies have examined responses to non-interactive social stimuli (e.g. photographs of faces). The neural mechanisms of real-world social behavior are of special interest during middle childhood (roughly ages 7-13), a time of increased social complexity and competence coinciding with structural and functional social brain development. Evidence from adult neuroscience studies suggests that social interaction may alter neural processing, but no neuroimaging studies in children have directly examined the effects of live social-interactive context on social cognition. In the current study of middle childhood, we compare the processing of two types of speech: speech that children believed was presented over a real-time audio-feed by a social partner and speech that they believed was recorded. Although in reality all speech was prerecorded, perceived live speech resulted in significantly greater neural activation in regions associated with social cognitive processing. These findings underscore the importance of using ecologically-valid and interactive methods to understand the developing social brain. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder.

PubMed

Elton, Amanda; Di Martino, Adriana; Hazlett, Heather Cody; Gao, Wei

2016-07-15

Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

PubMed

Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

2017-10-13

The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.

Information-geometric measures estimate neural interactions during oscillatory brain states

PubMed Central

Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

2014-01-01

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain. PMID:24605089

Information-geometric measures estimate neural interactions during oscillatory brain states.

PubMed

Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

2014-01-01

The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

mTOR regulates brain morphogenesis by mediating GSK3 signaling

PubMed Central

Ka, Minhan; Condorelli, Gianluigi; Woodgett, James R.; Kim, Woo-Yang

2014-01-01

Balanced control of neural progenitor maintenance and neuron production is crucial in establishing functional neural circuits during brain development, and abnormalities in this process are implicated in many neurological diseases. However, the regulatory mechanisms of neural progenitor homeostasis remain poorly understood. Here, we show that mammalian target of rapamycin (mTOR) is required for maintaining neural progenitor pools and plays a key role in mediating glycogen synthase kinase 3 (GSK3) signaling during brain development. First, we generated and characterized conditional mutant mice exhibiting deletion of mTOR in neural progenitors and neurons in the developing brain using Nestin-cre and Nex-cre lines, respectively. The elimination of mTOR resulted in abnormal cell cycle progression of neural progenitors in the developing brain and thereby disruption of progenitor self-renewal. Accordingly, production of intermediate progenitors and postmitotic neurons were markedly suppressed. Next, we discovered that GSK3, a master regulator of neural progenitors, interacts with mTOR and controls its activity in cortical progenitors. Finally, we found that inactivation of mTOR activity suppresses the abnormal proliferation of neural progenitors induced by GSK3 deletion. Our findings reveal that the interaction between mTOR and GSK3 signaling plays an essential role in dynamic homeostasis of neural progenitors during brain development. PMID:25273085

Role of FGF and noggin in neural crest induction.

PubMed

Mayor, R; Guerrero, N; Martínez, C

1997-09-01

A study of the molecules noggin and fibroblast growth factor (FGF) and its receptor in the induction of the prospective neural crest in Xenopus laevis embryos has been carried out, using the expression of the gene Xslu as a marker for the neural crest. We show that when a truncated FGF receptor (XFD) was expressed ectopically in order to block FGF signaling Xslu expression was inhibited. The effect of XFD on Xslu was specific and could be reversed by the coinjection of the wild-type FGF receptor (FGFR). Inhibition of Xslu expression by XFD is not a consequence of neural plate inhibition, as was shown by analyzing Xsox-2 expression. When ectoderm expressing XFD was transplanted into the prospective neural fold region of embryos Xslu induction was inhibited. The neural crest can also be induced by an interaction between neural plate and epidermis. As this induction is suppressed by the presence of XFD in the neural plate and not in the epidermis, it suggests that the neural crest is induced by FGF from the epidermis. However, treatment of neural plate with FGF was not able to induce Xslug expression, showing that in addition to FGF other non-FGF factors are also required. Previously we have suggested that the ectopic ventral expression of Xslu produced by overexpression of noggin mRNA resulted from an interaction of noggin with a ventral signal. Overexpression of XFD inhibits this effect, suggesting that FGF could be one component involved in this ventral signaling. Overexpression of FGFR produced a remarkable increase in the expression of Xslu in the posterior neural folds and around the blastopore. Injections in different blastomeres of the embryo suggest that the target cells of this effect are the ventral cells. Finally, we proposed a model in which the induction of the neural crests at the border of the neural plate requires functional FGF signaling, which possibly interacts with a neural inducer such as noggin.

Neural and behavioural changes in male periadolescent mice after prolonged nicotine-MDMA treatment.

PubMed

Adeniyi, Philip A; Ishola, Azeez O; Laoye, Babafemi J; Olatunji, Babawale P; Bankole, Oluwamolakun O; Shallie, Philemon D; Ogundele, Olalekan M

2016-02-01

The interaction between MDMA and Nicotine affects multiple brain centres and neurotransmitter systems (serotonin, dopamine and glutamate) involved in motor coordination and cognition. In this study, we have elucidated the effect of prolonged (10 days) MDMA, Nicotine and a combined Nicotine-MDMA treatment on motor-cognitive neural functions. In addition, we have shown the correlation between the observed behavioural change and neural structural changes induced by these treatments in BALB/c mice. We observed that MDMA (2 mg/Kg body weight; subcutaneous) induced a decline in motor function, while Nicotine (2 mg/Kg body weight; subcutaneous) improved motor function in male periadolescent mice. In combined treatment, Nicotine reduced the motor function decline observed in MDMA treatment, thus no significant change in motor function for the combined treatment versus the control. Nicotine or MDMA treatment reduced memory function and altered hippocampal structure. Similarly, a combined Nicotine-MDMA treatment reduced memory function when compared with the control. Ultimately, the metabolic and structural changes in these neural systems were seen to vary for the various forms of treatment. It is noteworthy to mention that a combined treatment increased the rate of lipid peroxidation in brain tissue.

GW182 controls Drosophila circadian behavior and PDF-Receptor signaling

PubMed Central

Zhang, Yong; Emery, Patrick

2013-01-01

The neuropeptide PDF is crucial for Drosophila circadian behavior: it keeps circadian neurons synchronized. Here, we identify GW182 as a key regulator of PDF signaling. Indeed, GW182 downregulation results in phenotypes similar to those of Pdf and Pdf-receptor (Pdfr) mutants. gw182 genetically interacts with Pdfr and cAMP signaling, which is essential for PDFR function. GW182 mediates miRNA-dependent gene silencing through its interaction with AGO1. Consistently, GW182's AGO1 interaction domain is required for GW182's circadian function. Moreover, our results indicate that GW182 modulates PDFR signaling by silencing the expression of the cAMP phosphodiesterase DUNCE. Importantly, this repression is under photic control, and GW182 activity level - which is limiting in circadian neurons - influences the responses of the circadian neural network to light. We propose that GW182's gene silencing activity functions as a rheostat for PDFR signaling, and thus profoundly impacts the circadian neural network and its response to environmental inputs. PMID:23583112

Similar patterns of neural activity predict memory function during encoding and retrieval.

PubMed

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Two Unipolar Terminal-Attractor-Based Associative Memories

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Wu, Chwan-Hwa

1995-01-01

Two unipolar mathematical models of electronic neural network functioning as terminal-attractor-based associative memory (TABAM) developed. Models comprise sets of equations describing interactions between time-varying inputs and outputs of neural-network memory, regarded as dynamical system. Simplifies design and operation of optoelectronic processor to implement TABAM performing associative recall of images. TABAM concept described in "Optoelectronic Terminal-Attractor-Based Associative Memory" (NPO-18790). Experimental optoelectronic apparatus that performed associative recall of binary images described in "Optoelectronic Inner-Product Neural Associative Memory" (NPO-18491).

Study of the functional hyperconnectivity between couples of pilots during flight simulation: an EEG hyperscanning study.

PubMed

Astolfi, L; Toppi, J; Borghini, G; Vecchiato, G; Isabella, R; De Vico Fallani, F; Cincotti, F; Salinari, S; Mattia, D; He, B; Caltagirone, C; Babiloni, F

2011-01-01

Brain Hyperscanning, i.e. the simultaneous recording of the cerebral activity of different human subjects involved in interaction tasks, is a very recent field of Neuroscience aiming at understanding the cerebral processes generating and generated by social interactions. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects, and, even more interestingly, of the functional links existing between the activities in the brains of the subjects interacting together. In this EEG hyperscanning study we explored the functional hyperconnectivity between the activity in different scalp sites of couples of Civil Aviation Pilots during different phases of a flight reproduced in a flight simulator. Results shown a dense network of connections between the two brains in the takeoff and landing phases, when the cooperation between them is maximal, in contrast with phases during which the activity of the two pilots was independent, when no or quite few links were shown. These results confirms that the study of the brain connectivity between the activity simultaneously acquired in human brains during interaction tasks can provide important information about the neural basis of the "spirit of the group".

A neural basis for category and modality specificity of semantic knowledge.

PubMed

Thompson-Schill, S L; Aguirre, G K; D'Esposito, M; Farah, M J

1999-06-01

Prevalent theories hold that semantic memory is organized by sensorimotor modality (e.g., visual knowledge, motor knowledge). While some neuroimaging studies support this idea, it cannot account for the category specific (e.g., living things) knowledge impairments seen in some brain damaged patients that cut across modalities. In this article we test an alternative model of how damage to interactive, modality-specific neural regions might give rise to these categorical impairments. Functional MRI was used to examine a cortical area with a known modality-specific function during the retrieval of visual and non-visual knowledge about living and non-living things. The specific predictions of our model regarding the signal observed in this area were confirmed, supporting the notion that semantic memory is functionally segregated into anatomically discrete, but highly interactive, modality-specific regions.

Solving the quantum many-body problem with artificial neural networks

NASA Astrophysics Data System (ADS)

Carleo, Giuseppe; Troyer, Matthias

2017-02-01

The challenge posed by the many-body problem in quantum physics originates from the difficulty of describing the nontrivial correlations encoded in the exponential complexity of the many-body wave function. Here we demonstrate that systematic machine learning of the wave function can reduce this complexity to a tractable computational form for some notable cases of physical interest. We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons. A reinforcement-learning scheme we demonstrate is capable of both finding the ground state and describing the unitary time evolution of complex interacting quantum systems. Our approach achieves high accuracy in describing prototypical interacting spins models in one and two dimensions.

Why we interact: on the functional role of the striatum in the subjective experience of social interaction.

PubMed

Pfeiffer, Ulrich J; Schilbach, Leonhard; Timmermans, Bert; Kuzmanovic, Bojana; Georgescu, Alexandra L; Bente, Gary; Vogeley, Kai

2014-11-01

There is ample evidence that human primates strive for social contact and experience interactions with conspecifics as intrinsically rewarding. Focusing on gaze behavior as a crucial means of human interaction, this study employed a unique combination of neuroimaging, eye-tracking, and computer-animated virtual agents to assess the neural mechanisms underlying this component of behavior. In the interaction task, participants believed that during each interaction the agent's gaze behavior could either be controlled by another participant or by a computer program. Their task was to indicate whether they experienced a given interaction as an interaction with another human participant or the computer program based on the agent's reaction. Unbeknownst to them, the agent was always controlled by a computer to enable a systematic manipulation of gaze reactions by varying the degree to which the agent engaged in joint attention. This allowed creating a tool to distinguish neural activity underlying the subjective experience of being engaged in social and non-social interaction. In contrast to previous research, this allows measuring neural activity while participants experience active engagement in real-time social interactions. Results demonstrate that gaze-based interactions with a perceived human partner are associated with activity in the ventral striatum, a core component of reward-related neurocircuitry. In contrast, interactions with a computer-driven agent activate attention networks. Comparisons of neural activity during interaction with behaviorally naïve and explicitly cooperative partners demonstrate different temporal dynamics of the reward system and indicate that the mere experience of engagement in social interaction is sufficient to recruit this system. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural assembly computing.

PubMed

Ranhel, João

2012-06-01

Spiking neurons can realize several computational operations when firing cooperatively. This is a prevalent notion, although the mechanisms are not yet understood. A way by which neural assemblies compute is proposed in this paper. It is shown how neural coalitions represent things (and world states), memorize them, and control their hierarchical relations in order to perform algorithms. It is described how neural groups perform statistic logic functions as they form assemblies. Neural coalitions can reverberate, becoming bistable loops. Such bistable neural assemblies become short- or long-term memories that represent the event that triggers them. In addition, assemblies can branch and dismantle other neural groups generating new events that trigger other coalitions. Hence, such capabilities and the interaction among assemblies allow neural networks to create and control hierarchical cascades of causal activities, giving rise to parallel algorithms. Computing and algorithms are used here as in a nonstandard computation approach. In this sense, neural assembly computing (NAC) can be seen as a new class of spiking neural network machines. NAC can explain the following points: 1) how neuron groups represent things and states; 2) how they retain binary states in memories that do not require any plasticity mechanism; and 3) how branching, disbanding, and interaction among assemblies may result in algorithms and behavioral responses. Simulations were carried out and the results are in agreement with the hypothesis presented. A MATLAB code is available as a supplementary material.

The coxsackievirus-adenovirus receptor reveals complex homophilic and heterophilic interactions on neural cells.

PubMed

Patzke, Christopher; Max, Klaas E A; Behlke, Joachim; Schreiber, Jadwiga; Schmidt, Hannes; Dorner, Armin A; Kröger, Stephan; Henning, Mechthild; Otto, Albrecht; Heinemann, Udo; Rathjen, Fritz G

2010-02-24

The coxsackievirus-adenovirus receptor (CAR) is a member of the Ig superfamily strongly expressed in the developing nervous system. Our histological investigations during development reveal an initial uniform distribution of CAR on all neural cells with a concentration on membranes that face the margins of the nervous system (e.g., the basal laminae and the ventricular side). At more advanced stages, CAR becomes downregulated and restricted to specific regions including areas rich in axonal and dendritic surfaces. To study the function of CAR on neural cells, we used the fiber knob of the adenovirus, extracellular CAR domains, blocking antibodies to CAR, as well as CAR-deficient neural cells. Blocking antibodies were found to inhibit neurite extension in retina organ and retinal explant cultures, whereas the application of the recombinant fiber knob of the adenovirus subtype Ad2 or extracellular CAR domains promoted neurite extension and adhesion to extracellular matrices. We observed a promiscuous interaction of CAR with extracellular matrix glycoproteins, which was deduced from analytical ultracentrifugation experiments, affinity chromatography, and adhesion assays. The membrane proximal Ig domain of CAR, termed D2, was found to bind to a fibronectin fragment, including the heparin-binding domain 2, which promotes neurite extension of wild type, but not of CAR-deficient neural cells. In contrast to heterophilic interactions, homophilic association of CAR involves both Ig domains, as was revealed by ultracentrifugation, chemical cross-linking, and adhesion studies. The results of these functional and binding studies are correlated to a U-shaped homodimer of the complete extracellular domains of CAR detected by x-ray crystallography.

Genetic Moderation of Stress Effects on Corticolimbic Circuitry.

PubMed

Bogdan, Ryan; Pagliaccio, David; Baranger, David Aa; Hariri, Ahmad R

2016-01-01

Stress exposure is associated with individual differences in corticolimbic structure and function that often mirror patterns observed in psychopathology. Gene x environment interaction research suggests that genetic variation moderates the impact of stress on risk for psychopathology. On the basis of these findings, imaging genetics, which attempts to link variability in DNA sequence and structure to neural phenotypes, has begun to incorporate measures of the environment. This research paradigm, known as imaging gene x environment interaction (iGxE), is beginning to contribute to our understanding of the neural mechanisms through which genetic variation and stress increase psychopathology risk. Although awaiting replication, evidence suggests that genetic variation within the canonical neuroendocrine stress hormone system, the hypothalamic-pituitary-adrenal axis, contributes to variability in stress-related corticolimbic structure and function, which, in turn, confers risk for psychopathology. For iGxE research to reach its full potential it will have to address many challenges, of which we discuss: (i) small effects, (ii) measuring the environment and neural phenotypes, (iii) the absence of detailed mechanisms, and (iv) incorporating development. By actively addressing these challenges, iGxE research is poised to help identify the neural mechanisms underlying genetic and environmental associations with psychopathology.

Enhancer Analysis Unveils Genetic Interactions between TLX and SOX2 in Neural Stem Cells and In Vivo Reprogramming.

PubMed

Islam, Mohammed M; Smith, Derek K; Niu, Wenze; Fang, Sanhua; Iqbal, Nida; Sun, Guoqiang; Shi, Yanhong; Zhang, Chun-Li

2015-11-10

The orphan nuclear receptor TLX is a master regulator of postnatal neural stem cell (NSC) self-renewal and neurogenesis; however, it remains unclear how TLX expression is precisely regulated in these tissue-specific stem cells. Here, we show that a highly conserved cis-element within the Tlx locus functions to drive gene expression in NSCs. We demonstrate that the transcription factors SOX2 and MYT1 specifically interact with this genomic element to directly regulate Tlx enhancer activity in vivo. Knockdown experiments further reveal that SOX2 dominantly controls endogenous expression of TLX, whereas MYT1 only plays a modulatory role. Importantly, TLX is essential for SOX2-mediated in vivo reprogramming of astrocytes and itself is also sufficient to induce neurogenesis in the adult striatum. Together, these findings unveil functional genetic interactions among transcription factors that are critical to NSCs and in vivo cell reprogramming.

An RNA-binding protein, Qki5, regulates embryonic neural stem cells through pre-mRNA processing in cell adhesion signaling.

PubMed

Hayakawa-Yano, Yoshika; Suyama, Satoshi; Nogami, Masahiro; Yugami, Masato; Koya, Ikuko; Furukawa, Takako; Zhou, Li; Abe, Manabu; Sakimura, Kenji; Takebayashi, Hirohide; Nakanishi, Atsushi; Okano, Hideyuki; Yano, Masato

2017-09-15

Cell type-specific transcriptomes are enabled by the action of multiple regulators, which are frequently expressed within restricted tissue regions. In the present study, we identify one such regulator, Quaking 5 (Qki5), as an RNA-binding protein (RNABP) that is expressed in early embryonic neural stem cells and subsequently down-regulated during neurogenesis. mRNA sequencing analysis in neural stem cell culture indicates that Qki proteins play supporting roles in the neural stem cell transcriptome and various forms of mRNA processing that may result from regionally restricted expression and subcellular localization. Also, our in utero electroporation gain-of-function study suggests that the nuclear-type Qki isoform Qki5 supports the neural stem cell state. We next performed in vivo transcriptome-wide protein-RNA interaction mapping to search for direct targets of Qki5 and elucidate how Qki5 regulates neural stem cell function. Combined with our transcriptome analysis, this mapping analysis yielded a bona fide map of Qki5-RNA interaction at single-nucleotide resolution, the identification of 892 Qki5 direct target genes, and an accurate Qki5-dependent alternative splicing rule in the developing brain. Last, our target gene list provides the first compelling evidence that Qki5 is associated with specific biological events; namely, cell-cell adhesion. This prediction was confirmed by histological analysis of mice in which Qki proteins were genetically ablated, which revealed disruption of the apical surface of the lateral wall in the developing brain. These data collectively indicate that Qki5 regulates communication between neural stem cells by mediating numerous RNA processing events and suggest new links between splicing regulation and neural stem cell states. © 2017 Hayakawa-Yano et al.; Published by Cold Spring Harbor Laboratory Press.

Fatty acid–induced gut-brain signaling attenuates neural and behavioral effects of sad emotion in humans

PubMed Central

Van Oudenhove, Lukas; McKie, Shane; Lassman, Daniel; Uddin, Bilal; Paine, Peter; Coen, Steven; Gregory, Lloyd; Tack, Jan; Aziz, Qasim

2011-01-01

Although a relationship between emotional state and feeding behavior is known to exist, the interactions between signaling initiated by stimuli in the gut and exteroceptively generated emotions remain incompletely understood. Here, we investigated the interaction between nutrient-induced gut-brain signaling and sad emotion induced by musical and visual cues at the behavioral and neural level in healthy nonobese subjects undergoing functional magnetic resonance imaging. Subjects received an intragastric infusion of fatty acid solution or saline during neutral or sad emotion induction and rated sensations of hunger, fullness, and mood. We found an interaction between fatty acid infusion and emotion induction both in the behavioral readouts (hunger, mood) and at the level of neural activity in multiple pre-hypothesized regions of interest. Specifically, the behavioral and neural responses to sad emotion induction were attenuated by fatty acid infusion. These findings increase our understanding of the interplay among emotions, hunger, food intake, and meal-induced sensations in health, which may have important implications for a wide range of disorders, including obesity, eating disorders, and depression. PMID:21785220

[Research Progress on the Interaction Effects and Its Neural Mechanisms between Physical Fatigue and Mental Fatigue].

PubMed

Zhang, Lixin; Zhang, Chuncui; He, Feng; Zhao, Xin; Qi, Hongzhi; Wan, Baikun; Ming, Dong

2015-10-01

Fatigue is an exhaustion state caused by prolonged physical work and mental work, which can reduce working efficiency and even cause industrial accidents. Fatigue is a complex concept involving both physiological and psychological factors. Fatigue can cause a decline of concentration and work performance and induce chronic diseases. Prolonged fatigue may endanger life safety. In most of the scenarios, physical and mental workloads co-lead operator into fatigue state. Thus, it is very important to study the interaction influence and its neural mechanisms between physical and mental fatigues. This paper introduces recent progresses on the interaction effects and discusses some research challenges and future development directions. It is believed that mutual influence between physical fatigue and mental fatigue may occur in the central nervous system. Revealing the basal ganglia function and dopamine release may be important to explore the neural mechanisms between physical fatigue and mental fatigue. Future effort is to optimize fatigue models, to evaluate parameters and to explore the neural mechanisms so as to provide scientific basis and theoretical guidance for complex task designs and fatigue monitoring.

Fatty acid-induced gut-brain signaling attenuates neural and behavioral effects of sad emotion in humans.

PubMed

Van Oudenhove, Lukas; McKie, Shane; Lassman, Daniel; Uddin, Bilal; Paine, Peter; Coen, Steven; Gregory, Lloyd; Tack, Jan; Aziz, Qasim

2011-08-01

Although a relationship between emotional state and feeding behavior is known to exist, the interactions between signaling initiated by stimuli in the gut and exteroceptively generated emotions remain incompletely understood. Here, we investigated the interaction between nutrient-induced gut-brain signaling and sad emotion induced by musical and visual cues at the behavioral and neural level in healthy nonobese subjects undergoing functional magnetic resonance imaging. Subjects received an intragastric infusion of fatty acid solution or saline during neutral or sad emotion induction and rated sensations of hunger, fullness, and mood. We found an interaction between fatty acid infusion and emotion induction both in the behavioral readouts (hunger, mood) and at the level of neural activity in multiple pre-hypothesized regions of interest. Specifically, the behavioral and neural responses to sad emotion induction were attenuated by fatty acid infusion. These findings increase our understanding of the interplay among emotions, hunger, food intake, and meal-induced sensations in health, which may have important implications for a wide range of disorders, including obesity, eating disorders, and depression.

Consciousness, cognition and brain networks: New perspectives.

PubMed

Aldana, E M; Valverde, J L; Fábregas, N

2016-10-01

A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

Future trends in Neuroimaging: Neural processes as expressed within real-life contexts

PubMed Central

Hasson, Uri; Honey, Christopher J.

2012-01-01

Human neuroscience research has changed dramatically with the proliferation and refinement of functional magnetic resonance imaging (fMRI) technologies. The early years of the technique were largely devoted to methods development and validation, and to the coarse-grained mapping of functional topographies. This paper will cover three emerging trends that we believe will be central to fMRI research in the coming decade. In the first section of this paper, we argue in favor of a shift from fine-grained functional labeling toward the characterization of underlying neural processes. In the second section, we examine three methodological developments that have improved our ability to characterize underlying neural processes using fMRI. In the last section, we highlight the trend towards more ecologically valid fMRI experiments, which engage neural circuits in real life conditions. We note that many of our cognitive faculties emerge from interpersonal interactions, and that a complete understanding of the cognitive processes within a single individual's brain cannot be achieved without understanding the interactions among individuals. Looking forward to the future of human fMRI, we conclude that the major constraint on new discoveries will not be related to the spatiotemporal resolution of the BOLD signal, which is constantly improving, but rather to the precision of our hypotheses and the creativity of our methods for testing them. PMID:22348879

Deconstructing Memory in Drosophila

PubMed Central

Margulies, Carla; Tully, Tim; Dubnau, Josh

2011-01-01

Unlike most organ systems, which have evolved to maintain homeostasis, the brain has been selected to sense and adapt to environmental stimuli by constantly altering interactions in a gene network that functions within a larger neural network. This unique feature of the central nervous system provides a remarkable plasticity of behavior, but also makes experimental investigations challenging. Each experimental intervention ramifies through both gene and neural networks, resulting in unpredicted and sometimes confusing phenotypic adaptations. Experimental dissection of mechanisms underlying behavioral plasticity ultimately must accomplish an integration across many levels of biological organization, including genetic pathways acting within individual neurons, neural network interactions which feed back to gene function, and phenotypic observations at the behavioral level. This dissection will be more easily accomplished for model systems such as Drosophila, which, compared with mammals, have relatively simple and manipulable nervous systems and genomes. The evolutionary conservation of behavioral phenotype and the underlying gene function ensures that much of what we learn in such model systems will be relevant to human cognition. In this essay, we have not attempted to review the entire Drosophila memory field. Instead, we have tried to discuss particular findings that provide some level of intellectual synthesis across three levels of biological organization: behavior, neural circuitry and biochemical pathways. We have attempted to use this integrative approach to evaluate distinct mechanistic hypotheses, and to propose critical experiments that will advance this field. PMID:16139203

Neural Correlates of Dynamically Evolving Interpersonal Ties Predict Prosocial Behavior

PubMed Central

Fahrenfort, Johannes J.; van Winden, Frans; Pelloux, Benjamin; Stallen, Mirre; Ridderinkhof, K. Richard

2011-01-01

There is a growing interest for the determinants of human choice behavior in social settings. Upon initial contact, investment choices in social settings can be inherently risky, as the degree to which the other person will reciprocate is unknown. Nevertheless, people have been shown to exhibit prosocial behavior even in one-shot laboratory settings where all interaction has been taken away. A logical step has been to link such behavior to trait empathy-related neurobiological networks. However, as a social interaction unfolds, the degree of uncertainty with respect to the expected payoff of choice behavior may change as a function of the interaction. Here we attempt to capture this factor. We show that the interpersonal tie one develops with another person during interaction – rather than trait empathy – motivates investment in a public good that is shared with an anonymous interaction partner. We examined how individual differences in trait empathy and interpersonal ties modulate neural responses to imposed monetary sharing. After, but not before interaction in a public good game, sharing prompted activation of neural systems associated with reward (striatum), empathy (anterior insular cortex and anterior cingulate cortex) as well as altruism, and social significance [posterior superior temporal sulcus (pSTS)]. Although these activations could be linked to both empathy and interpersonal ties, only tie-related pSTS activation predicted prosocial behavior during subsequent interaction, suggesting a neural substrate for keeping track of social relevance. PMID:22403524

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition

PubMed Central

2017-01-01

Abstract There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women. PMID:28497111

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition.

PubMed

Scherf, K Suzanne; Elbich, Daniel B; Motta-Mena, Natalie V

2017-01-01

There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women.

Vestigial-like 3 is a novel Ets1 interacting partner and regulates trigeminal nerve formation and cranial neural crest migration.

PubMed

Simon, Emilie; Thézé, Nadine; Fédou, Sandrine; Thiébaud, Pierre; Faucheux, Corinne

2017-10-15

Drosophila Vestigial is the founding member of a protein family containing a highly conserved domain, called Tondu, which mediates their interaction with members of the TEAD family of transcription factors (Scalloped in Drosophila ). In Drosophila , the Vestigial/Scalloped complex controls wing development by regulating the expression of target genes through binding to MCAT sequences. In vertebrates, there are four Vestigial-like genes, the functions of which are still not well understood. Here, we describe the regulation and function of vestigial-like 3 (vgll3) during Xenopus early development. A combination of signals, including FGF8, Wnt8a, Hoxa2, Hoxb2 and retinoic acid, limits vgll3 expression to hindbrain rhombomere 2. We show that vgll3 regulates trigeminal placode and nerve formation and is required for normal neural crest development by affecting their migration and adhesion properties. At the molecular level, vgll3 is a potent activator of pax3 , zic1 , Wnt and FGF , which are important for brain patterning and neural crest cell formation. Vgll3 interacts in the embryo with Tead proteins but unexpectedly with Ets1, with which it is able to stimulate a MCAT driven luciferase reporter gene. Our findings highlight a critical function for vgll3 in vertebrate early development. © 2017. Published by The Company of Biologists Ltd.

Multistability of second-order competitive neural networks with nondecreasing saturated activation functions.

PubMed

Nie, Xiaobing; Cao, Jinde

2011-11-01

In this paper, second-order interactions are introduced into competitive neural networks (NNs) and the multistability is discussed for second-order competitive NNs (SOCNNs) with nondecreasing saturated activation functions. Firstly, based on decomposition of state space, Cauchy convergence principle, and inequality technique, some sufficient conditions ensuring the local exponential stability of 2N equilibrium points are derived. Secondly, some conditions are obtained for ascertaining equilibrium points to be locally exponentially stable and to be located in any designated region. Thirdly, the theory is extended to more general saturated activation functions with 2r corner points and a sufficient criterion is given under which the SOCNNs can have (r+1)N locally exponentially stable equilibrium points. Even if there is no second-order interactions, the obtained results are less restrictive than those in some recent works. Finally, three examples with their simulations are presented to verify the theoretical analysis.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging.

PubMed

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging

PubMed Central

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research. PMID:29033866

A functional magnetic resonance imaging investigation of theory of mind impairments in patients with temporal lobe epilepsy.

PubMed

Hennion, Sophie; Delbeuck, Xavier; Koelkebeck, Katja; Brion, Marine; Tyvaert, Louise; Plomhause, Lucie; Derambure, Philippe; Lopes, Renaud; Szurhaj, William

2016-12-01

Although patients with mesial temporal lobe epilepsy (mTLE) are known to have theory of mind (ToM) impairments, the latter's neural functional bases have yet to be explored. We used functional magnetic resonance imaging (fMRI) to gain insights into the neural dysfunction associated with ToM impairments in patients with mTLE. Twenty-five patients (12 and 13 with right and left mTLE, respectively) and 25 healthy controls performed the "animated shapes" task during fMRI. This complex ToM task requires both explicit reasoning about mental states and implicit processing of information on biological motion and action. The animated shapes evoke both ToM and non-ToM interaction perception, and the corresponding neural activation patterns were compared. Behavioral performance (i.e. categorization of the interactions) was also recorded. Relative to healthy controls, both patients with right and left mTLE were impaired in categorizing ToM interactions. The fMRI results showed that both patients with right and left mTLE had less intense neural activation (relative to controls) in regions involved in the implicit component of ToM processes (i.e. the fusiform gyrus in patients with right mTLE and the supplementary motor area in patients with left mTLE). In patients with right mTLE, we also observed more intense activation (relative to controls) in regions involved in the explicit component of ToM processes (i.e. the dorsal medial prefrontal cortex); age at onset of epilepsy also mediated activation in regions involved in the explicit component (i.e. the ventral medial prefrontal cortex and the temporoparietal junction). Patients with left mTLE displayed greater activation of the contralateral mesial regions (relative to controls); we speculate that this may correspond to the deployment of a compensatory mechanism. This study provides insights into the disturbances of the implicit/explicit ToM neural network in patients with mTLE. These impairments in the ToM neural network depend on clinical characteristics, such as the laterality (right or left mTLE) and the age at onset of epilepsy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Information flow between interacting human brains: Identification, validation, and relationship to social expertise.

PubMed

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-04-21

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.

The neural correlates of reciprocity are sensitive to prior experience of reciprocity.

PubMed

Cáceda, Ricardo; Prendes-Alvarez, Stefania; Hsu, Jung-Jiin; Tripathi, Shanti P; Kilts, Clint D; James, G Andrew

2017-08-14

Reciprocity is central to human relationships and is strongly influenced by multiple factors including the nature of social exchanges and their attendant emotional reactions. Despite recent advances in the field, the neural processes involved in this modulation of reciprocal behavior by ongoing social interaction are poorly understood. We hypothesized that activity within a discrete set of neural networks including a putative moral cognitive neural network is associated with reciprocity behavior. Nineteen healthy adults underwent functional magnetic resonance imaging scanning while playing the trustee role in the Trust Game. Personality traits and moral development were assessed. Independent component analysis was used to identify task-related functional brain networks and assess their relationship to behavior. The saliency network (insula and anterior cingulate) was positively correlated with reciprocity behavior. A consistent array of brain regions supports the engagement of emotional, self-referential and planning processes during social reciprocity behavior. Published by Elsevier B.V.

Development of the brain's functional network architecture.

PubMed

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Development of the Brain's Functional Network Architecture

PubMed Central

Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

Older adults benefit from music training early in life: biological evidence for long-term training-driven plasticity.

PubMed

White-Schwoch, Travis; Woodruff Carr, Kali; Anderson, Samira; Strait, Dana L; Kraus, Nina

2013-11-06

Aging results in pervasive declines in nervous system function. In the auditory system, these declines include neural timing delays in response to fast-changing speech elements; this causes older adults to experience difficulty understanding speech, especially in challenging listening environments. These age-related declines are not inevitable, however: older adults with a lifetime of music training do not exhibit neural timing delays. Yet many people play an instrument for a few years without making a lifelong commitment. Here, we examined neural timing in a group of human older adults who had nominal amounts of music training early in life, but who had not played an instrument for decades. We found that a moderate amount (4-14 years) of music training early in life is associated with faster neural timing in response to speech later in life, long after training stopped (>40 years). We suggest that early music training sets the stage for subsequent interactions with sound. These experiences may interact over time to sustain sharpened neural processing in central auditory nuclei well into older age.

Older Adults Benefit from Music Training Early in Life: Biological Evidence for Long-Term Training-Driven Plasticity

PubMed Central

White-Schwoch, Travis; Carr, Kali Woodruff; Anderson, Samira; Strait, Dana L.

2013-01-01

Aging results in pervasive declines in nervous system function. In the auditory system, these declines include neural timing delays in response to fast-changing speech elements; this causes older adults to experience difficulty understanding speech, especially in challenging listening environments. These age-related declines are not inevitable, however: older adults with a lifetime of music training do not exhibit neural timing delays. Yet many people play an instrument for a few years without making a lifelong commitment. Here, we examined neural timing in a group of human older adults who had nominal amounts of music training early in life, but who had not played an instrument for decades. We found that a moderate amount (4–14 years) of music training early in life is associated with faster neural timing in response to speech later in life, long after training stopped (>40 years). We suggest that early music training sets the stage for subsequent interactions with sound. These experiences may interact over time to sustain sharpened neural processing in central auditory nuclei well into older age. PMID:24198359

Perception of social synchrony induces mother–child gamma coupling in the social brain

PubMed Central

Levy, Jonathan; Goldstein, Abraham

2017-01-01

Abstract The recent call to move from focus on one brain’s functioning to two-brain communication initiated a search for mechanisms that enable two humans to coordinate brain response during social interactions. Here, we utilized the mother–child context as a developmentally salient setting to study two-brain coupling. Mothers and their 9-year-old children were videotaped at home in positive and conflictual interactions. Positive interactions were microcoded for social synchrony and conflicts for overall dialogical style. Following, mother and child underwent magnetoencephalography while observing the positive vignettes. Episodes of behavioral synchrony, compared to non-synchrony, increased gamma-band power in the superior temporal sulcus (STS), hub of social cognition, mirroring and mentalizing. This neural pattern was coupled between mother and child. Brain-to-brain coordination was anchored in behavioral synchrony; only during episodes of behavioral synchrony, but not during non-synchronous moments, mother’s and child's STS gamma power was coupled. Importantly, neural synchrony was not found during observation of unfamiliar mother-child interaction Maternal empathic/dialogical conflict style predicted mothers’ STS activations whereas child withdrawal predicted attenuated STS response in both partners. Results define a novel neural marker for brain-to-brain synchrony, highlight the role of rapid bottom-up oscillatory mechanisms for neural coupling and indicate that behavior-based processes may drive synchrony between two brains during social interactions. PMID:28402479

Perception of social synchrony induces mother-child gamma coupling in the social brain.

PubMed

Levy, Jonathan; Goldstein, Abraham; Feldman, Ruth

2017-07-01

The recent call to move from focus on one brain's functioning to two-brain communication initiated a search for mechanisms that enable two humans to coordinate brain response during social interactions. Here, we utilized the mother-child context as a developmentally salient setting to study two-brain coupling. Mothers and their 9-year-old children were videotaped at home in positive and conflictual interactions. Positive interactions were microcoded for social synchrony and conflicts for overall dialogical style. Following, mother and child underwent magnetoencephalography while observing the positive vignettes. Episodes of behavioral synchrony, compared to non-synchrony, increased gamma-band power in the superior temporal sulcus (STS), hub of social cognition, mirroring and mentalizing. This neural pattern was coupled between mother and child. Brain-to-brain coordination was anchored in behavioral synchrony; only during episodes of behavioral synchrony, but not during non-synchronous moments, mother's and child's STS gamma power was coupled. Importantly, neural synchrony was not found during observation of unfamiliar mother-child interaction Maternal empathic/dialogical conflict style predicted mothers' STS activations whereas child withdrawal predicted attenuated STS response in both partners. Results define a novel neural marker for brain-to-brain synchrony, highlight the role of rapid bottom-up oscillatory mechanisms for neural coupling and indicate that behavior-based processes may drive synchrony between two brains during social interactions. © The Author (2017). Published by Oxford University Press.

Functionally integrated neural processing of linguistic and talker information: An event-related fMRI and ERP study.

PubMed

Zhang, Caicai; Pugh, Kenneth R; Mencl, W Einar; Molfese, Peter J; Frost, Stephen J; Magnuson, James S; Peng, Gang; Wang, William S-Y

2016-01-01

Speech signals contain information of both linguistic content and a talker's voice. Conventionally, linguistic and talker processing are thought to be mediated by distinct neural systems in the left and right hemispheres respectively, but there is growing evidence that linguistic and talker processing interact in many ways. Previous studies suggest that talker-related vocal tract changes are processed integrally with phonetic changes in the bilateral posterior superior temporal gyrus/superior temporal sulcus (STG/STS), because the vocal tract parameter influences the perception of phonetic information. It is yet unclear whether the bilateral STG is also activated by the integral processing of another parameter - pitch, which influences the perception of lexical tone information and is related to talker differences in tone languages. In this study, we conducted separate functional magnetic resonance imaging (fMRI) and event-related potential (ERP) experiments to examine the spatial and temporal loci of interactions of lexical tone and talker-related pitch processing in Cantonese. We found that the STG was activated bilaterally during the processing of talker changes when listeners attended to lexical tone changes in the stimuli and during the processing of lexical tone changes when listeners attended to talker changes, suggesting that lexical tone and talker processing are functionally integrated in the bilateral STG. It extends the previous study, providing evidence for a general neural mechanism of integral phonetic and talker processing in the bilateral STG. The ERP results show interactions of lexical tone and talker processing 500-800ms after auditory word onset (a simultaneous posterior P3b and a frontal negativity). Moreover, there is some asymmetry in the interaction, such that unattended talker changes affect linguistic processing more than vice versa, which may be related to the ambiguity that talker changes cause in speech perception and/or attention bias to talker changes. Our findings have implications for understanding the neural encoding of linguistic and talker information. Copyright © 2015 Elsevier Inc. All rights reserved.

Dynamic adjustments in prefrontal, hippocampal, and inferior temporal interactions with increasing visual working memory load.

PubMed

Rissman, Jesse; Gazzaley, Adam; D'Esposito, Mark

2008-07-01

The maintenance of visual stimuli across a delay interval in working memory tasks is thought to involve reverberant neural communication between the prefrontal cortex and posterior visual association areas. Recent studies suggest that the hippocampus might also contribute to this retention process, presumably via reciprocal interactions with visual regions. To characterize the nature of these interactions, we performed functional connectivity analysis on an event-related functional magnetic resonance imaging data set in which participants performed a delayed face recognition task. As the number of faces that participants were required to remember was parametrically increased, the right inferior frontal gyrus (IFG) showed a linearly decreasing degree of functional connectivity with the fusiform face area (FFA) during the delay period. In contrast, the hippocampus linearly increased its delay period connectivity with both the FFA and the IFG as the mnemonic load increased. Moreover, the degree to which participants' FFA showed a load-dependent increase in its connectivity with the hippocampus predicted the degree to which its connectivity with the IFG decreased with load. Thus, these neural circuits may dynamically trade off to accommodate the particular mnemonic demands of the task, with IFG-FFA interactions mediating maintenance at lower loads and hippocampal interactions supporting retention at higher loads.

The roof plate boundary is a bi-directional organiser of dorsal neural tube and choroid plexus development

PubMed Central

Broom, Emma R.; Gilthorpe, Jonathan D.; Butts, Thomas; Campo-Paysaa, Florent; Wingate, Richard J. T.

2012-01-01

The roof plate is a signalling centre positioned at the dorsal midline of the central nervous system and generates dorsalising morphogenic signals along the length of the neuraxis. Within cranial ventricles, the roof plate gives rise to choroid plexus, which regulates the internal environment of the developing and adult brain and spinal cord via the secretion of cerebrospinal fluid. Using the fourth ventricle as our model, we show that the organiser properties of the roof plate are determined by its boundaries with the adjacent neuroepithelium. Through a combination of in ovo transplantation, co-culture and electroporation techniques in chick embryos between embryonic days 3 and 6, we demonstrate that organiser properties are maintained by interactions between the non-neural roof plate and the neural rhombic lip. At the molecular level, this interaction is mediated by Delta-Notch signalling and upregulation of the chick homologue of Hes1: chairy2. Gain- and loss-of-function approaches reveal that cdelta1 is both necessary and sufficient for organiser function. Our results also demonstrate that while chairy2 is specifically required for the maintenance of the organiser, its ectopic expression is not sufficient to recapitulate organiser properties. Expression of atonal1 in the rhombic lip adjacent at the roof plate boundary is acutely dependent on both boundary cell interactions and Delta-Notch signalling. Correspondingly, the roof plate boundary organiser also signals to the roof plate itself to specify the expression of early choroid plexus markers. Thus, the roof plate boundary organiser signals bi-directionally to acutely coordinate the development of adjacent neural and non-neural tissues. PMID:23052907

The roof plate boundary is a bi-directional organiser of dorsal neural tube and choroid plexus development.

PubMed

Broom, Emma R; Gilthorpe, Jonathan D; Butts, Thomas; Campo-Paysaa, Florent; Wingate, Richard J T

2012-11-01

The roof plate is a signalling centre positioned at the dorsal midline of the central nervous system and generates dorsalising morphogenic signals along the length of the neuraxis. Within cranial ventricles, the roof plate gives rise to choroid plexus, which regulates the internal environment of the developing and adult brain and spinal cord via the secretion of cerebrospinal fluid. Using the fourth ventricle as our model, we show that the organiser properties of the roof plate are determined by its boundaries with the adjacent neuroepithelium. Through a combination of in ovo transplantation, co-culture and electroporation techniques in chick embryos between embryonic days 3 and 6, we demonstrate that organiser properties are maintained by interactions between the non-neural roof plate and the neural rhombic lip. At the molecular level, this interaction is mediated by Delta-Notch signalling and upregulation of the chick homologue of Hes1: chairy2. Gain- and loss-of-function approaches reveal that cdelta1 is both necessary and sufficient for organiser function. Our results also demonstrate that while chairy2 is specifically required for the maintenance of the organiser, its ectopic expression is not sufficient to recapitulate organiser properties. Expression of atonal1 in the rhombic lip adjacent at the roof plate boundary is acutely dependent on both boundary cell interactions and Delta-Notch signalling. Correspondingly, the roof plate boundary organiser also signals to the roof plate itself to specify the expression of early choroid plexus markers. Thus, the roof plate boundary organiser signals bi-directionally to acutely coordinate the development of adjacent neural and non-neural tissues.

GW182 controls Drosophila circadian behavior and PDF-receptor signaling.

PubMed

Zhang, Yong; Emery, Patrick

2013-04-10

The neuropeptide PDF is crucial for Drosophila circadian behavior: it keeps circadian neurons synchronized. Here, we identify GW182 as a key regulator of PDF signaling. Indeed, GW182 downregulation results in phenotypes similar to those of Pdf and Pdf-receptor (Pdfr) mutants. gw182 genetically interacts with Pdfr and cAMP signaling, which is essential for PDFR function. GW182 mediates miRNA-dependent gene silencing through its interaction with AGO1. Consistently, GW182's AGO1 interaction domain is required for GW182's circadian function. Moreover, our results indicate that GW182 modulates PDFR signaling by silencing the expression of the cAMP phosphodiesterase DUNCE. Importantly, this repression is under photic control, and GW182 activity level--which is limiting in circadian neurons--influences the responses of the circadian neural network to light. We propose that GW182's gene silencing activity functions as a rheostat for PDFR signaling and thus profoundly impacts the circadian neural network and its response to environmental inputs. Copyright © 2013 Elsevier Inc. All rights reserved.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

PubMed

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

The extracellular matrix controls gap junction protein expression and function in postnatal hippocampal neural progenitor cells

PubMed Central

Imbeault, Sophie; Gauvin, Lianne G; Toeg, Hadi D; Pettit, Alexandra; Sorbara, Catherine D; Migahed, Lamiaa; DesRoches, Rebecca; Menzies, A Sheila; Nishii, Kiyomasa; Paul, David L; Simon, Alexander M; Bennett, Steffany AL

2009-01-01

Background Gap junction protein and extracellular matrix signalling systems act in concert to influence developmental specification of neural stem and progenitor cells. It is not known how these two signalling systems interact. Here, we examined the role of ECM components in regulating connexin expression and function in postnatal hippocampal progenitor cells. Results We found that Cx26, Cx29, Cx30, Cx37, Cx40, Cx43, Cx45, and Cx47 mRNA and protein but only Cx32 and Cx36 mRNA are detected in distinct neural progenitor cell populations cultured in the absence of exogenous ECM. Multipotential Type 1 cells express Cx26, Cx30, and Cx43 protein. Their Type 2a progeny but not Type 2b and 3 neuronally committed progenitor cells additionally express Cx37, Cx40, and Cx45. Cx29 and Cx47 protein is detected in early oligodendrocyte progenitors and mature oligodendrocytes respectively. Engagement with a laminin substrate markedly increases Cx26 protein expression, decreases Cx40, Cx43, Cx45, and Cx47 protein expression, and alters subcellular localization of Cx30. These changes are associated with decreased neurogenesis. Further, laminin elicits the appearance of Cx32 protein in early oligodendrocyte progenitors and Cx36 protein in immature neurons. These changes impact upon functional connexin-mediated hemichannel activity but not gap junctional intercellular communication. Conclusion Together, these findings demonstrate a new role for extracellular matrix-cell interaction, specifically laminin, in the regulation of intrinsic connexin expression and function in postnatal neural progenitor cells. PMID:19236721

Neural Systems Underlying Individual Differences in Intertemporal Decision-making.

PubMed

Elton, Amanda; Smith, Christopher T; Parrish, Michael H; Boettiger, Charlotte A

2017-03-01

Excessively choosing immediate over larger future rewards, or delay discounting (DD), associates with multiple clinical conditions. Individual differences in DD likely depend on variations in the activation of and functional interactions between networks, representing possible endophenotypes for associated disorders, including alcohol use disorders (AUDs). Numerous fMRI studies have probed the neural bases of DD, but investigations of large-scale networks remain scant. We addressed this gap by testing whether activation within large-scale networks during Now/Later decision-making predicts individual differences in DD. To do so, we scanned 95 social drinkers (18-40 years old; 50 women) using fMRI during hypothetical choices between small monetary amounts available "today" or larger amounts available later. We identified neural networks engaged during Now/Later choice using independent component analysis and tested the relationship between component activation and degree of DD. The activity of two components during Now/Later choice correlated with individual DD rates: A temporal lobe network positively correlated with DD, whereas a frontoparietal-striatal network negatively correlated with DD. Activation differences between these networks predicted individual differences in DD, and their negative correlation during Now/Later choice suggests functional competition. A generalized psychophysiological interactions analysis confirmed a decrease in their functional connectivity during decision-making. The functional connectivity of these two networks negatively correlates with alcohol-related harm, potentially implicating these networks in AUDs. These findings provide novel insight into the neural underpinnings of individual differences in impulsive decision-making with potential implications for addiction and related disorders in which impulsivity is a defining feature.

A Within-subjects Experimental Protocol to Assess the Effects of Social Input on Infant EEG.

PubMed

St John, Ashley M; Kao, Katie; Chita-Tegmark, Meia; Liederman, Jacqueline; Grieve, Philip G; Tarullo, Amanda R

2017-05-03

Despite the importance of social interactions for infant brain development, little research has assessed functional neural activation while infants socially interact. Electroencephalography (EEG) power is an advantageous technique to assess infant functional neural activation. However, many studies record infant EEG only during one baseline condition. This protocol describes a paradigm that is designed to comprehensively assess infant EEG activity in both social and nonsocial contexts as well as tease apart how different types of social inputs differentially relate to infant EEG. The within-subjects paradigm includes four controlled conditions. In the nonsocial condition, infants view objects on computer screens. The joint attention condition involves an experimenter directing the infant's attention to pictures. The joint attention condition includes three types of social input: language, face-to-face interaction, and the presence of joint attention. Differences in infant EEG between the nonsocial and joint attention conditions could be due to any of these three types of input. Therefore, two additional conditions (one with language input while the experimenter is hidden behind a screen and one with face-to-face interaction) were included to assess the driving contextual factors in patterns of infant neural activation. Representative results demonstrate that infant EEG power varied by condition, both overall and differentially by brain region, supporting the functional nature of infant EEG power. This technique is advantageous in that it includes conditions that are clearly social or nonsocial and allows for examination of how specific types of social input relate to EEG power. This paradigm can be used to assess how individual differences in age, affect, socioeconomic status, and parent-infant interaction quality relate to the development of the social brain. Based on the demonstrated functional nature of infant EEG power, future studies should consider the role of EEG recording context and design conditions that are clearly social or nonsocial.

Hippo signaling is required for Notch-dependent smooth muscle differentiation of neural crest.

PubMed

Manderfield, Lauren J; Aghajanian, Haig; Engleka, Kurt A; Lim, Lillian Y; Liu, Feiyan; Jain, Rajan; Li, Li; Olson, Eric N; Epstein, Jonathan A

2015-09-01

Notch signaling has well-defined roles in the assembly of arterial walls and in the development of the endothelium and smooth muscle of the vasculature. Hippo signaling regulates cellular growth in many tissues, and contributes to regulation of organ size, in addition to other functions. Here, we show that the Notch and Hippo pathways converge to regulate smooth muscle differentiation of the neural crest, which is crucial for normal development of the aortic arch arteries and cranial vasculature during embryonic development. Neural crest-specific deletion of the Hippo effectors Yap and Taz produces neural crest precursors that migrate normally, but fail to produce vascular smooth muscle, and Notch target genes such as Jagged1 fail to activate normally. We show that Yap is normally recruited to a tissue-specific Jagged1 enhancer by directly interacting with the Notch intracellular domain (NICD). The Yap-NICD complex is recruited to chromatin by the DNA-binding protein Rbp-J in a Tead-independent fashion. Thus, Hippo signaling can modulate Notch signaling outputs, and components of the Hippo and Notch pathways physically interact. Convergence of Hippo and Notch pathways by the mechanisms described here might be relevant for the function of these signaling cascades in many tissues and in diseases such as cancer. © 2015. Published by The Company of Biologists Ltd.

Dysfunction of sensory oscillations in Autism Spectrum Disorder

PubMed Central

Simon, David M.; Wallace, Mark T.

2016-01-01

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD. PMID:27451342

Hypothalamic neural systems controlling the female reproductive life cycle: Gonadotropin-releasing hormone, glutamate, and GABA

PubMed Central

Maffucci, Jacqueline A.; Gore, Andrea C.

2009-01-01

The hypothalamic-pituitary-gonadal (HPG) axis undergoes a number of changes throughout the reproductive life cycle that are responsible for the development, puberty, adulthood, and senescence of reproductive systems. This natural progression is dictated by the neural network controlling the hypothalamus including the cells that synthesize and release gonadotropin-releasing hormone (GnRH) and their regulatory neurotransmitters. Glutamate and GABA are the primary excitatory and inhibitory neurotransmitters in the central nervous system, and as such contribute a great deal to modulating this axis throughout the lifetime via their actions on receptors in the hypothalamus, both directly on GnRH neurons as well as indirectly though other hypothalamic neural networks. Interactions among GnRH neurons, glutamate, and GABA, including the regulation of GnRH gene and protein expression, hormone release, and modulation by estrogen, are critical to age-appropriate changes in reproductive function. Here, we present evidence for the modulation of GnRH neurosecretory cells by the balance of glutamate and GABA in the hypothalamus, and the functional consequences of these interactions on reproductive physiology across the life cycle. PMID:19349036

Electrophysiological channel interactions using focused multipolar stimulation for cochlear implants

NASA Astrophysics Data System (ADS)

George, Shefin S.; Shivdasani, Mohit N.; Wise, Andrew K.; Shepherd, Robert K.; Fallon, James B.

2015-12-01

Objective. Speech intelligibility with existing multichannel cochlear implants (CIs) is thought to be limited by poor spatial selectivity and interactions between CI channels caused by overlapping activation with monopolar (MP) stimulation. Our previous studies have shown that focused multipolar (FMP) and tripolar (TP) stimulation produce more restricted neural activation in the inferior colliculus (IC), compared to MP stimulation. Approach. This study explored interactions in the IC produced by simultaneous stimulation of two CI channels. We recorded multi-unit neural activity in the IC of anaesthetized cats with normal and severely degenerated spiral ganglion neuron populations in response to FMP, TP and MP stimulation from a 14 channel CI. Stimuli were applied to a ‘fixed’ CI channel, chosen toward the middle of the cochlear electrode array, and the effects of simultaneously stimulating a more apical ‘test’ CI channel were measured as a function of spatial separation between the two stimulation channels and stimulus level of the fixed channel. Channel interactions were quantified by changes in neural responses and IC threshold (i.e., threshold shift) elicited by simultaneous stimulation of two CI channels, compared to stimulation of the test channel alone. Main results. Channel interactions were significantly lower for FMP and TP than for MP stimulation (p < 0.001), whereas no significant difference was observed between FMP and TP stimulation. With MP stimulation, threshold shifts increased with decreased inter-electrode spacing and increased stimulus levels of the fixed channel. For FMP and TP stimulation, channel interactions were found to be similar for different inter-electrode spacing and stimulus levels of the fixed channel. Significance. The present study demonstrates how the degree of channel interactions in a CI can be controlled using stimulation configurations such as FMP and TP; such knowledge is essential in enhancing CI function in complex acoustic environments.

