Neural Entrainment in Drum Rhythms with Silent Breaks: Evidence from Steady-state Evoked and Event-related Potentials.

PubMed

Stupacher, Jan; Witte, Matthias; Hove, Michael J; Wood, Guilherme

2016-12-01

The fusion of rhythm, beat perception, and movement is often summarized under the term "entrainment" and becomes obvious when we effortlessly tap our feet or snap our fingers to the pulse of music. Entrainment to music involves a large network of brain structures, and neural oscillations at beat-related frequencies can help elucidate how this network is connected. Here, we used EEG to investigate steady-state evoked potentials (SSEPs) and event-related potentials (ERPs) during listening and tapping to drum clips with different rhythmic structures that were interrupted by silent breaks of 2-6 sec. This design allowed us to address the question of whether neural entrainment processes persist after the physical presence of musical rhythms and to link neural oscillations and event-related neural responses. During stimulus presentation, SSEPs were elicited in both tasks (listening and tapping). During silent breaks, SSEPs were only present in the tapping task. Notably, the amplitude of the N1 ERP component was more negative after longer silent breaks, and both N1 and SSEP results indicate that neural entrainment was increased when listening to drum rhythms compared with an isochronous metronome. Taken together, this suggests that neural entrainment to music is not solely driven by the physical input but involves endogenous timing processes. Our findings break ground for a tighter linkage between steady-state and transient evoked neural responses in rhythm processing. Beyond music perception, they further support the crucial role of entrained oscillatory activity in shaping sensory, motor, and cognitive processes in general.

Experiencing Past and Future Personal Events: Functional Neuroimaging Evidence on the Neural Bases of Mental Time Travel

ERIC Educational Resources Information Center

Botzung, Anne; Denkova, Ekaterina; Manning, Lilianne

2008-01-01

Functional MRI was used in healthy subjects to investigate the existence of common neural structures supporting re-experiencing the past and pre-experiencing the future. Past and future events evocation appears to involve highly similar patterns of brain activation including, in particular, the medial prefrontal cortex, posterior regions and the…

A cortical network model of cognitive and emotional influences in human decision making.

PubMed

Nazir, Azadeh Hassannejad; Liljenström, Hans

2015-10-01

Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

Small leucine rich proteoglycan family regulates multiple signalling pathways in neural development and maintenance.

PubMed

Dellett, Margaret; Hu, Wanzhou; Papadaki, Vasiliki; Ohnuma, Shin-ichi

2012-04-01

The small leucine-rich repeat proteoglycan (SLRPs) family of proteins currently consists of five classes, based on their structural composition and chromosomal location. As biologically active components of the extracellular matrix (ECM), SLRPs were known to bind to various collagens, having a role in regulating fibril assembly, organization and degradation. More recently, as a function of their diverse proteins cores and glycosaminoglycan side chains, SLRPs have been shown to be able to bind various cell surface receptors, growth factors, cytokines and other ECM components resulting in the ability to influence various cellular functions. Their involvement in several signaling pathways such as Wnt, transforming growth factor-β and epidermal growth factor receptor also highlights their role as matricellular proteins. SLRP family members are expressed during neural development and in adult neural tissues, including ocular tissues. This review focuses on describing SLRP family members involvement in neural development with a brief summary of their role in non-neural ocular tissues and in response to neural injury. © 2012 The Authors Development, Growth & Differentiation © 2012 Japanese Society of Developmental Biologists.

New Insights on Neurobiological Mechanisms underlying Alcohol Addiction

PubMed Central

Cui, Changhai; Noronha, Antonio; Morikawa, Hitoshi; Alvarez, Veronica A.; Stuber, Garret D.; Szumlinski, Karen K.; Kash, Thomas L.; Roberto, Marisa; Wilcox, Mark V.

2012-01-01

Alcohol dependence/addiction is mediated by complex neural mechanisms that involve multiple brain circuits and neuroadaptive changes in a variety of neurotransmitter and neuropeptide systems. Although recent studies have provided substantial information on the neurobiological mechanisms that drive alcohol drinking behavior, significant challenges remain in understanding how alcohol-induced neuroadaptations occur and how different neurocircuits and pathways cross-talk. This review article highlights recent progress in understanding neural mechanisms of alcohol addiction from the perspectives of the development and maintenance of alcohol dependence. It provides insights on cross talks of different mechanisms and reviews the latest studies on metaplasticity, structural plasticity, interface of reward and stress pathways, and cross-talk of different neural signaling systems involved in binge-like drinking and alcohol dependence. PMID:23159531

Neural correlates of maintaining one's political beliefs in the face of counterevidence.

PubMed

Kaplan, Jonas T; Gimbel, Sarah I; Harris, Sam

2016-12-23

People often discount evidence that contradicts their firmly held beliefs. However, little is known about the neural mechanisms that govern this behavior. We used neuroimaging to investigate the neural systems involved in maintaining belief in the face of counterevidence, presenting 40 liberals with arguments that contradicted their strongly held political and non-political views. Challenges to political beliefs produced increased activity in the default mode network-a set of interconnected structures associated with self-representation and disengagement from the external world. Trials with greater belief resistance showed increased response in the dorsomedial prefrontal cortex and decreased activity in the orbitofrontal cortex. We also found that participants who changed their minds more showed less BOLD signal in the insula and the amygdala when evaluating counterevidence. These results highlight the role of emotion in belief-change resistance and offer insight into the neural systems involved in belief maintenance, motivated reasoning, and related phenomena.

Neural correlates of maintaining one’s political beliefs in the face of counterevidence

PubMed Central

Kaplan, Jonas T.; Gimbel, Sarah I.; Harris, Sam

2016-01-01

People often discount evidence that contradicts their firmly held beliefs. However, little is known about the neural mechanisms that govern this behavior. We used neuroimaging to investigate the neural systems involved in maintaining belief in the face of counterevidence, presenting 40 liberals with arguments that contradicted their strongly held political and non-political views. Challenges to political beliefs produced increased activity in the default mode network—a set of interconnected structures associated with self-representation and disengagement from the external world. Trials with greater belief resistance showed increased response in the dorsomedial prefrontal cortex and decreased activity in the orbitofrontal cortex. We also found that participants who changed their minds more showed less BOLD signal in the insula and the amygdala when evaluating counterevidence. These results highlight the role of emotion in belief-change resistance and offer insight into the neural systems involved in belief maintenance, motivated reasoning, and related phenomena. PMID:28008965

Neural Circuits Underlying Crying and Cry Responding in Mammals

PubMed Central

Newman, John D.

2007-01-01

Crying is a universal vocalization in human infants, as well as in the infants of other mammals. Little is known about the neural structures underlying cry production, or the circuitry that mediates a caregiver’s response to cry sounds. In this review, the specific structures known or suspected to be involved in this circuit are identified, along with neurochemical systems and hormones for which evidence suggests a role in responding to infants and infant cries. In addition, evidence that crying elicits parental responses in different mammals is presented. An argument is made for including ‘crying’ as a functional category in the vocal repertoire of all mammalian infants (and the adults of some species). The prevailing neural model for crying production considers forebrain structures to be dispensable. However, evidence for the anterior cingulate gyrus in cry production, and this structure along with the amygdala and some other forebrain areas in responding to cries is presented. PMID:17363076

Neural systems supporting linguistic structure, linguistic experience, and symbolic communication in sign language and gesture.

PubMed

Newman, Aaron J; Supalla, Ted; Fernandez, Nina; Newport, Elissa L; Bavelier, Daphne

2015-09-15

Sign languages used by deaf communities around the world possess the same structural and organizational properties as spoken languages: In particular, they are richly expressive and also tightly grammatically constrained. They therefore offer the opportunity to investigate the extent to which the neural organization for language is modality independent, as well as to identify ways in which modality influences this organization. The fact that sign languages share the visual-manual modality with a nonlinguistic symbolic communicative system-gesture-further allows us to investigate where the boundaries lie between language and symbolic communication more generally. In the present study, we had three goals: to investigate the neural processing of linguistic structure in American Sign Language (using verbs of motion classifier constructions, which may lie at the boundary between language and gesture); to determine whether we could dissociate the brain systems involved in deriving meaning from symbolic communication (including both language and gesture) from those specifically engaged by linguistically structured content (sign language); and to assess whether sign language experience influences the neural systems used for understanding nonlinguistic gesture. The results demonstrated that even sign language constructions that appear on the surface to be similar to gesture are processed within the left-lateralized frontal-temporal network used for spoken languages-supporting claims that these constructions are linguistically structured. Moreover, although nonsigners engage regions involved in human action perception to process communicative, symbolic gestures, signers instead engage parts of the language-processing network-demonstrating an influence of experience on the perception of nonlinguistic stimuli.

Evaluation of the cranial base in amnion rupture sequence involving the anterior neural tube: implications regarding recurrence risk.

PubMed

Jones, Kenneth Lyons; Robinson, Luther K; Benirschke, Kurt

2006-09-01

Amniotic bands can cause disruption of the cranial end of the developing fetus, leading in some cases to a neural tube closure defect. Although recurrence for unaffected parents of an affected child with a defect in which the neural tube closed normally but was subsequently disrupted by amniotic bands is negligible; for a primary defect in closure of the neural tube to which amnion has subsequently adhered, recurrence risk is 1.7%. In that primary defects of neural tube closure are characterized by typical abnormalities of the base of the skull, evaluation of the cranial base in such fetuses provides an approach for making a distinction between these 2 mechanisms. This distinction has implications regarding recurrence risk. The skull base of 2 fetuses with amnion rupture sequence involving the cranial end of the neural tube were compared to that of 1 fetus with anencephaly as well as that of a structurally normal fetus. The skulls were cleaned, fixed in 10% formalin, recleaned, and then exposed to 10% KOH solution. After washing and recleaning, the skulls were exposed to hydrogen peroxide for bleaching and photography. Despite involvement of the anterior neural tube in both fetuses with amnion rupture sequence, in Case 3 the cranial base was normal while in Case 4 the cranial base was similar to that seen in anencephaly. This technique provides a method for determining the developmental pathogenesis of anterior neural tube defects in cases of amnion rupture sequence. As such, it provides information that can be used to counsel parents of affected children with respect to recurrence risk.

Compensatory recruitment of neural resources in chronic alcoholism.

PubMed

Chanraud, Sandra; Sullivan, Edith V

2014-01-01

Functional recovery occurs with sustained sobriety, but the neural mechanisms enabling recovery are only now emerging. Theories about promising mechanisms involve concepts of neuroadaptation, where excessive alcohol consumption results in untoward structural and functional brain changes which are subsequently candidates for reversal with sobriety. Views on functional adaptation in chronic alcoholism have expanded with results from neuroimaging studies. Here, we first describe and define the concept of neuroadaptation according to emerging theories based on the growing literature in aging-related cognitive functioning. Then we describe findings as they apply to chronic alcoholism and factors that could influence compensation, such as functional brain reserve and the integrity of brain structure. Finally, we review brain plasticity based on physiologic mechanisms that could underlie mechanisms of neural compensation. Where possible, we provide operational criteria to define functional and neural compensation. © 2014 Elsevier B.V. All rights reserved.

Complex Networks in Psychological Models

NASA Astrophysics Data System (ADS)

Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

The non-canonical Wnt-PCP pathway shapes the mouse caudal neural plate.

PubMed

López-Escobar, Beatriz; Caro-Vega, José Manuel; Vijayraghavan, Deepthi S; Plageman, Timothy F; Sanchez-Alcazar, José A; Moreno, Roberto Carlos; Savery, Dawn; Márquez-Rivas, Javier; Davidson, Lance A; Ybot-González, Patricia

2018-05-08

The last stage of neural tube (NT) formation involves closure of the caudal neural plate (NP), an embryonic structure formed by neuromesodermal progenitors and newly differentiated cells that becomes incorporated into the NT. Here, we show in mouse that, as cell specification progresses, neuromesodermal progenitors and their progeny undergo significant changes in shape prior to their incorporation into the NT. The caudo-rostral progression towards differentiation is coupled to a gradual reliance on a unique combination of complex mechanisms that drive tissue folding, involving pulses of apical actomyosin contraction and planar polarised cell rearrangements, all of which are regulated by the Wnt-PCP pathway. Indeed, when this pathway is disrupted, either chemically or genetically, the polarisation and morphology of cells within the entire caudal NP is disturbed, producing delays in NT closure. The most severe disruptions of this pathway prevent caudal NT closure and result in spina bifida. In addition, a decrease in Vangl2 gene dosage also appears to promote more rapid progression towards a neural fate, but not the specification of more neural cells. © 2018. Published by The Company of Biologists Ltd.

Neural substrates of reward magnitude, probability, and risk during a wheel of fortune decision-making task.

PubMed

Smith, Bruce W; Mitchell, Derek G V; Hardin, Michael G; Jazbec, Sandra; Fridberg, Daniel; Blair, R James R; Ernst, Monique

2009-01-15

Economic decision-making involves the weighting of magnitude and probability of potential gains/losses. While previous work has examined the neural systems involved in decision-making, there is a need to understand how the parameters associated with decision-making (e.g., magnitude of expected reward, probability of expected reward and risk) modulate activation within these neural systems. In the current fMRI study, we modified the monetary wheel of fortune (WOF) task [Ernst, M., Nelson, E.E., McClure, E.B., Monk, C.S., Munson, S., Eshel, N., et al. (2004). Choice selection and reward anticipation: an fMRI study. Neuropsychologia 42(12), 1585-1597.] to examine in 25 healthy young adults the neural responses to selections of different reward magnitudes, probabilities, or risks. Selection of high, relative to low, reward magnitude increased activity in insula, amygdala, middle and posterior cingulate cortex, and basal ganglia. Selection of low-probability, as opposed to high-probability reward, increased activity in anterior cingulate cortex, as did selection of risky, relative to safe reward. In summary, decision-making that did not involve conflict, as in the magnitude contrast, recruited structures known to support the coding of reward values, and those that integrate motivational and perceptual information for behavioral responses. In contrast, decision-making under conflict, as in the probability and risk contrasts, engaged the dorsal anterior cingulate cortex whose role in conflict monitoring is well established. However, decision-making under conflict failed to activate the structures that track reward values per se. Thus, the presence of conflict in decision-making seemed to significantly alter the pattern of neural responses to simple rewards. In addition, this paradigm further clarifies the functional specialization of the cingulate cortex in processes of decision-making.

The Involvement of Endogenous Neural Oscillations in the Processing of Rhythmic Input: More Than a Regular Repetition of Evoked Neural Responses

PubMed Central

Zoefel, Benedikt; ten Oever, Sanne; Sack, Alexander T.

2018-01-01

It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature. PMID:29563860

Compliance control with embedded neural elements

NASA Technical Reports Server (NTRS)

Venkataraman, S. T.; Gulati, S.

1992-01-01

The authors discuss a control approach that embeds the neural elements within a model-based compliant control architecture for robotic tasks that involve contact with unstructured environments. Compliance control experiments have been performed on actual robotics hardware to demonstrate the performance of contact control schemes with neural elements. System parameters were identified under the assumption that environment dynamics have a fixed nonlinear structure. A robotics research arm, placed in contact with a single degree-of-freedom electromechanical environment dynamics emulator, was commanded to move through a desired trajectory. The command was implemented by using a compliant control strategy.

Structural and functional neural correlates of music perception.

PubMed

Limb, Charles J

2006-04-01

This review article highlights state-of-the-art functional neuroimaging studies and demonstrates the novel use of music as a tool for the study of human auditory brain structure and function. Music is a unique auditory stimulus with properties that make it a compelling tool with which to study both human behavior and, more specifically, the neural elements involved in the processing of sound. Functional neuroimaging techniques represent a modern and powerful method of investigation into neural structure and functional correlates in the living organism. These methods have demonstrated a close relationship between the neural processing of music and language, both syntactically and semantically. Greater neural activity and increased volume of gray matter in Heschl's gyrus has been associated with musical aptitude. Activation of Broca's area, a region traditionally considered to subserve language, is important in interpreting whether a note is on or off key. The planum temporale shows asymmetries that are associated with the phenomenon of perfect pitch. Functional imaging studies have also demonstrated activation of primitive emotional centers such as ventral striatum, midbrain, amygdala, orbitofrontal cortex, and ventral medial prefrontal cortex in listeners of moving musical passages. In addition, studies of melody and rhythm perception have elucidated mechanisms of hemispheric specialization. These studies show the power of music and functional neuroimaging to provide singularly useful tools for the study of brain structure and function.

Development of the field of structural physiology

PubMed Central

FUJIYOSHI, Yoshinori

2015-01-01

Electron crystallography is especially useful for studying the structure and function of membrane proteins — key molecules with important functions in neural and other cells. Electron crystallography is now an established technique for analyzing the structures of membrane proteins in lipid bilayers that closely simulate their natural biological environment. Utilizing cryo-electron microscopes with helium-cooled specimen stages that were developed through a personal motivation to understand the functions of neural systems from a structural point of view, the structures of membrane proteins can be analyzed at a higher than 3 Å resolution. This review covers four objectives. First, I introduce the new research field of structural physiology. Second, I recount some of the struggles involved in developing cryo-electron microscopes. Third, I review the structural and functional analyses of membrane proteins mainly by electron crystallography using cryo-electron microscopes. Finally, I discuss multifunctional channels named “adhennels” based on structures analyzed using electron and X-ray crystallography. PMID:26560835

Motor-Skill Learning in an Insect Inspired Neuro-Computational Control System

PubMed Central

Arena, Eleonora; Arena, Paolo; Strauss, Roland; Patané, Luca

2017-01-01

In nature, insects show impressive adaptation and learning capabilities. The proposed computational model takes inspiration from specific structures of the insect brain: after proposing key hypotheses on the direct involvement of the mushroom bodies (MBs) and on their neural organization, we developed a new architecture for motor learning to be applied in insect-like walking robots. The proposed model is a nonlinear control system based on spiking neurons. MBs are modeled as a nonlinear recurrent spiking neural network (SNN) with novel characteristics, able to memorize time evolutions of key parameters of the neural motor controller, so that existing motor primitives can be improved. The adopted control scheme enables the structure to efficiently cope with goal-oriented behavioral motor tasks. Here, a six-legged structure, showing a steady-state exponentially stable locomotion pattern, is exposed to the need of learning new motor skills: moving through the environment, the structure is able to modulate motor commands and implements an obstacle climbing procedure. Experimental results on a simulated hexapod robot are reported; they are obtained in a dynamic simulation environment and the robot mimicks the structures of Drosophila melanogaster. PMID:28337138

Neonatal Odor-Shock Conditioning Alters the Neural Network Involved in Odor Fear Learning at Adulthood

ERIC Educational Resources Information Center

Sevelinges, Yannick; Sullivan, Regina M.; Messaoudi, Belkacem; Mouly, Anne-Marie

2008-01-01

Adult learning and memory functions are strongly dependent on neonatal experiences. We recently showed that neonatal odor-shock learning attenuates later life odor fear conditioning and amygdala activity. In the present work we investigated whether changes observed in adults can also be observed in other structures normally involved, namely…

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Neural activation toward erotic stimuli in homosexual and heterosexual males.

PubMed

Kagerer, Sabine; Klucken, Tim; Wehrum, Sina; Zimmermann, Mark; Schienle, Anne; Walter, Bertram; Vaitl, Dieter; Stark, Rudolf

2011-11-01

Studies investigating sexual arousal exist, yet there are diverging findings on the underlying neural mechanisms with regard to sexual orientation. Moreover, sexual arousal effects have often been confounded with general arousal effects. Hence, it is still unclear which structures underlie the sexual arousal response in homosexual and heterosexual men. Neural activity and subjective responses were investigated in order to disentangle sexual from general arousal. Considering sexual orientation, differential and conjoint neural activations were of interest. The functional magnetic resonance imaging (fMRI) study focused on the neural networks involved in the processing of sexual stimuli in 21 male participants (11 homosexual, 10 heterosexual). Both groups viewed pictures with erotic content as well as aversive and neutral stimuli. The erotic pictures were subdivided into three categories (most sexually arousing, least sexually arousing, and rest) based on the individual subjective ratings of each participant. Blood oxygen level-dependent responses measured by fMRI and subjective ratings. A conjunction analysis revealed conjoint neural activation related to sexual arousal in thalamus, hypothalamus, occipital cortex, and nucleus accumbens. Increased insula, amygdala, and anterior cingulate gyrus activation could be linked to general arousal. Group differences emerged neither when viewing the most sexually arousing pictures compared with highly arousing aversive pictures nor compared with neutral pictures. Results suggest that a widespread neural network is activated by highly sexually arousing visual stimuli. A partly distinct network of structures underlies sexual and general arousal effects. The processing of preferred, highly sexually arousing stimuli recruited similar structures in homosexual and heterosexual males. © 2011 International Society for Sexual Medicine.

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.

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.

[Protective role of autotypic contacts under cerebellar neural net injury by toxic doses of NO-generative compounds].

PubMed

Samosudova, N V; Reutov, V P; Larionova, N P; Chaĭlakhian, L M

2005-01-01

In the present work, cerebellar neural net injury was induced by toxic doses of NO-generative compound (NaNO2). A protective role of glial cells was revealed in such conditions. The present results were compared with those of the previous work concerning the action of high concentration glutamate on the frog cerebellum (Samosudova et al., 1996). In both cases we observed the appearance of spiral-like structures--"wrappers)"--involving several rows of transformed glial processes with smaller width and bridges connecting the inner sides of row (autotypic contact). A statistic analysis was made according to both previous and present data. We calculated the number and width of rows, and intervals between bridges depending on experimental conditions. As the injury increased (stimulation in the NO-presence), the row number in "wrappers" also increased, while the row width and intervals between bridges decreased. The presence of autotypic contacts in glial "wrappers" enables us to suppose the involvement of adhesive proteins--cadherins in its formation. The obtained data suggested that the formation of spiral structures--"wrappers" may be regarded as a compensative-adaptive reaction on the injury of cerebellar neural net glutamate and NO-generative compounds.

Neural correlates of the self-concept in adolescence-A focus on the significance of friends.

PubMed

Romund, Lydia; Golde, Sabrina; Lorenz, Robert C; Raufelder, Diana; Pelz, Patricia; Gleich, Tobias; Heinz, Andreas; Beck, Anne

2017-02-01

The formation of a coherent and unified self-concept represents a key developmental stage during adolescence. Imaging studies on self-referential processing in adolescents are rare, and it is not clear whether neural structures involved in self-reflection are also involved in reflections of familiar others. In the current study, 41 adolescents were asked to make judgments about trait adjectives during functional magnetic resonance imaging (fMRI): they had to indicate whether the word describes themselves, their friends, their teachers or politicians. Findings indicate a greater overlap in neural networks for responses to self- and friend-related judgments compared to teachers and politicians. In particular, classic self-reference structures such as the ventromedial prefrontal cortex and medial posterior parietal cortex also exhibited higher activation to judgments about friends. In contrast, brain responses towards judgments of teachers (familiar others) compared to politicians (unfamiliar others) did not significantly differ. Results support behavioral findings of a greater relevance of friends for the development of a self-concept during adolescence and indicate underlying functional brain processes. Hum Brain Mapp 38:987-996, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Incidence and anatomy of gaze-evoked nystagmus in patients with cerebellar lesions.

PubMed

Baier, Bernhard; Dieterich, Marianne

2011-01-25

Disorders of gaze-holding--organized by a neural network located in the brainstem or the cerebellum--may lead to nystagmus. Based on previous animal studies it was concluded that one key player of the cerebellar part of this gaze-holding neural network is the flocculus. Up to now, in humans there are no systematic studies in patients with cerebellar lesions examining one of the most common forms of nystagmus: gaze-evoked nystagmus (GEN). The aim of our present study was to clarify which cerebellar structures are involved in the generation of GEN. Twenty-one patients with acute unilateral cerebellar stroke were analyzed by means of modern MRI-based voxel-wise lesion-behavior mapping. Our data indicate that cerebellar structures such as the vermal pyramid, the uvula, and the tonsil, but also parts of the biventer lobule and the inferior semilunar lobule, were affected in horizontal GEN. It seems that these structures are part of a gaze-holding neural integrator control system. Furthermore, GEN might present a diagnostic sign pointing toward ipsilesionally located lesions of midline and lower cerebellar structures.

Self-Disturbances as a Possible Premorbid Indicator of Schizophrenia Risk: A Neurodevelopmental Perspective

PubMed Central

Brent, Benjamin K.; Seidman, Larry J.; Thermenos, Heidi W.; Holt, Daphne J.; Keshavan, Matcheri S.

2013-01-01

Self-disturbances (SDs) are increasingly identified in schizophrenia and are theorized to confer vulnerability to psychosis. Neuroimaging research has shed some light on the neural correlates of SDs in schizophrenia. But, the onset and trajectory of the neural alterations underlying SDs in schizophrenia remain incompletely understood. We hypothesize that the aberrant structure and function of brain areas (e.g., prefrontal, lateral temporal, and parietal cortical structures) comprising the “neural circuitry of self” may represent an early, premorbid (i.e., pre-prodromal) indicator of schizophrenia risk. Consistent with neurodevelopmental models, we argue that “early” (i.e., perinatal) dysmaturational processes (e.g., abnormal cortical neural cell migration and mini-columnar formation) affecting key prefrontal (e.g., medial prefrontal cortex), lateral temporal cortical (e.g., superior temporal sulcus), parietal (e.g., inferior parietal lobule) structures involved in self-processing may lead to subtle disruptions of “self” during childhood in persons at risk for schizophrenia. During adolescence, progressive neurodevelopmental alterations (e.g., aberrant synaptic pruning) affecting the neural circuitry of self may contribute to worsening of SDs. This could result in the emergence of prodromal symptoms and, eventually, full-blown psychosis. To highlight why adolescence may be a period of heightened risk for SDs, we first summarize the literature regarding the neural correlates of self in typically developing children. Next, we present evidence from neuroimaging studies in genetic high-risk youth suggesting that fronto-temporal-parietal structures mediating self-reflection may be abnormal in the premorbid period. Our goal is that the ideas presented here might provide future directions for research into the neurobiology of SDs during the pre-psychosis development of youth at risk for schizophrenia. PMID:23932148

Hot and Spicy versus Cool and Minty as an Example of Organic Structure-Activity Relationships

NASA Astrophysics Data System (ADS)

Kimbrough, Doris R.

1997-07-01

There are two classes of substances that activate neural receptors that are involved in temperature perception. Structures of substances found in spices and food that we normally associate with "hot" (or spicy) and "cool" (or minty) flavors are presented and discussed. Functional group similarities within the two groups provide an interesting example of the relationship between molecular structure and molecular function in organic chemistry.

Relationship between the cervical component of the slump test and change in hamstring muscle tension.

PubMed

Lew, P. C.; Briggs, C. A.

1997-05-01

SUMMARY. The slump test has been used routinely to differentiate low back pain due to involvement of neural structures from low back pain attributable to other factors. It is also said to differentiate between posterior thigh pain due to neural involvement from that due to hamstring injury. If changes in cervical position affect the hamstring muscles, differential diagnosis is confounded. Posterior thigh pain caused by the cervical component of the slump could then be caused either by increased tension on neural structures or increased tension in the hamstrings themselves. The aim of this study was to determine whether changing the cervical position during slump altered posterior thigh pain and/or the tension in the hamstring muscle. Asymptomatic subjects aged between 18 and 30 years were tested. A special fixation device was engineered to fix the trunk, pelvis and lower limb. Pain levels in cervical flexion and extension were assessed by visual analogue scale. Fixation was successful in that there were no significant differences in position of the pelvis or knee during changes in cervical position. Averaged over the group, there was a 40% decrease (P < 0.05) in posterior thigh pain with cervical extension. There were no significant differences in hamstring electromyographic readings during the cervical movements. This indicated that: (1) cervical movement did not change hamstring muscle tension, and (2) the change in experimentally induced pain during cervical flexion was not due to changes in the hamstring muscle. This conclusion supports the view that posterior thigh pain caused by the slump test and relieved by cervical extension arises from neural structures rather than the hamstring muscle. Copyright 1997 Harcourt Publishers Ltd.

Olfactory systems and neural circuits that modulate predator odor fear

PubMed Central

Takahashi, Lorey K.

2014-01-01

When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS) and accessory olfactory systems (AOS) detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray (DPAG), paraventricular nucleus (PVN) of the hypothalamus, and the medial amygdala (MeA) appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal (HPA) stress hormone secretion. The MeA also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus (VHC) appear prominently involved in predator odor fear behavior. The basolateral amygdala (BLA), medial hypothalamic nuclei, and medial prefrontal cortex (mPFC) are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator odors activate fear. PMID:24653685

Olfactory systems and neural circuits that modulate predator odor fear.

PubMed

Takahashi, Lorey K

2014-01-01

When prey animals detect the odor of a predator a constellation of fear-related autonomic, endocrine, and behavioral responses rapidly occur to facilitate survival. How olfactory sensory systems process predator odor and channel that information to specific brain circuits is a fundamental issue that is not clearly understood. However, research in the last 15 years has begun to identify some of the essential features of the sensory detection systems and brain structures that underlie predator odor fear. For instance, the main (MOS) and accessory olfactory systems (AOS) detect predator odors and different types of predator odors are sensed by specific receptors located in either the MOS or AOS. However, complex predator chemosignals may be processed by both the MOS and AOS, which complicate our understanding of the specific neural circuits connected directly and indirectly from the MOS and AOS to activate the physiological and behavioral components of unconditioned and conditioned fear. Studies indicate that brain structures including the dorsal periaqueductal gray (DPAG), paraventricular nucleus (PVN) of the hypothalamus, and the medial amygdala (MeA) appear to be broadly involved in predator odor induced autonomic activity and hypothalamic-pituitary-adrenal (HPA) stress hormone secretion. The MeA also plays a key role in predator odor unconditioned fear behavior and retrieval of contextual fear memory associated with prior predator odor experiences. Other neural structures including the bed nucleus of the stria terminalis and the ventral hippocampus (VHC) appear prominently involved in predator odor fear behavior. The basolateral amygdala (BLA), medial hypothalamic nuclei, and medial prefrontal cortex (mPFC) are also activated by some but not all predator odors. Future research that characterizes how distinct predator odors are uniquely processed in olfactory systems and neural circuits will provide significant insights into the differences of how diverse predator odors activate fear.

Neural mechanisms of oculomotor abnormalities in the infantile strabismus syndrome.

PubMed

Walton, Mark M G; Pallus, Adam; Fleuriet, Jérome; Mustari, Michael J; Tarczy-Hornoch, Kristina

2017-07-01

Infantile strabismus is characterized by numerous visual and oculomotor abnormalities. Recently nonhuman primate models of infantile strabismus have been established, with characteristics that closely match those observed in human patients. This has made it possible to study the neural basis for visual and oculomotor symptoms in infantile strabismus. In this review, we consider the available evidence for neural abnormalities in structures related to oculomotor pathways ranging from visual cortex to oculomotor nuclei. These studies provide compelling evidence that a disturbance of binocular vision during a sensitive period early in life, whatever the cause, results in a cascade of abnormalities through numerous brain areas involved in visual functions and eye movements. Copyright © 2017 the American Physiological Society.

A model for integrating elementary neural functions into delayed-response behavior.

PubMed

Gisiger, Thomas; Kerszberg, Michel

2006-04-01

It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning), and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task), or recalling from this image another one that has been associated with it during training (delayed-pair association task). The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

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.

The time course of symbolic number adaptation: oscillatory EEG activity and event-related potential analysis.

PubMed

Hsu, Yi-Fang; Szűcs, Dénes

2012-02-15

Several functional magnetic resonance imaging (fMRI) studies have used neural adaptation paradigms to detect anatomical locations of brain activity related to number processing. However, currently not much is known about the temporal structure of number adaptation. In the present study, we used electroencephalography (EEG) to elucidate the time course of neural events in symbolic number adaptation. The numerical distance of deviants relative to standards was manipulated. In order to avoid perceptual confounds, all levels of deviants consisted of perceptually identical stimuli. Multiple successive numerical distance effects were detected in event-related potentials (ERPs). Analysis of oscillatory activity further showed at least two distinct stages of neural processes involved in the automatic analysis of numerical magnitude, with the earlier effect emerging at around 200ms and the later effect appearing at around 400ms. The findings support for the hypothesis that numerical magnitude processing involves a succession of cognitive events. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

The neural basis of monitoring goal progress

PubMed Central

Benn, Yael; Webb, Thomas L.; Chang, Betty P. I.; Sun, Yu-Hsuan; Wilkinson, Iain D.; Farrow, Tom F. D.

2014-01-01

The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC) as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent functional magnetic resonance imagining (fMRI) while playing a game that involved monitoring progress toward either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory (WM) in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress toward a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring. PMID:25309380

Percutaneous Pediculoplasty for Vertebral Hemangioma Involving the Neural Arch: A Case Report

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

Fuwa, Sokun, E-mail: sofuwa@luke.or.jp; Numaguchi, Yuji; Kobayashi, Nobuo

2008-01-15

Vertebral hemangiomas occasionally involve the neural arch and they can be symptomatic. We report a case of symptomatic vertebral hemangioma mainly involving the unilateral neural arch which was successfully treated with percutaneous pediculoplasty using a single-needle technique.

Similar Neural Correlates for Language and Sequential Learning: Evidence from Event-Related Brain Potentials

PubMed Central

Christiansen, Morten H.; Conway, Christopher M.; Onnis, Luca

2011-01-01

We used event-related potentials (ERPs) to investigate the time course and distribution of brain activity while adults performed (a) a sequential learning task involving complex structured sequences, and (b) a language processing task. The same positive ERP deflection, the P600 effect, typically linked to difficult or ungrammatical syntactic processing, was found for structural incongruencies in both sequential learning as well as natural language, and with similar topographical distributions. Additionally, a left anterior negativity (LAN) was observed for language but not for sequential learning. These results are interpreted as an indication that the P600 provides an index of violations and the cost of integration of expectations for upcoming material when processing complex sequential structure. We conclude that the same neural mechanisms may be recruited for both syntactic processing of linguistic stimuli and sequential learning of structured sequence patterns more generally. PMID:23678205

Neural activity in the prelimbic and infralimbic cortices of freely moving rats during social interaction: Effect of isolation rearing.