Brain correlates of recognition of communicative interactions from biological motion in schizophrenia.

PubMed

Okruszek, Ł; Wordecha, M; Jarkiewicz, M; Kossowski, B; Lee, J; Marchewka, A

2017-11-27

Recognition of communicative interactions is a complex social cognitive ability which is associated with a specific neural activity in healthy individuals. However, neural correlates of communicative interaction processing from whole-body motion have not been known in patients with schizophrenia (SCZ). Therefore, the current study aims to examine the neural activity associated with recognition of communicative interactions in SCZ by using displays of the dyadic interactions downgraded to minimalistic point-light presentations. Twenty-six healthy controls (HC) and 25 SCZ were asked to judge whether two agents presented only by point-light displays were communicating or acting independently. Task-related activity and functional connectivity of brain structures were examined with General Linear Model and Generalized Psychophysiological Interaction approach, respectively. HC were significantly more efficient in recognizing each type of action than SCZ. At the neural level, the activity of the right posterior superior temporal sulcus (pSTS) was observed to be higher in HC compared with SCZ for communicative v. individual action processing. Importantly, increased connectivity of the right pSTS with structures associated with mentalizing (left pSTS) and mirroring networks (left frontal areas) was observed in HC, but not in SCZ, during the presentation of social interactions. Under-recruitment of the right pSTS, a structure known to have a pivotal role in social processing, may also be of importance for higher-order social cognitive deficits in SCZ. Furthermore, decreased task-related connectivity of the right pSTS may result in reduced use of additional sources of information (for instance motor resonance signals) during social cognitive processing in schizophrenia.

Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

PubMed Central

Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B.

2012-01-01

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.

PubMed

Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B

2012-01-01

The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem.

Enhancer Analysis Unveils Genetic Interactions between TLX and SOX2 in Neural Stem Cells and In Vivo Reprogramming

PubMed Central

Islam, Mohammed M.; Smith, Derek K.; Niu, Wenze; Fang, Sanhua; Iqbal, Nida; Sun, Guoqiang; Shi, Yanhong; Zhang, Chun-Li

2015-01-01

Summary The orphan nuclear receptor TLX is a master regulator of postnatal neural stem cell (NSC) self-renewal and neurogenesis; however, it remains unclear how TLX expression is precisely regulated in these tissue-specific stem cells. Here, we show that a highly conserved cis-element within the Tlx locus functions to drive gene expression in NSCs. We demonstrate that the transcription factors SOX2 and MYT1 specifically interact with this genomic element to directly regulate Tlx enhancer activity in vivo. Knockdown experiments further reveal that SOX2 dominantly controls endogenous expression of TLX, whereas MYT1 only plays a modulatory role. Importantly, TLX is essential for SOX2-mediated in vivo reprogramming of astrocytes and itself is also sufficient to induce neurogenesis in the adult striatum. Together, these findings unveil functional genetic interactions among transcription factors that are critical to NSCs and in vivo cell reprogramming. PMID:26607952

Construction of multi-agent mobile robots control system in the problem of persecution with using a modified reinforcement learning method based on neural networks

NASA Astrophysics Data System (ADS)

Patkin, M. L.; Rogachev, G. N.

2018-02-01

A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.

Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe -decay searches

NASA Astrophysics Data System (ADS)

Caldwell, A.; Cossavella, F.; Majorovits, B.; Palioselitis, D.; Volynets, O.

2015-07-01

A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate variations of efficiencies as a function of used training set. It is verified that neural networks are well-suited to identify background pulses in true-coaxial high-purity germanium detectors. The systematic uncertainty on the signal recognition efficiency derived using signal-like evaluation samples from calibration measurements is estimated to be 5 %. This uncertainty is due to differences between signal and calibration samples.

Hybrid Thin Film Organosilica Sol-Gel Coatings To Support Neuronal Growth and Limit Astrocyte Growth.

PubMed

Capeletti, Larissa Brentano; Cardoso, Mateus Borba; Dos Santos, João Henrique Zimnoch; He, Wei

2016-10-07

Thin films of silica prepared by a sol-gel process are becoming a feasible coating option for surface modification of implantable neural sensors without imposing adverse effects on the devices' electrical properties. In order to advance the application of such silica-based coatings in the context of neural interfacing, the characteristics of silica sol-gel are further tailored to gain active control of interactions between cells and the coating materials. By incorporating various readily available organotrialkoxysilanes carrying distinct organic functional groups during the sol-gel process, a library of hybrid organosilica coatings is developed and investigated. In vitro neural cultures using PC12 cells and primary cortical neurons both reveal that, among these different types of hybrid organosilica, the introduction of aminopropyl groups drastically transforms the silica into robust neural permissive substrate, supporting neuron adhesion and neurite outgrowth. Moreover, when this organosilica is cultured with astrocytes, a key type of glial cells responsible for glial scar response toward neural implants, such cell growth promoting effect is not observed. These findings highlight the potential of organo-group-bearing silica sol-gel to function as advanced coating materials to selectively modulate cell response and promote neural integration with implantable sensing devices.

Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

The Neural Crest in Cardiac Congenital Anomalies

PubMed Central

Keyte, Anna; Hutson, Mary Redmond

2012-01-01

This review discusses the function of neural crest as they relate to cardiovascular defects. The cardiac neural crest cells are a subpopulation of cranial neural crest discovered nearly 30 years ago by ablation of premigratory neural crest. The cardiac neural crest cells are necessary for normal cardiovascular development. We begin with a description of the crest cells in normal development, including their function in remodeling the pharyngeal arch arteries, outflow tract septation, valvulogenesis, and development of the cardiac conduction system. The cells are also responsible for modulating signaling in the caudal pharynx, including the second heart field. Many of the molecular pathways that are known to influence specification, migration, patterning and final targeting of the cardiac neural crest cells are reviewed. The cardiac neural crest cells play a critical role in the pathogenesis of various human cardiocraniofacial syndromes such as DiGeorge, Velocardiofacial, CHARGE, Fetal Alcohol, Alagille, LEOPARD, and Noonan syndromes, as well as Retinoic Acid Embryopathy. The loss of neural crest cells or their dysfunction may not always directly cause abnormal cardiovascular development, but are involved secondarily because crest cells represent a major component in the complex tissue interactions in the head, pharynx and outflow tract. Thus many of the human syndromes linking defects in the heart, face and brain can be better understood when considered within the context of a single cardiocraniofacial developmental module with the neural crest being a key cell type that interconnects the regions. PMID:22595346

Carbon nanotubes in neural interfacing applications

NASA Astrophysics Data System (ADS)

Voge, Christopher M.; Stegemann, Jan P.

2011-02-01

Carbon nanotubes (CNT) are remarkable materials with a simple and inert molecular structure that gives rise to a range of potentially valuable physical and electronic properties, including high aspect ratio, high mechanical strength and excellent electrical conductivity. This review summarizes recent research on the application of CNT-based materials to study and control cells of the nervous system. It includes the use of CNT as cell culture substrates, to create patterned surfaces and to study cell-matrix interactions. It also summarizes recent investigations of CNT toxicity, particularly as related to neural cells. The application of CNT-based materials to directing the differentiation of progenitor and stem cells toward neural lineages is also discussed. The emphasis is on how CNT surface chemistry and nanotopography can be altered, and how such changes can affect neural cell function. This knowledge can be applied to creating improved neural interfaces and devices, as well as providing new approaches to neural tissue engineering and regeneration.

Ventral striatal hyperconnectivity during rewarded interference control in adolescents with ADHD.

PubMed

Ma, Ili; van Holstein, Mieke; Mies, Gabry W; Mennes, Maarten; Buitelaar, Jan; Cools, Roshan; Cillessen, Antonius H N; Krebs, Ruth M; Scheres, Anouk

2016-09-01

Attention-deficit/hyperactivity disorder (ADHD) is characterized by cognitive deficits (e.g., interference control) and altered reward processing. Cognitive control is influenced by incentive motivation and according to current theoretical models, ADHD is associated with abnormal interactions between incentive motivation and cognitive control. However, the neural mechanisms by which reward modulates cognitive control in individuals with ADHD are unknown. We used event-related functional resonance imaging (fMRI) to study neural responses during a rewarded Stroop color-word task in adolescents (14-17 years) with ADHD (n = 25; 19 boys) and healthy controls (n = 33; 22 boys). Adolescents with ADHD showed increased reward signaling within the superior frontal gyrus and ventral striatum (VS) relative to controls. Importantly, functional connectivity analyses revealed a hyperconnectivity between VS and motor control regions in the ADHD group, as a function of reward-cognitive control integration. Connectivity was associated with performance improvement in controls but not in the ADHD group, suggesting inefficient connectivity. Adolescents with ADHD show increased neural sensitivity to rewards and its interactions with interference control in VS and motor regions, respectively. The findings support theoretical models of altered reward-cognitive control integration in individuals with ADHD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility.

PubMed

Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L

2014-01-01

Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks was found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus was found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) was partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. © 2013.

Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility

PubMed Central

Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L.

2013-01-01

Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks were found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus were found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) were partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. PMID:24084068

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

NASA Astrophysics Data System (ADS)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

How the amygdala affects emotional memory by altering brain network properties.

PubMed

Hermans, Erno J; Battaglia, Francesco P; Atsak, Piray; de Voogd, Lycia D; Fernández, Guillén; Roozendaal, Benno

2014-07-01

The amygdala has long been known to play a key role in supporting memory for emotionally arousing experiences. For example, classical fear conditioning depends on neural plasticity within this anterior medial temporal lobe region. Beneficial effects of emotional arousal on memory, however, are not restricted to simple associative learning. Our recollection of emotional experiences often includes rich representations of, e.g., spatiotemporal context, visceral states, and stimulus-response associations. Critically, such memory features are known to bear heavily on regions elsewhere in the brain. These observations led to the modulation account of amygdala function, which postulates that amygdala activation enhances memory consolidation by facilitating neural plasticity and information storage processes in its target regions. Rodent work in past decades has identified the most important brain regions and neurochemical processes involved in these modulatory actions, and neuropsychological and neuroimaging work in humans has produced a large body of convergent data. Importantly, recent methodological developments make it increasingly realistic to monitor neural interactions underlying such modulatory effects as they unfold. For instance, functional connectivity network modeling in humans has demonstrated how information exchanges between the amygdala and specific target regions occur within the context of large-scale neural network interactions. Furthermore, electrophysiological and optogenetic techniques in rodents are beginning to make it possible to quantify and even manipulate such interactions with millisecond precision. In this paper we will discuss that these developments will likely lead to an updated view of the amygdala as a critical nexus within large-scale networks supporting different aspects of memory processing for emotionally arousing experiences. Copyright © 2014 Elsevier Inc. All rights reserved.

The immune-neuro-endocrine interactions.

PubMed

Tomaszewska, D; Przekop, F

1997-06-01

This article reviews data concerning the interactions between immune, endocrine and neural systems in physiological, pathophysiological and stress conditions in animals and humans. Numerous studies have provided evidence that these systems interact with each other in maintaining homeostasis. This interaction may be classified as follows: immune, endocrine and neural cell products coexist in lymphoid, endocrine and neural tissue. Endocrine and neural mediators modulate immune system activity. Immune, endocrine and neural cells express receptors for cytokines, hormones, neuropeptides and transmitters.

Relationships between Reward Sensitivity, Risk-Taking and Family History of Alcoholism during an Interactive Competitive fMRI Task

PubMed Central

Yarosh, Haley L.; Hyatt, Christopher J.; Meda, Shashwath A.; Jiantonio-Kelly, Rachel; Potenza, Marc N.; Assaf, Michal; D.Pearlson, Godfrey

2014-01-01

Background Individuals with a positive family history for alcoholism (FHP) have shown differences from family-history-negative (FHN) individuals in the neural correlates of reward processing. FHP, compared to FHN individuals, demonstrate relatively diminished ventral striatal activation during anticipation of monetary rewards, and the degree of ventral striatal activation shows an inverse correlation with specific impulsivity measures in alcohol-dependent individuals. Rewards in socially interactive contexts relate importantly to addictive propensities, yet have not been examined with respect to how their neural underpinnings relate to impulsivity-related measures. Here we describe impulsivity measures in FHN and FHP individuals as they relate to a socially interactive functional magnetic resonance imaging (fMRI) task. Methods Forty FHP and 29 FHN subjects without histories of Axis-I disorders completed a socially interactive Domino task during functional magnetic resonance imaging and completed self-report and behavioral impulsivity-related assessments. Results FHP compared to FHN individuals showed higher scores (p = .004) on one impulsivity-related factor relating to both compulsivity (Padua Inventory) and reward/punishment sensitivity (Sensitivity to Punishment/Sensitivity to Reward Questionnaire). Multiple regression analysis within a reward-related network revealed a correlation between risk-taking (involving another impulsivity-related factor, the Balloon Analog Risk Task (BART)) and right ventral striatum activation under reward >punishment contrast (p<0.05 FWE corrected) in the social task. Conclusions Behavioral risk-taking scores may be more closely associated with neural correlates of reward responsiveness in socially interactive contexts than are FH status or impulsivity-related self-report measures. These findings suggest that risk-taking assessments be examined further in socially interactive settings relevant to addictive behaviors. PMID:24505424

Oxytocin receptor polymorphism and childhood social experiences shape adult personality, brain structure and neural correlates of mentalizing.

PubMed

Schneider-Hassloff, H; Straube, B; Jansen, A; Nuscheler, B; Wemken, G; Witt, S H; Rietschel, M; Kircher, T

2016-07-01

The oxytocin system is involved in human social behavior and social cognition such as attachment, emotion recognition and mentalizing (i.e. the ability to represent mental states of oneself and others). It is shaped by social experiences in early life, especially by parent-infant interactions. The single nucleotid polymorphism rs53576 in the oxytocin receptor (OXTR) gene has been linked to social behavioral phenotypes. In 195 adult healthy subjects we investigated the interaction of OXTR rs53576 and childhood attachment security (CAS) on the personality traits "adult attachment style" and "alexithymia" (i.e. emotional self-awareness), on brain structure (voxel-based morphometry) and neural activation (fMRI) during an interactive mentalizing paradigm (prisoner's dilemma game; subgroup: n=163). We found that in GG-homozygotes, but not in A-allele carriers, insecure childhood attachment is - in adulthood - associated with a) higher attachment-related anxiety and alexithymia, b) higher brain gray matter volume of left amygdala and lower volumes in right superior parietal lobule (SPL), left temporal pole (TP), and bilateral frontal regions, and c) higher mentalizing-related neural activity in bilateral TP and precunei, and right middle and superior frontal gyri. Interaction effects of genotype and CAS on brain volume and/or function were associated with individual differences in alexithymia and attachment-related anxiety. Interactive effects were in part sexually dimorphic. The interaction of OXTR genotype and CAS modulates adult personality as well as brain structure and function of areas implicated in salience processing and mentalizing. Rs53576 GG-homozygotes are partially more susceptible to childhood attachment experiences than A-allele carriers. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural origins of psychosocial functioning impairments in major depression.

PubMed

Pulcu, Erdem; Elliott, Rebecca

2015-09-01

Major depressive disorder, a complex neuropsychiatric condition, is associated with psychosocial functioning impairments that could become chronic even after symptoms remit. Social functioning impairments in patients could also pose coping difficulties to individuals around them. In this Personal View, we trace the potential neurobiological origins of these impairments down to three candidate domains-namely, social perception and emotion processing, motivation and reward value processing, and social decision making. We argue that the neural basis of abnormalities in these domains could be detectable at different temporal stages during social interactions (eg, before and after decision stages), particularly within frontomesolimbic networks (ie, frontostriatal and amygdala-striatal circuitries). We review some of the experimental designs used to probe these circuits and suggest novel, integrative approaches. We propose that an understanding of the interactions between these domains could provide valuable insights for the clinical stratification of major depressive disorder subtypes and might inform future developments of novel treatment options in return. Copyright © 2015 Elsevier Ltd. All rights reserved.

Distinct Brain Systems Underlie the Processing of Valence and Arousal of Affective Pictures

ERIC Educational Resources Information Center

Nielen, M. M. A.; Heslenfeld, D. J.; Heinen, K.; Van Strien, J. W.; Witter, M. P.; Jonker, C.; Veltman, D. J.

2009-01-01

Valence and arousal are thought to be the primary dimensions of human emotion. However, the degree to which valence and arousal interact in determining brain responses to emotional pictures is still elusive. This functional MRI study aimed to delineate neural systems responding to valence and arousal, and their interaction. We measured neural…

Neural Correlates of Cross-Cultural Adaptation: How to Improve the Training and Selection for Military Personnel Involved in Cross-Cultural Interactions

DTIC Science & Technology

2015-09-01

of this study was to better understand the culture-general skills and traits needed to conduct successful cross-cultural interactions when lacking...5  2  Study 1: Online Behavioral Study ...12  3  Study 2: Functional Neuroimaging Study .......................................................... 13  3.1

Molecular parallels between neural and vascular development.

PubMed

Eichmann, Anne; Thomas, Jean-Léon

2013-01-01

The human central nervous system (CNS) features a network of ~400 miles of blood vessels that receives >20% of the body's cardiac output and uses most of its blood glucose. Many human diseases, including stroke, retinopathy, and cancer, are associated with the biology of CNS blood vessels. These vessels originate from extrinsic cell populations, including endothelial cells and pericytes that colonize the CNS and interact with glia and neurons to establish the blood-brain barrier and control cerebrovascular exchanges. Neurovascular interactions also play important roles in adult neurogenic niches, which harbor a unique population of neural stem cells that are intimately associated with blood vessels. We here review the cellular and molecular mechanisms required to establish the CNS vascular network, with a special focus on neurovascular interactions and the functions of vascular endothelial growth factors.

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

PubMed Central

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D.; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-01-01

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender’s and receiver’s temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions. PMID:25848050

Infrared neural stimulation in the cochlea

PubMed Central

Richter, Claus-Peter; Rajguru, Suhrud; Bendett, Mark

2014-01-01

The application of photonics to manipulate and stimulate neurons and to study neural networks has gained momentum over the last decade. Two general methods have been used: the genetic expression of light or temperature sensitive ion channels in the plasma membrane of neurons (Optogenetics and Thermogenetics) and the direct stimulation of neurons using infrared radiation (Infrared Neural Stimulation, INS). Both approaches have their strengths and challenges, which are well understood with a profound understanding of the light tissue interaction(s). This paper compares the opportunities of the methods for the use in cochlear prostheses. Ample data are already available on the stimulation of the cochlea with INS. The data show that the stimulation is selective, feasible at rates that would be sufficient to encode acoustic information and may be beneficial over conventional pulsed electrical stimulation. A third approach, using lasers in stress confinement to generate pressure waves and to stimulate the functional cochlea mechanically will also be discussed. PMID:25075260

Infrared neural stimulation in the cochlea

NASA Astrophysics Data System (ADS)

Richter, Claus-Peter; Rajguru, Suhrud; Bendett, Mark

2013-03-01

The application of photonics to manipulate and stimulate neurons and to study neural networks has gained momentum over the last decade. Two general methods have been used: the genetic expression of light or temperature sensitive ion channels in the plasma membrane of neurons (Optogenetics and Thermogenetics) and the direct stimulation of neurons using infrared radiation (Infrared Neural Stimulation, INS). Both approaches have their strengths and challenges, which are well understood with a profound understanding of the light tissue interaction(s). This paper compares the opportunities of the methods for the use in cochlear prostheses. Ample data are already available on the stimulation of the cochlea with INS. The data show that the stimulation is selective, feasible at rates that would be sufficient to encode acoustic information and may be beneficial over conventional pulsed electrical stimulation. A third approach, using lasers in stress confinement to generate pressure waves and to stimulate the functional cochlea mechanically will also be discussed.

Hippocampal-cortical interaction in decision making

PubMed Central

Yu, Jai Y.; Frank, Loren M.

2014-01-01

When making a decision it is often necessary to consider the available alternatives in order to choose the most appropriate option. This deliberative process, where the pros and cons of each option are considered, relies on memories of past actions and outcomes. The hippocampus and prefrontal cortex are required for memory encoding, memory retrieval and decision making, but it is unclear how these areas support deliberation. Here we examine the potential neural substrates of these processes in the rat. The rat is a powerful model to investigate the network mechanisms underlying deliberation in the mammalian brain given the anatomical and functional conservation of its hippocampus and prefrontal cortex to other mammalian systems. Importantly, it is amenable to large scale neural recording while performing laboratory tasks that exploit its natural decisionmaking behavior. Focusing on findings in the rat, we discuss how hippocampal-cortical interactions could provide a neural substrate for deliberative decision making. PMID:24530374

Identification of beta-2 as a key cell adhesion molecule in PCa cell neurotropic behavior: a novel ex vivo and biophysical approach.

PubMed

Jansson, Keith H; Castillo, Deborah G; Morris, Joseph W; Boggs, Mary E; Czymmek, Kirk J; Adams, Elizabeth L; Schramm, Lawrence P; Sikes, Robert A

2014-01-01

Prostate cancer (PCa) is believed to metastasize through the blood/lymphatics systems; however, PCa may utilize the extensive innervation of the prostate for glandular egress. The interaction of PCa and its nerve fibers is observed in 80% of PCa and is termed perineural invasion (PNI). PCa cells have been observed traveling through the endoneurium of nerves, although the underlying mechanisms have not been elucidated. Voltage sensitive sodium channels (VSSC) are multimeric transmembrane protein complexes comprised of a pore-forming α subunit and one or two auxiliary beta (β) subunits with inherent cell adhesion molecule (CAM) functions. The beta-2 isoform (gene SCN2B) interacts with several neural CAMs, while interacting putatively with other prominent neural CAMs. Furthermore, beta-2 exhibits elevated mRNA and protein levels in highly metastatic and castrate-resistant PCa. When overexpressed in weakly aggressive LNCaP cells (2BECFP), beta-2 alters LNCaP cell morphology and enhances LNCaP cell metastasis associated behavior in vitro. We hypothesize that PCa cells use beta-2 as a CAM during PNI and subsequent PCa metastasis. The objective of this study was to determine the effect of beta-2 expression on PCa cell neurotropic metastasis associated behavior. We overexpressed beta-2 as a fusion protein with enhanced cyan fluorescence protein (ECFP) in weakly aggressive LNCaP cells and observed neurotropic effects utilizing our novel ex vivo organotypic spinal cord co-culture model, and performed functional assays with neural matrices and atomic force microscopy. With increased beta-2 expression, PCa cells display a trend of enhanced association with nerve axons. On laminin, a neural CAM, overexpression of beta-2 enhances PCa cell migration, invasion, and growth. 2BECFP cells exhibit marked binding affinity to laminin relative to LNECFP controls, and recombinant beta-2 ectodomain elicits more binding events to laminin than BSA control. Functional overexpression of VSSC beta subunits in PCa may mediate PCa metastatic behavior through association with neural matrices.

Illusory Obesity Triggers Body Dissatisfaction Responses in the Insula and Anterior Cingulate Cortex

PubMed Central

Preston, Catherine; Ehrsson, H. Henrik

2016-01-01

In today's Western society, concerns regarding body size and negative feelings toward one's body are all too common. However, little is known about the neural mechanisms underlying negative feelings toward the body and how they relate to body perception and eating-disorder pathology. Here, we used multisensory illusions to elicit illusory ownership of obese and slim bodies during functional magnetic resonance imaging. The results implicate the anterior insula and the anterior cingulate cortex in the development of negative feelings toward the body through functional interactions with the posterior parietal cortex, which mediates perceived obesity. Moreover, cingulate neural responses were modulated by nonclinical eating-disorder psychopathology and were attenuated in females. These results reveal how perceptual and affective body representations interact in the human brain and may help explain the neurobiological underpinnings of eating-disorder vulnerability in women. PMID:27733537

Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H; Sun, Bilin

2016-11-01

Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features. Copyright © 2016. Published by Elsevier Inc.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

Neural mechanisms underlying sound-induced visual motion perception: An fMRI study.

PubMed

Hidaka, Souta; Higuchi, Satomi; Teramoto, Wataru; Sugita, Yoichi

2017-07-01

Studies of crossmodal interactions in motion perception have reported activation in several brain areas, including those related to motion processing and/or sensory association, in response to multimodal (e.g., visual and auditory) stimuli that were both in motion. Recent studies have demonstrated that sounds can trigger illusory visual apparent motion to static visual stimuli (sound-induced visual motion: SIVM): A visual stimulus blinking at a fixed location is perceived to be moving laterally when an alternating left-right sound is also present. Here, we investigated brain activity related to the perception of SIVM using a 7T functional magnetic resonance imaging technique. Specifically, we focused on the patterns of neural activities in SIVM and visually induced visual apparent motion (VIVM). We observed shared activations in the middle occipital area (V5/hMT), which is thought to be involved in visual motion processing, for SIVM and VIVM. Moreover, as compared to VIVM, SIVM resulted in greater activation in the superior temporal area and dominant functional connectivity between the V5/hMT area and the areas related to auditory and crossmodal motion processing. These findings indicate that similar but partially different neural mechanisms could be involved in auditory-induced and visually-induced motion perception, and neural signals in auditory, visual, and, crossmodal motion processing areas closely and directly interact in the perception of SIVM. Copyright © 2017 Elsevier B.V. All rights reserved.

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex.

PubMed

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were "non-task-specific" (NS) neurons that served as noise generators to "task-specific" neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors.

Interaction between oxytocin receptor polymorphism and interdependent culture values on human empathy

PubMed Central

Luo, Siyang; Ma, Yina; Liu, Yi; Li, Bingfeng; Wang, Chenbo; Shi, Zhenhao; Li, Xiaoyang; Zhang, Wenxia; Rao, Yi

2015-01-01

Recent evidence suggests that the association between oxytocin receptor polymorphism (OXTR rs53576) and emotion-related behavioral/psychological tendencies differs between individuals from East Asian and Western cultures. What remains unresolved is which specific dimension of cultural orientations interacts with OXTR rs53576 to shape these tendencies and whether such gene × culture interactions occurs at both behavioral and neural level. This study investigated whether and how OXTR rs53576 interacts with interdependence—a key dimension of cultural orientations that distinguish between East Asian and Western cultures—to affect human empathy that underlies altruistic motivation and prosocial behavior. Experiment 1 measured interdependence, empathy trait and OXTR rs53576 genotypes of 1536 Chinese participants. Hierarchical regression analyses revealed a stronger association between interdependence and empathy trait in G allele carriers compared with A/A homozygotes of OXTR rs53576. Experiment 2 measured neural responses to others’ suffering by scanning A/A and G/G homozygous of OXTR rs53576 using functional magnetic resonance imaging. Hierarchical regression analyses revealed stronger associations between interdependence and empathic neural responses in the insula, amygdala and superior temporal gyrus in G/G compared with A/A carriers. Our results provide the first evidence for gene × culture interactions on empathy at both behavioral tendency and underlying brain activity. PMID:25680993

Protein content and methyl donors in maternal diet interact to influence the proliferation rate and cell fate of neural stem cells in rat hippocampus.

PubMed

Amarger, Valérie; Lecouillard, Angèle; Ancellet, Laure; Grit, Isabelle; Castellano, Blandine; Hulin, Philippe; Parnet, Patricia

2014-10-14

Maternal diet during pregnancy and early postnatal life influences the setting up of normal physiological functions in the offspring. Epigenetic mechanisms regulate cell differentiation during embryonic development and may mediate gene/environment interactions. We showed here that high methyl donors associated with normal protein content in maternal diet increased the in vitro proliferation rate of neural stem/progenitor cells isolated from rat E19 fetuses. Gene expression on whole hippocampi at weaning confirmed this effect as evidenced by the higher expression of the Nestin and Igf2 genes, suggesting a higher amount of undifferentiated precursor cells. Additionally, protein restriction reduced the expression of the insulin receptor gene, which is essential to the action of IGFII. Inhibition of DNA methylation in neural stem/progenitor cells in vitro increased the expression of the astrocyte-specific Gfap gene and decreased the expression of the neuron-specific Dcx gene, suggesting an impact on cell differentiation. Our data suggest a complex interaction between methyl donors and protein content in maternal diet that influence the expression of major growth factors and their receptors and therefore impact the proliferation and differentiation capacities of neural stem cells, either through external hormone signals or internal genomic regulation.

Phase Transitions in Living Neural Networks

NASA Astrophysics Data System (ADS)

Williams-Garcia, Rashid Vladimir

Our nervous systems are composed of intricate webs of interconnected neurons interacting in complex ways. These complex interactions result in a wide range of collective behaviors with implications for features of brain function, e.g., information processing. Under certain conditions, such interactions can drive neural network dynamics towards critical phase transitions, where power-law scaling is conjectured to allow optimal behavior. Recent experimental evidence is consistent with this idea and it seems plausible that healthy neural networks would tend towards optimality. This hypothesis, however, is based on two problematic assumptions, which I describe and for which I present alternatives in this thesis. First, critical transitions may vanish due to the influence of an environment, e.g., a sensory stimulus, and so living neural networks may be incapable of achieving "critical" optimality. I develop a framework known as quasicriticality, in which a relative optimality can be achieved depending on the strength of the environmental influence. Second, the power-law scaling supporting this hypothesis is based on statistical analysis of cascades of activity known as neuronal avalanches, which conflate causal and non-causal activity, thus confounding important dynamical information. In this thesis, I present a new method to unveil causal links, known as causal webs, between neuronal activations, thus allowing for experimental tests of the quasicriticality hypothesis and other practical applications.

THE INTERACTION BETWEEN L1-TYPE PROTEINS AND ANKYRINS - A MASTER SWITCH FOR L1-TYPE CAM FUNCTION #

PubMed Central

HORTSCH, MICHAEL; NAGARAJ, KAKANAHALLI; GODENSCHWEGE, TANJA A.

2008-01-01

L1-type cell adhesion molecules (CAMs) are important mediators of neural differentiation, including axonal outgrowth and pathfinding and also of synapse formation and maintenance. In addition, their interactions with cytoskeletal components are highly conserved and regulated. How these different aspects of CAM functionality relate to each other is not well understood. Based on results from our and other laboratories we propose that Ankyrin-binding to L1-type CAMs provides a master switch. The interaction with Ankyrins directs L1-type adhesive proteins into different functional contexts, either Ankyrin-independent functions, such as neurite outgrowth and axonal pathfinding or into Ankyrin-dependent functions, such as L1’s role at axon initial segments (AIS), paranodal regions, synapses and in dendrites. PMID:18839070

Definition of tolerance to continuous hyperoxia in man - An abstract report of Predictive Studies V

NASA Technical Reports Server (NTRS)

Lambertsen, C. J.; Clark, J. M.; Gelfand, R.; Pisarello, J. B.; Cobbs, W. H.

1987-01-01

The overall goals, design, and procedures of Predictive Studies V are discussed as well as the specific elements of neural effects produced by prolonged hyperoxia. It is noted that Predictive Studies V study of oxygen poisoning in normal men during uninterrupted exposures to oxygen over the range of hyperbaric oxygen exposure most useful in diving, the treatment of gas lesion diseases, and general hyperbaric medicine. It is found that, throughout the study, the most striking observations were related to effects on visual function, on the lung, and the probable interactions of preconvulsive neural activity with effects on cardiovascular and respiratory-pulmonary functions.

[Neuronal and synaptic properties: fundamentals of network plasticity].

PubMed

Le Masson, G

2000-02-01

Neurons, within the nervous system, are organized in different neural networks through synaptic connections. Two fundamental components are dynamically interacting in these functional units. The first one are the neurons themselves, and far from being simple action potential generators, they are capable of complex electrical integrative properties due to various types, number, distribution and modulation of voltage-gated ionic channels. The second elements are the synapses where a similar complexity and plasticity is found. Identifying both cellular and synaptic intrinsic properties is necessary to understand the links between neural networks behavior and physiological function, and is a useful step towards a better control of neurological diseases.

Causal influence in neural systems: Reconciling mechanistic-reductionist and statistical perspectives. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino & S.L. Bressler

NASA Astrophysics Data System (ADS)

Griffiths, John D.

2015-12-01

The modern understanding of the brain as a large, complex network of interacting elements is a natural consequence of the Neuron Doctrine [1,2] that has been bolstered in recent years by the tools and concepts of connectomics. In this abstracted, network-centric view, the essence of neural and cognitive function derives from the flows between network elements of activity and information - or, more generally, causal influence. The appropriate characterization of causality in neural systems, therefore, is a question at the very heart of systems neuroscience.

Top-down modulation: the crossroads of perception, attention and memory

NASA Astrophysics Data System (ADS)

Gazzaley, Adam

2010-02-01

Research in our laboratory focuses on understanding the neural mechanisms that serve at the crossroads of perception, memory and attention, specifically exploring how brain region interactions underlie these abilities. To accomplish this, we study top-down modulation, the process by which we enhance neural activity associated with relevant information and suppress activity for irrelevant information, thus establishing a neural basis for all higher-order cognitive operations. We also study alterations in top-down modulation that occur with normal aging. Our experiments are performed on human participants, using a multimodal approach that integrates functional MRI (fMRI), transcranial magnetic stimulation (TMS) and electroencephalography (EEG).

Probing Compulsive and Impulsive Behaviors, from Animal Models to Endophenotypes: A Narrative Review

PubMed Central

Fineberg, Naomi A; Potenza, Marc N; Chamberlain, Samuel R; Berlin, Heather A; Menzies, Lara; Bechara, Antoine; Sahakian, Barbara J; Robbins, Trevor W; Bullmore, Edward T; Hollander, Eric

2010-01-01

Failures in cortical control of fronto-striatal neural circuits may underpin impulsive and compulsive acts. In this narrative review, we explore these behaviors from the perspective of neural processes and consider how these behaviors and neural processes contribute to mental disorders such as obsessive–compulsive disorder (OCD), obsessive–compulsive personality disorder, and impulse-control disorders such as trichotillomania and pathological gambling. We present findings from a broad range of data, comprising translational and human endophenotypes research and clinical treatment trials, focussing on the parallel, functionally segregated, cortico-striatal neural projections, from orbitofrontal cortex (OFC) to medial striatum (caudate nucleus), proposed to drive compulsive activity, and from the anterior cingulate/ventromedial prefrontal cortex to the ventral striatum (nucleus accumbens shell), proposed to drive impulsive activity, and the interaction between them. We suggest that impulsivity and compulsivity each seem to be multidimensional. Impulsive or compulsive behaviors are mediated by overlapping as well as distinct neural substrates. Trichotillomania may stand apart as a disorder of motor-impulse control, whereas pathological gambling involves abnormal ventral reward circuitry that identifies it more closely with substance addiction. OCD shows motor impulsivity and compulsivity, probably mediated through disruption of OFC-caudate circuitry, as well as other frontal, cingulate, and parietal connections. Serotonin and dopamine interact across these circuits to modulate aspects of both impulsive and compulsive responding and as yet unidentified brain-based systems may also have important functions. Targeted application of neurocognitive tasks, receptor-specific neurochemical probes, and brain systems neuroimaging techniques have potential for future research in this field. PMID:19940844

High order neural correlates of social behavior in the honeybee brain.

PubMed

Duer, Aron; Paffhausen, Benjamin H; Menzel, Randolf

2015-10-30

Honeybees are well established models of neural correlates of sensory function, learning and memory formation. Here we report a novel approach allowing to record high-order mushroom body-extrinsic interneurons in the brain of worker bees within a functional colony. New method The use of two 100 cm long twisted copper electrodes allowed recording of up to four units of mushroom body-extrinsic neurons simultaneously for up to 24h in animals moving freely between members of the colony. Every worker, including the recorded bee, hatched in the experimental environment. The group consisted of 200 animals in average. Animals explored different regions of the comb and interacted with other colony members. The activities of the units were not selective for locations on the comb, body directions with respect to gravity and olfactory signals on the comb, or different social interactions. However, combinations of these parameters defined neural activity in a unit-specific way. In addition, units recorded from the same animal co-varied according to unknown factors. Comparison with existing method(s): All electrophysiological studies with honey bees were performed so far on constrained animals outside their natural behavioral contexts. Yet no neuronal correlates were measured in a social context. Free mobility of recoded insects over a range of a quarter square meter allows addressing questions concerning neural correlates of social communication, planning of tasks within the colony and attention-like processes. The method makes it possible to study neural correlates of social behavior in a near-natural setting within the honeybee colony. Copyright © 2015 Elsevier B.V. All rights reserved.

Investigating the Neural Correlates of Emotion–Cognition Interaction Using an Affective Stroop Task

PubMed Central

Raschle, Nora M.; Fehlbaum, Lynn V.; Menks, Willeke M.; Euler, Felix; Sterzer, Philipp; Stadler, Christina

2017-01-01

The human brain has the capacity to integrate various sources of information and continuously adapts our behavior according to situational needs in order to allow a healthy functioning. Emotion–cognition interactions are a key example for such integrative processing. However, the neuronal correlates investigating the effects of emotion on cognition remain to be explored and replication studies are needed. Previous neuroimaging studies have indicated an involvement of emotion and cognition related brain structures including parietal and prefrontal cortices and limbic brain regions. Here, we employed whole brain event-related functional magnetic resonance imaging (fMRI) during an affective number Stroop task and aimed at replicating previous findings using an adaptation of an existing task design in 30 healthy young adults. The Stroop task is an indicator of cognitive control and enables the quantification of interference in relation to variations in cognitive load. By the use of emotional primes (negative/neutral) prior to Stroop task performance, an emotional variation is added as well. Behavioral in-scanner data showed that negative primes delayed and disrupted cognitive processing. Trials with high cognitive demand furthermore negatively influenced cognitive control mechanisms. Neuronally, the emotional primes consistently activated emotion-related brain regions (e.g., amygdala, insula, and prefrontal brain regions) while Stroop task performance lead to activations in cognition networks of the brain (prefrontal cortices, superior temporal lobe, and insula). When assessing the effect of emotion on cognition, increased cognitive demand led to decreases in neural activation in response to emotional stimuli (negative > neutral) within prefrontal cortex, amygdala, and insular cortex. Overall, these results suggest that emotional primes significantly impact cognitive performance and increasing cognitive demand leads to reduced neuronal activation in emotion related brain regions, and therefore support previous findings investigating emotion–cognition interaction in healthy adults. Moreover, emotion and cognition seem to be tightly related to each other, as indicated by shared neural networks involved in both of these processes. Emotion processing, cognitive control, and their interaction are crucial for healthy functioning and a lack thereof is related to psychiatric disorders such as, disruptive behavior disorders. Future studies may investigate the neural characteristics of children and adolescents with disruptive behavior disorders. PMID:28919871

The neural basis of the imitation drive

PubMed Central

Sugiura, Motoaki; Nozawa, Takayuki; Kotozaki, Yuka; Yomogida, Yukihito; Ihara, Mizuki; Akimoto, Yoritaka; Thyreau, Benjamin; Izumi, Shinichi; Kawashima, Ryuta

2016-01-01

Spontaneous imitation is assumed to underlie the acquisition of important skills by infants, including language and social interaction. In this study, functional magnetic resonance imaging (fMRI) was used to examine the neural basis of ‘spontaneously’ driven imitation, which has not yet been fully investigated. Healthy participants were presented with movie clips of meaningless bimanual actions and instructed to observe and imitate them during an fMRI scan. The participants were subsequently shown the movie clips again and asked to evaluate the strength of their ‘urge to imitate’ (Urge) for each action. We searched for cortical areas where the degree of activation positively correlated with Urge scores; significant positive correlations were observed in the right supplementary motor area (SMA) and bilateral midcingulate cortex (MCC) under the imitation condition. These areas were not explained by explicit reasons for imitation or the kinematic characteristics of the actions. Previous studies performed in monkeys and humans have implicated the SMA and MCC/caudal cingulate zone in voluntary actions. This study also confirmed the functional connectivity between Urge and imitation performance using a psychophysiological interaction analysis. Thus, our findings reveal the critical neural components that underlie spontaneous imitation and provide possible reasons why infants imitate spontaneously. PMID:26168793

A Generic Framework for Real-Time Multi-Channel Neuronal Signal Analysis, Telemetry Control, and Sub-Millisecond Latency Feedback Generation

PubMed Central

Zrenner, Christoph; Eytan, Danny; Wallach, Avner; Thier, Peter; Marom, Shimon

2010-01-01

Distinct modules of the neural circuitry interact with each other and (through the motor-sensory loop) with the environment, forming a complex dynamic system. Neuro-prosthetic devices seeking to modulate or restore CNS function need to interact with the information flow at the level of neural modules electrically, bi-directionally and in real-time. A set of freely available generic tools is presented that allow computationally demanding multi-channel short-latency bi-directional interactions to be realized in in vivo and in vitro preparations using standard PC data acquisition and processing hardware and software (Mathworks Matlab and Simulink). A commercially available 60-channel extracellular multi-electrode recording and stimulation set-up connected to an ex vivo developing cortical neuronal culture is used as a model system to validate the method. We demonstrate how complex high-bandwidth (>10 MBit/s) neural recording data can be analyzed in real-time while simultaneously generating specific complex electrical stimulation feedback with deterministically timed responses at sub-millisecond resolution. PMID:21060803

Information-theoretic decomposition of embodied and situated systems.

PubMed

Da Rold, Federico

2018-07-01

The embodied and situated view of cognition stresses the importance of real-time and nonlinear bodily interaction with the environment for developing concepts and structuring knowledge. In this article, populations of robots controlled by an artificial neural network learn a wall-following task through artificial evolution. At the end of the evolutionary process, time series are recorded from perceptual and motor neurons of selected robots. Information-theoretic measures are estimated on pairings of variables to unveil nonlinear interactions that structure the agent-environment system. Specifically, the mutual information is utilized to quantify the degree of dependence and the transfer entropy to detect the direction of the information flow. Furthermore, the system is analyzed with the local form of such measures, thus capturing the underlying dynamics of information. Results show that different measures are interdependent and complementary in uncovering aspects of the robots' interaction with the environment, as well as characteristics of the functional neural structure. Therefore, the set of information-theoretic measures provides a decomposition of the system, capturing the intricacy of nonlinear relationships that characterize robots' behavior and neural dynamics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sequence memory based on coherent spin-interaction neural networks.

PubMed

Xia, Min; Wong, W K; Wang, Zhijie

2014-12-01

Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

Neural signatures of cognitive and emotional biases in depression

PubMed Central

Fossati, Philippe

2008-01-01

Functional brain imaging studies suggest that depression is a system-level disorder affecting discrete but functionally linked cortical and limbic structures, with abnormalities in the anterior cingulate, lateral, ami medial prefrontal cortex, amygdala, ami hippocampus. Within this circuitry, abnormal corticolimbic interactions underlie cognitive deficits ami emotional impairment in depression. Depression involves biases toward processing negative emotional information and abnormal self-focus in response to emotional stimuli. These biases in depression could reflect excessive analytical self-focus in depression, as well as impaired cognitive control of emotional response to negative stimuli. By combining structural and functional investigations, brain imaging studies mav help to generate novel antidepressant treatments that regulate structural and factional plasticity within the neural network regulating mood and affective behavior.

Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations

PubMed Central

Holca-Lamarre, Raphaël; Lücke, Jörg; Obermayer, Klaus

2017-01-01

Biological and artificial neural networks (ANNs) represent input signals as patterns of neural activity. In biology, neuromodulators can trigger important reorganizations of these neural representations. For instance, pairing a stimulus with the release of either acetylcholine (ACh) or dopamine (DA) evokes long lasting increases in the responses of neurons to the paired stimulus. The functional roles of ACh and DA in rearranging representations remain largely unknown. Here, we address this question using a Hebbian-learning neural network model. Our aim is both to gain a functional understanding of ACh and DA transmission in shaping biological representations and to explore neuromodulator-inspired learning rules for ANNs. We model the effects of ACh and DA on synaptic plasticity and confirm that stimuli coinciding with greater neuromodulator activation are over represented in the network. We then simulate the physiological release schedules of ACh and DA. We measure the impact of neuromodulator release on the network's representation and on its performance on a classification task. We find that ACh and DA trigger distinct changes in neural representations that both improve performance. The putative ACh signal redistributes neural preferences so that more neurons encode stimulus classes that are challenging for the network. The putative DA signal adapts synaptic weights so that they better match the classes of the task at hand. Our model thus offers a functional explanation for the effects of ACh and DA on cortical representations. Additionally, our learning algorithm yields performances comparable to those of state-of-the-art optimisation methods in multi-layer perceptrons while requiring weaker supervision signals and interacting with synaptically-local weight updates. PMID:28690509

Functional changes of the reward system underlie blunted response to social gaze in cocaine users

PubMed Central

Preller, Katrin H.; Herdener, Marcus; Schilbach, Leonhard; Stämpfli, Philipp; Hulka, Lea M.; Vonmoos, Matthias; Ingold, Nina; Vogeley, Kai; Tobler, Philippe N.; Seifritz, Erich; Quednow, Boris B.

2014-01-01

Social interaction deficits in drug users likely impede treatment, increase the burden of the affected families, and consequently contribute to the high costs for society associated with addiction. Despite its significance, the neural basis of altered social interaction in drug users is currently unknown. Therefore, we investigated basal social gaze behavior in cocaine users by applying behavioral, psychophysiological, and functional brain-imaging methods. In study I, 80 regular cocaine users and 63 healthy controls completed an interactive paradigm in which the participants’ gaze was recorded by an eye-tracking device that controlled the gaze of an anthropomorphic virtual character. Valence ratings of different eye-contact conditions revealed that cocaine users show diminished emotional engagement in social interaction, which was also supported by reduced pupil responses. Study II investigated the neural underpinnings of changes in social reward processing observed in study I. Sixteen cocaine users and 16 controls completed a similar interaction paradigm as used in study I while undergoing functional magnetic resonance imaging. In response to social interaction, cocaine users displayed decreased activation of the medial orbitofrontal cortex, a key region of reward processing. Moreover, blunted activation of the medial orbitofrontal cortex was significantly correlated with a decreased social network size, reflecting problems in real-life social behavior because of reduced social reward. In conclusion, basic social interaction deficits in cocaine users as observed here may arise from altered social reward processing. Consequently, these results point to the importance of reinstatement of social reward in the treatment of stimulant addiction. PMID:24449854

Serotonin mediated immunoregulation and neural functions: Complicity in the aetiology of autism spectrum disorders.

PubMed

Jaiswal, Preeti; Mohanakumar, Kochupurackal P; Rajamma, Usha

2015-08-01

Serotonergic system has long been implicated in the aetiology of autism spectrum disorders (ASD), since platelet hyperserotonemia is consistently observed in a subset of autistic patients, who respond well to selective serotonin reuptake inhibitors. Apart from being a neurotransmitter, serotonin functions as a neurotrophic factor directing brain development and as an immunoregulator modulating immune responses. Serotonin transporter (SERT) regulates serotonin level in lymphoid tissues to ensure its proper functioning in innate and adaptive responses. Immunological molecules such as cytokines in turn regulate the transcription and activity of SERT. Dysregulation of serotonergic system could trigger signalling cascades that affect normal neural-immune interactions culminating in neurodevelopmental and neural connectivity defects precipitating behavioural abnormalities, or the disease phenotypes. Therefore, we suggest that a better understanding of the cross talk between serotonergic genes, immune systems and serotonergic neurotransmission will open wider avenues to develop pharmacological leads for addressing the core ASD behavioural deficits. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural pathway in the right hemisphere underlies verbal insight problem solving.

PubMed

Zhao, Q; Zhou, Z; Xu, H; Fan, W; Han, L

2014-01-03

Verbal insight problem solving means to break mental sets, to select the novel semantic information and to form novel, task-related associations. Although previous studies have identified the brain regions associated with these key processes, the interaction among these regions during insight is still unclear. In the present study, we explored the functional connectivity between the key regions during solving Chinese 'chengyu' riddles by using event-related functional magnetic resonance imaging. Results showed that both insight and noninsight solutions activated the bilateral inferior frontal gyri, middle temporal gyri and hippocampi, and these regions constituted a frontal to temporal to hippocampal neural pathway. Compared with noninsight solution, insight solution had a stronger functional connectivity between the inferior frontal gyrus and middle temporal gyrus in the right hemisphere. Our study reveals the neural pathway of information processing during verbal insight problem solving, and supports the right-hemisphere advantage theory of insight. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Alterations in Brain Activation During Cognitive Empathy Are Related to Social Functioning in Schizophrenia

PubMed Central

Smith, Matthew J.; Schroeder, Matthew P.; Abram, Samantha V.; Goldman, Morris B.; Parrish, Todd B.; Wang, Xue; Derntl, Birgit; Habel, Ute; Decety, Jean; Reilly, James L.; Csernansky, John G.; Breiter, Hans C.

2015-01-01

Impaired cognitive empathy (ie, understanding the emotional experiences of others) is associated with poor social functioning in schizophrenia. However, it is unclear whether the neural activity underlying cognitive empathy relates to social functioning. This study examined the neural activation supporting cognitive empathy performance and whether empathy-related activation during correctly performed trials was associated with self-reported cognitive empathy and measures of social functioning. Thirty schizophrenia outpatients and 24 controls completed a cognitive empathy paradigm during functional magnetic resonance imaging. Neural activity corresponding to correct judgments about the expected emotional expression in a social interaction was compared in schizophrenia subjects relative to control subjects. Participants also completed a self-report measure of empathy and 2 social functioning measures (social competence and social attainment). Schizophrenia subjects demonstrated significantly lower accuracy in task performance and were characterized by hypoactivation in empathy-related frontal, temporal, and parietal regions as well as hyperactivation in occipital regions compared with control subjects during accurate cognitive empathy trials. A cluster with peak activation in the supplementary motor area (SMA) extending to the anterior midcingulate cortex (aMCC) correlated with social competence and social attainment in schizophrenia subjects but not controls. These results suggest that neural correlates of cognitive empathy may be promising targets for interventions aiming to improve social functioning and that brain activation in the SMA/aMCC region could be used as a biomarker for monitoring treatment response. PMID:24583906

Glial-Specific Functions of Microcephaly Protein WDR62 and Interaction with the Mitotic Kinase AURKA Are Essential for Drosophila Brain Growth.

PubMed

Lim, Nicholas R; Shohayeb, Belal; Zaytseva, Olga; Mitchell, Naomi; Millard, S Sean; Ng, Dominic C H; Quinn, Leonie M

2017-07-11

The second most commonly mutated gene in primary microcephaly (MCPH) patients is wd40-repeat protein 62 (wdr62), but the relative contribution of WDR62 function to the growth of major brain lineages is unknown. Here, we use Drosophila models to dissect lineage-specific WDR62 function(s). Interestingly, although neural stem cell (neuroblast)-specific depletion of WDR62 significantly decreased neuroblast number, brain size was unchanged. In contrast, glial lineage-specific WDR62 depletion significantly decreased brain volume. Moreover, loss of function in glia not only decreased the glial population but also non-autonomously caused neuroblast loss. We further demonstrated that WDR62 controls brain growth through lineage-specific interactions with master mitotic signaling kinase, AURKA. Depletion of AURKA in neuroblasts drives brain overgrowth, which was suppressed by WDR62 co-depletion. In contrast, glial-specific depletion of AURKA significantly decreased brain volume, which was further decreased by WDR62 co-depletion. Thus, dissecting relative contributions of MCPH factors to individual neural lineages will be critical for understanding complex diseases such as microcephaly. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Optimal Design for Hetero-Associative Memory: Hippocampal CA1 Phase Response Curve and Spike-Timing-Dependent Plasticity

PubMed Central

Miyata, Ryota; Ota, Keisuke; Aonishi, Toru

2013-01-01

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-associative memory recalling such reversed and spread-out spike patterns. In line with Lengyel’s speculation (Lengyel et al., 2005), we firstly derive optimally designed spike-timing-dependent plasticity (STDP) rules that are matched to neural interactions formalized in terms of phase response curves (PRCs) for performing the hetero-associative memory function. By maximizing object functions formulated in terms of mutual information for evaluating memory retrieval performance, we search for STDP window functions that are optimal for retrieval of normal and doubly spread-out patterns under the constraint that the PRCs are those of CA1 pyramidal neurons. The system, which can retrieve normal and doubly spread-out patterns, can also retrieve reversed patterns with the same quality. Finally, we demonstrate that purposely designed STDP window functions qualitatively conform to typical ones found in CA1 pyramidal neurons. PMID:24204822

Exploring the Nature of Cortical Recurrent Interactions

NASA Astrophysics Data System (ADS)

Morita, Kenji; Kalra, Rita; Aihara, Kazuyuki; Robinson, Hugh P. C.

2011-09-01

Fast rhythmic activity of neural population has been frequently observed in cortical circuits, and suggested to be associated with various cognitive functions including working memory and selective attention. However, precisely how recurrent synaptic interactions, that are prominent in these circuits, shape and/or modulate such population rhythm has not been fully elucidated. We have addressed this issue by combining electrophysiological and computational approaches.

Dynamic interactions in neural networks

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

Arbib, M.A.; Amari, S.

The study of neural networks is enjoying a great renaissance, both in computational neuroscience, the development of information processing models of living brains, and in neural computing, the use of neurally inspired concepts in the construction of intelligent machines. This volume presents models and data on the dynamic interactions occurring in the brain, and exhibits the dynamic interactions between research in computational neuroscience and in neural computing. The authors present current research, future trends and open problems.

The influence of combined cognitive plus social-cognitive training on amygdala response during face emotion recognition in schizophrenia.

PubMed

Hooker, Christine I; Bruce, Lori; Fisher, Melissa; Verosky, Sara C; Miyakawa, Asako; D'Esposito, Mark; Vinogradov, Sophia

2013-08-30

Both cognitive and social-cognitive deficits impact functional outcome in schizophrenia. Cognitive remediation studies indicate that targeted cognitive and/or social-cognitive training improves behavioral performance on trained skills. However, the neural effects of training in schizophrenia and their relation to behavioral gains are largely unknown. This study tested whether a 50-h intervention which included both cognitive and social-cognitive training would influence neural mechanisms that support social ccognition. Schizophrenia participants completed a computer-based intervention of either auditory-based cognitive training (AT) plus social-cognition training (SCT) (N=11) or non-specific computer games (CG) (N=11). Assessments included a functional magnetic resonance imaging (fMRI) task of facial emotion recognition, and behavioral measures of cognition, social cognition, and functional outcome. The fMRI results showed the predicted group-by-time interaction. Results were strongest for emotion recognition of happy, surprise and fear: relative to CG participants, AT+SCT participants showed a neural activity increase in bilateral amygdala, right putamen and right medial prefrontal cortex. Across all participants, pre-to-post intervention neural activity increase in these regions predicted behavioral improvement on an independent emotion perception measure (MSCEIT: Perceiving Emotions). Among AT+SCT participants alone, neural activity increase in right amygdala predicted behavioral improvement in emotion perception. The findings indicate that combined cognition and social-cognition training improves neural systems that support social-cognition skills. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Orphan nuclear receptor TLX recruits histone deacetylases to repress transcription and regulate neural stem cell proliferation.

PubMed

Sun, Guoqiang; Yu, Ruth T; Evans, Ronald M; Shi, Yanhong

2007-09-25

TLX is a transcription factor that is essential for neural stem cell proliferation and self-renewal. However, the molecular mechanism of TLX-mediated neural stem cell proliferation and self-renewal is largely unknown. We show here that TLX recruits histone deacetylases (HDACs) to its downstream target genes to repress their transcription, which in turn regulates neural stem cell proliferation. TLX interacts with HDAC3 and HDAC5 in neural stem cells. The HDAC5-interaction domain was mapped to TLX residues 359-385, which contains a conserved nuclear receptor-coregulator interaction motif IXXLL. Both HDAC3 and HDAC5 have been shown to be recruited to the promoters of TLX target genes along with TLX in neural stem cells. Recruitment of HDACs led to transcriptional repression of TLX target genes, the cyclin-dependent kinase inhibitor, p21(CIP1/WAF1)(p21), and the tumor suppressor gene, pten. Either inhibition of HDAC activity or knockdown of HDAC expression led to marked induction of p21 and pten gene expression and dramatically reduced neural stem cell proliferation, suggesting that the TLX-interacting HDACs play an important role in neural stem cell proliferation. Moreover, expression of a TLX peptide containing the minimal HDAC5 interaction domain disrupted the TLX-HDAC5 interaction. Disruption of this interaction led to significant induction of p21 and pten gene expression and to dramatic inhibition of neural stem cell proliferation. Taken together, these findings demonstrate a mechanism for neural stem cell proliferation through transcriptional repression of p21 and pten gene expression by TLX-HDAC interactions.

Transdiagnostic dimensions of anxiety: Neural mechanisms, executive functions, and new directions.

PubMed

Sharp, Paul B; Miller, Gregory A; Heller, Wendy

2015-11-01

Converging neuroscientific and psychological evidence points to several transdiagnostic factors that cut across DSM-defined disorders, which both affect and are affected by executive dysfunction. Two of these factors, anxious apprehension and anxious arousal, have helped bridge the gap between psychological and neurobiological models of anxiety. The present integration of diverse findings advances an understanding of the relationships between these transdiagnostic anxiety dimensions, their interactions with each other and executive function, and their neural mechanisms. Additionally, a discussion is provided concerning how these constructs fit within the Research Domain Criteria (RDoC) matrix developed by the National Institutes of Mental Health and how they relate to other anxiety constructs studied with different methods and at other units of analysis. Suggestions for future research are offered, including how to (1) improve measurement and delineation of these constructs, (2) use new neuroimaging methods and theoretical approaches of how the brain functions to build neural mechanistic models of these constructs, and (3) advance understanding of the relationships of these constructs to diverse emotional phenomena and executive functions. Copyright © 2015 Elsevier B.V. All rights reserved.

Dynamic Neural Networks Supporting Memory Retrieval

PubMed Central

St. Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

2011-01-01

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) Medial Prefrontal Cortex (PFC) Network, associated with self-referential processes, 2) Medial Temporal Lobe (MTL) Network, associated with memory, 3) Frontoparietal Network, associated with strategic search, and 4) Cingulooperculum Network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior. PMID:21550407

Developmental Meta-Analysis of the Functional Neural Correlates of Autism Spectrum Disorders

ERIC Educational Resources Information Center

Dickstein, Daniel P.; Pescosolido, Matthew F.; Reidy, Brooke L.; Galvan, Thania; Kim, Kerri L.; Seymour, Karen E.; Laird, Angela R.; Di Martino, Adriana; Barrett, Rowland P.

2013-01-01

Objective: There is a pressing need to elucidate the brain-behavior interactions underlying autism spectrum disorders (ASD) given the marked rise in ASD diagnosis over the past decade. Functional magnetic resonance imaging (fMRI) has begun to address this need, but few fMRI studies have evaluated age-related changes in ASD. Therefore, we conducted…

Neural Pathways of Embarrassment and their Modulation by Social Anxiety

PubMed Central

Müller-Pinzler, L; Gazzola, V; Keysers, C; Sommer, J; Jansen, A; Frässle, S; Einhäuser, W

2016-01-01

While being in the center of attention and exposed to other’s evaluations humans are prone to experience embarrassment. To characterize the neural underpinnings of such aversive moments, we induced genuine experiences of embarrassment during person-group interactions in a functional neuroimaging study. Using a mock-up scenario with three confederates, we examined how the presence of an audience affected physiological and neural responses and the reported emotional experiences of failures and achievements. The results indicated that publicity induced activations in mentalizing areas and failures led to activations in arousal processing systems. Mentalizing activity as well as attention towards the audience were increased in socially anxious participants. The converging integration of information from mentalizing areas and arousal processing systems within the ventral anterior insula and amygdala form the neural pathways of embarrassment. Targeting these neural markers of embarrassment in the (para-)limbic system provides new perspectives for developing treatment strategies for social anxiety disorders. PMID:26093329

Neural correlates of genetically abnormal social cognition in Williams syndrome.

PubMed

Meyer-Lindenberg, Andreas; Hariri, Ahmad R; Munoz, Karen E; Mervis, Carolyn B; Mattay, Venkata S; Morris, Colleen A; Berman, Karen Faith

2005-08-01

Williams-Beuren syndrome (WBS), caused by a microdeletion of approximately 21 genes on chromosome 7q11.23, is characterized by unique hypersociability combined with increased non-social anxiety. Using functional neuroimaging, we found reduced amygdala activation in individuals with WBS for threatening faces but increased activation for threatening scenes, relative to matched normal controls. Activation and interactions of prefrontal regions linked to amygdala, especially orbitofrontal cortex, were abnormal, suggesting a genetically controlled neural circuitry for regulating human social behavior.

Applications of self-organizing neural networks in virtual screening and diversity selection.

PubMed

Selzer, Paul; Ertl, Peter

2006-01-01

Artificial neural networks provide a powerful technique for the analysis and modeling of nonlinear relationships between molecular structures and pharmacological activity. Many network types, including Kohonen and counterpropagation, also provide an intuitive method for the visual assessment of correspondence between the input and output data. This work shows how a combination of neural networks and radial distribution function molecular descriptors can be applied in various areas of industrial pharmaceutical research. These applications include the prediction of biological activity, the selection of screening candidates (cherry picking), and the extraction of representative subsets from large compound collections such as combinatorial libraries. The methods described have also been implemented as an easy-to-use Web tool, allowing chemists to perform interactive neural network experiments on the Novartis intranet.

Neural Darwinism and consciousness.

PubMed

Seth, Anil K; Baars, Bernard J

2005-03-01

Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

Molecular Parallels between Neural and Vascular Development

PubMed Central

Eichmann, Anne; Thomas, Jean-Léon

2013-01-01

The human central nervous system (CNS) features a network of ∼400 miles of blood vessels that receives >20% of the body’s cardiac output and uses most of its blood glucose. Many human diseases, including stroke, retinopathy, and cancer, are associated with the biology of CNS blood vessels. These vessels originate from extrinsic cell populations, including endothelial cells and pericytes that colonize the CNS and interact with glia and neurons to establish the blood–brain barrier and control cerebrovascular exchanges. Neurovascular interactions also play important roles in adult neurogenic niches, which harbor a unique population of neural stem cells that are intimately associated with blood vessels. We here review the cellular and molecular mechanisms required to establish the CNS vascular network, with a special focus on neurovascular interactions and the functions of vascular endothelial growth factors. PMID:23024177

Stochastic nanoroughness modulates neuron-astrocyte interactions and function via mechanosensing cation channels.

PubMed

Blumenthal, Nils R; Hermanson, Ola; Heimrich, Bernd; Shastri, V Prasad

2014-11-11

Extracellular soluble signals are known to play a critical role in maintaining neuronal function and homeostasis in the CNS. However, the CNS is also composed of extracellular matrix macromolecules and glia support cells, and the contribution of the physical attributes of these components in maintenance and regulation of neuronal function is not well understood. Because these components possess well-defined topography, we theorize a role for topography in neuronal development and we demonstrate that survival and function of hippocampal neurons and differentiation of telencephalic neural stem cells is modulated by nanoroughness. At roughnesses corresponding to that of healthy astrocytes, hippocampal neurons dissociated and survived independent from astrocytes and showed superior functional traits (increased polarity and calcium flux). Furthermore, telencephalic neural stem cells differentiated into neurons even under exogenous signals that favor astrocytic differentiation. The decoupling of neurons from astrocytes seemed to be triggered by changes to astrocyte apical-surface topography in response to nanoroughness. Blocking signaling through mechanosensing cation channels using GsMTx4 negated the ability of neurons to sense the nanoroughness and promoted decoupling of neurons from astrocytes, thus providing direct evidence for the role of nanotopography in neuron-astrocyte interactions. We extrapolate the role of topography to neurodegenerative conditions and show that regions of amyloid plaque buildup in brain tissue of Alzheimer's patients are accompanied by detrimental changes in tissue roughness. These findings suggest a role for astrocyte and ECM-induced topographical changes in neuronal pathologies and provide new insights for developing therapeutic targets and engineering of neural biomaterials.

Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions

PubMed Central

Testolin, Alberto; Zorzi, Marco

2016-01-01

Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage. PMID:27468262

Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

PubMed

Testolin, Alberto; Zorzi, Marco

2016-01-01

Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

Serotonin, neural markers, and memory

PubMed Central

Meneses, Alfredo

2015-01-01

Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals' species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6, and 5-HT7 receptors as well as SERT (serotonin transporter) seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence. PMID:26257650

State-Dependent Cross-Brain Information Flow in Borderline Personality Disorder.

PubMed

Bilek, Edda; Stößel, Gabriela; Schäfer, Axel; Clement, Laura; Ruf, Matthias; Robnik, Lydia; Neukel, Corinne; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2017-09-01

Although borderline personality disorder (BPD)-one of the most common, burdensome, and costly psychiatric conditions-is characterized by repeated interpersonal conflict and instable relationships, the neurobiological mechanism of social interactive deficits remains poorly understood. To apply recent advancements in the investigation of 2-person human social interaction to investigate interaction difficulties among people with BPD. Cross-brain information flow in BPD was examined from May 25, 2012, to December 4, 2015, in pairs of participants studied in 2 linked functional magnetic resonance imaging scanners in a university setting. Participants performed a joint attention task. Each pair included a healthy control individual (HC) and either a patient currently fulfilling DSM-IV criteria for BPD (cBPD) (n = 23), a patient in remission for 2 years or more (rBPD) (n = 17), or a second HC (n = 20). Groups were matched for age and educational level. A measure of cross-brain neural coupling was computed following previously published work to indicate synchronized flow between right temporoparietal junction networks (previously shown to host neural coupling abilities in health). This measure is derived from an independent component analysis contrasting the time courses of components between pairs of truly interacting participants compared with bootstrapped control pairs. In the sample including 23 women with cBPD (mean [SD] age, 26.8 [5.7] years), 17 women with rBPD (mean [SD] age, 28.5 [4.3] years), and 80 HCs (mean [SD] age, 24.0 [3.4] years]) investigated as dyads, neural coupling was found to be associated with disorder state (η2 = 0.17; P = .007): while HC-HC pairs showed synchronized neural responses, cBPD-HC pairs exhibited significantly lower neural coupling just above permutation-based data levels (η2 = 0.16; P = .009). No difference was found between neural coupling in rBPD-HC and HC-HC pairs. The neural coupling in patients was significantly associated with childhood adversity (T = 2.3; P = .03). This study provides a neural correlate for a core diagnostic and clinical feature of BPD. Results indicate that hyperscanning may deliver state-associated biomarkers for clinical social neuroscience. In addition, at least some neural deficits of BPD may be more reversible than is currently assumed for personality disorders.

Comprehensive interactome of Otx2 in the adult mouse neural retina.

PubMed

Fant, Bruno; Samuel, Alexander; Audebert, Stéphane; Couzon, Agnès; El Nagar, Salsabiel; Billon, Nathalie; Lamonerie, Thomas

2015-11-01

The Otx2 homeodomain transcription factor exerts multiple functions in specific developmental contexts, probably through the regulation of different sets of genes. Protein partners of Otx2 have been shown to modulate its activity. Therefore, the Otx2 interactome may play a key role in selecting a precise target-gene repertoire, hence determining its function in a specific tissue. To address the nature of Otx2 interactome, we generated a new recombinant Otx2(CTAP-tag) mouse line, designed for protein complexes purification. We validated this mouse line by establishing the Otx2 interactome in the adult neural retina. In this tissue, Otx2 is thought to have overlapping function with its paralog Crx. Our analysis revealed that, in contrary to Crx, Otx2 did not develop interactions with proteins that are known to regulate phototransduction genes but showed specific partnership with factors associated with retinal development. The relationship between Otx2 and Crx in the neural retina should therefore be considered as complementarity rather than redundancy. Furthermore, study of the Otx2 interactome revealed strong associations with RNA processing and translation machineries, suggesting unexpected roles for Otx2 in the regulation of selected target genes all along the transcription/translation pathway. The Otx2(CTAP-tag) line, therefore, appears suitable for a systematic approach to Otx2 protein-protein interactions. genesis 53:685-694, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Neural networks within multi-core optic fibers

PubMed Central

Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

2016-01-01

Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks. PMID:27383911

Neural networks within multi-core optic fibers.

PubMed

Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

2016-07-07

Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

Cortical activity and functional hyperconnectivity by simultaneous EEG recordings from interacting couples of professional pilots.

PubMed

Astolfi, L; Toppi, J; Borghini, G; Vecchiato, G; He, E J; Roy, A; Cincotti, F; Salinari, S; Mattia, D; He, B; Babiloni, F

2012-01-01

Controlling an aircraft during a flight is a compelling condition, which requires a strict and well coded interaction between the crew. The interaction level between the Captain and the First Officer changes during the flight, ranging from a maximum (during takeoff and landing, as well as in case of a failure of the instrumentation or other emergency situations) to a minimum during quiet mid-flight. In this study, our aim is to investigate the neural correlates of different kinds and levels of interaction between couples of professional crew members by means of the innovative technique called brain hyperscanning, i.e. the simultaneous recording of the hemodynamic or neuroelectrical activity of different human subjects involved in interaction tasks. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects, and, even more interestingly, of the functional links existing between the brain activities of the subjects interacting together. In this EEG hyperscanning study, different phases of a flight were reproduced in a professional flight simulator, which allowed, on one side, to reproduce the ecological setting of a real flight, and, on the other, to keep under control the different levels of interaction induced in the crew by means of systematic and simulated failures of the aircraft instrumentation. Results of the procedure of linear inverse estimation, together with functional hyperconnectivity estimated by means of Partial Directed Coherence, showed a dense network of connections between the activity in the two brains in the takeoff and landing phases, when the cooperation between the crew is maximal, while conversely no significant links were shown during the phases in which the activity of the two pilots was independent.

Context and hand posture modulate the neural dynamics of tool-object perception.

PubMed

Natraj, Nikhilesh; Poole, Victoria; Mizelle, J C; Flumini, Andrea; Borghi, Anna M; Wheaton, Lewis A

2013-02-01

Prior research has linked visual perception of tools with plausible motor strategies. Thus, observing a tool activates the putative action-stream, including the left posterior parietal cortex. Observing a hand functionally grasping a tool involves the inferior frontal cortex. However, tool-use movements are performed in a contextual and grasp specific manner, rather than relative isolation. Our prior behavioral data has demonstrated that the context of tool-use (by pairing the tool with different objects) and varying hand grasp postures of the tool can interact to modulate subjects' reaction times while evaluating tool-object content. Specifically, perceptual judgment was delayed in the evaluation of functional tool-object pairings (Correct context) when the tool was non-functionally (Manipulative) grasped. Here, we hypothesized that this behavioral interference seen with the Manipulative posture would be due to increased and extended left parietofrontal activity possibly underlying motor simulations when resolving action conflict due to this particular grasp at time scales relevant to the behavioral data. Further, we hypothesized that this neural effect will be restricted to the Correct tool-object context wherein action affordances are at a maximum. 64-channel electroencephalography (EEG) was recorded from 16 right-handed subjects while viewing images depicting three classes of tool-object contexts: functionally Correct (e.g. coffee pot-coffee mug), functionally Incorrect (e.g. coffee pot-marker) and Spatial (coffee pot-milk). The Spatial context pairs a tool and object that would not functionally match, but may commonly appear in the same scene. These three contexts were modified by hand interaction: No Hand, Static Hand near the tool, Functional Hand posture and Manipulative Hand posture. The Manipulative posture is convenient for relocating a tool but does not afford a functional engagement of the tool on the target object. Subjects were instructed to visually assess whether the pictures displayed correct tool-object associations. EEG data was analyzed in time-voltage and time-frequency domains. Overall, Static Hand, Functional and Manipulative postures cause early activation (100-400ms post image onset) of parietofrontal areas, to varying intensity in each context, when compared to the No Hand control condition. However, when context is Correct, only the Manipulative Posture significantly induces extended neural responses, predominantly over right parietal and right frontal areas [400-600ms post image onset]. Significant power increase was observed in the theta band [4-8Hz] over the right frontal area, [0-500ms]. In addition, when context is Spatial, Manipulative posture alone significantly induces extended neural responses, over bilateral parietofrontal and left motor areas [400-600ms]. Significant power decrease occurred primarily in beta bands [12-16, 20-25Hz] over the aforementioned brain areas [400-600ms]. Here, we demonstrate that the neural processing of tool-object perception is sensitive to several factors. While both Functional and Manipulative postures in Correct context engage predominantly an early left parietofrontal circuit, the Manipulative posture alone extends the neural response and transitions to a late right parietofrontal network. This suggests engagement of a right neural system to evaluate action affordances when hand posture does not support action (Manipulative). Additionally, when tool-use context is ambiguous (Spatial context), there is increased bilateral parietofrontal activation and, extended neural response for the Manipulative posture. These results point to the existence of other networks evaluating tool-object associations when motoric affordances are not readily apparent and underlie corresponding delayed perceptual judgment in our prior behavioral data wherein Manipulative postures had exclusively interfered in judging tool-object content. Copyright © 2012 Elsevier Ltd. All rights reserved.

The neural subjective frame: from bodily signals to perceptual consciousness

PubMed Central

Park, Hyeong-Dong; Tallon-Baudry, Catherine

2014-01-01

The report ‘I saw the stimulus’ operationally defines visual consciousness, but where does the ‘I’ come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness. PMID:24639580

The neural subjective frame: from bodily signals to perceptual consciousness.

PubMed

Park, Hyeong-Dong; Tallon-Baudry, Catherine

2014-05-05

The report 'I saw the stimulus' operationally defines visual consciousness, but where does the 'I' come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness.

Social Interaction Affects Neural Outcomes of Sign Language Learning As a Foreign Language in Adults.

PubMed

Yusa, Noriaki; Kim, Jungho; Koizumi, Masatoshi; Sugiura, Motoaki; Kawashima, Ryuta

2017-01-01

Children naturally acquire a language in social contexts where they interact with their caregivers. Indeed, research shows that social interaction facilitates lexical and phonological development at the early stages of child language acquisition. It is not clear, however, whether the relationship between social interaction and learning applies to adult second language acquisition of syntactic rules. Does learning second language syntactic rules through social interactions with a native speaker or without such interactions impact behavior and the brain? The current study aims to answer this question. Adult Japanese participants learned a new foreign language, Japanese sign language (JSL), either through a native deaf signer or via DVDs. Neural correlates of acquiring new linguistic knowledge were investigated using functional magnetic resonance imaging (fMRI). The participants in each group were indistinguishable in terms of their behavioral data after the instruction. The fMRI data, however, revealed significant differences in the neural activities between two groups. Significant activations in the left inferior frontal gyrus (IFG) were found for the participants who learned JSL through interactions with the native signer. In contrast, no cortical activation change in the left IFG was found for the group who experienced the same visual input for the same duration via the DVD presentation. Given that the left IFG is involved in the syntactic processing of language, spoken or signed, learning through social interactions resulted in an fMRI signature typical of native speakers: activation of the left IFG. Thus, broadly speaking, availability of communicative interaction is necessary for second language acquisition and this results in observed changes in the brain.

Orphan nuclear receptor TLX recruits histone deacetylases to repress transcription and regulate neural stem cell proliferation

PubMed Central

Sun, GuoQiang; Yu, Ruth T.; Evans, Ronald M.; Shi, Yanhong

2007-01-01

TLX is a transcription factor that is essential for neural stem cell proliferation and self-renewal. However, the molecular mechanism of TLX-mediated neural stem cell proliferation and self-renewal is largely unknown. We show here that TLX recruits histone deacetylases (HDACs) to its downstream target genes to repress their transcription, which in turn regulates neural stem cell proliferation. TLX interacts with HDAC3 and HDAC5 in neural stem cells. The HDAC5-interaction domain was mapped to TLX residues 359–385, which contains a conserved nuclear receptor–coregulator interaction motif IXXLL. Both HDAC3 and HDAC5 have been shown to be recruited to the promoters of TLX target genes along with TLX in neural stem cells. Recruitment of HDACs led to transcriptional repression of TLX target genes, the cyclin-dependent kinase inhibitor, p21CIP1/WAF1(p21), and the tumor suppressor gene, pten. Either inhibition of HDAC activity or knockdown of HDAC expression led to marked induction of p21 and pten gene expression and dramatically reduced neural stem cell proliferation, suggesting that the TLX-interacting HDACs play an important role in neural stem cell proliferation. Moreover, expression of a TLX peptide containing the minimal HDAC5 interaction domain disrupted the TLX–HDAC5 interaction. Disruption of this interaction led to significant induction of p21 and pten gene expression and to dramatic inhibition of neural stem cell proliferation. Taken together, these findings demonstrate a mechanism for neural stem cell proliferation through transcriptional repression of p21 and pten gene expression by TLX–HDAC interactions. PMID:17873065

Biophotons as neural communication signals demonstrated by in situ biophoton autography.

PubMed

Sun, Yan; Wang, Chao; Dai, Jiapei

2010-03-01

Cell to cell communication by biophotons has been demonstrated in plants, bacteria, animal neutrophil granulocytes and kidney cells. Whether such signal communication exists in neural cells is unclear. By developing a new biophoton detection method, called in situ biophoton autography (IBA), we have investigated biophotonic activities in rat spinal nerve roots in vitro. We found that different spectral light stimulation (infrared, red, yellow, blue, green and white) at one end of the spinal sensory or motor nerve roots resulted in a significant increase in the biophotonic activity at the other end. Such effects could be significantly inhibited by procaine (a regional anaesthetic for neural conduction block) or classic metabolic inhibitors, suggesting that light stimulation can generate biophotons that conduct along the neural fibers, probably as neural communication signals. The mechanism of biophotonic conduction along neural fibers may be mediated by protein-protein biophotonic interactions. This study may provide a better understanding of the fundamental mechanisms of neural communication, the functions of the nervous system, such as vision, learning and memory, as well as the mechanisms of human neurological diseases.

Mood disorders: neurocognitive models.

PubMed

Malhi, Gin S; Byrow, Yulisha; Fritz, Kristina; Das, Pritha; Baune, Bernhard T; Porter, Richard J; Outhred, Tim

2015-12-01

In recent years, a number of neurocognitive models stemming from psychiatry and psychology schools of thought have conceptualized the pathophysiology of mood disorders in terms of dysfunctional neural mechanisms that underpin and drive neurocognitive processes. Though these models have been useful for advancing our theoretical understanding and facilitating important lines of research, translation of these models and their application within the clinical arena have been limited-partly because of lack of integration and synthesis. Cognitive neuroscience provides a novel perspective for understanding and modeling mood disorders. This selective review of influential neurocognitive models develops an integrative approach that can serve as a template for future research and the development of a clinically meaningful framework for investigating, diagnosing, and treating mood disorders. A selective literature search was conducted using PubMed and PsychINFO to identify prominent neurobiological and neurocognitive models of mood disorders. Most models identify similar neural networks and brain regions and neuropsychological processes in the neurocognition of mood, however, they differ in terms of specific functions attached to neural processes and how these interact. Furthermore, cognitive biases, reward processing and motivation, rumination, and mood stability, which play significant roles in the manner in which attention, appraisal, and response processes are deployed in mood disorders, are not sufficiently integrated. The inclusion of interactions between these additional components enhances our understanding of the etiology and pathophysiology of mood disorders. Through integration of key cognitive functions and understanding of how these interface with neural functioning within neurocognitive models of mood disorders, a framework for research can be created for translation to diagnosis and treatment of mood disorders. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Language, Tone and Prosody of Emotions: Neural Substrates and Dynamics of Spoken-Word Emotion Perception

PubMed Central

Liebenthal, Einat; Silbersweig, David A.; Stern, Emily

2016-01-01

Rapid assessment of emotions is important for detecting and prioritizing salient input. Emotions are conveyed in spoken words via verbal and non-verbal channels that are mutually informative and unveil in parallel over time, but the neural dynamics and interactions of these processes are not well understood. In this paper, we review the literature on emotion perception in faces, written words, and voices, as a basis for understanding the functional organization of emotion perception in spoken words. The characteristics of visual and auditory routes to the amygdala—a subcortical center for emotion perception—are compared across these stimulus classes in terms of neural dynamics, hemispheric lateralization, and functionality. Converging results from neuroimaging, electrophysiological, and lesion studies suggest the existence of an afferent route to the amygdala and primary visual cortex for fast and subliminal processing of coarse emotional face cues. We suggest that a fast route to the amygdala may also function for brief non-verbal vocalizations (e.g., laugh, cry), in which emotional category is conveyed effectively by voice tone and intensity. However, emotional prosody which evolves on longer time scales and is conveyed by fine-grained spectral cues appears to be processed via a slower, indirect cortical route. For verbal emotional content, the bulk of current evidence, indicating predominant left lateralization of the amygdala response and timing of emotional effects attributable to speeded lexical access, is more consistent with an indirect cortical route to the amygdala. Top-down linguistic modulation may play an important role for prioritized perception of emotions in words. Understanding the neural dynamics and interactions of emotion and language perception is important for selecting potent stimuli and devising effective training and/or treatment approaches for the alleviation of emotional dysfunction across a range of neuropsychiatric states. PMID:27877106

The Language, Tone and Prosody of Emotions: Neural Substrates and Dynamics of Spoken-Word Emotion Perception.

PubMed

Liebenthal, Einat; Silbersweig, David A; Stern, Emily

2016-01-01

Rapid assessment of emotions is important for detecting and prioritizing salient input. Emotions are conveyed in spoken words via verbal and non-verbal channels that are mutually informative and unveil in parallel over time, but the neural dynamics and interactions of these processes are not well understood. In this paper, we review the literature on emotion perception in faces, written words, and voices, as a basis for understanding the functional organization of emotion perception in spoken words. The characteristics of visual and auditory routes to the amygdala-a subcortical center for emotion perception-are compared across these stimulus classes in terms of neural dynamics, hemispheric lateralization, and functionality. Converging results from neuroimaging, electrophysiological, and lesion studies suggest the existence of an afferent route to the amygdala and primary visual cortex for fast and subliminal processing of coarse emotional face cues. We suggest that a fast route to the amygdala may also function for brief non-verbal vocalizations (e.g., laugh, cry), in which emotional category is conveyed effectively by voice tone and intensity. However, emotional prosody which evolves on longer time scales and is conveyed by fine-grained spectral cues appears to be processed via a slower, indirect cortical route. For verbal emotional content, the bulk of current evidence, indicating predominant left lateralization of the amygdala response and timing of emotional effects attributable to speeded lexical access, is more consistent with an indirect cortical route to the amygdala. Top-down linguistic modulation may play an important role for prioritized perception of emotions in words. Understanding the neural dynamics and interactions of emotion and language perception is important for selecting potent stimuli and devising effective training and/or treatment approaches for the alleviation of emotional dysfunction across a range of neuropsychiatric states.

Improved Estimation and Interpretation of Correlations in Neural Circuits

PubMed Central

Yatsenko, Dimitri; Josić, Krešimir; Ecker, Alexander S.; Froudarakis, Emmanouil; Cotton, R. James; Tolias, Andreas S.

2015-01-01

Ambitious projects aim to record the activity of ever larger and denser neuronal populations in vivo. Correlations in neural activity measured in such recordings can reveal important aspects of neural circuit organization. However, estimating and interpreting large correlation matrices is statistically challenging. Estimation can be improved by regularization, i.e. by imposing a structure on the estimate. The amount of improvement depends on how closely the assumed structure represents dependencies in the data. Therefore, the selection of the most efficient correlation matrix estimator for a given neural circuit must be determined empirically. Importantly, the identity and structure of the most efficient estimator informs about the types of dominant dependencies governing the system. We sought statistically efficient estimators of neural correlation matrices in recordings from large, dense groups of cortical neurons. Using fast 3D random-access laser scanning microscopy of calcium signals, we recorded the activity of nearly every neuron in volumes 200 μm wide and 100 μm deep (150–350 cells) in mouse visual cortex. We hypothesized that in these densely sampled recordings, the correlation matrix should be best modeled as the combination of a sparse graph of pairwise partial correlations representing local interactions and a low-rank component representing common fluctuations and external inputs. Indeed, in cross-validation tests, the covariance matrix estimator with this structure consistently outperformed other regularized estimators. The sparse component of the estimate defined a graph of interactions. These interactions reflected the physical distances and orientation tuning properties of cells: The density of positive ‘excitatory’ interactions decreased rapidly with geometric distances and with differences in orientation preference whereas negative ‘inhibitory’ interactions were less selective. Because of its superior performance, this ‘sparse+latent’ estimator likely provides a more physiologically relevant representation of the functional connectivity in densely sampled recordings than the sample correlation matrix. PMID:25826696

Intrinsic protective mechanisms of the neuron-glia network against glioma invasion.

PubMed

Iwadate, Yasuo; Fukuda, Kazumasa; Matsutani, Tomoo; Saeki, Naokatsu

2016-04-01

Gliomas arising in the brain parenchyma infiltrate into the surrounding brain and break down established complex neuron-glia networks. However, mounting evidence suggests that initially the network microenvironment of the adult central nervous system (CNS) is innately non-permissive to glioma cell invasion. The main players are inhibitory molecules in CNS myelin, as well as proteoglycans associated with astrocytes. Neural stem cells, and neurons themselves, possess inhibitory functions against neighboring tumor cells. These mechanisms have evolved to protect the established neuron-glia network, which is necessary for brain function. Greater insight into the interaction between glioma cells and the surrounding neuron-glia network is crucial for developing new therapies for treating these devastating tumors while preserving the important and complex neural functions of patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Induced neural stem cells achieve long-term survival and functional integration in the adult mouse brain.

PubMed

Hemmer, Kathrin; Zhang, Mingyue; van Wüllen, Thea; Sakalem, Marna; Tapia, Natalia; Baumuratov, Aidos; Kaltschmidt, Christian; Kaltschmidt, Barbara; Schöler, Hans R; Zhang, Weiqi; Schwamborn, Jens C

2014-09-09

Differentiated cells can be converted directly into multipotent neural stem cells (i.e., induced neural stem cells [iNSCs]). iNSCs offer an attractive alternative to induced pluripotent stem cell (iPSC) technology with regard to regenerative therapies. Here, we show an in vivo long-term analysis of transplanted iNSCs in the adult mouse brain. iNSCs showed sound in vivo long-term survival rates without graft overgrowths. The cells displayed a neural multilineage potential with a clear bias toward astrocytes and a permanent downregulation of progenitor and cell-cycle markers, indicating that iNSCs are not predisposed to tumor formation. Furthermore, the formation of synaptic connections as well as neuronal and glial electrophysiological properties demonstrated that differentiated iNSCs migrated, functionally integrated, and interacted with the existing neuronal circuitry. We conclude that iNSC long-term transplantation is a safe procedure; moreover, it might represent an interesting tool for future personalized regenerative applications. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Disambiguating brain functional connectivity.

PubMed

Duff, Eugene P; Makin, Tamar; Cottaar, Michiel; Smith, Stephen M; Woolrich, Mark W

2018-06-01

Functional connectivity (FC) analyses of correlations of neural activity are used extensively in neuroimaging and electrophysiology to gain insights into neural interactions. However, analyses assessing changes in correlation fail to distinguish effects produced by sources as different as changes in neural signal amplitudes or noise levels. This ambiguity substantially diminishes the value of FC for inferring system properties and clinical states. Network modelling approaches may avoid ambiguities, but require specific assumptions. We present an enhancement to FC analysis with improved specificity of inferences, minimal assumptions and no reduction in flexibility. The Additive Signal Change (ASC) approach characterizes FC changes into certain prevalent classes of signal change that involve the input of additional signal to existing activity. With FMRI data, the approach reveals a rich diversity of signal changes underlying measured changes in FC, suggesting that it could clarify our current understanding of FC changes in many contexts. The ASC method can also be used to disambiguate other measures of dependency, such as regression and coherence, providing a flexible tool for the analysis of neural data. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

Cortical–Subcortical Interactions in Hypersomnia Disorders: Mechanisms Underlying Cognitive and Behavioral Aspects of the Sleep–Wake Cycle

PubMed Central

Larson-Prior, Linda J.; Ju, Yo-El; Galvin, James E.

2014-01-01

Subcortical circuits mediating sleep–wake functions have been well characterized in animal models, and corroborated by more recent human studies. Disruptions in these circuits have been identified in hypersomnia disorders (HDs) such as narcolepsy and Kleine–Levin Syndrome, as well as in neurodegenerative disorders expressing excessive daytime sleepiness. However, the behavioral expression of sleep–wake functions is not a simple on-or-off state determined by subcortical circuits, but encompasses a complex range of behaviors determined by the interaction between cortical networks and subcortical circuits. While conceived as disorders of sleep, HDs are equally disorders of wake, representing a fundamental instability in neural state characterized by lapses of alertness during wake. These episodic lapses in alertness and wakefulness are also frequently seen in neurodegenerative disorders where electroencephalogram demonstrates abnormal function in cortical regions associated with cognitive fluctuations (CFs). Moreover, functional connectivity MRI shows instability of cortical networks in individuals with CFs. We propose that the inability to stabilize neural state due to disruptions in the sleep–wake control networks is common to the sleep and cognitive dysfunctions seen in hypersomnia and neurodegenerative disorders. PMID:25309500

Interaction between oxytocin receptor polymorphism and interdependent culture values on human empathy.

PubMed

Luo, Siyang; Ma, Yina; Liu, Yi; Li, Bingfeng; Wang, Chenbo; Shi, Zhenhao; Li, Xiaoyang; Zhang, Wenxia; Rao, Yi; Han, Shihui

2015-09-01

Recent evidence suggests that the association between oxytocin receptor polymorphism (OXTR rs53576) and emotion-related behavioral/psychological tendencies differs between individuals from East Asian and Western cultures. What remains unresolved is which specific dimension of cultural orientations interacts with OXTR rs53576 to shape these tendencies and whether such gene × culture interactions occurs at both behavioral and neural level. This study investigated whether and how OXTR rs53576 interacts with interdependence-a key dimension of cultural orientations that distinguish between East Asian and Western cultures-to affect human empathy that underlies altruistic motivation and prosocial behavior. Experiment 1 measured interdependence, empathy trait and OXTR rs53576 genotypes of 1536 Chinese participants. Hierarchical regression analyses revealed a stronger association between interdependence and empathy trait in G allele carriers compared with A/A homozygotes of OXTR rs53576. Experiment 2 measured neural responses to others' suffering by scanning A/A and G/G homozygous of OXTR rs53576 using functional magnetic resonance imaging. Hierarchical regression analyses revealed stronger associations between interdependence and empathic neural responses in the insula, amygdala and superior temporal gyrus in G/G compared with A/A carriers. Our results provide the first evidence for gene × culture interactions on empathy at both behavioral tendency and underlying brain activity. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions

NASA Astrophysics Data System (ADS)

Nguyen, Thuong T.; Székely, Eszter; Imbalzano, Giulio; Behler, Jörg; Csányi, Gábor; Ceriotti, Michele; Götz, Andreas W.; Paesani, Francesco

2018-06-01

The accurate representation of multidimensional potential energy surfaces is a necessary requirement for realistic computer simulations of molecular systems. The continued increase in computer power accompanied by advances in correlated electronic structure methods nowadays enables routine calculations of accurate interaction energies for small systems, which can then be used as references for the development of analytical potential energy functions (PEFs) rigorously derived from many-body (MB) expansions. Building on the accuracy of the MB-pol many-body PEF, we investigate here the performance of permutationally invariant polynomials (PIPs), neural networks, and Gaussian approximation potentials (GAPs) in representing water two-body and three-body interaction energies, denoting the resulting potentials PIP-MB-pol, Behler-Parrinello neural network-MB-pol, and GAP-MB-pol, respectively. Our analysis shows that all three analytical representations exhibit similar levels of accuracy in reproducing both two-body and three-body reference data as well as interaction energies of small water clusters obtained from calculations carried out at the coupled cluster level of theory, the current gold standard for chemical accuracy. These results demonstrate the synergy between interatomic potentials formulated in terms of a many-body expansion, such as MB-pol, that are physically sound and transferable, and machine-learning techniques that provide a flexible framework to approximate the short-range interaction energy terms.

Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks

PubMed Central

Simão, Daniel; Terrasso, Ana P.; Teixeira, Ana P.; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M.

2016-01-01

The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-13C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells. PMID:27619889

Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks.

PubMed

Simão, Daniel; Terrasso, Ana P; Teixeira, Ana P; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M

2016-09-13

The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-(13)C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells.

Interaction matters: A perceived social partner alters the neural processing of human speech.

PubMed

Rice, Katherine; Redcay, Elizabeth

2016-04-01

Mounting evidence suggests that social interaction changes how communicative behaviors (e.g., spoken language, gaze) are processed, but the precise neural bases by which social-interactive context may alter communication remain unknown. Various perspectives suggest that live interactions are more rewarding, more attention-grabbing, or require increased mentalizing-thinking about the thoughts of others. Dissociating between these possibilities is difficult because most extant neuroimaging paradigms examining social interaction have not directly compared live paradigms to conventional "offline" (or recorded) paradigms. We developed a novel fMRI paradigm to assess whether and how an interactive context changes the processing of speech matched in content and vocal characteristics. Participants listened to short vignettes--which contained no reference to people or mental states--believing that some vignettes were prerecorded and that others were presented over a real-time audio-feed by a live social partner. In actuality, all speech was prerecorded. Simply believing that speech was live increased activation in each participant's own mentalizing regions, defined using a functional localizer. Contrasting live to recorded speech did not reveal significant differences in attention or reward regions. Further, higher levels of autistic-like traits were associated with altered neural specialization for live interaction. These results suggest that humans engage in ongoing mentalizing about social partners, even when such mentalizing is not explicitly required, illustrating how social context shapes social cognition. Understanding communication in social context has important implications for typical and atypical social processing, especially for disorders like autism where social difficulties are more acute in live interaction. Copyright © 2015 Elsevier Inc. All rights reserved.

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex

PubMed Central

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were “non-task-specific” (NS) neurons that served as noise generators to “task-specific” neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors. PMID:27536235

Evolvable synthetic neural system

NASA Technical Reports Server (NTRS)

Curtis, Steven A. (Inventor)

2009-01-01

An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

Indian hedgehog signaling from endothelial cells is required for sclera and retinal pigment epithelium development in the mouse eye.

PubMed

Dakubo, Gabriel D; Mazerolle, Chantal; Furimsky, Marosh; Yu, Chuan; St-Jacques, Benoit; McMahon, Andrew P; Wallace, Valerie A

2008-08-01

The development of extraocular orbital structures, in particular the choroid and sclera, is regulated by a complex series of interactions between neuroectoderm, neural crest and mesoderm derivatives, although in many instances the signals that mediate these interactions are not known. In this study we have investigated the function of Indian hedgehog (Ihh) in the developing mammalian eye. We show that Ihh is expressed in a population of non-pigmented cells located in the developing choroid adjacent to the RPE. The analysis of Hh mutant mice demonstrates that the RPE and developing scleral mesenchyme are direct targets of Ihh signaling and that Ihh is required for the normal pigmentation pattern of the RPE and the condensation of mesenchymal cells to form the sclera. Our findings also indicate that Ihh signals indirectly to promote proliferation and photoreceptor specification in the neural retina. This study identifies Ihh as a novel choroid-derived signal that regulates RPE, sclera and neural retina development.

Alterations in brain activation during cognitive empathy are related to social functioning in schizophrenia.

PubMed

Smith, Matthew J; Schroeder, Matthew P; Abram, Samantha V; Goldman, Morris B; Parrish, Todd B; Wang, Xue; Derntl, Birgit; Habel, Ute; Decety, Jean; Reilly, James L; Csernansky, John G; Breiter, Hans C

2015-01-01

Impaired cognitive empathy (ie, understanding the emotional experiences of others) is associated with poor social functioning in schizophrenia. However, it is unclear whether the neural activity underlying cognitive empathy relates to social functioning. This study examined the neural activation supporting cognitive empathy performance and whether empathy-related activation during correctly performed trials was associated with self-reported cognitive empathy and measures of social functioning. Thirty schizophrenia outpatients and 24 controls completed a cognitive empathy paradigm during functional magnetic resonance imaging. Neural activity corresponding to correct judgments about the expected emotional expression in a social interaction was compared in schizophrenia subjects relative to control subjects. Participants also completed a self-report measure of empathy and 2 social functioning measures (social competence and social attainment). Schizophrenia subjects demonstrated significantly lower accuracy in task performance and were characterized by hypoactivation in empathy-related frontal, temporal, and parietal regions as well as hyperactivation in occipital regions compared with control subjects during accurate cognitive empathy trials. A cluster with peak activation in the supplementary motor area (SMA) extending to the anterior midcingulate cortex (aMCC) correlated with social competence and social attainment in schizophrenia subjects but not controls. These results suggest that neural correlates of cognitive empathy may be promising targets for interventions aiming to improve social functioning and that brain activation in the SMA/aMCC region could be used as a biomarker for monitoring treatment response. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

msh/Msx gene family in neural development.

PubMed

Ramos, Casto; Robert, Benoît

2005-11-01

The involvement of Msx homeobox genes in skull and tooth formation has received a great deal of attention. Recent studies also indicate a role for the msh/Msx gene family in development of the nervous system. In this article, we discuss the functions of these transcription factors in neural-tissue organogenesis. We will deal mainly with the interactions of the Drosophila muscle segment homeobox (msh) gene with other homeobox genes and the repressive cascade that leads to neuroectoderm patterning; the role of Msx genes in neural-crest induction, focusing especially on the differences between lower and higher vertebrates; their implication in patterning of the vertebrate neural tube, particularly in diencephalon midline formation. Finally, we will examine the distinct activities of Msx1, Msx2 and Msx3 genes during neurogenesis, taking into account their relationships with signalling molecules such as BMP.

Spatial Working Memory Performance and fMRI Activation Interactions in Abstinent Adolescent Marijuana Users

PubMed Central

Padula, Claudia B.; Schweinsburg, Alecia D.; Tapert, Susan F.

2008-01-01

Previous studies have suggested neural disruption and reorganization in adult marijuana users. However, it remains unclear whether these effects persist in adolescents after 28 days of abstinence and, if they do, what Performance × Brain Response interactions occur. Adolescent marijuana users (n = 17) and controls (n = 17) aged 16–18 years were recruited from local schools. Functional magnetic resonance imaging data were collected after 28 days’ monitored abstinence as participants performed a spatial working memory task. Marijuana users show Performance × Brain Response interactions in the bilateral temporal lobes, left anterior cingulate, left parahippocampal gyrus, and right thalamus (clusters ≥ 1358 μl; p <.05), although groups do not differ on behavioral measures of task performance. Marijuana users show differences in brain response to a spatial working memory task despite adequate performance, suggesting a different approach to the task via altered neural pathways. PMID:18072830

Attachment in integrative neuroscientific perspective.

PubMed

Hruby, Radovan; Hasto, Jozef; Minarik, Peter

2011-01-01

Attachment theory is a very influential general concept of human social and emotional development, which emphasizes the role of early mother-infant interactions for infant's adaptive behavioural and stress copying strategies, personality organization and mental health. Individuals with disrupted development of secure attachment to mother/primary caregiver are at higher risk of developing mental disorders. This theory consists of the complex developmental psycho-neurobiological model of attachment and emerges from principles of psychoanalysis, evolutionary biology, cognitive-developmental psychology, ethology, physiology and control systems theory. The progress of modern neuroscience enables interpretation of neurobiological aspects of the theory as multi-level neural interactions and functional development of important neural structures, effects of neuromediattors, hormones and essential neurobiological processes including emotional, cognitive, social interactions and the special key role of mentalizing. It has multiple neurobiological, neuroendocrine, neurophysiological, ethological, genetic, developmental, psychological, psychotherapeutic and neuropsychiatric consequences and is a prototype of complex neuroscientific concept as interpretation of modern integrated neuroscience.

Formation and remodeling of the brain extracellular matrix in neural plasticity: Roles of chondroitin sulfate and hyaluronan.

PubMed

Miyata, Shinji; Kitagawa, Hiroshi

2017-10-01

The extracellular matrix (ECM) of the brain is rich in glycosaminoglycans such as chondroitin sulfate (CS) and hyaluronan. These glycosaminoglycans are organized into either diffuse or condensed ECM. Diffuse ECM is distributed throughout the brain and fills perisynaptic spaces, whereas condensed ECM selectively surrounds parvalbumin-expressing inhibitory neurons (PV cells) in mesh-like structures called perineuronal nets (PNNs). The brain ECM acts as a non-specific physical barrier that modulates neural plasticity and axon regeneration. Here, we review recent progress in understanding of the molecular basis of organization and remodeling of the brain ECM, and the involvement of several types of experience-dependent neural plasticity, with a particular focus on the mechanism that regulates PV cell function through specific interactions between CS chains and their binding partners. We also discuss how the barrier function of the brain ECM restricts dendritic spine dynamics and limits axon regeneration after injury. The brain ECM not only forms physical barriers that modulate neural plasticity and axon regeneration, but also forms molecular brakes that actively controls maturation of PV cells and synapse plasticity in which sulfation patterns of CS chains play a key role. Structural remodeling of the brain ECM modulates neural function during development and pathogenesis. Genetic or enzymatic manipulation of the brain ECM may restore neural plasticity and enhance recovery from nerve injury. This article is part of a Special Issue entitled Neuro-glycoscience, edited by Kenji Kadomatsu and Hiroshi Kitagawa. Copyright © 2017 Elsevier B.V. All rights reserved.

The role of sensorimotor learning in the perception of letter-like forms: tracking the causes of neural specialization for letters.

PubMed

James, Karin H; Atwood, Thea P

2009-02-01

Functional specialization in the brain is considered a hallmark of efficient processing. It is therefore not surprising that there are brain areas specialized for processing letters. To better understand the causes of functional specialization for letters, we explore the emergence of this pattern of response in the ventral processing stream through a training paradigm. Previously, we hypothesized that the specialized response pattern seen during letter perception may be due in part to our experience in writing letters. The work presented here investigates whether or not this aspect of letter processing-the integration of sensorimotor systems through writing-leads to functional specialization in the visual system. To test this idea, we investigated whether or not different types of experiences with letter-like stimuli ("pseudoletters") led to functional specialization similar to that which exists for letters. Neural activation patterns were measured using functional magnetic resonance imaging (fMRI) before and after three different types of training sessions. Participants were trained to recognize pseudoletters by writing, typing, or purely visual practice. Results suggested that only after writing practice did neural activation patterns to pseudoletters resemble patterns seen for letters. That is, neural activation in the left fusiform and dorsal precentral gyrus was greater when participants viewed pseudoletters than other, similar stimuli but only after writing experience. Neural activation also increased after typing practice in the right fusiform and left precentral gyrus, suggesting that in some areas, any motor experience may change visual processing. The results of this experiment suggest an intimate interaction among perceptual and motor systems during pseudoletter perception that may be extended to everyday letter perception.

A loop-based neural architecture for structured behavior encoding and decoding.

PubMed

Gisiger, Thomas; Boukadoum, Mounir

2018-02-01

We present a new type of artificial neural network that generalizes on anatomical and dynamical aspects of the mammal brain. Its main novelty lies in its topological structure which is built as an array of interacting elementary motifs shaped like loops. These loops come in various types and can implement functions such as gating, inhibitory or executive control, or encoding of task elements to name a few. Each loop features two sets of neurons and a control region, linked together by non-recurrent projections. The two neural sets do the bulk of the loop's computations while the control unit specifies the timing and the conditions under which the computations implemented by the loop are to be performed. By functionally linking many such loops together, a neural network is obtained that may perform complex cognitive computations. To demonstrate the potential offered by such a system, we present two neural network simulations. The first illustrates the structure and dynamics of a single loop implementing a simple gating mechanism. The second simulation shows how connecting four loops in series can produce neural activity patterns that are sufficient to pass a simplified delayed-response task. We also show that this network reproduces electrophysiological measurements gathered in various regions of the brain of monkeys performing similar tasks. We also demonstrate connections between this type of neural network and recurrent or long short-term memory network models, and suggest ways to generalize them for future artificial intelligence research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cooperation of Deterministic Dynamics and Random Noise in Production of Complex Syntactical Avian Song Sequences: A Neural Network Model

PubMed Central

Yamashita, Yuichi; Okumura, Tetsu; Okanoya, Kazuo; Tani, Jun

2011-01-01

How the brain learns and generates temporal sequences is a fundamental issue in neuroscience. The production of birdsongs, a process which involves complex learned sequences, provides researchers with an excellent biological model for this topic. The Bengalese finch in particular learns a highly complex song with syntactical structure. The nucleus HVC (HVC), a premotor nucleus within the avian song system, plays a key role in generating the temporal structures of their songs. From lesion studies, the nucleus interfacialis (NIf) projecting to the HVC is considered one of the essential regions that contribute to the complexity of their songs. However, the types of interaction between the HVC and the NIf that can produce complex syntactical songs remain unclear. In order to investigate the function of interactions between the HVC and NIf, we have proposed a neural network model based on previous biological evidence. The HVC is modeled by a recurrent neural network (RNN) that learns to generate temporal patterns of songs. The NIf is modeled as a mechanism that provides auditory feedback to the HVC and generates random noise that feeds into the HVC. The model showed that complex syntactical songs can be replicated by simple interactions between deterministic dynamics of the RNN and random noise. In the current study, the plausibility of the model is tested by the comparison between the changes in the songs of actual birds induced by pharmacological inhibition of the NIf and the changes in the songs produced by the model resulting from modification of parameters representing NIf functions. The efficacy of the model demonstrates that the changes of songs induced by pharmacological inhibition of the NIf can be interpreted as a trade-off between the effects of noise and the effects of feedback on the dynamics of the RNN of the HVC. These facts suggest that the current model provides a convincing hypothesis for the functional role of NIf–HVC interaction. PMID:21559065

Zebrafish zic2 controls formation of periocular neural crest and choroid fissure morphogenesis.

PubMed

Sedykh, Irina; Yoon, Baul; Roberson, Laura; Moskvin, Oleg; Dewey, Colin N; Grinblat, Yevgenya

2017-09-01

The vertebrate retina develops in close proximity to the forebrain and neural crest-derived cartilages of the face and jaw. Coloboma, a congenital eye malformation, is associated with aberrant forebrain development (holoprosencephaly) and with craniofacial defects (frontonasal dysplasia) in humans, suggesting a critical role for cross-lineage interactions during retinal morphogenesis. ZIC2, a zinc-finger transcription factor, is linked to human holoprosencephaly. We have previously used morpholino assays to show zebrafish zic2 functions in the developing forebrain, retina and craniofacial cartilage. We now report that zebrafish with genetic lesions in zebrafish zic2 orthologs, zic2a and zic2b, develop with retinal coloboma and craniofacial anomalies. We demonstrate a requirement for zic2 in restricting pax2a expression and show evidence that zic2 function limits Hh signaling. RNA-seq transcriptome analysis identified an early requirement for zic2 in periocular neural crest as an activator of alx1, a transcription factor with essential roles in craniofacial and ocular morphogenesis in human and zebrafish. Collectively, these data establish zic2 mutant zebrafish as a powerful new genetic model for in-depth dissection of cell interactions and genetic controls during craniofacial complex development. Copyright © 2017 Elsevier Inc. All rights reserved.

The neural basis of the imitation drive.

PubMed

Hanawa, Sugiko; Sugiura, Motoaki; Nozawa, Takayuki; Kotozaki, Yuka; Yomogida, Yukihito; Ihara, Mizuki; Akimoto, Yoritaka; Thyreau, Benjamin; Izumi, Shinichi; Kawashima, Ryuta

2016-01-01

Spontaneous imitation is assumed to underlie the acquisition of important skills by infants, including language and social interaction. In this study, functional magnetic resonance imaging (fMRI) was used to examine the neural basis of 'spontaneously' driven imitation, which has not yet been fully investigated. Healthy participants were presented with movie clips of meaningless bimanual actions and instructed to observe and imitate them during an fMRI scan. The participants were subsequently shown the movie clips again and asked to evaluate the strength of their 'urge to imitate' (Urge) for each action. We searched for cortical areas where the degree of activation positively correlated with Urge scores; significant positive correlations were observed in the right supplementary motor area (SMA) and bilateral midcingulate cortex (MCC) under the imitation condition. These areas were not explained by explicit reasons for imitation or the kinematic characteristics of the actions. Previous studies performed in monkeys and humans have implicated the SMA and MCC/caudal cingulate zone in voluntary actions. This study also confirmed the functional connectivity between Urge and imitation performance using a psychophysiological interaction analysis. Thus, our findings reveal the critical neural components that underlie spontaneous imitation and provide possible reasons why infants imitate spontaneously. © The Author (2015). Published by Oxford University Press.