PubMed

Minami, Chihiro; Shimizu, Tomoko; Mitani, Akira

2017-01-01

Sociability promotes a sound daily life for individuals. Reduced sociability is a central symptom of various neuropsychiatric disorders, and yet the neural mechanisms underlying reduced sociability remain unclear. The prelimbic cortex (PL) and infralimbic cortex (IL) have been suggested to play an important role in the neural mechanisms underlying sociability because isolation rearing in rats results in impairment of social behavior and structural changes in the PL and IL. One possible mechanism underlying reduced sociability involves dysfunction of the PL and IL. We made a wireless telemetry system to record multiunit activity in the PL and IL of pairs of freely moving rats during social interaction and examined the influence of isolation rearing on this activity. In group-reared rats, PL neurons increased firing when the rat showed approaching behavior and also contact behavior, especially when the rat attacked the partner. Conversely, IL neurons increased firing when the rat exhibited leaving behavior, especially when the partner left on its own accord. In social interaction, the PL may be involved in active actions toward others, whereas the IL may be involved in passive relief from cautionary subjects. Isolation rearing altered social behavior and neural activity. Isolation-reared rats showed an increased frequency and decreased duration of contact behavior. The increased firing of PL neurons during approaching and contact behavior, observed in group-reared rats, was preserved in isolation-reared rats, whereas the increased firing of IL neurons during leaving behavior, observed in group-reared rats, was suppressed in isolation-reared rats. This result indicates that isolation rearing differentially alters neural activity in the PL and IL during social behavior. The differential influence of isolation rearing on neural activity in the PL and IL may be one of the neural bases of isolation rearing-induced behavior.

Anatomical Pathways Involved in Generating and Sensing Rhythmic Whisker Movements

PubMed Central

Bosman, Laurens W. J.; Houweling, Arthur R.; Owens, Cullen B.; Tanke, Nouk; Shevchouk, Olesya T.; Rahmati, Negah; Teunissen, Wouter H. T.; Ju, Chiheng; Gong, Wei; Koekkoek, Sebastiaan K. E.; De Zeeuw, Chris I.

2011-01-01

The rodent whisker system is widely used as a model system for investigating sensorimotor integration, neural mechanisms of complex cognitive tasks, neural development, and robotics. The whisker pathways to the barrel cortex have received considerable attention. However, many subcortical structures are paramount to the whisker system. They contribute to important processes, like filtering out salient features, integration with other senses, and adaptation of the whisker system to the general behavioral state of the animal. We present here an overview of the brain regions and their connections involved in the whisker system. We do not only describe the anatomy and functional roles of the cerebral cortex, but also those of subcortical structures like the striatum, superior colliculus, cerebellum, pontomedullary reticular formation, zona incerta, and anterior pretectal nucleus as well as those of level setting systems like the cholinergic, histaminergic, serotonergic, and noradrenergic pathways. We conclude by discussing how these brain regions may affect each other and how they together may control the precise timing of whisker movements and coordinate whisker perception. PMID:22065951

Identification of neural structures involved in stuttering using vibrotactile feedback.

PubMed

Cheadle, Oliver; Sorger, Clarissa; Howell, Peter

Feedback delivered over auditory and vibratory afferent pathways has different effects on the fluency of people who stutter (PWS). These features were exploited to investigate the neural structures involved in stuttering. The speech signal vibrated locations on the body (vibrotactile feedback, VTF). Eleven PWS read passages under VTF and control (no-VTF) conditions. All combinations of vibration amplitude, synchronous or delayed VTF and vibrator position (hand, sternum or forehead) were presented. Control conditions were performed at the beginning, middle and end of test sessions. Stuttering rate, but not speaking rate, differed between the control and VTF conditions. Notably, speaking rate did not change between when VTF was delayed versus when it was synchronous in contrast with what happens with auditory feedback. This showed that cerebellar mechanisms, which are affected when auditory feedback is delayed, were not implicated in the fluency-enhancing effects of VTF, suggesting that there is a second fluency-enhancing mechanism. Copyright © 2018 Elsevier Inc. All rights reserved.

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

Estimation of effective connectivity via data-driven neural modeling

PubMed Central

Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

2014-01-01

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

Neural Basis of Interpersonal Traits in Neurodegenerative Diseases

PubMed Central

Sollberger, Marc; Stanley, Christine M.; Wilson, Stephen M.; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W.; Miller, Bruce L.; Rankin, Katherine P.

2009-01-01

Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (dominance, arrogance, coldness, introversion, submissiveness, ingenuousness, warmth, and extraversion) in 257 subjects: 214 patients with neurodegenerative diseases such as FTD, SD, progressive non-fluent aphasia, Alzheimer’s disease, amnestic mild cognitive impairment, corticobasal degeneration, and progressive supranuclear palsy and 43 healthy elderly people. Measures of interpersonal traits were correlated with regional atrophy pattern using voxel-based morphometry (VBM) analysis of structural MR images. Interpersonal traits mapped onto distinct brain regions depending on the degree to which they involved agency and affiliation. Interpersonal traits high in agency related to left dorsolateral prefrontal and left lateral frontopolar regions, whereas interpersonal traits high in affiliation related to right ventromedial prefrontal and right anteromedial temporal regions. Consistent with the existing literature on neural networks underlying social cognition, these results indicate that brain regions related to externally-focused, executive control-related processes underlie agentic interpersonal traits such as dominance, whereas brain regions related to internally-focused, emotion- and reward-related processes underlie affiliative interpersonal traits such as warmth. In addition, these findings indicate that interpersonal traits are subserved by complex neural networks rather than discrete anatomic areas. PMID:19540253

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

Training verb argument structure production in agrammatic aphasia: Behavioral and neural recovery patterns

PubMed Central

Thompson, Cynthia K.; Riley, Ellyn A.; den Ouden, Dirk-Bart; Meltzer-Asscher, Aya; Lukic, Sladjana

2013-01-01

Introduction Neuroimaging and lesion studies indicate a left hemisphere network for verb and verb argument structure processing, involving both frontal and temporoparietal brain regions. Although their verb comprehension is generally unimpaired, it is well known that individuals with agrammatic aphasia often present with verb production deficits, characterized by an argument structure complexity hierarchy, indicating faulty access to argument structure representations for production and integration into syntactic contexts. Recovery of verb processing in agrammatism, however, has received little attention and no studies have examined the neural mechanisms associated with improved verb and argument structure processing. In the present study we trained agrammatic individuals on verbs with complex argument structure in sentence contexts and examined generalization to verbs with less complex argument structure. The neural substrates of improved verb production were examined using functional magnetic resonance imaging (fMRI). Methods Eight individuals with chronic agrammatic aphasia participated in the study (four experimental and four control participants). Production of three-argument verbs in active sentences was trained using a sentence generation task emphasizing the verb’s argument structure and the thematic roles of sentential noun phrases. Before and after training, production of trained and untrained verbs was tested in naming and sentence production and fMRI scans were obtained, using an action naming task. Results Significant pre- to post-training improvement in trained and untrained (one- and two-argument) verbs was found for treated, but not control, participants, with between-group differences found for verb naming, production of verbs in sentences, and production of argument structure. fMRI activation derived from post-treatment compared to pre-treatment scans revealed upregulation in cortical regions implicated for verb and argument structure processing in healthy controls. Conclusions Training verb deficits emphasizing argument structure and thematic role mapping is effective for improving verb and sentence production and results in recruitment of neural networks engaged for verb and argument structure processing in healthy individuals. PMID:23514929

Cell fate control in the developing central nervous system

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

Guérout, Nicolas; Li, Xiaofei; Barnabé-Heider, Fanie, E-mail: Fanie.Barnabe-Heider@ki.se

The principal neural cell types forming the mature central nervous system (CNS) are now understood to be diverse. This cellular subtype diversity originates to a large extent from the specification of the earlier proliferating progenitor populations during development. Here, we review the processes governing the differentiation of a common neuroepithelial cell progenitor pool into mature neurons, astrocytes, oligodendrocytes, ependymal cells and adult stem cells. We focus on studies performed in mice and involving two distinct CNS structures: the spinal cord and the cerebral cortex. Understanding the origin, specification and developmental regulators of neural cells will ultimately impact comprehension and treatmentsmore » of neurological disorders and diseases. - Highlights: • Similar mechanisms regulate cell fate in different CNS cell types and structures. • Cell fate regulators operate in a spatial–temporal manner. • Different neural cell types rely on the generation of a diversity of progenitor cells. • Cell fate decision is dictated by the integration of intrinsic and extrinsic signals.« less

The neural crest, a multifaceted structure of the vertebrates.

PubMed

Dupin, Elisabeth; Le Douarin, Nicole M

2014-09-01

In this review, several features of the cells originating from the lateral borders of the primitive neural anlagen, the neural crest (NC) are considered. Among them, their multipotentiality, which together with their migratory properties, leads them to colonize the developing body and to participate in the development of many tissues and organs. The in vitro analysis of the developmental capacities of single NC cells (NCC) showed that they present several analogies with the hematopoietic cells whose differentiation involves the activity of stem cells endowed with different arrays of developmental potentialities. The permanence of such NC stem cells in the adult organism raises the problem of their role at that stage of life. The NC has appeared during evolution in the vertebrate phylum and is absent in their Protocordates ancestors. The major role of the NCC in the development of the vertebrate head points to a critical role for this structure in the remarkable diversification and radiation of this group of animals. © 2014 Wiley Periodicals, Inc.

The Neuroscience of PowerPoint[TM

ERIC Educational Resources Information Center

Horvath, Jared Cooney

2014-01-01

Many concepts have been published relevant to improving the design of PowerPoint[TM] (PP) presentations for didactic purposes, including the redundancy, modality, and signaling principles of multimedia learning. In this article, we review the recent neuroimaging findings that have emerged elucidating the neural structures involved in many of these…

Unification of Speaker and Meaning in Language Comprehension: An fMRI Study

ERIC Educational Resources Information Center

Tesink, Cathelijne M. J. Y.; Petersson, Karl Magnus; van Berkum, Jos J. A.; van den Brink, Danielle; Buitelaar, Jan K.; Hagoort, Peter

2009-01-01

When interpreting a message, a listener takes into account several sources of linguistic and extralinguistic information. Here we focused on one particular form of extralinguistic information, certain speaker characteristics as conveyed by the voice. Using functional magnetic resonance imaging, we examined the neural structures involved in the…

Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

NASA Astrophysics Data System (ADS)

Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

2017-02-01

It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

A Neuropsychological Approach to Understanding Risk-Taking for Potential Gains and Losses

PubMed Central

Levin, Irwin P.; Xue, Gui; Weller, Joshua A.; Reimann, Martin; Lauriola, Marco; Bechara, Antoine

2012-01-01

Affective neuroscience has helped guide research and theory development in judgment and decision-making by revealing the role of emotional processes in choice behavior, especially when risk is involved. Evidence is emerging that qualitatively and quantitatively different processes may be involved in risky decision-making for gains and losses. We start by reviewing behavioral work by Kahneman and Tversky (1979) and others, which shows that risk-taking differs for potential gains and potential losses. We then turn to the literature in decision neuroscience to support the gain versus loss distinction. Relying in part on data from a new task that separates risky decision-making for gains and losses, we test a neural model that assigns unique mechanisms for risky decision-making involving potential losses. Included are studies using patients with lesions to brain areas specified as important in the model and studies with healthy individuals whose brains are scanned to reveal activation in these and other areas during risky decision-making. In some cases, there is evidence that gains and losses are processed in different regions of the brain, while in other cases the same region appears to process risk in a different manner for gains and losses. At a more general level, we provide strong support for the notion that decisions involving risk-taking for gains and decisions involving risk-taking for losses represent different psychological processes. At a deeper level, we present mounting evidence that different neural structures play different roles in guiding risky choices in these different domains. Some structures are differentially activated by risky gains and risky losses while others respond uniquely in one domain or the other. Taken together, these studies support a clear functional dissociation between risk-taking for gains and risk-taking for losses, and further dissociation at the neural level. PMID:22347161

Three-dimensional fine structure of the organization of microtubules in neurite varicosities by ultra-high voltage electron microscope tomography.

PubMed

Nishida, Tomoki; Yoshimura, Ryoichi; Endo, Yasuhisa

2017-09-01

Neurite varicosities are highly specialized compartments that are involved in neurotransmitter/ neuromodulator release and provide a physiological platform for neural functions. However, it remains unclear how microtubule organization contributes to the form of varicosity. Here, we examine the three-dimensional structure of microtubules in varicosities of a differentiated PC12 neural cell line using ultra-high voltage electron microscope tomography. Three-dimensional imaging showed that a part of the varicosities contained an accumulation of organelles that were separated from parallel microtubule arrays. Further detailed analysis using serial sections and whole-mount tomography revealed microtubules running in a spindle shape of swelling in some other types of varicosities. These electron tomographic results showed that the structural diversity and heterogeneity of microtubule organization supported the form of varicosities, suggesting that a different distribution pattern of microtubules in varicosities is crucial to the regulation of varicosities development.

Neural basis of hierarchical visual form processing of Japanese Kanji characters.

PubMed

Higuchi, Hiroki; Moriguchi, Yoshiya; Murakami, Hiroki; Katsunuma, Ruri; Mishima, Kazuo; Uno, Akira

2015-12-01

We investigated the neural processing of reading Japanese Kanji characters, which involves unique hierarchical visual processing, including the recognition of visual components specific to Kanji, such as "radicals." We performed functional MRI to measure brain activity in response to hierarchical visual stimuli containing (1) real Kanji characters (complete structure with semantic information), (2) pseudo Kanji characters (subcomponents without complete character structure), (3) artificial characters (character fragments), and (4) checkerboard (simple photic stimuli). As we expected, the peaks of the activation in response to different stimulus types were aligned within the left occipitotemporal visual region along the posterior-anterior axis in order of the structural complexity of the stimuli, from fragments (3) to complete characters (1). Moreover, only the real Kanji characters produced functional connectivity between the left inferotemporal area and the language area (left inferior frontal triangularis), while pseudo Kanji characters induced connectivity between the left inferotemporal area and the bilateral cerebellum and left putamen. Visual processing of Japanese Kanji takes place in the left occipitotemporal cortex, with a clear hierarchy within the region such that the neural activation differentiates the elements in Kanji characters' fragments, subcomponents, and semantics, with different patterns of connectivity to remote regions among the elements.

Neural Substrates Underlying Effort, Time, and Risk-Based Decision Making in Motivated Behavior

PubMed Central

Bailey, Matthew R.; Simpson, Eleanor H.; Balsam, Peter D

2016-01-01

All mobile organisms rely on adaptive motivated behavior to overcome the challenges of living in an environment in which essential resources may be limited. A variety of influences ranging from an organism’s environment, experiential history, and physiological state all influence a cost-benefit analysis which allows motivation to energize behavior and direct it toward specific goals. Here we review the substantial amount of research aimed at discovering the interconnected neural circuits which allow organisms to carry-out the cost-benefit computations which allow them to behave in adaptive ways. We specifically focus on how the brain deals with different types of costs, including effort requirements, delays to reward and payoff riskiness. An examination of this broad literature highlights the importance of the extended neural circuits which enable organisms to make decisions about these different types of costs. This involves Cortical Structures, including the Anterior Cingulate Cortex (ACC), the Orbital Frontal Cortex (OFC), the Infralimbic Cortex (IL), and prelimbic Cortex (PL), as well as the Baso-Lateral Amygdala (BLA), the Nucleus Accumbens (Nacc), the Ventral Pallidal (VP), the Sub Thalamic Nucleus (STN) among others. Some regions are involved in multiple aspects of cost-benefit computations while the involvement of other regions is restricted to information relating to specific types of costs. PMID:27427327

Neural substrates underlying effort, time, and risk-based decision making in motivated behavior.

PubMed

Bailey, Matthew R; Simpson, Eleanor H; Balsam, Peter D

2016-09-01

All mobile organisms rely on adaptive motivated behavior to overcome the challenges of living in an environment in which essential resources may be limited. A variety of influences ranging from an organism's environment, experiential history, and physiological state all influence a cost-benefit analysis which allows motivation to energize behavior and direct it toward specific goals. Here we review the substantial amount of research aimed at discovering the interconnected neural circuits which allow organisms to carry-out the cost-benefit computations which allow them to behave in adaptive ways. We specifically focus on how the brain deals with different types of costs, including effort requirements, delays to reward and payoff riskiness. An examination of this broad literature highlights the importance of the extended neural circuits which enable organisms to make decisions about these different types of costs. This involves Cortical Structures, including the Anterior Cingulate Cortex (ACC), the Orbital Frontal Cortex (OFC), the Infralimbic Cortex (IL), and prelimbic Cortex (PL), as well as the Baso-Lateral Amygdala (BLA), the Nucleus Accumbens (NAcc), the Ventral Pallidal (VP), the Sub Thalamic Nucleus (STN) among others. Some regions are involved in multiple aspects of cost-benefit computations while the involvement of other regions is restricted to information relating to specific types of costs. Copyright © 2016 Elsevier Inc. All rights reserved.

The oscillatory entrainment of virtual pitch perception

PubMed Central

Aksentijevic, Aleksandar; Northeast, Anthony; Canty, Daniel; Elliott, Mark A.

2013-01-01

Evidence suggests that synchronized brain oscillations in the low gamma range (around 33 Hz) are involved in the perceptual integration of harmonic complex tones. This process involves the binding of harmonic components into “harmonic templates” – neural structures responsible for pitch coding in the brain. We investigated the hypothesis that oscillatory harmonic binding promotes a change in pitch perception style from spectral (frequency) to virtual (relational). Using oscillatory priming we asked 24 participants to judge as rapidly as possible, the direction of an ambiguous target with ascending spectral and descending virtual contour. They made significantly more virtual responses when primed at 29, 31, and 33 Hz and when the first target tone was harmonically related to the prime, suggesting that neural synchronization in the low gamma range could facilitate a shift toward virtual pitch processing. PMID:23630515

Postnatal brain development: Structural imaging of dynamic neurodevelopmental processes

PubMed Central

Jernigan, Terry L.; Baaré, William F. C.; Stiles, Joan; Madsen, Kathrine Skak

2013-01-01

After birth, there is striking biological and functional development of the brain’s fiber tracts as well as remodeling of cortical and subcortical structures. Behavioral development in children involves a complex and dynamic set of genetically guided processes by which neural structures interact constantly with the environment. This is a protracted process, beginning in the third week of gestation and continuing into early adulthood. Reviewed here are studies using structural imaging techniques, with a special focus on diffusion weighted imaging, describing age-related brain maturational changes in children and adolescents, as well as studies that link these changes to behavioral differences. Finally, we discuss evidence for effects on the brain of several factors that may play a role in mediating these brain–behavior associations in children, including genetic variation, behavioral interventions, and hormonal variation associated with puberty. At present longitudinal studies are few, and we do not yet know how variability in individual trajectories of biological development in specific neural systems map onto similar variability in behavioral trajectories. PMID:21489384

The neural correlates of regulating another person's emotions: an exploratory fMRI study

PubMed Central

Hallam, Glyn P.; Webb, Thomas L.; Sheeran, Paschal; Miles, Eleanor; Niven, Karen; Wilkinson, Iain D.; Hunter, Michael D.; Woodruff, Peter W. R.; Totterdell, Peter; Farrow, Tom F. D.

2014-01-01

Studies investigating the neurophysiological basis of intrapersonal emotion regulation (control of one's own emotional experience) report that the frontal cortex exerts a modulatory effect on limbic structures such as the amygdala and insula. However, no imaging study to date has examined the neurophysiological processes involved in interpersonal emotion regulation, where the goal is explicitly to regulate another person's emotion. Twenty healthy participants (10 males) underwent fMRI while regulating their own or another person's emotions. Intrapersonal and interpersonal emotion regulation tasks recruited an overlapping network of brain regions including bilateral lateral frontal cortex, pre-supplementary motor area, and left temporo-parietal junction. Activations unique to the interpersonal condition suggest that both affective (emotional simulation) and cognitive (mentalizing) aspects of empathy may be involved in the process of interpersonal emotion regulation. These findings provide an initial insight into the neural correlates of regulating another person's emotions and may be relevant to understanding mental health issues that involve problems with social interaction. PMID:24936178

Vascular pattern of the dentate gyrus is regulated by neural progenitors.

PubMed

Pombero, Ana; Garcia-Lopez, Raquel; Estirado, Alicia; Martinez, Salvador

2018-05-01

Neurogenesis is a vital process that begins during early embryonic development and continues until adulthood, though in the latter case, it is restricted to the subventricular zone and the subgranular zone of the dentate gyrus (DG). In particular, the DG's neurogenic properties are structurally and functionally unique, which may be related to its singular vascular pattern. Neurogenesis and angiogenesis share molecular signals and act synergistically, supporting the concept of a neurogenic niche as a functional unit between neural precursors cells and their environment, in which the blood vessels play an important role. Whereas it is well known that vascular development controls neural proliferation in the embryonary and in the adult brain, by releasing neurotrophic factors; the potential influence of neural cells on vascular components during angiogenesis is largely unknown. We have demonstrated that the reduction of neural progenitors leads to a significant impairment of vascular development. Since VEGF is a potential regulator in the neurogenesis-angiogenesis crosstalk, we were interested in assessing the possible role of this molecule in the hippocampal neurovascular development. Our results showed that VEGF is the molecule involved in the regulation of vascular development by neural progenitor cells in the DG.

Neural codes of seeing architectural styles

PubMed Central

Choo, Heeyoung; Nasar, Jack L.; Nikrahei, Bardia; Walther, Dirk B.

2017-01-01

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people’s visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture. PMID:28071765

Neural codes of seeing architectural styles.

PubMed

Choo, Heeyoung; Nasar, Jack L; Nikrahei, Bardia; Walther, Dirk B

2017-01-10

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture.

Traumatic brain injury causes long-term behavioral changes related to region-specific increases of cerebral blood flow.

PubMed

Pöttker, Bruno; Stöber, Franziska; Hummel, Regina; Angenstein, Frank; Radyushkin, Konstantin; Goldschmidt, Jürgen; Schäfer, Michael K E

2017-12-01

Traumatic brain injury (TBI) is a leading cause of disability and death and survivors often suffer from long-lasting motor impairment, cognitive deficits, anxiety disorders and epilepsy. Few experimental studies have investigated long-term sequelae after TBI and relations between behavioral changes and neural activity patterns remain elusive. We examined these issues in a murine model of TBI combining histology, behavioral analyses and single-photon emission computed tomography (SPECT) imaging of regional cerebral blood flow (CBF) as a proxy for neural activity. Adult C57Bl/6N mice were subjected to unilateral cortical impact injury and investigated at early (15-57 days after lesion, dal) and late (184-225 dal) post-traumatic time points. TBI caused pronounced tissue loss of the parietal cortex and subcortical structures and enduring neurological deficits. Marked perilesional astro- and microgliosis was found at 57 dal and declined at 225 dal. Motor and gait pattern deficits occurred at early time points after TBI and improved over the time. In contrast, impaired performance in the Morris water maze test and decreased anxiety-like behavior persisted together with an increased susceptibility to pentylenetetrazole-induced seizures suggesting alterations in neural activity patterns. Accordingly, SPECT imaging of CBF indicated asymmetric hemispheric baseline neural activity patterns. In the ipsilateral hemisphere, increased baseline neural activity was found in the amygdala. In the contralateral hemisphere, homotopic to the structural brain damage, the hippocampus and distinct cortex regions displayed increased baseline neural activity. Thus, regionally elevated CBF along with behavioral alterations indicate that increased neural activity is critically involved in the long-lasting consequences of TBI.

Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks

NASA Astrophysics Data System (ADS)

Raff, L. M.; Malshe, M.; Hagan, M.; Doughan, D. I.; Rockley, M. G.; Komanduri, R.

2005-02-01

A neural network/trajectory approach is presented for the development of accurate potential-energy hypersurfaces that can be utilized to conduct ab initio molecular dynamics (AIMD) and Monte Carlo studies of gas-phase chemical reactions, nanometric cutting, and nanotribology, and of a variety of mechanical properties of importance in potential microelectromechanical systems applications. The method is sufficiently robust that it can be applied to a wide range of polyatomic systems. The overall method integrates ab initio electronic structure calculations with importance sampling techniques that permit the critical regions of configuration space to be determined. The computed ab initio energies and gradients are then accurately interpolated using neural networks (NN) rather than arbitrary parametrized analytical functional forms, moving interpolation or least-squares methods. The sampling method involves a tight integration of molecular dynamics calculations with neural networks that employ early stopping and regularization procedures to improve network performance and test for convergence. The procedure can be initiated using an empirical potential surface or direct dynamics. The accuracy and interpolation power of the method has been tested for two cases, the global potential surface for vinyl bromide undergoing unimolecular decomposition via four different reaction channels and nanometric cutting of silicon. The results show that the sampling methods permit the important regions of configuration space to be easily and rapidly identified, that convergence of the NN fit to the ab initio electronic structure database can be easily monitored, and that the interpolation accuracy of the NN fits is excellent, even for systems involving five atoms or more. The method permits a substantial computational speed and accuracy advantage over existing methods, is robust, and relatively easy to implement.

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

Adaptive nonlinear polynomial neural networks for control of boundary layer/structural interaction

NASA Technical Reports Server (NTRS)

Parker, B. Eugene, Jr.; Cellucci, Richard L.; Abbott, Dean W.; Barron, Roger L.; Jordan, Paul R., III; Poor, H. Vincent

1993-01-01

The acoustic pressures developed in a boundary layer can interact with an aircraft panel to induce significant vibration in the panel. Such vibration is undesirable due to the aerodynamic drag and structure-borne cabin noises that result. The overall objective of this work is to develop effective and practical feedback control strategies for actively reducing this flow-induced structural vibration. This report describes the results of initial evaluations using polynomial, neural network-based, feedback control to reduce flow induced vibration in aircraft panels due to turbulent boundary layer/structural interaction. Computer simulations are used to develop and analyze feedback control strategies to reduce vibration in a beam as a first step. The key differences between this work and that going on elsewhere are as follows: that turbulent and transitional boundary layers represent broadband excitation and thus present a more complex stochastic control scenario than that of narrow band (e.g., laminar boundary layer) excitation; and secondly, that the proposed controller structures are adaptive nonlinear infinite impulse response (IIR) polynomial neural network, as opposed to the traditional adaptive linear finite impulse response (FIR) filters used in most studies to date. The controllers implemented in this study achieved vibration attenuation of 27 to 60 dB depending on the type of boundary layer established by laminar, turbulent, and intermittent laminar-to-turbulent transitional flows. Application of multi-input, multi-output, adaptive, nonlinear feedback control of vibration in aircraft panels based on polynomial neural networks appears to be feasible today. Plans are outlined for Phase 2 of this study, which will include extending the theoretical investigation conducted in Phase 2 and verifying the results in a series of laboratory experiments involving both bum and plate models.

Effects of Time-Compressed Speech Training on Multiple Functional and Structural Neural Mechanisms Involving the Left Superior Temporal Gyrus.

PubMed

Maruyama, Tsukasa; Takeuchi, Hikaru; Taki, Yasuyuki; Motoki, Kosuke; Jeong, Hyeonjeong; Kotozaki, Yuka; Nakagawa, Seishu; Nouchi, Rui; Iizuka, Kunio; Yokoyama, Ryoichi; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Sakaki, Kohei; Sasaki, Yukako; Magistro, Daniele; Kawashima, Ryuta

2018-01-01

Time-compressed speech is an artificial form of rapidly presented speech. Training with time-compressed speech (TCSSL) in a second language leads to adaptation toward TCSSL. Here, we newly investigated the effects of 4 weeks of training with TCSSL on diverse cognitive functions and neural systems using the fractional amplitude of spontaneous low-frequency fluctuations (fALFF), resting-state functional connectivity (RSFC) with the left superior temporal gyrus (STG), fractional anisotropy (FA), and regional gray matter volume (rGMV) of young adults by magnetic resonance imaging. There were no significant differences in change of performance of measures of cognitive functions or second language skills after training with TCSSL compared with that of the active control group. However, compared with the active control group, training with TCSSL was associated with increased fALFF, RSFC, and FA and decreased rGMV involving areas in the left STG. These results lacked evidence of a far transfer effect of time-compressed speech training on a wide range of cognitive functions and second language skills in young adults. However, these results demonstrated effects of time-compressed speech training on gray and white matter structures as well as on resting-state intrinsic activity and connectivity involving the left STG, which plays a key role in listening comprehension.

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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.

Unihemispheric sleep and asymmetrical sleep: behavioral, neurophysiological, and functional perspectives.

PubMed

Mascetti, Gian Gastone

2016-01-01

Sleep is a behavior characterized by a typical body posture, both eyes' closure, raised sensory threshold, distinctive electrographic signs, and a marked decrease of motor activity. In addition, sleep is a periodically necessary behavior and therefore, in the majority of animals, it involves the whole brain and body. However, certain marine mammals and species of birds show a different sleep behavior, in which one cerebral hemisphere sleeps while the other is awake. In dolphins, eared seals, and manatees, unihemispheric sleep allows them to have the benefits of sleep, breathing, thermoregulation, and vigilance. In birds, antipredation vigilance is the main function of unihemispheric sleep, but in domestic chicks, it is also associated with brain lateralization or dominance in the control of behavior. Compared to bihemispheric sleep, unihemispheric sleep would mean a reduction of the time spent sleeping and of the associated recovery processes. However, the behavior and health of aquatic mammals and birds does not seem at all impaired by the reduction of sleep. The neural mechanisms of unihemispheric sleep are unknown, but assuming that the neural structures involved in sleep in cetaceans, seals, and birds are similar to those of terrestrial mammals, it is suggested that they involve the interaction of structures of the hypothalamus, basal forebrain, and brain stem. The neural mechanisms promoting wakefulness dominate one side of the brain, while those promoting sleep predominates the other side. For cetaceans, unihemispheric sleep is the only way to sleep, while in seals and birds, unihemispheric sleep events are intermingled with bihemispheric and rapid eye movement sleep events. Electroencephalogram hemispheric asymmetries are also reported during bihemispheric sleep, at awakening, and at sleep onset, as well as being associated with a use-dependent process (local sleep).

Chlorpyrifos exposure affects fgf8, sox9, and bmp4 expression required for cranial neural crest morphogenesis and chondrogenesis in Xenopus laevis embryos.

PubMed

Tussellino, Margherita; Ronca, Raffaele; Carotenuto, Rosa; Pallotta, Maria M; Furia, Maria; Capriglione, Teresa

2016-10-01

Chlorpyrifos (CPF) is an organophosphate insecticide used primarily to control foliage and soil-borne insect pests on a variety of food and feed crops. In mammals, maternal exposure to CPF has been reported to induce dose-related abnormalities such as slower brain growth and cerebral cortex thinning. In lower vertebrates, for example, fish and amphibians, teratogenic activity of this compound is correlated with several anatomical alterations. Little is known about the effects of CPF on mRNA expression of genes involved in early development of the anatomical structures appearing abnormal in embryos. This study investigated the effects of exposure to different CPF concentrations (10, 15 and 20 mg/L) on Xenopus laevis embryos from stage 4/8 to stage 46. Some of the morphological changes we detected in CPF-exposed embryos included cranial neural crest cell (NCC)-derived structures. For this reason, we analyzed the expression of select genes involved in hindbrain patterning (egr2), cranial neural crest chondrogenesis, and craniofacial development (fgf8, bmp4, sox9, hoxa2 and hoxb2). We found that CPF exposure induced a reduction in transcription of all the genes involved in NCC-dependent chondrogenesis, with largest reductions in fgf8 and sox9; whereas, in hindbrain, we did not find any alterations in egr2 expression. Changes in the expression of fgf8, bmp4, and sox9, which are master regulators of several developmental pathways, have important implications. If these changes are confirmed to belong to a general pattern of alterations in vertebrates prenatally exposed to OP, they might be useful to assess damage during vertebrate embryo development. Environ. Mol. Mutagen. 57:589-604, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neural network based load and price forecasting and confidence interval estimation in deregulated power markets

NASA Astrophysics Data System (ADS)

Zhang, Li

With the deregulation of the electric power market in New England, an independent system operator (ISO) has been separated from the New England Power Pool (NEPOOL). The ISO provides a regional spot market, with bids on various electricity-related products and services submitted by utilities and independent power producers. A utility can bid on the spot market and buy or sell electricity via bilateral transactions. Good estimation of market clearing prices (MCP) will help utilities and independent power producers determine bidding and transaction strategies with low risks, and this is crucial for utilities to compete in the deregulated environment. MCP prediction, however, is difficult since bidding strategies used by participants are complicated and MCP is a non-stationary process. The main objective of this research is to provide efficient short-term load and MCP forecasting and corresponding confidence interval estimation methodologies. In this research, the complexity of load and MCP with other factors is investigated, and neural networks are used to model the complex relationship between input and output. With improved learning algorithm and on-line update features for load forecasting, a neural network based load forecaster was developed, and has been in daily industry use since summer 1998 with good performance. MCP is volatile because of the complexity of market behaviors. In practice, neural network based MCP predictors usually have a cascaded structure, as several key input factors need to be estimated first. In this research, the uncertainties involved in a cascaded neural network structure for MCP prediction are analyzed, and prediction distribution under the Bayesian framework is developed. A fast algorithm to evaluate the confidence intervals by using the memoryless Quasi-Newton method is also developed. The traditional back-propagation algorithm for neural network learning needs to be improved since MCP is a non-stationary process. The extended Kalman filter (EKF) can be used as an integrated adaptive learning and confidence interval estimation algorithm for neural networks, with fast convergence and small confidence intervals. However, EKF learning is computationally expensive because it involves high dimensional matrix manipulations. A modified U-D factorization within the decoupled EKF (DEKF-UD) framework is developed in this research. The computational efficiency and numerical stability are significantly improved.

Shared motion signals for human perceptual decisions and oculomotor actions

NASA Technical Reports Server (NTRS)

Stone, Leland S.; Krauzlis, Richard J.

2003-01-01

A fundamental question in primate neurobiology is to understand to what extent motor behaviors are driven by shared neural signals that also support conscious perception or by independent subconscious neural signals dedicated to motor control. Although it has clearly been established that cortical areas involved in processing visual motion support both perception and smooth pursuit eye movements, it remains unknown whether the same or different sets of neurons within these structures perform these two functions. Examination of the trial-by-trial variation in human perceptual and pursuit responses during a simultaneous psychophysical and oculomotor task reveals that the direction signals for pursuit and perception are not only similar on average but also co-vary on a trial-by-trial basis, even when performance is at or near chance and the decisions are determined largely by neural noise. We conclude that the neural signal encoding the direction of target motion that drives steady-state pursuit and supports concurrent perceptual judgments emanates from a shared ensemble of cortical neurons.

Neural correlates of social motivation: an fMRI study on power versus affiliation.

PubMed

Quirin, Markus; Meyer, Frank; Heise, Nils; Kuhl, Julius; Küstermann, Ekkehard; Strüber, Daniel; Cacioppo, John T

2013-06-01

Power versus affiliation motivations refer to two different strivings relevant in the context of social relationships. We used functional magnetic resonance imaging (fMRI) to determine neural structures involved in power versus affiliation motivation based on an individual differences approach. Seventeen participants provided self-reports of power and affiliation motives and were presented with love, power-related, and control movie clips. The power motive predicted activity in four clusters within the left prefrontal cortex (PFC), while participants viewed power-related film clips. The affiliation motive predicted activity in the right putamen/pallidum while participants viewed love stories. The present findings extend previous research on social motivations to the level of neural functioning and suggest differential networks for power-related versus affiliation-related social motivations. Copyright © 2012 Elsevier B.V. All rights reserved.

Reward for food odors: an fMRI study of liking and wanting as a function of metabolic state and BMI

PubMed Central

Jiang, Tao; Soussignan, Robert; Schaal, Benoist

2015-01-01

Brain reward systems mediate liking and wanting for food reward. Here, we explore the differential involvement of the following structures for these two components: the ventral and dorsal striatopallidal area, orbitofrontal cortex (OFC), anterior insula and anterior cingulate. Twelve healthy female participants were asked to rate pleasantness (liking of food and non-food odors) and the desire to eat (wanting of odor-evoked food) during event-related functional magnetic resonance imaging (fMRI). The subjective ratings and fMRI were performed in hunger and satiety states. Activations of regions of interest were compared as a function of task (liking vs wanting), odor category (food vs non-food) and metabolic state (hunger vs satiety). We found that the nucleus accumbens and ventral pallidum were differentially involved in liking or wanting during the hunger state, which suggests a reciprocal inhibitory influence between these structures. Neural activation of OFC subregions was correlated with either liking or wanting ratings, suggesting an OFC role in reward processing magnitude. Finally, during the hunger state, participants with a high body mass index exhibited less activation in neural structures underlying food reward processing. Our results suggest that food liking and wanting are two separable psychological constructs and may be functionally segregated within the cortico-striatopallidal circuit. PMID:24948157

Observational Learning in Mice Can Be Prevented by Medial Prefrontal Cortex Stimulation and Enhanced by Nucleus Accumbens Stimulation

ERIC Educational Resources Information Center

Jurado-Parras, M. Teresa; Gruart, Agnes; Delgado-Garcia, Jose M.

2012-01-01

The neural structures involved in ongoing appetitive and/or observational learning behaviors remain largely unknown. Operant conditioning and observational learning were evoked and recorded in a modified Skinner box provided with an on-line video recording system. Mice improved their acquisition of a simple operant conditioning task by…

Perception of Emotions from Facial Expressions in High-Functioning Adults with Autism

ERIC Educational Resources Information Center

Kennedy, Daniel P.; Adolphs, Ralph

2012-01-01

Impairment in social communication is one of the diagnostic hallmarks of autism spectrum disorders, and a large body of research has documented aspects of impaired social cognition in autism, both at the level of the processes and the neural structures involved. Yet one of the most common social communicative abilities in everyday life, the…

Similar Neural Correlates for Language and Sequential Learning: Evidence from Event-Related Brain Potentials

ERIC Educational Resources Information Center

Christiansen, Morten H.; Conway, Christopher M.; Onnis, Luca

2012-01-01

We used event-related potentials (ERPs) to investigate the time course and distribution of brain activity while adults performed (1) a sequential learning task involving complex structured sequences and (2) a language processing task. The same positive ERP deflection, the P600 effect, typically linked to difficult or ungrammatical syntactic…

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

PubMed

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Dynamics of sleep/wake determination--Normal and abnormal

NASA Astrophysics Data System (ADS)

Mahowald, Mark W.; Schenck, Carlos H.; O'Connor, Kevin A.

1991-10-01

Virtually all members of the animal kingdom experience a relentless and powerful cycling of states of being: wakefulness, rapid eye movement sleep, and nonrapid eye movement sleep. Each of these states is composed of a number of physiologic variables generated in a variety of neural structures. The predictable oscillations of these states are driven by presumed neural pacemakers which are entrained to the 24 h geophysical environment by the light/dark cycle. Experiments in nature have indicated that wake/sleep rhythm perturbations may occur either involving desynchronization of the basic 24 h wake/sleep cycle within the geophysical 24 h cycle (circadian rhythm disturbances) or involving the rapid oscillation or incomplete declaration of state (such as narcolepsy). The use of phase spaces to describe states of being may be of interest in the description of state determination in both illness and health. Some fascinating clinical and experimental phenomena may represent bifurcations in the sleep/wake control system.

Semantic representations in the temporal pole predict false memories

PubMed Central

Chadwick, Martin J.; Anjum, Raeesa S.; Kumaran, Dharshan; Schacter, Daniel L.; Spiers, Hugo J.; Hassabis, Demis

2016-01-01

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the “semantic hub” of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories. PMID:27551087

A systematic review on the neural effects of music on emotion regulation: implications for music therapy practice.

PubMed

Moore, Kimberly Sena

2013-01-01

Emotion regulation (ER) is an internal process through which a person maintains a comfortable state of arousal by modulating one or more aspects of emotion. The neural correlates underlying ER suggest an interplay between cognitive control areas and areas involved in emotional reactivity. Although some studies have suggested that music may be a useful tool in ER, few studies have examined the links between music perception/production and the neural mechanisms that underlie ER and resulting implications for clinical music therapy treatment. Objectives of this systematic review were to explore and synthesize what is known about how music and music experiences impact neural structures implicated in ER, and to consider clinical implications of these findings for structuring music stimuli to facilitate ER. A comprehensive electronic database search resulted in 50 studies that met predetermined inclusion and exclusion criteria. Pertinent data related to the objective were extracted and study outcomes were analyzed and compared for trends and common findings. Results indicated there are certain music characteristics and experiences that produce desired and undesired neural activation patterns implicated in ER. Desired activation patterns occurred when listening to preferred and familiar music, when singing, and (in musicians) when improvising; undesired activation patterns arose when introducing complexity, dissonance, and unexpected musical events. Furthermore, the connection between music-influenced changes in attention and its link to ER was explored. Implications for music therapy practice are discussed and preliminary guidelines for how to use music to facilitate ER are shared.

Semantic representations in the temporal pole predict false memories.

PubMed

Chadwick, Martin J; Anjum, Raeesa S; Kumaran, Dharshan; Schacter, Daniel L; Spiers, Hugo J; Hassabis, Demis

2016-09-06

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.

Fibulin-1 Binds to Fibroblast Growth Factor 8 with High Affinity: EFFECTS ON EMBRYO SURVIVAL.

PubMed

Fresco, Victor M; Kern, Christine B; Mohammadi, Moosa; Twal, Waleed O

2016-09-02

Fibulin-1 (FBLN1) is a member of a growing family of extracellular matrix glycoproteins that includes eight members and is involved in cellular functions such as adhesion, migration, and differentiation. FBLN1 has also been implicated in embryonic heart and valve development and in the formation of neural crest-derived structures, including aortic arch, thymus, and cranial nerves. Fibroblast growth factor 8 (FGF8) is a member of a large family of growth factors, and its functions include neural crest cell (NCC) maintenance, specifically NCC migration as well as patterning of structures formed from NCC such as outflow tract and cranial nerves. In this report, we sought to investigate whether FBLN1 and FGF8 have cooperative roles in vivo given their influence on the development of the same NCC-derived structures. Surface plasmon resonance binding data showed that FBLN1 binds tightly to FGF8 and prevents its enzymatic degradation by ADAM17. Moreover, overexpression of FBLN1 up-regulates FGF8 gene expression, and down-regulation of FBLN1 by siRNA inhibits FGF8 expression. The generation of a double mutant Fbln1 and Fgf8 mice (Fbln1(-/-) and Fgf8(-/-)) showed that haplo-insufficiency (Fbln1(+/-) and Fgf8(+/-)) resulted in increased embryonic mortality compared with single heterozygote crosses. The mortality of the FGF8/Fbln1 double heterozygote embryos occurred between 14.5 and 16.5 days post-coitus. In conclusion, FBLN1/FGF8 interaction plays a role in survival of vertebrate embryos, and reduced levels of both proteins resulted in added mortality in utero The FBLN1/FGF8 interaction may also be involved in the survival of neural crest cell population during development. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design.

PubMed

Huang, Ri-Bo; Du, Qi-Shi; Wei, Yu-Tuo; Pang, Zong-Wen; Wei, Hang; Chou, Kuo-Chen

2009-02-07

Predicting the bioactivity of peptides and proteins is an important challenge in drug development and protein engineering. In this study we introduce a novel approach, the so-called "physics and chemistry-driven artificial neural network (Phys-Chem ANN)", to deal with such a problem. Unlike the existing ANN approaches, which were designed under the inspiration of biological neural system, the Phys-Chem ANN approach is based on the physical and chemical principles, as well as the structural features of proteins. In the Phys-Chem ANN model the "hidden layers" are no longer virtual "neurons", but real structural units of proteins and peptides. It is a hybridization approach, which combines the linear free energy concept of quantitative structure-activity relationship (QSAR) with the advanced mathematical technique of ANN. The Phys-Chem ANN approach has adopted an iterative and feedback procedure, incorporating both machine-learning and artificial intelligence capabilities. In addition to making more accurate predictions for the bioactivities of proteins and peptides than is possible with the traditional QSAR approach, the Phys-Chem ANN approach can also provide more insights about the relationship between bioactivities and the structures involved than the ANN approach does. As an example of the application of the Phys-Chem ANN approach, a predictive model for the conformational stability of human lysozyme is presented.

Structural and functional correlates for language efficiency in auditory word processing.

PubMed

Jung, JeYoung; Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally.

Structural and functional correlates for language efficiency in auditory word processing

PubMed Central

Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally. PMID:28892503

Nonlinear channel equalization for QAM signal constellation using artificial neural networks.

PubMed

Patra, J C; Pal, R N; Baliarsingh, R; Panda, G

1999-01-01

Application of artificial neural networks (ANN's) to adaptive channel equalization in a digital communication system with 4-QAM signal constellation is reported in this paper. A novel computationally efficient single layer functional link ANN (FLANN) is proposed for this purpose. This network has a simple structure in which the nonlinearity is introduced by functional expansion of the input pattern by trigonometric polynomials. Because of input pattern enhancement, the FLANN is capable of forming arbitrarily nonlinear decision boundaries and can perform complex pattern classification tasks. Considering channel equalization as a nonlinear classification problem, the FLANN has been utilized for nonlinear channel equalization. The performance of the FLANN is compared with two other ANN structures [a multilayer perceptron (MLP) and a polynomial perceptron network (PPN)] along with a conventional linear LMS-based equalizer for different linear and nonlinear channel models. The effect of eigenvalue ratio (EVR) of input correlation matrix on the equalizer performance has been studied. The comparison of computational complexity involved for the three ANN structures is also provided.

Neural correlates of cognitive improvements following cognitive remediation in schizophrenia: a systematic review of randomized trials

PubMed Central

Isaac, Clémence; Januel, Dominique

2016-01-01

Background Cognitive impairments are a core feature in schizophrenia and are linked to poor social functioning. Numerous studies have shown that cognitive remediation can enhance cognitive and functional abilities in patients with this pathology. The underlying mechanism of these behavioral improvements seems to be related to structural and functional changes in the brain. However, studies on neural correlates of such enhancement remain scarce. Objectives We explored the neural correlates of cognitive enhancement following cognitive remediation interventions in schizophrenia and the differential effect between cognitive training and other therapeutic interventions or patients’ usual care. Method We searched MEDLINE, PsycInfo, and ScienceDirect databases for studies on cognitive remediation therapy in schizophrenia that used neuroimaging techniques and a randomized design. Search terms included randomized controlled trial, cognitive remediation, cognitive training, rehabilitation, magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, near infrared spectroscopy, and diffusion tensor imaging. We selected randomized controlled trials that proposed multiple sessions of cognitive training to adult patients with a schizophrenia spectrum disorder and assessed its efficacy with imaging techniques. Results In total, 15 reports involving 19 studies were included in the systematic review. They involved a total of 455 adult patients, 271 of whom received cognitive remediation. Cognitive remediation therapy seems to provide a neurobiological enhancing effect in schizophrenia. After therapy, increased activations are observed in various brain regions mainly in frontal – especially prefrontal – and also in occipital and anterior cingulate regions during working memory and executive tasks. Several studies provide evidence of an improved functional connectivity after cognitive training, suggesting a neuroplastic effect of therapy through mechanisms of functional reorganization. Neurocognitive and social-cognitive training may have a cumulative effect on neural networks involved in social cognition. The variety of proposed programs, imaging tasks, and techniques may explain the heterogeneity of observed neural improvements. Future studies would need to specify the effect of cognitive training depending on those variables. PMID:26993787

Neural retina of chick embryo in organ culture: effects of blockade of growth factors by suramin.

PubMed

Cirillo, A; Chifflet, S; Villar, B

2001-06-01

The neural retina is a highly organized organ whose final histoarchitecture depends on the presence of diverse growth factors and on their interactions with extracellular matrix components. However, the role of growth factors on retinal development is not fully understood. Suramin has been shown to produce diverse cellular effects via the simultaneous block of the action of several growth factors. We have therefore studied the effects of suramin on organotypic culture of chick embryo neural retina in order to gain further insights into the participation of growth factors in neural retinal development. Neural retina was incubated for 24 h with suramin at 50-200 microM and then processed to determine cell proliferation, nuclear morphology, and actin distribution. Suramin provoked extensive morphological changes revealed by a decrease in BrdU incorporation, alterations in cellular organization, and disruption of the outer limiting membrane, with the emergence of cellular elements through it. All of these effects were dose-dependent and markedly attenuated by the simultaneous presence of suramin and fibroblast growth factor 2 (FGF-2) in the culture medium. These findings indicate that suramin induces pleiotropic effects on the histoarchitecture of the chicken neural retina in organ culture and suggest that FGF-2 is one of the biological modulators involved in the maintenance of the structural organization of the chicken neural retina.

Applications of artificial neural nets in structural mechanics

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Hajela, Prabhat

1990-01-01

A brief introduction to the fundamental of Neural Nets is given, followed by two applications in structural optimization. In the first case, the feasibility of simulating with neural nets the many structural analyses performed during optimization iterations was studied. In the second case, the concept of using neural nets to capture design expertise was studied.

Applications of artificial neural nets in structural mechanics

NASA Technical Reports Server (NTRS)

Berke, L.; Hajela, P.

1992-01-01

A brief introduction to the fundamental of Neural Nets is given, followed by two applications in structural optimization. In the first case, the feasibility of simulating with neural nets the many structural analyses performed during optimization iterations was studied. In the second case, the concept of using neural nets to capture design expertise was studied.

Neural plasticity and its initiating conditions in tinnitus.

PubMed

Roberts, L E

2018-03-01

Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.

Neuronal bases of structural coherence in contemporary dance observation.

PubMed

Bachrach, Asaf; Jola, Corinne; Pallier, Christophe

2016-01-01

The neuronal processes underlying dance observation have been the focus of an increasing number of brain imaging studies over the past decade. However, the existing literature mainly dealt with effects of motor and visual expertise, whereas the neural and cognitive mechanisms that underlie the interpretation of dance choreographies remained unexplored. Hence, much attention has been given to the action observation network (AON) whereas the role of other potentially relevant neuro-cognitive mechanisms such as mentalizing (theory of mind) or language (narrative comprehension) in dance understanding is yet to be elucidated. We report the results of an fMRI study where the structural coherence of short contemporary dance choreographies was manipulated parametrically using the same taped movement material. Our participants were all trained dancers. The whole-brain analysis argues that the interpretation of structurally coherent dance phrases involves a subpart (superior parietal) of the AON as well as mentalizing regions in the dorsomedial prefrontal cortex. An ROI analysis based on a similar study using linguistic materials (Pallier et al., 2011) suggests that structural processing in language and dance might share certain neural mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.

Structure and function of primitive immunoglobulin superfamily neural cell adhesion molecules: a lesson from studies on planarian.

PubMed

Fusaoka, Eri; Inoue, Takeshi; Mineta, Katsuhiko; Agata, Kiyokazu; Takeuchi, Kosei

2006-05-01

Precise wiring and proper remodeling of the neural network are essential for its normal function. The freshwater planarian is an attractive animal in which to study the formation and maintenance of the neural network due to its high regenerative capability and developmental plasticity. Although a recent study revealed that homologs of netrin and its receptors are required for regeneration and maintenance of the planarian central nervous system (CNS), the roles of cell adhesion in the formation and maintenance of the planarian neural network remain poorly understood. In the present study, we found primitive immunoglobulin superfamily cell adhesion molecules (IgCAMs) in a planarian that are homologous to vertebrate neural IgCAMs. We identified planarian orthologs of NCAM, L1CAM, contactin and DSCAM, and designated them DjCAM, DjLCAM, DjCTCAM and DjDSCAM, respectively. We further confirmed that they function as cell adhesion molecules using cell aggregation assays. DjCAM and DjDSCAM were found to be differentially expressed in the CNS. Functional analyses using RNA interference revealed that DjCAM is partly involved in axon formation, and that DjDSCAM plays crucial roles in neuronal cell migration, axon outgrowth, fasciculation and projection.

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

[Head and neck paragangliomas. Embryological origin and anatomical characteristics: topographic distribution and vascularization pattern].

PubMed

Carretero González, José; Blanco Pérez, Pedro; Vázquez Osorio, María Teresa; Benito González, Fernando; Sañudo Tejedo, José Ramón

2009-02-01

Paragangliomas are tumors that arise in the extraadrenal paraganglia and result from migration of neural crest cells during embryonic development. Based on their anatomical distribution, innervation and microscopic structure, these tumors can be classified into interrelated families: branchiomeric paraganglia (related to the branchial clefts and arches), intravagal, aortic-sympathetic and visceral-autonomic. Head and neck paragangliomas belong mainly to the first two of these families. The present article is divided into two parts. The first part reviews the embryological origin of these tumors. Special emphasis is placed on the process of neurulation or neural tube formation, neurosegmentation (with a summary of the mechanisms involved in the initial segmentation of the neural tube and of the hindbrain and spinal medulla), and the development of the sensory placodes and secondary inductions in the cranial region. Subsequently, the neural crest is analyzed, with special attention paid to the cranial neural crest. The embryonogenesis of paragangliomas is also described. The second part describes the topographical distribution of head and neck paragangliomas according to their localization: jugulotympanic, orbit, intercarotid, subclavian and laryngeal. The embryonogenesis and most important anatomical characteristics are described for each type.

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.

Implanted neural network potentials: Application to Li-Si alloys

NASA Astrophysics Data System (ADS)

Onat, Berk; Cubuk, Ekin D.; Malone, Brad D.; Kaxiras, Efthimios

2018-03-01

Modeling the behavior of materials composed of elements with different bonding and electronic structure character for large spatial and temporal scales and over a large compositional range is a challenging problem. Cases in point are amorphous alloys of Si, a prototypical covalent material, and Li, a prototypical metal, which are being considered as anodes for high-energy-density batteries. To address this challenge, we develop a methodology based on neural networks that extends the conventional training approach to incorporate pre-trained parts that capture the character of different components, into the overall network; we refer to this model as the "implanted neural network" method. We show that this approach works well for the Si-Li amorphous alloys for a wide range of compositions, giving good results for key quantities like the diffusion coefficients. The method is readily generalizable to more complicated situations that involve two or more different elements.

Imaging of human differentiated 3D neural aggregates using light sheet fluorescence microscopy.

PubMed

Gualda, Emilio J; Simão, Daniel; Pinto, Catarina; Alves, Paula M; Brito, Catarina

2014-01-01

The development of three dimensional (3D) cell cultures represents a big step for the better understanding of cell behavior and disease in a more natural like environment, providing not only single but multiple cell type interactions in a complex 3D matrix, highly resembling physiological conditions. Light sheet fluorescence microscopy (LSFM) is becoming an excellent tool for fast imaging of such 3D biological structures. We demonstrate the potential of this technique for the imaging of human differentiated 3D neural aggregates in fixed and live samples, namely calcium imaging and cell death processes, showing the power of imaging modality compared with traditional microscopy. The combination of light sheet microscopy and 3D neural cultures will open the door to more challenging experiments involving drug testing at large scale as well as a better understanding of relevant biological processes in a more realistic environment.

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Huang, K. S.; Diep, J.

1993-01-01

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

A symbolic/subsymbolic interface protocol for cognitive modeling

PubMed Central

Simen, Patrick; Polk, Thad

2009-01-01

Researchers studying complex cognition have grown increasingly interested in mapping symbolic cognitive architectures onto subsymbolic brain models. Such a mapping seems essential for understanding cognition under all but the most extreme viewpoints (namely, that cognition consists exclusively of digitally implemented rules; or instead, involves no rules whatsoever). Making this mapping reduces to specifying an interface between symbolic and subsymbolic descriptions of brain activity. To that end, we propose parameterization techniques for building cognitive models as programmable, structured, recurrent neural networks. Feedback strength in these models determines whether their components implement classically subsymbolic neural network functions (e.g., pattern recognition), or instead, logical rules and digital memory. These techniques support the implementation of limited production systems. Though inherently sequential and symbolic, these neural production systems can exploit principles of parallel, analog processing from decision-making models in psychology and neuroscience to explain the effects of brain damage on problem solving behavior. PMID:20711520

Imaging of human differentiated 3D neural aggregates using light sheet fluorescence microscopy

PubMed Central

Gualda, Emilio J.; Simão, Daniel; Pinto, Catarina; Alves, Paula M.; Brito, Catarina

2014-01-01

The development of three dimensional (3D) cell cultures represents a big step for the better understanding of cell behavior and disease in a more natural like environment, providing not only single but multiple cell type interactions in a complex 3D matrix, highly resembling physiological conditions. Light sheet fluorescence microscopy (LSFM) is becoming an excellent tool for fast imaging of such 3D biological structures. We demonstrate the potential of this technique for the imaging of human differentiated 3D neural aggregates in fixed and live samples, namely calcium imaging and cell death processes, showing the power of imaging modality compared with traditional microscopy. The combination of light sheet microscopy and 3D neural cultures will open the door to more challenging experiments involving drug testing at large scale as well as a better understanding of relevant biological processes in a more realistic environment. PMID:25161607

Memory loss in Alzheimer's disease

PubMed Central

Jahn, Holger

2013-01-01

Loss of memory is among the first symptoms reported by patients suffering from Alzheimer's disease (AD) and by their caretakers. Working memory and long-term declarative memory are affected early during the course of the disease. The individual pattern of impaired memory functions correlates with parameters of structural or functional brain integrity. AD pathology interferes with the formation of memories from the molecular level to the framework of neural networks. The investigation of AD memory loss helps to identify the involved neural structures, such as the default mode network, the influence of epigenetic and genetic factors, such as ApoE4 status, and evolutionary aspects of human cognition. Clinically, the analysis of memory assists the definition of AD subtypes, disease grading, and prognostic predictions. Despite new AD criteria that allow the earlier diagnosis of the disease by inclusion of biomarkers derived from cerebrospinal fluid or hippocampal volume analysis, neuropsychological testing remains at the core of AD diagnosis. PMID:24459411

ERP effects and perceived exclusion in the Cyberball paradigm: Correlates of expectancy violation?

PubMed

Weschke, Sarah; Niedeggen, Michael

2015-10-22

A virtual ball-tossing game called Cyberball has allowed the identification of neural structures involved in the processing of social exclusion by using neurocognitive methods. However, there is still an ongoing debate if structures involved are either pain- or exclusion-specific or part of a broader network. In electrophysiological Cyberball studies we have shown that the P3b component is sensitive to exclusion manipulations, possibly modulated by the probability of ball possession of the participant (event "self") or the presumed co-players (event "other"). Since it is known from oddball studies that the P3b is not only modulated by the objective probability of an event, but also by subjective expectancy, we independently manipulated the probability of the events "self" and "other" and the expectancy for these events. Questionnaire data indicate that social need threat is only induced when the expectancy for involvement in the ball-tossing game is violated. Similarly, the P3b amplitude of both "self" and "other" events was a correlate of expectancy violation. We conclude that both the subjective report of exclusion and the P3b effect induced in the Cyberball paradigm are primarily based on a cognitive process sensitive to expectancy violations, and that the P3b is not related to the activation of an exclusion-specific neural alarm system. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of Time-Compressed Speech Training on Multiple Functional and Structural Neural Mechanisms Involving the Left Superior Temporal Gyrus

PubMed Central

Maruyama, Tsukasa; Taki, Yasuyuki; Motoki, Kosuke; Jeong, Hyeonjeong; Kotozaki, Yuka; Nakagawa, Seishu; Iizuka, Kunio; Yokoyama, Ryoichi; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Sakaki, Kohei; Sasaki, Yukako; Magistro, Daniele; Kawashima, Ryuta

2018-01-01

Time-compressed speech is an artificial form of rapidly presented speech. Training with time-compressed speech (TCSSL) in a second language leads to adaptation toward TCSSL. Here, we newly investigated the effects of 4 weeks of training with TCSSL on diverse cognitive functions and neural systems using the fractional amplitude of spontaneous low-frequency fluctuations (fALFF), resting-state functional connectivity (RSFC) with the left superior temporal gyrus (STG), fractional anisotropy (FA), and regional gray matter volume (rGMV) of young adults by magnetic resonance imaging. There were no significant differences in change of performance of measures of cognitive functions or second language skills after training with TCSSL compared with that of the active control group. However, compared with the active control group, training with TCSSL was associated with increased fALFF, RSFC, and FA and decreased rGMV involving areas in the left STG. These results lacked evidence of a far transfer effect of time-compressed speech training on a wide range of cognitive functions and second language skills in young adults. However, these results demonstrated effects of time-compressed speech training on gray and white matter structures as well as on resting-state intrinsic activity and connectivity involving the left STG, which plays a key role in listening comprehension. PMID:29675038

Compensation or inhibitory failure? Testing hypotheses of age-related right frontal lobe involvement in verbal memory ability using structural and diffusion MRI

PubMed Central

Cox, Simon R.; Bastin, Mark E.; Ferguson, Karen J.; Allerhand, Mike; Royle, Natalie A.; Maniega, Susanna Muñoz; Starr, John M.; MacLullich, Alasdair M.J.; Wardlaw, Joanna M.; Deary, Ian J.; MacPherson, Sarah E.

2015-01-01

Functional neuroimaging studies report increased right prefrontal cortex (PFC) involvement during verbal memory tasks amongst low-scoring older individuals, compared to younger controls and their higher-scoring contemporaries. Some propose that this reflects inefficient use of neural resources through failure of the left PFC to inhibit non-task-related right PFC activity, via the anterior corpus callosum (CC). For others, it indicates partial compensation – that is, the right PFC cannot completely supplement the failing neural network, but contributes positively to performance. We propose that combining structural and diffusion brain MRI can be used to test predictions from these theories which have arisen from fMRI studies. We test these hypotheses in immediate and delayed verbal memory ability amongst 90 healthy older adults of mean age 73 years. Right hippocampus and left dorsolateral prefrontal cortex (DLPFC) volumes, and fractional anisotropy (FA) in the splenium made unique contributions to verbal memory ability in the whole group. There was no significant effect of anterior callosal white matter integrity on performance. Rather, segmented linear regression indicated that right DLPFC volume was a significantly stronger positive predictor of verbal memory for lower-scorers than higher-scorers, supporting a compensatory explanation for the differential involvement of the right frontal lobe in verbal memory tasks in older age. PMID:25241394

Atg7-Mediated Autophagy Is Involved in the Neural Crest Cell Generation in Chick Embryo.

PubMed

Wang, Guang; Chen, En-Ni; Liang, Chang; Liang, Jianxin; Gao, Lin-Rui; Chuai, Manli; Münsterberg, Andrea; Bao, Yongping; Cao, Liu; Yang, Xuesong

2018-04-01

Autophagy plays a very important role in numerous physiological and pathological events. However, it still remains unclear whether Atg7-induced autophagy is involved in the regulation of neural crest cell production. In this study, we found the co-location of Atg7 and Pax7 + neural crest cells in early chick embryo development. Upregulation of Atg7 with unilateral transfection of full-length Atg7 increased Pax7 + and HNK-1 + cephalic and trunk neural crest cell numbers compared to either Control-GFP transfection or opposite neural tubes, suggesting that Atg7 over-expression in neural tubes could enhance the production of neural crest cells. BMP4 in situ hybridization and p-Smad1/5/8 immunofluorescent staining demonstrated that upregulation of Atg7 in neural tubes suppressed the BMP4/Smad signaling, which is considered to promote the delamination of neural crest cells. Interestingly, upregulation of Atg7 in neural tubes could significantly accelerate cell progression into the S phase, implying that Atg7 modulates cell cycle progression. However, β-catenin expression was not significantly altered. Finally, we demonstrated that upregulation of the Atg7 gene could activate autophagy as did Atg8. We have also observed that similar phenotypes, such as more HNK-1 + neural crest cells in the unilateral Atg8 transfection side of neural tubes, and the transfection with full-length Atg8-GFP certainly promote the numbers of BrdU + neural crest cells in comparison to the GFP control. Taken together, we reveal that Atg7-induced autophagy is involved in regulating the production of neural crest cells in early chick embryos through the modification of the cell cycle.

Applications of Acupuncture Therapy in Modulating Plasticity of Central Nervous System.

PubMed

Xiao, Ling-Yong; Wang, Xue-Rui; Yang, Ye; Yang, Jing-Wen; Cao, Yan; Ma, Si-Ming; Li, Tian-Ran; Liu, Cun-Zhi

2017-11-07

Acupuncture is widely applied for treatment of various neurological disorders. This manuscript will review the preclinical evidence of acupuncture in mediating neural plasticity, the mechanisms involved. We searched acupuncture, plasticity, and other potential related words at the following sites: PubMed, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), and VIP information data base. The following keywords were used: acupuncture, electroacupuncture, plasticity, neural plasticity, neuroplasticity, neurogenesis, neuroblast, stem cell, progenitor cell, BrdU, synapse, synapse structure, synaptogenesis, axon, axon regeneration, synaptic plasticity, LTP, LTD, neurotrophin, neurotrophic factor, BDNF, GDNF, VEGF, bFGF, EGF, NT-3, NT-4, NT-5, p75NTR, neurotransmitter, acetylcholine, norepinephrine, noradrenaline, dopamine, monamine. We assessed the effects of acupuncture on plasticity under pathological conditions in this review. Relevant references were reviewed and presented to reflect the effects of acupuncture on neural plasticity. The acquired literatures mainly focused on neurogenesis, alterations of synapses, neurotrophins (NTs), and neurotranimitters. Acupuncture methods mentioned in this article include manual acupuncture and electroacupuncture. The cumulative evidences demonstrated that acupuncture could induce neural plasticity in rodents exposed to cerebral ischemia. Neural plasticity mediated by acupuncture in other neural disorders, such as Alzheimer's disease, Parkinson's disease, and depression, were also investigated and there is evidence of positive role of acupuncture induced plasticity in these disorders as well. Mediation of neural plasticity by acupuncture is likely associated with its modulation on NTs and neurotransmitters. The exact mechanisms underlying acupuncture's effects on neural plasticity remain to be elucidated. Neural plasticity may be the potential bridge between acupuncture and the treatment of various neurological diseases. © 2017 International Neuromodulation Society.

Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective.

PubMed

Krystal, John H; Anticevic, Alan; Yang, Genevieve J; Dragoi, George; Driesen, Naomi R; Wang, Xiao-Jing; Murray, John D

2017-05-15

The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders. Published by Elsevier Inc.

Serotonin 2A Receptor Signaling Underlies LSD-induced Alteration of the Neural Response to Dynamic Changes in Music.

PubMed

Barrett, Frederick S; Preller, Katrin H; Herdener, Marcus; Janata, Petr; Vollenweider, Franz X

2017-09-28

Classic psychedelic drugs (serotonin 2A, or 5HT2A, receptor agonists) have notable effects on music listening. In the current report, blood oxygen level-dependent (BOLD) signal was collected during music listening in 25 healthy adults after administration of placebo, lysergic acid diethylamide (LSD), and LSD pretreated with the 5HT2A antagonist ketanserin, to investigate the role of 5HT2A receptor signaling in the neural response to the time-varying tonal structure of music. Tonality-tracking analysis of BOLD data revealed that 5HT2A receptor signaling alters the neural response to music in brain regions supporting basic and higher-level musical and auditory processing, and areas involved in memory, emotion, and self-referential processing. This suggests a critical role of 5HT2A receptor signaling in supporting the neural tracking of dynamic tonal structure in music, as well as in supporting the associated increases in emotionality, connectedness, and meaningfulness in response to music that are commonly observed after the administration of LSD and other psychedelics. Together, these findings inform the neuropsychopharmacology of music perception and cognition, meaningful music listening experiences, and altered perception of music during psychedelic experiences. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Neurobiological Risk Factors for Suicide Insights from Brain Imaging

PubMed Central

Cox Lippard, Elizabeth T.; Johnston, Jennifer A.Y.; Blumberg, Hilary P.