Neural connectivity during reward expectation dissociates psychopathic criminals from non-criminal individuals with high impulsive/antisocial psychopathic traits

PubMed Central

von Borries, Katinka; Volman, Inge; Bulten, Berend Hendrik; Cools, Roshan; Verkes, Robbert-Jan

2016-01-01

Criminal behaviour poses a big challenge for society. A thorough understanding of the neurobiological mechanisms underlying criminality could optimize its prevention and management. Specifically,elucidating the neural mechanisms underpinning reward expectation might be pivotal to understanding criminal behaviour. So far no study has assessed reward expectation and its mechanisms in a criminal sample. To fill this gap, we assessed reward expectation in incarcerated, psychopathic criminals. We compared this group to two groups of non-criminal individuals: one with high levels and another with low levels of impulsive/antisocial traits. Functional magnetic resonance imaging was used to quantify neural responses to reward expectancy. Psychophysiological interaction analyses were performed to examine differences in functional connectivity patterns of reward-related regions. The data suggest that overt criminality is characterized, not by abnormal reward expectation per se, but rather by enhanced communication between reward-related striatal regions and frontal brain regions. We establish that incarcerated psychopathic criminals can be dissociated from non-criminal individuals with comparable impulsive/antisocial personality tendencies based on the degree to which reward-related brain regions interact with brain regions that control behaviour. The present results help us understand why some people act according to their impulsive/antisocial personality while others are able to behave adaptively despite reward-related urges. PMID:27217111

Facing changes and changing faces in adolescence: A new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development

PubMed Central

Scherf, K. Suzanne; Behrmann, Marlene; Dahl, Ronald E.

2015-01-01

Adolescence is a time of dramatic physical, cognitive, emotional, and social changes as well as a time for the development of many social-emotional problems. These characteristics raise compelling questions about accompanying neural changes that are unique to this period of development. Here, we propose that studying adolescent-specific changes in face processing and its underlying neural circuitry provides an ideal model for addressing these questions. We also use this model to formulate new hypotheses. Specifically, pubertal hormones are likely to increase motivation to master new peer-oriented developmental tasks, which will in turn, instigate the emergence of new social/affective components of face processing. We also predict that pubertal hormones have a fundamental impact on the reorganization of neural circuitry supporting face processing and propose, in particular, that, the functional connectivity, or temporal synchrony, between regions of the face-processing network will change with the emergence of these new components of face processing in adolescence. Finally, we show how this approach will help reveal why adolescence may be a period of vulnerability in brain development and suggest how it could lead to prevention and intervention strategies that facilitate more adaptive functional interactions between regions within the broader social information processing network. PMID:22483070

Consciousness, Plasticity, and Connectomics: The Role of Intersubjectivity in Human Cognition

PubMed Central

Allen, Micah; Williams, Gary

2011-01-01

Consciousness is typically construed as being explainable purely in terms of either private, raw feels or higher-order, reflective representations. In contrast to this false dichotomy, we propose a new view of consciousness as an interactive, plastic phenomenon open to sociocultural influence. We take up our account of consciousness from the observation of radical cortical neuroplasticity in human development. Accordingly, we draw upon recent research on macroscopic neural networks, including the “default mode,” to illustrate cases in which an individual's particular “connectome” is shaped by encultured social practices that depend upon and influence phenomenal and reflective consciousness. On our account, the dynamically interacting connectivity of these networks bring about important individual differences in conscious experience and determine what is “present” in consciousness. Further, we argue that the organization of the brain into discrete anti-correlated networks supports the phenomenological distinction of prereflective and reflective consciousness, but we emphasize that this finding must be interpreted in light of the dynamic, category-resistant nature of consciousness. Our account motivates philosophical and empirical hypotheses regarding the appropriate time-scale and function of neuroplastic adaptation, the relation of high and low-frequency neural activity to consciousness and cognitive plasticity, and the role of ritual social practices in neural development and cognitive function. PMID:21687435

Effects of the BDNF Val66Met polymorphism on neural responses to facial emotion.

PubMed

Mukherjee, Prerona; Whalley, Heather C; McKirdy, James W; McIntosh, Andrew M; Johnstone, Eve C; Lawrie, Stephen M; Hall, Jeremy

2011-03-31

The brain derived neurotrophic factor (BDNF) Val66Met polymorphism has been associated with affective disorders, but its role in emotion processing has not been fully established. Due to the clinically heterogeneous nature of these disorders, studying the effect of genetic variation in the BDNF gene on a common attribute such as fear processing may elucidate how the BDNF Val66Met polymorphism impacts brain function. Here we use functional magnetic resonance imaging examine the effect of the BDNF Val66Met genotype on neural activity for fear processing. Forty healthy participants performed an implicit fear task during scanning, where subjects made gender judgments from facial images with neutral or fearful emotion. Subjects were tested for facial emotion recognition post-scan. Functional connectivity was investigated using psycho-physiological interactions. Subjects were genotyped for the BDNF Val66Met polymorphism and the measures compared between genotype groups. Met carriers showed overactivation in the anterior cingulate cortex (ACC), brainstem and insula bilaterally for fear processing, along with reduced functional connectivity from the ACC to the left hippocampus, and impaired fear recognition ability. The results show that during fear processing, Met allele carriers show an increased neural response in regions previously implicated in mediating autonomic arousal. Further, the Met carriers show decreased functional connectivity with the hippocampus, which may reflect differential retrieval of emotional associations. Together, these effects show significant differences in the neural substrate for fear processing with genetic variation in BDNF. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

False Belief Reasoning in Adults with and without Autistic Spectrum Disorder: Similarities and Differences.

PubMed

Sommer, Monika; Döhnel, Katrin; Jarvers, Irina; Blaas, Lore; Singer, Manuela; Nöth, Victoria; Schuwerk, Tobias; Rupprecht, Rainer

2018-01-01

A central diagnostic criteria for autism spectrum disorder (ASD) is the qualitative impairment in reciprocal social interaction and a prominent hypotheses that tried to explain this impairment is the Theory of Mind (ToM) deficit hypotheses. On a behavioral level the critical test for having a ToM, the understanding of false beliefs (FB), is often used for testing ToM abilities in individuals with ASD. Investigating the neural underpinnings several neuroimaging studies revealed a network of areas involved in FB reasoning in neurotypical individuals. For ASD individuals the neural correlates of false belief processing are largely unknown. Using functional magnetic resonance imaging and an adapted unexpected transfer task, that makes it possible to distinguish between the computation of diverging beliefs and the selection of a belief-associated response, we investigated a group of adult high-functioning individuals with ASD ( N = 15) and an age and IQ matched group of neurotypical adults (NT; N = 15). On the behavioral level we found no group differences. On the neural level, results were two-fold: In the story phase, in which participants had to compute whether the character's belief is congruent or incongruent to their own belief, there were no differences between neurotypical participants and those diagnosed with ASD. But, in the subsequent question phase, participants with ASD showed increased activity in the bilateral anterior prefrontal cortex, the left posterior frontal cortex, the left superior temporal gyrus, and the left temporoparietal area. These results suggest that during the story phase in which the participants processed observable actions the neural correlates do not differ between adult individuals with ASD and NT individuals. But in the question phase in which participants had to infer an unobservable mental state results revealed neural differences between the two groups. Possibly, these subtle neural processing differences may contribute to the fact that adult ASD individuals are able to master explicit false belief tasks but fail to apply their strategies during everyday social interaction.

False Belief Reasoning in Adults with and without Autistic Spectrum Disorder: Similarities and Differences

PubMed Central

Sommer, Monika; Döhnel, Katrin; Jarvers, Irina; Blaas, Lore; Singer, Manuela; Nöth, Victoria; Schuwerk, Tobias; Rupprecht, Rainer

2018-01-01

A central diagnostic criteria for autism spectrum disorder (ASD) is the qualitative impairment in reciprocal social interaction and a prominent hypotheses that tried to explain this impairment is the Theory of Mind (ToM) deficit hypotheses. On a behavioral level the critical test for having a ToM, the understanding of false beliefs (FB), is often used for testing ToM abilities in individuals with ASD. Investigating the neural underpinnings several neuroimaging studies revealed a network of areas involved in FB reasoning in neurotypical individuals. For ASD individuals the neural correlates of false belief processing are largely unknown. Using functional magnetic resonance imaging and an adapted unexpected transfer task, that makes it possible to distinguish between the computation of diverging beliefs and the selection of a belief-associated response, we investigated a group of adult high-functioning individuals with ASD (N = 15) and an age and IQ matched group of neurotypical adults (NT; N = 15). On the behavioral level we found no group differences. On the neural level, results were two-fold: In the story phase, in which participants had to compute whether the character's belief is congruent or incongruent to their own belief, there were no differences between neurotypical participants and those diagnosed with ASD. But, in the subsequent question phase, participants with ASD showed increased activity in the bilateral anterior prefrontal cortex, the left posterior frontal cortex, the left superior temporal gyrus, and the left temporoparietal area. These results suggest that during the story phase in which the participants processed observable actions the neural correlates do not differ between adult individuals with ASD and NT individuals. But in the question phase in which participants had to infer an unobservable mental state results revealed neural differences between the two groups. Possibly, these subtle neural processing differences may contribute to the fact that adult ASD individuals are able to master explicit false belief tasks but fail to apply their strategies during everyday social interaction. PMID:29503627

The Blood–Brain Barrier

PubMed Central

Daneman, Richard; Prat, Alexandre

2015-01-01

Blood vessels are critical to deliver oxygen and nutrients to all of the tissues and organs throughout the body. The blood vessels that vascularize the central nervous system (CNS) possess unique properties, termed the blood–brain barrier, which allow these vessels to tightly regulate the movement of ions, molecules, and cells between the blood and the brain. This precise control of CNS homeostasis allows for proper neuronal function and also protects the neural tissue from toxins and pathogens, and alterations of these barrier properties are an important component of pathology and progression of different neurological diseases. The physiological barrier is coordinated by a series of physical, transport, and metabolic properties possessed by the endothelial cells (ECs) that form the walls of the blood vessels, and these properties are regulated by interactions with different vascular, immune, and neural cells. Understanding how these different cell populations interact to regulate the barrier properties is essential for understanding how the brain functions during health and disease. PMID:25561720

Short- and long-term memory are modulated by multiple isoforms of the fragile X mental retardation protein.

PubMed

Banerjee, Paromita; Schoenfeld, Brian P; Bell, Aaron J; Choi, Catherine H; Bradley, Michael P; Hinchey, Paul; Kollaros, Maria; Park, Jae H; McBride, Sean M J; Dockendorff, Thomas C

2010-05-12

The diversity of protein isoforms arising from alternative splicing is thought to modulate fine-tuning of synaptic plasticity. Fragile X mental retardation protein (FMRP), a neuronal RNA binding protein, exists in isoforms as a result of alternative splicing, but the contribution of these isoforms to neural plasticity are not well understood. We show that two isoforms of Drosophila melanogaster FMRP (dFMR1) have differential roles in mediating neural development and behavior functions conferred by the dfmr1 gene. These isoforms differ in the presence of a protein interaction module that is related to prion domains and is functionally conserved between FMRPs. Expression of both isoforms is necessary for optimal performance in tests of short- and long-term memory of courtship training. The presence or absence of the protein interaction domain may govern the types of ribonucleoprotein (RNP) complexes dFMR1 assembles into, with different RNPs regulating gene expression in a manner necessary for establishing distinct phases of memory formation.

Neural Networks

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

Smith, Patrick I.

2003-09-23

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neuralmore » networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing information [2]. Each one of these cells acts as a simple processor. When individual cells interact with one another, the complex abilities of the brain are made possible. In neural networks, the input or data are processed by a propagation function that adds up the values of all the incoming data. The ending value is then compared with a threshold or specific value. The resulting value must exceed the activation function value in order to become output. The activation function is a mathematical function that a neuron uses to produce an output referring to its input value. [8] Figure 1 depicts this process. Neural networks usually have three components an input, a hidden, and an output. These layers create the end result of the neural network. A real world example is a child associating the word dog with a picture. The child says dog and simultaneously looks a picture of a dog. The input is the spoken word ''dog'', the hidden is the brain processing, and the output will be the category of the word dog based on the picture. This illustration describes how a neural network functions.« less

Early neural activation during facial affect processing in adolescents with Autism Spectrum Disorder.

PubMed

Leung, Rachel C; Pang, Elizabeth W; Cassel, Daniel; Brian, Jessica A; Smith, Mary Lou; Taylor, Margot J

2015-01-01

Impaired social interaction is one of the hallmarks of Autism Spectrum Disorder (ASD). Emotional faces are arguably the most critical visual social stimuli and the ability to perceive, recognize, and interpret emotions is central to social interaction and communication, and subsequently healthy social development. However, our understanding of the neural and cognitive mechanisms underlying emotional face processing in adolescents with ASD is limited. We recruited 48 adolescents, 24 with high functioning ASD and 24 typically developing controls. Participants completed an implicit emotional face processing task in the MEG. We examined spatiotemporal differences in neural activation between the groups during implicit angry and happy face processing. While there were no differences in response latencies between groups across emotions, adolescents with ASD had lower accuracy on the implicit emotional face processing task when the trials included angry faces. MEG data showed atypical neural activity in adolescents with ASD during angry and happy face processing, which included atypical activity in the insula, anterior and posterior cingulate and temporal and orbitofrontal regions. Our findings demonstrate differences in neural activity during happy and angry face processing between adolescents with and without ASD. These differences in activation in social cognitive regions may index the difficulties in face processing and in comprehension of social reward and punishment in the ASD group. Thus, our results suggest that atypical neural activation contributes to impaired affect processing, and thus social cognition, in adolescents with ASD.

Neural Integration in Body Perception.

PubMed

Ramsey, Richard

2018-06-19

The perception of other people is instrumental in guiding social interactions. For example, the appearance of the human body cues a wide range of inferences regarding sex, age, health, and personality, as well as emotional state and intentions, which influence social behavior. To date, most neuroscience research on body perception has aimed to characterize the functional contribution of segregated patches of cortex in the ventral visual stream. In light of the growing prominence of network architectures in neuroscience, the current article reviews neuroimaging studies that measure functional integration between different brain regions during body perception. The review demonstrates that body perception is not restricted to processing in the ventral visual stream but instead reflects a functional alliance between the ventral visual stream and extended neural systems associated with action perception, executive functions, and theory of mind. Overall, these findings demonstrate how body percepts are constructed through interactions in distributed brain networks and underscore that functional segregation and integration should be considered together when formulating neurocognitive theories of body perception. Insight from such an updated model of body perception generalizes to inform the organizational structure of social perception and cognition more generally and also informs disorders of body image, such as anorexia nervosa, which may rely on atypical integration of body-related information.

What can we learn from a two-brain approach to verbal interaction?

PubMed

Schoot, Lotte; Hagoort, Peter; Segaert, Katrien

2016-09-01

Verbal interaction is one of the most frequent social interactions humans encounter on a daily basis. In the current paper, we zoom in on what the multi-brain approach has contributed, and can contribute in the future, to our understanding of the neural mechanisms supporting verbal interaction. Indeed, since verbal interaction can only exist between individuals, it seems intuitive to focus analyses on inter-individual neural markers, i.e. between-brain neural coupling. To date, however, there is a severe lack of theoretically-driven, testable hypotheses about what between-brain neural coupling actually reflects. In this paper, we develop a testable hypothesis in which between-pair variation in between-brain neural coupling is of key importance. Based on theoretical frameworks and empirical data, we argue that the level of between-brain neural coupling reflects speaker-listener alignment at different levels of linguistic and extra-linguistic representation. We discuss the possibility that between-brain neural coupling could inform us about the highest level of inter-speaker alignment: mutual understanding. Copyright © 2016 Elsevier Ltd. All rights reserved.

Infant Neural Sensitivity to Dynamic Eye Gaze Relates to Quality of Parent-Infant Interaction at 7-Months in Infants at Risk for Autism

ERIC Educational Resources Information Center

Elsabbagh, Mayada; Bruno, Ruth; Wan, Ming Wai; Charman, Tony; Johnson, Mark H.; Green, Jonathan

2015-01-01

Links between brain function measures and quality of parent-child interactions within the early developmental period have been investigated in typical and atypical development. We examined such links in a group of 104 infants with and without a family history for autism in the first year of life. Our findings suggest robust associations between…

How humans integrate the prospects of pain and reward during choice

PubMed Central

Talmi, Deborah; Dayan, Peter; Kiebel, Stefan J.; Frith, Chris D.; Dolan, Raymond J.

2010-01-01

The maxim “no pain, no gain” summarises scenarios where an action leading to reward also entails a cost. Although we know a substantial amount about how the brain represents pain and reward separately, we know little about how they are integrated during goal directed behaviour. Two theoretical models might account for the integration of reward and pain. An additive model specifies that the disutility of costs is summed linearly with the utility of benefits, while an interactive model suggests that cost and benefit utilities interact so that the sensitivity to benefits is attenuated as costs become increasingly aversive. Using a novel task that required integration of physical pain and monetary reward, we examined the mechanism underlying cost-benefit integration in humans. We provide evidence in support of an interactive model in behavioural choice. Using functional neuroimaging we identify a neural signature for this interaction such that when the consequences of actions embody a mixture of reward and pain, there is an attenuation of a predictive reward-signal in both ventral anterior cingulate cortex and ventral striatum. We conclude that these regions subserve integration of action costs and benefits in humans, a finding that suggests a cross-species similarity in neural substrates that implement this function and illuminates mechanisms that underlie altered decision making under aversive conditions. PMID:19923294

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

PubMed

Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Alcohol and behavioral control: cognitive and neural mechanisms.

PubMed

Vogel-Sprott, M; Easdon, C; Fillmore, M; Finn, P; Justus, A

2001-01-01

This article represents the proceedings of a symposium at the 2000 RSA Meeting in Denver, Colorado. The organizer/chair was Muriel Vogel-Sprott. The presentations were (1) Alcohol-induced impairment of inhibitory control: Some commonalities with attention deficit hyperactivity disorder, by Mark Fillmore; (2) Neural interactions that underlie response inhibition under alcohol: A functional magnetic resonance imaging investigation, by Craig Easdon; (3) Intentional control of behavior under alcohol, by Muriel Vogel-Sprott; and (4) Working memory and the disinhibiting effects of alcohol on passive avoidance learning, by Alicia Justius and Peter Finn.

Triangular Quantum Loop Topography for Machine Learning

NASA Astrophysics Data System (ADS)

Zhang, Yi; Kim, Eun-Ah

Despite rapidly growing interest in harnessing machine learning in the study of quantum many-body systems there has been little success in training neural networks to identify topological phases. The key challenge is in efficiently extracting essential information from the many-body Hamiltonian or wave function and turning the information into an image that can be fed into a neural network. When targeting topological phases, this task becomes particularly challenging as topological phases are defined in terms of non-local properties. Here we introduce triangular quantum loop (TQL) topography: a procedure of constructing a multi-dimensional image from the ''sample'' Hamiltonian or wave function using two-point functions that form triangles. Feeding the TQL topography to a fully-connected neural network with a single hidden layer, we demonstrate that the architecture can be effectively trained to distinguish Chern insulator and fractional Chern insulator from trivial insulators with high fidelity. Given the versatility of the TQL topography procedure that can handle different lattice geometries, disorder, interaction and even degeneracy our work paves the route towards powerful applications of machine learning in the study of topological quantum matters.

Self-esteem modulates amygdala-ventrolateral prefrontal cortex connectivity in response to mortality threats.

PubMed

Yanagisawa, Kuniaki; Abe, Nobuhito; Kashima, Emiko S; Nomura, Michio

2016-03-01

Reminders of death often elicit defensive responses in individuals, especially among those with low self-esteem. Although empirical evidence indicates that self-esteem serves as a buffer against mortality threats, the precise neural mechanism underlying this effect remains unknown. We used functional magnetic resonance imaging (fMRI) to test the hypothesis that self-esteem modulates neural responses to death-related stimuli, especially functional connectivity within the limbic-frontal circuitry, thereby affecting subsequent defensive reactions. As predicted, individuals with high self-esteem subjected to a mortality threat exhibited increased amygdala-ventrolateral prefrontal cortex (VLPFC) connectivity during the processing of death-related stimuli compared with individuals who have low self-esteem. Further analysis revealed that stronger functional connectivity between the amygdala and the VLPFC predicted a subsequent decline in responding defensively to those who threaten one's beliefs. These results suggest that the amygdala-VLPFC interaction, which is modulated by self-esteem, can reduce the defensiveness caused by death-related stimuli, thereby providing a neural explanation for why individuals with high self-esteem exhibit less defensive reactions to mortality threats. (c) 2016 APA, all rights reserved).

Interactivity and reward-related neural activation during a serious videogame.

PubMed

Cole, Steven W; Yoo, Daniel J; Knutson, Brian

2012-01-01

This study sought to determine whether playing a "serious" interactive digital game (IDG)--the Re-Mission videogame for cancer patients--activates mesolimbic neural circuits associated with incentive motivation, and if so, whether such effects stem from the participatory aspects of interactive gameplay, or from the complex sensory/perceptual engagement generated by its dynamic event-stream. Healthy undergraduates were randomized to groups in which they were scanned with functional magnetic resonance imaging (FMRI) as they either actively played Re-Mission or as they passively observed a gameplay audio-visual stream generated by a yoked active group subject. Onset of interactive game play robustly activated mesolimbic projection regions including the caudate nucleus and nucleus accumbens, as well as a subregion of the parahippocampal gyrus. During interactive gameplay, subjects showed extended activation of the thalamus, anterior insula, putamen, and motor-related regions, accompanied by decreased activation in parietal and medial prefrontal cortex. Offset of interactive gameplay activated the anterior insula and anterior cingulate. Between-group comparisons of within-subject contrasts confirmed that mesolimbic activation was significantly more pronounced in the active playgroup than in the passive exposure control group. Individual difference analyses also found the magnitude of parahippocampal activation following gameplay onset to correlate with positive attitudes toward chemotherapy assessed both at the end of the scanning session and at an unannounced one-month follow-up. These findings suggest that IDG-induced activation of reward-related mesolimbic neural circuits stems primarily from participatory engagement in gameplay (interactivity), rather than from the effects of vivid and dynamic sensory stimulation.

Interactivity and Reward-Related Neural Activation during a Serious Videogame

PubMed Central

Cole, Steven W.; Yoo, Daniel J.; Knutson, Brian

2012-01-01

This study sought to determine whether playing a “serious” interactive digital game (IDG) – the Re-Mission videogame for cancer patients – activates mesolimbic neural circuits associated with incentive motivation, and if so, whether such effects stem from the participatory aspects of interactive gameplay, or from the complex sensory/perceptual engagement generated by its dynamic event-stream. Healthy undergraduates were randomized to groups in which they were scanned with functional magnetic resonance imaging (FMRI) as they either actively played Re-Mission or as they passively observed a gameplay audio-visual stream generated by a yoked active group subject. Onset of interactive game play robustly activated mesolimbic projection regions including the caudate nucleus and nucleus accumbens, as well as a subregion of the parahippocampal gyrus. During interactive gameplay, subjects showed extended activation of the thalamus, anterior insula, putamen, and motor-related regions, accompanied by decreased activation in parietal and medial prefrontal cortex. Offset of interactive gameplay activated the anterior insula and anterior cingulate. Between-group comparisons of within-subject contrasts confirmed that mesolimbic activation was significantly more pronounced in the active playgroup than in the passive exposure control group. Individual difference analyses also found the magnitude of parahippocampal activation following gameplay onset to correlate with positive attitudes toward chemotherapy assessed both at the end of the scanning session and at an unannounced one-month follow-up. These findings suggest that IDG-induced activation of reward-related mesolimbic neural circuits stems primarily from participatory engagement in gameplay (interactivity), rather than from the effects of vivid and dynamic sensory stimulation. PMID:22442733

The Cluster Variation Method: A Primer for Neuroscientists.

PubMed

Maren, Alianna J

2016-09-30

Effective Brain-Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables , is defined in terms of a single interaction enthalpy parameter ( h ) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

Amigo adhesion protein regulates development of neural circuits in zebrafish brain.

PubMed

Zhao, Xiang; Kuja-Panula, Juha; Sundvik, Maria; Chen, Yu-Chia; Aho, Vilma; Peltola, Marjaana A; Porkka-Heiskanen, Tarja; Panula, Pertti; Rauvala, Heikki

2014-07-18

The Amigo protein family consists of three transmembrane proteins characterized by six leucine-rich repeat domains and one immunoglobulin-like domain in their extracellular moieties. Previous in vitro studies have suggested a role as homophilic adhesion molecules in brain neurons, but the in vivo functions remain unknown. Here we have cloned all three zebrafish amigos and show that amigo1 is the predominant family member expressed during nervous system development in zebrafish. Knockdown of amigo1 expression using morpholino oligonucleotides impairs the formation of fasciculated tracts in early fiber scaffolds of brain. A similar defect in fiber tract development is caused by mRNA-mediated expression of the Amigo1 ectodomain that inhibits adhesion mediated by the full-length protein. Analysis of differentiated neural circuits reveals defects in the catecholaminergic system. At the behavioral level, the disturbed formation of neural circuitry is reflected in enhanced locomotor activity and in the inability of the larvae to perform normal escape responses. We suggest that Amigo1 is essential for the development of neural circuits of zebrafish, where its mechanism involves homophilic interactions within the developing fiber tracts and regulation of the Kv2.1 potassium channel to form functional neural circuitry that controls locomotion. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The Cluster Variation Method: A Primer for Neuroscientists

PubMed Central

Maren, Alianna J.

2016-01-01

Effective Brain–Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables, is defined in terms of a single interaction enthalpy parameter (h) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found. PMID:27706022

Influence of the cortical midline structures on moral emotion and motivation in moral decision-making.

PubMed

Han, Hyemin; Chen, Jingyuan; Jeong, Changwoo; Glover, Gary H

2016-04-01

The present study aims to examine the relationship between the cortical midline structures (CMS), which have been regarded to be associated with selfhood, and moral decision making processes at the neural level. Traditional moral psychological studies have suggested the role of moral self as the moderator of moral cognition, so activity of moral self would present at the neural level. The present study examined the interaction between the CMS and other moral-related regions by conducting psycho-physiological interaction analysis of functional images acquired while 16 subjects were solving moral dilemmas. Furthermore, we performed Granger causality analysis to demonstrate the direction of influences between activities in the regions in moral decision-making. We first demonstrate there are significant positive interactions between two central CMS seed regions-i.e., the medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC)-and brain regions associated with moral functioning including the cerebellum, brainstem, midbrain, dorsolateral prefrontal cortex, orbitofrontal cortex and anterior insula (AI); on the other hand, the posterior insula (PI) showed significant negative interaction with the seed regions. Second, several significant Granger causality was found from CMS to insula regions particularly under the moral-personal condition. Furthermore, significant dominant influence from the AI to PI was reported. Moral psychological implications of these findings are discussed. The present study demonstrated the significant interaction and influence between the CMS and morality-related regions while subject were solving moral dilemmas. Given that, activity in the CMS is significantly involved in human moral functioning. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural Signatures of Trust During Human-Automation Interactions

DTIC Science & Technology

2016-04-01

magnetic resonance imaging by manipulating the reliability of advice from a human or automated luggage inspector framed as experts. HAT and HHT were...human-human trust, human-automation trust, brain, functional magnetic resonance imaging 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18...behavioral X-ray luggage-screening task with functional magnetic resonance imaging (fMRI) and manipulated reliabilities of advice (unknown to the

Effects of Career Duration, Concussion History, and Playing Position on White Matter Microstructure and Functional Neural Recruitment in Former College and Professional Football Athletes.

PubMed

Clark, Michael D; Varangis, Eleanna M L; Champagne, Allen A; Giovanello, Kelly S; Shi, Feng; Kerr, Zachary Y; Smith, J Keith; Guskiewicz, Kevin M

2018-03-01

Purpose To better understand the relationship between exposure to concussive and subconcussive head impacts, white matter integrity, and functional task-related neural activity in former U.S. football athletes. Materials and Methods Between 2011 and 2013, 61 cognitively unimpaired former collegiate and professional football players (age range, 52-65 years) provided informed consent to participate in this cross-sectional study. Participants were stratified across three crossed factors: career duration, concussion history, and primary playing position. Fractional anisotropy (FA) and blood oxygen level-dependent (BOLD) percent signal change (PSC) were measured with diffusion-weighted and task-related functional magnetic resonance imaging, respectively. Analyses of variance of FA and BOLD PSC were used to determine main or interaction effects of the three factors. Results A significant interaction between career duration and concussion history was observed; former college players with more than three concussions had lower FA in a broadly distributed area of white matter compared with those with zero to one concussion (t29 = 2.774; adjusted P = .037), and the opposite was observed for former professional players (t29 = 3.883; adjusted P = .001). A separate interaction between concussion history and position was observed: Nonspeed players with more than three concussions had lower FA in frontal white matter compared with those with zero to one concussion (t25 = 3.861; adjusted P = .002). Analysis of working memory-task BOLD PSC revealed a similar interaction between concussion history and position (all adjusted P < .004). Overall, former players with lower FA tended to have lower BOLD PSC across three levels of a working memory task. Conclusion Career duration and primary playing position seem to modify the effects of concussion history on white matter structure and neural recruitment. The differences in brain structure and function were observed in the absence of clinical impairment, which suggested that multimodal imaging may provide early markers of onset of traumatic neurodegenerative disease. © RSNA, 2017 Online supplemental material is available for this article.

Interactions between glutamate, dopamine, and the neuronal signature of response inhibition in the human striatum.

PubMed

Lorenz, Robert C; Gleich, Tobias; Buchert, Ralph; Schlagenhauf, Florian; Kühn, Simone; Gallinat, Jürgen

2015-10-01

Response inhibition is a basic mechanism in cognitive control and dysfunctional in major psychiatric disorders. The neuronal mechanisms are in part driven by dopamine in the striatum. Animal data suggest a regulatory role of glutamate on the level of the striatum. We used a trimodal imaging procedure of the human striatum including F18-DOPA positron emission tomography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging of a stop signal task. We investigated dopamine synthesis capacity and glutamate concentration in vivo and their relation to functional properties of response inhibition. A mediation analysis revealed a significant positive association between dopamine synthesis capacity and inhibition-related neural activity in the caudate nucleus. This relationship was significantly mediated by striatal glutamate concentration. Furthermore, stop signal reaction time was inversely related to striatal activity during inhibition. The data show, for the first time in humans, an interaction between dopamine, glutamate, and the neural signature of response inhibition in the striatum. This finding stresses the importance of the dopamine-glutamate interaction for behavior and may facilitate the understanding of psychiatric disorders characterized by impaired response inhibition. © 2015 Wiley Periodicals, Inc.

Collybistin binds and inhibits mTORC1 signaling: a potential novel mechanism contributing to intellectual disability and autism.

PubMed

Machado, Camila Oliveira Freitas; Griesi-Oliveira, Karina; Rosenberg, Carla; Kok, Fernando; Martins, Stephanie; Passos-Bueno, Maria Rita; Sertie, Andrea Laurato

2016-01-01

Protein synthesis regulation via mammalian target of rapamycin complex 1 (mTORC1) signaling pathway has key roles in neural development and function, and its dysregulation is involved in neurodevelopmental disorders associated with autism and intellectual disability. mTOR regulates assembly of the translation initiation machinery by interacting with the eukaryotic initiation factor eIF3 complex and by controlling phosphorylation of key translational regulators. Collybistin (CB), a neuron-specific Rho-GEF responsible for X-linked intellectual disability with epilepsy, also interacts with eIF3, and its binding partner gephyrin associates with mTOR. Therefore, we hypothesized that CB also binds mTOR and affects mTORC1 signaling activity in neuronal cells. Here, by using induced pluripotent stem cell-derived neural progenitor cells from a male patient with a deletion of entire CB gene and from control individuals, as well as a heterologous expression system, we describe that CB physically interacts with mTOR and inhibits mTORC1 signaling pathway and protein synthesis. These findings suggest that disinhibited mTORC1 signaling may also contribute to the pathological process in patients with loss-of-function variants in CB.

Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

PubMed Central

Lücke, Jörg

2012-01-01

Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing. PMID:22457610

Collybistin binds and inhibits mTORC1 signaling: a potential novel mechanism contributing to intellectual disability and autism

PubMed Central

Machado, Camila Oliveira Freitas; Griesi-Oliveira, Karina; Rosenberg, Carla; Kok, Fernando; Martins, Stephanie; Rita Passos-Bueno, Maria; Sertie, Andrea Laurato

2016-01-01

Protein synthesis regulation via mammalian target of rapamycin complex 1 (mTORC1) signaling pathway has key roles in neural development and function, and its dysregulation is involved in neurodevelopmental disorders associated with autism and intellectual disability. mTOR regulates assembly of the translation initiation machinery by interacting with the eukaryotic initiation factor eIF3 complex and by controlling phosphorylation of key translational regulators. Collybistin (CB), a neuron-specific Rho-GEF responsible for X-linked intellectual disability with epilepsy, also interacts with eIF3, and its binding partner gephyrin associates with mTOR. Therefore, we hypothesized that CB also binds mTOR and affects mTORC1 signaling activity in neuronal cells. Here, by using induced pluripotent stem cell-derived neural progenitor cells from a male patient with a deletion of entire CB gene and from control individuals, as well as a heterologous expression system, we describe that CB physically interacts with mTOR and inhibits mTORC1 signaling pathway and protein synthesis. These findings suggest that disinhibited mTORC1 signaling may also contribute to the pathological process in patients with loss-of-function variants in CB. PMID:25898924

Feedforward inhibition and synaptic scaling--two sides of the same coin?

PubMed

Keck, Christian; Savin, Cristina; Lücke, Jörg

2012-01-01

Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

Spikes alone do not behavior make: Why neuroscience needs biomechanics

PubMed Central

Tytell, E.D.; Holmes, P.; Cohen, A.H.

2011-01-01

Neural circuits do not function in isolation; they interact with the physical world, accepting sensory inputs and producing outputs via muscles. Since both these pathways are constrained by physics, the activity of neural circuits can only be understood by considering biomechanics of muscles, bodies, and the exterior world. We discuss how animal bodies have natural stable motions that require relatively little activation or control from the nervous system. The nervous system can substantially alter these motions, by subtly changing mechanical properties such as leg sti ness. Mechanics can also provide robustness to perturbations without sensory reflexes. By considering a complete neuromechanical system, neuroscientists and biomechanicians together can provide a more integrated view of neural circuitry and behavior. PMID:21683575

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Role of local network oscillations in resting-state functional connectivity.

PubMed

Cabral, Joana; Hugues, Etienne; Sporns, Olaf; Deco, Gustavo

2011-07-01

Spatio-temporally organized low-frequency fluctuations (<0.1 Hz), observed in BOLD fMRI signal during rest, suggest the existence of underlying network dynamics that emerge spontaneously from intrinsic brain processes. Furthermore, significant correlations between distinct anatomical regions-or functional connectivity (FC)-have led to the identification of several widely distributed resting-state networks (RSNs). This slow dynamics seems to be highly structured by anatomical connectivity but the mechanism behind it and its relationship with neural activity, particularly in the gamma frequency range, remains largely unknown. Indeed, direct measurements of neuronal activity have revealed similar large-scale correlations, particularly in slow power fluctuations of local field potential gamma frequency range oscillations. To address these questions, we investigated neural dynamics in a large-scale model of the human brain's neural activity. A key ingredient of the model was a structural brain network defined by empirically derived long-range brain connectivity together with the corresponding conduction delays. A neural population, assumed to spontaneously oscillate in the gamma frequency range, was placed at each network node. When these oscillatory units are integrated in the network, they behave as weakly coupled oscillators. The time-delayed interaction between nodes is described by the Kuramoto model of phase oscillators, a biologically-based model of coupled oscillatory systems. For a realistic setting of axonal conduction speed, we show that time-delayed network interaction leads to the emergence of slow neural activity fluctuations, whose patterns correlate significantly with the empirically measured FC. The best agreement of the simulated FC with the empirically measured FC is found for a set of parameters where subsets of nodes tend to synchronize although the network is not globally synchronized. Inside such clusters, the simulated BOLD signal between nodes is found to be correlated, instantiating the empirically observed RSNs. Between clusters, patterns of positive and negative correlations are observed, as described in experimental studies. These results are found to be robust with respect to a biologically plausible range of model parameters. In conclusion, our model suggests how resting-state neural activity can originate from the interplay between the local neural dynamics and the large-scale structure of the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Neural mirroring and social interaction: Motor system involvement during action observation relates to early peer cooperation.

PubMed

Endedijk, H M; Meyer, M; Bekkering, H; Cillessen, A H N; Hunnius, S

2017-04-01

Whether we hand over objects to someone, play a team sport, or make music together, social interaction often involves interpersonal action coordination, both during instances of cooperation and entrainment. Neural mirroring is thought to play a crucial role in processing other's actions and is therefore considered important for social interaction. Still, to date, it is unknown whether interindividual differences in neural mirroring play a role in interpersonal coordination during different instances of social interaction. A relation between neural mirroring and interpersonal coordination has particularly relevant implications for early childhood, since successful early interaction with peers is predictive of a more favorable social development. We examined the relation between neural mirroring and children's interpersonal coordination during peer interaction using EEG and longitudinal behavioral data. Results showed that 4-year-old children with higher levels of motor system involvement during action observation (as indicated by lower beta-power) were more successful in early peer cooperation. This is the first evidence for a relation between motor system involvement during action observation and interpersonal coordination during other instances of social interaction. The findings suggest that interindividual differences in neural mirroring are related to interpersonal coordination and thus successful social interaction. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

In Vivo Neuromechanics: Decoding Causal Motor Neuron Behavior with Resulting Musculoskeletal Function.

PubMed

Sartori, Massimo; Yavuz, Utku Ş; Farina, Dario

2017-10-18

Human motor function emerges from the interaction between the neuromuscular and the musculoskeletal systems. Despite the knowledge of the mechanisms underlying neural and mechanical functions, there is no relevant understanding of the neuro-mechanical interplay in the neuro-musculo-skeletal system. This currently represents the major challenge to the understanding of human movement. We address this challenge by proposing a paradigm for investigating spinal motor neuron contribution to skeletal joint mechanical function in the intact human in vivo. We employ multi-muscle spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-motor neuron discharges across five lumbosacral segments in the human spinal cord. We use complete α-motor neuron discharge series to drive forward subject-specific models of the musculoskeletal system in open-loop with no corrective feedback. We perform validation tests where mechanical moments are estimated with no knowledge of reference data over unseen conditions. This enables accurate blinded estimation of ankle function purely from motor neuron information. Remarkably, this enables observing causal associations between spinal motor neuron activity and joint moment control. We provide a new class of neural data-driven musculoskeletal modeling formulations for bridging between movement neural and mechanical levels in vivo with implications for understanding motor physiology, pathology, and recovery.

Neural correlates of spontaneous deception: A functional near-infrared spectroscopy (fNIRS) study

PubMed Central

Ding, Xiao Pan; Gao, Xiaoqing; Fu, Genyue; Lee, Kang

2013-01-01

Deception is commonly seen in everyday social interactions. However, most of the knowledge about the underlying neural mechanism of deception comes from studies where participants were instructed when and how to lie. To study spontaneous deception, we designed a guessing game modeled after Greene and Paxton (2009), in which lying is the only way to achieve the performance level needed to end the game. We recorded neural responses during the game using near-infrared spectroscopy (NIRS). We found that when compared to truth-telling, spontaneous deception, like instructed deception, engenders greater involvement of such prefrontal regions as the left superior frontal gyrus. We also found that the correct-truth trials produced greater neural activities in the left middle frontal gyrus and right superior frontal gyrus than the incorrect-truth trials, suggesting the involvement of the reward system. Furthermore, the present study confirmed the feasibility of using NIRS to study spontaneous deception. PMID:23340482

Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

PubMed

Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

2017-01-01

This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

Reduced neural activity of the prefrontal cognitive control circuitry during response inhibition to negative words in people with schizophrenia

PubMed Central

Vercammen, Ans; Morris, Richard; Green, Melissa J.; Lenroot, Rhoshel; Kulkarni, Jayashri; Carr, Vaughan J.; Weickert, Cynthia Shannon; Weickert, Thomas W.

2012-01-01

Background Schizophrenia is characterized by deficits in executive control and impairments in emotion processing. This study assessed the nature and extent of potential alterations in the neural substrates supporting the interaction between cognitive control mechanisms and emotion attribution processes in people with schizophrenia. Methods Functional magnetic resonance imaging was performed during a verbal emotional go/no-go task. People with schizophrenia and healthy controls responded to word stimuli of a prespecified emotional valence (positive, negative or neutral) while inhibiting responses to stimuli of a different valence. Results We enrolled 20 people with schizophrenia and 23 controls in the study. Healthy controls activated an extensive dorsal prefrontal–parietal network while inhibiting responses to negative words compared to neutral words, but showed deactivation of the midcingulate cortex while inhibiting responses to positive words compared to neutral words. People with schizophrenia failed to activate this network during response inhibition to negative words, whereas during response inhibition to positive words they did not deactivate the cingulate, but showed increased responsivity in the frontal cortex. Limitations Sample heterogeneity is characteristic of studies of schizophrenia and may have contributed to more variable neural responses in the patient sample despite the care taken to control for potentially confounding variables. Conclusion Our results showed that schizophrenia is associated with aberrant modulation of neural responses during the interaction between cognitive control and emotion processing. Failure of the frontal circuitry to regulate goal-directed behaviour based on emotion attributions may contribute to deficits in psychosocial functioning in daily life. PMID:22617625

Computational Models and Emergent Properties of Respiratory Neural Networks

PubMed Central

Lindsey, Bruce G.; Rybak, Ilya A.; Smith, Jeffrey C.

2012-01-01

Computational models of the neural control system for breathing in mammals provide a theoretical and computational framework bringing together experimental data obtained from different animal preparations under various experimental conditions. Many of these models were developed in parallel and iteratively with experimental studies and provided predictions guiding new experiments. This data-driven modeling approach has advanced our understanding of respiratory network architecture and neural mechanisms underlying generation of the respiratory rhythm and pattern, including their functional reorganization under different physiological conditions. Models reviewed here vary in neurobiological details and computational complexity and span multiple spatiotemporal scales of respiratory control mechanisms. Recent models describe interacting populations of respiratory neurons spatially distributed within the Bötzinger and pre-Bötzinger complexes and rostral ventrolateral medulla that contain core circuits of the respiratory central pattern generator (CPG). Network interactions within these circuits along with intrinsic rhythmogenic properties of neurons form a hierarchy of multiple rhythm generation mechanisms. The functional expression of these mechanisms is controlled by input drives from other brainstem components, including the retrotrapezoid nucleus and pons, which regulate the dynamic behavior of the core circuitry. The emerging view is that the brainstem respiratory network has rhythmogenic capabilities at multiple levels of circuit organization. This allows flexible, state-dependent expression of different neural pattern-generation mechanisms under various physiological conditions, enabling a wide repertoire of respiratory behaviors. Some models consider control of the respiratory CPG by pulmonary feedback and network reconfiguration during defensive behaviors such as cough. Future directions in modeling of the respiratory CPG are considered. PMID:23687564

Beyond perceptual expertise: revisiting the neural substrates of expert object recognition

PubMed Central

Harel, Assaf; Kravitz, Dwight; Baker, Chris I.

2013-01-01

Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex. PMID:24409134

Spatial working memory in neurofibromatosis 1: Altered neural activity and functional connectivity.

PubMed

Ibrahim, Amira F A; Montojo, Caroline A; Haut, Kristen M; Karlsgodt, Katherine H; Hansen, Laura; Congdon, Eliza; Rosser, Tena; Bilder, Robert M; Silva, Alcino J; Bearden, Carrie E

2017-01-01

Neurofibromatosis Type 1 (NF1) is a genetic disorder that disrupts central nervous system development and neuronal function. Cognitively, NF1 is characterized by difficulties with executive control and visuospatial abilities. Little is known about the neural substrates underlying these deficits. The current study utilized Blood-Oxygen-Level-Dependent (BOLD) functional MRI (fMRI) to explore the neural correlates of spatial working memory (WM) deficits in patients with NF1. BOLD images were acquired from 23 adults with NF1 (age M  = 32.69; 61% male) and 25 matched healthy controls (age M  = 33.08; 64% male) during an in-scanner visuo-spatial WM task. Whole brain functional and psycho-physiological interaction analyses were utilized to investigate neural activity and functional connectivity, respectively, during visuo-spatial WM performance. Participants also completed behavioral measures of spatial reasoning and verbal WM. Relative to healthy controls, participants with NF1 showed reduced recruitment of key components of WM circuitry, the left dorsolateral prefrontal cortex and right parietal cortex. In addition, healthy controls exhibited greater simultaneous deactivation between the posterior cingulate cortex (PCC) and temporal regions than NF1 patients. In contrast, NF1 patients showed greater PCC and bilateral parietal connectivity with visual cortices as well as between the PCC and the cerebellum. In NF1 participants, increased functional coupling of the PCC with frontal and parietal regions was associated with better spatial reasoning and WM performance, respectively; these relationships were not observed in controls. Dysfunctional engagement of WM circuitry, and aberrant functional connectivity of 'task-negative' regions in NF1 patients may underlie spatial WM difficulties characteristic of the disorder.

Separate neural mechanisms underlie choices and strategic preferences in risky decision making.

PubMed

Venkatraman, Vinod; Payne, John W; Bettman, James R; Luce, Mary Frances; Huettel, Scott A

2009-05-28

Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using an economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual's preferred strategy. Choices that maximized gains or minimized losses were predicted by functional magnetic resonance imaging activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending on strategies, traits, and context.

Convergent dysregulation of frontal cortical cognitive and reward systems in eating disorders.

PubMed

Stefano, George B; Ptáček, Radek; Kuželová, Hana; Mantione, Kirk J; Raboch, Jiří; Papezova, Hana; Kream, Richard M

2013-05-10

A substantive literature has drawn a compelling case for the functional involvement of mesolimbic/prefrontal cortical neural reward systems in normative control of eating and in the etiology and persistence of severe eating disorders that affect diverse human populations. Presently, we provide a short review that develops an equally compelling case for the importance of dysregulated frontal cortical cognitive neural networks acting in concert with regional reward systems in the regulation of complex eating behaviors and in the presentation of complex pathophysiological symptoms associated with major eating disorders. Our goal is to highlight working models of major eating disorders that incorporate complementary approaches to elucidate functionally interactive neural circuits defined by their regulatory neurochemical phenotypes. Importantly, we also review evidence-based linkages between widely studied psychiatric and neurodegenerative syndromes (e.g., autism spectrum disorders and Parkinson's disease) and co-morbid eating disorders to elucidate basic mechanisms involving dopaminergic transmission and its regulation by endogenously expressed morphine in these same cortical regions.

The Brain's Response to Digital Math Apps: A Pilot Study Examining Children's Cortical Responses during Touch-Screen Interactions

ERIC Educational Resources Information Center

Baker, Joseph M.; Moyer-Packenham, Patricia S.; Tucker, Stephen I.; Shumway, Jessica F.; Jordan, Kerry E.; Gillam, Ronald B.

2018-01-01

Functional near-infrared spectroscopy (fNIRS) is an easy to use neuroimaging technique that is portable and maintains a liberal tolerance to movement. As such, fNIRS represents an ideal tool to observe children's neural activity as they engage in real-world classroom activities, such as the interaction with digital math apps on an iPad. Here, we…

Neural transcription factors bias cleavage stage blastomeres to give rise to neural ectoderm

PubMed Central

Gaur, Shailly; Mandelbaum, Max; Herold, Mona; Majumdar, Himani Datta; Neilson, Karen M.; Maynard, Thomas M.; Mood, Kathy; Daar, Ira O.; Moody, Sally A.

2016-01-01

The decision by embryonic ectoderm to give rise to epidermal versus neural derivatives is the result of signaling events during blastula and gastrula stages. However, there also is evidence in Xenopus that cleavage stage blastomeres contain maternally derived molecules that bias them toward a neural fate. We used a blastomere explant culture assay to test whether maternally deposited transcription factors bias 16-cell blastomere precursors of epidermal or neural ectoderm to express early zygotic neural genes in the absence of gastrulation interactions or exogenously supplied signaling factors. We found that Foxd4l1, Zic2, Gmnn and Sox11 each induced explants made from ventral, epidermis-producing blastomeres to express early neural genes, and that at least some of the Foxd4l1 and Zic2 activity is required at cleavage stages. Similarly, providing extra Foxd4l1 or Zic2 to explants made from dorsal, neural plate-producing blastomeres significantly increased expression of early neural genes, whereas knocking down either significantly reduced them. These results show that maternally delivered transcription factors bias cleavage stage blastomeres to a neural fate. We demonstrate that mouse and human homologues of Foxd4l1 have similar functional domains compared to the frog protein, as well as conserved transcriptional activities when expressed in Xenopus embryos and blastomere explants. PMID:27092474

A Balanced Accuracy Fitness Function Leads to Robust Analysis Using Grammatical Evolution Neural Networks in the Case of Class Imbalance

EPA Science Inventory

The identification and characterization of genetic and environmental factors that predict common, complex disease is a major goal of human genetics. The ubiquitous nature of epistatic interaction in the underlying genetic etiology of such disease presents a difficult analytical ...

Cognitive Control over Learning: Creating, Clustering, and Generalizing Task-Set Structure

ERIC Educational Resources Information Center

Collins, Anne G. E.; Frank, Michael J.

2013-01-01

Learning and executive functions such as task-switching share common neural substrates, notably prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for…

Abnormal Functional Activation and Connectivity in the Working Memory Network in Early-Onset Schizophrenia

ERIC Educational Resources Information Center

Kyriakopoulos, Marinos; Dima, Danai; Roiser, Jonathan P.; Corrigall, Richard; Barker, Gareth J.; Frangou, Sophia

2012-01-01

Objective: Disruption within the working memory (WM) neural network is considered an integral feature of schizophrenia. The WM network, and the dorsolateral prefrontal cortex (DLPFC) in particular, undergo significant remodeling in late adolescence. Potential interactions between developmental changes in the WM network and disease-related…

Vicariously touching products through observing others' hand actions increases purchasing intention, and the effect of visual perspective in this process: An fMRI study.

PubMed

Liu, Yi; Zang, Xuelian; Chen, Lihan; Assumpção, Leonardo; Li, Hong

2018-01-01

The growth of online shopping increases consumers' dependence on vicarious sensory experiences, such as observing others touching products in commercials. However, empirical evidence on whether observing others' sensory experiences increases purchasing intention is still scarce. In the present study, participants observed others interacting with products in the first- or third-person perspective in video clips, and their neural responses were measured with functional magnetic resonance imaging (fMRI). We investigated (1) whether and how vicariously touching certain products affected purchasing intention, and the neural correlates of this process; and (2) how visual perspective interacts with vicarious tactility. Vicarious tactile experiences were manipulated by hand actions touching or not touching the products, while the visual perspective was manipulated by showing the hand actions either in first- or third-person perspective. During the fMRI scanning, participants watched the video clips and rated their purchasing intention for each product. The results showed that, observing others touching (vs. not touching) the products increased purchasing intention, with vicarious neural responses found in mirror neuron systems (MNS) and lateral occipital complex (LOC). Moreover, the stronger neural activities in MNS was associated with higher purchasing intention. The effects of visual perspectives were found in left superior parietal lobule (SPL), while the interaction of tactility and visual perspective was shown in precuneus and precuneus-LOC connectivity. The present study provides the first evidence that vicariously touching a given product increased purchasing intention and the neural activities in bilateral MNS, LOC, left SPL and precuneus are involved in this process. Hum Brain Mapp 39:332-343, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Social anhedonia is associated with neural abnormalities during face emotion processing.

PubMed

Germine, Laura T; Garrido, Lucia; Bruce, Lori; Hooker, Christine

2011-10-01

Human beings are social organisms with an intrinsic desire to seek and participate in social interactions. Social anhedonia is a personality trait characterized by a reduced desire for social affiliation and reduced pleasure derived from interpersonal interactions. Abnormally high levels of social anhedonia prospectively predict the development of schizophrenia and contribute to poorer outcomes for schizophrenia patients. Despite the strong association between social anhedonia and schizophrenia, the neural mechanisms that underlie individual differences in social anhedonia have not been studied and are thus poorly understood. Deficits in face emotion recognition are related to poorer social outcomes in schizophrenia, and it has been suggested that face emotion recognition deficits may be a behavioral marker for schizophrenia liability. In the current study, we used functional magnetic resonance imaging (fMRI) to see whether there are differences in the brain networks underlying basic face emotion processing in a community sample of individuals low vs. high in social anhedonia. We isolated the neural mechanisms related to face emotion processing by comparing face emotion discrimination with four other baseline conditions (identity discrimination of emotional faces, identity discrimination of neutral faces, object discrimination, and pattern discrimination). Results showed a group (high/low social anhedonia) × condition (emotion discrimination/control condition) interaction in the anterior portion of the rostral medial prefrontal cortex, right superior temporal gyrus, and left somatosensory cortex. As predicted, high (relative to low) social anhedonia participants showed less neural activity in face emotion processing regions during emotion discrimination as compared to each control condition. The findings suggest that social anhedonia is associated with abnormalities in networks responsible for basic processes associated with social cognition, and provide a starting point for understanding the neural basis of social motivation and our drive to seek social affiliation. Copyright © 2011 Elsevier Inc. All rights reserved.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

Extended Neural Metastability in an Embodied Model of Sensorimotor Coupling

PubMed Central

Aguilera, Miguel; Bedia, Manuel G.; Barandiaran, Xabier E.

2016-01-01

The hypothesis that brain organization is based on mechanisms of metastable synchronization in neural assemblies has been popularized during the last decades of neuroscientific research. Nevertheless, the role of body and environment for understanding the functioning of metastable assemblies is frequently dismissed. The main goal of this paper is to investigate the contribution of sensorimotor coupling to neural and behavioral metastability using a minimal computational model of plastic neural ensembles embedded in a robotic agent in a behavioral preference task. Our hypothesis is that, under some conditions, the metastability of the system is not restricted to the brain but extends to the system composed by the interaction of brain, body and environment. We test this idea, comparing an agent in continuous interaction with its environment in a task demanding behavioral flexibility with an equivalent model from the point of view of “internalist neuroscience.” A statistical characterization of our model and tools from information theory allow us to show how (1) the bidirectional coupling between agent and environment brings the system closer to a regime of criticality and triggers the emergence of additional metastable states which are not found in the brain in isolation but extended to the whole system of sensorimotor interaction, (2) the synaptic plasticity of the agent is fundamental to sustain open structures in the neural controller of the agent flexibly engaging and disengaging different behavioral patterns that sustain sensorimotor metastable states, and (3) these extended metastable states emerge when the agent generates an asymmetrical circular loop of causal interaction with its environment, in which the agent responds to variability of the environment at fast timescales while acting over the environment at slow timescales, suggesting the constitution of the agent as an autonomous entity actively modulating its sensorimotor coupling with the world. We conclude with a reflection about how our results contribute in a more general way to current progress in neuroscientific research. PMID:27721746

Extended Neural Metastability in an Embodied Model of Sensorimotor Coupling.

PubMed

Aguilera, Miguel; Bedia, Manuel G; Barandiaran, Xabier E

2016-01-01

The hypothesis that brain organization is based on mechanisms of metastable synchronization in neural assemblies has been popularized during the last decades of neuroscientific research. Nevertheless, the role of body and environment for understanding the functioning of metastable assemblies is frequently dismissed. The main goal of this paper is to investigate the contribution of sensorimotor coupling to neural and behavioral metastability using a minimal computational model of plastic neural ensembles embedded in a robotic agent in a behavioral preference task. Our hypothesis is that, under some conditions, the metastability of the system is not restricted to the brain but extends to the system composed by the interaction of brain, body and environment. We test this idea, comparing an agent in continuous interaction with its environment in a task demanding behavioral flexibility with an equivalent model from the point of view of "internalist neuroscience." A statistical characterization of our model and tools from information theory allow us to show how (1) the bidirectional coupling between agent and environment brings the system closer to a regime of criticality and triggers the emergence of additional metastable states which are not found in the brain in isolation but extended to the whole system of sensorimotor interaction, (2) the synaptic plasticity of the agent is fundamental to sustain open structures in the neural controller of the agent flexibly engaging and disengaging different behavioral patterns that sustain sensorimotor metastable states, and (3) these extended metastable states emerge when the agent generates an asymmetrical circular loop of causal interaction with its environment, in which the agent responds to variability of the environment at fast timescales while acting over the environment at slow timescales, suggesting the constitution of the agent as an autonomous entity actively modulating its sensorimotor coupling with the world. We conclude with a reflection about how our results contribute in a more general way to current progress in neuroscientific research.

Functional neural correlates of social approval in schizophrenia

PubMed Central

Lepage, Martin

2016-01-01

Social approval is a reward that uses abstract social reinforcers to guide interpersonal interactions. Few studies have specifically explored social reward processing and its related neural substrates in schizophrenia. Fifteen patients with schizophrenia and fifteen healthy controls participated in a two-part study to explore the functional neural correlates of social approval. In the first session, participants were led to believe their personality would be assessed based on their results from various questionnaires and an interview. Participants were then presented with the results of their supposed evaluation in the scanner, while engaging in a relevant fMRI social approval task. Subjects provided subjective reports of pleasure associated with receiving self-directed positive or negative feedback. Higher activation of the right parietal lobe was found in controls compared with individuals with schizophrenia. Both groups rated traits from the high social reward condition as more pleasurable than the low social reward condition, while intergroup differences emerged in the low social reward condition. Positive correlations were found in patients only between subjective ratings of positive feedback and right insula activation, and a relevant behavioural measure. Evidence suggests potential neural substrates underlying the cognitive representation of social reputation in schizophrenia. PMID:26516171

Quantification of intensity variations in functional MR images using rotated principal components

NASA Astrophysics Data System (ADS)

Backfrieder, W.; Baumgartner, R.; Sámal, M.; Moser, E.; Bergmann, H.

1996-08-01

In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.

Oxytocin attenuates neural reactivity to masked threat cues from the eyes.

PubMed

Kanat, Manuela; Heinrichs, Markus; Schwarzwald, Ralf; Domes, Gregor

2015-01-01

The neuropeptide oxytocin has recently been shown to modulate covert attention shifts to emotional face cues and to improve discrimination of masked facial emotions. These results suggest that oxytocin modulates facial emotion processing at early perceptual stages prior to full evaluation of the emotional expression. Here, we used functional magnetic resonance imaging to examine whether oxytocin alters neural responses to backwardly masked angry and happy faces while controlling for attention to the eye vs the mouth region. Intranasal oxytocin administration reduced amygdala reactivity to masked emotions when attending to salient facial features, ie, the eyes of angry faces and the mouth of happy faces. In addition, oxytocin decreased neural responses within the fusiform gyrus and brain stem areas, as well as functional coupling between the amygdala and the fusiform gyrus specifically for threat cues from the eyes. Effects of oxytocin on brain activity were not attributable to differences in behavioral performance, as oxytocin had no impact on mere emotion detection. Our results suggest that oxytocin attenuates neural correlates of early arousal by threat signals from the eye region. As reduced threat sensitivity may increase the likelihood of engaging in social interactions, our findings may have important implications for clinical states of social anxiety.

Neural differentiation promoted by truncated trkC receptors in collaboration with p75(NTR).

PubMed

Hapner, S J; Boeshore, K L; Large, T H; Lefcort, F

1998-09-01

trkC receptors, which serve critical functions during the development of the nervous system, are alternatively spliced to yield isoforms containing the catalytic tyrosine kinase domain (TK+) and truncated isoforms which lack this domain (TK-). To test for potential differences in their roles during early stages of neural development, TK+ and TK- isoforms were ectopically expressed in cultures of neural crest, the stem cell population that gives rise to the vast majority of the peripheral nervous system. NT-3 activation of ectopically expressed trkC TK+ receptors promoted both proliferation of neural crest cells and neuronal differentiation. Strikingly, the trkC TK- isoform was significantly more effective at promoting neuronal differentiation, but had no effect on proliferation. Furthermore, the trkC TK- response was dependent on a conserved receptor cytoplasmic domain and required the participation of the p75(NTR) neurotrophin receptor. Antibody-mediated receptor dimerization of TK+ receptors, but not TK- receptors, was sufficient to stimulate differentiation. These data identify a phenotypic response to activation of the trkC TK- receptor and demonstrate a functional interaction with p75(NTR), indicating there may be multiple trkC receptor-mediated systems guiding neuronal differentiation. Copyright 1998 Academic Press.

Dissociable neural correlates of contour completion and contour representation in illusory contour perception.

PubMed

Wu, Xiang; He, Sheng; Bushara, Khalaf; Zeng, Feiyan; Liu, Ying; Zhang, Daren

2012-10-01

Object recognition occurs even when environmental information is incomplete. Illusory contours (ICs), in which a contour is perceived though the contour edges are incomplete, have been extensively studied as an example of such a visual completion phenomenon. Despite the neural activity in response to ICs in visual cortical areas from low (V1 and V2) to high (LOC: the lateral occipital cortex) levels, the details of the neural processing underlying IC perception are largely not clarified. For example, how do the visual areas function in IC perception and how do they interact to archive the coherent contour perception? IC perception involves the process of completing the local discrete contour edges (contour completion) and the process of representing the global completed contour information (contour representation). Here, functional magnetic resonance imaging was used to dissociate contour completion and contour representation by varying each in opposite directions. The results show that the neural activity was stronger to stimuli with more contour completion than to stimuli with more contour representation in V1 and V2, which was the reverse of that in the LOC. When inspecting the neural activity change across the visual pathway, the activation remained high for the stimuli with more contour completion and increased for the stimuli with more contour representation. These results suggest distinct neural correlates of contour completion and contour representation, and the possible collaboration between the two processes during IC perception, indicating a neural connection between the discrete retinal input and the coherent visual percept. Copyright © 2011 Wiley Periodicals, Inc.

Bacterial Signaling to the Nervous System through Toxins and Metabolites.

PubMed

Yang, Nicole J; Chiu, Isaac M

2017-03-10

Mammalian hosts interface intimately with commensal and pathogenic bacteria. It is increasingly clear that molecular interactions between the nervous system and microbes contribute to health and disease. Both commensal and pathogenic bacteria are capable of producing molecules that act on neurons and affect essential aspects of host physiology. Here we highlight several classes of physiologically important molecular interactions that occur between bacteria and the nervous system. First, clostridial neurotoxins block neurotransmission to or from neurons by targeting the SNARE complex, causing the characteristic paralyses of botulism and tetanus during bacterial infection. Second, peripheral sensory neurons-olfactory chemosensory neurons and nociceptor sensory neurons-detect bacterial toxins, formyl peptides, and lipopolysaccharides through distinct molecular mechanisms to elicit smell and pain. Bacteria also damage the central nervous system through toxins that target the brain during infection. Finally, the gut microbiota produces molecules that act on enteric neurons to influence gastrointestinal motility, and metabolites that stimulate the "gut-brain axis" to alter neural circuits, autonomic function, and higher-order brain function and behavior. Furthering the mechanistic and molecular understanding of how bacteria affect the nervous system may uncover potential strategies for modulating neural function and treating neurological diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evolution of neuroarchitecture, multi-level analyses and calibrative reductionism

PubMed Central

Berntson, Gary G.; Norman, Greg J.; Hawkley, Louise C.; Cacioppo, John T.

2012-01-01

Evolution has sculpted the incredibly complex human nervous system, among the most complex functions of which extend beyond the individual to an intricate social structure. Although these functions are deterministic, those determinants are legion, heavily interacting and dependent on a specific evolutionary trajectory. That trajectory was directed by the adaptive significance of quasi-random genetic variations, but was also influenced by chance and caprice. With a different evolutionary pathway, the same neural elements could subserve functions distinctly different from what they do in extant human brains. Consequently, the properties of higher level neural networks cannot be derived readily from the properties of the lower level constituent elements, without studying these elements in the aggregate. Thus, a multi-level approach to integrative neuroscience may offer an optimal strategy. Moreover, the process of calibrative reductionism, by which concepts and understandings from one level of organization or analysis can mutually inform and ‘calibrate’ those from other levels (both higher and lower), may represent a viable approach to the application of reductionism in science. This is especially relevant in social neuroscience, where the basic subject matter of interest is defined by interacting organisms across diverse environments. PMID:23386961

Oligodendrocyte-Neuron Interactions: Impact on Myelination and Brain Function.

PubMed

Shimizu, Takeshi; Osanai, Yasuyuki; Ikenaka, Kazuhiro

2018-01-01

In the past, glial cells were considered to be 'glue' cells whose primary role was thought to be merely filling gaps in neural circuits. However, a growing number of reports have indicated the role of glial cells in higher brain function through their interaction with neurons. Myelin was originally thought to be just a sheath structure surrounding neuronal axons, but recently it has been shown that myelin exerts effects on the conduction velocity of neuronal axons even after myelin formation. Therefore, the investigation of glial cell properties and the neuron-glial interactions is important for understanding higher brain function. Moreover, since there are many neurological disorders caused by glial abnormalities, further understanding of glial cell-related diseases and the development of effective therapeutic strategies are warranted. In this review, we focused on oligodendrocyte-neuron interactions, with particular attention on (1) axonal signals underlying oligodendrocyte differentiation and myelination, (2) neuronal activity-dependent myelination and (3) the effects of myelination on higher brain function.

Triadic (ecological, neural, cognitive) niche construction: a scenario of human brain evolution extrapolating tool use and language from the control of reaching actions

PubMed Central

Iriki, Atsushi; Taoka, Miki

2012-01-01

Hominin evolution has involved a continuous process of addition of new kinds of cognitive capacity, including those relating to manufacture and use of tools and to the establishment of linguistic faculties. The dramatic expansion of the brain that accompanied additions of new functional areas would have supported such continuous evolution. Extended brain functions would have driven rapid and drastic changes in the hominin ecological niche, which in turn demanded further brain resources to adapt to it. In this way, humans have constructed a novel niche in each of the ecological, cognitive and neural domains, whose interactions accelerated their individual evolution through a process of triadic niche construction. Human higher cognitive activity can therefore be viewed holistically as one component in a terrestrial ecosystem. The brain's functional characteristics seem to play a key role in this triadic interaction. We advance a speculative argument about the origins of its neurobiological mechanisms, as an extension (with wider scope) of the evolutionary principles of adaptive function in the animal nervous system. The brain mechanisms that subserve tool use may bridge the gap between gesture and language—the site of such integration seems to be the parietal and extending opercular cortices. PMID:22106423

Triadic (ecological, neural, cognitive) niche construction: a scenario of human brain evolution extrapolating tool use and language from the control of reaching actions.

PubMed

Iriki, Atsushi; Taoka, Miki

2012-01-12

Hominin evolution has involved a continuous process of addition of new kinds of cognitive capacity, including those relating to manufacture and use of tools and to the establishment of linguistic faculties. The dramatic expansion of the brain that accompanied additions of new functional areas would have supported such continuous evolution. Extended brain functions would have driven rapid and drastic changes in the hominin ecological niche, which in turn demanded further brain resources to adapt to it. In this way, humans have constructed a novel niche in each of the ecological, cognitive and neural domains, whose interactions accelerated their individual evolution through a process of triadic niche construction. Human higher cognitive activity can therefore be viewed holistically as one component in a terrestrial ecosystem. The brain's functional characteristics seem to play a key role in this triadic interaction. We advance a speculative argument about the origins of its neurobiological mechanisms, as an extension (with wider scope) of the evolutionary principles of adaptive function in the animal nervous system. The brain mechanisms that subserve tool use may bridge the gap between gesture and language--the site of such integration seems to be the parietal and extending opercular cortices.

Development of human nervous tissue upon differentiation of embryonic stem cells in three-dimensional culture.

PubMed

Preynat-Seauve, Olivier; Suter, David M; Tirefort, Diderik; Turchi, Laurent; Virolle, Thierry; Chneiweiss, Herve; Foti, Michelangelo; Lobrinus, Johannes-Alexander; Stoppini, Luc; Feki, Anis; Dubois-Dauphin, Michel; Krause, Karl Heinz

2009-03-01

Researches on neural differentiation using embryonic stem cells (ESC) require analysis of neurogenesis in conditions mimicking physiological cellular interactions as closely as possible. In this study, we report an air-liquid interface-based culture of human ESC. This culture system allows three-dimensional cell expansion and neural differentiation in the absence of added growth factors. Over a 3-month period, a macroscopically visible, compact tissue developed. Histological coloration revealed a dense neural-like neural tissue including immature tubular structures. Electron microscopy, immunochemistry, and electrophysiological recordings demonstrated a dense network of neurons, astrocytes, and oligodendrocytes able to propagate signals. Within this tissue, tubular structures were niches of cells resembling germinal layers of human fetal brain. Indeed, the tissue contained abundant proliferating cells expressing markers of neural progenitors. Finally, the capacity to generate neural tissues on air-liquid interface differed for different ESC lines, confirming variations of their neurogenic potential. In conclusion, this study demonstrates in vitro engineering of a human neural-like tissue with an organization that bears resemblance to early developing brain. As opposed to previously described methods, this differentiation (a) allows three-dimensional organization, (b) yields dense interconnected neural tissue with structurally and functionally distinct areas, and (c) is spontaneously guided by endogenous developmental cues.

Individual Differences in Sentence Comprehension: A Functional Magnetic Resonance Imaging Investigation of Syntactic and Lexical Processing Demands

PubMed Central

Prat, Chantel S.; Keller, Timothy A.; Just, Marcel Adam

2008-01-01

Language comprehension is neurally underpinned by a network of collaborating cortical processing centers; individual differences in comprehension must be related to some set of this network’s properties. This study investigated the neural bases of individual differences during sentence comprehension by examining the network’s response to two variations in processing demands: reading sentences containing words of high versus low lexical frequency and having simpler versus more complex syntax. In a functional magnetic resonance imaging study, readers who were independently identified as having high or low working memory capacity for language exhibited three differentiating properties of their language network, namely, neural efficiency, adaptability, and synchronization. First, greater efficiency (defined as a reduction in activation associated with improved performance) was manifested as less activation in the bilateral middle frontal and right lingual gyri in high-capacity readers. Second, increased adaptability was indexed by larger lexical frequency effects in high-capacity readers across bilateral middle frontal, bilateral inferior occipital, and right temporal regions. Third, greater synchronization was observed in high-capacity readers between left temporal and left inferior frontal, left parietal, and right occipital regions. Synchronization interacted with adaptability, such that functional connectivity remained constant or increased with increasing lexical and syntactic demands in high-capacity readers, whereas low-capacity readers either showed no reliable differentiation or a decrease in functional connectivity with increasing demands. These results are among the first to relate multiple cortical network properties to individual differences in reading capacity and suggest a more general framework for understanding the relation between neural function and individual differences in cognitive performance. PMID:17892384

Multi-voxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

PubMed Central

Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.; Munhall, Kevin G.; Cusack, Rhodri; Johnsrude, Ingrid S.

2013-01-01

The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations within a multi-voxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was employed to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during vocalization, compared to during passive listening. One network of regions appears to encode an ‘error signal’ irrespective of acoustic features of the error: this network, including right angular gyrus, right supplementary motor area, and bilateral cerebellum, yielded consistent neural patterns across acoustically different, distorted feedback types, only during articulation (not during passive listening). In contrast, a fronto-temporal network appears sensitive to the speech features of auditory stimuli during passive listening; this preference for speech features was diminished when the same stimuli were presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Taken together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple, interactive, functionally differentiated neural systems. PMID:23467350

Individual differences in sentence comprehension: a functional magnetic resonance imaging investigation of syntactic and lexical processing demands.

PubMed

Prat, Chantel S; Keller, Timothy A; Just, Marcel Adam

2007-12-01

Language comprehension is neurally underpinned by a network of collaborating cortical processing centers; individual differences in comprehension must be related to some set of this network's properties. This study investigated the neural bases of individual differences during sentence comprehension by examining the network's response to two variations in processing demands: reading sentences containing words of high versus low lexical frequency and having simpler versus more complex syntax. In a functional magnetic resonance imaging study, readers who were independently identified as having high or low working memory capacity for language exhibited three differentiating properties of their language network, namely, neural efficiency, adaptability, and synchronization. First, greater efficiency (defined as a reduction in activation associated with improved performance) was manifested as less activation in the bilateral middle frontal and right lingual gyri in high-capacity readers. Second, increased adaptability was indexed by larger lexical frequency effects in high-capacity readers across bilateral middle frontal, bilateral inferior occipital, and right temporal regions. Third, greater synchronization was observed in high-capacity readers between left temporal and left inferior frontal, left parietal, and right occipital regions. Synchronization interacted with adaptability, such that functional connectivity remained constant or increased with increasing lexical and syntactic demands in high-capacity readers, whereas low-capacity readers either showed no reliable differentiation or a decrease in functional connectivity with increasing demands. These results are among the first to relate multiple cortical network properties to individual differences in reading capacity and suggest a more general framework for understanding the relation between neural function and individual differences in cognitive performance.

Spatial channel interactions in cochlear implants

NASA Astrophysics Data System (ADS)

Tang, Qing; Benítez, Raul; Zeng, Fan-Gang

2011-08-01

The modern multi-channel cochlear implant is widely considered to be the most successful neural prosthesis owing to its ability to restore partial hearing to post-lingually deafened adults and to allow essentially normal language development in pre-lingually deafened children. However, the implant performance varies greatly in individuals and is still limited in background noise, tonal language understanding, and music perception. One main cause for the individual variability and the limited performance in cochlear implants is spatial channel interaction from the stimulating electrodes to the auditory nerve and brain. Here we systematically examined spatial channel interactions at the physical, physiological, and perceptual levels in the same five modern cochlear implant subjects. The physical interaction was examined using an electric field imaging technique, which measured the voltage distribution as a function of the electrode position in the cochlea in response to the stimulation of a single electrode. The physiological interaction was examined by recording electrically evoked compound action potentials as a function of the electrode position in response to the stimulation of the same single electrode position. The perceptual interactions were characterized by changes in detection threshold as well as loudness summation in response to in-phase or out-of-phase dual-electrode stimulation. To minimize potentially confounding effects of temporal factors on spatial channel interactions, stimulus rates were limited to 100 Hz or less in all measurements. Several quantitative channel interaction indexes were developed to define and compare the width, slope and symmetry of the spatial excitation patterns derived from these physical, physiological and perceptual measures. The electric field imaging data revealed a broad but uniformly asymmetrical intracochlear electric field pattern, with the apical side producing a wider half-width and shallower slope than the basal side. In contrast, the evoked compound action potential and perceptual channel interaction data showed much greater individual variability. It is likely that actual reduction in neural and higher level interactions, instead of simple sharpening of the electric current field, would be the key to predicting and hopefully improving the variable cochlear implant performance. The present results are obtained with auditory prostheses but can be applied to other neural prostheses, in which independent spatial channels, rather than a high stimulation rate, are critical to their performance.

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.

Non-invasive neural stimulation

NASA Astrophysics Data System (ADS)

Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

2017-05-01

Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks.

PubMed

Shtark, Mark B; Kozlova, Lyudmila I; Bezmaternykh, Dmitriy D; Mel'nikov, Mikhail Ye; Savelov, Andrey A; Sokhadze, Estate M

2018-06-01

Neural networks interaction was studied in healthy men (20-35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI-EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as "successful" in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these "successful" trainees. The experimental group (N = 23 total, N = 13 "successful") upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 "successful") beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

Revealing networks from dynamics: an introduction

NASA Astrophysics Data System (ADS)

Timme, Marc; Casadiego, Jose

2014-08-01

What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity.

Preliminary investigation of the relationships between sleep duration, reward circuitry function, and mood dysregulation in youth offspring of parents with bipolar disorder.

PubMed

Soehner, Adriane M; Bertocci, Michele A; Manelis, Anna; Bebko, Genna; Ladouceur, Cecile D; Graur, Simona; Monk, Kelly; Bonar, Lisa K; Hickey, Mary Beth; Axelson, David; Goldstein, Benjamin I; Goldstein, Tina R; Birmaher, Boris; Phillips, Mary L

2016-11-15

Altered reward circuitry function is observed in individuals with bipolar disorder (BD) and their unaffected offspring (OBP). While OBP are at elevated risk for BD, modifiable risk factors that may exacerbate neural vulnerabilities in OBP remain under-characterized. As sleep loss is strongly linked to mania in BD, this study tested associations between sleep duration, reward circuitry function, and mood dysregulation in OBP. Two groups of youth unaffected with BD (9-17yr) completed a number-guessing fMRI reward paradigm: 25 OBP and 21 age-sex-IQ-matched offspring of control parents with non-BD psychopathology (OCP), to differentiate risk for BD from risk for psychopathology more broadly. Regressions tested effects of group status, self-reported past-week sleep duration, and their interaction on neural activity and bilateral ventral striatum (VS) functional connectivity to win>control. Correlations with parent-reported mood dysregulation were assessed. Group effects were observed for right posterior insula activity (OCP>OBP) and VS-left posterior insula connectivity (OBP>OCP). Group ⁎ sleep duration interactions were observed for left dorsal anterior-mid-cingulate (daMCC) activity and VS-left anterior insula/ventrolateral prefrontal cortex (VLPFC) connectivity. Specifically, sleep duration and daMCC activity were positively related in OBP, but negatively related in OCP and sleep duration and VS-left anterior insula/VLPFC connectivity were negatively related in OBP, but positively in OCP. Additionally, increased VS-left posterior insula connectivity and VS-left anterior insula/VLPFC connectivity were associated with greater mood dysregulation in OBP only. Cross-sectional design and small sample size. Altered reward-related VS-insula connectivity could represent a neural pathway underpinning mood dysregulation in OBP, and may be modulated by shortened sleep duration. Copyright © 2016 Elsevier B.V. All rights reserved.

Construction of a Piezoresistive Neural Sensor Array

NASA Technical Reports Server (NTRS)

Carlson, W. B.; Schulze, W. A.; Pilgrim, P. M.

1996-01-01

The construction of a piezoresistive - piezoelectric sensor (or actuator) array is proposed using 'neural' connectivity for signal recognition and possible actuation functions. A closer integration of the sensor and decision functions is necessary in order to achieve intrinsic identification within the sensor. A neural sensor is the next logical step in development of truly 'intelligent' arrays. This proposal will integrate 1-3 polymer piezoresistors and MLC electroceramic devices for applications involving acoustic identification. The 'intelligent' piezoresistor -piezoelectric system incorporates printed resistors, composite resistors, and a feedback for the resetting of resistances. A model of a design is proposed in order to simulate electromechanical resistor interactions. The goal of optimizing a sensor geometry for improving device reliability, training, & signal identification capabilities is the goal of this work. At present, studies predict performance of a 'smart' device with a significant control of 'effective' compliance over a narrow pressure range due to a piezoresistor percolation threshold. An interesting possibility may be to use an array of control elements to shift the threshold function in order to change the level of resistance in a neural sensor array for identification, or, actuation applications. The proposed design employs elements of: (1) conductor loaded polymers for a 'fast' RC time constant response; and (2) multilayer ceramics for actuation or sensing and shifting of resistance in the polymer. Other material possibilities also exist using magnetoresistive layered systems for shifting the resistance. It is proposed to use a neural net configuration to test and to help study the possible changes required in the materials design of these devices. Numerical design models utilize electromechanical elements, in conjunction with structural elements in order to simulate piezoresistively controlled actuators and changes in resistance of sensors. The construction of these devices may show significant improvement in ability to interrogate signals and in the control of effective compliance. This work focuses on the development a variety of series/parallel interconnected piezoresistive control elements for the neural sensing function.

Visualizing the spinal neuronal dynamics of locomotion

NASA Astrophysics Data System (ADS)

Subramanian, Kalpathi R.; Bashor, D. P.; Miller, M. T.; Foster, J. A.

2004-06-01

Modern imaging and simulation techniques have enhanced system-level understanding of neural function. In this article, we present an application of interactive visualization to understanding neuronal dynamics causing locomotion of a single hip joint, based on pattern generator output of the spinal cord. Our earlier work visualized cell-level responses of multiple neuronal populations. However, the spatial relationships were abstract, making communication with colleagues difficult. We propose two approaches to overcome this: (1) building a 3D anatomical model of the spinal cord with neurons distributed inside, animated by the simulation and (2) adding limb movements predicted by neuronal activity. The new system was tested using a cat walking central pattern generator driving a pair of opposed spinal motoneuron pools. Output of opposing motoneuron pools was combined into a single metric, called "Net Neural Drive", which generated angular limb movement in proportion to its magnitude. Net neural drive constitutes a new description of limb movement control. The combination of spatial and temporal information in the visualizations elegantly conveys the neural activity of the output elements (motoneurons), as well as the resulting movement. The new system encompasses five biological levels of organization from ion channels to observed behavior. The system is easily scalable, and provides an efficient interactive platform for rapid hypothesis testing.

Model of brain activation predicts the neural collective influence map of the brain

PubMed Central

Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.

2017-01-01

Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973

Quick fuzzy backpropagation algorithm.

PubMed

Nikov, A; Stoeva, S

2001-03-01

A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.

Motor cortical activity changes during neuroprosthetic-controlled object interaction.

PubMed

Downey, John E; Brane, Lucas; Gaunt, Robert A; Tyler-Kabara, Elizabeth C; Boninger, Michael L; Collinger, Jennifer L

2017-12-05

Brain-computer interface (BCI) controlled prosthetic arms are being developed to restore function to people with upper-limb paralysis. This work provides an opportunity to analyze human cortical activity during complex tasks. Previously we observed that BCI control became more difficult during interactions with objects, although we did not quantify the neural origins of this phenomena. Here, we investigated how motor cortical activity changed in the presence of an object independently of the kinematics that were being generated using intracortical recordings from two people with tetraplegia. After identifying a population-wide increase in neural firing rates that corresponded with the hand being near an object, we developed an online scaling feature in the BCI system that operated without knowledge of the task. Online scaling increased the ability of two subjects to control the robotic arm when reaching to grasp and transport objects. This work suggests that neural representations of the environment, in this case the presence of an object, are strongly and consistently represented in motor cortex but can be accounted for to improve BCI performance.

Neural modeling and functional neuroimaging.

PubMed

Horwitz, B; Sporns, O

1994-01-01

Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America. Copyright © 1994 Wiley-Liss, Inc.

Facing changes and changing faces in adolescence: a new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development.

PubMed

Scherf, K Suzanne; Behrmann, Marlene; Dahl, Ronald E

2012-04-01

Adolescence is a time of dramatic physical, cognitive, emotional, and social changes as well as a time for the development of many social-emotional problems. These characteristics raise compelling questions about accompanying neural changes that are unique to this period of development. Here, we propose that studying adolescent-specific changes in face processing and its underlying neural circuitry provides an ideal model for addressing these questions. We also use this model to formulate new hypotheses. Specifically, pubertal hormones are likely to increase motivation to master new peer-oriented developmental tasks, which will in turn, instigate the emergence of new social/affective components of face processing. We also predict that pubertal hormones have a fundamental impact on the re-organization of neural circuitry supporting face processing and propose, in particular, that, the functional connectivity, or temporal synchrony, between regions of the face-processing network will change with the emergence of these new components of face processing in adolescence. Finally, we show how this approach will help reveal why adolescence may be a period of vulnerability in brain development and suggest how it could lead to prevention and intervention strategies that facilitate more adaptive functional interactions between regions within the broader social information processing network. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cortical Neural Computation by Discrete Results Hypothesis

PubMed Central

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation. PMID:27807408

Cortical Neural Computation by Discrete Results Hypothesis.

PubMed

Castejon, Carlos; Nuñez, Angel

2016-01-01

One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.

Stimulation Mapping of Myelinated Tracts in Awake Patients

PubMed Central

Duffau, Hugues

2016-01-01

For a long time, although the functional anatomy of human cortex has extensively been studied, subcortical white matter tracts have received little consideration. Recent advances in tractography have opened the door to a non-invasive investigation of the subcortical fibers in vivo. However, this method cannot study directly the function of the bundles. Interestingly, for the first time in the history of cognitive neurosciences, direct axonal electrostimulation (DES) mapping of the neural pathways offers the unique opportunity to investigate the function of the connectomal anatomy. Indeed, this technique is able to perform real-time anatomo-functional correlations in awake patients who undergo brain surgery, especially at the level of the subcortical fibers. Here, the aim is to review original data issued from DES of myelinated tracts in adults, with regard to the functional connectivity mediating the sensorimotor, visuo-spatial, language, cognitive and emotional functions, as well as the interactions between these different sub-networks, leading ultimately to explore consciousness. Therefore, axonal stimulation is a valuable tool in the field of connectomics, that is, the map of neural connections, in order to switch from the traditional localizationist view of brain processing to a networking model in which cerebral functions are underpinned by the dynamic interactions of large-scale distributed and parallel sub-circuits. Such connectomal account should integrate the anatomic constraint represented by the subcortical fascicles. Indeed, post-lesional neuroplasticity is possible only on the condition that the white matter fibers are preserved, to allow communication and temporal synchronization among delocalized inter-connected networks. PMID:29765851

Characterizing the Anomalous Cognition-Emotion Interactions in Externalizing

PubMed Central

Baskin-Sommers, Arielle R.; Curtin, John J.; Larson, Christine L.; Stout, Daniel; Kiehl, Kent A.; Newman, Joseph P.

2012-01-01

Externalizing traits are characterized by exaggerated emotional (e.g., frustration, anger) and behavioral (e.g., drug seeking, reactive aggression) reactions to motivationally-significant stimuli. Explanations for this exaggerated reactivity emphasize attention, executive function, and affective processes, but the associations among these processes is rarely investigated. To examine these interactions, we measure fear potentiated startle (FPS; Experiment 1) and neural activation (Experiment 2) in an instructed fear paradigm that manipulates attentional focus, demands on executive functioning, and emotion. In both studies, exaggerated emotional reactivity associated with externalizing was specific to conditions that focused attention on threat information and placed minimal demands on executive functioning. Results suggest that a crucial cognition-emotion interaction affecting externalizing is the over-prioritization and over-allocation of attention to motivationally-significant information, which in turn, may impair executive and affective regulation. PMID:22579718

Decoding the representation of learned social roles in the human brain.

PubMed

Eger, Evelyn; Moretti, Laura; Dehaene, Stanislas; Sirigu, Angela

2013-10-01

Humans as social beings are profoundly affected by exclusion. Short experiences with people differing in their degree of prosocial behaviour can induce reliable preferences for including partners, but the neural mechanisms of this learning remain unclear. Here, we asked participants to play a short social interaction game based on "cyber-ball" where one fictive partner included and another excluded the subject, thus defining social roles (includer - "good", excluder - "bad"). We then used multivariate pattern recognition on high-resolution functional magnetic resonance imaging (fMRI) data acquired before and after this game to test whether neural responses to the partners' and neutral control faces during a perceptual task reflect their learned social valence. Support vector classification scores revealed a learning-related increase in neural discrimination of social status in anterior insula and anterior cingulate regions, which was mainly driven by includer faces becoming distinguishable from excluder and control faces. Thus, face-evoked responses in anterior insula and anterior cingulate cortex contain fine-grained information shaped by prior social interactions that allow for categorisation of faces according to their learned social status. These lasting traces of social experience in cortical areas important for emotional and social processing could provide a substrate of how social inclusion shapes future behaviour and promotes cooperative interactions between individuals. Copyright © 2013 Elsevier Ltd. All rights reserved.

Differences in neural activation between preterm and full term born adolescents on a sentence comprehension task: implications for educational accommodations.

PubMed

Barde, Laura H F; Yeatman, Jason D; Lee, Eliana S; Glover, Gary; Feldman, Heidi M

2012-02-15

Adolescent survivors of preterm birth experience persistent functional problems that negatively impact academic outcomes, even when standardized measures of cognition and language suggest normal ability. In this fMRI study, we compared the neural activation supporting auditory sentence comprehension in two groups of adolescents (ages 9-16 years); sentences varied in length and syntactic difficulty. Preterms (n=18, mean gestational age 28.8 weeks) and full terms (n=14) had scores on verbal IQ, receptive vocabulary, and receptive language tests that were within or above normal limits and similar between groups. In early and late phases of the trial, we found interactions by group and length; in the late phase, we also found a group by syntactic difficulty interaction. Post hoc tests revealed that preterms demonstrated significant activation in the left and right middle frontal gyri as syntactic difficulty increased. ANCOVA showed that the interactions could not be attributed to differences in age, receptive language skill, or reaction time. Results are consistent with the hypothesis that preterm birth modulates brain-behavior relations in sentence comprehension as task demands increase. We suggest preterms' differences in neural processing may indicate a need for educational accommodations, even when formal test scores indicate normal academic achievement. Copyright © 2011 Elsevier Ltd. All rights reserved.

Neural correlates of trust.

PubMed

Krueger, Frank; McCabe, Kevin; Moll, Jorge; Kriegeskorte, Nikolaus; Zahn, Roland; Strenziok, Maren; Heinecke, Armin; Grafman, Jordan

2007-12-11

Trust is a critical social process that helps us to cooperate with others and is present to some degree in all human interaction. However, the underlying brain mechanisms of conditional and unconditional trust in social reciprocal exchange are still obscure. Here, we used hyperfunctional magnetic resonance imaging, in which two strangers interacted online with one another in a sequential reciprocal trust game while their brains were simultaneously scanned. By designing a nonanonymous, alternating multiround game, trust became bidirectional, and we were able to quantify partnership building and maintenance. Using within- and between-brain analyses, an examination of functional brain activity supports the hypothesis that the preferential activation of different neuronal systems implements these two trust strategies. We show that the paracingulate cortex is critically involved in building a trust relationship by inferring another person's intentions to predict subsequent behavior. This more recently evolved brain region can be differently engaged to interact with more primitive neural systems in maintaining conditional and unconditional trust in a partnership. Conditional trust selectively activated the ventral tegmental area, a region linked to the evaluation of expected and realized reward, whereas unconditional trust selectively activated the septal area, a region linked to social attachment behavior. The interplay of these neural systems supports reciprocal exchange that operates beyond the immediate spheres of kinship, one of the distinguishing features of the human species.

Neural correlates of trust

PubMed Central

Krueger, Frank; McCabe, Kevin; Moll, Jorge; Kriegeskorte, Nikolaus; Zahn, Roland; Strenziok, Maren; Heinecke, Armin; Grafman, Jordan

2007-01-01

Trust is a critical social process that helps us to cooperate with others and is present to some degree in all human interaction. However, the underlying brain mechanisms of conditional and unconditional trust in social reciprocal exchange are still obscure. Here, we used hyperfunctional magnetic resonance imaging, in which two strangers interacted online with one another in a sequential reciprocal trust game while their brains were simultaneously scanned. By designing a nonanonymous, alternating multiround game, trust became bidirectional, and we were able to quantify partnership building and maintenance. Using within- and between-brain analyses, an examination of functional brain activity supports the hypothesis that the preferential activation of different neuronal systems implements these two trust strategies. We show that the paracingulate cortex is critically involved in building a trust relationship by inferring another person's intentions to predict subsequent behavior. This more recently evolved brain region can be differently engaged to interact with more primitive neural systems in maintaining conditional and unconditional trust in a partnership. Conditional trust selectively activated the ventral tegmental area, a region linked to the evaluation of expected and realized reward, whereas unconditional trust selectively activated the septal area, a region linked to social attachment behavior. The interplay of these neural systems supports reciprocal exchange that operates beyond the immediate spheres of kinship, one of the distinguishing features of the human species. PMID:18056800

Interactions between neural networks: a mechanism for tuning chaos and oscillations.

PubMed

Wang, Lipo

2007-06-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

Nanotools for Neuroscience and Brain Activity Mapping

PubMed Central

Alivisatos, A. Paul; Andrews, Anne M.; Boyden, Edward S.; Chun, Miyoung; Church, George M.; Deisseroth, Karl; Donoghue, John P.; Fraser, Scott E.; Lippincott-Schwartz, Jennifer; Looger, Loren L.; Masmanidis, Sotiris; McEuen, Paul L.; Nurmikko, Arto V.; Park, Hongkun; Peterka, Darcy S.; Reid, Clay; Roukes, Michael L.; Scherer, Axel; Schnitzer, Mark; Sejnowski, Terrence J.; Shepard, Kenneth L.; Tsao, Doris; Turrigiano, Gina; Weiss, Paul S.; Xu, Chris; Yuste, Rafael; Zhuang, Xiaowei

2013-01-01

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function. PMID:23514423

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

The neural bases of host plant selection in a Neuroecology framework.

PubMed

Reisenman, Carolina E; Riffell, Jeffrey A

2015-01-01

Understanding how animals make use of environmental information to guide behavior is a fundamental problem in the field of neuroscience. Similarly, the field of ecology seeks to understand the role of behavior in shaping interactions between organisms at various levels of organization, including population-, community- and even ecosystem-level scales. Together, the newly emerged field of "Neuroecology" seeks to unravel this fundamental question by studying both the function of neurons at many levels of the sensory pathway and the interactions between organisms and their natural environment. The interactions between herbivorous insects and their host plants are ideal examples of Neuroecology given the strong ecological and evolutionary forces and the underlying physiological and behavioral mechanisms that shaped these interactions. In this review we focus on an exemplary herbivorous insect within the Lepidoptera, the giant sphinx moth Manduca sexta, as much is known about the natural behaviors related to host plant selection and the involved neurons at several level of the sensory pathway. We also discuss how herbivore-induced plant odorants and secondary metabolites in floral nectar in turn can affect moth behavior, and the underlying neural mechanisms.

The Brain in its Body: Motor Control and Sensing in a Biomechanical Context

PubMed Central

Chiel, Hillel J.; Ting, Lena H.; Ekeberg, Orjan; Hartmann, Mitra J. Z.

2009-01-01

Although it is widely recognized that adaptive behavior emerges from the ongoing interactions among the nervous system, the body, and the environment, it has only become possible in recent years to experimentally study and to simulate these interacting systems. We briefly review work on molluscan feeding, maintenance of postural control in cats and humans, simulations of locomotion in lamprey, insect, cat and salamander, and active vibrissal sensing in rats to illustrate the insights that can be derived from studies of neural control and sensing within a biomechanical context. These studies illustrate that control may be shared between the nervous system and the periphery, that neural activity organizes degrees of freedom into biomechanically meaningful subsets, that mechanics alone may play crucial roles in enforcing gait patterns, and that mechanics of sensors is crucial for their function. PMID:19828793

Potential involvement of kinesin-1 in the regulation of subcellular localization of Girdin

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

Muramatsu, Aya; Enomoto, Atsushi, E-mail: enomoto@iar.nagoya-u.ac.jp; Kato, Takuya

Girdin is an actin-binding protein that has multiple functions in postnatal neural development and cancer progression. We previously showed that Girdin is a regulator of migration for neuroblasts born from neural stem cells in the subventricular zone (SVZ) and the dentate gyrus of the hippocampus in the postnatal brain. Despite a growing list of Girdin-interacting proteins, the mechanism of Girdin-mediated migration has not been fully elucidated. Girdin interacts with Disrupted-In-Schizophrenia 1 and partitioning-defective 3, both of which have been shown to interact with the kinesin microtubule motor proteins. Based on this, we have identified that Girdin also interacts with kinesin-1,more » a member of neuronal kinesin proteins. Although a direct interaction of Girdin and kinesin-1 has not been determined, it is of interest to find that Girdin loss-of-function mutant mice with the mutation of a basic amino acid residue-rich region (Basic mut mice) exhibit limited interaction with kinesin-1. Furthermore, expression of a kinesin-1 mutant with motor defects, leads to Girdin mislocalization. Finally, consistent with previous studies on the role of kinesin proteins in trafficking a cell–cell adhesion molecule N-cadherin, Basic mut mice showed an aberrant expression pattern of N-cadherin in migrating SVZ neuroblasts. These findings suggest a potential role of Girdin/kinesin-1 interaction in the regulation of neuroblast migration in the postnatal brain. - Highlights: • Girdin is a regulator of migration for neuroblasts in the postnatal brain. • Girdin interacts with kinesin-1, a member of neuronal kinesin proteins. • Girdin mutant mice showed an aberrant expression of N-cadherin in neuroblasts.« less

Multiple conserved cell adhesion protein interactions mediate neural wiring of a sensory circuit in C. elegans.

PubMed

Kim, Byunghyuk; Emmons, Scott W

2017-09-13

Nervous system function relies on precise synaptic connections. A number of widely-conserved cell adhesion proteins are implicated in cell recognition between synaptic partners, but how these proteins act as a group to specify a complex neural network is poorly understood. Taking advantage of known connectivity in C. elegans , we identified and studied cell adhesion genes expressed in three interacting neurons in the mating circuits of the adult male. Two interacting pairs of cell surface proteins independently promote fasciculation between sensory neuron HOA and its postsynaptic target interneuron AVG: BAM-2/neurexin-related in HOA binds to CASY-1/calsyntenin in AVG; SAX-7/L1CAM in sensory neuron PHC binds to RIG-6/contactin in AVG. A third, basal pathway results in considerable HOA-AVG fasciculation and synapse formation in the absence of the other two. The features of this multiplexed mechanism help to explain how complex connectivity is encoded and robustly established during nervous system development.

Neural control of circulation and exercise: a translational approach disclosing interactions between central command, arterial baroreflex, and muscle metaboreflex.

PubMed

Michelini, Lisete C; O'Leary, Donal S; Raven, Peter B; Nóbrega, Antonio C L

2015-08-01

The last 100 years witnessed a rapid and progressive development of the body of knowledge concerning the neural control of the cardiovascular system in health and disease. The understanding of the complexity and the relevance of the neuroregulatory system continues to evolve and as a result raises new questions. The purpose of this review is to articulate results from studies involving experimental models in animals as well as in humans concerning the interaction between the neural mechanisms mediating the hemodynamic responses during exercise. The review describes the arterial baroreflex, the pivotal mechanism controlling mean arterial blood pressure and its fluctuations along with the two main activation mechanisms to exercise: central command (parallel activation of central somatomotor and autonomic descending pathways) and the muscle metaboreflex, the metabolic component of exercise pressor reflex (feedback from ergoreceptors within contracting skeletal muscles). In addition, the role of the cardiopulmonary baroreceptors in modulating the resetting of arterial baroreflex is identified, and the mechanisms in the central nervous system involved with the resetting of baroreflex function during dynamic exercise are also described. Approaching a very relevant clinical condition, the review also presents the concept that the impaired arterial baroreflex function is an integral component of the metaboreflex-mediated exaggerated sympathetic tone in subjects with heart failure. This increased sympathetic activity has a major role in causing the depressed ventricular function observed during submaximal dynamic exercise in these patients. The potential contribution of a metaboreflex arising from respiratory muscles is also considered. Copyright © 2015 the American Physiological Society.

Structural covariance mapping delineates medial and medio-lateral temporal networks in déjà vu.

PubMed

Shaw, Daniel Joel; Mareček, Radek; Brázdil, Milan

2016-12-01

Déjà vu (DV) is an eerie phenomenon experienced frequently as an aura of temporal lobe epilepsy, but also reported commonly by healthy individuals. The former pathological manifestation appears to result from aberrant neural activity among brain structures within the medial temporal lobes. Recent studies also implicate medial temporal brain structures in the non-pathological experience of DV, but as one element of a diffuse neuroanatomical correlate; it remains to be seen if neural activity among the medial temporal lobes also underlies this benign manifestation. The present study set out to investigate this. Due to its unpredictable and infrequent occurrence, however, non-pathological DV does not lend itself easily to functional neuroimaging. Instead, we draw on research showing that brain structure covaries among regions that interact frequently as nodes of functional networks. Specifically, we assessed whether grey-matter covariance among structures implicated in non-pathological DV differs according to the frequency with which the phenomenon is experienced. This revealed two diverging patterns of structural covariation: Among the first, comprised primarily of medial temporal structures and the caudate, grey-matter volume becomes more positively correlated with higher frequency of DV experience. The second pattern encompasses medial and lateral temporal structures, among which greater DV frequency is associated with more negatively correlated grey matter. Using a meta-analytic method of co-activation mapping, we demonstrate a higher probability of functional interactions among brain structures constituting the former pattern, particularly during memory-related processes. Our findings suggest that altered neural signalling within memory-related medial temporal brain structures underlies both pathological and non-pathological DV.

Chronic multiunit recordings in behaving animals: advantages and limitations.

PubMed

Supèr, Hans; Roelfsema, Pieter R

2005-01-01

By simultaneous recording from neural responses at many different loci at the same time, we can understand the interaction between neurons, and thereby gain insight into the network properties of neural processing, instead of the functioning of individual neurons. Here we will discuss a method for recording in behaving animals that uses chronically implanted micro-electrodes that allow one to track neural responses over a long period of time. In a majority of cases, multiunit activity, which is the aggregate spiking activity of a number of neurons in the vicinity of an electrode tip, is recorded through these electrodes, and occasionally single neurons can be isolated. Here we compare the properties of multiunit responses to the responses of single neurons in the primary visual cortex. We also discuss the advantages and disadvantages of the multiunit signal as opposed to a signal of single neurons. We demonstrate that multiunit recording provides a reliable and useful technique in cases where the neurons at the electrodes have similar response properties. Multiunit recording is therefore especially valuable when task variables have an effect that is consistent across the population of neurons. In the primary visual cortex, this is the case for figure-ground segregation and visual attention. Multiunit recording also has clear advantages for cross-correlation analysis. We show that the cross-correlation function between multiunit signals gives a reliable estimate of the average single-unit cross-correlation function. By the use of multiunit recording, it becomes much easier to detect relatively weak interactions between neurons at different cortical locations.

Neural control of circulation and exercise: a translational approach disclosing interactions between central command, arterial baroreflex, and muscle metaboreflex

PubMed Central

Michelini, Lisete C.; O'Leary, Donal S.; Raven, Peter B.

2015-01-01

The last 100 years witnessed a rapid and progressive development of the body of knowledge concerning the neural control of the cardiovascular system in health and disease. The understanding of the complexity and the relevance of the neuroregulatory system continues to evolve and as a result raises new questions. The purpose of this review is to articulate results from studies involving experimental models in animals as well as in humans concerning the interaction between the neural mechanisms mediating the hemodynamic responses during exercise. The review describes the arterial baroreflex, the pivotal mechanism controlling mean arterial blood pressure and its fluctuations along with the two main activation mechanisms to exercise: central command (parallel activation of central somatomotor and autonomic descending pathways) and the muscle metaboreflex, the metabolic component of exercise pressor reflex (feedback from ergoreceptors within contracting skeletal muscles). In addition, the role of the cardiopulmonary baroreceptors in modulating the resetting of arterial baroreflex is identified, and the mechanisms in the central nervous system involved with the resetting of baroreflex function during dynamic exercise are also described. Approaching a very relevant clinical condition, the review also presents the concept that the impaired arterial baroreflex function is an integral component of the metaboreflex-mediated exaggerated sympathetic tone in subjects with heart failure. This increased sympathetic activity has a major role in causing the depressed ventricular function observed during submaximal dynamic exercise in these patients. The potential contribution of a metaboreflex arising from respiratory muscles is also considered. PMID:26024683

Dietary Proteins as Determinants of Metabolic and Physiologic Functions of the Gastrointestinal Tract

PubMed Central

Jahan-Mihan, Alireza; Luhovyy, Bohdan L.; Khoury, Dalia El; Anderson, G. Harvey

2011-01-01

Dietary proteins elicit a wide range of nutritional and biological functions. Beyond their nutritional role as the source of amino acids for protein synthesis, they are instrumental in the regulation of food intake, glucose and lipid metabolism, blood pressure, bone metabolism and immune function. The interaction of dietary proteins and their products of digestion with the regulatory functions of the gastrointestinal (GI) tract plays a dominant role in determining the physiological properties of proteins. The site of interaction is widespread, from the oral cavity to the colon. The characteristics of proteins that influence their interaction with the GI tract in a source-dependent manner include their physico-chemical properties, their amino acid composition and sequence, their bioactive peptides, their digestion kinetics and also the non-protein bioactive components conjugated with them. Within the GI tract, these products affect several regulatory functions by interacting with receptors releasing hormones, affecting stomach emptying and GI transport and absorption, transmitting neural signals to the brain, and modifying the microflora. This review discusses the interaction of dietary proteins during digestion and absorption with the physiological and metabolic functions of the GI tract, and illustrates the importance of this interaction in the regulation of amino acid, glucose, lipid metabolism, and food intake. PMID:22254112

Artistic explorations of the brain

PubMed Central

Fetz, Eberhard E.

2012-01-01

The symbiotic relationships between art and the brain begin with the obvious fact that brain mechanisms underlie the creation and appreciation of art. Conversely, many spectacular images of neural structures have remarkable aesthetic appeal. But beyond its fascinating forms, the many functions performed by brain mechanisms provide a profound subject for aesthetic exploration. Complex interactions in the tangled neural networks in our brain miraculously generate coherent behavior and cognition. Neuroscientists tackle these phenomena with specialized methodologies that limit the scope of exposition and are comprehensible to an initiated minority. Artists can perform an end run around these limitations by representing the brain's remarkable functions in a manner that can communicate to a wide and receptive audience. This paper explores the ways that brain mechanisms can provide a largely untapped subject for artistic exploration. PMID:22347178

Cognition, emotion, and attention.

PubMed

Müller-Oehring, Eva M; Schulte, Tilman

2014-01-01

Deficits of attention, emotion, and cognition occur in individuals with alcohol abuse and addiction. This review elucidates the concepts of attention, emotion, and cognition and references research on the underlying neural networks and their compromise in alcohol use disorder. Neuroimaging research on adolescents with family history of alcoholism contributes to the understanding of pre-existing brain structural conditions and characterization of cognition and attention processes in high-risk individuals. Attention and cognition interact with other brain functions, including perceptual selection, salience, emotion, reward, and memory, through interconnected neural networks. Recent research reports compromised microstructural and functional network connectivity in alcoholism, which can have an effect on the dynamic tuning between brain systems, e.g., the frontally based executive control system, the limbic emotion system, and the midbrain-striatal reward system, thereby impeding cognitive flexibility and behavioral adaptation to changing environments. Finally, we introduce concepts of functional compensation, the capacity to generate attentional resources for performance enhancement, and brain structure recovery with abstinence. An understanding of the neural mechanisms of attention, emotion, and cognition will likely provide the basis for better treatment strategies for developing skills that enhance alcoholism therapy adherence and quality of life, and reduce the propensity for relapse. © 2014 Elsevier B.V. All rights reserved.

Emotional reactivity and its impact on neural circuitry for attention-emotion interaction in childhood and adolescence

PubMed Central

Perlman, Susan B.; Hein, Tyler C.; Stepp, Stephanie D.

2013-01-01

Attention modulation when confronted with emotional stimuli is considered a critical aspect of executive function, yet rarely studied during childhood and adolescence, a developmental period marked with changes in these processes. We employed a novel, and child-friendly fMRI task that used emotional faces to investigate the neural underpinnings of the attention-emotion interaction in a child and adolescent sample (n=23, Age m=13.46, sd=2.86, range=8.05–16.93 years). Results implied modulation of activation in the orbitofrontal cortex (OFC) due to emotional distractor valence, which marginally correlated with participant age. Additionally, parent-reported emotional reactivity predicted the trajectory of BOLD signal increase for fearful emotional face distractors such that participants low in emotional reactivity had a steeper latency to peak activation. Results imply that the use of the OFC to modulate attention in the face of social/emotional stimuli may mature with age and may be tightly coupled with adaptive emotional functioning. Findings are discussed in the context of risk for the development of psychiatric disorders, where increased emotional reactivity is particularly apparent. PMID:24055416

Post-learning hippocampal dynamics promote preferential retention of rewarding events

PubMed Central

Gruber, Matthias J.; Ritchey, Maureen; Wang, Shao-Fang; Doss, Manoj K.; Ranganath, Charan

2016-01-01

Reward motivation is known to modulate memory encoding, and this effect depends on interactions between the substantia nigra/ ventral tegmental area complex (SN/VTA) and the hippocampus. It is unknown, however, whether these interactions influence offline neural activity in the human brain that is thought to promote memory consolidation. Here, we used functional magnetic resonance imaging (fMRI) to test the effect of reward motivation on post-learning neural dynamics and subsequent memory for objects that were learned in high- or low-reward motivation contexts. We found that post-learning increases in resting-state functional connectivity between the SN/VTA and hippocampus predicted preferential retention of objects that were learned in high-reward contexts. In addition, multivariate pattern classification revealed that hippocampal representations of high-reward contexts were preferentially reactivated during post-learning rest, and the number of hippocampal reactivations was predictive of preferential retention of items learned in high-reward contexts. These findings indicate that reward motivation alters offline post-learning dynamics between the SN/VTA and hippocampus, providing novel evidence for a potential mechanism by which reward could influence memory consolidation. PMID:26875624

The relationship between spatial configuration and functional connectivity of brain regions

PubMed Central

Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C

2018-01-01

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used ‘functional connectivity fingerprints’ to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. PMID:29451491

Interactions between neural networks: a mechanism for tuning chaos and oscillations

PubMed Central

2007-01-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability. PMID:19003511

Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture

PubMed Central

Ferguson, Michael A.; Anderson, Jeffrey S.; Spreng, R. Nathan

2017-01-01

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

Neuroendocrine circuits governing energy balance and stress regulation: functional overlap and therapeutic implications

PubMed Central

Ulrich-Lai, Yvonne M.; Ryan, Karen K.