2014-01-01

Context This article reviews neuroimaging studies on neural circuitry associated with suicide-related thoughts and behaviors to identify areas of convergence in findings. Gaps in the literature for which additional research is needed are identified. Evidence acquisition A PubMed search was conducted and articles published prior to March 2014 were reviewed that compared individuals who made suicide attempts to those with similar diagnoses who had not made attempts or to healthy comparison subjects. Articles on adults with suicidal ideation and adolescents who had made attempts, or with suicidal ideation, were also included. Reviewed imaging modalities included structural magnetic resonance imaging, diffusion tensor imaging, single photon emission computerized tomography, positron emission tomography, and functional magnetic resonance imaging. Evidence synthesis Although many studies include small samples, and subject characteristics and imaging methods vary across studies, there were convergent findings involving the structure and function of frontal neural systems and the serotonergic system. Conclusions These initial neuroimaging studies of suicide behavior have provided promising results. Future neuroimaging efforts could be strengthened by more strategic use of common data elements, and a focus on suicide risk trajectories. At-risk subgroups defined by biopsychosocial risk factors and multidimensional assessment of suicidal thoughts and behaviors may provide a clearer picture of the neural circuitry associated with risk status—both current and lifetime. Also needed are studies investigating neural changes associated with interventions that are effective in risk reduction. PMID:25145733

MicroRNA Profiling as Tool for In Vitro Developmental Neurotoxicity Testing: The Case of Sodium Valproate

PubMed Central

Smirnova, Lena; Block, Katharina; Sittka, Alexandra; Oelgeschläger, Michael; Seiler, Andrea E. M.; Luch, Andreas

2014-01-01

Studying chemical disturbances during neural differentiation of murine embryonic stem cells (mESCs) has been established as an alternative in vitro testing approach for the identification of developmental neurotoxicants. miRNAs represent a class of small non-coding RNA molecules involved in the regulation of neural development and ESC differentiation and specification. Thus, neural differentiation of mESCs in vitro allows investigating the role of miRNAs in chemical-mediated developmental toxicity. We analyzed changes in miRNome and transcriptome during neural differentiation of mESCs exposed to the developmental neurotoxicant sodium valproate (VPA). A total of 110 miRNAs and 377 mRNAs were identified differently expressed in neurally differentiating mESCs upon VPA treatment. Based on miRNA profiling we observed that VPA shifts the lineage specification from neural to myogenic differentiation (upregulation of muscle-abundant miRNAs, mir-206, mir-133a and mir-10a, and downregulation of neural-specific mir-124a, mir-128 and mir-137). These findings were confirmed on the mRNA level and via immunochemistry. Particularly, the expression of myogenic regulatory factors (MRFs) as well as muscle-specific genes (Actc1, calponin, myosin light chain, asporin, decorin) were found elevated, while genes involved in neurogenesis (e.g. Otx1, 2, and Zic3, 4, 5) were repressed. These results were specific for valproate treatment and―based on the following two observations―most likely due to the inhibition of histone deacetylase (HDAC) activity: (i) we did not observe any induction of muscle-specific miRNAs in neurally differentiating mESCs exposed to the unrelated developmental neurotoxicant sodium arsenite; and (ii) the expression of muscle-abundant mir-206 and mir-10a was similarly increased in cells exposed to the structurally different HDAC inhibitor trichostatin A (TSA). Based on our results we conclude that miRNA expression profiling is a suitable molecular endpoint for developmental neurotoxicity. The observed lineage shift into myogenesis, where miRNAs may play an important role, could be one of the developmental neurotoxic mechanisms of VPA. PMID:24896083

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

PubMed Central

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A.; Navas, Adrian; Villacorta-Atienza, Jose A.

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh–Rose neurons. PMID:26648863

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

PubMed

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A; Navas, Adrian; Villacorta-Atienza, Jose A

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

Dynamic sensory cues shape song structure in Drosophila

NASA Astrophysics Data System (ADS)

Coen, Philip; Clemens, Jan; Weinstein, Andrew J.; Pacheco, Diego A.; Deng, Yi; Murthy, Mala

2014-03-01

The generation of acoustic communication signals is widespread across the animal kingdom, and males of many species, including Drosophilidae, produce patterned courtship songs to increase their chance of success with a female. For some animals, song structure can vary considerably from one rendition to the next; neural noise within pattern generating circuits is widely assumed to be the primary source of such variability, and statistical models that incorporate neural noise are successful at reproducing the full variation present in natural songs. In direct contrast, here we demonstrate that much of the pattern variability in Drosophila courtship song can be explained by taking into account the dynamic sensory experience of the male. In particular, using a quantitative behavioural assay combined with computational modelling, we find that males use fast modulations in visual and self-motion signals to pattern their songs, a relationship that we show is evolutionarily conserved. Using neural circuit manipulations, we also identify the pathways involved in song patterning choices and show that females are sensitive to song features. Our data not only demonstrate that Drosophila song production is not a fixed action pattern, but establish Drosophila as a valuable new model for studies of rapid decision-making under both social and naturalistic conditions.

Reward for food odors: an fMRI study of liking and wanting as a function of metabolic state and BMI.

PubMed

Jiang, Tao; Soussignan, Robert; Schaal, Benoist; Royet, Jean-Pierre

2015-04-01

Brain reward systems mediate liking and wanting for food reward. Here, we explore the differential involvement of the following structures for these two components: the ventral and dorsal striatopallidal area, orbitofrontal cortex (OFC), anterior insula and anterior cingulate. Twelve healthy female participants were asked to rate pleasantness (liking of food and non-food odors) and the desire to eat (wanting of odor-evoked food) during event-related functional magnetic resonance imaging (fMRI). The subjective ratings and fMRI were performed in hunger and satiety states. Activations of regions of interest were compared as a function of task (liking vs wanting), odor category (food vs non-food) and metabolic state (hunger vs satiety). We found that the nucleus accumbens and ventral pallidum were differentially involved in liking or wanting during the hunger state, which suggests a reciprocal inhibitory influence between these structures. Neural activation of OFC subregions was correlated with either liking or wanting ratings, suggesting an OFC role in reward processing magnitude. Finally, during the hunger state, participants with a high body mass index exhibited less activation in neural structures underlying food reward processing. Our results suggest that food liking and wanting are two separable psychological constructs and may be functionally segregated within the cortico-striatopallidal circuit. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Heparanase confers a growth advantage to differentiating murine embryonic stem cells, and enhances oligodendrocyte formation.

PubMed

Xiong, Anqi; Kundu, Soumi; Forsberg, Maud; Xiong, Yuyuan; Bergström, Tobias; Paavilainen, Tanja; Kjellén, Lena; Li, Jin-Ping; Forsberg-Nilsson, Karin

2017-10-01

Heparan sulfate proteoglycans (HSPGs), ubiquitous components of mammalian cells, play important roles in development and homeostasis. These molecules are located primarily on the cell surface and in the pericellular matrix, where they interact with a multitude of macromolecules, including many growth factors. Manipulation of the enzymes involved in biosynthesis and modification of HSPG structures alters the properties of stem cells. Here, we focus on the involvement of heparanase (HPSE), the sole endo-glucuronidase capable of cleaving of HS, in differentiation of embryonic stem cells into the cells of the neural lineage. Embryonic stem (ES) cells overexpressing HPSE (Hpse-Tg) proliferated more rapidly than WT ES cells in culture and formed larger teratomas in vivo. In addition, differentiating Hpse-Tg ES cells also had a higher growth rate, and overexpression of HPSE in NSPCs enhanced Erk and Akt phosphorylation. Employing a two-step, monolayer differentiation, we observed an increase in HPSE as wild-type (WT) ES cells differentiated into neural stem and progenitor cells followed by down-regulation of HPSE as these NSPCs differentiated into mature cells of the neural lineage. Furthermore, NSPCs overexpressing HPSE gave rise to more oligodendrocytes than WT cultures, with a concomitant reduction in the number of neurons. Our present findings emphasize the importance of HS, in neural differentiation and suggest that by regulating the availability of growth factors and, or other macromolecules, HPSE promotes differentiation into oligodendrocytes. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolic activation of amygdala, lateral septum and accumbens circuits during food anticipatory behavior.

PubMed

Olivo, Diana; Caba, Mario; Gonzalez-Lima, Francisco; Rodríguez-Landa, Juan F; Corona-Morales, Aleph A

2017-01-01

When food is restricted to a brief fixed period every day, animals show an increase in temperature, corticosterone concentration and locomotor activity for 2-3h before feeding time, termed food anticipatory activity. Mechanisms and neuroanatomical circuits responsible for food anticipatory activity remain unclear, and may involve both oscillators and networks related to temporal conditioning. Rabbit pups are nursed once-a-day so they represent a natural model of circadian food anticipatory activity. Food anticipatory behavior in pups may be associated with neural circuits that temporally anticipate feeding, while the nursing event may produce consummatory effects. Therefore, we used New Zealand white rabbit pups entrained to circadian feeding to investigate the hypothesis that structures related to reward expectation and conditioned emotional responses would show a metabolic rhythm anticipatory of the nursing event, different from that shown by structures related to reward delivery. Quantitative cytochrome oxidase histochemistry was used to measure regional brain metabolic activity at eight different times during the day. We found that neural metabolism peaked before nursing, during food anticipatory behavior, in nuclei of the extended amygdala (basolateral, medial and central nuclei, bed nucleus of the stria terminalis), lateral septum and accumbens core. After pups were fed, however, maximal metabolic activity was expressed in the accumbens shell, caudate, putamen and cortical amygdala. Neural and behavioral activation persisted when animals were fasted by two cycles, at the time of expected nursing. These findings suggest that metabolic activation of amygdala-septal-accumbens circuits involved in temporal conditioning may contribute to food anticipatory activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Auditory cortex stimulation to suppress tinnitus: mechanisms and strategies.

PubMed

Zhang, Jinsheng

2013-01-01

Brain stimulation is an important method used to modulate neural activity and suppress tinnitus. Several auditory and non-auditory brain regions have been targeted for stimulation. This paper reviews recent progress on auditory cortex (AC) stimulation to suppress tinnitus and its underlying neural mechanisms and stimulation strategies. At the same time, the author provides his opinions and hypotheses on both animal and human models. The author also proposes a medial geniculate body (MGB)-thalamic reticular nucleus (TRN)-Gating mechanism to reflect tinnitus-related neural information coming from upstream and downstream projection structures. The upstream structures include the lower auditory brainstem and midbrain structures. The downstream structures include the AC and certain limbic centers. Both upstream and downstream information is involved in a dynamic gating mechanism in the MGB together with the TRN. When abnormal gating occurs at the thalamic level, the spilled-out information interacts with the AC to generate tinnitus. The tinnitus signals at the MGB-TRN-Gating may be modulated by different forms of stimulations including brain stimulation. Each stimulation acts as a gain modulator to control the level of tinnitus signals at the MGB-TRN-Gate. This hypothesis may explain why different types of stimulation can induce tinnitus suppression. Depending on the tinnitus etiology, MGB-TRN-Gating may be different in levels and dynamics, which cause variability in tinnitus suppression induced by different gain controllers. This may explain why the induced suppression of tinnitus by one type of stimulation varies across individual patients. Copyright © 2012. Published by Elsevier B.V.

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.

Chondroitin sulphate-mediated fusion of brain neural folds in rat embryos.

PubMed

Alonso, M I; Moro, J A; Martín, C; de la Mano, A; Carnicero, E; Martínez-Alvarez, C; Navarro, N; Cordero, J; Gato, A

2009-01-01

Previous studies have demonstrated that during neural fold fusion in different species, an apical extracellular material rich in glycoconjugates is involved. However, the composition and the biological role of this material remain undetermined. In this paper, we show that this extracellular matrix in rat increases notably prior to contact between the neural folds, suggesting the dynamic behaviour of the secretory process. Immunostaining has allowed us to demonstrate that this extracellular matrix contains chondroitin sulphate proteoglycan (CSPG), with a spatio-temporal distribution pattern, suggesting a direct relationship with the process of adhesion. The degree of CSPG involvement in cephalic neural fold fusion in rat embryos was determined by treatment with specific glycosidases.In vitro rat embryo culture and microinjection techniques were employed to carry out selective digestion, with chondroitinase AC, of the CSPG on the apical surface of the neural folds; this was done immediately prior to the bonding of the cephalic neural folds. In all the treated embryos, cephalic defects of neural fold fusion could be detected. These results show that CSPG plays an important role in the fusion of the cephalic neural folds in rat embryos, which implies that this proteoglycan could be involved in cellular recognition and adhesion. (c) 2008 S. Karger AG, Basel.

Sip1 mediates an E-cadherin-to-N-cadherin switch during cranial neural crest EMT

PubMed Central

Rogers, Crystal D.; Saxena, Ankur

2013-01-01

The neural crest, an embryonic stem cell population, initially resides within the dorsal neural tube but subsequently undergoes an epithelial-to-mesenchymal transition (EMT) to commence migration. Although neural crest and cancer EMTs are morphologically similar, little is known regarding conservation of their underlying molecular mechanisms. We report that Sip1, which is involved in cancer EMT, plays a critical role in promoting the neural crest cell transition to a mesenchymal state. Sip1 transcripts are expressed in premigratory/migrating crest cells. After Sip1 loss, the neural crest specifier gene FoxD3 was abnormally retained in the dorsal neuroepithelium, whereas Sox10, which is normally required for emigration, was diminished. Subsequently, clumps of adherent neural crest cells remained adjacent to the neural tube and aberrantly expressed E-cadherin while lacking N-cadherin. These findings demonstrate two distinct phases of neural crest EMT, detachment and mesenchymalization, with the latter involving a novel requirement for Sip1 in regulation of cadherin expression during completion of neural crest EMT. PMID:24297751

Journey to the Edges: Social Structures and Neural Maps of Intergroup Processes

PubMed Central

Fiske, Susan T.

2013-01-01

This article explores boundaries of the intellectual map of intergroup processes, going to the macro (social structure) boundary and the micro (neural systems) boundary. Both are illustrated by with my own and others’ work on social structures and on neural structures related to intergroup processes. Analyzing the impact of social structures on intergroup processes led to insights about distinct forms of sexism and underlies current work on forms of ageism. The stereotype content model also starts with the social structure of intergroup relations (interdependence and status) and predicts images, emotions, and behaviors. Social structure has much to offer the social psychology of intergroup processes. At the other, less explored boundary, social neuroscience addresses the effects of social contexts on neural systems relevant to intergroup processes. Both social structural and neural analyses circle back to traditional social psychology as converging indicators of intergroup processes. PMID:22435843

Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles

PubMed Central

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P. Read; Camerer, Colin F.

2014-01-01

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations—price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation. PMID:25002476

Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

PubMed

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

2014-07-22

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.

Quantitative proteomics analysis highlights the role of redox hemostasis and energy metabolism in human embryonic stem cell differentiation to neural cells.

PubMed

Fathi, Ali; Hatami, Maryam; Vakilian, Haghighat; Han, Chia-Li; Chen, Yu-Ju; Baharvand, Hossein; Salekdeh, Ghasem Hosseini

2014-04-14

Neural differentiation of human embryonic stem cells (hESCs) is a unique opportunity for in vitro analyses of neurogenesis in humans. Extrinsic cues through neural plate formation are well described in the hESCs although intracellular mechanisms underlying neural development are largely unknown. Proteome analysis of hESC differentiation to neural cells will help to further define molecular mechanisms involved in neurogenesis in humans. Using a two-dimensional differential gel electrophoresis (2D-DIGE) system, we analyzed the proteome of hESC differentiation to neurons at three stages, early neural differentiation, neural ectoderm and mature neurons. Out of 137 differentially accumulated protein spots, 118 spots were identified using MALDI-TOF/TOF and LC MS/MS. We observed that proteins involved in redox hemostasis, vitamin and energy metabolism and ubiquitin dependent proteolysis were more abundant in differentiated cells, whereas the abundance of proteins associated with RNA processing and protein folding was higher in hESCs. Higher abundance of proteins involved in maintaining cellular redox state suggests the importance of redox hemostasis in neural differentiation. Furthermore, our results support the concept of a coupling mechanism between neuronal activity and glucose utilization. The protein network analysis showed that the majority of the interacting proteins were associated with the cell cycle and cellular proliferation. These results enhanced our understanding of the molecular dynamics that underlie neural commitment and differentiation. In highlighting the role of redox and unique metabolic properties of neuronal cells, the present findings add insight to our understanding of hESC differentiation to neurons. The abundance of fourteen proteins involved in maintaining cellular redox state, including 10 members of peroxiredoxin (Prdx) family, mainly increased during differentiation, thus highlighting a link of neural differentiation to redox. Our results revealed markedly higher expression of genes encoding enzymes involved in the glycolysis and amino acid synthesis during differentiation. Protein network analysis predicted a number of critical mediators in hESC differentiation. These proteins included TP53, CTNNB1, SMARCA4, TNF, TERT, E2F1, MYC, RB1, and AR. Copyright © 2014 Elsevier B.V. All rights reserved.

Kcnip1 a Ca²⁺-dependent transcriptional repressor regulates the size of the neural plate in Xenopus.

PubMed

Néant, Isabelle; Mellström, Britt; Gonzalez, Paz; Naranjo, Jose R; Moreau, Marc; Leclerc, Catherine

2015-09-01

In amphibian embryos, our previous work has demonstrated that calcium transients occurring in the dorsal ectoderm at the onset of gastrulation are necessary and sufficient to engage the ectodermal cells into a neural fate by inducing neural specific genes. Some of these genes are direct targets of calcium. Here we search for a direct transcriptional mechanism by which calcium signals are acting. The only known mechanism responsible for a direct action of calcium on gene transcription involves an EF-hand Ca²⁺ binding protein which belongs to a group of four proteins (Kcnip1 to 4). Kcnip protein can act in a Ca²⁺-dependent manner as a transcriptional repressor by binding to a specific DNA sequence, the Downstream Regulatory Element (DRE) site. In Xenopus, among the four kcnips, we show that only kcnip1 is timely and spatially present in the presumptive neural territories and is able to bind DRE sites in a Ca²⁺-dependent manner. The loss of function of kcnip1 results in the expansion of the neural plate through an increased proliferation of neural progenitors. Later on, this leads to an impairment in the development of anterior neural structures. We propose that, in the embryo, at the onset of neurogenesis Kcnip1 is the Ca²⁺-dependent transcriptional repressor that controls the size of the neural plate. This article is part of a Special Issue entitled: 13th European Symposium on Calcium. Copyright © 2014. Published by Elsevier B.V.

Fitting of dynamic recurrent neural network models to sensory stimulus-response data.

PubMed

Doruk, R Ozgur; Zhang, Kechen

2018-06-02

We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a smooth time-dependent variable, the associated response will be a set of neural spike timings (roughly the instants of successive action potential peaks) that have no amplitude information. A recurrent neural network model can be fitted to such a stimulus-response data pair by using the maximum likelihood estimation method where the likelihood function is derived from Poisson statistics of neural spiking. The universal approximation feature of the recurrent dynamical neuron network models allows us to describe excitatory-inhibitory characteristics of an actual sensory neural network with any desired number of neurons. The stimulus data are generated by a phased cosine Fourier series having a fixed amplitude and frequency but a randomly shot phase. Various values of amplitude, stimulus component size, and sample size are applied in order to examine the effect of the stimulus to the identification process. Results are presented in tabular and graphical forms at the end of this text. In addition, to demonstrate the success of this research, a study involving the same model, nominal parameters and stimulus structure, and another study that works on different models are compared to that of this research.

Neural Correlates of Motor Learning, Transfer of Learning, and Learning to Learn

PubMed Central

Seidler, Rachael D.

2009-01-01

Recent studies on the neural bases of sensorimotor adaptation demonstrate that the cerebellar and striatal thalamocortical pathways contribute to early learning. Transfer of learning involves a reduction in the contribution of early learning networks, and increased reliance on the cerebellum. The neural correlates of learning to learn remain to be determined, but likely involve enhanced functioning of general aspects of early learning. PMID:20016293

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.

Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network.

PubMed

Jeng, J T; Lee, T T

2000-01-01

A Chebyshev polynomial-based unified model (CPBUM) neural network is introduced and applied to control a magnetic bearing systems. First, we show that the CPBUM neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional feedforward/recurrent neural network. It turns out that the CPBUM neural network is more suitable in the design of controller than the conventional feedforward/recurrent neural network. Second, we propose the inverse system method, based on the CPBUM neural networks, to control a magnetic bearing system. The proposed controller has two structures; namely, off-line and on-line learning structures. We derive a new learning algorithm for each proposed structure. The experimental results show that the proposed neural network architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Plasticity-related genes in brain development and amygdala-dependent learning.

PubMed

Ehrlich, D E; Josselyn, S A

2016-01-01

Learning about motivationally important stimuli involves plasticity in the amygdala, a temporal lobe structure. Amygdala-dependent learning involves a growing number of plasticity-related signaling pathways also implicated in brain development, suggesting that learning-related signaling in juveniles may simultaneously influence development. Here, we review the pleiotropic functions in nervous system development and amygdala-dependent learning of a signaling pathway that includes brain-derived neurotrophic factor (BDNF), extracellular signaling-related kinases (ERKs) and cyclic AMP-response element binding protein (CREB). Using these canonical, plasticity-related genes as an example, we discuss the intersection of learning-related and developmental plasticity in the immature amygdala, when aversive and appetitive learning may influence the developmental trajectory of amygdala function. We propose that learning-dependent activation of BDNF, ERK and CREB signaling in the immature amygdala exaggerates and accelerates neural development, promoting amygdala excitability and environmental sensitivity later in life. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Boosted ARTMAP: modifications to fuzzy ARTMAP motivated by boosting theory.

PubMed

Verzi, Stephen J; Heileman, Gregory L; Georgiopoulos, Michael

2006-05-01

In this paper, several modifications to the Fuzzy ARTMAP neural network architecture are proposed for conducting classification in complex, possibly noisy, environments. The goal of these modifications is to improve upon the generalization performance of Fuzzy ART-based neural networks, such as Fuzzy ARTMAP, in these situations. One of the major difficulties of employing Fuzzy ARTMAP on such learning problems involves over-fitting of the training data. Structural risk minimization is a machine-learning framework that addresses the issue of over-fitting by providing a backbone for analysis as well as an impetus for the design of better learning algorithms. The theory of structural risk minimization reveals a trade-off between training error and classifier complexity in reducing generalization error, which will be exploited in the learning algorithms proposed in this paper. Boosted ART extends Fuzzy ART by allowing the spatial extent of each cluster formed to be adjusted independently. Boosted ARTMAP generalizes upon Fuzzy ARTMAP by allowing non-zero training error in an effort to reduce the hypothesis complexity and hence improve overall generalization performance. Although Boosted ARTMAP is strictly speaking not a boosting algorithm, the changes it encompasses were motivated by the goals that one strives to achieve when employing boosting. Boosted ARTMAP is an on-line learner, it does not require excessive parameter tuning to operate, and it reduces precisely to Fuzzy ARTMAP for particular parameter values. Another architecture described in this paper is Structural Boosted ARTMAP, which uses both Boosted ART and Boosted ARTMAP to perform structural risk minimization learning. Structural Boosted ARTMAP will allow comparison of the capabilities of off-line versus on-line learning as well as empirical risk minimization versus structural risk minimization using Fuzzy ARTMAP-based neural network architectures. Both empirical and theoretical results are presented to enhance the understanding of these architectures.

Self processing in the brain: a paradigmatic fMRI case study with a professional singer.

PubMed

Zaytseva, Yuliya; Gutyrchik, Evgeny; Bao, Yan; Pöppel, Ernst; Han, Shihui; Northoff, Georg; Welker, Lorenz; Meindl, Thomas; Blautzik, Janusch

2014-06-01

Understanding the mechanisms involved in perception and conception of oneself is a fundamental psychological topic with high relevance for psychiatric and neurological issues, and it is one of the great challenges in neuroscientific research. The paradigmatic single-case study presented here aimed to investigate different components of self- and other-processes and to elucidate corresponding neurobiological underpinnings. An eminent professional opera singer with profound performance experience has undergone functional magnetic resonance imaging and was exposed to excerpts of Mozart arias, sung by herself or another singer. The results indicate a distinction between self- and other conditions in cortical midline structures, differentially involved in self-related and self-referential processing. This lends further support to the assumption of cortical midline structures being involved in the neural processing of self-specific stimuli and also confirms the power of single case studies as a research tool. Copyright © 2014 Elsevier Inc. All rights reserved.

On the nature and evolution of the neural bases of human language

NASA Technical Reports Server (NTRS)

Lieberman, Philip

2002-01-01

The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on the brains of human beings and other species provides insight into the evolution of the brain bases of human language. The neural substrate that regulated motor control in the common ancestor of apes and humans most likely was modified to enhance cognitive and linguistic ability. Speech communication played a central role in this process. However, the process that ultimately resulted in the human brain may have started when our earliest hominid ancestors began to walk.

Kohonen and counterpropagation neural networks applied for mapping and interpretation of IR spectra.

PubMed

Novic, Marjana

2008-01-01

The principles of learning strategy of Kohonen and counterpropagation neural networks are introduced. The advantages of unsupervised learning are discussed. The self-organizing maps produced in both methods are suitable for a wide range of applications. Here, we present an example of Kohonen and counterpropagation neural networks used for mapping, interpretation, and simulation of infrared (IR) spectra. The artificial neural network models were trained for prediction of structural fragments of an unknown compound from its infrared spectrum. The training set contained over 3,200 IR spectra of diverse compounds of known chemical structure. The structure-spectra relationship was encompassed by the counterpropagation neural network, which assigned structural fragments to individual compounds within certain probability limits, assessed from the predictions of test compounds. The counterpropagation neural network model for prediction of fragments of chemical structure is reversible, which means that, for a given structural domain, limited to the training data set in the study, it can be used to simulate the IR spectrum of a chemical defined with a set of structural fragments.

The role of neural precursor cells and self assembling peptides in nerve regeneration

PubMed Central

2013-01-01

Objective Cranial nerve injury involves loss of central neural cells in the brain stem and surrounding support matrix, leading to severe functional impairment. Therapeutically targeting cellular replacement and enhancing structural support may promote neural regeneration. We examined the combinatorial effect of neural precursor cells (NPC) and self assembling peptide (SAP) administration on nerve regeneration. Methods Nerve injury was induced by clip compression of the rodent spinal cord. SAPs were injected immediately into the injured cord and NPCs at 2 weeks post-injury. Behavioral analysis was done weekly and rats were sacrificed at 11 weeks post injury. LFB-H&E staining was done on cord tissue to assess cavitation volume. Motor evoked potentials (MEP) were measured at week 11 to assess nerve conduction and Kaplan meier curves were created to compare survival estimates. Results NPCs and SAPs were distributed both caudal and rostral to the injury site. Behavioral analysis showed that SAP + NPC transplantation significantly improved locomotor score p <0.03) and enhanced survival (log rank test, p = 0.008) compared to control. SAP + NPC treatment also improved nerve conduction velocity (p = 0.008) but did not affect cavitation volume (p = 0.73). Conclusion Combinatorial NPC and SAP injection into injured nerve tissue may enhance neural repair and regeneration. PMID:24351041

The role of neural precursor cells and self assembling peptides in nerve regeneration.

PubMed

Zhao, Xiao; Yao, Gordon S; Liu, Yang; Wang, Jian; Satkunendrarajah, Kajana; Fehlings, Michael

2013-12-19

Cranial nerve injury involves loss of central neural cells in the brain stem and surrounding support matrix, leading to severe functional impairment. Therapeutically targeting cellular replacement and enhancing structural support may promote neural regeneration. We examined the combinatorial effect of neural precursor cells (NPC) and self assembling peptide (SAP) administration on nerve regeneration. Nerve injury was induced by clip compression of the rodent spinal cord. SAPs were injected immediately into the injured cord and NPCs at 2 weeks post-injury. Behavioral analysis was done weekly and rats were sacrificed at 11 weeks post injury. LFB-H&E staining was done on cord tissue to assess cavitation volume. Motor evoked potentials (MEP) were measured at week 11 to assess nerve conduction and Kaplan Meier curves were created to compare survival estimates. NPCs and SAPs were distributed both caudal and rostral to the injury site. Behavioral analysis showed that SAP + NPC transplantation significantly improved locomotor score p <0.03) and enhanced survival (log rank test, p = 0.008) compared to control. SAP + NPC treatment also improved nerve conduction velocity (p = 0.008) but did not affect cavitation volume (p = 0.73). Combinatorial NPC and SAP injection into injured nerve tissue may enhance neural repair and regeneration.

Neural correlates of corporate camaraderie and teamwork.

PubMed

Levine, Catherine

2007-11-01

Corporate citizenship creates an ethical and professional accountability among the employee, the organization, and the outside market. Teamwork is an essential part of this corporate accountability because it increases communication and confidence within the organization and promotes camaraderie and goal completion. Cognitive neuroscience research has been able to localize socialization to various areas of the limbic system, which includes, among other structures, the hypothalamus and amygdala, and is associated with the prefrontal cortex. These neurocortical areas can be monitored while set tasks are performed experimentally or observed naturally. Within the framework of cognitive neuroscience, one can evaluate the neural architecture involved in various states of organizational behavior. One can then use this framework as an overlay in the corporate environment to track project completion and profitability.

Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

PubMed

Witoonchart, Peerajak; Chongstitvatana, Prabhas

2017-08-01

In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

A homeobox gene involved in node, notochord and neural plate formation of chick embryos.

PubMed

Stein, S; Kessel, M

1995-01-01

We have isolated a chicken cDNA clone, Cnot, resembling in sequence and expression pattern the Xenopus homeobox gene Xnot. The major, early transcription domains of Cnot are the node, the notochord and prenodal and postnodal neural plate caudal from the prospective hindbrain level. All these cell populations appear to be descendants of the Cnot-expressing cells of the node, suggesting a cell lineage relationship. After the onset of somitogenesis, a second, independent expression domain appears in the neural folds at the prospective mid- and forebrain levels, and further transcripts are found in the epiphysis, the ventral diencephalon, the preoral gut and the limb buds. Transplantation of nodes from extended streak embryos leads to the formation of ectopic notochords, which express Cnot in the typical, cranially decreasing gradient. Transplantation of young nodes to young hosts has previously been described to induce secondary embryos. We observed that secondary chick embryos express Cnot in node derived, notochord-like structures and in the anterior neural plate, similar to the domains seen in primary embryos. However, expression was absent from the posterior neural plate, which in the induction experiments is excluded from the node lineage. This finding corroborates our initial conclusion about a cell lineage relationship between node, notochord, and neural plate defined by Cnot expression. The midline mesoderm of vertebrate embryos consists of two tissues, the prechordal mesoderm and the notochord. The anterior notochord, the head process, may represent an intermediate form. The transition from prechordal to chordal mesoderm can be followed by the expression of the two marker homeobox genes goosecoid and Cnot, first in the primitive streak, and then in the head process. We suggest that expression of goosecoid or Cnot is involved in the specification of a prechordal or notochordal identity, respectively. A transition from goosecoid to Cnot expression may proceed, while cells are still in the epiblast, but not after becoming mesodermal. A molecular coding of axial positions in the midline mesoderm may occur by specific homeobox genes, similar to the situation in the neural tube and the somitic mesoderm.

The steady-state response of the cerebral cortex to the beat of music reflects both the comprehension of music and attention

PubMed Central

Meltzer, Benjamin; Reichenbach, Chagit S.; Braiman, Chananel; Schiff, Nicholas D.; Hudspeth, A. J.; Reichenbach, Tobias

2015-01-01

The brain’s analyses of speech and music share a range of neural resources and mechanisms. Music displays a temporal structure of complexity similar to that of speech, unfolds over comparable timescales, and elicits cognitive demands in tasks involving comprehension and attention. During speech processing, synchronized neural activity of the cerebral cortex in the delta and theta frequency bands tracks the envelope of a speech signal, and this neural activity is modulated by high-level cortical functions such as speech comprehension and attention. It remains unclear, however, whether the cortex also responds to the natural rhythmic structure of music and how the response, if present, is influenced by higher cognitive processes. Here we employ electroencephalography to show that the cortex responds to the beat of music and that this steady-state response reflects musical comprehension and attention. We show that the cortical response to the beat is weaker when subjects listen to a familiar tune than when they listen to an unfamiliar, non-sensical musical piece. Furthermore, we show that in a task of intermodal attention there is a larger neural response at the beat frequency when subjects attend to a musical stimulus than when they ignore the auditory signal and instead focus on a visual one. Our findings may be applied in clinical assessments of auditory processing and music cognition as well as in the construction of auditory brain-machine interfaces. PMID:26300760

Modified neural networks for rapid recovery of tokamak plasma parameters for real time control

NASA Astrophysics Data System (ADS)

Sengupta, A.; Ranjan, P.

2002-07-01

Two modified neural network techniques are used for the identification of the equilibrium plasma parameters of the Superconducting Steady State Tokamak I from external magnetic measurements. This is expected to ultimately assist in a real time plasma control. As different from the conventional network structure where a single network with the optimum number of processing elements calculates the outputs, a multinetwork system connected in parallel does the calculations here in one of the methods. This network is called the double neural network. The accuracy of the recovered parameters is clearly more than the conventional network. The other type of neural network used here is based on the statistical function parametrization combined with a neural network. The principal component transformation removes linear dependences from the measurements and a dimensional reduction process reduces the dimensionality of the input space. This reduced and transformed input set, rather than the entire set, is fed into the neural network input. This is known as the principal component transformation-based neural network. The accuracy of the recovered parameters in the latter type of modified network is found to be a further improvement over the accuracy of the double neural network. This result differs from that obtained in an earlier work where the double neural network showed better performance. The conventional network and the function parametrization methods have also been used for comparison. The conventional network has been used for an optimization of the set of magnetic diagnostics. The effective set of sensors, as assessed by this network, are compared with the principal component based network. Fault tolerance of the neural networks has been tested. The double neural network showed the maximum resistance to faults in the diagnostics, while the principal component based network performed poorly. Finally the processing times of the methods have been compared. The double network and the principal component network involve the minimum computation time, although the conventional network also performs well enough to be used in real time.

Neural Systems Involved in Fear and Anxiety Measured with Fear-Potentiated Startle

ERIC Educational Resources Information Center

Davis, Michael

2006-01-01

A good deal is now known about the neural circuitry involved in how conditioned fear can augment a simple reflex (fear-potentiated startle). This involves visual or auditory as well as shock pathways that project via the thalamus and perirhinal or insular cortex to the basolateral amygdala (BLA). The BLA projects to the central (CeA) and medial…

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

PubMed

Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

2018-01-01

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

On the neural substrates leading to the emergence of mental operational structures

NASA Technical Reports Server (NTRS)

Ogmen, H.

1993-01-01

A developmental approach to the study of the emergence of mental operational structures in neural networks is presented. Neural architectures proposed to underlie the six stages of the sensory-motor period are discussed.