2014-01-01

Significant co-morbidities between obesity-related metabolic disease and stress-related psychological disorders suggest important functional interactions between energy balance and brain stress integration. Largely overlapping neural circuits control these systems, and this anatomical arrangement optimizes opportunities for mutual influence. Here we first review the current literature identifying effects of metabolic neuroendocrine signals on stress regulation, and vice versa. Next, the contributions of reward driven food intake to these metabolic and stress interactions are discussed. Lastly, we consider the inter-relationships among metabolism, stress and reward in light of their important implications in the development of therapies for metabolism- or stress-related disease. PMID:24630812

The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

PubMed Central

Deco, Gustavo; Jirsa, Viktor K.; Robinson, Peter A.; Breakspear, Michael; Friston, Karl

2008-01-01

The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space–time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalogram (MEG). Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences. PMID:18769680

Neural Correlates of Hostile Jokes: Cognitive and Motivational Processes in Humor Appreciation

PubMed Central

Chan, Yu-Chen; Liao, Yi-Jun; Tu, Cheng-Hao

2016-01-01

Hostile jokes (HJs) provide aggressive catharsis and a feeling of superiority. Behavioral research has found that HJs are perceived as funnier than non-hostile jokes (NJs). The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing HJs, NJs, and their corresponding hostile sentences (HSs) and non-hostile sentences (NSs). HJs primarily showed activation in the dorsomedial prefrontal cortex (dmPFC) and midbrain compared with the corresponding hostile baseline. Conversely, NJs primarily revealed activation in the ventromedial PFC (vmPFC), amygdala, midbrain, ventral anterior cingulate cortex, and nucleus accumbens (NAcc) compared with the corresponding non-hostile baseline. These results support the critical role of the medial PFC (mPFC) for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of HJs showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of NJs displayed increased activation in the vmPFC, which suggested social-affective engagement. HJs versus NJs primarily showed increased activation in the dmPFC and midbrain, whereas NJs versus HJs primarily displayed greater activation in the amygdala and midbrain. The psychophysiological interaction (PPI) analysis demonstrated functional coupling of the dmPFC–dlPFC and midbrain–dmPFC for HJs and functional coupling of the vmPFC–midbrain and amygdala–midbrain–NAcc for NJs. Surprisingly, HJs were not perceived as funnier than NJs. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation based on the psychoanalytic and superiority theories of humor. PMID:27840604

Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats

PubMed Central

Deolindo, Camila S.; Kunicki, Ana C. B.; da Silva, Maria I.; Lima Brasil, Fabrício; Moioli, Renan C.

2018-01-01

Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits—neuronal assemblies (NAs)—and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior. PMID:29375324

Neural Correlates of Hostile Jokes: Cognitive and Motivational Processes in Humor Appreciation.

PubMed

Chan, Yu-Chen; Liao, Yi-Jun; Tu, Cheng-Hao; Chen, Hsueh-Chih

2016-01-01

Hostile jokes (HJs) provide aggressive catharsis and a feeling of superiority. Behavioral research has found that HJs are perceived as funnier than non-hostile jokes (NJs). The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing HJs, NJs, and their corresponding hostile sentences (HSs) and non-hostile sentences (NSs). HJs primarily showed activation in the dorsomedial prefrontal cortex (dmPFC) and midbrain compared with the corresponding hostile baseline. Conversely, NJs primarily revealed activation in the ventromedial PFC (vmPFC), amygdala, midbrain, ventral anterior cingulate cortex, and nucleus accumbens (NAcc) compared with the corresponding non-hostile baseline. These results support the critical role of the medial PFC (mPFC) for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of HJs showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of NJs displayed increased activation in the vmPFC, which suggested social-affective engagement. HJs versus NJs primarily showed increased activation in the dmPFC and midbrain, whereas NJs versus HJs primarily displayed greater activation in the amygdala and midbrain. The psychophysiological interaction (PPI) analysis demonstrated functional coupling of the dmPFC-dlPFC and midbrain-dmPFC for HJs and functional coupling of the vmPFC-midbrain and amygdala-midbrain-NAcc for NJs. Surprisingly, HJs were not perceived as funnier than NJs. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation based on the psychoanalytic and superiority theories of humor.

Interaction of notochord-derived fibrinogen-like protein with Notch regulates the patterning of the central nervous system of Ciona intestinalis embryos.

PubMed

Yamada, Shigehiro; Hotta, Kohji; Yamamoto, Takamasa S; Ueno, Naoto; Satoh, Nori; Takahashi, Hiroki

2009-04-01

The midline organ the notochord and its overlying dorsal neural tube are the most prominent features of the chordate body plan. Although the molecular mechanisms involved in the formation of the central nervous system (CNS) have been studied extensively in vertebrate embryos, none of the genes that are expressed exclusively in notochord cells has been shown to function in this process. Here, we report a gene in the urochordate Ciona intestinalis encoding a fibrinogen-like protein that plays a pivotal role in the notochord-dependent positioning of neuronal cells. While this gene (Ci-fibrn) is expressed exclusively in notochord cells, its protein product is not confined to these cells but is distributed underneath the CNS as fibril-like protrusions. We demonstrated that Ci-fibrn interacts physically and functionally with Ci-Notch that is expressed in the central nervous system, and that the correct distribution of Ci-fibrn protein is dependent on Notch signaling. Disturbance of the Ci-fibrn distribution caused an abnormal positioning of neuronal cells and an abnormal track of axon extension. Therefore, it is highly likely that the interaction between the notochord-based fibrinogen-like protein and the neural tube-based Notch signaling plays an essential role in the proper patterning of CNS.

Proto-experiences and subjective experiences: classical and quantum concepts.

PubMed

Vimal, Ram Lakhan Pandey

2008-03-01

Deterministic reductive monism and non-reductive substance dualism are two opposite views for consciousness, and both have serious problems. An alternative view is needed. For this, we hypothesize that strings or elementary particles (fermions and bosons) have two aspects: (i) elemental proto-experiences (PEs) as phenomenal aspect, and (ii) mass, charge, and spin as material aspect. Elemental PEs are hypothesized to be the properties of elementary particles and their interactions, which are composed of irreducible fundamental subjective experiences (SEs)/PEs that are in superimposed form in elementary particles and in their interactions. Since SEs/PEs are superimposed, elementary particles are not specific to any SE/PE; they (and all inert matter) are carriers of SEs/PEs, and hence, appear as non-experiential material entities. Furthermore, our hypothesis is that matter and associated elemental PEs co-evolved and co-developed into neural-nets and associated neural-net PEs (neural Darminism), respectively. The signals related to neural PEs interact in a neural-net and neural-net PEs emerges from random process of self-organization. The neural-net PEs are a set of SEs embedded in the neural-net by a non-computational or non-algorithmic process. The non-specificity of elementary particles is transformed into the specificity of neural-nets by neural Darwinism. The specificity of SEs emerges when feedforward and feedback signal interacts in the neuropil and are dependent on wakefulness (i.e., activation) attention, re-entry between neural populations, working memory, stimulus at above threshold, and neural net PE signals. This PE-SE framework integrates reductive and non-reductive views, complements the existing models, bridges the explanatory gaps, and minimizes the problem of causation.

Altered Synchronizations among Neural Networks in Geriatric Depression

PubMed Central

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G.; Steffens, David C.

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression. PMID:26180795

Altered Synchronizations among Neural Networks in Geriatric Depression.

PubMed

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

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

Intrahemispheric white matter asymmetries: the missing link between brain structure and functional lateralization?

PubMed

Ocklenburg, Sebastian; Friedrich, Patrick; Güntürkün, Onur; Genç, Erhan

2016-07-01

Hemispheric asymmetries are a central principle of nervous system architecture and shape the functional organization of most cognitive systems. Structural gray matter asymmetries and callosal interactions have been identified as contributing neural factors but always fell short to constitute a full explanans. Meanwhile, recent advances in in vivo white matter tractography have unrevealed the asymmetrical organization of many intrahemispheric white matter pathways, which might serve as the missing link to explain the substrate of functional lateralization. By taking into account callosal interactions, gray matter asymmetries and asymmetrical interhemispheric pathways, we opt for a new triadic model that has the potential to explain many observations which cannot be elucidated within the current frameworks of lateralized cognition.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments.

PubMed

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments

NASA Astrophysics Data System (ADS)

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Differential reward network functional connectivity in cannabis dependent and non-dependent users☆

PubMed Central

Filbey, Francesca M.; Dunlop, Joseph

2015-01-01

Background Emergent studies show that similar to other substances of abuse, cue-reactivity to cannabis is also associated with neural response in the brain’s reward pathway (Filbey et al., 2009). However, the inter-relatedness of brain regions during cue-reactivity in cannabis users remains unknown. Methods In this study, we conducted a series of investigations to determine functional connectivity during cue-reactivity in 71 cannabis users. First, we used psychophysiological interaction (PPI) analysis to examine coherent neural response to cannabis cues. Second, we evaluated whether these patterns of network functional connectivity differentiated dependent and non-dependent users. Finally, as an exploratory analysis, we determined the directionality of these connections via Granger connectivity analyses. Results PPI analyses showed reward network functional connectivity with the nucleus accumbens (NAc) seed region during cue exposure. Between-group contrasts found differential effects of dependence status. Dependent users (N = 31) had greater functional connectivity with amygdala and anterior cingulate gyrus (ACG) seeds while the non-dependent users (N = 24) had greater functional connectivity with the NAc, orbitofrontal cortex (OFC) and hippocampus seeds. Granger analyses showed that hippocampal and ACG activation preceded neural response in reward areas. Conclusions Both PPI and Granger analyses demonstrated strong functional coherence in reward regions during exposure to cannabis cues in current cannabis users. Functional connectivity (but not regional activation) in the reward network differentiated dependent from non-dependent cannabis users. Our findings suggest that repeated cannabis exposure causes observable changes in functional connectivity in the reward network and should be considered in intervention strategies. PMID:24838032

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

PubMed

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

Epigenetic Principles and Mechanisms Underlying Nervous System Functions in Health and Disease

PubMed Central

Mehler, Mark F.

2009-01-01

Epigenetics and epigenomic medicine encompass a new science of brain and behavior that are already providing unique insights into the mechanisms underlying brain development, evolution, neuronal and network plasticity and homeostasis, senescence, the etiology of diverse neurological diseases and neural regenerative processes. Epigenetic mechanisms include DNA methylation, histone modifications, nucleosome repositioning, higher-order chromatin remodeling, non-coding RNAs, and RNA and DNA editing. RNA is centrally involved in directing these processes, implying that the transcriptional state of the cell is the primary determinant of epigenetic memory. This transcriptional state can be modified by internal and external cues affecting gene expression and post-transcriptional processing, but also by RNA and DNA editing through activity-dependent intracellular transport and modulation of RNAs and RNA regulatory supercomplexes, and through trans-neuronal and systemic trafficking of functional RNA subclasses. These integrated processes promote dynamic reorganization of nuclear architecture and the genomic landscape to modulate functional gene and neural networks with complex temporal and spatial trajectories. Epigenetics represents the long sought after molecular interface mediating gene-environmental interactions during critical periods throughout the lifecycle. The discipline of environmental epigenomics has begun to identify combinatorial profiles of environmental stressors modulating the latency, initiation and progression of specific neurological disorders, and more selective disease biomarkers and graded molecular responses to emerging therapeutic interventions. Pharmacoepigenomic therapies will promote accelerated recovery of impaired and seemingly irrevocably lost cognitive, behavioral, sensorimotor functions through epigenetic reprogramming of endogenous regional neural stem cell fate decisions, targeted tissue remodeling and restoration of neural network integrity, plasticity and connectivity. PMID:18940229

Cognitive Training for Impaired Neural Systems in Neuropsychiatric Illness

PubMed Central

Vinogradov, Sophia; Fisher, Melissa; de Villers-Sidani, Etienne

2012-01-01

Neuropsychiatric illnesses are associated with dysfunction in distributed prefrontal neural systems that underlie perception, cognition, social interactions, emotion regulation, and motivation. The high degree of learning-dependent plasticity in these networks—combined with the availability of advanced computerized technology—suggests that we should be able to engineer very specific training programs that drive meaningful and enduring improvements in impaired neural systems relevant to neuropsychiatric illness. However, cognitive training approaches for mental and addictive disorders must take into account possible inherent limitations in the underlying brain ‘learning machinery' due to pathophysiology, must grapple with the presence of complex overlearned maladaptive patterns of neural functioning, and must find a way to ally with developmental and psychosocial factors that influence response to illness and to treatment. In this review, we briefly examine the current state of knowledge from studies of cognitive remediation in psychiatry and we highlight open questions. We then present a systems neuroscience rationale for successful cognitive training for neuropsychiatric illnesses, one that emphasizes the distributed nature of neural assemblies that support cognitive and affective processing, as well as their plasticity. It is based on the notion that, during successful learning, the brain represents the relevant perceptual and cognitive/affective inputs and action outputs with disproportionately larger and more coordinated populations of neurons that are distributed (and that are interacting) across multiple levels of processing and throughout multiple brain regions. This approach allows us to address limitations found in earlier research and to introduce important principles for the design and evaluation of the next generation of cognitive training for impaired neural systems. We summarize work to date using such neuroscience-informed methods and indicate some of the exciting future directions of this field. PMID:22048465

Neural Correlates of Impaired Reward-Effort Integration in Remitted Bulimia Nervosa.

PubMed

Mueller, Stefanie Verena; Morishima, Yosuke; Schwab, Simon; Wiest, Roland; Federspiel, Andrea; Hasler, Gregor

2018-03-01

The integration of reward magnitudes and effort costs is required for an effective behavioral guidance. This reward-effort integration was reported to be dependent on dopaminergic neurotransmission. As bulimia nervosa has been associated with a dysregulated dopamine system and catecholamine depletion led to reward-processing deficits in remitted bulimia nervosa, the purpose of this study was to identify the role of catecholamine dysfunction and its relation to behavioral and neural reward-effort integration in bulimia nervosa. To investigate the interaction between catecholamine functioning and behavioral, and neural responses directly, 17 remitted bulimic (rBN) and 21 healthy individuals (HC) received alpha-methyl-paratyrosine (AMPT) over 24 h to achieve catecholamine depletion in a randomized, crossover study design. We used functional magnetic resonance imaging (fMRI) and the monetary incentive delay (MID) task to assess reward-effort integration in relation to catecholaminergic neurotransmission at the behavioral and neural level. AMPT reduced the ability to integrate rewards and efforts effectively in HC participants. In contrast, in rBN participants, the reduced reward-effort integration was associated with illness duration in the sham condition and unrelated to catecholamine depletion. Regarding neural activation, AMPT decreased the reward anticipation-related neural activation in the anteroventral striatum. This decrease was associated with the AMPT-induced reduction of monetary earning in HC in contrast to rBN participants. Our findings contributed to the theory of a desensitized dopaminergic system in bulimia nervosa. A disrupted processing of reward magnitudes and effort costs might increase the probability of maintenance of bulimic symptoms.

Capturing the temporal evolution of choice across prefrontal cortex

PubMed Central

Hunt, Laurence T; Behrens, Timothy EJ; Hosokawa, Takayuki; Wallis, Jonathan D; Kennerley, Steven W

2015-01-01

Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making. DOI: http://dx.doi.org/10.7554/eLife.11945.001 PMID:26653139

Neural systems analysis of decision making during goal-directed navigation.

PubMed

Penner, Marsha R; Mizumori, Sheri J Y

2012-01-01

The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors. Copyright © 2011. Published by Elsevier Ltd.

Predicting wettability behavior of fluorosilica coated metal surface using optimum neural network

NASA Astrophysics Data System (ADS)

Taghipour-Gorjikolaie, Mehran; Valipour Motlagh, Naser

2018-02-01

The interaction between variables, which are effective on the surface wettability, is very complex to predict the contact angles and sliding angles of liquid drops. In this paper, in order to solve this complexity, artificial neural network was used to develop reliable models for predicting the angles of liquid drops. Experimental data are divided into training data and testing data. By using training data and feed forward structure for the neural network and using particle swarm optimization for training the neural network based models, the optimum models were developed. The obtained results showed that regression index for the proposed models for the contact angles and sliding angles are 0.9874 and 0.9920, respectively. As it can be seen, these values are close to unit and it means the reliable performance of the models. Also, it can be inferred from the results that the proposed model have more reliable performance than multi-layer perceptron and radial basis function based models.

Playing Music for a Smarter Ear: Cognitive, Perceptual and Neurobiological Evidence

PubMed Central

Strait, Dana; Kraus, Nina

2012-01-01

Human hearing depends on a combination of cognitive and sensory processes that function by means of an interactive circuitry of bottom-up and top-down neural pathways, extending from the cochlea to the cortex and back again. Given that similar neural pathways are recruited to process sounds related to both music and language, it is not surprising that the auditory expertise gained over years of consistent music practice fine-tunes the human auditory system in a comprehensive fashion, strengthening neurobiological and cognitive underpinnings of both music and speech processing. In this review we argue not only that common neural mechanisms for speech and music exist, but that experience in music leads to enhancements in sensory and cognitive contributors to speech processing. Of specific interest is the potential for music training to bolster neural mechanisms that undergird language-related skills, such as reading and hearing speech in background noise, which are critical to academic progress, emotional health, and vocational success. PMID:22993456

Tone-deafness – a new disconnection syndrome?

PubMed Central

Loui, Psyche; Alsop, David; Schlaug, Gottfried

2009-01-01

Communicating with one’s environment requires efficient neural interaction between action and perception. Neural substrates ofsound perception and production are connected by the arcuate fasciculus (AF). While AF is known to be involved in language, its roles in non-linguistic functions are unexplored. Here we show that tone-deaf people, with impaired sound perception and production, have reduced AF connectivity. Diffusion tensor tractography and psychophysics were assessed in tone-deaf individuals and matched controls. Abnormally-reduced AF connectivity was observed in the tone-deaf. Furthermore, we observed relationships between AF and auditory-motor behavior: superior and inferior AF branches predict psychophysically-assessed pitch-discrimination and sound production-perception abilities respectively. This neural abnormality suggests that tone-deafness leads to a reduction in connectivity resulting in pitch-related impairments. Results support a dual-stream anatomy of sound production and perception implicated in vocal communications. By identifying white-matter differences and their psychophysical correlates, results contribute to our understanding of how neural connectivity subserves behavior. PMID:19692596

Closed Loop Interactions between Spiking Neural Network and Robotic Simulators Based on MUSIC and ROS.

PubMed

Weidel, Philipp; Djurfeldt, Mikael; Duarte, Renato C; Morrison, Abigail

2016-01-01

In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning.

Closed Loop Interactions between Spiking Neural Network and Robotic Simulators Based on MUSIC and ROS

PubMed Central

Weidel, Philipp; Djurfeldt, Mikael; Duarte, Renato C.; Morrison, Abigail

2016-01-01

In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning. PMID:27536234

Linear summation of outputs in a balanced network model of motor cortex.

PubMed

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

Mindful attention reduces neural and self-reported cue-induced craving in smokers

PubMed Central

Creswell, John David; Tabibnia, Golnaz; Julson, Erica; Kober, Hedy; Tindle, Hilary A.

2013-01-01

An emerging body of research suggests that mindfulness-based interventions may be beneficial for smoking cessation and the treatment of other addictive disorders. One way that mindfulness may facilitate smoking cessation is through the reduction of craving to smoking cues. The present work considers whether mindful attention can reduce self-reported and neural markers of cue-induced craving in treatment seeking smokers. Forty-seven (n = 47) meditation-naïve treatment-seeking smokers (12-h abstinent from smoking) viewed and made ratings of smoking and neutral images while undergoing functional magnetic resonance imaging (fMRI). Participants were trained and instructed to view these images passively or with mindful attention. Results indicated that mindful attention reduced self-reported craving to smoking images, and reduced neural activity in a craving-related region of subgenual anterior cingulate cortex (sgACC). Moreover, a psychophysiological interaction analysis revealed that mindful attention reduced functional connectivity between sgACC and other craving-related regions compared to passively viewing smoking images, suggesting that mindfulness may decouple craving neurocircuitry when viewing smoking cues. These results provide an initial indication that mindful attention may describe a ‘bottom-up’ attention to one’s present moment experience in ways that can help reduce subjective and neural reactivity to smoking cues in smokers. PMID:22114078

The scaffold protein Nde1 safeguards the brain genome during S phase of early neural progenitor differentiation

PubMed Central

Houlihan, Shauna L; Feng, Yuanyi

2014-01-01

Successfully completing the S phase of each cell cycle ensures genome integrity. Impediment of DNA replication can lead to DNA damage and genomic disorders. In this study, we show a novel function for NDE1, whose mutations cause brain developmental disorders, in safeguarding the genome through S phase during early steps of neural progenitor fate restrictive differentiation. Nde1 mutant neural progenitors showed catastrophic DNA double strand breaks concurrent with the DNA replication. This evoked DNA damage responses, led to the activation of p53-dependent apoptosis, and resulted in the reduction of neurons in cortical layer II/III. We discovered a nuclear pool of Nde1, identified the interaction of Nde1 with cohesin and its associated chromatin remodeler, and showed that stalled DNA replication in Nde1 mutants specifically occurred in mid-late S phase at heterochromatin domains. These findings suggest that NDE1-mediated heterochromatin replication is indispensible for neuronal differentiation, and that the loss of NDE1 function may lead to genomic neurological disorders. DOI: http://dx.doi.org/10.7554/eLife.03297.001 PMID:25245017

Motivational Impact of Palatable Food Correlates With Functional Brain Responses to Food Images in Adolescents.

PubMed

Jensen, Chad D; Duraccio, Kara M; Carbine, Kaylie A; Barnett, Kimberly A; Kirwan, C Brock

2017-06-01

To examine associations between motivational impact of palatable foods and neural activity in brain regions involved in inhibitory control among adolescents. Thirty-four adolescents aged 14-20 years underwent functional magnetic resonance imaging while viewing images of high- and low-energy foods. Participants completed the Power of Food Scale (PFS). Whole-brain analyses of variance tested for neural activation differences and correlations between brain activation and PFS scores were tested. We found an interaction between food type (high energy vs. low energy) and PFS scores in the right dorsolateral prefrontal cortex and right inferior parietal lobule. We also found that PFS scores correlated negatively with activation to high-energy foods in prefrontal cortical and parietal regions. These findings suggest that individuals with high motivation for high-energy foods also demonstrate lower neural activation in inhibition-related brain regions when viewing images of high-energy foods, indicating that they may have difficulty inhibiting consumption impulses. © The Author 2016. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Neural correlates of naturalistic social cognition: brain-behavior relationships in healthy adults

PubMed Central

Rademacher, L.M.; Winkler, L.; Schultz, R.T.; Gründer, G.; Lammertz, S.E.

2016-01-01

Being able to infer the thoughts, feelings and intentions of those around us is indispensable in order to function in a social world. Despite growing interest in social cognition and its neural underpinnings, the factors that contribute to successful mental state attribution remain unclear. Current knowledge is limited because the most widely used tasks suffer from two main constraints: (i) They fail to capture individual variability due to ceiling effects and (ii) they use highly simplistic, often artificial stimuli inapt to mirror real-world socio-cognitive demands. In the present study, we address these problems by employing complex depictions of naturalistic social interactions that vary in both valence (positive vs negative) and ambiguity (high vs low). Thirty-eight healthy participants (20 female) made mental state judgments while brain responses were obtained using functional magnetic resonance imaging (fMRI). Accuracy varied based on valence and ambiguity conditions and women were more accurate than men with highly ambiguous social stimuli. Activity of the orbitofrontal cortex predicted performance in the high ambiguity condition. The results shed light on subtle differences in mentalizing abilities and associated neural activity. PMID:27496338

Computing the Social Brain Connectome Across Systems and States.

PubMed

Alcalá-López, Daniel; Smallwood, Jonathan; Jefferies, Elizabeth; Van Overwalle, Frank; Vogeley, Kai; Mars, Rogier B; Turetsky, Bruce I; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B; Bzdok, Danilo

2017-05-18

Social skills probably emerge from the interaction between different neural processing levels. However, social neuroscience is fragmented into highly specialized, rarely cross-referenced topics. The present study attempts a systematic reconciliation by deriving a social brain definition from neural activity meta-analyses on social-cognitive capacities. The social brain was characterized by meta-analytic connectivity modeling evaluating coactivation in task-focused brain states and physiological fluctuations evaluating correlations in task-free brain states. Network clustering proposed a functional segregation into (1) lower sensory, (2) limbic, (3) intermediate, and (4) high associative neural circuits that together mediate various social phenomena. Functional profiling suggested that no brain region or network is exclusively devoted to social processes. Finally, nodes of the putative mirror-neuron system were coherently cross-connected during tasks and more tightly coupled to embodied simulation systems rather than abstract emulation systems. These first steps may help reintegrate the specialized research agendas in the social and affective sciences. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Theory of correlation in a network with synaptic depression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Oizumi, Masafumi; Okada, Masato

2012-01-01

Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

2016-11-14

In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

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

PubMed

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

2012-01-01

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

The Neural Representations Underlying Human Episodic Memory.

PubMed

Xue, Gui

2018-06-01

A fundamental question of human episodic memory concerns the cognitive and neural representations and processes that give rise to the neural signals of memory. By integrating behavioral tests, formal computational models, and neural measures of brain activity patterns, recent studies suggest that memory signals not only depend on the neural processes and representations during encoding and retrieval, but also on the interaction between encoding and retrieval (e.g., transfer-appropriate processing), as well as on the interaction between the tested events and all other events in the episodic memory space (e.g., global matching). In addition, memory signals are also influenced by the compatibility of the event with the existing long-term knowledge (e.g., schema matching). These studies highlight the interactive nature of human episodic memory. Copyright © 2018 Elsevier Ltd. All rights reserved.

Gender Differences in the Cognitive Control of Emotion: An fMRI Study

ERIC Educational Resources Information Center

Koch, Kathrin; Pauly, Katharina; Kellermann, Thilo; Seiferth, Nina Y.; Reske, Martina; Backes, Volker; Stocker, Tony; Shah, N. Jon; Amunts, Katrin; Kircher, Tilo; Schneider, Frank; Habel, Ute

2007-01-01

The interaction of emotion and cognition has become a topic of major interest. However, the influence of gender on the interplay between the two processes, along with its neural correlates have not been fully analysed so far. In this functional magnetic resonance imaging (fMRI) study we induced negative emotion using negative olfactory stimulation…

The Somatic Appraisal Model of Affect: Paradigm for Educational Neuroscience and Neuropedagogy

ERIC Educational Resources Information Center

Patten, Kathryn E.

2011-01-01

This chapter presents emotion as a function of brain-body interaction, as a vital part of a multi-tiered phylogenetic set of neural mechanisms, evoked by both instinctive processes and learned appraisal systems, and argues to establish the primacy of emotion in relation to cognition. Primarily based on Damasio's somatic marker hypothesis, but also…

An evolutionary recent neuroepithelial cell adhesion function of huntingtin implicates ADAM10-Ncadherin.

PubMed

Lo Sardo, Valentina; Zuccato, Chiara; Gaudenzi, Germano; Vitali, Barbara; Ramos, Catarina; Tartari, Marzia; Myre, Michael A; Walker, James A; Pistocchi, Anna; Conti, Luciano; Valenza, Marta; Drung, Binia; Schmidt, Boris; Gusella, James; Zeitlin, Scott; Cotelli, Franco; Cattaneo, Elena

2012-05-01

The Huntington's disease gene product, huntingtin, is indispensable for neural tube formation, but its role is obscure. We studied neurulation in htt-null embryonic stem cells and htt-morpholino zebrafish embryos and found a previously unknown, evolutionarily recent function for this ancient protein. We found that htt was essential for homotypic interactions between neuroepithelial cells; it permitted neurulation and rosette formation by regulating metalloprotease ADAM10 activity and Ncadherin cleavage. This function was embedded in the N terminus of htt and was phenocopied by treatment of htt knockdown zebrafish with an ADAM10 inhibitor. Notably, in htt-null cells, reversion of the rosetteless phenotype occurred only with expression of evolutionarily recent htt heterologues from deuterostome organisms. Conversely, all of the heterologues that we tested, including htt from Drosophila melanogaster and Dictyostelium discoideum, exhibited anti-apoptotic activity. Thus, anti-apoptosis may have been one of htt’s ancestral function(s), but, in deuterostomes, htt evolved to acquire a unique regulatory activity for controlling neural adhesion via ADAM10-Ncadherin, with implications for brain evolution and development.

Neural activity during emotion recognition after combined cognitive plus social cognitive training in schizophrenia.

PubMed

Hooker, Christine I; Bruce, Lori; Fisher, Melissa; Verosky, Sara C; Miyakawa, Asako; Vinogradov, Sophia

2012-08-01

Cognitive remediation training has been shown to improve both cognitive and social cognitive deficits in people with schizophrenia, but the mechanisms that support this behavioral improvement are largely unknown. One hypothesis is that intensive behavioral training in cognition and/or social cognition restores the underlying neural mechanisms that support targeted skills. However, there is little research on the neural effects of cognitive remediation training. This study investigated whether a 50 h (10-week) remediation intervention which included both cognitive and social cognitive training would influence neural function in regions that support social cognition. Twenty-two stable, outpatient schizophrenia participants were randomized to a treatment condition consisting of auditory-based cognitive training (AT) [Brain Fitness Program/auditory module ~60 min/day] plus social cognition training (SCT) which was focused on emotion recognition [~5-15 min per day] or a placebo condition of non-specific computer games (CG) for an equal amount of time. Pre and post intervention assessments included an fMRI task of positive and negative facial emotion recognition, and standard behavioral assessments of cognition, emotion processing, and functional outcome. There were no significant intervention-related improvements in general cognition or functional outcome. fMRI results showed the predicted group-by-time interaction. Specifically, in comparison to CG, AT+SCT participants had a greater pre-to-post intervention increase in postcentral gyrus activity during emotion recognition of both positive and negative emotions. Furthermore, among all participants, the increase in postcentral gyrus activity predicted behavioral improvement on a standardized test of emotion processing (MSCEIT: Perceiving Emotions). Results indicate that combined cognition and social cognition training impacts neural mechanisms that support social cognition skills. Copyright © 2012 Elsevier B.V. All rights reserved.

Neural activity during emotion recognition after combined cognitive plus social-cognitive training in schizophrenia

PubMed Central

Hooker, Christine I.; Bruce, Lori; Fisher, Melissa; Verosky, Sara C.; Miyakawa, Asako; Vinogradov, Sophia

2012-01-01

Cognitive remediation training has been shown to improve both cognitive and social-cognitive deficits in people with schizophrenia, but the mechanisms that support this behavioral improvement are largely unknown. One hypothesis is that intensive behavioral training in cognition and/or social-cognition restores the underlying neural mechanisms that support targeted skills. However, there is little research on the neural effects of cognitive remediation training. This study investigated whether a 50 hour (10-week) remediation intervention which included both cognitive and social-cognitive training would influence neural function in regions that support social-cognition. Twenty-two stable, outpatient schizophrenia participants were randomized to a treatment condition consisting of auditory-based cognitive training (AT) [Brain Fitness Program/auditory module ~60 minutes/day] plus social-cognition training (SCT) which was focused on emotion recognition [~5–15 minutes per day] or a placebo condition of non-specific computer games (CG) for an equal amount of time. Pre and post intervention assessments included an fMRI task of positive and negative facial emotion recognition, and standard behavioral assessments of cognition, emotion processing, and functional outcome. There were no significant intervention-related improvements in general cognition or functional outcome. FMRI results showed the predicted group-by-time interaction. Specifically, in comparison to CG, AT+SCT participants had a greater pre-to-post intervention increase in postcentral gyrus activity during emotion recognition of both positive and negative emotions. Furthermore, among all participants, the increase in postcentral gyrus activity predicted behavioral improvement on a standardized test of emotion processing (MSCEIT: Perceiving Emotions). Results indicate that combined cognition and social-cognition training impacts neural mechanisms that support social-cognition skills. PMID:22695257

Abnormal relationships between the neural response to high- and low-calorie foods and endogenous acylated ghrelin in women with active and weight-recovered anorexia nervosa

PubMed Central

Holsen, Laura M.; Lawson, Elizabeth A.; Christensen, Kara; Klibanski, Anne; Goldstein, Jill M.

2014-01-01

Evidence contributing to the understanding of neurobiological mechanisms underlying appetite dysregulation in anorexia nervosa draws heavily on separate lines of research into neuroendocrine and neural circuitry functioning. In particular, studies consistently cite elevated ghrelin and abnormal activation patterns in homeostatic (hypothalamus) and hedonic (striatum, amygdala, insula) regions governing appetite. The current preliminary study examined the interaction of these systems, based on research demonstrating associations between circulating ghrelin levels and activity in these regions in healthy individuals. In a cross-sectional design, we studied 13 women with active anorexia nervosa (AN), 9 women weight-recovered from AN (AN-WR), and 12 healthy-weight control women using a food cue functional magnetic resonance imaging paradigm, with assessment of fasting levels of acylated ghrelin. Healthy-weight control women exhibited significant positive associations between fasting acylated ghrelin and activity in the right amygdala, hippocampus, insula, and orbitofrontal cortex in response to high-calorie foods, associations which were absent in the AN and AN-WR groups. Women with AN-WR demonstrated a negative relationship between ghrelin and activity in the left hippocampus in response to high-calorie foods, while women with AN showed a positive association between ghrelin and activity in the right orbitofrontal cortex in response to low-calorie foods. Findings suggest a breakdown in the interaction between ghrelin signaling and neural activity in relation to reward responsivity in AN, a phenomenon that may be further characterized using pharmacogenetic studies. PMID:24862390

A neural model of valuation and information virality

PubMed Central

Baek, Elisa C.; O’Donnell, Matthew Brook; Kim, Hyun Suk; Cappella, Joseph N.

2017-01-01

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds. PMID:28242678

Disrupted intrinsic and remote functional connectivity in heterotopia-related epilepsy.

PubMed

Liu, W; Hu, X; An, D; Gong, Q; Zhou, D

2018-01-01

Several neuroimaging studies have examined neural interactions in patients with periventricular nodular heterotopia (PNH). However, features of the underlying functional network remain poorly understood. In this study, we examined alterations in the local (regional) and remote (interregional) cerebral networks in this disorder. Twenty-eight subjects all having suffered from PNH with epilepsy, as well as 28 age- and sex- matched healthy controls, were enrolled in this study. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were calculated to detect regional neural function and functional network integration, respectively. Compared with healthy controls, patients with PNH-related epilepsy showed decreased ALFF in the ventromedial prefrontal cortex (vmPFC) and precuneus areas. ALFF values in both areas were negative correlated with epilepsy duration (P < .05, Bonferroni-corrected). Furthermore, patients with PNH-related epilepsy had increased remote interregional FC mainly in bilateral prefrontal and parietal cortices, supramarginal gyrus, dorsal cingulate gyrus, and right insula; lower FC was found in posterior brain regions including bilateral parahippocampal gyrus and inferior temporal gyrus. Focal spontaneous hypofunction, as assessed by ALFF, correlates with epilepsy duration in patients with PNH-related epilepsy. Abnormalities existed both within the default-mode network and then across the whole brain, demonstrating that intrinsic brain dysfunction may be related to specific network interactions. Our findings provide novel understanding of the connectivity-based pathophysiological mechanisms of PNH. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identifying autism from neural representations of social interactions: neurocognitive markers of autism.

PubMed

Just, Marcel Adam; Cherkassky, Vladimir L; Buchweitz, Augusto; Keller, Timothy A; Mitchell, Tom M

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought's underlying brain activation patterns.

Identifying Autism from Neural Representations of Social Interactions: Neurocognitive Markers of Autism

PubMed Central

Just, Marcel Adam; Cherkassky, Vladimir L.; Buchweitz, Augusto; Keller, Timothy A.; Mitchell, Tom M.

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought’s underlying brain activation patterns. PMID:25461818

Rivalry of homeostatic and sensory-evoked emotions: Dehydration attenuates olfactory disgust and its neural correlates.

PubMed

Meier, Lea; Friedrich, Hergen; Federspiel, Andrea; Jann, Kay; Morishima, Yosuke; Landis, Basile Nicolas; Wiest, Roland; Strik, Werner; Dierks, Thomas

2015-07-01

Neural correlates have been described for emotions evoked by states of homeostatic imbalance (e.g. thirst, hunger, and breathlessness) and for emotions induced by external sensory stimulation (such as fear and disgust). However, the neurobiological mechanisms of their interaction, when they are experienced simultaneously, are still unknown. We investigated the interaction on the neurobiological and the perceptional level using subjective ratings, serum parameters, and functional magnetic resonance imaging (fMRI) in a situation of emotional rivalry, when both a homeostatic and a sensory-evoked emotion were experienced at the same time. Twenty highly dehydrated male subjects rated a disgusting odor as significantly less repulsive when they were thirsty. On the neurobiological level, we found that this reduction in subjective disgust during thirst was accompanied by a significantly reduced neural activity in the insular cortex, a brain area known to be considerably involved in processing of disgust. Furthermore, during the experience of disgust in the satiated condition, we observed a significant functional connectivity between brain areas responding to the disgusting odor, which was absent during the stimulation in the thirsty condition. These results suggest interference of conflicting emotions: an acute homeostatic imbalance can attenuate the experience of another emotion evoked by the sensory perception of a potentially harmful external agent. This finding offers novel insights with regard to the behavioral relevance of biologically different types of emotions, indicating that some types of emotions are more imperative for behavior than others. As a general principle, this modulatory effect during the conflict of homeostatic and sensory-evoked emotions may function to safeguard survival. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural correlates for perception of companion animal photographs.

PubMed

Hayama, Sara; Chang, Linda; Gumus, Kazim; King, George R; Ernst, Thomas

2016-05-01

Anthrozoological neuroscience, which we propose as the use of neuroscience techniques to study human-animal interaction, may help to elucidate mechanisms underlying the associated psychological, physiological, and other purported health effects. This preliminary study investigates the neural response to animal photographs in pet owners and non-pet owners, and both attraction and attachment to companion animals as modulators of human perception of companion animal photographs. Thirty male participants, 15 "Pet Owners" (PO) and 15 "Non-Pet Owners" (NPO), viewed photographs of companion animals during functional MRI (fMRI) scans at 3 T and provided ratings of attraction to the animal species represented in the photographs. Fourteen subjects additionally submitted and viewed personal pet photographs during fMRI scans, and completed the Lexington Attachment to Pets Scale (LAPS). PO exhibited greater activation than NPO during the viewing of animal photographs in areas of the insula, and frontal and occipital cortices. Moreover, ratings of attraction to animals correlated positively with neural activation in the cingulate gyrus, precentral gyrus, inferior parietal lobule, and superior temporal gyrus during the viewing of representative photographs. For subjects with household pets, scores on the LAPS correlated positively with neural activation during the viewing of owned pet photographs in the precuneus, cuneus, and superior parietal lobule. Our preliminary findings suggest that human perception of companion animals involve the visual attention network, which may be modulated at the neural level by subjective experiences of attraction or attachment to animals. Our understanding of human-animal interactions through anthrozoological neuroscience may better direct therapeutic applications, such as animal-assisted therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

On cortical coding of vocal communication sounds in primates

NASA Astrophysics Data System (ADS)

Wang, Xiaoqin

2000-10-01

Understanding how the brain processes vocal communication sounds is one of the most challenging problems in neuroscience. Our understanding of how the cortex accomplishes this unique task should greatly facilitate our understanding of cortical mechanisms in general. Perception of species-specific communication sounds is an important aspect of the auditory behavior of many animal species and is crucial for their social interactions, reproductive success, and survival. The principles of neural representations of these behaviorally important sounds in the cerebral cortex have direct implications for the neural mechanisms underlying human speech perception. Our progress in this area has been relatively slow, compared with our understanding of other auditory functions such as echolocation and sound localization. This article discusses previous and current studies in this field, with emphasis on nonhuman primates, and proposes a conceptual platform to further our exploration of this frontier. It is argued that the prerequisite condition for understanding cortical mechanisms underlying communication sound perception and production is an appropriate animal model. Three issues are central to this work: (i) neural encoding of statistical structure of communication sounds, (ii) the role of behavioral relevance in shaping cortical representations, and (iii) sensory-motor interactions between vocal production and perception systems.

Neuronal Nitric Oxide Synthase and NADPH Oxidase Interact to Affect Cognitive, Affective, and Social Behaviors in Mice

PubMed Central

Walton, James C.; Selvakumar, Balakrishnan; Weil, Zachary M.; Snyder, Solomon H.; Nelson, Randy J.

2013-01-01

Both nitric oxide (NO) and reactive oxygen species (ROS) generated by nNOS and NADPH oxidase (NOX), respectively, in the brain have been implicated in an array of behaviors ranging from learning and memory to social interactions. Although recent work has elucidated how these separate redox pathways regulate neural function and behavior, the interaction of these two pathways in the regulation of neural function and behavior remains unspecified. Toward this end, the p47phox subunit of NOX, and nNOS were deleted to generate double knockout mice that were used to characterize the behavioral outcomes of concurrent impairment of the NO and ROS pathways in the brain. Mice were tested in a battery of behavioral tasks to evaluate learning and memory, as well as social, affective, and cognitive behaviors. p47phox deletion did not affect depressive-like behavior, whereas nNOS deletion abolished it. Both p47phox and nNOS deletion singly reduced anxiety-like behavior, increased general locomotor activity, impaired spatial learning and memory, and impaired preference for social novelty. Deletion of both genes concurrently had synergistic effects to elevate locomotor activity, impair spatial learning and memory, and disrupt prepulse inhibition of acoustic startle. Although preference for social novelty was impaired in single knockouts, double knockout mice displayed elevated levels of preference for social novelty above that of wild type littermates. These data demonstrate that, depending upon modality, deletion of p47phox and nNOS genes have dissimilar, similar, or additive effects. The current findings provide evidence that the NOX and nNOS redox signaling cascades interact in the brain to affect both cognitive function and social behavior. PMID:23948215

NIRS-Based Hyperscanning Reveals Inter-brain Neural Synchronization during Cooperative Jenga Game with Face-to-Face Communication.

PubMed

Liu, Ning; Mok, Charis; Witt, Emily E; Pradhan, Anjali H; Chen, Jingyuan E; Reiss, Allan L

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying social cognition. In particular, fNIRS permits simultaneous measurement of hemodynamic activity in two or more individuals interacting in a naturalistic setting. Here, we used fNIRS hyperscanning to study social cognition and communication in human dyads engaged in cooperative and obstructive interaction while they played the game of Jenga™. Novel methods were developed to identify synchronized channels for each dyad and a structural node-based spatial registration approach was utilized for inter-dyad analyses. Strong inter-brain neural synchrony (INS) was observed in the posterior region of the right middle and superior frontal gyrus, in particular Brodmann area 8 (BA8), during cooperative and obstructive interaction. This synchrony was not observed during the parallel game play condition and the dialog section, suggesting that BA8 was involved in goal-oriented social interaction such as complex interactive movements and social decision-making. INS was also observed in the dorsomedial prefrontal cortex (dmPFC), in particular Brodmann 9, during cooperative interaction only. These additional findings suggest that BA9 may be particularly engaged when theory-of-mind (ToM) is required for cooperative social interaction. The new methods described here have the potential to significantly extend fNIRS applications to social cognitive research.

The two-brain approach: how can mutually interacting brains teach us something about social interaction?

PubMed Central

Konvalinka, Ivana; Roepstorff, Andreas

2012-01-01

Measuring brain activity simultaneously from two people interacting is intuitively appealing if one is interested in putative neural markers of social interaction. However, given the complex nature of interactions, it has proven difficult to carry out two-person brain imaging experiments in a methodologically feasible and conceptually relevant way. Only a small number of recent studies have put this into practice, using fMRI, EEG, or NIRS. Here, we review two main two-brain methodological approaches, each with two conceptual strategies. The first group has employed two-brain fMRI recordings, studying (1) turn-based interactions on the order of seconds, or (2) pseudo-interactive scenarios, where only one person is scanned at a time, investigating the flow of information between brains. The second group of studies has recorded dual EEG/NIRS from two people interacting, in (1) face-to-face turn-based interactions, investigating functional connectivity between theory-of-mind regions of interacting partners, or in (2) continuous mutual interactions on millisecond timescales, to measure coupling between the activity in one person's brain and the activity in the other's brain. We discuss the questions these approaches have addressed, and consider scenarios when simultaneous two-brain recordings are needed. Furthermore, we suggest that (1) quantification of inter-personal neural effects via measures of emergence, and (2) multivariate decoding models that generalize source-specific features of interaction, may provide novel tools to study brains in interaction. This may allow for a better understanding of social cognition as both representation and participation. PMID:22837744

Directed Neural Differentiation of Mouse Embryonic Stem Cells Is a Sensitive System for the Identification of Novel Hox Gene Effectors

PubMed Central

Bami, Myrto; Episkopou, Vasso; Gavalas, Anthony; Gouti, Mina

2011-01-01

The evolutionarily conserved Hox family of homeodomain transcription factors plays fundamental roles in regulating cell specification along the anterior posterior axis during development of all bilaterian animals by controlling cell fate choices in a highly localized, extracellular signal and cell context dependent manner. Some studies have established downstream target genes in specific systems but their identification is insufficient to explain either the ability of Hox genes to direct homeotic transformations or the breadth of their patterning potential. To begin delineating Hox gene function in neural development we used a mouse ES cell based system that combines efficient neural differentiation with inducible Hoxb1 expression. Gene expression profiling suggested that Hoxb1 acted as both activator and repressor in the short term but predominantly as a repressor in the long run. Activated and repressed genes segregated in distinct processes suggesting that, in the context examined, Hoxb1 blocked differentiation while activating genes related to early developmental processes, wnt and cell surface receptor linked signal transduction and cell-to-cell communication. To further elucidate aspects of Hoxb1 function we used loss and gain of function approaches in the mouse and chick embryos. We show that Hoxb1 acts as an activator to establish the full expression domain of CRABPI and II in rhombomere 4 and as a repressor to restrict expression of Lhx5 and Lhx9. Thus the Hoxb1 patterning activity includes the regulation of the cellular response to retinoic acid and the delay of the expression of genes that commit cells to neural differentiation. The results of this study show that ES neural differentiation and inducible Hox gene expression can be used as a sensitive model system to systematically identify Hox novel target genes, delineate their interactions with signaling pathways in dictating cell fate and define the extent of functional overlap among different Hox genes. PMID:21637844

Expectations impact short-term memory through changes in connectivity between attention- and task-related brain regions.

PubMed

Sinke, Christopher; Forkmann, Katarina; Schmidt, Katharina; Wiech, Katja; Bingel, Ulrike

2016-05-01

Over the recent years, neuroimaging studies have investigated the neural mechanisms underlying the influence of expectations on perception. However, it seems equally reasonable to assume that expectations impact cognitive functions. Here we used fMRI to explore the role of expectations on task performance and its underlying neural mechanisms. 43 healthy participants were randomly assigned to two groups. Using verbal instructions, group 1 was led to believe that pain enhances task performance while group 2 was instructed that pain hampers their performance. All participants performed a Rapid-Serial-Visual-Presentation (RSVP) Task (target detection and short-term memory component) with or without concomitant painful heat stimulation during 3T fMRI scanning. As hypothesized, short-term memory performance showed an interaction between painful stimulation and expectation. Positive expectations induced stronger neural activation in the right inferior parietal cortex (IPC) during painful stimulation than negative expectation. Moreover, IPC displayed differential functional coupling with the left inferior occipital cortex under pain as a function of expectancy. Our data show that an individual's expectation can influence cognitive performance in a visual short-term memory task which is associated with activity and connectivity changes in brain areas implicated in attentional processing and task performance. Copyright © 2016. Published by Elsevier Ltd.

Distinct pathways of neural coupling for different basic emotions.

PubMed

Tettamanti, Marco; Rognoni, Elena; Cafiero, Riccardo; Costa, Tommaso; Galati, Dario; Perani, Daniela

2012-01-16

Emotions are complex events recruiting distributed cortical and subcortical cerebral structures, where the functional integration dynamics within the involved neural circuits in relation to the nature of the different emotions are still unknown. Using fMRI, we measured the neural responses elicited by films representing basic emotions (fear, disgust, sadness, happiness). The amygdala and the associative cortex were conjointly activated by all basic emotions. Furthermore, distinct arrays of cortical and subcortical brain regions were additionally activated by each emotion, with the exception of sadness. Such findings informed the definition of three effective connectivity models, testing for the functional integration of visual cortex and amygdala, as regions processing all emotions, with domain-specific regions, namely: i) for fear, the frontoparietal system involved in preparing adaptive motor responses; ii) for disgust, the somatosensory system, reflecting protective responses against contaminating stimuli; iii) for happiness: medial prefrontal and temporoparietal cortices involved in understanding joyful interactions. Consistently with these domain-specific models, the results of the effective connectivity analysis indicate that the amygdala is involved in distinct functional integration effects with cortical networks processing sensorimotor, somatosensory, or cognitive aspects of basic emotions. The resulting effective connectivity networks may serve to regulate motor and cognitive behavior based on the quality of the induced emotional experience. Copyright © 2011. Published by Elsevier Inc.

A neural link between affective understanding and interpersonal attraction

PubMed Central

Anders, Silke; de Jong, Roos; Beck, Christian; Haynes, John-Dylan; Ethofer, Thomas

2016-01-01

Being able to comprehend another person’s intentions and emotions is essential for successful social interaction. However, it is currently unknown whether the human brain possesses a neural mechanism that attracts people to others whose mental states they can easily understand. Here we show that the degree to which a person feels attracted to another person can change while they observe the other’s affective behavior, and that these changes depend on the observer’s confidence in having correctly understood the other’s affective state. At the neural level, changes in interpersonal attraction were predicted by activity in the reward system of the observer’s brain. Importantly, these effects were specific to individual observer–target pairs and could not be explained by a target’s general attractiveness or expressivity. Furthermore, using multivoxel pattern analysis (MVPA), we found that neural activity in the reward system of the observer’s brain varied as a function of how well the target’s affective behavior matched the observer’s neural representation of the underlying affective state: The greater the match, the larger the brain’s intrinsic reward signal. Taken together, these findings provide evidence that reward-related neural activity during social encounters signals how well an individual’s “neural vocabulary” is suited to infer another person’s affective state, and that this intrinsic reward might be a source of changes in interpersonal attraction. PMID:27044071

Multiple neural network approaches to clinical expert systems

NASA Astrophysics Data System (ADS)

Stubbs, Derek F.

1990-08-01

We briefly review the concept of computer aided medical diagnosis and more extensively review the the existing literature on neural network applications in the field. Neural networks can function as simple expert systems for diagnosis or prognosis. Using a public database we develop a neural network for the diagnosis of a major presenting symptom while discussing the development process and possible approaches. MEDICAL EXPERTS SYSTEMS COMPUTER AIDED DIAGNOSIS Biomedicine is an incredibly diverse and multidisciplinary field and it is not surprising that neural networks with their many applications are finding more and more applications in the highly non-linear field of biomedicine. I want to concentrate on neural networks as medical expert systems for clinical diagnosis or prognosis. Expert Systems started out as a set of computerized " ifthen" rules. Everything was reduced to boolean logic and the promised land of computer experts was said to be in sight. It never came. Why? First the computer code explodes as the number of " ifs" increases. All the " ifs" have to interact. Second experts are not very good at reducing expertise to language. It turns out that experts recognize patterns and have non-verbal left-brain intuition decision processes. Third learning by example rather than learning by rule is the way natural brains works and making computers work by rule-learning is hideously labor intensive. Neural networks can learn from example. They learn the results

Immobilization of Heparan Sulfate on Electrospun Meshes to Support Embryonic Stem Cell Culture and Differentiation*

PubMed Central

Meade, Kate A.; White, Kathryn J.; Pickford, Claire E.; Holley, Rebecca J.; Marson, Andrew; Tillotson, Donna; van Kuppevelt, Toin H.; Whittle, Jason D.; Day, Anthony J.; Merry, Catherine L. R.

2013-01-01

As our understanding of what guides the behavior of multi- and pluripotent stem cells deepens, so too does our ability to utilize certain cues to manipulate their behavior and maximize their therapeutic potential. Engineered, biologically functionalized materials have the capacity to influence stem cell behavior through a powerful combination of biological, mechanical, and topographical cues. Here, we present the development of a novel electrospun scaffold, functionalized with glycosaminoglycans (GAGs) ionically immobilized onto the fiber surface. Bound GAGs retained the ability to interact with GAG-binding molecules and, crucially, presented GAG sulfation motifs fundamental to mediating stem cell behavior. Bound GAG proved to be biologically active, rescuing the neural differentiation capacity of heparan sulfate-deficient mouse embryonic stem cells and functioning in concert with FGF4 to facilitate the formation of extensive neural processes across the scaffold surface. The combination of GAGs with electrospun scaffolds creates a biomaterial with potent applicability for the propagation and effective differentiation of pluripotent stem cells. PMID:23235146

Immobilization of heparan sulfate on electrospun meshes to support embryonic stem cell culture and differentiation.

PubMed

Meade, Kate A; White, Kathryn J; Pickford, Claire E; Holley, Rebecca J; Marson, Andrew; Tillotson, Donna; van Kuppevelt, Toin H; Whittle, Jason D; Day, Anthony J; Merry, Catherine L R

2013-02-22

As our understanding of what guides the behavior of multi- and pluripotent stem cells deepens, so too does our ability to utilize certain cues to manipulate their behavior and maximize their therapeutic potential. Engineered, biologically functionalized materials have the capacity to influence stem cell behavior through a powerful combination of biological, mechanical, and topographical cues. Here, we present the development of a novel electrospun scaffold, functionalized with glycosaminoglycans (GAGs) ionically immobilized onto the fiber surface. Bound GAGs retained the ability to interact with GAG-binding molecules and, crucially, presented GAG sulfation motifs fundamental to mediating stem cell behavior. Bound GAG proved to be biologically active, rescuing the neural differentiation capacity of heparan sulfate-deficient mouse embryonic stem cells and functioning in concert with FGF4 to facilitate the formation of extensive neural processes across the scaffold surface. The combination of GAGs with electrospun scaffolds creates a biomaterial with potent applicability for the propagation and effective differentiation of pluripotent stem cells.

The N-Methyl-D-Aspartate Receptor in Heart Development: A Gene Knockdown Model Using siRNA

PubMed Central

Lie, Octavian V.; Bennett, Gregory D.; Rosenquist, Thomas H

2009-01-01

Antagonists of the N-methyl-D-aspartate receptor (NMDAR) may disrupt the development of the cardiac neural crest (CNC) and contribute to conotruncal heart defects. To test this interaction, a loss-of-function model was generated using small interfering RNAs (siRNA) directed against the critical NR1-subunit of this receptor in avian embryos. The coding sequence of the chicken NR1-gene and predicted protein sequences were characterized and found to be homologous with other vertebrate species. Analysis of its spatiotemporal expression demonstrated its expression within the neural tube at pre-migratory CNC sites. siRNA targeted to the NR1-mRNA in pre-migratory CNC lead to a significant decrease in NR1 protein expression. However, embryo survival and heart development were not adversely affected. These results indicate that the CNC may function normally in the absence of functional NMDAR, and that NMDAR antagonists may have a complex impact upon the CNC that transcends impairment of a single receptor type. PMID:19737608

Toward an Integration of Deep Learning and Neuroscience

PubMed Central

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P.