Feeling Present in Arousing Virtual Reality Worlds: Prefrontal Brain Regions Differentially Orchestrate Presence Experience in Adults and Children

PubMed Central

Baumgartner, Thomas; Speck, Dominique; Wettstein, Denise; Masnari, Ornella; Beeli, Gian; Jäncke, Lutz

2008-01-01

Virtual reality (VR) is a powerful tool for simulating aspects of the real world. The success of VR is thought to depend on its ability to evoke a sense of “being there”, that is, the feeling of “Presence”. In view of the rapid progress in the development of increasingly more sophisticated virtual environments (VE), the importance of understanding the neural underpinnings of presence is growing. To date however, the neural correlates of this phenomenon have received very scant attention. An fMRI-based study with 52 adults and 25 children was therefore conducted using a highly immersive VE. The experience of presence in adult subjects was found to be modulated by two major strategies involving two homologous prefrontal brain structures. Whereas the right DLPFC controlled the sense of presence by down-regulating the activation in the egocentric dorsal visual processing stream, the left DLPFC up-regulated widespread areas of the medial prefrontal cortex known to be involved in self-reflective and stimulus-independent thoughts. In contrast, there was no evidence of these two strategies in children. In fact, anatomical analyses showed that these two prefrontal areas have not yet reached full maturity in children. Taken together, this study presents the first findings that show activation of a highly specific neural network orchestrating the experience of presence in adult subjects, and that the absence of activity in this neural network might contribute to the generally increased susceptibility of children for the experience of presence in VEs. PMID:18958209

The evolutionary neuroscience of musical beat perception: the Action Simulation for Auditory Prediction (ASAP) hypothesis

PubMed Central

Patel, Aniruddh D.; Iversen, John R.

2013-01-01

Every human culture has some form of music with a beat: a perceived periodic pulse that structures the perception of musical rhythm and which serves as a framework for synchronized movement to music. What are the neural mechanisms of musical beat perception, and how did they evolve? One view, which dates back to Darwin and implicitly informs some current models of beat perception, is that the relevant neural mechanisms are relatively general and are widespread among animal species. On the basis of recent neural and cross-species data on musical beat processing, this paper argues for a different view. Here we argue that beat perception is a complex brain function involving temporally-precise communication between auditory regions and motor planning regions of the cortex (even in the absence of overt movement). More specifically, we propose that simulation of periodic movement in motor planning regions provides a neural signal that helps the auditory system predict the timing of upcoming beats. This “action simulation for auditory prediction” (ASAP) hypothesis leads to testable predictions. We further suggest that ASAP relies on dorsal auditory pathway connections between auditory regions and motor planning regions via the parietal cortex, and suggest that these connections may be stronger in humans than in non-human primates due to the evolution of vocal learning in our lineage. This suggestion motivates cross-species research to determine which species are capable of human-like beat perception, i.e., beat perception that involves accurate temporal prediction of beat times across a fairly broad range of tempi. PMID:24860439

Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

PubMed Central

Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

2015-01-01

Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269

Population-wide distributions of neural activity during perceptual decision-making

PubMed Central

Machens, Christian

2018-01-01

Cortical activity involves large populations of neurons, even when it is limited to functionally coherent areas. Electrophysiological recordings, on the other hand, involve comparatively small neural ensembles, even when modern-day techniques are used. Here we review results which have started to fill the gap between these two scales of inquiry, by shedding light on the statistical distributions of activity in large populations of cells. We put our main focus on data recorded in awake animals that perform simple decision-making tasks and consider statistical distributions of activity throughout cortex, across sensory, associative, and motor areas. We transversally review the complexity of these distributions, from distributions of firing rates and metrics of spike-train structure, through distributions of tuning to stimuli or actions and of choice signals, and finally the dynamical evolution of neural population activity and the distributions of (pairwise) neural interactions. This approach reveals shared patterns of statistical organization across cortex, including: (i) long-tailed distributions of activity, where quasi-silence seems to be the rule for a majority of neurons; that are barely distinguishable between spontaneous and active states; (ii) distributions of tuning parameters for sensory (and motor) variables, which show an extensive extrapolation and fragmentation of their representations in the periphery; and (iii) population-wide dynamics that reveal rotations of internal representations over time, whose traces can be found both in stimulus-driven and internally generated activity. We discuss how these insights are leading us away from the notion of discrete classes of cells, and are acting as powerful constraints on theories and models of cortical organization and population coding. PMID:23123501

Autonomic innervation of immune organs and neuroimmune modulation.

PubMed

Mignini, F; Streccioni, V; Amenta, F

2003-02-01

1. Increasing evidence indicates the occurrence of functional interconnections between immune and nervous systems, although data available on the mechanisms of this bi-directional cross-talking are frequently incomplete and not always focussed on their relevance for neuroimmune modulation. 2. Primary (bone marrow and thymus) and secondary (spleen and lymph nodes) lymphoid organs are supplied with an autonomic (mainly sympathetic) efferent innervation and with an afferent sensory innervation. Anatomical studies have revealed origin, pattern of distribution and targets of nerve fibre populations supplying lymphoid organs. 3. Classic (catecholamines and acetylcholine) and peptide transmitters of neural and non-neural origin are released in the lymphoid microenvironment and contribute to neuroimmune modulation. Neuropeptide Y, substance P, calcitonin gene-related peptide, and vasoactive intestinal peptide represent the neuropeptides most involved in neuroimmune modulation. 4. Immune cells and immune organs express specific receptors for (neuro)transmitters. These receptors have been shown to respond in vivo and/or in vitro to the neural substances and their manipulation can alter immune responses. Changes in immune function can also influence the distribution of nerves and the expression of neural receptors in lymphoid organs. 5. Data on different populations of nerve fibres supplying immune organs and their role in providing a link between nervous and immune systems are reviewed. Anatomical connections between nervous and immune systems represent the structural support of the complex network of immune responses. A detailed knowledge of interactions between nervous and immune systems may represent an important basis for the development of strategies for treating pathologies in which altered neuroimmune cross-talking may be involved.

A feedback regulatory loop involving microRNA-9 and nuclear receptor TLX in neural stem cell fate determination.

PubMed

Zhao, Chunnian; Sun, GuoQiang; Li, Shengxiu; Shi, Yanhong

2009-04-01

MicroRNAs have been implicated as having important roles in stem cell biology. MicroRNA-9 (miR-9) is expressed specifically in neurogenic areas of the brain and may be involved in neural stem cell self-renewal and differentiation. We showed previously that the nuclear receptor TLX is an essential regulator of neural stem cell self-renewal. Here we show that miR-9 suppresses TLX expression to negatively regulate neural stem cell proliferation and accelerate neural differentiation. Introducing a TLX expression vector that is not prone to miR-9 regulation rescued miR-9-induced proliferation deficiency and inhibited precocious differentiation. In utero electroporation of miR-9 in embryonic brains led to premature differentiation and outward migration of the transfected neural stem cells. Moreover, TLX represses expression of the miR-9 pri-miRNA. By forming a negative regulatory loop with TLX, miR-9 provides a model for controlling the balance between neural stem cell proliferation and differentiation.

Research Review: Neural response to threat in children, adolescents, and adults after child maltreatment - a quantitative meta-analysis.

PubMed

Hein, Tyler C; Monk, Christopher S

2017-03-01

Child maltreatment is common and has long-term consequences for affective function. Investigations of neural consequences of maltreatment have focused on the amygdala. However, developmental neuroscience indicates that other brain regions are also likely to be affected by child maltreatment, particularly in the social information processing network (SIPN). We conducted a quantitative meta-analysis to: confirm that maltreatment is related to greater bilateral amygdala activation in a large sample that was pooled across studies; investigate other SIPN structures that are likely candidates for altered function; and conduct a data-driven examination to identify additional regions that show altered activation in maltreated children, teens, and adults. We conducted an activation likelihood estimation analysis with 1,733 participants across 20 studies of emotion processing in maltreated individuals. Maltreatment is associated with increased bilateral amygdala activation to emotional faces. One SIPN structure is altered: superior temporal gyrus, of the detection node, is hyperactive in maltreated individuals. The results of the whole-brain corrected analysis also show hyperactivation of the parahippocampal gyrus and insula in maltreated individuals. The meta-analysis confirms that maltreatment is related to increased bilateral amygdala reactivity and also shows that maltreatment affects multiple additional structures in the brain that have received little attention in the literature. Thus, although the majority of studies examining maltreatment and brain function have focused on the amygdala, these findings indicate that the neural consequences of child maltreatment involve a broader network of structures. © 2016 Association for Child and Adolescent Mental Health.

Neural networks involved in learning lexical-semantic and syntactic information in a second language.

PubMed

Mueller, Jutta L; Rueschemeyer, Shirley-Ann; Ono, Kentaro; Sugiura, Motoaki; Sadato, Norihiro; Nakamura, Akinori

2014-01-01

The present study used functional magnetic resonance imaging (fMRI) to investigate the neural correlates of language acquisition in a realistic learning environment. Japanese native speakers were trained in a miniature version of German prior to fMRI scanning. During scanning they listened to (1) familiar sentences, (2) sentences including a novel sentence structure, and (3) sentences containing a novel word while visual context provided referential information. Learning-related decreases of brain activation over time were found in a mainly left-hemispheric network comprising classical frontal and temporal language areas as well as parietal and subcortical regions and were largely overlapping for novel words and the novel sentence structure in initial stages of learning. Differences occurred at later stages of learning during which content-specific activation patterns in prefrontal, parietal and temporal cortices emerged. The results are taken as evidence for a domain-general network supporting the initial stages of language learning which dynamically adapts as learners become proficient.

Implications on visual apperception: energy, duration, structure and synchronization.

PubMed

Bókkon, I; Vimal, Ram Lakhan Pandey

2010-07-01

Although primary visual cortex (V1 or striate) activity per se is not sufficient for visual apperception (normal conscious visual experiences and conscious functions such as detection, discrimination, and recognition), the same is also true for extrastriate visual areas (such as V2, V3, V4/V8/VO, V5/M5/MST, IT, and GF). In the lack of V1 area, visual signals can still reach several extrastriate parts but appear incapable of generating normal conscious visual experiences. It is scarcely emphasized in the scientific literature that conscious perceptions and representations must have also essential energetic conditions. These energetic conditions are achieved by spatiotemporal networks of dynamic mitochondrial distributions inside neurons. However, the highest density of neurons in neocortex (number of neurons per degree of visual angle) devoted to representing the visual field is found in retinotopic V1. It means that the highest mitochondrial (energetic) activity can be achieved in mitochondrial cytochrome oxidase-rich V1 areas. Thus, V1 bear the highest energy allocation for visual representation. In addition, the conscious perceptions also demand structural conditions, presence of adequate duration of information representation, and synchronized neural processes and/or 'interactive hierarchical structuralism.' For visual apperception, various visual areas are involved depending on context such as stimulus characteristics such as color, form/shape, motion, and other features. Here, we focus primarily on V1 where specific mitochondrial-rich retinotopic structures are found; we will concisely discuss V2 where smaller riches of these structures are found. We also point out that residual brain states are not fully reflected in active neural patterns after visual perception. Namely, after visual perception, subliminal residual states are not being reflected in passive neural recording techniques, but require active stimulation to be revealed.

Growing a hypercubical output space in a self-organizing feature map.

PubMed

Bauer, H U; Villmann, T

1997-01-01

Neural maps project data from an input space onto a neuron position in a (often lower dimensional) output space grid in a neighborhood preserving way, with neighboring neurons in the output space responding to neighboring data points in the input space. A map-learning algorithm can achieve an optimal neighborhood preservation only, if the output space topology roughly matches the effective structure of the data in the input space. We here present a growth algorithm, called the GSOM or growing self-organizing map, which enhances a widespread map self-organization process, Kohonen's self-organizing feature map (SOFM), by an adaptation of the output space grid during learning. The GSOM restricts the output space structure to the shape of a general hypercubical shape, with the overall dimensionality of the grid and its extensions along the different directions being subject of the adaptation. This constraint meets the demands of many larger information processing systems, of which the neural map can be a part. We apply our GSOM-algorithm to three examples, two of which involve real world data. Using recently developed methods for measuring the degree of neighborhood preservation in neural maps, we find the GSOM-algorithm to produce maps which preserve neighborhoods in a nearly optimal fashion.

Neuroimaging Study of the Human Amygdala - Toward an Understanding of Emotional and Stress Responses -

NASA Astrophysics Data System (ADS)

Iidaka, Tetsuya

The amygdala plays a critical role in the neural system involved in emotional responses and conditioned fear. The dysfunction of this system is thought to be a cause of several neuropsychiatric disorders. A neuroimaging study provides a unique opportunity for noninvasive investigation of the human amygdala. We studied the activity of this structure in normal subjects and patients with schizophrenia by using the face recognition task. Our results showed that the amygdala was activated by presentation of face stimuli, and negative face activated the amygdala to a greater extent than a neutral face. Under the happy face condition, the activation of the amygdala was higher in the schizophrenic patients than in control subjects. A single nucleotide polymorphism in the regulatory region of the serotonin type 3 receptor gene had modulatory effects on the amygdaloid activity. The emotion regulation had a significant impact on neural interaction between the amygdala and prefrontal cortices. Thus, studies on the human amygdala would greatly contribute to the elucidation of the neural system that determines emotional and stress responses. To clarify the relevance of the neural dysfunction and neuropsychiatric disorders, further studies using physiological, genetic, and hormonal approaches are essential.

Neural invasion in pancreatic carcinoma.

PubMed

Liu, Bin; Lu, Kui-Yang

2002-08-01

Neural invasion is a special metastatic route in pancreatic cancer and responsible for the high recurrence in curatively resected cases. To summarize the characteristics and mechanisms of neural invasion in pancreatic carcinoma for the better treatment of this disease. The international literatures were reviewed about the definition, incidence and mechanisms of neural invasion and its clinicopathology, diagnosis and treatment. Neural invasion is defined when the medial perineurium is involved by cancer cells, accounting for 45%-100% of all cases. It can be divided into different kinds or stages according to its locations and the number of nerve fascicles involved. Invasion along vascularity, lymphatic vessels, perineural space and neurotropism is considered as its primary mechanisms. No clinicopathologic factors are correlated with neural invasion. Intravascular ultrasound, CT scan and immunostaining K-ras gene analysis can be used to diagnose neural invasion pre-, intra- or postoperatively. Neural invasion is an important prognostic factor for the recurrence of pancreatic carcinoma after pancreatectomy. Because of its high incidence, pancreatectomy with extended radical retroperitoneal dissection should be considered as a basic procedure in the treatment of pancreatic carcinoma.

Synthetic Glycopolymers for Highly Efficient Differentiation of Embryonic Stem Cells into Neurons: Lipo- or Not?

PubMed

Liu, Qi; Lyu, Zhonglin; Yu, You; Zhao, Zhen-Ao; Hu, Shijun; Yuan, Lin; Chen, Gaojian; Chen, Hong

2017-04-05

To realize the potential application of embryonic stem cells (ESCs) for the treatment of neurodegenerative diseases, it is a prerequisite to develop an effective strategy for the neural differentiation of ESCs so as to obtain adequate amount of neurons. Considering the efficacy of glycosaminoglycans (GAG) and their disadvantages (e.g., structure heterogeneity and impurity), GAG-mimicking glycopolymers (designed polymers containing functional units similar to natural GAG) with or without phospholipid groups were synthesized in the present work and their ability to promote neural differentiation of mouse ESCs (mESCs) was investigated. It was found that the lipid-anchored GAG-mimicking glycopolymers (lipo-pSGF) retained on the membrane of mESCs rather than being internalized by cells after 1 h of incubation. Besides, lipo-pSGF showed better activity in promoting neural differentiation. The expression of the neural-specific maker β3-tubulin in lipo-pSGF-treated cells was ∼3.8- and ∼1.9-fold higher compared to natural heparin- and pSGF-treated cells at day 14. The likely mechanism involved in lipo-pSGF-mediated neural differentiation was further investigated by analyzing its effect on fibroblast growth factor 2 (FGF2)-mediated extracellular signal-regulated kinases 1 and 2 (ERK1/2) signaling pathway which is important for neural differentiation of ESCs. Lipo-pSGF was found to efficiently bind FGF2 and enhance the phosphorylation of ERK1/2, thus promoting neural differentiation. These findings demonstrated that engineering of cell surface glycan using our synthetic lipo-glycopolymer is a highly efficient approach for neural differentiation of ESCs and this strategy can be applied for the regulation of other cellular activities mediated by cell membrane receptors.

Geometric Bioinspired Networks for Recognition of 2-D and 3-D Low-Level Structures and Transformations.

PubMed

Bayro-Corrochano, Eduardo; Vazquez-Santacruz, Eduardo; Moya-Sanchez, Eduardo; Castillo-Munis, Efrain

2016-10-01

This paper presents the design of radial basis function geometric bioinspired networks and their applications. Until now, the design of neural networks has been inspired by the biological models of neural networks but mostly using vector calculus and linear algebra. However, these designs have never shown the role of geometric computing. The question is how biological neural networks handle complex geometric representations involving Lie group operations like rotations. Even though the actual artificial neural networks are biologically inspired, they are just models which cannot reproduce a plausible biological process. Until now researchers have not shown how, using these models, one can incorporate them into the processing of geometric computing. Here, for the first time in the artificial neural networks domain, we address this issue by designing a kind of geometric RBF using the geometric algebra framework. As a result, using our artificial networks, we show how geometric computing can be carried out by the artificial neural networks. Such geometric neural networks have a great potential in robot vision. This is the most important aspect of this contribution to propose artificial geometric neural networks for challenging tasks in perception and action. In our experimental analysis, we show the applicability of our geometric designs, and present interesting experiments using 2-D data of real images and 3-D screw axis data. In general, our models should be used to process different types of inputs, such as visual cues, touch (texture, elasticity, temperature), taste, and sound. One important task of a perception-action system is to fuse a variety of cues coming from the environment and relate them via a sensor-motor manifold with motor modules to carry out diverse reasoned actions.

Structural reliability calculation method based on the dual neural network and direct integration method.

PubMed

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Rafts, Nanoparticles and Neural Disease

PubMed Central

Gulati, Vishal; Wallace, Ron

2012-01-01

This review examines the role of membrane rafts in neural disease as a rationale for drug targeting utilizing lipid-based nanoparticles. The article begins with an overview of methodological issues involving the existence, sizes, and lifetimes of rafts, and then examines raft function in the etiologies of three major neural diseases—epilepsy, Parkinson’s disease, and Alzheimer’s disease—selected as promising candidates for raft-based therapeutics. Raft-targeting drug delivery systems involving liposomes and solid lipid nanoparticles are then examined in detail. PMID:28348305

Fabrication of micropatterned hydrogels for neural culture systems using dynamic mask projection photolithography.

PubMed

Curley, J Lowry; Jennings, Scott R; Moore, Michael J

2011-02-11

Increasingly, patterned cell culture environments are becoming a relevant technique to study cellular characteristics, and many researchers believe in the need for 3D environments to represent in vitro experiments which better mimic in vivo qualities. Studies in fields such as cancer research, neural engineering, cardiac physiology, and cell-matrix interaction have shown cell behavior differs substantially between traditional monolayer cultures and 3D constructs. Hydrogels are used as 3D environments because of their variety, versatility and ability to tailor molecular composition through functionalization. Numerous techniques exist for creation of constructs as cell-supportive matrices, including electrospinning, elastomer stamps, inkjet printing, additive photopatterning, static photomask projection-lithography, and dynamic mask microstereolithography. Unfortunately, these methods involve multiple production steps and/or equipment not readily adaptable to conventional cell and tissue culture methods. The technique employed in this protocol adapts the latter two methods, using a digital micromirror device (DMD) to create dynamic photomasks for crosslinking geometrically specific poly-(ethylene glycol) (PEG) hydrogels, induced through UV initiated free radical polymerization. The resulting "2.5D" structures provide a constrained 3D environment for neural growth. We employ a dual-hydrogel approach, where PEG serves as a cell-restrictive region supplying structure to an otherwise shapeless but cell-permissive self-assembling gel made from either Puramatrix or agarose. The process is a quick simple one step fabrication which is highly reproducible and easily adapted for use with conventional cell culture methods and substrates. Whole tissue explants, such as embryonic dorsal root ganglia (DRG), can be incorporated into the dual hydrogel constructs for experimental assays such as neurite outgrowth. Additionally, dissociated cells can be encapsulated in the photocrosslinkable or self polymerizing hydrogel, or selectively adhered to the permeable support membrane using cell-restrictive photopatterning. Using the DMD, we created hydrogel constructs up to ~1mm thick, but thin film (<200 μm) PEG structures were limited by oxygen quenching of the free radical polymerization reaction. We subsequently developed a technique utilizing a layer of oil above the polymerization liquid which allowed thin PEG structure polymerization. In this protocol, we describe the expeditious creation of 3D hydrogel systems for production of microfabricated neural cell and tissue cultures. The dual hydrogel constructs demonstrated herein represent versatile in vitro models that may prove useful for studies in neuroscience involving cell survival, migration, and/or neurite growth and guidance. Moreover, as the protocol can work for many types of hydrogels and cells, the potential applications are both varied and vast.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

PubMed

Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

2015-11-01

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

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

Liu, Hui; Song, Yongduan; Xue, Fangzheng

In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than themore » SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.« less

Neural correlates of Self and its interaction with memory in healthy adolescents

PubMed Central

Dégeilh, Fanny; Guillery-Girard, Bérengère; Dayan, Jacques; Gaubert, Malo; Chételat, Gael; 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 fMRI study consists in 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. PMID:26443236

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

Hippocampal Plasticity During the Progression of Alzheimer’s disease

PubMed Central

Mufson, Elliott J.; Mahady, Laura; Waters, Diana; Counts, Scott E.; Perez, Sylvia E.; DeKosky, Steven; Ginsberg, Stephen D.; Ikonomovic, Milos D.; Scheff, Stephen; Binder, Lester

2015-01-01

Neuroplasticity involves molecular changes in central nervous system (CNS) synaptic structure and function throughout life. The concept of neural organization allows for synaptic remodeling as a compensatory mechanism to the early pathobiology of Alzheimer’s disease (AD) in an attempt to maintain brain function and cognition during the onset of dementia. The hippocampus, a crucial component of the medial temporal lobe memory circuit, is affected early in AD and displays synaptic and intraneuronal molecular remodeling against a pathological background of extracellular amyloid-beta (Aβ) deposition and intracellular neurofibrillary tangle (NFT) formation in the early stages of AD. Here we discuss human clinical pathological findings supporting the concept that the hippocampus is capable of neural plasticity during mild cognitive impairment (MCI), a prodromal stage of AD and early stage AD. PMID:25772787

Modulation of hippocampal neural plasticity by glucose-related signaling.

PubMed

Mainardi, Marco; Fusco, Salvatore; Grassi, Claudio

2015-01-01

Hormones and peptides involved in glucose homeostasis are emerging as important modulators of neural plasticity. In this regard, increasing evidence shows that molecules such as insulin, insulin-like growth factor-I, glucagon-like peptide-1, and ghrelin impact on the function of the hippocampus, which is a key area for learning and memory. Indeed, all these factors affect fundamental hippocampal properties including synaptic plasticity (i.e., synapse potentiation and depression), structural plasticity (i.e., dynamics of dendritic spines), and adult neurogenesis, thus leading to modifications in cognitive performance. Here, we review the main mechanisms underlying the effects of glucose metabolism on hippocampal physiology. In particular, we discuss the role of these signals in the modulation of cognitive functions and their potential implications in dysmetabolism-related cognitive decline.

Neural responses to salient visual stimuli.

PubMed Central

Morris, J S; Friston, K J; Dolan, R J

1997-01-01

The neural mechanisms involved in the selective processing of salient or behaviourally important stimuli are uncertain. We used an aversive conditioning paradigm in human volunteer subjects to manipulate the salience of visual stimuli (emotionally expressive faces) presented during positron emission tomography (PET) neuroimaging. Increases in salience, and conflicts between the innate and acquired value of the stimuli, produced augmented activation of the pulvinar nucleus of the right thalamus. Furthermore, this pulvinar activity correlated positively with responses in structures hypothesized to mediate value in the brain right amygdala and basal forebrain (including the cholinergic nucleus basalis of Meynert). The results provide evidence that the pulvinar nucleus of the thalamus plays a crucial modulatory role in selective visual processing, and that changes in perceptual salience are mediated by value-dependent plasticity in pulvinar responses. PMID:9178546

Materials and technologies for soft implantable neuroprostheses

NASA Astrophysics Data System (ADS)

Lacour, Stéphanie P.; Courtine, Grégoire; Guck, Jochen

2016-10-01

Implantable neuroprostheses are engineered systems designed to restore or substitute function for individuals with neurological deficits or disabilities. These systems involve at least one uni- or bidirectional interface between a living neural tissue and a synthetic structure, through which information in the form of electrons, ions or photons flows. Despite a few notable exceptions, the clinical dissemination of implantable neuroprostheses remains limited, because many implants display inconsistent long-term stability and performance, and are ultimately rejected by the body. Intensive research is currently being conducted to untangle the complex interplay of failure mechanisms. In this Review, we emphasize the importance of minimizing the physical and mechanical mismatch between neural tissues and implantable interfaces. We explore possible materials solutions to design and manufacture neurointegrated prostheses, and outline their immense therapeutic potential.

Deficits in facial affect recognition among antisocial populations: a meta-analysis.

PubMed

Marsh, Abigail A; Blair, R J R

2008-01-01

Individuals with disorders marked by antisocial behavior frequently show deficits in recognizing displays of facial affect. Antisociality may be associated with specific deficits in identifying fearful expressions, which would implicate dysfunction in neural structures that subserve fearful expression processing. A meta-analysis of 20 studies was conducted to assess: (a) if antisocial populations show any consistent deficits in recognizing six emotional expressions; (b) beyond any generalized impairment, whether specific fear recognition deficits are apparent; and (c) if deficits in fear recognition are a function of task difficulty. Results show a robust link between antisocial behavior and specific deficits in recognizing fearful expressions. This impairment cannot be attributed solely to task difficulty. These results suggest dysfunction among antisocial individuals in specified neural substrates, namely the amygdala, involved in processing fearful facial affect.

Transition from 'model-based' to 'model-free' behavioral control in addiction: Involvement of the orbitofrontal cortex and dorsolateral striatum.

PubMed

Lucantonio, Federica; Caprioli, Daniele; Schoenbaum, Geoffrey

2014-01-01

Cocaine addiction is a complex and multidimensional process involving a number of behavioral and neural forms of plasticity. The behavioral transition from voluntary drug use to compulsive drug taking may be explained at the neural level by drug-induced changes in function or interaction between a flexible planning system, associated with prefrontal cortical regions, and a rigid habit system, associated with the striatum. The dichotomy between these two systems is operationalized in computational theory by positing model-based and model-free learning mechanisms, the former relying on an "internal model" of the environment and the latter on pre-computed or cached values to control behavior. In this review, we will suggest that model-free and model-based learning mechanisms appear to be differentially affected, at least in the case of psychostimulants such as cocaine, with the former being enhanced while the latter are disrupted. As a result, the behavior of long-term drug users becomes less flexible and responsive to the desirability of expected outcomes and more habitual, based on the long history of reinforcement. To support our specific proposal, we will review recent neural and behavioral evidence on the effect of psychostimulant exposure on orbitofrontal and dorsolateral striatum structure and function. This article is part of a Special Issue entitled 'NIDA 40th Anniversary Issue'. Published by Elsevier Ltd.

Reduced evoked fos expression in activity-related brain regions in animal models of behavioral depression.

PubMed

Stone, Eric A; Lehmann, Michael L; Lin, Yan; Quartermain, David

2007-08-15

A previous study showed that two mouse models of behavioral depression, immune system activation and depletion of brain monoamines, are accompanied by marked reductions in stimulated neural activity in brain regions involved in motivated behavior. The present study tested whether this effect is common to other depression models by examining the effects of repeated forced swimming, chronic subordination stress or acute intraventricular galanin injection - three additional models - on baseline or stimulated c-fos expression in several brain regions known to be involved in motor or motivational processes (secondary motor, M2, anterior piriform cortex, APIR, posterior cingulate gyrus, CG, nucleus accumbens, NAC). Each of the depression models was found to reduce the fos response stimulated by exposure to a novel cage or a swim stress in all four of these brain areas but not to affect the response of a stress-sensitive region (paraventricular hypothalamus, PVH) that was included for control purposes. Baseline fos expression in these structures was either unaffected or affected in an opposite direction to the stimulated response. Pretreatment with either desmethylimipramine (DMI) or tranylcypromine (tranyl) attenuated these changes. It is concluded that the pattern of a reduced neural function of CNS motor/motivational regions with an increased function of stress areas is common to 5 models of behavioral depression in the mouse and is a potential experimental analog of the neural activity changes occurring in the clinical condition.

The influence of emotion regulation on decision-making under risk.

PubMed

Martin, Laura N; Delgado, Mauricio R

2011-09-01

Cognitive strategies typically involved in regulating negative emotions have recently been shown to also be effective with positive emotions associated with monetary rewards. However, it is less clear how these strategies influence behavior, such as preferences expressed during decision-making under risk, and the underlying neural circuitry. That is, can the effective use of emotion regulation strategies during presentation of a reward-conditioned stimulus influence decision-making under risk and neural structures involved in reward processing such as the striatum? To investigate this question, we asked participants to engage in imagery-focused regulation strategies during the presentation of a cue that preceded a financial decision-making phase. During the decision phase, participants then made a choice between a risky and a safe monetary lottery. Participants who successfully used cognitive regulation, as assessed by subjective ratings about perceived success and facility in implementation of strategies, made fewer risky choices in comparison with trials where decisions were made in the absence of cognitive regulation. Additionally, BOLD responses in the striatum were attenuated during decision-making as a function of successful emotion regulation. These findings suggest that exerting cognitive control over emotional responses can modulate neural responses associated with reward processing (e.g., striatum) and promote more goal-directed decision-making (e.g., less risky choices), illustrating the potential importance of cognitive strategies in curbing risk-seeking behaviors before they become maladaptive (e.g., substance abuse).

Diminished caudate and superior temporal gyrus responses to effort-based decision making in patients with first-episode major depressive disorder.

PubMed

Yang, Xin-hua; Huang, Jia; Lan, Yong; Zhu, Cui-ying; Liu, Xiao-qun; Wang, Ye-fei; Cheung, Eric F C; Xie, Guang-rong; Chan, Raymond C K

2016-01-04

Anhedonia, the loss of interest or pleasure in reward processing, is a hallmark feature of major depressive disorder (MDD), but its underlying neurobiological mechanism is largely unknown. The present study aimed to examine the underlying neural mechanism of reward-related decision-making in patients with MDD. We examined behavioral and neural responses to rewards in patients with first-episode MDD (N=25) and healthy controls (N=25) using the Effort-Expenditure for Rewards Task (EEfRT). The task involved choices about possible rewards of varying magnitude and probability. We tested the hypothesis that individuals with MDD would exhibit a reduced neural response in reward-related brain structures involved in cost-benefit decision-making. Compared with healthy controls, patients with MDD showed significantly weaker responses in the left caudate nucleus when contrasting the 'high reward'-'low reward' condition, and blunted responses in the left superior temporal gyrus and the right caudate nucleus when contrasting high and low probabilities. In addition, hard tasks chosen during high probability trials were negatively correlated with superior temporal gyrus activity in MDD patients, while the same choices were negatively correlated with caudate nucleus activity in healthy controls. These results indicate that reduced caudate nucleus and superior temporal gyrus activation may underpin abnormal cost-benefit decision-making in MDD. Copyright © 2015 Elsevier Inc. All rights reserved.

Enhanced biocompatibility of neural probes by integrating microstructures and delivering anti-inflammatory agents via microfluidic channels

NASA Astrophysics Data System (ADS)

Liu, Bin; Kim, Eric; Meggo, Anika; Gandhi, Sachin; Luo, Hao; Kallakuri, Srinivas; Xu, Yong; Zhang, Jinsheng

2017-04-01

Objective. Biocompatibility is a major issue for chronic neural implants, involving inflammatory and wound healing responses of neurons and glial cells. To enhance biocompatibility, we developed silicon-parylene hybrid neural probes with open architecture electrodes, microfluidic channels and a reservoir for drug delivery to suppress tissue responses. Approach. We chronically implanted our neural probes in the rat auditory cortex and investigated (1) whether open architecture electrode reduces inflammatory reaction by measuring glial responses; and (2) whether delivery of antibiotic minocycline reduces inflammatory and tissue reaction. Four weeks after implantation, immunostaining for glial fibrillary acid protein (astrocyte marker) and ionizing calcium-binding adaptor molecule 1 (macrophages/microglia cell marker) were conducted to identify immunoreactive astrocyte and microglial cells, and to determine the extent of astrocytes and microglial cell reaction/activation. A comparison was made between using traditional solid-surface electrodes and newly-designed electrodes with open architecture, as well as between deliveries of minocycline and artificial cerebral-spinal fluid diffused through microfluidic channels. Main results. The new probes with integrated micro-structures induced minimal tissue reaction compared to traditional electrodes at 4 weeks after implantation. Microcycline delivered through integrated microfluidic channels reduced tissue response as indicated by decreased microglial reaction around the neural probes implanted. Significance. The new design will help enhance the long-term stability of the implantable 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.

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.

Geometrical structure of Neural Networks: Geodesics, Jeffrey's Prior and Hyper-ribbons

NASA Astrophysics Data System (ADS)

Hayden, Lorien; Alemi, Alex; Sethna, James

2014-03-01

Neural networks are learning algorithms which are employed in a host of Machine Learning problems including speech recognition, object classification and data mining. In practice, neural networks learn a low dimensional representation of high dimensional data and define a model manifold which is an embedding of this low dimensional structure in the higher dimensional space. In this work, we explore the geometrical structure of a neural network model manifold. A Stacked Denoising Autoencoder and a Deep Belief Network are trained on handwritten digits from the MNIST database. Construction of geodesics along the surface and of slices taken from the high dimensional manifolds reveal a hierarchy of widths corresponding to a hyper-ribbon structure. This property indicates that neural networks fall into the class of sloppy models, in which certain parameter combinations dominate the behavior. Employing this information could prove valuable in designing both neural network architectures and training algorithms. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No . DGE-1144153.

Neural correlates of nesting behavior in zebra finches (Taeniopygia guttata).

PubMed

Hall, Zachary J; Bertin, Marion; Bailey, Ida E; Meddle, Simone L; Healy, Susan D

2014-05-01

Nest building in birds involves a behavioral sequence (nest material collection and deposition in the nest) that offers a unique model for addressing how the brain sequences motor actions. In this study, we identified brain regions involved in nesting behavior in male and female zebra finches (Taeniopygia guttata). We used Fos immunohistochemistry to quantify production of the immediate early gene protein product Fos (a molecular indicator of neuronal activity) in the brain correlated this expression with the variation in nesting behavior. Using this technique, we found that neural circuitry involved in motor sequencing, social behavior, reward and motivation were active during nesting. Within pairs of nesting birds, the number of times a male picked up or deposited nesting material and the amount of time a female spent in the nest explained the variation in Fos expression in the anterior motor pathway, social behavior network, and reward neural circuits. Identification of the brain regions that are involved in nesting enables us to begin studying the roles of motor sequencing, context, and reward in construction behavior at the neural level. Copyright © 2014 Elsevier B.V. All rights reserved.

Neural correlates of nesting behavior in zebra finches (Taeniopygia guttata)

PubMed Central

Hall, Zachary J.; Bertin, Marion; Bailey, Ida E.; Meddle, Simone L.; Healy, Susan D.

2014-01-01

Nest building in birds involves a behavioral sequence (nest material collection and deposition in the nest) that offers a unique model for addressing how the brain sequences motor actions. In this study, we identified brain regions involved in nesting behavior in male and female zebra finches (Taeniopygia guttata). We used Fos immunohistochemistry to quantify production of the immediate early gene protein product Fos (a molecular indicator of neuronal activity) in the brain correlated this expression with the variation in nesting behavior. Using this technique, we found that neural circuitry involved in motor sequencing, social behavior, reward and motivation were active during nesting. Within pairs of nesting birds, the number of times a male picked up or deposited nesting material and the amount of time a female spent in the nest explained the variation in Fos expression in the anterior motor pathway, social behavior network, and reward neural circuits. Identification of the brain regions that are involved in nesting enables us to begin studying the roles of motor sequencing, context, and reward in construction behavior at the neural level. PMID:24508238

Stroke rehabilitation using noninvasive cortical stimulation: aphasia.

PubMed

Mylius, Veit; Zouari, Hela G; Ayache, Samar S; Farhat, Wassim H; Lefaucheur, Jean-Pascal

2012-08-01

Poststroke aphasia results from the lesion of cortical areas involved in the motor production of speech (Broca's aphasia) or in the semantic aspects of language comprehension (Wernicke's aphasia). Such lesions produce an important reorganization of speech/language-specific brain networks due to an imbalance between cortical facilitation and inhibition. In fact, functional recovery is associated with changes in the excitability of the damaged neural structures and their connections. Two main mechanisms are involved in poststroke aphasia recovery: the recruitment of perilesional regions of the left hemisphere in case of small lesion and the acquisition of language processing ability in homotopic areas of the nondominant right hemisphere when left hemispheric language abilities are permanently lost. There is some evidence that noninvasive cortical stimulation, especially when combined with language therapy or other therapeutic approaches, can promote aphasia recovery. Cortical stimulation was mainly used to either increase perilesional excitability or reduce contralesional activity based on the concept of reciprocal inhibition and maladaptive plasticity. However, recent studies also showed some positive effects of the reinforcement of neural activities in the contralateral right hemisphere, based on the potential compensatory role of the nondominant hemisphere in stroke recovery.

Neural basis of bilingual language control.

PubMed

Calabria, Marco; Costa, Albert; Green, David W; Abutalebi, Jubin

2018-06-19

Acquiring and speaking a second language increases demand on the processes of language control for bilingual as compared to monolingual speakers. Language control for bilingual speakers involves the ability to keep the two languages separated to avoid interference and to select one language or the other in a given conversational context. This ability is what we refer with the term "bilingual language control" (BLC). It is now well established that the architecture of this complex system of language control encompasses brain networks involving cortical and subcortical structures, each responsible for different cognitive processes such as goal maintenance, conflict monitoring, interference suppression, and selective response inhibition. Furthermore, advances have been made in determining the overlap between the BLC and the nonlinguistic executive control networks, under the hypothesis that the BLC processes are just an instantiation of a more domain-general control system. Here, we review the current knowledge about the neural basis of these control systems. Results from brain imaging studies of healthy adults and on the performance of bilingual individuals with brain damage are discussed. © 2018 New York Academy of Sciences.

Potential Involvement of Draxin in the Axonal Projection of Cranial Nerves, Especially Cranial Nerve X, in the Chick Hindbrain

PubMed Central

Zhang, Sanbing; Cui, Huixian; Wang, Lei; Kang, Lin; Huang, Guannan; Du, Juan; Li, Sha; Tanaka, Hideaki; Su, Yuhong

2016-01-01

The appropriate projection of axons within the nervous system is a crucial component of the establishment of neural circuitry. Draxin is a repulsive axon guidance protein. Draxin has important functions in the guidance of three commissures in the central nervous system and in the migration of neural crest cells and dI3 interneurons in the chick spinal cord. Here, we report that the distribution of the draxin protein and the location of 23C10-positive areas have a strong temporal and spatial correlation. The overexpression of draxin, especially transmembrane draxin, caused 23C10-positive axon bundles to misproject in the dorsal hindbrain. In addition, the overexpression of transmembrane draxin caused abnormal formation of the ganglion crest of the IX and X cranial nerves, misprojection of some anti-human natural killer-1 (HNK-1)-stained structures in the dorsal roof of the hindbrain, and a simultaneous reduction in the efferent nerves of some motoneuron axons inside the hindbrain. Our data reveal that draxin might be involved in the fascicular projection of cranial nerves in the hindbrain. PMID:27199282

Father's brain is sensitive to childcare experiences

PubMed Central

Abraham, Eyal; Hendler, Talma; Shapira-Lichter, Irit; Kanat-Maymon, Yaniv; Zagoory-Sharon, Orna; Feldman, Ruth

2014-01-01

Although contemporary socio-cultural changes dramatically increased fathers' involvement in childrearing, little is known about the brain basis of human fatherhood, its comparability with the maternal brain, and its sensitivity to caregiving experiences. We measured parental brain response to infant stimuli using functional MRI, oxytocin, and parenting behavior in three groups of parents (n = 89) raising their firstborn infant: heterosexual primary-caregiving mothers (PC-Mothers), heterosexual secondary-caregiving fathers (SC-Fathers), and primary-caregiving homosexual fathers (PC-Fathers) rearing infants without maternal involvement. Results revealed that parenting implemented a global “parental caregiving” neural network, mainly consistent across parents, which integrated functioning of two systems: the emotional processing network including subcortical and paralimbic structures associated with vigilance, salience, reward, and motivation, and mentalizing network involving frontopolar-medial-prefrontal and temporo-parietal circuits implicated in social understanding and cognitive empathy. These networks work in concert to imbue infant care with emotional salience, attune with the infant state, and plan adequate parenting. PC-Mothers showed greater activation in emotion processing structures, correlated with oxytocin and parent-infant synchrony, whereas SC-Fathers displayed greater activation in cortical circuits, associated with oxytocin and parenting. PC-Fathers exhibited high amygdala activation similar to PC-Mothers, alongside high activation of superior temporal sulcus (STS) comparable to SC-Fathers, and functional connectivity between amygdala and STS. Among all fathers, time spent in direct childcare was linked with the degree of amygdala-STS connectivity. Findings underscore the common neural basis of maternal and paternal care, chart brain–hormone–behavior pathways that support parenthood, and specify mechanisms of brain malleability with caregiving experiences in human fathers. PMID:24912146

Topographic and functional neuroanatomical study of GABAergic disinhibitory striatum-nigral inputs and inhibitory nigrocollicular pathways: neural hodology recruiting the substantia nigra, pars reticulata, for the modulation of the neural activity in the inferior colliculus involved with panic-like emotions.

PubMed

Castellan-Baldan, Lissandra; da Costa Kawasaki, Mateus; Ribeiro, Sandro José; Calvo, Fabrício; Corrêa, Vani Maria Alves; Coimbra, Norberto Cysne

2006-08-01

Considering the influence of the substantia nigra on mesencephalic neurons involved with fear-induced reactions organized in rostral aspects of the dorsal midbrain, the present work investigated the topographical and functional neuroanatomy of similar influence on caudal division of the corpora quadrigemina, addressing: (a) the neural hodology connecting the neostriatum, the substantia nigra, periaqueductal gray matter and inferior colliculus (IC) neural networks; (b) the influence of the inhibitory neostriatonigral-nigrocollicular GABAergic links on the control of the defensive behavior organized in the IC. The effects of the increase or decrease of activity of nigrocollicular inputs on defensive responses elicited by either electrical or chemical stimulation of the IC were also determined. Electrolytic or chemical lesions of the substantia nigra, pars reticulata (SNpr), decreased the freezing and escape behaviors thresholds elicited by electrical stimulation of the IC, and increased the behavioral responses evoked by the GABAA blockade in the same sites of the mesencephalic tectum (MT) electrically stimulated. These findings were corroborated by similar effects caused by microinjections of the GABAA-receptor agonist muscimol in the SNpr, followed by electrical and chemical stimulations of the IC. The GABAA blockade in the SNpr caused a significant increase in the defensive behavior thresholds elicited by electrical stimulation of the IC and a decrease in the mean incidence of panic-like responses induced by microinjections of bicuculline in the mesencephalic tectum (inferior colliculus). These findings suggest that the substantia nigra receives GABAergic inputs that modulate local and also inhibitory GABAergic outputs toward the IC. In fact, neurotracing experiments with fast blue and iontophoretic microinjections of biotinylated dextran amine either into the inferior colliculus or in the reticular division of the substantia nigra demonstrated a neural link between these structures, as well as between the neostriatum and SNpr.

Natural History of Plexiform Neurofibromas in NF1. Addendum

DTIC Science & Technology

2008-10-01

neural foraminal widening, greater sciatic notch widening, and spinal cord com- pression were evaluated. Lesion signal intensity charac- teristics were...neural foraminal widening (n=20), greater sciatic foramina widening (n=2), and neural canal involvement (n=18). Target-like appearance was noted in 53

Automated selection of computed tomography display parameters using neural networks

NASA Astrophysics Data System (ADS)

Zhang, Di; Neu, Scott; Valentino, Daniel J.

2001-07-01

A collection of artificial neural networks (ANN's) was trained to identify simple anatomical structures in a set of x-ray computed tomography (CT) images. These neural networks learned to associate a point in an image with the anatomical structure containing the point by using the image pixels located on the horizontal and vertical lines that ran through the point. The neural networks were integrated into a computer software tool whose function is to select an index into a list of CT window/level values from the location of the user's mouse cursor. Based upon the anatomical structure selected by the user, the software tool automatically adjusts the image display to optimally view the structure.

Age-related reorganization of functional networks for successful conflict resolution: a combined functional and structural MRI study.

PubMed

Schulte, Tilman; Müller-Oehring, Eva M; Chanraud, Sandra; Rosenbloom, Margaret J; Pfefferbaum, Adolf; Sullivan, Edith V

2011-11-01

Aging has readily observable effects on the ability to resolve conflict between competing stimulus attributes that are likely related to selective structural and functional brain changes. To identify age-related differences in neural circuits subserving conflict processing, we combined structural and functional MRI and a Stroop Match-to-Sample task involving perceptual cueing and repetition to modulate resources in healthy young and older adults. In our Stroop Match-to-Sample task, older adults handled conflict by activating a frontoparietal attention system more than young adults and engaged a visuomotor network more than young adults when processing repetitive conflict and when processing conflict following valid perceptual cueing. By contrast, young adults activated frontal regions more than older adults when processing conflict with perceptual cueing. These differential activation patterns were not correlated with regional gray matter volume despite smaller volumes in older than young adults. Given comparable performance in speed and accuracy of responding between both groups, these data suggest that successful aging is associated with functional reorganization of neural systems to accommodate functionally increasing task demands on perceptual and attentional operations. Copyright © 2009 Elsevier Inc. All rights reserved.

A Deep Machine Learning Method for Classifying Cyclic Time Series of Biological Signals Using Time-Growing Neural Network.

PubMed

Gharehbaghi, Arash; Linden, Maria

2017-10-12

This paper presents a novel method for learning the cyclic contents of stochastic time series: the deep time-growing neural network (DTGNN). The DTGNN combines supervised and unsupervised methods in different levels of learning for an enhanced performance. It is employed by a multiscale learning structure to classify cyclic time series (CTS), in which the dynamic contents of the time series are preserved in an efficient manner. This paper suggests a systematic procedure for finding the design parameter of the classification method for a one-versus-multiple class application. A novel validation method is also suggested for evaluating the structural risk, both in a quantitative and a qualitative manner. The effect of the DTGNN on the performance of the classifier is statistically validated through the repeated random subsampling using different sets of CTS, from different medical applications. The validation involves four medical databases, comprised of 108 recordings of the electroencephalogram signal, 90 recordings of the electromyogram signal, 130 recordings of the heart sound signal, and 50 recordings of the respiratory sound signal. Results of the statistical validations show that the DTGNN significantly improves the performance of the classification and also exhibits an optimal structural risk.

[Motivation and Emotional States: Structural Systemic, Neurochemical, Molecular and Cellular Mechanisms].

PubMed

Bazyan, A S

2016-01-01

The structural, systemic, neurochemical, molecular and cellular mechanisms of organization and coding motivation and emotional states are describe. The GABA and glutamatergic synaptic systems of basal ganglia form a neural network and participate in the implementation of voluntary behavior. Neuropeptides, neurohormones and paracrine neuromodulators involved in the organization of motivation and emotional states, integrated with synaptic systems, controlled by neural networks and organizing goal-directed behavior. Structural centers for united and integrated of information in voluntary and goal-directed behavior are globus pallidus. Substantia nigra pars reticulata switches the information from corticobasal networks to thalamocortical networks, induces global dopaminergic (DA) signal and organize interaction of mesolimbic and nigostriatnoy DA systems controlled by prefrontal and motor cortex. Together with the motor cortex, substantia nigra displays information in the brainstem and spinal cord to implementation of behavior. Motivation states are formed in the interaction of neurohormonal and neuropeptide systems by monoaminergic systems of brain. Emotional states are formed by monoaminergic systems of the mid-brain, where the leading role belongs to the mesolimbic DA system. The emotional and motivation state of the encoded specific epigenetic molecular and chemical pattern of neuron.

Brain structure links everyday creativity to creative achievement.

PubMed

Zhu, Wenfeng; Chen, Qunlin; Tang, Chaoying; Cao, Guikang; Hou, Yuling; Qiu, Jiang

2016-03-01

Although creativity is commonly considered to be a cornerstone of human progress and vital to all realms of our lives, its neural basis remains elusive, partly due to the different tasks and measurement methods applied in research. In particular, the neural correlates of everyday creativity that can be experienced by everyone, to some extent, are still unexplored. The present study was designed to investigate the brain structure underlying individual differences in everyday creativity, as measured by the Creative Behavioral Inventory (CBI) (N=163). The results revealed that more creative activities were significantly and positively associated with larger gray matter volume (GMV) in the regional premotor cortex (PMC), which is a motor planning area involved in the creation and selection of novel actions and inhibition. In addition, the gray volume of the PMC had a significant positive relationship with creative achievement and Art scores, which supports the notion that training and practice may induce changes in brain structures. These results indicate that everyday creativity is linked to the PMC and that PMC volume can predict creative achievement, supporting the view that motor planning may play a crucial role in creative behavior. Published by Elsevier Inc.

Cocaine action on peripheral, non-monoamine neural substrates as a trigger of EEG desynchronization and EMG activation following intravenous administration in freely moving rats

PubMed Central

Smirnov, Michael S.; Kiyatkin, Eugene A.

2009-01-01

Many important physiological, behavioral and subjective effects of intravenous (iv) cocaine (COC) are exceptionally rapid and transient, suggesting a possible involvement of peripheral neural substrates in their triggering. In the present study, we used high-speed EEG and EMG recordings (4-s resolution) in freely moving rats to characterize the central electrophysiological effects of iv COC at low doses within a self-administration range (0.25-1.0 mg/kg). We found that COC induces rapid, strong, and prolonged desynchronization of cortical EEG (decrease in alpha and increase in beta and gamma activity) and activation of the neck EMG that begin within 2-6 s following the start of a 10-s injection; immediate components of both effects were dose-independent. The rapid effects of COC were mimicked by iv COC methiodide, a derivative that cannot cross the blood-brain barrier. At equimolar doses (0.33-1.33 mg/kg), COC methiodide had equally fast and strong effects on EEG and EMG total powers, decreasing alpha and increasing beta and gamma activities. Rapid EEG desynchronization and EMG activation was also induced by iv procaine, a structurally similar, short-acting local anesthetic with virtually no effects on monoamine uptake; at equipotential doses (1.25-5.0 mg/kg), these effects were weaker and shorter in duration than those of COC. Surprisingly, iv saline injection delivered during slow-wave sleep (but not during quiet wakefulness) also induced a transient EEG desynchronization but without changes in EMG and motor activity; these effects were significantly weaker and much shorter than those induced by all tested drugs. These data suggest that in awake animals, iv COC induces rapid cortical activation and a subsequent motor response via its action on peripheral non-monoamine neural elements, involving neural transmission via visceral sensory pathways. By providing a rapid neural signal and triggering neural activation, such an action might play a crucial role in the sensory effects of COC, thus contributing to the learning and development of drug-taking behavior. PMID:19861149

Cocaine action on peripheral, non-monoamine neural substrates as a trigger of electroencephalographic desynchronization and electromyographic activation following i.v. administration in freely moving rats.

PubMed

Smirnov, M S; Kiyatkin, E A

2010-01-20

Many important physiological, behavioral and subjective effects of i.v. cocaine (COC) are exceptionally rapid and transient, suggesting a possible involvement of peripheral neural substrates in their triggering. In the present study, we used high-speed electroencephalographic (EEG) and electromyographic (EMG) recordings (4-s resolution) in freely moving rats to characterize the central electrophysiological effects of i.v. COC at low doses within a self-administration range (0.25-1.0 mg/kg). We found that COC induces rapid, strong, and prolonged desynchronization of cortical EEG (decrease in alpha and increase in beta and gamma activity) and activation of the neck EMG that begin within 2-6 s following the start of a 10-s injection; immediate components of both effects were dose-independent. The rapid effects of COC were mimicked by i.v. COC methiodide (COC-MET), a derivative that cannot cross the blood-brain barrier. At equimolar doses (0.33-1.33 mg/kg), COC-MET had equally fast and strong effects on EEG and EMG total powers, decreasing alpha and increasing beta and gamma activities. Rapid EEG desynchronization and EMG activation was also induced by i.v. procaine, a structurally similar, short-acting local anesthetic with virtually no effects on monoamine uptake; at equipotential doses (1.25-5.0 mg/kg), these effects were weaker and shorter in duration than those of COC. Surprisingly, i.v. saline injection delivered during slow-wave sleep (but not during quiet wakefulness) also induced a transient EEG desynchronization but without changes in EMG and motor activity; these effects were significantly weaker and much shorter than those induced by all tested drugs. These data suggest that in awake animals, i.v. COC induces rapid cortical activation and a subsequent motor response via its action on peripheral non-monoamine neural elements, involving neural transmission via visceral sensory pathways. By providing a rapid neural signal and triggering neural activation, such an action might play a crucial role in the sensory effects of COC, thus contributing to the learning and development of drug-taking behavior.

Neural model of gene regulatory network: a survey on supportive meta-heuristics.

PubMed

Biswas, Surama; Acharyya, Sriyankar

2016-06-01

Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

Mindfulness training induces structural connectome changes in insula networks.

PubMed

Sharp, Paul B; Sutton, Bradley P; Paul, Erick J; Sherepa, Nikolai; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Prakash, Ruchika Shaurya; Heller, Wendy; Telzer, Eva H; Barbey, Aron K

2018-05-21

Although mindfulness meditation is known to provide a wealth of psychological benefits, the neural mechanisms involved in these effects remain to be well characterized. A central question is whether the observed benefits of mindfulness training derive from specific changes in the structural brain connectome that do not result from alternative forms of experimental intervention. Measures of whole-brain and node-level structural connectome changes induced by mindfulness training were compared with those induced by cognitive and physical fitness training within a large, multi-group intervention protocol (n = 86). Whole-brain analyses examined global graph-theoretical changes in structural network topology. A hypothesis-driven approach was taken to investigate connectivity changes within the insula, which was predicted here to mediate interoceptive awareness skills that have been shown to improve through mindfulness training. No global changes were observed in whole-brain network topology. However, node-level results confirmed a priori hypotheses, demonstrating significant increases in mean connection strength in right insula across all of its connections. Present findings suggest that mindfulness strengthens interoception, operationalized here as the mean insula connection strength within the overall connectome. This finding further elucidates the neural mechanisms of mindfulness meditation and motivates new perspectives about the unique benefits of mindfulness training compared to contemporary cognitive and physical fitness interventions.

The syntactic organization of pasta-eating and the structure of reach movements in the head-fixed mouse.

PubMed

Whishaw, Ian Q; Faraji, Jamshid; Kuntz, Jessica R; Mirza Agha, Behroo; Metz, Gerlinde A S; Mohajerani, Majid H

2017-09-08

Mice are adept in the use of their hands for activities such as feeding, which has led to their use in investigations of the neural basis of skilled-movements. We describe the syntactic organization of pasta-eating and the structure of hand movements used for pasta manipulation by the head-fixed mouse. An ethogram of mice consuming pieces of spaghetti reveals that they eat in bite/chew bouts. A bout begins with pasta lifted to the mouth and then manipulated with hand movements into a preferred orientation for biting. Manipulation involves many hand release-reach movements, each with a similar structure. A hand is advanced from a digit closed and flexed (collect) position to a digit extended and open position (overgrasp) and then to a digit closed and flexed (grasp) position. Reach distance, hand shaping, and grasp patterns featuring precision grasps or whole hand grasps are related. To bite, mice display hand preference and asymmetric grasps; one hand (guide grasp) directs food into the mouth and the other stabilizes the pasta for biting. When chewing after biting, the hands hold the pasta in a symmetric resting position. Pasta-eating is organized and features structured hand movements and so lends itself to the neural investigation of skilled-movements.

Motor Cortex Reorganization across the Lifespan

ERIC Educational Resources Information Center

Plowman, Emily K.; Kleim, Jeffrey A.

2010-01-01

The brain is a highly dynamic structure with the capacity for profound structural and functional change. Such neural plasticity has been well characterized within motor cortex and is believed to represent one of the neural mechanisms for acquiring and modifying motor behaviors. A number of behavioral and neural signals have been identified that…

An amphioxus winged helix/forkhead gene, AmphiFoxD: insights into vertebrate neural crest evolution

NASA Technical Reports Server (NTRS)

Yu, Jr-Kai; Holland, Nicholas D.; Holland, Linda Z.

2002-01-01

During amphioxus development, the neural plate is bordered by cells expressing many genes with homologs involved in vertebrate neural crest induction. However, these amphioxus cells evidently lack additional genetic programs for the cell delaminations, migrations, and differentiations characterizing definitive vertebrate neural crest. We characterize an amphioxus winged helix/forkhead gene (AmphiFoxD) closely related to vertebrate FoxD genes. Phylogenetic analysis indicates that the AmphiFoxD is basal to vertebrate FoxD1, FoxD2, FoxD3, FoxD4, and FoxD5. One of these vertebrate genes (FoxD3) consistently marks neural crest during development. Early in amphioxus development, AmphiFoxD is expressed medially in the anterior neural plate as well as in axial (notochordal) and paraxial mesoderm; later, the gene is expressed in the somites, notochord, cerebral vesicle (diencephalon), and hindgut endoderm. However, there is never any expression in cells bordering the neural plate. We speculate that an AmphiFoxD homolog in the common ancestor of amphioxus and vertebrates was involved in histogenic processes in the mesoderm (evagination and delamination of the somites and notochord); then, in the early vertebrates, descendant paralogs of this gene began functioning in the presumptive neural crest bordering the neural plate to help make possible the delaminations and cell migrations that characterize definitive vertebrate neural crest. Copyright 2002 Wiley-Liss, Inc.

Optogenetic dissection of neural circuits underlying emotional valence and motivated behaviors

PubMed Central

Nieh, Edward H.; Kim, Sung-Yon; Namburi, Praneeth; Tye, Kay M.

2014-01-01

The neural circuits underlying emotional valence and motivated behaviors are several synapses away from both defined sensory inputs and quantifiable motor outputs. Electrophysiology has provided us with a suitable means for observing neural activity during behavior, but methods for controlling activity for the purpose of studying motivated behaviors have been inadequate: electrical stimulation lacks cellular specificity and pharmacological manipulation lacks temporal resolution. The recent emergence of optogenetic tools provides a new means for establishing causal relationships between neural activity and behavior. Optogenetics, the use of genetically-encodable light-activated proteins, permits the modulation of specific neural circuit elements with millisecond precision. The ability to control individual cell types, and even projections between distal regions, allows us to investigate functional connectivity in a causal manner. The greatest consequence of controlling neural activity with finer precision has been the characterization of individual neural circuits within anatomical brain regions as defined functional units. Within the mesolimbic dopamine system, optogenetics has helped separate subsets of dopamine neurons with distinct functions for reward, aversion and salience processing, elucidated GABA neuronal effects on behavior, and characterized connectivity with forebrain and cortical structures. Within the striatum, optogenetics has confirmed the opposing relationship between direct and indirect pathway medium spiny neurons (MSNs), in addition to characterizing the inhibition of MSNs by cholinergic interneurons. Within the hypothalamus, optogenetics has helped overcome the heterogeneity in neuronal cell-type and revealed distinct circuits mediating aggression and feeding. Within the amygdala, optogenetics has allowed the study of intra-amygdala microcircuitry as well as interconnections with distal regions involved in fear and anxiety. In this review, we will present the body of optogenetic studies that has significantly enhanced our understanding of emotional valence and motivated behaviors. PMID:23142759

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

Characterizing Deep Brain Stimulation effects in computationally efficient neural network models.

PubMed

Latteri, Alberta; Arena, Paolo; Mazzone, Paolo

2011-04-15

Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to find efficient treatments to face with this important disease. Experimental results in fact show that the PD neurological diseases are characterized by a pathological signal synchronization in BG. Parkinsonian tremor, for example, is ascribed to be caused by neuron populations of the Thalamic and Striatal structures that undergo an abnormal synchronization. On the contrary, in normal conditions, the activity of the same neuron populations do not appear to be correlated and synchronized. To study in details the effect of the stimulation signal on a pathological neural medium, efficient models of these neural structures were built, which are able to show, without any external input, the intrinsic properties of a pathological neural tissue, mimicking the BG synchronized dynamics.We start considering a model already introduced in the literature to investigate the effects of electrical stimulation on pathologically synchronized clusters of neurons. This model used Morris Lecar type neurons. This neuron model, although having a high level of biological plausibility, requires a large computational effort to simulate large scale networks. For this reason we considered a reduced order model, the Izhikevich one, which is computationally much lighter. The comparison between neural lattices built using both neuron models provided comparable results, both without traditional stimulation and in presence of all the stimulation protocols. This was a first result toward the study and simulation of the large scale neural networks involved in pathological dynamics.Using the reduced order model an inspection on the activity of two neural lattices was also carried out at the aim to analyze how the stimulation in one area could affect the dynamics in another area, like the usual medical treatment protocols require.The study of population dynamics that was carried out allowed us to investigate, through simulations, the positive effects of the stimulation signals in terms of desynchronization of the neural dynamics. The results obtained constitute a significant added value to the analysis of synchronization and desynchronization effects due to neural stimulation. This work gives the opportunity to more efficiently study the effect of stimulation in large scale yet computationally efficient neural networks. Results were compared both with the other mathematical models, using Morris Lecar and Izhikevich neurons, and with simulated Local Field Potentials (LFP).

Neural processing of musical meter in musicians and non-musicians.

PubMed

Zhao, T Christina; Lam, H T Gloria; Sohi, Harkirat; Kuhl, Patricia K

2017-11-01

Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses indicated that the reduction was driven by responses to sounds that defined the structure (Standard), not by responses to Deviants. We argue that musicians maintain a more accurate and efficient mental model for metrical structures, which incorporates occasional disruptions using significantly fewer neural resources. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural Correlates of Glucocorticoids Effects on Autobiographical Memory Retrieval in Healthy Women.

PubMed

Fleischer, Juliane; Metz, Sophie; Düsenberg, Moritz; Grimm, Simone; Golde, Sabrina; Roepke, Stefan; Renneberg, Babette; Wolf, Oliver T; Otte, Christian; Wingenfeld, Katja

2018-06-22

It is well known that elevated cortisol after stress or after exogenous administration impairs episodic memory retrieval including autobiographical memory (AM) retrieval. This impairment might be mediated by deactivation of a neural network associated with memory retrieval including the prefrontal cortex (PFC) and limbic structures. However, the neural underpinnings of these cortisol effects on AM retrieval have not been investigated yet. In this study, thirty-three healthy women received either placebo or 10 mg hydrocortisone in a double blind cross-over design before completing an AM test during fMRI. In this test, participants are asked to recall specific events from their own past in response to a cue word. In a first step, we analyzed the neural underpinnings of AM retrieval in the placebo condition. We found an activation pattern consistent with core regions involved in autobiographical memory recall, including the ventromedial PFC, anterior medial (am)PFC, inferior frontal gyrus, the posterior cingulate cortex, the tempoparietal junction, the middle temporal gyrus and the hippocampus. Further, we analyzed brain activation during AM retrieval after hydrocortisone compared to placebo. Region of interest (ROI) analyses revealed a hydrocortisone-induced deactivation during AM retrieval in the right amPFC. Results of the ROI analyses were non-significant in the left and right hippocampus, the left and right vmPFC and the left amPFC In sum, during AM retrieval hydrocortisone had the most pronounced effects on the amPFC. This might be explained by the strong involvement of this brain region in self-referential behavior, which is essential for recalling autobiographic information. Copyright © 2018. Published by Elsevier B.V.

Estimating the functional dimensionality of neural representations.

PubMed

Ahlheim, Christiane; Love, Bradley C

2018-06-07

Recent advances in multivariate fMRI analysis stress the importance of information inherent to voxel patterns. Key to interpreting these patterns is estimating the underlying dimensionality of neural representations. Dimensions may correspond to psychological dimensions, such as length and orientation, or involve other coding schemes. Unfortunately, the noise structure of fMRI data inflates dimensionality estimates and thus makes it difficult to assess the true underlying dimensionality of a pattern. To address this challenge, we developed a novel approach to identify brain regions that carry reliable task-modulated signal and to derive an estimate of the signal's functional dimensionality. We combined singular value decomposition with cross-validation to find the best low-dimensional projection of a pattern of voxel-responses at a single-subject level. Goodness of the low-dimensional reconstruction is measured as Pearson correlation with a test set, which allows to test for significance of the low-dimensional reconstruction across participants. Using hierarchical Bayesian modeling, we derive the best estimate and associated uncertainty of underlying dimensionality across participants. We validated our method on simulated data of varying underlying dimensionality, showing that recovered dimensionalities match closely true dimensionalities. We then applied our method to three published fMRI data sets all involving processing of visual stimuli. The results highlight three possible applications of estimating the functional dimensionality of neural data. Firstly, it can aid evaluation of model-based analyses by revealing which areas express reliable, task-modulated signal that could be missed by specific models. Secondly, it can reveal functional differences across brain regions. Thirdly, knowing the functional dimensionality allows assessing task-related differences in the complexity of neural patterns. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

PubMed

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

Physical exercise increases involvement of motor networks as a compensatory mechanism during a cognitively challenging task.

PubMed

Ji, Lanxin; Pearlson, Godfrey D; Zhang, Xue; Steffens, David C; Ji, Xiaoqing; Guo, Hua; Wang, Lihong

2018-05-31

Neuroimaging studies suggest that older adults may compensate for declines in cognitive function through neural compensation and reorganization of neural resources. While neural compensation as a key component of cognitive reserve is an important factor that mediates cognitive decline, the field lacks a quantitative measure of neural compensatory ability, and little is known about factors that may modify compensation, such as physical exercise. Twenty-five healthy older adults participated in a 6-week dance training exercise program. Gait speed, cognitive function, and functional magnetic resonance imaging during a challenging memory task were measured before and after the exercise program. In this study, we used a newly proposed data-driven independent component analysis approach to measure neural compensatory ability and tested the effect of physical exercise on neural compensation through a longitudinal study. After the exercise program, participants showed significantly improved memory performance in Logical Memory Test (WMS(LM)) (P < .001) and Rey Auditory Verbal Learning Test (P = .001) and increased gait speed measured by the 6-minute walking test (P = .01). Among all identified neural networks, only the motor cortices and cerebellum showed greater involvement during the memory task after exercise. Importantly, subjects who activated the motor network only after exercise (but not before exercise) showed WMS(LM) increases. We conclude that physical exercise improved gait speed, cognitive function, and compensatory ability through increased involvement of motor-related networks. Copyright © 2018 John Wiley & Sons, Ltd.

Cognitive Control Mechanisms, Emotion & Memory: A neural perspective with implications for psychopathology

PubMed Central

Banich, Marie T.; Mackiewicz, Kristen L.; Depue, Brendan E.; Whitmer, Anson; Miller, Gregory A.; Heller, Wendy

2009-01-01

In this paper we provide a focused review of the literature examining neural mechanisms involved in cognitive control over memory processes that can influence, and in turn are influenced, by emotional processes. The review is divided into two parts, the first focusing on working memory and the second on long-term memory. With regard to working memory, we discuss the neural bases of 1) control mechanisms that can select against distracting emotional information, 2) mechanisms that can regulate emotional reactions or responses, 3) how mood state influences cognitive control, and 4) individual differences in control mechanisms. For long-term memory, we briefly review 1) the neural substrates of emotional memory, 2) the cognitive and neural mechanisms that are involved in controlling emotional memories and 3) how these systems are altered in post-traumatic stress disorder. Finally, we consider tentative generalizations that can be drawn from this relatively unexplored conjunction of research endeavors. PMID:18948135

The Effects of Aging on the Neural Basis of Implicit Associative Learning in a Probabilistic Triplets Learning Task

ERIC Educational Resources Information Center

Simon, Jessica R.; Vaidya, Chandan J.; Howard, James H., Jr.; Howard, Darlene V.

2012-01-01

Few studies have investigated how aging influences the neural basis of implicit associative learning, and available evidence is inconclusive. One emerging behavioral pattern is that age differences increase with practice, perhaps reflecting the involvement of different brain regions with training. Many studies report hippocampal involvement early…

Neural markers of loss aversion in resting-state brain activity.