2016-01-01

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses. PMID:27683554

Immunomodulation of enteric neural function in irritable bowel syndrome.

PubMed

O'Malley, Dervla

2015-06-28

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder which is characterised by symptoms such as bloating, altered bowel habit and visceral pain. It's generally accepted that miscommunication between the brain and gut underlies the changes in motility, absorpto-secretory function and pain sensitivity associated with IBS. However, partly due to the lack of disease-defining biomarkers, understanding the aetiology of this complex and multifactorial disease remains elusive. Anecdotally, IBS patients have noted that periods of stress can result in symptom flares and many patients exhibit co-morbid stress-related mood disorders such as anxiety and depression. However, in addition to psychosocial stressors, infection-related stress has also been linked with the initiation, persistence and severity of symptom flares. Indeed, prior gastrointestinal infection is one of the strongest predictors of developing IBS. Despite a lack of overt morphological inflammation, the importance of immune factors in the pathophysiology of IBS is gaining acceptance. Subtle changes in the numbers of mucosal immune cell infiltrates and elevated levels of circulating pro-inflammatory cytokines have been reproducibly demonstrated in IBS populations. Moreover, these immune mediators directly affect neural signalling. An exciting new area of research is the role of luminal microbiota in the modulation of neuro-immune signalling, resulting in local changes in gastrointestinal function and alterations in central neural functioning. Progress in this area has begun to unravel some of the complexities of neuroimmune and neuroendocrine interactions and how these molecular exchanges contribute to GI dysfunction.

Hyperscanning: simultaneous fMRI during linked social interactions.

PubMed

Montague, P Read; Berns, Gregory S; Cohen, Jonathan D; McClure, Samuel M; Pagnoni, Giuseppe; Dhamala, Mukesh; Wiest, Michael C; Karpov, Igor; King, Richard D; Apple, Nathan; Fisher, Ronald E

2002-08-01

"Plain question and plain answer make the shortest road out of most perplexities." Mark Twain-Life on the Mississippi. A new methodology for the measurement of the neural substrates of human social interaction is described. This technology, termed "Hyperscan," embodies both the hardware and the software necessary to link magnetic resonance scanners through the internet. Hyperscanning allows for the performance of human behavioral experiments in which participants can interact with each other while functional MRI is acquired in synchrony with the behavioral interactions. Data are presented from a simple game of deception between pairs of subjects. Because people may interact both asymmetrically and asynchronously, both the design and the analysis must accommodate this added complexity. Several potential approaches are described.

Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability

PubMed Central

Barnett, Michael A.; Hartley, Jake; Gomez, Jesse; Stigliani, Anthony; Grill-Spector, Kalanit

2016-01-01

Face perception is subserved by a series of face-selective regions in the human ventral stream, which undergo prolonged development from childhood to adulthood. However, it is unknown how neural development of these regions relates to the development of face-perception abilities. Here, we used functional magnetic resonance imaging (fMRI) to measure brain responses of ventral occipitotemporal regions in children (ages, 5–12 years) and adults (ages, 19–34 years) when they viewed faces that parametrically varied in dissimilarity. Since similar faces generate lower responses than dissimilar faces due to fMRI adaptation, this design objectively evaluates neural sensitivity to face identity across development. Additionally, a subset of subjects participated in a behavioral experiment to assess perceptual discriminability of face identity. Our data reveal three main findings: (1) neural sensitivity to face identity increases with age in face-selective but not object-selective regions; (2) the amplitude of responses to faces increases with age in both face-selective and object-selective regions; and (3) perceptual discriminability of face identity is correlated with the neural sensitivity to face identity of face-selective regions. In contrast, perceptual discriminability is not correlated with the amplitude of response in face-selective regions or of responses of object-selective regions. These data suggest that developmental increases in neural sensitivity to face identity in face-selective regions improve perceptual discriminability of faces. Our findings significantly advance the understanding of the neural mechanisms of development of face perception and open new avenues for using fMRI adaptation to study the neural development of high-level visual and cognitive functions more broadly. SIGNIFICANCE STATEMENT Face perception, which is critical for daily social interactions, develops from childhood to adulthood. However, it is unknown what developmental changes in the brain lead to improved performance. Using fMRI in children and adults, we find that from childhood to adulthood, neural sensitivity to changes in face identity increases in face-selective regions. Critically, subjects' perceptual discriminability among faces is linked to neural sensitivity: participants with higher neural sensitivity in face-selective regions demonstrate higher perceptual discriminability. Thus, our results suggest that developmental increases in face-selective regions' sensitivity to face identity improve perceptual discrimination of faces. These findings significantly advance understanding of the neural mechanisms underlying the development of face perception and have important implications for assessing both typical and atypical development. PMID:27798143

Real-time interactive tractography analysis for multimodal brain visualization tool: MultiXplore

NASA Astrophysics Data System (ADS)

Bakhshmand, Saeed M.; de Ribaupierre, Sandrine; Eagleson, Roy

2017-03-01

Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.

Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases.

PubMed

Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

2014-04-15

Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted displays and joystick allow interaction and immersion in unreal environments created from computer software. Virtual environments are highly interactive, generating great activation of visual, vestibular and proprioceptive systems during the execution of a video game. In addition, they are entertaining and safe for the user. Recently, incorporating therapeutic purposes in virtual reality interface devices has allowed them to be used for the rehabilitation of neurological patients, e.g., balance training in older adults and dynamic stability in healthy participants. The improvements observed in neurological diseases (chronic stroke and cerebral palsy) have been shown by changes in the reorganization of neural networks in patients' brain, along with better hand function and other skills, contributing to their quality of life. The data generated by such studies could substantially contribute to physical rehabilitation strategies.

Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases

PubMed Central

Gatica-Rojas, Valeska; Méndez-Rebolledo, Guillermo

2014-01-01

Two key characteristics of all virtual reality applications are interaction and immersion. Systemic interaction is achieved through a variety of multisensory channels (hearing, sight, touch, and smell), permitting the user to interact with the virtual world in real time. Immersion is the degree to which a person can feel wrapped in the virtual world through a defined interface. Virtual reality interface devices such as the Nintendo® Wii and its peripheral nunchuks-balance board, head mounted displays and joystick allow interaction and immersion in unreal environments created from computer software. Virtual environments are highly interactive, generating great activation of visual, vestibular and proprioceptive systems during the execution of a video game. In addition, they are entertaining and safe for the user. Recently, incorporating therapeutic purposes in virtual reality interface devices has allowed them to be used for the rehabilitation of neurological patients, e.g., balance training in older adults and dynamic stability in healthy participants. The improvements observed in neurological diseases (chronic stroke and cerebral palsy) have been shown by changes in the reorganization of neural networks in patients’ brain, along with better hand function and other skills, contributing to their quality of life. The data generated by such studies could substantially contribute to physical rehabilitation strategies. PMID:25206907

Mechanical and Biological Interactions of Implants with the Brain and Their Impact on Implant Design

PubMed Central

Prodanov, Dimiter; Delbeke, Jean

2016-01-01

Neural prostheses have already a long history and yet the cochlear implant remains the only success story about a longterm sensory function restoration. On the other hand, neural implants for deep brain stimulation are gaining acceptance for variety of disorders including Parkinsons disease and obsessive-compulsive disorder. It is anticipated that the progress in the field has been hampered by a combination of technological and biological factors, such as the limited understanding of the longterm behavior of implants, unreliability of devices, biocompatibility of the implants among others. While the field's understanding of the cell biology of interactions at the biotic-abiotic interface has improved, relatively little attention has been paid on the mechanical factors (stress, strain), and hence on the geometry that can modulate it. This focused review summarizes the recent progress in the understanding of the mechanisms of mechanical interaction between the implants and the brain. The review gives an overview of the factors by which the implants interact acutely and chronically with the tissue: blood-brain barrier (BBB) breach, vascular damage, micromotions, diffusion etc. We propose some design constraints to be considered in future studies. Aspects of the chronic cell-implant interaction will be discussed in view of the chronic local inflammation and the ways of modulating it. PMID:26903786

Parkin mediates the ubiquitination of VPS35 and modulates retromer-dependent endosomal sorting.

PubMed

Williams, Erin T; Glauser, Liliane; Tsika, Elpida; Jiang, Haisong; Islam, Shariful; Moore, Darren J

2018-06-11

Mutations in a number of genes cause familial forms of Parkinson's disease (PD), including mutations in the vacuolar protein sorting 35 ortholog (VPS35) and parkin genes. In this study, we identify a novel functional interaction between parkin and VPS35. We demonstrate that parkin interacts with and robustly ubiquitinates VPS35 in human neural cells. Familial parkin mutations are impaired in their ability to ubiquitinate VPS35. Parkin mediates the attachment of an atypical poly-ubiquitin chain to VPS35 with three lysine residues identified within the C-terminal region of VPS35 that are covalently modified by ubiquitin. Notably, parkin-mediated VPS35 ubiquitination does not promote the proteasomal degradation of VPS35. Furthermore, parkin does not influence the steady-state levels or turnover of VPS35 in neural cells and VPS35 levels are normal in the brains of parkin knockout mice. These data suggest that ubiquitination of VPS35 by parkin may instead serve a non-degradative cellular function potentially by regulating retromer-dependent sorting. Accordingly, we find that components of the retromer-associated WASH complex are markedly decreased in the brain of parkin knockout mice, suggesting that parkin may modulate WASH complex-dependent retromer sorting. Parkin gene silencing in primary cortical neurons selectively disrupts the vesicular sorting of the autophagy receptor ATG9A, a WASH-dependent retromer cargo. Parkin is not required for dopaminergic neurodegeneration induced by the expression of PD-linked D620N VPS35 in mice, consistent with VPS35 being located downstream of parkin function. Our data reveal a novel functional interaction of parkin with VPS35 that may be important for retromer-mediated endosomal sorting and PD.

Psychological and neural contributions to appetite self-regulation.

PubMed

Stoeckel, Luke E; Birch, Leann L; Heatherton, Todd; Mann, Traci; Hunter, Christine; Czajkowski, Susan; Onken, Lisa; Berger, Paige K; Savage, Cary R

2017-03-01

This paper reviews the state of the science on psychological and neural contributions to appetite self-regulation in the context of obesity. Three content areas (neural systems and cognitive functions; parenting and early childhood development; and goal setting and goal striving) served to illustrate different perspectives on the psychological and neural factors that contribute to appetite dysregulation in the context of obesity. Talks were initially delivered at an NIH workshop consisting of experts in these three content areas, and then content areas were further developed through a review of the literature. Self-regulation of appetite involves a complex interaction between multiple domains, including cognitive, neural, social, and goal-directed behaviors and decision-making. Self-regulation failures can arise from any of these factors, and the resulting implications for obesity should be considered in light of each domain. In some cases, self-regulation is amenable to intervention; however, this does not appear to be universally true, which has implications for both prevention and intervention efforts. Appetite regulation is a complex, multifactorial construct. When considering its role in the obesity epidemic, it is advisable to consider its various dimensions together to best inform prevention and treatment efforts. © 2017 The Obesity Society.

Culture, gaze and the neural processing of fear expressions

PubMed Central

Franklin, Robert G.; Rule, Nicholas O.; Freeman, Jonathan B.; Kveraga, Kestutis; Hadjikhani, Nouchine; Yoshikawa, Sakiko; Ambady, Nalini

2010-01-01

The direction of others’ eye gaze has important influences on how we perceive their emotional expressions. Here, we examined differences in neural activation to direct- versus averted-gaze fear faces as a function of culture of the participant (Japanese versus US Caucasian), culture of the stimulus face (Japanese versus US Caucasian), and the relation between the two. We employed a previously validated paradigm to examine differences in neural activation in response to rapidly presented direct- versus averted-fear expressions, finding clear evidence for a culturally determined role of gaze in the processing of fear. Greater neural responsivity was apparent to averted- versus direct-gaze fear in several regions related to face and emotion processing, including bilateral amygdalae, when posed on same-culture faces, whereas greater response to direct- versus averted-gaze fear was apparent in these same regions when posed on other-culture faces. We also found preliminary evidence for intercultural variation including differential responses across participants to Japanese versus US Caucasian stimuli, and to a lesser degree differences in how Japanese and US Caucasian participants responded to these stimuli. These findings reveal a meaningful role of culture in the processing of eye gaze and emotion, and highlight their interactive influences in neural processing. PMID:20019073

Psychological and Neural Contributions to Appetite Self-Regulation

PubMed Central

Stoeckel, Luke E.; Birch, Leann L.; Heatherton, Todd; Mann, Traci; Hunter, Christine; Czajkowski, Susan; Onken, Lisa; Berger, Paige K.; Savage, Cary R.

2017-01-01

Objective Review the state-of-the-science on psychological and neural contributions to appetite self-regulation in the context of obesity. Methods Three content areas (neural systems and cognitive functions; parenting and early childhood development; and goal setting and goal striving) served as examples of different perspectives on the psychological and neural factors that contribute to appetite dysregulation in the context of obesity. Talks were initially delivered at a workshop consisting of experts in these three content areas and then content areas were further developed through a review of the literature. Results Self-regulation of appetite involves a complex interaction between multiple domains, including cognitive, neural, social, and goal-directed behaviors and decision-making. Self-regulation failures can results from any of these factors, and the resulting implications for obesity should be considered in light of each domain. In some cases, self-regulation appears to be amenable to intervention; however, this does not appear to be universally true, which has implications for both prevention and intervention efforts. Conclusions Appetite regulation is a complex, multi-factorial construct. When considering its role in the obesity epidemic, it is advisable to consider these various contributions together to best inform prevention and treatment efforts. PMID:28229541

Listening to Brain Microcircuits for Interfacing With External World—Progress in Wireless Implantable Microelectronic Neuroengineering Devices

PubMed Central

Nurmikko, Arto V.; Donoghue, John P.; Hochberg, Leigh R.; Patterson, William R.; Song, Yoon-Kyu; Bull, Christopher W.; Borton, David A.; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2011-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature’s amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic “brain-interfaces” within the body, a point of special emphasis of this paper. PMID:21654935

Complexity and Competition in Appetitive and Aversive Neural Circuits

PubMed Central

Barberini, Crista L.; Morrison, Sara E.; Saez, Alex; Lau, Brian; Salzman, C. Daniel

2012-01-01

Decision-making often involves using sensory cues to predict possible rewarding or punishing reinforcement outcomes before selecting a course of action. Recent work has revealed complexity in how the brain learns to predict rewards and punishments. Analysis of neural signaling during and after learning in the amygdala and orbitofrontal cortex, two brain areas that process appetitive and aversive stimuli, reveals a dynamic relationship between appetitive and aversive circuits. Specifically, the relationship between signaling in appetitive and aversive circuits in these areas shifts as a function of learning. Furthermore, although appetitive and aversive circuits may often drive opposite behaviors – approaching or avoiding reinforcement depending upon its valence – these circuits can also drive similar behaviors, such as enhanced arousal or attention; these processes also may influence choice behavior. These data highlight the formidable challenges ahead in dissecting how appetitive and aversive neural circuits interact to produce a complex and nuanced range of behaviors. PMID:23189037

Creating buzz: the neural correlates of effective message propagation.

PubMed

Falk, Emily B; Morelli, Sylvia A; Welborn, B Locke; Dambacher, Karl; Lieberman, Matthew D

2013-07-01

Social interaction promotes the spread of values, attitudes, and behaviors. Here, we report on neural responses to ideas that are destined to spread. We scanned message communicators using functional MRI during their initial exposure to the to-be-communicated ideas. These message communicators then had the opportunity to spread the messages and their corresponding subjective evaluations to message recipients outside the scanner. Successful ideas were associated with neural responses in the communicators' mentalizing systems and reward systems when they first heard the messages, prior to spreading them. Similarly, individuals more able to spread their own views to others produced greater mentalizing-system activity during initial encoding. Unlike prior social-influence studies that focused on the individuals being influenced, this investigation focused on the brains of influencers. Successful social influence is reliably associated with an influencer-to-be's state of mind when first encoding ideas.

Emotional Intent Modulates The Neural Substrates Of Creativity: An fMRI Study of Emotionally Targeted Improvisation in Jazz Musicians.

PubMed

McPherson, Malinda J; Barrett, Frederick S; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J

2016-01-04

Emotion is a primary motivator for creative behaviors, yet the interaction between the neural systems involved in creativity and those involved in emotion has not been studied. In the current study, we addressed this gap by using fMRI to examine piano improvisation in response to emotional cues. We showed twelve professional jazz pianists photographs of an actress representing a positive, negative or ambiguous emotion. Using a non-ferromagnetic thirty-five key keyboard, the pianists improvised music that they felt represented the emotion expressed in the photographs. Here we show that activity in prefrontal and other brain networks involved in creativity is highly modulated by emotional context. Furthermore, emotional intent directly modulated functional connectivity of limbic and paralimbic areas such as the amygdala and insula. These findings suggest that emotion and creativity are tightly linked, and that the neural mechanisms underlying creativity may depend on emotional state.

Neural correlates of depth of strategic reasoning in medial prefrontal cortex

PubMed Central

Coricelli, Giorgio; Nagel, Rosemarie

2009-01-01

We used functional MRI (fMRI) to investigate human mental processes in a competitive interactive setting—the “beauty contest” game. This game is well-suited for investigating whether and how a player's mental processing incorporates the thinking process of others in strategic reasoning. We apply a cognitive hierarchy model to classify subject's choices in the experimental game according to the degree of strategic reasoning so that we can identify the neural substrates of different levels of strategizing. According to this model, high-level reasoners expect the others to behave strategically, whereas low-level reasoners choose based on the expectation that others will choose randomly. The data show that high-level reasoning and a measure of strategic IQ (related to winning in the game) correlate with the neural activity in the medial prefrontal cortex, demonstrating its crucial role in successful mentalizing. This supports a cognitive hierarchy model of human brain and behavior. PMID:19470476

The neural basis of hand gesture comprehension: A meta-analysis of functional magnetic resonance imaging studies.

PubMed

Yang, Jie; Andric, Michael; Mathew, Mili M

2015-10-01

Gestures play an important role in face-to-face communication and have been increasingly studied via functional magnetic resonance imaging. Although a large amount of data has been provided to describe the neural substrates of gesture comprehension, these findings have never been quantitatively summarized and the conclusion is still unclear. This activation likelihood estimation meta-analysis investigated the brain networks underpinning gesture comprehension while considering the impact of gesture type (co-speech gestures vs. speech-independent gestures) and task demand (implicit vs. explicit) on the brain activation of gesture comprehension. The meta-analysis of 31 papers showed that as hand actions, gestures involve a perceptual-motor network important for action recognition. As meaningful symbols, gestures involve a semantic network for conceptual processing. Finally, during face-to-face interactions, gestures involve a network for social emotive processes. Our finding also indicated that gesture type and task demand influence the involvement of the brain networks during gesture comprehension. The results highlight the complexity of gesture comprehension, and suggest that future research is necessary to clarify the dynamic interactions among these networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sympathetic neural control of the kidney in hypertension.

PubMed

DiBona, G F

1992-01-01

Efferent renal sympathetic nerve activity is elevated in human essential hypertension as well as in several forms of experimental hypertension in animals. In addition, bilateral complete renal denervation delays the development and/or attenuates the magnitude of the hypertension in several different forms of experimental hypertension in animals. Efferent renal sympathetic nerve activity is known to have dose-dependent effects on renal blood flow, the glomerular filtration rate, renal tubular sodium and water reabsorption, and the renin secretion rate, which are capable of contributing, singly or in combination, to the development, maintenance, and exacerbation of the hypertensive state. Of the many factors known to influence the central nervous system integrative regulation of efferent renal sympathetic nerve activity, two environmental factors, a high dietary sodium intake and environmental stress, are capable of significant interaction. This resultant increase in efferent renal sympathetic nerve activity and subsequent renal functional alterations can participate in the hypertensive process. This is especially evident in the presence of an underlying genetic predisposition to the development of hypertension. Thus, interactions between environmental and genetic influences can produce alterations in the sympathetic neural control of renal function that play an important role in hypertension.

Speech comprehension aided by multiple modalities: behavioural and neural interactions

PubMed Central

McGettigan, Carolyn; Faulkner, Andrew; Altarelli, Irene; Obleser, Jonas; Baverstock, Harriet; Scott, Sophie K.

2014-01-01

Speech comprehension is a complex human skill, the performance of which requires the perceiver to combine information from several sources – e.g. voice, face, gesture, linguistic context – to achieve an intelligible and interpretable percept. We describe a functional imaging investigation of how auditory, visual and linguistic information interact to facilitate comprehension. Our specific aims were to investigate the neural responses to these different information sources, alone and in interaction, and further to use behavioural speech comprehension scores to address sites of intelligibility-related activation in multifactorial speech comprehension. In fMRI, participants passively watched videos of spoken sentences, in which we varied Auditory Clarity (with noise-vocoding), Visual Clarity (with Gaussian blurring) and Linguistic Predictability. Main effects of enhanced signal with increased auditory and visual clarity were observed in overlapping regions of posterior STS. Two-way interactions of the factors (auditory × visual, auditory × predictability) in the neural data were observed outside temporal cortex, where positive signal change in response to clearer facial information and greater semantic predictability was greatest at intermediate levels of auditory clarity. Overall changes in stimulus intelligibility by condition (as determined using an independent behavioural experiment) were reflected in the neural data by increased activation predominantly in bilateral dorsolateral temporal cortex, as well as inferior frontal cortex and left fusiform gyrus. Specific investigation of intelligibility changes at intermediate auditory clarity revealed a set of regions, including posterior STS and fusiform gyrus, showing enhanced responses to both visual and linguistic information. Finally, an individual differences analysis showed that greater comprehension performance in the scanning participants (measured in a post-scan behavioural test) were associated with increased activation in left inferior frontal gyrus and left posterior STS. The current multimodal speech comprehension paradigm demonstrates recruitment of a wide comprehension network in the brain, in which posterior STS and fusiform gyrus form sites for convergence of auditory, visual and linguistic information, while left-dominant sites in temporal and frontal cortex support successful comprehension. PMID:22266262

Speech comprehension aided by multiple modalities: behavioural and neural interactions.

PubMed

McGettigan, Carolyn; Faulkner, Andrew; Altarelli, Irene; Obleser, Jonas; Baverstock, Harriet; Scott, Sophie K

2012-04-01

Speech comprehension is a complex human skill, the performance of which requires the perceiver to combine information from several sources - e.g. voice, face, gesture, linguistic context - to achieve an intelligible and interpretable percept. We describe a functional imaging investigation of how auditory, visual and linguistic information interact to facilitate comprehension. Our specific aims were to investigate the neural responses to these different information sources, alone and in interaction, and further to use behavioural speech comprehension scores to address sites of intelligibility-related activation in multifactorial speech comprehension. In fMRI, participants passively watched videos of spoken sentences, in which we varied Auditory Clarity (with noise-vocoding), Visual Clarity (with Gaussian blurring) and Linguistic Predictability. Main effects of enhanced signal with increased auditory and visual clarity were observed in overlapping regions of posterior STS. Two-way interactions of the factors (auditory × visual, auditory × predictability) in the neural data were observed outside temporal cortex, where positive signal change in response to clearer facial information and greater semantic predictability was greatest at intermediate levels of auditory clarity. Overall changes in stimulus intelligibility by condition (as determined using an independent behavioural experiment) were reflected in the neural data by increased activation predominantly in bilateral dorsolateral temporal cortex, as well as inferior frontal cortex and left fusiform gyrus. Specific investigation of intelligibility changes at intermediate auditory clarity revealed a set of regions, including posterior STS and fusiform gyrus, showing enhanced responses to both visual and linguistic information. Finally, an individual differences analysis showed that greater comprehension performance in the scanning participants (measured in a post-scan behavioural test) were associated with increased activation in left inferior frontal gyrus and left posterior STS. The current multimodal speech comprehension paradigm demonstrates recruitment of a wide comprehension network in the brain, in which posterior STS and fusiform gyrus form sites for convergence of auditory, visual and linguistic information, while left-dominant sites in temporal and frontal cortex support successful comprehension. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Physics-driven Neural Networks-based Simulation System (PhyNNeSS) for multimodal interactive virtual environments involving nonlinear deformable objects

PubMed Central

De, Suvranu; Deo, Dhannanjay; Sankaranarayanan, Ganesh; Arikatla, Venkata S.

2012-01-01

Background While an update rate of 30 Hz is considered adequate for real time graphics, a much higher update rate of about 1 kHz is necessary for haptics. Physics-based modeling of deformable objects, especially when large nonlinear deformations and complex nonlinear material properties are involved, at these very high rates is one of the most challenging tasks in the development of real time simulation systems. While some specialized solutions exist, there is no general solution for arbitrary nonlinearities. Methods In this work we present PhyNNeSS - a Physics-driven Neural Networks-based Simulation System - to address this long-standing technical challenge. The first step is an off-line pre-computation step in which a database is generated by applying carefully prescribed displacements to each node of the finite element models of the deformable objects. In the next step, the data is condensed into a set of coefficients describing neurons of a Radial Basis Function network (RBFN). During real-time computation, these neural networks are used to reconstruct the deformation fields as well as the interaction forces. Results We present realistic simulation examples from interactive surgical simulation with real time force feedback. As an example, we have developed a deformable human stomach model and a Penrose-drain model used in the Fundamentals of Laparoscopic Surgery (FLS) training tool box. Conclusions A unique computational modeling system has been developed that is capable of simulating the response of nonlinear deformable objects in real time. The method distinguishes itself from previous efforts in that a systematic physics-based pre-computational step allows training of neural networks which may be used in real time simulations. We show, through careful error analysis, that the scheme is scalable, with the accuracy being controlled by the number of neurons used in the simulation. PhyNNeSS has been integrated into SoFMIS (Software Framework for Multimodal Interactive Simulation) for general use. PMID:22629108

Understanding the dynamical control of animal movement

NASA Astrophysics Data System (ADS)

Edwards, Donald

2008-03-01

Over the last 50 years, neurophysiologists have described many neural circuits that transform sensory input into motor commands, while biomechanicians and behavioral biologists have described many patterns of animal movement that occur in response to sensory input. Attempts to link these two have been frustrated by our technical inability to record from the necessary neurons in a freely behaving animal. As a result, we don't know how these neural circuits function in the closed loop context of free behavior, where the sensory and motor context changes on a millisecond time-scale. To address this problem, we have developed a software package, AnimatLab (www.AnimatLab.com), that enables users to reconstruct an animal's body and its relevant neural circuits, to link them at the sensory and motor ends, and through simulation, to test their ability to reproduce appropriate patterns of the animal's movements in a simulated Newtonian world. A Windows-based program, AnimatLab consists of a neural editor, a body editor, a world editor, stimulus and recording facilities, neural and physics engines, and an interactive 3-D graphical display. We have used AnimatLab to study three patterns of behavior: the grasshopper jump, crayfish escape, and crayfish leg movements used in postural control, walking, reaching and grasping. In each instance, the simulation helped identify constraints on both nervous function and biomechanical performance that have provided the basis for new experiments. Colleagues elsewhere have begun to use AnimatLab to study control of paw movements in cats and postural control in humans. We have also used AnimatLab simulations to guide the development of an autonomous hexapod robot in which the neural control circuitry is downloaded to the robot from the test computer.

Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

PubMed Central

Hasson, Uri; Frith, Chris D.

2016-01-01

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader–follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis PMID:27069044

Social risky decision-making reveals gender differences in the TPJ: A hyperscanning study using functional near-infrared spectroscopy.

PubMed

Zhang, Mingming; Liu, Tao; Pelowski, Matthew; Jia, Huibin; Yu, Dongchuan

2017-12-01

Previous neuroscience studies have investigated neural correlates of risky decision-making in a single-brain frame during pseudo social (predominantly non face-to-face) contexts. To fully understand the risky decision-making behavior in more natural social interactions, the present study employed a functional near-infrared spectroscopy (fNIRS) hyperscanning technique to simultaneously measure pairs of participants' fronto-temporal activations in a face-to-face gambling card-game. The intra-brain results revealed that both those who identified as males and as females showed higher activations in their mPFC and in the inferior parts of the frontopolar area, as well as in the tempo-parietal junction (TPJ) in cases involving higher versus lower risk. This is consistent with previous findings suggesting importance of the mentalizing network in decision tasks. The fNIRS results of inter-brain neural synchronization (INS) also revealed that males and females showed increased inter-brain coherence in the mPFC and dlPFC. Females, however, uniquely showed increased inter-brain coherence in the left TPJ. This INS result suggests that males may primarily depend on non-social cognitive ability to make a risky decision in a social interaction, while females may use both social and non-social cognitive abilities. The implications are also discussed for general topics of human interaction and two-person neuroscience. Copyright © 2017 Elsevier Inc. All rights reserved.

Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.

PubMed

Gritsenko, Valeriya; Hardesty, Russell L; Boots, Mathew T; Yakovenko, Sergiy

2016-01-01

Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb. This model was used to calculate muscle lengths across the full range of motion of the arm and examined the correlations between these values between all pairs of muscles. Musculoskeletal coupling was quantified using hierarchical clustering analysis. Muscle lengths between multiple pairs of muscles across multiple postures were highly correlated. These correlations broadly formed two proximal and distal groups, where proximal muscles of the arm were correlated with each other and distal muscles of the arm and hand were correlated with each other, but not between groups. Using hierarchical clustering, between 11 and 14 reliable muscle groups were identified. This shows that musculoskeletal anatomy does indeed shape the mechanical interactions by grouping muscles into functional clusters that generally match the functional repertoire of the human arm. Together, these results support the idea that the structure of the musculoskeletal system is tuned to solve movement complexity problem by reducing the dimensionality of available solutions.

Controlling specific locomotor behaviors through multidimensional monoaminergic modulation of spinal circuitries

PubMed Central

Musienko, Pavel; van den Brand, Rubia; Märzendorfer, Olivia; Roy, Roland R.; Gerasimenko, Yury; Edgerton, V. Reggie; Courtine, Grégoire

2012-01-01

Descending monoaminergic inputs markedly influence spinal locomotor circuits, but the functional relationships between specific receptors and the control of walking behavior remain poorly understood. To identify these interactions, we manipulated serotonergic, dopaminergic, and noradrenergic neural pathways pharmacologically during locomotion enabled by electrical spinal cord stimulation in adult spinal rats in vivo. Using advanced neurobiomechanical recordings and multidimensional statistical procedures, we reveal that each monoaminergic receptor modulates a broad but distinct spectrum of kinematic, kinetic and EMG characteristics, which we expressed into receptor–specific functional maps. We then exploited this catalogue of monoaminergic tuning functions to devise optimal pharmacological combinations to encourage locomotion in paralyzed rats. We found that, in most cases, receptor-specific modulatory influences summed near algebraically when stimulating multiple pathways concurrently. Capitalizing on these predictive interactions, we elaborated a multidimensional monoaminergic intervention that restored coordinated hindlimb locomotion with normal levels of weight bearing and partial equilibrium maintenance in spinal rats. These findings provide new perspectives on the functions of and interactions between spinal monoaminergic receptor systems in producing stepping, and define a framework to tailor pharmacotherapies for improving neurological functions after CNS disorders. PMID:21697376

The relationship between spatial configuration and functional connectivity of brain regions.

PubMed

Bijsterbosch, Janine Diane; Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C; Harrison, Samuel J; Smith, Stephen M

2018-02-16

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used 'functional connectivity fingerprints' to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. © 2018, Bijsterbosch et al.

Oxytocin-secreting system: A major part of the neuroendocrine center regulating immunologic activity.

PubMed

Wang, Ping; Yang, Hai-Peng; Tian, Shujun; Wang, Liwei; Wang, Stephani C; Zhang, Fengmin; Wang, Yu-Feng

2015-12-15

Interactions between the nervous system and immune system have been studied extensively. However, the mechanisms underlying the neural regulation of immune activity, particularly the neuroendocrine regulation of immunologic functions, remain elusive. In this review, we provide a comprehensive examination of current evidence on interactions between the immune system and hypothalamic oxytocin-secreting system. We highlight the fact that oxytocin may have significant effects in the body, beyond its classical functions in lactation and parturition. Similar to the hypothalamo-pituitary-adrenal axis, the oxytocin-secreting system closely interacts with classical immune system, integrating both neurochemical and immunologic signals in the central nervous system and in turn affects immunologic defense, homeostasis, and surveillance. Lastly, this review explores therapeutic potentials of oxytocin in treating immunologic disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

Learning in neural networks based on a generalized fluctuation theorem

NASA Astrophysics Data System (ADS)

Hayakawa, Takashi; Aoyagi, Toshio

2015-11-01

Information maximization has been investigated as a possible mechanism of learning governing the self-organization that occurs within the neural systems of animals. Within the general context of models of neural systems bidirectionally interacting with environments, however, the role of information maximization remains to be elucidated. For bidirectionally interacting physical systems, universal laws describing the fluctuation they exhibit and the information they possess have recently been discovered. These laws are termed fluctuation theorems. In the present study, we formulate a theory of learning in neural networks bidirectionally interacting with environments based on the principle of information maximization. Our formulation begins with the introduction of a generalized fluctuation theorem, employing an interpretation appropriate for the present application, which differs from the original thermodynamic interpretation. We analytically and numerically demonstrate that the learning mechanism presented in our theory allows neural networks to efficiently explore their environments and optimally encode information about them.

Neural Correlates of Self and Its Interaction With Memory in Healthy Adolescents.

PubMed

Dégeilh, Fanny; Guillery-Girard, Bérengère; Dayan, Jacques; Gaubert, Malo; Chételat, Gaël; Egler, Pierre-Jean; Baleyte, Jean-Marc; Eustache, Francis; Viard, Armelle

2015-01-01

Adolescence is marked by the development of personal identity and is associated with structural and functional changes in brain regions associated with Self processing. Yet, little is known about the neural correlates of self-reference processing and self-reference effect in adolescents. This functional magnetic resonance imaging study consists of a self-reference paradigm followed by a recognition test proposed to 30 healthy adolescents aged 13-18 years old. Results showed that the rostral anterior cingulate cortex is specifically involved in self-reference processing and that this specialization develops gradually from 13 to 18 years old. The self-reference effect is associated with increased brain activation changes during encoding, suggesting that the beneficial effect of Self on memory may occur at encoding of self-referential information, rather than at retrieval. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.

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

Neuroglial modulation in peripheral sensory systems.

PubMed

Pack, Adam K; Pawson, Lorraine J

2010-08-01

Glia are increasingly appreciated as active participants in central neural processing via calcium waves, electrical coupling, and even synaptic-like release of "neuro"-transmitters. In some sensory organs (e.g., retina, olfactory bulb), glia have been shown to interact with neurons in the same manner, although their role in perception has yet to be elucidated. In the organ of Corti, synapses occur between supporting cells and neurons. In one sensory organ, the Pacinian corpuscle (fine touch), glia have been shown to play just as important a role in sensory transduction as they do in neural processing in the brain, and the functional role is quite clear; the modified Schwann cells of the capsule are responsible for the rapid adaptation process of the PCs, integral to its function as a vibration detector. This complex glial/neuronal relationship may be a recent evolutionary phenomenon and may account for much of the relative sophistication of vertebrate nervous systems.

Mentalizing and motivation neural function during social interactions in autism spectrum disorders☆

PubMed Central

Assaf, Michal; Hyatt, Christopher J.; Wong, Christina G.; Johnson, Matthew R.; Schultz, Robert T.; Hendler, Talma; Pearlson, Godfrey D.

2013-01-01

Autism Spectrum Disorders (ASDs) are characterized by core deficits in social functions. Two theories have been suggested to explain these deficits: mind-blindness theory posits impaired mentalizing processes (i.e. decreased ability for establishing a representation of others' state of mind), while social motivation theory proposes that diminished reward value for social information leads to reduced social attention, social interactions, and social learning. Mentalizing and motivation are integral to typical social interactions, and neuroimaging evidence points to independent brain networks that support these processes in healthy individuals. However, the simultaneous function of these networks has not been explored in individuals with ASDs. We used a social, interactive fMRI task, the Domino game, to explore mentalizing- and motivation-related brain activation during a well-defined interval where participants respond to rewards or punishments (i.e. motivation) and concurrently process information about their opponent's potential next actions (i.e. mentalizing). Thirteen individuals with high-functioning ASDs, ages 12–24, and 14 healthy controls played fMRI Domino games against a computer-opponent and separately, what they were led to believe was a human-opponent. Results showed that while individuals with ASDs understood the game rules and played similarly to controls, they showed diminished neural activity during the human-opponent runs only (i.e. in a social context) in bilateral middle temporal gyrus (MTG) during mentalizing and right Nucleus Accumbens (NAcc) during reward-related motivation (Pcluster < 0.05 FWE). Importantly, deficits were not observed in these areas when playing against a computer-opponent or in areas related to motor and visual processes. These results demonstrate that while MTG and NAcc, which are critical structures in the mentalizing and motivation networks, respectively, activate normally in a non-social context, they fail to respond in an otherwise identical social context in ASD compared to controls. We discuss implications to both the mind-blindness and social motivation theories of ASD and the importance of social context in research and treatment protocols. PMID:24273716

The Development of the Neural Substrates of Cognitive Control in Adolescents with Autism Spectrum Disorders

PubMed Central

Solomon, Marjorie; Yoon, Jong; Ragland, J. Daniel; Niendam, Tara; Lesh, Tyler A.; Fairbrother, Wonja; Carter, Cameron S.

2013-01-01

Background Autism spectrum disorders (ASD) involve impairments in cognitive control. In typical development (TYP), neural systems underlying cognitive control undergo substantial maturation during adolescence. Development is delayed in adolescents with ASD. Little is known about the neural substrates of this delay. Method We used event-related functional magnetic resonance imaging (fMRI) and a cognitive control task involving overcoming a prepotent response tendency to examine the development of cognitive control in young (ages 12–15; n = 13 with ASD and n = 13 with TYP) and older (ages 16–18; n= 14 with ASD and n = 14 with TYP) adolescents with whole-brain voxel-wise univariate and task-related functional connectivity analyses. Results Older ASD and TYP showed reduced activation in sensory and premotor areas relative to younger ones. The older ASD group showed reduced left parietal activation relative to TYP. Functional connectivity analyses showed a significant age by group interaction with the older ASD group exhibiting increased functional connectivity strength between the ventrolateral prefrontal cortex (VLPFC) and the anterior cingulate cortex (ACC), bilaterally. This functional connectivity strength was related to task performance in ASD, whereas that between DLPFC and parietal cortex (BA 9 and BA 40) was related to task performance in TYP. Conclusions Adolescents with ASD rely more on “reactive” cognitive control, involving last minute conflict detection and control implementation by the ACC and VLPFC, versus “proactive” cognitive control requiring processing by DLPFC and parietal cortex. Findings await replication in larger longitudinal studies that examine their functional consequences and amenability to intervention. PMID:24209777

Learning control of inverted pendulum system by neural network driven fuzzy reasoning: The learning function of NN-driven fuzzy reasoning under changes of reasoning environment

NASA Technical Reports Server (NTRS)

Hayashi, Isao; Nomura, Hiroyoshi; Wakami, Noboru

1991-01-01

Whereas conventional fuzzy reasonings are associated with tuning problems, which are lack of membership functions and inference rule designs, a neural network driven fuzzy reasoning (NDF) capable of determining membership functions by neural network is formulated. In the antecedent parts of the neural network driven fuzzy reasoning, the optimum membership function is determined by a neural network, while in the consequent parts, an amount of control for each rule is determined by other plural neural networks. By introducing an algorithm of neural network driven fuzzy reasoning, inference rules for making a pendulum stand up from its lowest suspended point are determined for verifying the usefulness of the algorithm.

A recurrent neural network for nonlinear optimization with a continuously differentiable objective function and bound constraints.

PubMed

Liang, X B; Wang, J

2000-01-01

This paper presents a continuous-time recurrent neural-network model for nonlinear optimization with any continuously differentiable objective function and bound constraints. Quadratic optimization with bound constraints is a special problem which can be solved by the recurrent neural network. The proposed recurrent neural network has the following characteristics. 1) It is regular in the sense that any optimum of the objective function with bound constraints is also an equilibrium point of the neural network. If the objective function to be minimized is convex, then the recurrent neural network is complete in the sense that the set of optima of the function with bound constraints coincides with the set of equilibria of the neural network. 2) The recurrent neural network is primal and quasiconvergent in the sense that its trajectory cannot escape from the feasible region and will converge to the set of equilibria of the neural network for any initial point in the feasible bound region. 3) The recurrent neural network has an attractivity property in the sense that its trajectory will eventually converge to the feasible region for any initial states even at outside of the bounded feasible region. 4) For minimizing any strictly convex quadratic objective function subject to bound constraints, the recurrent neural network is globally exponentially stable for almost any positive network parameters. Simulation results are given to demonstrate the convergence and performance of the proposed recurrent neural network for nonlinear optimization with bound constraints.

Linear summation of outputs in a balanced network model of motor cortex

PubMed Central

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis. PMID:26097452

Inflammatory Th17 cells promote depression-like behavior in mice

PubMed Central

Beurel, Eléonore; Harrington, Laurie E.; Jope, Richard S.

2012-01-01

Background Recognition of substantial immune-neural interactions is revising dogmas about their insular actions and revealing that immune-neural interactions can substantially impact CNS functions. The inflammatory cytokine interleukin-6 promotes susceptibility to depression and drives production of inflammatory T helper 17 (Th17) T cells, raising the hypothesis that in mouse models Th17 cells promote susceptibility to depression-like behaviors. Methods Behavioral characteristics were measured in male mice administered Th17 cells, CD4+ cells, or vehicle, and in RORγT+/GFP mice or male mice treated with RORγT inhibitor or anti-IL-17A antibodies. Results Mouse brain Th17 cells were elevated by learned helplessness and chronic restraint stress, two common depression-like models. Th17 cell administration promoted learned helplessness in 89% of mice in a paradigm where no vehicle-treated mice developed learned helplessness, and impaired novelty suppressed feeding and social interaction behaviors. Mice deficient in the RORγT transcription factor necessary for Th17 cell production exhibited resistance to learned helplessness, identifying modulation of RORγT as a potential intervention. Treatment with the RORγT inhibitor SR1001, or anti-IL-17A antibodies to abrogate Th17 cell function, reduced Th17-dependent learned helplessness. Conclusions These findings indicate that Th17 cells are increased in the brain during depression-like states, promote depression-like behaviors in mice, and specifically inhibiting the production or function of Th17 cells reduces vulnerability to depression-like behavior, suggesting antidepressant effects may be attained by targeting Th17 cells. PMID:23174342

Lighting up the brain's reward circuitry.

PubMed

Lobo, Mary Kay

2012-07-01

The brain's reward circuit is critical for mediating natural reward behaviors including food, sex, and social interaction. Drugs of abuse take over this circuit and produce persistent molecular and cellular alterations in the brain regions and their neural circuitry that make up the reward pathway. Recent use of optogenetic technologies has provided novel insights into the functional and molecular role of the circuitry and cell subtypes within these circuits that constitute this pathway. This perspective will address the current and future use of light-activated proteins, including those involved in modulating neuronal activity, cellular signaling, and molecular properties in the neural circuitry mediating rewarding stimuli and maladaptive responses to drugs of abuse. © 2012 New York Academy of Sciences.

An evolutionary algorithm that constructs recurrent neural networks.

PubMed

Angeline, P J; Saunders, G M; Pollack, J B

1994-01-01

Standard methods for simultaneously inducing the structure and weights of recurrent neural networks limit every task to an assumed class of architectures. Such a simplification is necessary since the interactions between network structure and function are not well understood. Evolutionary computations, which include genetic algorithms and evolutionary programming, are population-based search methods that have shown promise in many similarly complex tasks. This paper argues that genetic algorithms are inappropriate for network acquisition and describes an evolutionary program, called GNARL, that simultaneously acquires both the structure and weights for recurrent networks. GNARL's empirical acquisition method allows for the emergence of complex behaviors and topologies that are potentially excluded by the artificial architectural constraints imposed in standard network induction methods.

Still searching for the engram.

PubMed

Eichenbaum, Howard

2016-09-01

For nearly a century, neurobiologists have searched for the engram-the neural representation of a memory. Early studies showed that the engram is widely distributed both within and across brain areas and is supported by interactions among large networks of neurons. Subsequent research has identified engrams that support memory within dedicated functional systems for habit learning and emotional memory, but the engram for declarative memories has been elusive. Nevertheless, recent years have brought progress from molecular biological approaches that identify neurons and networks that are necessary and sufficient to support memory, and from recording approaches and population analyses that characterize the information coded by large neural networks. These new directions offer the promise of revealing the engrams for episodic and semantic memories.

Chaotic simulated annealing by a neural network with a variable delay: design and application.

PubMed

Chen, Shyan-Shiou

2011-10-01

In this paper, we have three goals: the first is to delineate the advantages of a variably delayed system, the second is to find a more intuitive Lyapunov function for a delayed neural network, and the third is to design a delayed neural network for a quadratic cost function. For delayed neural networks, most researchers construct a Lyapunov function based on the linear matrix inequality (LMI) approach. However, that approach is not intuitive. We provide a alternative candidate Lyapunov function for a delayed neural network. On the other hand, if we are first given a quadratic cost function, we can construct a delayed neural network by suitably dividing the second-order term into two parts: a self-feedback connection weight and a delayed connection weight. To demonstrate the advantage of a variably delayed neural network, we propose a transiently chaotic neural network with variable delay and show numerically that the model should possess a better searching ability than Chen-Aihara's model, Wang's model, and Zhao's model. We discuss both the chaotic and the convergent phases. During the chaotic phase, we simply present bifurcation diagrams for a single neuron with a constant delay and with a variable delay. We show that the variably delayed model possesses the stochastic property and chaotic wandering. During the convergent phase, we not only provide a novel Lyapunov function for neural networks with a delay (the Lyapunov function is independent of the LMI approach) but also establish a correlation between the Lyapunov function for a delayed neural network and an objective function for the traveling salesman problem. © 2011 IEEE

Deep neural networks for direct, featureless learning through observation: The case of two-dimensional spin models

NASA Astrophysics Data System (ADS)

Mills, Kyle; Tamblyn, Isaac

2018-03-01

We demonstrate the capability of a convolutional deep neural network in predicting the nearest-neighbor energy of the 4 ×4 Ising model. Using its success at this task, we motivate the study of the larger 8 ×8 Ising model, showing that the deep neural network can learn the nearest-neighbor Ising Hamiltonian after only seeing a vanishingly small fraction of configuration space. Additionally, we show that the neural network has learned both the energy and magnetization operators with sufficient accuracy to replicate the low-temperature Ising phase transition. We then demonstrate the ability of the neural network to learn other spin models, teaching the convolutional deep neural network to accurately predict the long-range interaction of a screened Coulomb Hamiltonian, a sinusoidally attenuated screened Coulomb Hamiltonian, and a modified Potts model Hamiltonian. In the case of the long-range interaction, we demonstrate the ability of the neural network to recover the phase transition with equivalent accuracy to the numerically exact method. Furthermore, in the case of the long-range interaction, the benefits of the neural network become apparent; it is able to make predictions with a high degree of accuracy, and do so 1600 times faster than a CUDA-optimized exact calculation. Additionally, we demonstrate how the neural network succeeds at these tasks by looking at the weights learned in a simplified demonstration.

Thalamic amplification of cortical connectivity sustains attentional control

PubMed Central

Schmitt, L. Ian; Wimmer, Ralf D.; Nakajima, Miho; Happ, Michael; Mofakham, Sima; Halassa, Michael M.

2017-01-01

While interactions between the thalamus and cortex are critical for cognitive function1–3, the exact contribution of the thalamus to these interactions is often unclear. Recent studies have shown diverse connectivity patterns across the thalamus 4,5, but whether this diversity translates to thalamic functions beyond relaying information to or between cortical regions6 is unknown. Here, by investigating prefrontal cortical (PFC) representation of two rules used to guide attention, we find that the mediodorsal thalamus (MD) sustains these representations without relaying categorical information. Specifically, MD input amplifies local PFC connectivity, enabling rule-specific neural sequences to emerge and thereby maintain rule representations. Consistent with this notion, broadly enhancing PFC excitability diminishes rule specificity and behavioral performance, while enhancing MD excitability improves both. Overall, our results define a previously unknown principle in neuroscience; thalamic control of functional cortical connectivity. This function indicates that the thalamus plays much more central roles in cognition than previously thought. PMID:28467827

Trying to Put the Puzzle Together: Age and Performance Level Modulate the Neural Response to Increasing Task Load within Left Rostral Prefrontal Cortex.

PubMed

Bauer, Eva; Sammer, Gebhard; Toepper, Max

2015-01-01

Age-related working memory decline is associated with functional cerebral changes within prefrontal cortex (PFC). Kind and meaning of these changes are heavily discussed since they depend on performance level and task load. Hence, we investigated the effects of age, performance level, and load on spatial working memory retrieval-related brain activation in different subregions of the PFC. 19 younger (Y) and 21 older (O) adults who were further subdivided into high performers (HP) and low performers (LP) performed a modified version of the Corsi Block-Tapping test during fMRI. Brain data was analyzed by a 4 (groups: YHP, OHP, YLP, and OLP) × 3 (load levels: loads 4, 5, and 6) ANOVA. Results revealed significant group × load interaction effects within rostral dorsolateral and ventrolateral PFC. YHP showed a flexible neural upregulation with increasing load, whereas YLP reached a resource ceiling at a moderate load level. OHP showed a similar (though less intense) pattern as YHP and may have compensated age-effects at high task load. OLP showed neural inefficiency at low and no upregulation at higher load. Our findings highlight the relevance of age and performance level for load-dependent activation within rostral PFC. Results are discussed in the context of the compensation-related utilization of neural circuits hypothesis (CRUNCH) and functional PFC organization.

Feedback associated with expectation for larger-reward improves visuospatial working memory performances in children with ADHD.

PubMed

Hammer, Rubi; Tennekoon, Michael; Cooke, Gillian E; Gayda, Jessica; Stein, Mark A; Booth, James R

2015-08-01

We tested the interactive effect of feedback and reward on visuospatial working memory in children with ADHD. Seventeen boys with ADHD and 17 Normal Control (NC) boys underwent functional magnetic resonance imaging (fMRI) while performing four visuospatial 2-back tasks that required monitoring the spatial location of letters presented on a display. Tasks varied in reward size (large; small) and feedback availability (no-feedback; feedback). While the performance of NC boys was high in all conditions, boys with ADHD exhibited higher performance (similar to those of NC boys) only when they received feedback associated with large-reward. Performance pattern in both groups was mirrored by neural activity in an executive function neural network comprised of few distinct frontal brain regions. Specifically, neural activity in the left and right middle frontal gyri of boys with ADHD became normal-like only when feedback was available, mainly when feedback was associated with large-reward. When feedback was associated with small-reward, or when large-reward was expected but feedback was not available, boys with ADHD exhibited altered neural activity in the medial orbitofrontal cortex and anterior insula. This suggests that contextual support normalizes activity in executive brain regions in children with ADHD, which results in improved working memory. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback

PubMed Central

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone. PMID:29342146

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

PubMed

Buckley, Christopher L; Toyoizumi, Taro

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone.

Transplantation of motoneurons derived from MASH1-transfected mouse ES cells reconstitutes neural networks and improves motor function in hemiplegic mice.

PubMed

Ikeda, Ritsuko; Kurokawa, Manae S; Chiba, Shunmei; Yoshikawa, Hideshi; Hashimoto, Takuo; Tadokoro, Mamoru; Suzuki, Noboru

2004-10-01

Mouse embryonic stem (ES) cells were transfected with a MASH1 expression vector and G418-resistant cells were selected. The MASH1-transfected cells became neuron-like appearance and expressed betaIIItubulin and panNCAM. Glial fibrillary acidic protein (GFAP) and galactocerebroside (GalC)-expressing cells were rarely detected. Half of the neural cells differentiated into the Islet1+ motoneuron lineage. Thus, we obtained motoneuron lineage-enriched neuronal cells by transfection of ES cells with MASH1. A hemiplegic model of mice was developed by cryogenic injury of the motor cortex, and motoneuron lineage-enriched neuronal cells were transplanted underneath the injured motor cortex neighboring the periventricular region. The motor function of the recipients was assessed by a beam walking and rotarod tests, whereby the results gradually improved, but little improvement was observed in vehicle injected control mice. We found that the grafted cells not only remained close to the implantation site, but also exhibited substantial migration, penetrating into the damaged lesion in a directed manner up to the cortical region. Grafted neuronal cells that had migrated into the cortex were elongated axon-positive for neurofilament middle chain (NFM). Synaptophysin immunostaining showed a positive staining pattern around the graft, suggesting that the transplanted neurons interacted with the recipient neurons to form a neural network. Our study suggests that the motoneuron lineage can be induced from ES cells, and grafted cells adapt to the host environment and can reconstitute a neural network to improve motor function of a paralyzed limb.

Age-dependent effects of brain stimulation on network centrality.

PubMed

Antonenko, Daria; Nierhaus, Till; Meinzer, Marcus; Prehn, Kristin; Thielscher, Axel; Ittermann, Bernd; Flöel, Agnes

2018-04-18

Functional magnetic resonance imaging (fMRI) studies have suggested that advanced age may mediate the effects of transcranial direct current stimulation (tDCS) on brain function. However, studies directly comparing neural tDCS effects between young and older adults are scarce and limited to task-related imaging paradigms. Resting-state (rs-) fMRI, that is independent of age-related differences in performance, is well suited to investigate age-associated differential neural tDCS effects. Three "online" tDCS conditions (anodal, cathodal, sham) were compared in a cross-over, within-subject design, in 30 young and 30 older adults. Active stimulation targeted the left sensorimotor network (active electrode over left sensorimotor cortex with right supraorbital reference electrode). A graph-based rs-fMRI data analysis approach (eigenvector centrality mapping) and complementary seed-based analyses characterized neural tDCS effects. An interaction between anodal tDCS and age group was observed. Specifically, centrality in bilateral paracentral and posterior regions (precuneus, superior parietal cortex) was increased in young, but decreased in older adults. Seed-based analyses revealed that these opposing patterns of tDCS-induced centrality modulation originated from differential effects of tDCS on functional coupling of the stimulated left paracentral lobule. Cathodal tDCS did not show significant effects. Our study provides first evidence for differential tDCS effects on neural network organization in young and older adults. Anodal stimulation mainly affected coupling of sensorimotor with ventromedial prefrontal areas in young and decoupling with posteromedial areas in older adults. Copyright © 2018 Elsevier Inc. All rights reserved.