PubMed

Canessa, Nicola; Crespi, Chiara; Baud-Bovy, Gabriel; Dodich, Alessandra; Falini, Andrea; Antonellis, Giulia; Cappa, Stefano F

2017-02-01

Neural responses in striatal, limbic and somatosensory brain regions track individual differences in loss aversion, i.e. the higher sensitivity to potential losses compared with equivalent gains in decision-making under risk. The engagement of structures involved in the processing of aversive stimuli and experiences raises a further question, i.e. whether the tendency to avoid losses rather than acquire gains represents a transient fearful overreaction elicited by choice-related information, or rather a stable component of one's own preference function, reflecting a specific pattern of neural activity. We tested the latter hypothesis by assessing in 57 healthy human subjects whether the relationship between behavioral and neural loss aversion holds at rest, i.e. when the BOLD signal is collected during 5minutes of cross-fixation in the absence of an explicit task. Within the resting-state networks highlighted by a spatial group Independent Component Analysis (gICA), we found a significant correlation between strength of activity and behavioral loss aversion in the left ventral striatum and right posterior insula/supramarginal gyrus, i.e. the very same regions displaying a pattern of neural loss aversion during explicit choices. Cross-study analyses confirmed that this correlation holds when voxels identified by gICA are used as regions of interest in task-related activity and vice versa. These results suggest that the individual degree of (neural) loss aversion represents a stable dimension of decision-making, which reflects in specific metrics of intrinsic brain activity at rest possibly modulating cortical excitability at choice. Copyright © 2016 Elsevier Inc. All rights reserved.

Emergence of semiology in epileptic seizures.

PubMed

Chauvel, Patrick; McGonigal, Aileen

2014-09-01

Semiology, the manifestation of epilepsy, is dependent upon electrical activity produced by epileptic seizures that are organized within existing neural pathways. Clinical signs evolve as the epileptic discharge spreads in both time and space. Studying the relation between these, of which the temporal component is at least as important as the spatial one, is possible using anatomo-electro-clinical correlations of stereoelectroencephalography (SEEG) data. The period of semiology production occurs with variable time lag after seizure onset and signs then emerge more or less rapidly depending on seizure type (temporal seizures generally propagating more slowly and frontal seizures more quickly). The subset of structures involved in semiological production, the "early spread network", is tightly linked to those constituting the epileptogenic zone. The level of complexity of semiological features varies according to the degree of involvement of the primary or associative cortex, with the former having a direct relation to peripheral sensory and motor systems with production of hallucinations (visual and auditory) or elementary sensorimotor signs. Depending on propagation pattern, these signs can occur in a "march" fashion as described by Jackson. On the other hand, seizures involving the associative cortex, having a less direct relation with the peripheral nervous system, and necessarily involving more widely distributed networks manifest with altered cognitive and/or behavioral signs whose neural substrate involves a network of cortical structures, as has been observed for normal cognitive processes. Other than the anatomical localization of these structures, the frequency of the discharge is a crucial determinant of semiological effect since a fast (gamma) discharge will tend to deactivate normal function, whereas a slower theta discharge can mimic physiological function. In terms of interaction between structures, the degree of synchronization plays a key role in clinical expression, as evidenced, for example, by studies of ictal fear-related behavior (decorrelation of activity between structures inducing "release" phenomena) and of déjà vu (increased synchronization). Studies of functional coupling within networks underlying complex ictal behavior indicate that the clinical semiology of a given seizure depends upon neither the anatomical origin of ictal discharge nor the target areas of its propagation alone but on the dynamic interaction between these. Careful mapping of the ictal network in its full spread offers essential information as to the localization of seizure onset, by deducing that a given network configuration could only be generated by a given area or group of areas. Copyright © 2013. Published by Elsevier Inc.

Maternal interpersonal affiliation is associated with adolescents' brain structure and reward processing

PubMed Central

Schneider, S; Brassen, S; Bromberg, U; Banaschewski, T; Conrod, P; Flor, H; Gallinat, J; Garavan, Hugh; Heinz, A; Martinot, J-L; Nees, F; Rietschel, M; Smolka, M N; Ströhle, A; Struve, M; Schumann, G; Büchel, C

2012-01-01

Considerable animal and human research has been dedicated to the effects of parenting on structural brain development, focusing on hippocampal and prefrontal areas. Conversely, although functional imaging studies suggest that the neural reward circuitry is involved in parental affection, little is known about mothers' interpersonal qualities in relation to their children's brain structure and function. Moreover, gender differences concerning the effect of maternal qualities have rarely been investigated systematically. In 63 adolescents, we assessed structural and functional magnetic resonance imaging as well as interpersonal affiliation in their mothers. This allowed us to associate maternal affiliation with gray matter density and neural responses during different phases of the well-established Monetary Incentive Delay task. Maternal affiliation was positively associated with hippocampal and orbitofrontal gray matter density. Moreover, in the feedback of reward hit as compared with reward miss, an association with caudate activation was found. Although no significant gender effects were observed in these associations, during reward feedback as compared with baseline, maternal affiliation was significantly associated with ventral striatal and caudate activation only in females. Our findings demonstrate that maternal interpersonal affiliation is related to alterations in both the brain structure and reward-related activation in healthy adolescents. Importantly, the pattern is in line with typical findings in depression and post-traumatic stress disorder, suggesting that a lack of maternal affiliation might have a role in the genesis of mental disorders. PMID:23149446

Genetic variant rs17225178 in the ARNT2 gene is associated with Asperger Syndrome.

PubMed

Di Napoli, Agnese; Warrier, Varun; Baron-Cohen, Simon; Chakrabarti, Bhismadev

2015-01-01

Autism Spectrum Conditions (ASC) are neurodevelopmental conditions characterized by difficulties in communication and social interaction, alongside unusually repetitive behaviours and narrow interests. Asperger Syndrome (AS) is one subgroup of ASC and differs from classic autism in that in AS there is no language or general cognitive delay. Genetic, epigenetic and environmental factors are implicated in ASC and genes involved in neural connectivity and neurodevelopment are good candidates for studying the susceptibility to ASC. The aryl-hydrocarbon receptor nuclear translocator 2 (ARNT2) gene encodes a transcription factor involved in neurodevelopmental processes, neuronal connectivity and cellular responses to hypoxia. A mutation in this gene has been identified in individuals with ASC and single nucleotide polymorphisms (SNPs) have been nominally associated with AS and autistic traits in previous studies. In this study, we tested 34 SNPs in ARNT2 for association with AS in 118 cases and 412 controls of Caucasian origin. P values were adjusted for multiple comparisons, and linkage disequilibrium (LD) among the SNPs analysed was calculated in our sample. Finally, SNP annotation allowed functional and structural analyses of the genetic variants in ARNT2. We tested the replicability of our result using the genome-wide association studies (GWAS) database of the Psychiatric Genomics Consortium (PGC). We report statistically significant association of rs17225178 with AS. This SNP modifies transcription factor binding sites and regions that regulate the chromatin state in neural cell lines. It is also included in a LD block in our sample, alongside other genetic variants that alter chromatin regulatory regions in neural cells. These findings demonstrate that rs17225178 in the ARNT2 gene is associated with AS and support previous studies that pointed out an involvement of this gene in the predisposition to ASC.

The origins of originality: the neural bases of creative thinking and originality.

PubMed

Shamay-Tsoory, S G; Adler, N; Aharon-Peretz, J; Perry, D; Mayseless, N

2011-01-01

Although creativity has been related to prefrontal activity, recent neurological case studies postulate that patients who have left frontal and temporal degeneration involving deterioration of language abilities may actually develop de novo artistic abilities. In this study, we propose a neural and cognitive model according to which a balance between the two hemispheres affects a major aspect of creative cognition, namely, originality. In order to examine the neural basis of originality, that is, the ability to produce statistically infrequent ideas, patients with localized lesions in the medial prefrontal cortex (mPFC), inferior frontal gyrus (IFG), and posterior parietal and temporal cortex (PC), were assessed by two tasks involving divergent thinking and originality. Results indicate that lesions in the mPFC involved the most profound impairment in originality. Furthermore, precise anatomical mapping of lesions indicated that while the extent of lesion in the right mPFC was associated with impaired originality, lesions in the left PC were associated with somewhat elevated levels of originality. A positive correlation between creativity scores and left PC lesions indicated that the larger the lesion is in this area the greater the originality. On the other hand, a negative correlation was observed between originality scores and lesions in the right mPFC. It is concluded that the right mPFC is part of a right fronto-parietal network which is responsible for producing original ideas. It is possible that more linear cognitive processing such as language, mediated by left hemisphere structures interferes with creative cognition. Therefore, lesions in the left hemisphere may be associated with elevated levels of originality. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

Neural-like growing networks

NASA Astrophysics Data System (ADS)

Yashchenko, Vitaliy A.

2000-03-01

On the basis of the analysis of scientific ideas reflecting the law in the structure and functioning the biological structures of a brain, and analysis and synthesis of knowledge, developed by various directions in Computer Science, also there were developed the bases of the theory of a new class neural-like growing networks, not having the analogue in world practice. In a base of neural-like growing networks the synthesis of knowledge developed by classical theories - semantic and neural of networks is. The first of them enable to form sense, as objects and connections between them in accordance with construction of the network. With thus each sense gets a separate a component of a network as top, connected to other tops. In common it quite corresponds to structure reflected in a brain, where each obvious concept is presented by certain structure and has designating symbol. Secondly, this network gets increased semantic clearness at the expense owing to formation not only connections between neural by elements, but also themselves of elements as such, i.e. here has a place not simply construction of a network by accommodation sense structures in environment neural of elements, and purely creation of most this environment, as of an equivalent of environment of memory. Thus neural-like growing networks are represented by the convenient apparatus for modeling of mechanisms of teleological thinking, as a fulfillment of certain psychophysiological of functions.

Enhanced immunohistochemical detection of neural infiltration in primary melanoma: is there a clinical value?

PubMed

Scanlon, Patrick; Tian, Jaiying; Zhong, Judy; Silva, Ines; Shapiro, Richard; Pavlick, Anna; Berman, Russell; Osman, Iman; Darvishian, Farbod

2014-08-01

Neural infiltration in primary melanoma is a histopathologic feature that has been associated with desmoplastic histopathologic subtype and local recurrence in the literature. We tested the hypothesis that improved detection and characterization of neural infiltration into peritumoral or intratumoral location and perineural or intraneural involvement could have a prognostic relevance. We studied 128 primary melanoma cases prospectively accrued and followed at New York University using immunohistochemical detection with antihuman neurofilament protein and routine histology with hematoxylin and eosin. Neural infiltration, defined as the presence of tumor cells involving or immediately surrounding nerve foci, was identified and characterized using both detection methods. Neural infiltration rate of detection was enhanced by immunohistochemistry for neurofilament in matched-pair design (47% by immunohistochemistry versus 25% by routine histology). Immunohistochemical detection of neural infiltration was significantly associated with ulceration (P = .021), desmoplastic and acral lentiginous histologic subtype (P = .008), and head/neck/hands/feet tumor location (P = .037). Routinely detected neural infiltration was significantly associated with local recurrence (P = .010). Immunohistochemistry detected more intratumoral neural infiltration cases compared with routine histology (30% versus 3%, respectively). Peritumoral and intratumoral nerve location had no impact on clinical outcomes. Using a multivariate model controlling for stage, neither routinely detected neural infiltration nor enhanced immunohistochemical characterization of neural infiltration was significantly associated with disease-free or overall survival. Our data demonstrate that routinely detected neural infiltration is associated with local recurrence in all histologic subtypes but that improved detection and characterization of neural infiltration with immunohistochemistry in primary melanoma does not add to prognostic relevance. Copyright © 2014 Elsevier Inc. All rights reserved.

Accelerating Learning By Neural Networks

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad; Barhen, Jacob

1992-01-01

Electronic neural networks made to learn faster by use of terminal teacher forcing. Method of supervised learning involves addition of teacher forcing functions to excitations fed as inputs to output neurons. Initially, teacher forcing functions are strong enough to force outputs to desired values; subsequently, these functions decay with time. When learning successfully completed, terminal teacher forcing vanishes, and dynamics or neural network become equivalent to those of conventional neural network. Simulated neural network with terminal teacher forcing learned to produce close approximation of circular trajectory in 400 iterations.

Dynamic neural network reorganization associated with second language vocabulary acquisition: a multimodal imaging study.

PubMed

Hosoda, Chihiro; Tanaka, Kanji; Nariai, Tadashi; Honda, Manabu; Hanakawa, Takashi

2013-08-21

It remains unsettled whether human language relies exclusively on innately privileged brain structure in the left hemisphere or is more flexibly shaped through experiences, which induce neuroplastic changes in potentially relevant neural circuits. Here we show that learning of second language (L2) vocabulary and its cessation can induce bidirectional changes in the mirror-reverse of the traditional language areas. A cross-sectional study identified that gray matter volume in the inferior frontal gyrus pars opercularis (IFGop) and connectivity of the IFGop with the caudate nucleus and the superior temporal gyrus/supramarginal (STG/SMG), predominantly in the right hemisphere, were positively correlated with L2 vocabulary competence. We then implemented a cohort study involving 16 weeks of L2 training in university students. Brain structure before training did not predict the later gain in L2 ability. However, training intervention did increase IFGop volume and reorganization of white matter including the IFGop-caudate and IFGop-STG/SMG pathways in the right hemisphere. These "positive" plastic changes were correlated with the gain in L2 ability in the trained group but were not observed in the control group. We propose that the right hemispheric network can be reorganized into language-related areas through use-dependent plasticity in young adults, reflecting a repertoire of flexible reorganization of the neural substrates responding to linguistic experiences.

A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design

PubMed Central

Kwong, C. K.; Fung, K. Y.; Jiang, Huimin; Chan, K. Y.

2013-01-01

Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort. PMID:24385884

A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design.

PubMed

Kwong, C K; Fung, K Y; Jiang, Huimin; Chan, K Y; Siu, Kin Wai Michael

2013-01-01

Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

Global cluster synchronization in nonlinearly coupled community networks with heterogeneous coupling delays.

PubMed

Tseng, Jui-Pin

2017-02-01

This investigation establishes the global cluster synchronization of complex networks with a community structure based on an iterative approach. The units comprising the network are described by differential equations, and can be non-autonomous and involve time delays. In addition, units in the different communities can be governed by different equations. The coupling configuration of the network is rather general. The coupling terms can be non-diffusive, nonlinear, asymmetric, and with heterogeneous coupling delays. Based on this approach, both delay-dependent and delay-independent criteria for global cluster synchronization are derived. We implement the present approach for a nonlinearly coupled neural network with heterogeneous coupling delays. Two numerical examples are given to show that neural networks can behave in a variety of new collective ways under the synchronization criteria. These examples also demonstrate that neural networks remain synchronized in spite of coupling delays between neurons across different communities; however, they may lose synchrony if the coupling delays between the neurons within the same community are too large, such that the synchronization criteria are violated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design Optimization of Microalloyed Steels Using Thermodynamics Principles and Neural-Network-Based Modeling

NASA Astrophysics Data System (ADS)

Mohanty, Itishree; Chintha, Appa Rao; Kundu, Saurabh

2018-06-01

The optimization of process parameters and composition is essential to achieve the desired properties with minimal additions of alloying elements in microalloyed steels. In some cases, it may be possible to substitute such steels for those which are more richly alloyed. However, process control involves a larger number of parameters, making the relationship between structure and properties difficult to assess. In this work, neural network models have been developed to estimate the mechanical properties of steels containing Nb + V or Nb + Ti. The outcomes have been validated by thermodynamic calculations and plant data. It has been shown that subtle thermodynamic trends can be captured by the neural network model. Some experimental rolling data have also been used to support the model, which in addition has been applied to calculate the costs of optimizing microalloyed steel. The generated pareto fronts identify many combinations of strength and elongation, making it possible to select composition and process parameters for a range of applications. The ANN model and the optimization model are being used for prediction of properties in a running plant and for development of new alloys, respectively.

Frizzled 1 and frizzled 2 genes function in palate, ventricular septum and neural tube closure: general implications for tissue fusion processes

PubMed Central

Yu, Huimin; Smallwood, Philip M.; Wang, Yanshu; Vidaltamayo, Roman; Reed, Randall; Nathans, Jeremy

2010-01-01

The closure of an open anatomical structure by the directed growth and fusion of two tissue masses is a recurrent theme in mammalian embryology, and this process plays an integral role in the development of the palate, ventricular septum, neural tube, urethra, diaphragm and eye. In mice, targeted mutations of the genes encoding frizzled 1 (Fz1) and frizzled 2 (Fz2) show that these highly homologous integral membrane receptors play an essential and partially redundant role in closure of the palate and ventricular septum, and in the correct positioning of the cardiac outflow tract. When combined with a mutant allele of the planar cell polarity gene Vangl2 (Vangl2Lp), Fz1 and/or Fz2 mutations also cause defects in neural tube closure and misorientation of inner ear sensory hair cells. These observations indicate that frizzled signaling is involved in diverse tissue closure processes, defects in which account for some of the most common congenital anomalies in humans. PMID:20940229

Neural Events in the Reinforcement Contingency

ERIC Educational Resources Information Center

Silva, Maria Teresa Araujo; Goncalves, Fabio Leyser; Garcia-Mijares, Miriam

2007-01-01

When neural events are analyzed as stimuli and responses, functional relations among them and among overt stimuli and responses can be unveiled. The integration of neuroscience and the experimental analysis of behavior is beginning to provide empirical evidence of involvement of neural events in the three-term contingency relating discriminative…

Linking structure and activity in nonlinear spiking networks

PubMed Central

Josić, Krešimir; Shea-Brown, Eric

2017-01-01

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks’ spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities—including those of different cell types—combine with connectivity to shape population activity and function. PMID:28644840

Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

PubMed

Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

2010-12-01

The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Linking Neural and Symbolic Representation and Processing of Conceptual Structures

PubMed Central

van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S.; Wiggins, Geraint A.

2017-01-01

We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking), which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures. PMID:28848460

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.

Distinct representations of subtraction and multiplication in the neural systems for numerosity and language

PubMed Central

Prado, Jérôme; Mutreja, Rachna; Zhang, Hongchuan; Mehta, Rucha; Desroches, Amy S.; Minas, Jennifer E.; Booth, James R.

2010-01-01

It has been proposed that recent cultural inventions such as symbolic arithmetic recycle evolutionary older neural mechanisms. A central assumption of this hypothesis is that the degree to which a pre-existing mechanism is recycled depends upon the degree of similarity between its initial function and the novel task. To test this assumption, we investigated whether the brain region involved in magnitude comparison in the intraparietal sulcus (IPS), localized by a numerosity comparison task, is recruited to a greater degree by arithmetic problems that involve number comparison (single-digit subtractions) than by problems that involve retrieving facts from memory (single-digit multiplications). Our results confirmed that subtractions are associated with greater activity in the IPS than multiplications, whereas multiplications elicit greater activity than subtractions in regions involved in verbal processing including the middle temporal gyrus and inferior frontal gyrus that were localized by a phonological processing task. Pattern analyses further indicated that the neural mechanisms more active for subtraction than multiplication in the IPS overlap with those involved in numerosity comparison, and that the strength of this overlap predicts inter-individual performance in the subtraction task. These findings provide novel evidence that elementary arithmetic relies on the co-option of evolutionary older neural circuits. PMID:21246667

Neural Correlates of Aggressive Behavior in Real Time: a Review of fMRI Studies of Laboratory Reactive Aggression

PubMed Central

Keedy, Sarah; Berman, Mitchell E.; Lee, Royce; Coccaro, Emil F.

2017-01-01

Purpose of review Aggressive behavior has adaptive value in many natural environments; however, it places substantial burden and costs on human society. For this reason, there has long been interest in understanding the neurobiological basis of aggression. This interest, and the flourishing of neuroimaging research in general, has spurred the development of a large and growing scientific literature on the topic. As a result, a neural circuit model of aggressive behavior has emerged that implicates interconnected brain regions that are involved in emotional reactivity, emotion regulation, and cognitive control. Recent findings Recently, behavioral paradigms that simulate provocative interactions have been adapted to neuroimaging protocols, providing an opportunity to directly probe the involvement of neural circuits in an aggressive interaction. Here we review neuroimaging studies of simulated aggressive interactions in research volunteers. We focus on studies that use a well-validated laboratory paradigm for reactive physical aggression and examine the neural correlates of provocation, retaliation, and evaluating punishment of an opponent. Summary Overall, the studies reviewed support the involvement of neural circuits that support emotional reactivity, emotion regulation, and cognitive control in aggressive behavior. Based on a synthesis of this literature, future research directions are discussed. PMID:29607288

What’s bad in cancer is good in the embryo: Importance of EMT in neural crest development

PubMed Central

Kerosuo, Laura; Bronner-Fraser, Marianne

2012-01-01

Although the epithelial to mesenchymal transition (EMT) is famous for its role in cancer metastasis, it also is a normal developmental event in which epithelial cells are converted into migratory mesenchymal cells. A prime example of EMT during development occurs when neural crest (NC) cells emigrate from the neural tube thus providing an excellent model to study the principles of EMT in a nonmalignant environment. NC cells start life as neuroepithelial cells intermixed with precursors of the central nervous system. After EMT, they delaminate and begin migrating, often to distant sites in the embryo. While proliferating and maintaining multipotency and cell survival the transitioning neural crest cells lose apicobasal polarity and the basement membrane is broken down. This review discusses how these events are coordinated and regulated, by series of events involving signaling factors, gene regulatory interactions, as well as epigenetic and post-transcriptional modifications. Even though the series of events involved in NC EMT are well known, the sequence in which these steps take place remains a subject of debate, raising the intriguing possibility that, rather than being a single event, neural crest EMT may involve multiple parallel mechanisms. PMID:22430756

Neural substrates of interactive musical improvisation: an FMRI study of 'trading fours' in jazz.

PubMed

Donnay, Gabriel F; Rankin, Summer K; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J

2014-01-01

Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication.

Neural Substrates of Interactive Musical Improvisation: An fMRI Study of ‘Trading Fours’ in Jazz

PubMed Central

Donnay, Gabriel F.; Rankin, Summer K.; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J.

2014-01-01

Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication. PMID:24586366

Brain mesenchymal stem cells: physiology and pathological implications.

PubMed

Pombero, Ana; Garcia-Lopez, Raquel; Martinez, Salvador

2016-06-01

Mesenchymal stem cells (MSCs) are defined as progenitor cells that give rise to a number of unique, differentiated mesenchymal cell types. This concept has progressively evolved towards an all-encompassing concept including multipotent perivascular cells of almost any tissue. In central nervous system, pericytes are involved in blood-brain barrier, and angiogenesis and vascular tone regulation. They form the neurovascular unit (NVU) together with endothelial cells, astrocytes and neurons. This functional structure provides an optimal microenvironment for neural proliferation in the adult brain. Neurovascular niche include both diffusible signals and direct contact with endothelial and pericytes, which are a source of diffusible neurotrophic signals that affect neural precursors. Therefore, MSCs/pericyte properties such as differentiation capability, as well as immunoregulatory and paracrine effects make them a potential resource in regenerative medicine. © 2016 Japanese Society of Developmental Biologists.

Flexibility of movement organization in piano performance.

PubMed

Furuya, Shinichi; Altenmüller, Eckart

2013-01-01

Piano performance involves a large repertoire of highly skilled movements. The acquisition of these exceptional skills despite innate neural and biomechanical constraints requires a sophisticated interaction between plasticity of the neural system and organization of a redundant number of degrees of freedom (DOF) in the motor system. Neuroplasticity subserving virtuosity of pianists has been documented in neuroimaging studies investigating effects of long-term piano training on structure and function of the cortical and subcortical regions. By contrast, recent behavioral studies have advanced the understanding of neuromuscular strategies and biomechanical principles behind the movement organization that enables skilled piano performance. Here we review the motor control and biomechanics literature, introducing the importance of describing motor behaviors not only for understanding mechanisms responsible for skillful motor actions in piano playing, but also for advancing diagnosis and rehabilitation of movement disorders caused by extensive piano practice.

Solving deterministic non-linear programming problem using Hopfield artificial neural network and genetic programming techniques

NASA Astrophysics Data System (ADS)

Vasant, P.; Ganesan, T.; Elamvazuthi, I.

2012-11-01

A fairly reasonable result was obtained for non-linear engineering problems using the optimization techniques such as neural network, genetic algorithms, and fuzzy logic independently in the past. Increasingly, hybrid techniques are being used to solve the non-linear problems to obtain better output. This paper discusses the use of neuro-genetic hybrid technique to optimize the geological structure mapping which is known as seismic survey. It involves the minimization of objective function subject to the requirement of geophysical and operational constraints. In this work, the optimization was initially performed using genetic programming, and followed by hybrid neuro-genetic programming approaches. Comparative studies and analysis were then carried out on the optimized results. The results indicate that the hybrid neuro-genetic hybrid technique produced better results compared to the stand-alone genetic programming method.

Brain correlates of music-evoked emotions.

PubMed

Koelsch, Stefan

2014-03-01

Music is a universal feature of human societies, partly owing to its power to evoke strong emotions and influence moods. During the past decade, the investigation of the neural correlates of music-evoked emotions has been invaluable for the understanding of human emotion. Functional neuroimaging studies on music and emotion show that music can modulate activity in brain structures that are known to be crucially involved in emotion, such as the amygdala, nucleus accumbens, hypothalamus, hippocampus, insula, cingulate cortex and orbitofrontal cortex. The potential of music to modulate activity in these structures has important implications for the use of music in the treatment of psychiatric and neurological disorders.

Calcium signaling mediates five types of cell morphological changes to form neural rosettes.

PubMed

Hříbková, Hana; Grabiec, Marta; Klemová, Dobromila; Slaninová, Iva; Sun, Yuh-Man

2018-02-12

Neural rosette formation is a critical morphogenetic process during neural development, whereby neural stem cells are enclosed in rosette niches to equipoise proliferation and differentiation. How neural rosettes form and provide a regulatory micro-environment remains to be elucidated. We employed the human embryonic stem cell-based neural rosette system to investigate the structural development and function of neural rosettes. Our study shows that neural rosette formation consists of five types of morphological change: intercalation, constriction, polarization, elongation and lumen formation. Ca 2+ signaling plays a pivotal role in the five steps by regulating the actions of the cytoskeletal complexes, actin, myosin II and tubulin during intercalation, constriction and elongation. These, in turn, control the polarizing elements, ZO-1, PARD3 and β-catenin during polarization and lumen production for neural rosette formation. We further demonstrate that the dismantlement of neural rosettes, mediated by the destruction of cytoskeletal elements, promotes neurogenesis and astrogenesis prematurely, indicating that an intact rosette structure is essential for orderly neural development. © 2018. Published by The Company of Biologists Ltd.

Processing structure in language and music: a case for shared reliance on cognitive control.

PubMed

Slevc, L Robert; Okada, Brooke M

2015-06-01

The relationship between structural processing in music and language has received increasing interest in the past several years, spurred by the influential Shared Syntactic Integration Resource Hypothesis (SSIRH; Patel, Nature Neuroscience, 6, 674-681, 2003). According to this resource-sharing framework, music and language rely on separable syntactic representations but recruit shared cognitive resources to integrate these representations into evolving structures. The SSIRH is supported by findings of interactions between structural manipulations in music and language. However, other recent evidence suggests that such interactions also can arise with nonstructural manipulations, and some recent neuroimaging studies report largely nonoverlapping neural regions involved in processing musical and linguistic structure. These conflicting results raise the question of exactly what shared (and distinct) resources underlie musical and linguistic structural processing. This paper suggests that one shared resource is prefrontal cortical mechanisms of cognitive control, which are recruited to detect and resolve conflict that occurs when expectations are violated and interpretations must be revised. By this account, musical processing involves not just the incremental processing and integration of musical elements as they occur, but also the incremental generation of musical predictions and expectations, which must sometimes be overridden and revised in light of evolving musical input.

Neural net target-tracking system using structured laser patterns

NASA Astrophysics Data System (ADS)

Cho, Jae-Wan; Lee, Yong-Bum; Lee, Nam-Ho; Park, Soon-Yong; Lee, Jongmin; Choi, Gapchu; Baek, Sunghyun; Park, Dong-Sun

1996-06-01

In this paper, we describe a robot endeffector tracking system using sensory information from recently-announced structured pattern laser diodes, which can generate images with several different types of structured pattern. The neural network approach is employed to recognize the robot endeffector covering the situation of three types of motion: translation, scaling and rotation. Features for the neural network to detect the position of the endeffector are extracted from the preprocessed images. Artificial neural networks are used to store models and to match with unknown input features recognizing the position of the robot endeffector. Since a minimal number of samples are used for different directions of the robot endeffector in the system, an artificial neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network trained with the back propagation learning is used to detect the position of the robot endeffector. Another feedforward neural network module is used to estimate the motion from a sequence of images and to control movements of the robot endeffector. COmbining the tow neural networks for recognizing the robot endeffector and estimating the motion with the preprocessing stage, the whole system keeps tracking of the robot endeffector effectively.

AKT signaling displays multifaceted functions in neural crest development.

PubMed

Sittewelle, Méghane; Monsoro-Burq, Anne H

2018-05-31

AKT signaling is an essential intracellular pathway controlling cell homeostasis, cell proliferation and survival, as well as cell migration and differentiation in adults. Alterations impacting the AKT pathway are involved in many pathological conditions in human disease. Similarly, during development, multiple transmembrane molecules, such as FGF receptors, PDGF receptors or integrins, activate AKT to control embryonic cell proliferation, migration, differentiation, and also cell fate decisions. While many studies in mouse embryos have clearly implicated AKT signaling in the differentiation of several neural crest derivatives, information on AKT functions during the earliest steps of neural crest development had remained relatively scarce until recently. However, recent studies on known and novel regulators of AKT signaling demonstrate that this pathway plays critical roles throughout the development of neural crest progenitors. Non-mammalian models such as fish and frog embryos have been instrumental to our understanding of AKT functions in neural crest development, both in neural crest progenitors and in the neighboring tissues. This review combines current knowledge acquired from all these different vertebrate animal models to describe the various roles of AKT signaling related to neural crest development in vivo. We first describe the importance of AKT signaling in patterning the tissues involved in neural crest induction, namely the dorsal mesoderm and the ectoderm. We then focus on AKT signaling functions in neural crest migration and differentiation. Copyright © 2018 Elsevier Inc. All rights reserved.

Discovery of Benzofuran Derivatives that Collaborate with Insulin-Like Growth Factor 1 (IGF-1) to Promote Neuroprotection.

PubMed

Wakabayashi, Takeshi; Tokunaga, Norihito; Tokumaru, Kazuyuki; Ohra, Taiichi; Koyama, Nobuyuki; Hayashi, Satoru; Yamada, Ryuji; Shirasaki, Mikio; Inui, Yoshitaka; Tsukamoto, Tetsuya

2016-05-26

A series of benzofuran derivatives with neuroprotective activity in collaboration with IGF-1 was discovered using a newly developed cell-based assay involving primary neural cells prepared from rat hippocampal and cerebral cortical tissues. A structure-activity relationship study identified compound 8 as exhibiting potent activity and brain penetrability. An in vitro pharmacological study demonstrated that although IGF-1 and 8 individually exhibited the neuroprotective effect, the latter acted in collaboration with IGF-1 to enhance neuroprotective activity.

A Disintegrin and Metalloprotease 17 in the Cardiovascular and Central Nervous Systems.

PubMed

Xu, Jiaxi; Mukerjee, Snigdha; Silva-Alves, Cristiane R A; Carvalho-Galvão, Alynne; Cruz, Josiane C; Balarini, Camille M; Braga, Valdir A; Lazartigues, Eric; França-Silva, Maria S

2016-01-01

ADAM17 is a metalloprotease and disintegrin that lodges in the plasmatic membrane of several cell types and is able to cleave a wide variety of cell surface proteins. It is somatically expressed in mammalian organisms and its proteolytic action influences several physiological and pathological processes. This review focuses on the structure of ADAM17, its signaling in the cardiovascular system and its participation in certain disorders involving the heart, blood vessels, and neural regulation of autonomic and cardiovascular modulation.

Neurophysiology and Neuroanatomy of Reflexive and Volitional Saccades: Evidence from Studies of Humans

PubMed Central

McDowell, Jennifer E.; Dyckman, Kara A.; Austin, Benjamin; Clementz, Brett A.

2008-01-01

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually-guided saccades (redirections of gaze to a visual stimulus or prosaccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human primates (e.g. single unit recordings) and humans (e.g. lesions and neuroimaging). Considerable knowledge of this system’s functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in prosaccade generation (by definition exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical structures (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields). Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g. antisaccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution. PMID:18835656

Partial information decomposition as a unified approach to the specification of neural goal functions.

PubMed

Wibral, Michael; Priesemann, Viola; Kay, Jim W; Lizier, Joseph T; Phillips, William A

2017-03-01

In many neural systems anatomical motifs are present repeatedly, but despite their structural similarity they can serve very different tasks. A prime example for such a motif is the canonical microcircuit of six-layered neo-cortex, which is repeated across cortical areas, and is involved in a number of different tasks (e.g. sensory, cognitive, or motor tasks). This observation has spawned interest in finding a common underlying principle, a 'goal function', of information processing implemented in this structure. By definition such a goal function, if universal, cannot be cast in processing-domain specific language (e.g. 'edge filtering', 'working memory'). Thus, to formulate such a principle, we have to use a domain-independent framework. Information theory offers such a framework. However, while the classical framework of information theory focuses on the relation between one input and one output (Shannon's mutual information), we argue that neural information processing crucially depends on the combination of multiple inputs to create the output of a processor. To account for this, we use a very recent extension of Shannon Information theory, called partial information decomposition (PID). PID allows to quantify the information that several inputs provide individually (unique information), redundantly (shared information) or only jointly (synergistic information) about the output. First, we review the framework of PID. Then we apply it to reevaluate and analyze several earlier proposals of information theoretic neural goal functions (predictive coding, infomax and coherent infomax, efficient coding). We find that PID allows to compare these goal functions in a common framework, and also provides a versatile approach to design new goal functions from first principles. Building on this, we design and analyze a novel goal function, called 'coding with synergy', which builds on combining external input and prior knowledge in a synergistic manner. We suggest that this novel goal function may be highly useful in neural information processing. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

What can be found in scalp EEG spectrum beyond common frequency bands. EEG-fMRI study

NASA Astrophysics Data System (ADS)

Marecek, R.; Lamos, M.; Mikl, M.; Barton, M.; Fajkus, J.; I, Rektor; Brazdil, M.