Touching moments: desire modulates the neural anticipation of active romantic caress

PubMed Central

Ebisch, Sjoerd J.; Ferri, Francesca; Gallese, Vittorio

2014-01-01

A romantic caress is a basic expression of affiliative behavior and a primary reinforcer. Given its inherent affective valence, its performance also would imply the prediction of reward values. For example, touching a person for whom one has strong passionate feelings likely is motivated by a strong desire for physical contact and associated with the anticipation of hedonic experiences. The present study aims at investigating how the anticipatory neural processes of active romantic caress are modulated by the intensity of the desire for affective contact as reflected by passionate feelings for the other. Functional magnetic resonance imaging scanning was performed in romantically involved partners using a paradigm that allowed to isolate the specific anticipatory representations of active romantic caress, compared with control caress, while testing for the relationship between neural activity and measures of feelings of passionate love for the other. The results demonstrated that right posterior insula activity in anticipation of romantic caress significantly co-varied with the intensity of desire for union with the other. This effect was independent of the sensory-affective properties of the performed touch, like its pleasantness. Furthermore, functional connectivity analysis showed that the same posterior insula cluster interacted with brain regions related to sensory-motor functions as well as to the processing and anticipation of reward. The findings provide insight on the neural substrate mediating between the desire for and the performance of romantic caress. In particular, we propose that anticipatory activity patterns in posterior insula may modulate subsequent sensory-affective processing of skin-to-skin contact. PMID:24616676

Multiple mechanisms of consciousness: the neural correlates of emotional awareness.

PubMed

Amting, Jayna M; Greening, Steven G; Mitchell, Derek G V

2010-07-28

Emotional stimuli, including facial expressions, are thought to gain rapid and privileged access to processing resources in the brain. Despite this access, we are conscious of only a fraction of the myriad of emotion-related cues we face everyday. It remains unclear, therefore, what the relationship is between activity in neural regions associated with emotional representation and the phenomenological experience of emotional awareness. We used functional magnetic resonance imaging and binocular rivalry to delineate the neural correlates of awareness of conflicting emotional expressions in humans. Behaviorally, fearful faces were significantly more likely to be perceived than disgusted or neutral faces. Functionally, increased activity was observed in regions associated with facial expression processing, including the amygdala and fusiform gyrus during emotional awareness. In contrast, awareness of neutral faces and suppression of fearful faces were associated with increased activity in dorsolateral prefrontal and inferior parietal cortices. The amygdala showed increased functional connectivity with ventral visual system regions during fear awareness and increased connectivity with perigenual prefrontal cortex (pgPFC; Brodmann's area 32/10) when fear was suppressed. Despite being prioritized for awareness, emotional items were associated with reduced activity in areas considered critical for consciousness. Contributions to consciousness from bottom-up and top-down neural regions may be additive, such that increased activity in specialized regions within the extended ventral visual system may reduce demands on a frontoparietal system important for awareness. The possibility is raised that interactions between pgPFC and the amygdala, previously implicated in extinction, may also influence whether or not an emotional stimulus is accessible to consciousness.

Neural mechanisms underlying the effects of face-based affective signals on memory for faces: a tentative model

PubMed Central

Tsukiura, Takashi

2012-01-01

In our daily lives, we form some impressions of other people. Although those impressions are affected by many factors, face-based affective signals such as facial expression, facial attractiveness, or trustworthiness are important. Previous psychological studies have demonstrated the impact of facial impressions on remembering other people, but little is known about the neural mechanisms underlying this psychological process. The purpose of this article is to review recent functional MRI (fMRI) studies to investigate the effects of face-based affective signals including facial expression, facial attractiveness, and trustworthiness on memory for faces, and to propose a tentative concept for understanding this affective-cognitive interaction. On the basis of the aforementioned research, three brain regions are potentially involved in the processing of face-based affective signals. The first candidate is the amygdala, where activity is generally modulated by both affectively positive and negative signals from faces. Activity in the orbitofrontal cortex (OFC), as the second candidate, increases as a function of perceived positive signals from faces; whereas activity in the insular cortex, as the third candidate, reflects a function of face-based negative signals. In addition, neuroscientific studies have reported that the three regions are functionally connected to the memory-related hippocampal regions. These findings suggest that the effects of face-based affective signals on memory for faces could be modulated by interactions between the regions associated with the processing of face-based affective signals and the hippocampus as a memory-related region. PMID:22837740

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

PubMed

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Carbon nanotube multilayered nanocomposites as multifunctional substrates for actuating neuronal differentiation and functions of neural stem cells.

PubMed

Shao, Han; Li, Tingting; Zhu, Rong; Xu, Xiaoting; Yu, Jiandong; Chen, Shengfeng; Song, Li; Ramakrishna, Seeram; Lei, Zhigang; Ruan, Yiwen; He, Liumin

2018-08-01

Carbon nanotubes (CNTs) have shown potential applications in neuroscience as growth substrates owing to their numerous unique properties. However, a key concern in the fabrication of homogeneous composites is the serious aggregation of CNTs during incorporation into the biomaterial matrix. Moreover, the regulation mechanism of CNT-based substrates on neural differentiation remains unclear. Here, a novel strategy was introduced for the construction of CNT nanocomposites via layer-by-layer assembly of negatively charged multi-walled CNTs and positively charged poly(dimethyldiallylammonium chloride). Results demonstrated that the CNT-multilayered nanocomposites provided a potent regulatory signal over neural stem cells (NSCs), including cell adhesion, viability, differentiation, neurite outgrowth, and electrophysiological maturation of NSC-derived neurons. Importantly, the dynamic molecular mechanisms in the NSC differentiation involved the integrin-mediated interactions between NSCs and CNT multilayers, thereby activating focal adhesion kinase, subsequently triggering downstream signaling events to regulate neuronal differentiation and synapse formation. This study provided insights for future applications of CNT-multilayered nanomaterials in neural fields as potent modulators of stem cell behavior. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.

PubMed

Hanson, Jack; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

2017-03-01

Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction. The new method, named SPOT-Disorder, has steadily improved over a similar method using a traditional, window-based neural network (SPINE-D) in all datasets tested without separate training on short and long disordered regions. Independent tests on four other datasets including the datasets from critical assessment of structure prediction (CASP) techniques and >10 000 annotated proteins from MobiDB, confirmed SPOT-Disorder as one of the best methods in disorder prediction. Moreover, initial studies indicate that the method is more accurate in predicting functional sites in disordered regions. These results highlight the usefulness combining LSTM with deep bidirectional recurrent neural networks in capturing non-local, long-range interactions for bioinformatics applications. SPOT-disorder is available as a web server and as a standalone program at: http://sparks-lab.org/server/SPOT-disorder/index.php . j.hanson@griffith.edu.au or yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au. Supplementary data is available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Neural Basis of Self and Other Representation in Autism: An fMRI Study of Self-Face Recognition

PubMed Central

Uddin, Lucina Q.; Davies, Mari S.; Scott, Ashley A.; Zaidel, Eran; Bookheimer, Susan Y.; Iacoboni, Marco; Dapretto, Mirella

2008-01-01

Background Autism is a developmental disorder characterized by decreased interest and engagement in social interactions and by enhanced self-focus. While previous theoretical approaches to understanding autism have emphasized social impairments and altered interpersonal interactions, there is a recent shift towards understanding the nature of the representation of the self in individuals with autism spectrum disorders (ASD). Still, the neural mechanisms subserving self-representations in ASD are relatively unexplored. Methodology/Principal Findings We used event-related fMRI to investigate brain responsiveness to images of the subjects' own face and to faces of others. Children with ASD and typically developing (TD) children viewed randomly presented digital morphs between their own face and a gender-matched other face, and made “self/other” judgments. Both groups of children activated a right premotor/prefrontal system when identifying images containing a greater percentage of the self face. However, while TD children showed activation of this system during both self- and other-processing, children with ASD only recruited this system while viewing images containing mostly their own face. Conclusions/Significance This functional dissociation between the representation of self versus others points to a potential neural substrate for the characteristic self-focus and decreased social understanding exhibited by these individuals, and suggests that individuals with ASD lack the shared neural representations for self and others that TD children and adults possess and may use to understand others. PMID:18958161

Combining Computational Modeling and Neuroimaging to Examine Multiple Category Learning Systems in the Brain

PubMed Central

Nomura, Emi M.; Reber, Paul J.

2012-01-01

Considerable evidence has argued in favor of multiple neural systems supporting human category learning, one based on conscious rule inference and one based on implicit information integration. However, there have been few attempts to study potential system interactions during category learning. The PINNACLE (Parallel Interactive Neural Networks Active in Category Learning) model incorporates multiple categorization systems that compete to provide categorization judgments about visual stimuli. Incorporating competing systems requires inclusion of cognitive mechanisms associated with resolving this competition and creates a potential credit assignment problem in handling feedback. The hypothesized mechanisms make predictions about internal mental states that are not always reflected in choice behavior, but may be reflected in neural activity. Two prior functional magnetic resonance imaging (fMRI) studies of category learning were re-analyzed using PINNACLE to identify neural correlates of internal cognitive states on each trial. These analyses identified additional brain regions supporting the two types of category learning, regions particularly active when the systems are hypothesized to be in maximal competition, and found evidence of covert learning activity in the “off system” (the category learning system not currently driving behavior). These results suggest that PINNACLE provides a plausible framework for how competing multiple category learning systems are organized in the brain and shows how computational modeling approaches and fMRI can be used synergistically to gain access to cognitive processes that support complex decision-making machinery. PMID:24962771

A Social-Interactive Neuroscience Approach to Understanding the Developing Brain.

PubMed

Redcay, Elizabeth; Warnell, Katherine Rice

2018-01-01

From birth onward, social interaction is central to our everyday lives. Our ability to seek out social partners, flexibly navigate and learn from social interactions, and develop social relationships is critically important for our social and cognitive development and for our mental and physical health. Despite the importance of our social interactions, the neurodevelopmental bases of such interactions are underexplored, as most research examines social processing in noninteractive contexts. We begin this chapter with evidence from behavioral work and adult neuroimaging studies demonstrating how social-interactive context fundamentally alters cognitive and neural processing. We then highlight four brain networks that play key roles in social interaction and, drawing on existing developmental neuroscience literature, posit the functional roles these networks may play in social-interactive development. We conclude by discussing how a social-interactive neuroscience approach holds great promise for advancing our understanding of both typical and atypical social development. © 2018 Elsevier Inc. All rights reserved.

[Measurement and performance analysis of functional neural network].

PubMed

Li, Shan; Liu, Xinyu; Chen, Yan; Wan, Hong

2018-04-01

The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.

Intrinsic functional connectivity underlying successful emotion regulation of angry faces

PubMed Central

Morawetz, Carmen; Kellermann, Tanja; Kogler, Lydia; Radke, Sina; Blechert, Jens; Derntl, Birgit

2016-01-01

Most of our social interaction is naturally based on emotional information derived from the perception of faces of other people. Negative facial expressions of a counterpart might trigger negative emotions and initiate emotion regulatory efforts to reduce the impact of the received emotional message in a perceiver. Despite the high adaptive value of emotion regulation in social interaction, the neural underpinnings of it are largely unknown. To remedy this, this study investigated individual differences in emotion regulation effectiveness during the reappraisal of angry faces on the underlying functional activity using functional magnetic resonance imaging (fMRI) as well as the underlying functional connectivity using resting-state fMRI. Greater emotion regulation ability was associated with greater functional activity in the ventromedial prefrontal cortex. Furthermore, greater functional coupling between activity in the ventrolateral prefrontal cortex and the amygdala was associated with emotion regulation success. Our findings provide a first link between prefrontal cognitive control and subcortical emotion processing systems during successful emotion regulation in an explicitly social context. PMID:27510495

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural mechanisms tracking popularity in real-world social networks.

PubMed

Zerubavel, Noam; Bearman, Peter S; Weber, Jochen; Ochsner, Kevin N

2015-12-08

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.

Age-related differences in the neural bases of phonological and semantic processes

PubMed Central

Diaz, Michele T.; Johnson, Micah A.; Burke, Deborah M.; Madden, David J.

2014-01-01

Changes in language functions during normal aging are greater for phonological compared to semantic processes. To investigate the behavioral and neural basis for these age-related differences, we used functional magnetic resonance imaging (fMRI) to examine younger and older adults who made semantic and phonological decisions about pictures. The behavioral performance of older adults was less accurate and less efficient than younger adults’ in the phonological task, but did not differ in the semantic task. In the fMRI analyses, the semantic task activated left-hemisphere language regions, while the phonological task activated bilateral cingulate and ventral precuneus. Age-related effects were widespread throughout the brain, and most often expressed as greater activation for older adults. Activation was greater for younger compared to older adults in ventral brain regions involved in visual and object processing. Although there was not a significant Age x Condition interaction in the whole-brain fMRI results, correlations examining the relationship between behavior and fMRI activation were stronger for younger compared to older adults. Our results suggest that the relationship between behavior and neural activation declines with age and this may underlie some of the observed declines in performance. PMID:24893737

Mindfulness and dynamic functional neural connectivity in children and adolescents.

PubMed

Marusak, Hilary A; Elrahal, Farrah; Peters, Craig A; Kundu, Prantik; Lombardo, Michael V; Calhoun, Vince D; Goldberg, Elimelech K; Cohen, Cindy; Taub, Jeffrey W; Rabinak, Christine A

2018-01-15

Interventions that promote mindfulness consistently show salutary effects on cognition and emotional wellbeing in adults, and more recently, in children and adolescents. However, we lack understanding of the neurobiological mechanisms underlying mindfulness in youth that should allow for more judicious application of these interventions in clinical and educational settings. Using multi-echo multi-band fMRI, we examined dynamic (i.e., time-varying) and conventional static resting-state connectivity between core neurocognitive networks (i.e., salience/emotion, default mode, central executive) in 42 children and adolescents (ages 6-17). We found that trait mindfulness in youth relates to dynamic but not static resting-state connectivity. Specifically, more mindful youth transitioned more between brain states over the course of the scan, spent overall less time in a certain connectivity state, and showed a state-specific reduction in connectivity between salience/emotion and central executive networks. The number of state transitions mediated the link between higher mindfulness and lower anxiety, providing new insights into potential neural mechanisms underlying benefits of mindfulness on psychological health in youth. Our results provide new evidence that mindfulness in youth relates to functional neural dynamics and interactions between neurocognitive networks, over time. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural correlates of naturalistic social cognition: brain-behavior relationships in healthy adults.

PubMed

Deuse, L; Rademacher, L M; Winkler, L; Schultz, R T; Gründer, G; Lammertz, S E

2016-11-01

Being able to infer the thoughts, feelings and intentions of those around us is indispensable in order to function in a social world. Despite growing interest in social cognition and its neural underpinnings, the factors that contribute to successful mental state attribution remain unclear. Current knowledge is limited because the most widely used tasks suffer from two main constraints: (i) They fail to capture individual variability due to ceiling effects and (ii) they use highly simplistic, often artificial stimuli inapt to mirror real-world socio-cognitive demands. In the present study, we address these problems by employing complex depictions of naturalistic social interactions that vary in both valence (positive vs negative) and ambiguity (high vs low). Thirty-eight healthy participants (20 female) made mental state judgments while brain responses were obtained using functional magnetic resonance imaging (fMRI). Accuracy varied based on valence and ambiguity conditions and women were more accurate than men with highly ambiguous social stimuli. Activity of the orbitofrontal cortex predicted performance in the high ambiguity condition. The results shed light on subtle differences in mentalizing abilities and associated neural activity. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Performance monitoring in the medial frontal cortex and related neural networks: From monitoring self actions to understanding others' actions.

PubMed

Ninomiya, Taihei; Noritake, Atsushi; Ullsperger, Markus; Isoda, Masaki

2018-04-27

Action is a key channel for interacting with the outer world. As such, the ability to monitor actions and their consequences - regardless as to whether they are self-generated or other-generated - is of crucial importance for adaptive behavior. The medial frontal cortex (MFC) has long been studied as a critical node for performance monitoring in nonsocial contexts. Accumulating evidence suggests that the MFC is involved in a wide range of functions necessary for one's own performance monitoring, including error detection, and monitoring and resolving response conflicts. Recent studies, however, have also pointed to the importance of the MFC in performance monitoring under social conditions, ranging from monitoring and understanding others' actions to reading others' mental states, such as their beliefs and intentions (i.e., mentalizing). Here we review the functional roles of the MFC and related neural networks in performance monitoring in both nonsocial and social contexts, with an emphasis on the emerging field of a social systems neuroscience approach using macaque monkeys as a model system. Future work should determine the way in which the MFC exerts its monitoring function via interactions with other brain regions, such as the superior temporal sulcus in the mentalizing system and the ventral premotor cortex in the mirror system. Copyright © 2018. Published by Elsevier B.V.

Adult Restoration of Shank3 Expression Rescues Selective Autistic-Like Phenotypes

PubMed Central

Mei, Yuan; Monteiro, Patricia; Zhou, Yang; Kim, Jin-Ah; Gao, Xian; Fu, Zhanyan; Feng, Guoping

2016-01-01

Because ASD is a neurodevelopmental disorder and patients typically display symptoms before the age of three1, one of the key questions in autism research is whether the pathology is reversible in adults. Here we investigated the developmental requirement of Shank3, one of the most prominent monogenic ASD genes that is estimated to contribute to ~1% of all ASD cases2–6. SHANK3 is a postsynaptic scaffold protein that regulates synaptic development, function and plasticity by orchestrating the assembly of postsynaptic density (PSD) macromolecular signaling complex7–9. Disruptions of the Shank3 gene in mouse models have resulted in synaptic defects and autistic-like behaviors including anxiety, social interaction deficits, and repetitive behavior10–13. We generated a novel Shank3 conditional knock-in mouse model and used it to demonstrate that re-expression of the Shank3 gene in adult led to improvements in synaptic protein composition, spine density and neural function in the striatum. We also provided behavioral evidence that certain behavioral abnormalities including social interaction deficit and repetitive grooming behavior could be rescued, while anxiety and motor coordination deficit could not be recovered in adulthood. Together, these results elucidate the profound impact of post-developmental activation of Shank3 expression on neural function and demonstrate certain degree of continued plasticity in the adult diseased brain. PMID:26886798

Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

NASA Astrophysics Data System (ADS)

Georgopoulos, Apostolos P.; Karageorgiou, Elissaios; Leuthold, Arthur C.; Lewis, Scott M.; Lynch, Joshua K.; Alonso, Aurelio A.; Aslam, Zaheer; Carpenter, Adam F.; Georgopoulos, Angeliki; Hemmy, Laura S.; Koutlas, Ioannis G.; Langheim, Frederick J. P.; Riley McCarten, J.; McPherson, Susan E.; Pardo, José V.; Pardo, Patricia J.; Parry, Gareth J.; Rottunda, Susan J.; Segal, Barbara M.; Sponheim, Scott R.; Stanwyck, John J.; Stephane, Massoud; Westermeyer, Joseph J.

2007-12-01

We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCCij0) and their z-transforms (zij0) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of zij0 successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results. Contribution by the authors: Designed research (APG); acquired data (AAA, IGK, FJPL, ACL, SML, JJS); analyzed data (APG, EK, ACL, JKL); wrote the paper (APG, EK, ACL, SML); contributed subjects (AAA, ZA, AFC, AG, LSH, IGK, FJPL, SML, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW); discussed results (All); contributed equally (ZA, AFC, AG, LSH, FJPL, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW).

Adaptive coding of the value of social cues with oxytocin, an fMRI study in autism spectrum disorder.

PubMed

Andari, Elissar; Richard, Nathalie; Leboyer, Marion; Sirigu, Angela

2016-03-01

The neuropeptide oxytocin (OT) is one of the major targets of research in neuroscience, with respect to social functioning. Oxytocin promotes social skills and improves the quality of face processing in individuals with social dysfunctions such as autism spectrum disorder (ASD). Although one of OT's key functions is to promote social behavior during dynamic social interactions, the neural correlates of this function remain unknown. Here, we combined acute intranasal OT (IN-OT) administration (24 IU) and fMRI with an interactive ball game and a face-matching task in individuals with ASD (N = 20). We found that IN-OT selectively enhanced the brain activity of early visual areas in response to faces as compared to non-social stimuli. OT inhalation modulated the BOLD activity of amygdala and hippocampus in a context-dependent manner. Interestingly, IN-OT intake enhanced the activity of mid-orbitofrontal cortex in response to a fair partner, and insula region in response to an unfair partner. These OT-induced neural responses were accompanied by behavioral improvements in terms of allocating appropriate feelings of trust toward different partners' profiles. Our findings suggest that OT impacts the brain activity of key areas implicated in attention and emotion regulation in an adaptive manner, based on the value of social cues. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural signatures of the response to emotional distraction: a review of evidence from brain imaging investigations

PubMed Central

Iordan, A. D.; Dolcos, S.; Dolcos, F.

2013-01-01

Prompt responses to emotional, potentially threatening, stimuli are supported by neural mechanisms that allow for privileged access of emotional information to processing resources. The existence of these mechanisms can also make emotional stimuli potent distracters, particularly when task-irrelevant. The ability to deploy cognitive control in order to cope with emotional distraction is essential for adaptive behavior, while reduced control may lead to enhanced emotional distractibility, which is often a hallmark of affective disorders. Evidence suggests that increased susceptibility to emotional distraction is linked to changes in the processing of emotional information that affect both the basic response to and coping with emotional distraction, but the neural correlates of these phenomena are not clear. The present review discusses emerging evidence from brain imaging studies addressing these issues, and highlights the following three aspects. First, the response to emotional distraction is associated with opposing patterns of activity in a ventral “hot” affective system (HotEmo, showing increased activity) and a dorsal “cold” executive system (ColdEx, showing decreased activity). Second, coping with emotional distraction involves top–down control in order to counteract the bottom-up influence of emotional distraction, and involves interactions between the amygdala and the prefrontal cortex. Third, both the response to and coping with emotional distraction are influenced by individual differences affecting emotional sensitivity and distractibility, which are linked to alterations of both HotEmo and ColdEx neural systems. Collectively, the available evidence identifies specific neural signatures of the response to emotional challenge, which are fundamental to understanding the mechanisms of emotion-cognition interactions in healthy functioning, and the changes linked to individual variation in emotional distractibility and susceptibility to affective disorders. PMID:23761741

A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

PubMed Central

Ross, James D.; Cullen, D. Kacy; Harris, James P.; LaPlaca, Michelle C.; DeWeerth, Stephen P.

2015-01-01

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions. PMID:26257609

A Cognitive Neural Architecture Able to Learn and Communicate through Natural Language.

PubMed

Golosio, Bruno; Cangelosi, Angelo; Gamotina, Olesya; Masala, Giovanni Luca

2015-01-01

Communicative interactions involve a kind of procedural knowledge that is used by the human brain for processing verbal and nonverbal inputs and for language production. Although considerable work has been done on modeling human language abilities, it has been difficult to bring them together to a comprehensive tabula rasa system compatible with current knowledge of how verbal information is processed in the brain. This work presents a cognitive system, entirely based on a large-scale neural architecture, which was developed to shed light on the procedural knowledge involved in language elaboration. The main component of this system is the central executive, which is a supervising system that coordinates the other components of the working memory. In our model, the central executive is a neural network that takes as input the neural activation states of the short-term memory and yields as output mental actions, which control the flow of information among the working memory components through neural gating mechanisms. The proposed system is capable of learning to communicate through natural language starting from tabula rasa, without any a priori knowledge of the structure of phrases, meaning of words, role of the different classes of words, only by interacting with a human through a text-based interface, using an open-ended incremental learning process. It is able to learn nouns, verbs, adjectives, pronouns and other word classes, and to use them in expressive language. The model was validated on a corpus of 1587 input sentences, based on literature on early language assessment, at the level of about 4-years old child, and produced 521 output sentences, expressing a broad range of language processing functionalities.

Abnormal relationships between the neural response to high- and low-calorie foods and endogenous acylated ghrelin in women with active and weight-recovered anorexia nervosa.

PubMed

Holsen, Laura M; Lawson, Elizabeth A; Christensen, Kara; Klibanski, Anne; Goldstein, Jill M

2014-08-30

Evidence contributing to the understanding of neurobiological mechanisms underlying appetite dysregulation in anorexia nervosa draws heavily on separate lines of research into neuroendocrine and neural circuitry functioning. In particular, studies consistently cite elevated ghrelin and abnormal activation patterns in homeostatic (hypothalamus) and hedonic (striatum, amygdala, insula) regions governing appetite. The current preliminary study examined the interaction of these systems, based on research demonstrating associations between circulating ghrelin levels and activity in these regions in healthy individuals. In a cross-sectional design, we studied 13 women with active anorexia nervosa (AN), 9 women weight-recovered from AN (AN-WR), and 12 healthy-weight control women using a food cue functional magnetic resonance imaging paradigm, with assessment of fasting levels of acylated ghrelin. Healthy-weight control women exhibited significant positive associations between fasting acylated ghrelin and activity in the right amygdala, hippocampus, insula, and orbitofrontal cortex in response to high-calorie foods, associations which were absent in the AN and AN-WR groups. Women with AN-WR demonstrated a negative relationship between ghrelin and activity in the left hippocampus in response to high-calorie foods, while women with AN showed a positive association between ghrelin and activity in the right orbitofrontal cortex in response to low-calorie foods. Findings suggest a breakdown in the interaction between ghrelin signaling and neural activity in relation to reward responsivity in AN, a phenomenon that may be further characterized using pharmacogenetic studies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

CRHR1 genotypes, neural circuits and the diathesis for anxiety and depression.

PubMed

Rogers, J; Raveendran, M; Fawcett, G L; Fox, A S; Shelton, S E; Oler, J A; Cheverud, J; Muzny, D M; Gibbs, R A; Davidson, R J; Kalin, N H

2013-06-01

The corticotrophin-releasing hormone (CRH) system integrates the stress response and is associated with stress-related psychopathology. Previous reports have identified interactions between childhood trauma and sequence variation in the CRH receptor 1 gene (CRHR1) that increase risk for affective disorders. However, the underlying mechanisms that connect variation in CRHR1 to psychopathology are unknown. To explore potential mechanisms, we used a validated rhesus macaque model to investigate association between genetic variation in CRHR1, anxious temperament (AT) and brain metabolic activity. In young rhesus monkeys, AT is analogous to the childhood risk phenotype that predicts the development of human anxiety and depressive disorders. Regional brain metabolism was assessed with (18)F-labeled fluoro-2-deoxyglucose (FDG) positron emission tomography in 236 young, normally reared macaques that were also characterized for AT. We show that single nucleotide polymorphisms (SNPs) affecting exon 6 of CRHR1 influence both AT and metabolic activity in the anterior hippocampus and amygdala, components of the neural circuit underlying AT. We also find evidence for association between SNPs in CRHR1 and metabolism in the intraparietal sulcus and precuneus. These translational data suggest that genetic variation in CRHR1 affects the risk for affective disorders by influencing the function of the neural circuit underlying AT and that differences in gene expression or the protein sequence involving exon 6 may be important. These results suggest that variation in CRHR1 may influence brain function before any childhood adversity and may be a diathesis for the interaction between CRHR1 genotypes and childhood trauma reported to affect human psychopathology.

An on-line BCI for control of hand grasp sequence and holding using adaptive probabilistic neural network.

PubMed

Hazrati, Mehrnaz Kh; Erfanian, Abbas

2008-01-01

This paper presents a new EEG-based Brain-Computer Interface (BCI) for on-line controlling the sequence of hand grasping and holding in a virtual reality environment. The goal of this research is to develop an interaction technique that will allow the BCI to be effective in real-world scenarios for hand grasp control. Moreover, for consistency of man-machine interface, it is desirable the intended movement to be what the subject imagines. For this purpose, we developed an on-line BCI which was based on the classification of EEG associated with imagination of the movement of hand grasping and resting state. A classifier based on probabilistic neural network (PNN) was introduced for classifying the EEG. The PNN is a feedforward neural network that realizes the Bayes decision discriminant function by estimating probability density function using mixtures of Gaussian kernels. Two types of classification schemes were considered here for on-line hand control: adaptive and static. In contrast to static classification, the adaptive classifier was continuously updated on-line during recording. The experimental evaluation on six subjects on different days demonstrated that by using the static scheme, a classification accuracy as high as the rate obtained by the adaptive scheme can be achieved. At the best case, an average classification accuracy of 93.0% and 85.8% was obtained using adaptive and static scheme, respectively. The results obtained from more than 1500 trials on six subjects showed that interactive virtual reality environment can be used as an effective tool for subject training in BCI.

Neurodevelopmental Hypothesis about the Etiology of Autism Spectrum Disorders

PubMed Central

Inui, Toshio; Kumagaya, Shinichiro; Myowa-Yamakoshi, Masako

2017-01-01

Previous models or hypotheses of autism spectral disorder (ASD) failed to take into full consideration the chronological and causal developmental trajectory, leading to the emergence of diverse phenotypes through a complex interaction between individual etiologies and environmental factors. Those phenotypes include persistent deficits in social communication and social interaction (criteria A in DSM-5), and restricted, repetitive patterns of behavior, interests, or activities (criteria B in DSM-5). In this article, we proposed a domain-general model that can explain criteria in DSM-5 based on the assumption that the same etiological mechanism would trigger the various phenotypes observed in different individuals with ASD. In the model, we assumed the following joint causes as the etiology of autism: (1) Hypoplasia of the pons in the brainstem, occurring immediately following neural tube closure; and (2) Deficiency in the GABA (γ-aminobutyric acid) developmental switch during the perinatal period. Microstructural abnormalities of the pons directly affect both the structural and functional development of the brain areas strongly connected to it, especially amygdala. The impairment of GABA switch could not only lead to the deterioration of inhibitory processing in the neural network, but could also cause abnormal cytoarchitecture. We introduced a perspective that atypical development in both brain structure and function can give full explanation of diverse phenotypes and pathogenetic mechanism of ASD. Finally, we discussed about neural mechanisms underlying the phenotypic characteristics of ASD that are not described in DSM-5 but should be considered as important foundation: sleep, global precedence, categorical perception, intelligence, interoception and motor control. PMID:28744208

Abnormal regional activity and functional connectivity in resting-state brain networks associated with etiology confirmed unilateral pulsatile tinnitus in the early stage of disease.

PubMed

Lv, Han; Zhao, Pengfei; Liu, Zhaohui; Li, Rui; Zhang, Ling; Wang, Peng; Yan, Fei; Liu, Liheng; Wang, Guopeng; Zeng, Rong; Li, Ting; Dong, Cheng; Gong, Shusheng; Wang, Zhenchang

2017-03-01

Abnormal neural activities can be revealed by resting-state functional magnetic resonance imaging (rs-fMRI) using analyses of the regional activity and functional connectivity (FC) of the networks in the brain. This study was designed to demonstrate the functional network alterations in the patients with pulsatile tinnitus (PT). In this study, we recruited 45 patients with unilateral PT in the early stage of disease (less than 48 months of disease duration) and 45 normal controls. We used regional homogeneity (ReHo) and seed-based FC computational methods to reveal resting-state brain activity features associated with pulsatile tinnitus. Compared with healthy controls, PT patients showed regional abnormalities mainly in the left middle occipital gyrus (MOG), posterior cingulate gyrus (PCC), precuneus and right anterior insula (AI). When these regions were defined as seeds, we demonstrated widespread modification of interaction between the auditory and non-auditory networks. The auditory network was positively connected with the cognitive control network (CCN), which may associate with tinnitus related distress. Both altered regional activity and changed FC were found in the visual network. The modification of interactions of higher order networks were mainly found in the DMN, CCN and limbic networks. Functional connectivity between the left MOG and left parahippocampal gyrus could also be an index to reflect the disease duration. This study helped us gain a better understanding of the characteristics of neural network modifications in patients with pulsatile tinnitus. Copyright © 2017 Elsevier B.V. All rights reserved.

Folate receptor 1 is necessary for neural plate cell apical constriction during Xenopus neural tube formation

PubMed Central

Balashova, Olga A.; Visina, Olesya

2017-01-01

Folate supplementation prevents up to 70% of neural tube defects (NTDs), which result from a failure of neural tube closure during embryogenesis. The elucidation of the mechanisms underlying folate action has been challenging. This study introduces Xenopus laevis as a model to determine the cellular and molecular mechanisms involved in folate action during neural tube formation. We show that knockdown of folate receptor 1 (Folr1; also known as FRα) impairs neural tube formation and leads to NTDs. Folr1 knockdown in neural plate cells only is necessary and sufficient to induce NTDs. Folr1-deficient neural plate cells fail to constrict, resulting in widening of the neural plate midline and defective neural tube closure. Pharmacological inhibition of folate action by methotrexate during neurulation induces NTDs by inhibiting folate interaction with its uptake systems. Our findings support a model in which the folate receptor interacts with cell adhesion molecules, thus regulating the apical cell membrane remodeling and cytoskeletal dynamics necessary for neural plate folding. Further studies in this organism could unveil novel cellular and molecular events mediated by folate and lead to new ways of preventing NTDs. PMID:28255006

Interactions between the nucleus accumbens and auditory cortices predict music reward value.

PubMed

Salimpoor, Valorie N; van den Bosch, Iris; Kovacevic, Natasa; McIntosh, Anthony Randal; Dagher, Alain; Zatorre, Robert J

2013-04-12

We used functional magnetic resonance imaging to investigate neural processes when music gains reward value the first time it is heard. The degree of activity in the mesolimbic striatal regions, especially the nucleus accumbens, during music listening was the best predictor of the amount listeners were willing to spend on previously unheard music in an auction paradigm. Importantly, the auditory cortices, amygdala, and ventromedial prefrontal regions showed increased activity during listening conditions requiring valuation, but did not predict reward value, which was instead predicted by increasing functional connectivity of these regions with the nucleus accumbens as the reward value increased. Thus, aesthetic rewards arise from the interaction between mesolimbic reward circuitry and cortical networks involved in perceptual analysis and valuation.

Microcrack Quantification in Composite Materials by a Neural Network Analysis of Ultrasound Spectral Data

NASA Technical Reports Server (NTRS)

Walker, James L.; Russell, Samuel S.; Suits, Michael W.

2003-01-01

Intra-ply microcracking in unlined composite pressure vessels can be very troublesome to detect and when linked through the thickness can provide leak paths that may hinder mission success. The leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping into air pockets within the laminate. Ultrasonic techniques have been shown capable of detecting the presence of microcracking and in this work they are used to quantify the level of microcracking. Resonance ultrasound methods are utilized with artificial neural networks to build a microcrack prediction/measurement tool. Two networks are presented, one unsupervised to provide a qualitative measure of microcracking and one supervised which provides a quantitative assessment of the level of microcracking. The resonant ultrasound spectroscopic method is made sensitive to microcracking by tuning the input spectrum to the higher frequency (shorter wavelength) components allowing more significant interaction with the defects. This interaction causes the spectral characteristics to shift toward lower amplitudes at the higher frequencies. As the density of the defects increases more interactions occur and more drastic amplitude changes are observed. Preliminary experiments to quantify the level of microcracking induced in graphite/epoxy composite samples through a combination of tensile loading and cryogenic temperatures are presented. Both unsupervised (Kohonen) and supervised (radial basis function) artificial neural networks are presented to determine the measurable effect on the resonance spectrum of the ultrasonic data taken from the samples.

Children's Elementary School Social Experience and Executive Functions Development: Introduction to a Special Section.

PubMed

van Lier, Pol A C; Deater-Deckard, Kirby

2016-01-01

Children's executive functions, encompassing inhibitory control, working memory and attention are vital for their self-regulation. With the transition to formal schooling, children need to learn to manage their emotions and behavior in a new and complex social environment that with age increases in the intensity of social interactions with peers and teachers. Stronger executive functions skills facilitate children's social development. In addition, new experiences in the social environments of school also may influence executive function development. The focus of this special section is on this potential impact of elementary school social experiences with peers and teacher on the development of children's executive functions. The collection of papers encompass various aspects of peer and teacher social environments, and cover broad as well as specific facets and measures of executive functions including neural responses. The collection of papers sample developmental periods that span preschool through mid-adolescence. In this introduction, we summarize and highlight the main findings of each of the papers, organized around social interactions with peers and interactions with teachers. We conclude our synopsis with implications for future research, and a specific focus on prevention and intervention.

Alcohol and Drug Use and the Developing Brain

PubMed Central

Gray, Kevin M.

2016-01-01

Adolescence is an important neurodevelopmental period marked by rapidly escalating rates of alcohol and drug use. Over the past decade, research has attempted to disentangle pre- and post-substance use effects on brain development by using sophisticated longitudinal designs. This review focuses on recent, prospective studies and addresses the following important questions: (1) what neuropsychological and neural features predate adolescent substance use, making youth more vulnerable to engage in heavy alcohol or drug use, and (2) how does heavy alcohol and drug use affect normal neural development and cognitive functioning? Findings suggest that pre-existing neural features that relate to increased substance use during adolescence include poorer neuropsychological functioning on tests of inhibition and working memory, smaller gray and white matter volume, changes in white matter integrity, and altered brain activation during inhibition, working memory, reward, and resting state. After substance use is initiated, alcohol and marijuana use are associated with poorer cognitive functioning on tests of verbal memory, visuospatial functioning, psychomotor speed, working memory, attention, cognitive control, and overall IQ. Heavy alcohol use during adolescence is related to accelerated decreases in gray matter and attenuated increases in white matter volume, as well as increased brain activation during tasks of inhibition and working memory, relative to controls. Larger longitudinal studies with more diverse samples are needed to better understand the interactive effects of alcohol, marijuana, and other substances, as well as the role of sex, co-occurring psychopathology, genetics, sleep, and age of initiation on substance use. PMID:26984684

The Effects of Pharmacological Opioid Blockade on Neural Measures of Drug Cue-Reactivity in Humans.

PubMed

Courtney, Kelly E; Ghahremani, Dara G; Ray, Lara A

2016-11-01

Interactions between dopaminergic and opioidergic systems have been implicated in the reinforcing properties of drugs of abuse. The present study investigated the effects of opioid blockade, via naltrexone, on functional magnetic resonance imaging (fMRI) measures during methamphetamine cue-reactivity to elucidate the role of endogenous opioids in the neural systems underlying drug craving. To investigate this question, non-treatment seeking individuals with methamphetamine use disorder (N=23; 74% male, mean age=34.70 (SD=8.95)) were recruited for a randomized, placebo controlled, within-subject design and underwent a visual methamphetamine cue-reactivity task during two blood-oxygen-level dependent (BOLD) fMRI sessions following 3 days of naltrexone (50 mg) and matched time for placebo. fMRI analyses tested naltrexone-induced differences in BOLD activation and functional connectivity during cue processing. The results showed that naltrexone administration reduced cue-reactivity in sensorimotor regions and related to altered functional connectivity of dorsal striatum, ventral tegmental area, and precuneus with frontal, visual, sensory, and motor-related regions. Naltrexone also weakened the associations between subjective craving and precuneus functional connectivity with sensorimotor regions and strengthened the associations between subjective craving and dorsal striatum and precuneus connectivity with frontal regions. In conclusion, this study provides the first evidence that opioidergic blockade alters neural responses to drug cues in humans with methamphetamine addiction and suggests that naltrexone may be reducing drug cue salience by decreasing the involvement of sensorimotor regions and by engaging greater frontal regulation over salience attribution.

Co-ordinated structural and functional covariance in the adolescent brain underlies face processing performance

PubMed Central

Joel Shaw, Daniel; Mareček, Radek; Grosbras, Marie-Helene; Leonard, Gabriel; Bruce Pike, G.

2016-01-01

Our ability to process complex social cues presented by faces improves during adolescence. Using multivariate analyses of neuroimaging data collected longitudinally from a sample of 38 adolescents (17 males) when they were 10, 11.5, 13 and 15 years old, we tested the possibility that there exists parallel variations in the structural and functional development of neural systems supporting face processing. By combining measures of task-related functional connectivity and brain morphology, we reveal that both the structural covariance and functional connectivity among ‘distal’ nodes of the face-processing network engaged by ambiguous faces increase during this age range. Furthermore, we show that the trajectory of increasing functional connectivity between the distal nodes occurs in tandem with the development of their structural covariance. This demonstrates a tight coupling between functional and structural maturation within the face-processing network. Finally, we demonstrate that increased functional connectivity is associated with age-related improvements of face-processing performance, particularly in females. We suggest that our findings reflect greater integration among distal elements of the neural systems supporting the processing of facial expressions. This, in turn, might facilitate an enhanced extraction of social information from faces during a time when greater importance is placed on social interactions. PMID:26772669

Lateral hypothalamus, nucleus accumbens, and ventral pallidum roles in eating and hunger: interactions between homeostatic and reward circuitry

PubMed Central

Castro, Daniel C.; Cole, Shannon L.; Berridge, Kent C.

2015-01-01

The study of the neural bases of eating behavior, hunger, and reward has consistently implicated the lateral hypothalamus (LH) and its interactions with mesocorticolimbic circuitry, such as mesolimbic dopamine projections to nucleus accumbens (NAc) and ventral pallidum (VP), in controlling motivation to eat. The NAc and VP play special roles in mediating the hedonic impact (“liking”) and motivational incentive salience (“wanting”) of food rewards, and their interactions with LH help permit regulatory hunger/satiety modulation of food motivation and reward. Here, we review some progress that has been made regarding this circuitry and its functions: the identification of localized anatomical hedonic hotspots within NAc and VP for enhancing hedonic impact; interactions of NAc/VP hedonic hotspots with specific LH signals such as orexin; an anterior-posterior gradient of sites in NAc shell for producing intense appetitive eating vs. intense fearful reactions; and anatomically distributed appetitive functions of dopamine and mu opioid signals in NAc shell and related structures. Such findings help improve our understanding of NAc, VP, and LH interactions in mediating affective and motivation functions, including “liking” and “wanting” for food rewards. PMID:26124708

Brain basis of communicative actions in language

PubMed Central

Egorova, Natalia; Shtyrov, Yury; Pulvermüller, Friedemann

2016-01-01

Although language is a key tool for communication in social interaction, most studies in the neuroscience of language have focused on language structures such as words and sentences. Here, the neural correlates of speech acts, that is, the actions performed by using language, were investigated with functional magnetic resonance imaging (fMRI). Participants were shown videos, in which the same critical utterances were used in different communicative contexts, to Name objects, or to Request them from communication partners. Understanding of critical utterances as Requests was accompanied by activation in bilateral premotor, left inferior frontal and temporo-parietal cortical areas known to support action-related and social interactive knowledge. Naming, however, activated the left angular gyrus implicated in linking information about word forms and related reference objects mentioned in critical utterances. These findings show that understanding of utterances as different communicative actions is reflected in distinct brain activation patterns, and thus suggest different neural substrates for different speech act types. PMID:26505303

Brain basis of communicative actions in language.

PubMed

Egorova, Natalia; Shtyrov, Yury; Pulvermüller, Friedemann

2016-01-15

Although language is a key tool for communication in social interaction, most studies in the neuroscience of language have focused on language structures such as words and sentences. Here, the neural correlates of speech acts, that is, the actions performed by using language, were investigated with functional magnetic resonance imaging (fMRI). Participants were shown videos, in which the same critical utterances were used in different communicative contexts, to Name objects, or to Request them from communication partners. Understanding of critical utterances as Requests was accompanied by activation in bilateral premotor, left inferior frontal and temporo-parietal cortical areas known to support action-related and social interactive knowledge. Naming, however, activated the left angular gyrus implicated in linking information about word forms and related reference objects mentioned in critical utterances. These findings show that understanding of utterances as different communicative actions is reflected in distinct brain activation patterns, and thus suggest different neural substrates for different speech act types. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars

NASA Astrophysics Data System (ADS)

Boucenna, Sofiane; Cohen, David; Meltzoff, Andrew N.; Gaussier, Philippe; Chetouani, Mohamed

2016-02-01

Prior to language, human infants are prolific imitators. Developmental science grounds infant imitation in the neural coding of actions, and highlights the use of imitation for learning from and about people. Here, we used computational modeling and a robot implementation to explore the functional value of action imitation. We report 3 experiments using a mutual imitation task between robots, adults, typically developing children, and children with Autism Spectrum Disorder. We show that a particular learning architecture - specifically one combining artificial neural nets for (i) extraction of visual features, (ii) the robot’s motor internal state, (iii) posture recognition, and (iv) novelty detection - is able to learn from an interactive experience involving mutual imitation. This mutual imitation experience allowed the robot to recognize the interactive agent in a subsequent encounter. These experiments using robots as tools for modeling human cognitive development, based on developmental theory, confirm the promise of developmental robotics. Additionally, findings illustrate how person recognition may emerge through imitative experience, intercorporeal mapping, and statistical learning.

Circles of Engagement: Childhood Pain and Parent Brain

PubMed Central

Simons, Laura; Goubert, Liesbet; Vervoort, Tine; Borsook, David

2016-01-01

Social interaction can have a profound effect on individual behavior, perhaps most salient in interactions between sick suffering children and their parents. Chronic pain is a difficult condition that can produce considerable changes in behaviors in children that can secondarily have profound effects on their parents. It may create a functionally disabling negative feedback loop. Research supports the notion of alterations in the brain of individuals who observe and empathize with loved ones in acute pain. However, neural activity in relation to empathic responses in the context of chronic pain has not been examined. Ongoing suffering with chronic pain in a child can result in child's brain circuit alterations. However, prolonged suffering jointly experienced by the parent may putatively also produce maladaptive changes in their neural networks and consequently in parental behaviors. Here we put forth the conceptual framework for ‘Chronic pain contagion’ (CPC). We review the underlying processes in CPC and we discuss implications for devising and implementing treatments for children in chronic pain and their parents. PMID:27320958

Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars

PubMed Central

Boucenna, Sofiane; Cohen, David; Meltzoff, Andrew N.; Gaussier, Philippe; Chetouani, Mohamed

2016-01-01

Prior to language, human infants are prolific imitators. Developmental science grounds infant imitation in the neural coding of actions, and highlights the use of imitation for learning from and about people. Here, we used computational modeling and a robot implementation to explore the functional value of action imitation. We report 3 experiments using a mutual imitation task between robots, adults, typically developing children, and children with Autism Spectrum Disorder. We show that a particular learning architecture - specifically one combining artificial neural nets for (i) extraction of visual features, (ii) the robot’s motor internal state, (iii) posture recognition, and (iv) novelty detection - is able to learn from an interactive experience involving mutual imitation. This mutual imitation experience allowed the robot to recognize the interactive agent in a subsequent encounter. These experiments using robots as tools for modeling human cognitive development, based on developmental theory, confirm the promise of developmental robotics. Additionally, findings illustrate how person recognition may emerge through imitative experience, intercorporeal mapping, and statistical learning. PMID:26844862

Supersensitive Ras activation in dendrites and spines revealed by two-photon fluorescence lifetime imaging.

PubMed

Yasuda, Ryohei; Harvey, Christopher D; Zhong, Haining; Sobczyk, Aleksander; van Aelst, Linda; Svoboda, Karel

2006-02-01

To understand the biochemical signals regulated by neural activity, it is necessary to measure protein-protein interactions and enzymatic activity in neuronal microcompartments such as axons, dendrites and their spines. We combined two-photon excitation laser scanning with fluorescence lifetime imaging to measure fluorescence resonance energy transfer at high resolutions in brain slices. We also developed sensitive fluorescent protein-based sensors for the activation of the small GTPase protein Ras with slow (FRas) and fast (FRas-F) kinetics. Using FRas-F, we found in CA1 hippocampal neurons that trains of back-propagating action potentials rapidly and reversibly activated Ras in dendrites and spines. The relationship between firing rate and Ras activation was highly nonlinear (Hill coefficient approximately 5). This steep dependence was caused by a highly cooperative interaction between calcium ions (Ca(2+)) and Ras activators. The Ras pathway therefore functions as a supersensitive threshold detector for neural activity and Ca(2+) concentration.

Cognitive deficits caused by prefrontal cortical and hippocampal neural disinhibition.

PubMed

Bast, Tobias; Pezze, Marie; McGarrity, Stephanie

2017-10-01

We review recent evidence concerning the significance of inhibitory GABA transmission and of neural disinhibition, that is, deficient GABA transmission, within the prefrontal cortex and the hippocampus, for clinically relevant cognitive functions. Both regions support important cognitive functions, including attention and memory, and their dysfunction has been implicated in cognitive deficits characterizing neuropsychiatric disorders. GABAergic inhibition shapes cortico-hippocampal neural activity, and, recently, prefrontal and hippocampal neural disinhibition has emerged as a pathophysiological feature of major neuropsychiatric disorders, especially schizophrenia and age-related cognitive decline. Regional neural disinhibition, disrupting spatio-temporal control of neural activity and causing aberrant drive of projections, may disrupt processing within the disinhibited region and efferent regions. Recent studies in rats showed that prefrontal and hippocampal neural disinhibition (by local GABA antagonist microinfusion) dysregulates burst firing, which has been associated with important aspects of neural information processing. Using translational tests of clinically relevant cognitive functions, these studies showed that prefrontal and hippocampal neural disinhibition disrupts regional cognitive functions (including prefrontal attention and hippocampal memory function). Moreover, hippocampal neural disinhibition disrupted attentional performance, which does not require the hippocampus but requires prefrontal-striatal circuits modulated by the hippocampus. However, some prefrontal and hippocampal functions (including inhibitory response control) are spared by regional disinhibition. We consider conceptual implications of these findings, regarding the distinct relationships of distinct cognitive functions to prefrontal and hippocampal GABA tone and neural activity. Moreover, the findings support the proposition that prefrontal and hippocampal neural disinhibition contributes to clinically relevant cognitive deficits, and we consider pharmacological strategies for ameliorating cognitive deficits by rebalancing disinhibition-induced aberrant neural activity. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc. © 2017 The British Pharmacological Society.

Neural mechanisms mediating degrees of strategic uncertainty.

PubMed

Nagel, Rosemarie; Brovelli, Andrea; Heinemann, Frank; Coricelli, Giorgio

2018-01-01

In social interactions, strategic uncertainty arises when the outcome of one's choice depends on the choices of others. An important question is whether strategic uncertainty can be resolved by assessing subjective probabilities to the counterparts' behavior, as if playing against nature, and thus transforming the strategic interaction into a risky (individual) situation. By means of functional magnetic resonance imaging with human participants we tested the hypothesis that choices under strategic uncertainty are supported by the neural circuits mediating choices under individual risk and deliberation in social settings (i.e. strategic thinking). Participants were confronted with risky lotteries and two types of coordination games requiring different degrees of strategic thinking of the kind 'I think that you think that I think etc.' We found that the brain network mediating risk during lotteries (anterior insula, dorsomedial prefrontal cortex and parietal cortex) is also engaged in the processing of strategic uncertainty in games. In social settings, activity in this network is modulated by the level of strategic thinking that is reflected in the activity of the dorsomedial and dorsolateral prefrontal cortex. These results suggest that strategic uncertainty is resolved by the interplay between the neural circuits mediating risk and higher order beliefs (i.e. beliefs about others' beliefs). © The Author(s) (2017). Published by Oxford University Press.

Neural mechanisms mediating degrees of strategic uncertainty

PubMed Central

Nagel, Rosemarie; Brovelli, Andrea; Heinemann, Frank

2018-01-01

Abstract In social interactions, strategic uncertainty arises when the outcome of one’s choice depends on the choices of others. An important question is whether strategic uncertainty can be resolved by assessing subjective probabilities to the counterparts’ behavior, as if playing against nature, and thus transforming the strategic interaction into a risky (individual) situation. By means of functional magnetic resonance imaging with human participants we tested the hypothesis that choices under strategic uncertainty are supported by the neural circuits mediating choices under individual risk and deliberation in social settings (i.e. strategic thinking). Participants were confronted with risky lotteries and two types of coordination games requiring different degrees of strategic thinking of the kind ‘I think that you think that I think etc.’ We found that the brain network mediating risk during lotteries (anterior insula, dorsomedial prefrontal cortex and parietal cortex) is also engaged in the processing of strategic uncertainty in games. In social settings, activity in this network is modulated by the level of strategic thinking that is reflected in the activity of the dorsomedial and dorsolateral prefrontal cortex. These results suggest that strategic uncertainty is resolved by the interplay between the neural circuits mediating risk and higher order beliefs (i.e. beliefs about others’ beliefs). PMID:29228378

Grammatical categories in the brain: the role of morphological structure.

PubMed

Longe, O; Randall, B; Stamatakis, E A; Tyler, L K

2007-08-01

The current study addresses the controversial issue of how different grammatical categories are neurally processed. Several lesion-deficit studies suggest that distinct neural substrates underlie the representation of nouns and verbs, with verb deficits associated with damage to left inferior frontal gyrus (LIFG) and noun deficits with damage to left temporal cortex. However, this view is not universally shared by neuropsychological and neuroimaging studies. We have suggested that these inconsistencies may reflect interactions between the morphological structure of nouns and verbs and the processing implications of this, rather than differences in their neural representations (Tyler et al. 2004). We tested this hypothesis using event-related functional magnetic resonance imaging, to scan subjects performing a valence judgment on unambiguous nouns and verbs, presented as stems ('snail, hear') and inflected forms ('snails, hears'). We predicted that activations for noun and verb stems would not differ, whereas inflected verbs would generate more activation in left frontotemporal areas than inflected nouns. Our findings supported this hypothesis, with greater activation of this network for inflected verbs compared with inflected nouns. These results support the claim that form class is not a first-order organizing principle underlying the representation of words but rather interacts with the processes that operate over lexical representations.

Nonassociative Plasticity Alters Competitive Interactions Among Mixture Components In Early Olfactory Processing

PubMed Central

Locatelli, Fernando F; Fernandez, Patricia C; Villareal, Francis; Muezzinoglu, Kerem; Huerta, Ramon; Galizia, C. Giovanni; Smith, Brian H.

2012-01-01

Experience related plasticity is an essential component of networks involved in early olfactory processing. However, the mechanisms and functions of plasticity in these neural networks are not well understood. We studied nonassociative plasticity by evaluating responses to two pure odors (A and X) and their binary mixture using calcium imaging of odor elicited activity in output neurons of the honey bee antennal lobe. Unreinforced exposure to A or X produced no change in the neural response elicited by the pure odors. However, exposure to one odor (e.g. A) caused the response to the mixture to become more similar to the other component (X). We also show in behavioral analyses that unreinforced exposure to A caused the mixture to become perceptually more similar to X. These results suggest that nonassociative plasticity modifies neural networks in such a way that it affects local competitive interactions among mixture components. We used a computational model to evaluate the most likely targets for modification. Hebbian modification of synapses from inhibitory local interneurons to projection neurons most reliably produces the observed shift in response to the mixture. These results are consistent with a model in which the antennal lobe acts to filter olfactory information according to its relevance for performing a particular task. PMID:23167675