2016-08-01

Objective. The scalp EEG spectrum is a frequently used marker of neural activity. Commonly, the preprocessing of EEG utilizes constraints, e.g. dealing with a predefined subset of electrodes or a predefined frequency band of interest. Such treatment of the EEG spectrum neglects the fact that particular neural processes may be reflected in several frequency bands and/or several electrodes concurrently, and can overlook the complexity of the structure of the EEG spectrum. Approach. We showed that the EEG spectrum structure can be described by parallel factor analysis (PARAFAC), a method which blindly uncovers the spatial-temporal-spectral patterns of EEG. We used an algorithm based on variational Bayesian statistics to reveal nine patterns from the EEG of 38 healthy subjects, acquired during a semantic decision task. The patterns reflected neural activity synchronized across theta, alpha, beta and gamma bands and spread over many electrodes, as well as various EEG artifacts. Main results. Specifically, one of the patterns showed significant correlation with the stimuli timing. The correlation was higher when compared to commonly used models of neural activity (power fluctuations in distinct frequency band averaged across a subset of electrodes) and we found significantly correlated hemodynamic fluctuations in simultaneously acquired fMRI data in regions known to be involved in speech processing. Further, we show that the pattern also occurs in EEG data which were acquired outside the MR machine. Two other patterns reflected brain rhythms linked to the attentional and basal ganglia large scale networks. The other patterns were related to various EEG artifacts. Significance. These results show that PARAFAC blindly identifies neural activity in the EEG spectrum and that it naturally handles the correlations among frequency bands and electrodes. We conclude that PARAFAC seems to be a powerful tool for analysis of the EEG spectrum and might bring novel insight to the relationships between EEG activity and brain hemodynamics.

AmphiPax3/7, an amphioxus paired box gene: insights into chordate myogenesis, neurogenesis, and the possible evolutionary precursor of definitive vertebrate neural crest.

PubMed

Holland, L Z; Schubert, M; Kozmik, Z; Holland, N D

1999-01-01

Amphioxus probably has only a single gene (AmphiPax3/7) in the Pax3/7 subfamily. Like its vertebrate homologs (Pax3 and Pax7), amphioxus AmphiPax3/7 is probably involved in specifying the axial musculature and muscularized notochord. During nervous system development, AmphiPax3/7 is first expressed in bilateral anteroposterior stripes along the edges of the neural plate. This early neural expression may be comparable to the transcription of Pax3 and Pax7 in some of the anterior neural crest cells of vertebrates. Previous studies by others and ourselves have demonstrated that several genes homologous to genetic markers for vertebrate neural crest are expressed along the neural plate-epidermis boundary in embryos of tunicates and amphioxus. Taken together, the early neural expression patterns of AmphiPax3/7 and other neural crest markers of amphioxus and tunicates suggest that cell populations that eventually gave rise to definitive vertebrate neural crest may have been present in ancestral invertebrate chordates. During later neurogenesis in amphioxus, AmphiPax3/7, like its vertebrate homologs, is expressed dorsally and dorsolaterally in the neural tube and may be involved in dorsoventral patterning. However, unlike its vertebrate homologs, AmphiPax3/7 is expressed only at the anterior end of the central nervous system instead of along much of the neuraxis; this amphioxus pattern may represent the loss of a primitive chordate character.

RIP140/PGC-1α axis involved in vitamin A-induced neural differentiation by increasing mitochondrial function.

PubMed

Mu, Qing; Yu, Weidong; Zheng, Shuying; Shi, Hongxia; Li, Mei; Sun, Jie; Wang, Di; Hou, Xiaoli; Liu, Ling; Wang, Xinjuan; Zhao, Zhuran; Liang, Rong; Zhang, Xue; Dong, Wei; Zeng, Chaomei; Guo, Jingzhu

2018-03-07

Vitamin A deficiency and mitochondrial dysfunction are both associated with neural differentiation-related disorders, such as Alzheimer's disease (AD) and Down syndrome (DS). The mechanism of vitamin A-induced neural differentiation and the notion that vitamin A can regulate the morphology and function of mitochondria in its induction of neural differentiation through the RIP140/PGC-1α axis are unclear. The aim of this study was to investigate the roles and underlying mechanisms of RIP140/PGC-1α axis in vitamin A-induced neural differentiation. Human neuroblastoma cells (SH-SY5Y) were used as a model of neural stem cells, which were incubated with DMSO, 9-cis-retinoic acid (9-cis-RA), 13-cis-retinoic acid (13-cis-RA) and all-trans-retinoic acid (at-RA). Neural differentiation of SH-SY5Y was evaluated by Sandquist calculation, combined with immunofluorescence and real-time polymerase chain reaction (PCR) of neural markers. Mitochondrial function was estimated by ultrastructure assay using transmission electron microscopy (TEM) combined with the expression of PGC-1α and NEMGs using real-time PCR. The participation of the RA signaling pathway was demonstrated by adding RA receptor antagonists. Vitamin A derivatives are able to regulate mitochondrial morphology and function, and furthermore to induce neural differentiation through the RA signaling pathway. The RIP140/PGC-1α axis is involved in the regulation of mitochondrial function in vitamin A derivative-induced neural differentiation.

Microscopic neural image registration based on the structure of mitochondria

NASA Astrophysics Data System (ADS)

Cao, Huiwen; Han, Hua; Rao, Qiang; Xiao, Chi; Chen, Xi

2017-02-01

Microscopic image registration is a key component of the neural structure reconstruction with serial sections of neural tissue. The goal of microscopic neural image registration is to recover the 3D continuity and geometrical properties of specimen. During image registration, various distortions need to be corrected, including image rotation, translation, tissue deformation et.al, which come from the procedure of sample cutting, staining and imaging. Furthermore, there is only certain similarity between adjacent sections, and the degree of similarity depends on local structure of the tissue and the thickness of the sections. These factors make the microscopic neural image registration a challenging problem. To tackle the difficulty of corresponding landmarks extraction, we introduce a novel image registration method for Scanning Electron Microscopy (SEM) images of serial neural tissue sections based on the structure of mitochondria. The ellipsoidal shape of mitochondria ensures that the same mitochondria has similar shape between adjacent sections, and its characteristic of broad distribution in the neural tissue guarantees that landmarks based on the mitochondria distributed widely in the image. The proposed image registration method contains three parts: landmarks extraction between adjacent sections, corresponding landmarks matching and image deformation based on the correspondences. We demonstrate the performance of our method with SEM images of drosophila brain.

Structured prediction models for RNN based sequence labeling in clinical text.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

Structured prediction models for RNN based sequence labeling in clinical text

PubMed Central

Jagannatha, Abhyuday N; Yu, Hong

2016-01-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies1 for structured prediction in order to improve the exact phrase detection of various medical entities. PMID:28004040

Scary symptoms? Functional magnetic resonance imaging evidence for symptom interpretation bias in pathological health anxiety.

PubMed

Yan, Zhimin; Witthöft, Michael; Bailer, Josef; Diener, Carsten; Mier, Daniela

2017-08-12

Patients with pathological health anxiety (PHA) tend to automatically interpret bodily sensations as sign of a severe illness. To elucidate the neural correlates of this cognitive bias, we applied an functional magnetic resonance imaging adaption of a body-symptom implicit association test with symptom words in patients with PHA (n = 32) in comparison to patients with depression (n = 29) and healthy participants (n = 35). On the behavioral level, patients with PHA did not significantly differ from the control groups. However, on the neural-level patients with PHA in comparison to the control groups showed hyperactivation independent of condition in bilateral amygdala, right parietal lobe, and left nucleus accumbens. Moreover, patients with PHA, again in comparison to the control groups, showed hyperactivation in bilateral posterior parietal cortex and left dorsolateral prefrontal cortex during incongruent (i.e., harmless) versus congruent (i.e., dangerous) categorizations of body symptoms. Thus, body-symptom cues seem to trigger hyperactivity in salience and emotion processing brain regions in PHA. In addition, hyperactivity in brain regions involved in cognitive control and conflict resolution during incongruent categorization emphasizes enhanced neural effort to cope with negative implicit associations to body-symptom-related information in PHA. These results suggest increased neural responding in key structures for the processing of both emotional and cognitive aspects of body-symptom information in PHA, reflecting potential neural correlates of a negative somatic symptom interpretation bias.

Grand Research Plan for Neural Circuits of Emotion and Memory--current status of neural circuit studies in China.

PubMed

Zhu, Yuan-Gui; Cao, He-Qi; Dong, Er-Dan

2013-02-01

During recent years, major advances have been made in neuroscience, i.e., asynchronous release, three-dimensional structural data sets, saliency maps, magnesium in brain research, and new functional roles of long non-coding RNAs. Especially, the development of optogenetic technology provides access to important information about relevant neural circuits by allowing the activation of specific neurons in awake mammals and directly observing the resulting behavior. The Grand Research Plan for Neural Circuits of Emotion and Memory was launched by the National Natural Science Foundation of China. It takes emotion and memory as its main objects, making the best use of cutting-edge technologies from medical science, life science and information science. In this paper, we outline the current status of neural circuit studies in China and the technologies and methodologies being applied, as well as studies related to the impairments of emotion and memory. In this phase, we are making efforts to repair the current deficiencies by making adjustments, mainly involving four aspects of core scientific issues to investigate these circuits at multiple levels. Five research directions have been taken to solve important scientific problems while the Grand Research Plan is implemented. Future research into this area will be multimodal, incorporating a range of methods and sciences into each project. Addressing these issues will ensure a bright future, major discoveries, and a higher level of treatment for all affected by debilitating brain illnesses.

Diprosopia revisited in light of the recognized role of neural crest cells in facial development.

PubMed

Carles, D; Weichhold, W; Alberti, E M; Léger, F; Pigeau, F; Horovitz, J

1995-01-01

The aim of this study is to compare the theory of embryogenesis of the face with human diprosopia. This peculiar form of conjoined twinning is of great interest because 1) only the facial structures are duplicated and 2) almost all cases have a rather monomorphic pattern. The hypothesis is that an initial duplication of the notochord leads to two neural plates and subsequently duplicated neural crests. In those conditions, derivatives of the neural crests will be partially or totally duplicated; therefore, in diprosopia, the duplicated facial structures would be considered to be neural crest derivatives. If these structures are identical to those that are experimentally demonstrated to be neural crest derivatives in animals, these findings are an argument to apply this theory of facial embryogenesis in man. Serial horizontal sections of the face of two diprosopic fetuses (11 and 21 weeks gestation) were studied macro- and microscopically to determine the external and internal structures that are duplicated. Complete postmortem examination was performed in search for additional malformations. The face of both fetuses showed a very similar morphologic pattern with duplication of ocular, nasal, and buccal structures. The nasal fossae and the anterior part of the tongue were also duplicated, albeit the posterior part and the pharyngolaryngeal structures were unique. Additional facial clefts were present in both fetuses. Extrafacial anomalies were represented by a craniorachischisis, two fused vertebral columns and, in the older fetus, by a complex cardiac malformation morphologically identical to malformations induced by removal or grafting of additional cardiac neural crest cells in animals. These pathological findings could identify the facial structures that are neural crest derivatives in man. They are similar to those experimentally demonstrated to be neural crest derivatives in animals. In this respect, diprosopia could be considered as the end of a spectrum, whereas the other end is agnathia-holoprosencephaly complex. This assumption has to be discussed, but we want to draw attention to the fact that diprosopia must not be considered as a curious form of conjoined twinning, but as a major means of bringing us a better knowledge of the facial embryogenesis in man.

The Influence of Emotion Regulation on Decision-making under Risk

PubMed Central

Martin, Laura N.; Delgado, Mauricio R.

2011-01-01

Cognitive strategies typically involved in regulating negative emotions have recently been shown to also be effective with positive emotions associated with monetary rewards. However, it is less clear how these strategies influence behavior, such as preferences expressed during decision-making under risk, and the underlying neural circuitry. That is, can the effective use of emotion regulation strategies during presentation of a reward-conditioned stimulus influence decision-making under risk and neural structures involved in reward processing such as the striatum? To investigate this question, we asked participants to engage in imagery-focused regulation strategies during the presentation of a cue that preceded a financial decision-making phase. During the decision phase, participants then made a choice between a risky and a safe monetary lottery. Participants who successfully used cognitive regulation, as assessed by subjective ratings about perceived success and facility in implementation of strategies, made fewer risky choices in comparison to trials where decisions were made in the absence of cognitive regulation. Additionally, blood-oxygen-level-dependent (BOLD) responses in the striatum were attenuated during decision-making as a function of successful emotion regulation. These findings suggest that exerting cognitive control over emotional responses can modulate neural responses associated with reward processing (e.g., striatum), and promote more goal-directed decision-making (e.g., less risky choices), illustrating the potential importance of cognitive strategies in curbing risk-seeking behaviors before they become maladaptive (e.g., substance abuse). PMID:21254801

Expression of a desaturase gene, desat1, in neural and nonneural tissues separately affects perception and emission of sex pheromones in Drosophila

PubMed Central

Bousquet, François; Nojima, Tetsuya; Houot, Benjamin; Chauvel, Isabelle; Chaudy, Sylvie; Dupas, Stéphane; Yamamoto, Daisuke; Ferveur, Jean-François

2012-01-01

Animals often use sex pheromones for mate choice and reproduction. As for other signals, the genetic control of the emission and perception of sex pheromones must be tightly coadapted, and yet we still have no worked-out example of how these two aspects interact. Most models suggest that emission and perception rely on separate genetic control. We have identified a Drosophila melanogaster gene, desat1, that is involved in both the emission and the perception of sex pheromones. To explore the mechanism whereby these two aspects of communication interact, we investigated the relationship between the molecular structure, tissue-specific expression, and pheromonal phenotypes of desat1. We characterized the five desat1 transcripts—all of which yielded the same desaturase protein—and constructed transgenes with the different desat1 putative regulatory regions. Each region was used to target reporter transgenes with either (i) the fluorescent GFP marker to reveal desat1 tissue expression, or (ii) the desat1 RNAi sequence to determine the effects of genetic down-regulation on pheromonal phenotypes. We found that desat1 is expressed in a variety of neural and nonneural tissues, most of which are involved in reproductive functions. Our results suggest that distinct desat1 putative regulatory regions independently drive the expression in nonneural and in neural cells, such that the emission and perception of sex pheromones are precisely coordinated in this species. PMID:22114190

Resolving bulimia nervosa using an innovative neural therapy approach: two case reports.

PubMed

Gurevich, Michael I; Chung, Myung Kyu; LaRiccia, Patrick J

2018-02-01

Conventional treatment of Bulimia Nervosa is long term, expensive, and often ineffective. Neural therapy holds promise for treating Bulimia Nervosa in a shorter term, lower cost, and more effective manner. Much of neural therapy involves the superficial injection of local anesthetic injections. Implementation into current practice would be feasible.

Enhancing the efficiency of direct reprogramming of human mesenchymal stem cells into mature neuronal-like cells with the combination of small molecule modulators of chromatin modifying enzymes, SMAD signaling and cyclic adenosine monophosphate levels.

PubMed

Alexanian, Arshak R; Liu, Qing-song; Zhang, Zhiying

2013-08-01

Advances in cell reprogramming technologies to generate patient-specific cells of a desired type will revolutionize the field of regenerative medicine. While several cell reprogramming methods have been developed over the last decades, the majority of these technologies require the exposure of cell nuclei to reprogramming large molecules via transfection, transduction, cell fusion or nuclear transfer. This raises several technical, safety and ethical issues. Chemical genetics is an alternative approach for cell reprogramming that uses small, cell membrane penetrable substances to regulate multiple cellular processes including cell plasticity. Recently, using the combination of small molecules that are involved in the regulation chromatin structure and function and agents that favor neural differentiation we have been able to generate neural-like cells from human mesenchymal stem cells. In this study, to improve the efficiency of neuronal differentiation and maturation, two specific inhibitors of SMAD signaling (SMAD1/3 and SMAD3/5/8) that play an important role in neuronal differentiation of embryonic stem cells, were added to our previous neural induction recipe. Results demonstrated that human mesenchymal stem cells grown in this culture conditions exhibited higher expression of several mature neuronal genes, formed synapse-like structures and exerted electrophysiological properties of differentiating neural stem cells. Thus, an efficient method for production of mature neuronal-like cells from human adult bone marrow derived mesenchymal stem cells has been developed. We concluded that specific combinations of small molecules that target specific cell signaling pathways and chromatin modifying enzymes could be a promising approach for manipulation of adult stem cell plasticity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Flexible body control using neural networks

NASA Technical Reports Server (NTRS)

Mccullough, Claire L.

1992-01-01

Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

Meta-analytic investigations of structural grey matter, executive domain-related functional activations, and white matter diffusivity in obsessive compulsive disorder: an integrative review.

PubMed

Eng, Goi Khia; Sim, Kang; Chen, Shen-Hsing Annabel

2015-05-01

Obsessive-compulsive disorder (OCD) is a debilitating disorder. However, existing neuroimaging findings involving executive function and structural abnormalities in OCD have been mixed. Here we conducted meta-analyses to investigate differences in OCD samples and controls in: Study 1 - grey matter structure; Study 2 - executive function task-related activations during (i) response inhibition, (ii) interference, and (iii) switching tasks; and Study 3 - white matter diffusivity. Results showed grey matter differences in the frontal, striatal, thalamus, parietal and cerebellar regions; task domain-specific neural differences in similar regions; and abnormal diffusivity in major white matter regions in OCD samples compared to controls. Our results reported concurrence of abnormal white matter diffusivity with corresponding abnormalities in grey matter and task-related functional activations. Our findings suggested the involvement of other brain regions not included in the cortico-striato-thalamo-cortical network, such as the cerebellum and parietal cortex, and questioned the involvement of the orbitofrontal region in OCD pathophysiology. Future research is needed to clarify the roles of these brain regions in the disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural correlates of social exclusion across ages: A coordinate-based meta-analysis of functional MRI studies.

PubMed

Vijayakumar, Nandita; Cheng, Theresa W; Pfeifer, Jennifer H

2017-06-01

Given the recent surge in functional neuroimaging studies on social exclusion, the current study employed activation likelihood estimation (ALE) based meta-analyses to identify brain regions that have consistently been implicated across different experimental paradigms used to investigate exclusion. We also examined the neural correlates underlying Cyberball, the most commonly used paradigm to study exclusion, as well as differences in exclusion-related activation between developing (7-18 years of age, from pre-adolescence up to late adolescence) and emerging adult (broadly defined as undergraduates, including late adolescence and young adulthood) samples. Results revealed involvement of the bilateral medial prefrontal and posterior cingulate cortices, right precuneus and left ventrolateral prefrontal cortex across the different paradigms used to examine social exclusion; similar activation patterns were identified when restricting the analysis to Cyberball studies. Investigations into age-related effects revealed that ventrolateral prefrontal activations identified in the full sample were driven by (i.e. present in) developmental samples, while medial prefrontal activations were driven by emerging adult samples. In addition, the right ventral striatum was implicated in exclusion, but only in developmental samples. Subtraction analysis revealed significantly greater activation likelihood in striatal and ventrolateral prefrontal clusters in the developmental samples as compared to emerging adults, though the opposite contrast failed to identify any significant regions. Findings integrate the knowledge accrued from functional neuroimaging studies on social exclusion to date, highlighting involvement of lateral prefrontal regions implicated in regulation and midline structures involved in social cognitive and self-evaluative processes across experimental paradigms and ages, as well as limbic structures in developing samples specifically. Copyright © 2017 Elsevier Inc. All rights reserved.

The silicon synapse or, neural net computing.

PubMed

Frenger, P

1989-01-01

Recent developments have rekindled interest in the electronic neural network, a form of parallel computer architecture loosely based on the nervous system of living creatures. This paper describes the elements of neural net computers, reviews the historical milestones in their development, and lists the advantages and disadvantages of their use. Methods for software simulation of neural network systems on existing computers, as well as creation of hardware analogues, are given. The most successful applications of these techniques, involving emulation of biological system responses, are presented. The author's experiences with neural net systems are discussed.

Activity of the anterior cingulate cortex and ventral hippocampus underlie increases in contextual fear generalization.

PubMed

Cullen, Patrick K; Gilman, T Lee; Winiecki, Patrick; Riccio, David C; Jasnow, Aaron M

2015-10-01

Memories for context become less specific with time resulting in animals generalizing fear from training contexts to novel contexts. Though much attention has been given to the neural structures that underlie the long-term consolidation of a context fear memory, very little is known about the mechanisms responsible for the increase in fear generalization that occurs as the memory ages. Here, we examine the neural pattern of activation underlying the expression of a generalized context fear memory in male C57BL/6J mice. Animals were context fear conditioned and tested for fear in either the training context or a novel context at recent and remote time points. Animals were sacrificed and fluorescent in situ hybridization was performed to assay neural activation. Our results demonstrate activity of the prelimbic, infralimbic, and anterior cingulate (ACC) cortices as well as the ventral hippocampus (vHPC) underlie expression of a generalized fear memory. To verify the involvement of the ACC and vHPC in the expression of a generalized fear memory, animals were context fear conditioned and infused with 4% lidocaine into the ACC, dHPC, or vHPC prior to retrieval to temporarily inactivate these structures. The results demonstrate that activity of the ACC and vHPC is required for the expression of a generalized fear memory, as inactivation of these regions returned the memory to a contextually precise form. Current theories of time-dependent generalization of contextual memories do not predict involvement of the vHPC. Our data suggest a novel role of this region in generalized memory, which should be incorporated into current theories of time-dependent memory generalization. We also show that the dorsal hippocampus plays a prolonged role in contextually precise memories. Our findings suggest a possible interaction between the ACC and vHPC controls the expression of fear generalization. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Translating Principles of Neural Plasticity into Research on Speech Motor Control Recovery and Rehabilitation

ERIC Educational Resources Information Center

Ludlow, Christy L.; Hoit, Jeannette; Kent, Raymond; Ramig, Lorraine O.; Shrivastav, Rahul; Strand, Edythe; Yorkston, Kathryn; Sapienza, Christine M.

2008-01-01

Purpose: To review the principles of neural plasticity and make recommendations for research on the neural bases for rehabilitation of neurogenic speech disorders. Method: A working group in speech motor control and disorders developed this report, which examines the potential relevance of basic research on the brain mechanisms involved in neural…

Analog Processor To Solve Optimization Problems

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Eberhardt, Silvio P.; Thakoor, Anil P.

1993-01-01

Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.

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.

What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic variant primary progressive aphasia.

PubMed

Wilson, Stephen M; DeMarco, Andrew T; Henry, Maya L; Gesierich, Benno; Babiak, Miranda; Mandelli, Maria Luisa; Miller, Bruce L; Gorno-Tempini, Maria Luisa

2014-05-01

Neuroimaging and neuropsychological studies have implicated the anterior temporal lobe (ATL) in sentence-level processing, with syntactic structure-building and/or combinatorial semantic processing suggested as possible roles. A potential challenge to the view that the ATL is involved in syntactic aspects of sentence processing comes from the clinical syndrome of semantic variant primary progressive aphasia (semantic PPA; also known as semantic dementia). In semantic PPA, bilateral neurodegeneration of the ATLs is associated with profound lexical semantic deficits, yet syntax is strikingly spared. The goal of this study was to investigate the neural correlates of syntactic processing in semantic PPA to determine which regions normally involved in syntactic processing are damaged in semantic PPA and whether spared syntactic processing depends on preserved functionality of intact regions, preserved functionality of atrophic regions, or compensatory functional reorganization. We scanned 20 individuals with semantic PPA and 24 age-matched controls using structural MRI and fMRI. Participants performed a sentence comprehension task that emphasized syntactic processing and minimized lexical semantic demands. We found that, in controls, left inferior frontal and left posterior temporal regions were modulated by syntactic processing, whereas anterior temporal regions were not significantly modulated. In the semantic PPA group, atrophy was most severe in the ATLs but extended to the posterior temporal regions involved in syntactic processing. Functional activity for syntactic processing was broadly similar in patients and controls; in particular, whole-brain analyses revealed no significant differences between patients and controls in the regions modulated by syntactic processing. The atrophic left ATL did show abnormal functionality in semantic PPA patients; however, this took the unexpected form of a failure to deactivate. Taken together, our findings indicate that spared syntactic processing in semantic PPA depends on preserved functionality of structurally intact left frontal regions and moderately atrophic left posterior temporal regions, but no functional reorganization was apparent as a consequence of anterior temporal atrophy and dysfunction. These results suggest that the role of the ATL in sentence processing is less likely to relate to syntactic structure-building and more likely to relate to higher-level processes such as combinatorial semantic processing.

Central mechanisms for force and motion--towards computational synthesis of human movement.

PubMed

Hemami, Hooshang; Dariush, Behzad

2012-12-01

Anatomical, physiological and experimental research on the human body can be supplemented by computational synthesis of the human body for all movement: routine daily activities, sports, dancing, and artistic and exploratory involvements. The synthesis requires thorough knowledge about all subsystems of the human body and their interactions, and allows for integration of known knowledge in working modules. It also affords confirmation and/or verification of scientific hypotheses about workings of the central nervous system (CNS). A simple step in this direction is explored here for controlling the forces of constraint. It requires co-activation of agonist-antagonist musculature. The desired trajectories of motion and the force of contact have to be provided by the CNS. The spinal control involves projection onto a muscular subset that induces the force of contact. The projection of force in the sensory motor cortex is implemented via a well-defined neural population unit, and is executed in the spinal cord by a standard integral controller requiring input from tendon organs. The sensory motor cortex structure is extended to the case for directing motion via two neural population units with vision input and spindle efferents. Digital computer simulations show the feasibility of the system. The formulation is modular and can be extended to multi-link limbs, robot and humanoid systems with many pairs of actuators or muscles. It can be expanded to include reticular activating structures and learning. Copyright © 2012 Elsevier Ltd. All rights reserved.

Visually cued motor synchronization: modulation of fMRI activation patterns by baseline condition.

PubMed

Cerasa, Antonio; Hagberg, Gisela E; Bianciardi, Marta; Sabatini, Umberto

2005-01-03

A well-known issue in functional neuroimaging studies, regarding motor synchronization, is to design suitable control tasks able to discriminate between the brain structures involved in primary time-keeper functions and those related to other processes such as attentional effort. The aim of this work was to investigate how the predictability of stimulus onsets in the baseline condition modulates the activity in brain structures related to processes involved in time-keeper functions during the performance of a visually cued motor synchronization task (VM). The rational behind this choice derives from the notion that using different stimulus predictability can vary the subject's attention and the consequently neural activity. For this purpose, baseline levels of BOLD activity were obtained from 12 subjects during a conventional-baseline condition: maintained fixation of the visual rhythmic stimuli presented in the VM task, and a random-baseline condition: maintained fixation of visual stimuli occurring randomly. fMRI analysis demonstrated that while brain areas with a documented role in basic time processing are detected independent of the baseline condition (right cerebellum, bilateral putamen, left thalamus, left superior temporal gyrus, left sensorimotor cortex, left dorsal premotor cortex and supplementary motor area), the ventral premotor cortex, caudate nucleus, insula and inferior frontal gyrus exhibited a baseline-dependent activation. We conclude that maintained fixation of unpredictable visual stimuli can be employed in order to reduce or eliminate neural activity related to attentional components present in the synchronization task.

The Application of Electro- and Magneto-Encephalography in Tinnitus Research – Methods and Interpretations

PubMed Central

Adjamian, Peyman

2014-01-01

In recent years, there has been a significant increase in the use of electroencephalography (EEG) and magnetoencephalography (MEG) to investigate changes in oscillatory brain activity associated with tinnitus with many conflicting results. Current view of the underlying mechanism of tinnitus is that it results from changes in brain activity in various structures of the brain as a consequence of sensory deprivation. This in turn gives rise to increased spontaneous activity and/or synchrony in the auditory centers but also involves modulation from non-auditory processes from structures of the limbic and paralimbic system. Some of the neural changes associated with tinnitus may be assessed non-invasively in human beings with MEG and EEG (M/EEG) in ways, which are superior to animal studies and other non-invasive imaging techniques. However, both MEG and EEG have their limitations and research results can be misinterpreted without appropriate consideration of these limitations. In this article, I intend to provide a brief review of these techniques, describe what the recorded signals reflect in terms of the underlying neural activity, and their strengths and limitations. I also discuss some pertinent methodological issues involved in tinnitus-related studies and conclude with suggestions to minimize possible discrepancies between results. The overall message is that while MEG and EEG are extremely useful techniques, the interpretation of results from tinnitus studies requires much caution given the individual variability in oscillatory activity and the limits of these techniques. PMID:25431567

Subliminal versus supraliminal stimuli activate neural responses in anterior cingulate cortex, fusiform gyrus and insula: a meta-analysis of fMRI studies.

PubMed

Meneguzzo, Paolo; Tsakiris, Manos; Schioth, Helgi B; Stein, Dan J; Brooks, Samantha J

2014-01-01

Non-conscious neural activation may underlie various psychological functions in health and disorder. However, the neural substrates of non-conscious processing have not been entirely elucidated. Examining the differential effects of arousing stimuli that are consciously, versus unconsciously perceived will improve our knowledge of neural circuitry involved in non-conscious perception. Here we conduct preliminary analyses of neural activation in studies that have used both subliminal and supraliminal presentation of the same stimulus. We use Activation Likelihood Estimation (ALE) to examine functional Magnetic Resonance Imaging (fMRI) studies that uniquely present the same stimuli subliminally and supraliminally to healthy participants during functional magnetic resonance imaging (fMRI). We included a total of 193 foci from 9 studies representing subliminal stimulation and 315 foci from 10 studies representing supraliminal stimulation. The anterior cingulate cortex is significantly activated during both subliminal and supraliminal stimulus presentation. Subliminal stimuli are linked to significantly increased activation in the right fusiform gyrus and right insula. Supraliminal stimuli show significantly increased activation in the left rostral anterior cingulate. Non-conscious processing of arousing stimuli may involve primary visual areas and may also recruit the insula, a brain area involved in eventual interoceptive awareness. The anterior cingulate is perhaps a key brain region for the integration of conscious and non-conscious processing. These preliminary data provide candidate brain regions for further study in to the neural correlates of conscious experience.

Ca(2+) coding and decoding strategies for the specification of neural and renal precursor cells during development.

PubMed

Moreau, Marc; Néant, Isabelle; Webb, Sarah E; Miller, Andrew L; Riou, Jean-François; Leclerc, Catherine

2016-03-01

During embryogenesis, a rise in intracellular Ca(2+) is known to be a widespread trigger for directing stem cells towards a specific tissue fate, but the precise Ca(2+) signalling mechanisms involved in achieving these pleiotropic effects are still poorly understood. In this review, we compare the Ca(2+) signalling events that appear to be one of the first steps in initiating and regulating both neural determination (neural induction) and kidney development (nephrogenesis). We have highlighted the necessary and sufficient role played by Ca(2+) influx and by Ca(2+) transients in the determination and differentiation of pools of neural or renal precursors. We have identified new Ca(2+) target genes involved in neural induction and we showed that the same Ca(2+) early target genes studied are not restricted to neural tissue but are also present in other tissues, principally in the pronephros. In this review, we also described a mechanism whereby the transcriptional control of gene expression during neurogenesis and nephrogenesis might be directly controlled by Ca(2+) signalling. This mechanism involves members of the Kcnip family such that a change in their binding properties to specific DNA sites is a result of Ca(2+) binding to EF-hand motifs. The different functions of Ca(2+) signalling during these two events illustrate the versatility of Ca(2+) as a second messenger. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding Neurological Disease Mechanisms in the Era of Epigenetics

PubMed Central

Qureshi, Irfan A.; Mehler, Mark F.

2015-01-01

The burgeoning field of epigenetics is making a significant impact on our understanding of brain evolution, development, and function. In fact, it is now clear that epigenetic mechanisms promote seminal neurobiological processes, ranging from neural stem cell maintenance and differentiation to learning and memory. At the molecular level, epigenetic mechanisms regulate the structure and activity of the genome in response to intracellular and environmental cues, including the deployment of cell type–specific gene networks and those underlying synaptic plasticity. Pharmacological and genetic manipulation of epigenetic factors can, in turn, induce remarkable changes in neural cell identity and cognitive and behavioral phenotypes. Not surprisingly, it is also becoming apparent that epigenetics is intimately involved in neurological disease pathogenesis. Herein, we highlight emerging paradigms for linking epigenetic machinery and processes with neurological disease states, including how (1) mutations in genes encoding epigenetic factors cause disease, (2) genetic variation in genes encoding epigenetic factors modify disease risk, (3) abnormalities in epigenetic factor expression, localization, or function are involved in disease pathophysiology, (4) epigenetic mechanisms regulate disease-associated genomic loci, gene products, and cellular pathways, and (5) differential epigenetic profiles are present in patient-derived central and peripheral tissues. PMID:23571666

A structural variant in the 5’-flanking region of the TWIST2 gene affects melanocyte development in belted cattle

PubMed Central

Drögemüller, Cord; Jagannathan, Vidhya; Keller, Irene; Wüthrich, Daniel; Bruggmann, Rémy; Schütz, Ekkehard; Demmel, Steffi; Moser, Simon; Signer-Hasler, Heidi; Pieńkowska-Schelling, Aldona; Schelling, Claude; Sande, Marcos; Rongen, Ronald

2017-01-01

Belted cattle have a circular belt of unpigmented hair and skin around their midsection. The belt is inherited as a monogenic autosomal dominant trait. We mapped the causative variant to a 37 kb segment on bovine chromosome 3. Whole genome sequence data of 2 belted and 130 control cattle yielded only one private genetic variant in the critical interval in the two belted animals. The belt-associated variant was a copy number variant (CNV) involving the quadruplication of a 6 kb non-coding sequence located approximately 16 kb upstream of the TWIST2 gene. Increased copy numbers at this CNV were strongly associated with the belt phenotype in a cohort of 333 cases and 1322 controls. We hypothesized that the CNV causes aberrant expression of TWIST2 during neural crest development, which might negatively affect melanoblasts. Functional studies showed that ectopic expression of bovine TWIST2 in neural crest in transgenic zebrafish led to a decrease in melanocyte numbers. Our results thus implicate an unsuspected involvement of TWIST2 in regulating pigmentation and reveal a non-coding CNV underlying a captivating Mendelian character. PMID:28658273

The extended amygdala and salt appetite

NASA Technical Reports Server (NTRS)

Johnson, A. K.; de Olmos, J.; Pastuskovas, C. V.; Zardetto-Smith, A. M.; Vivas, L.

1999-01-01

Both chemo- and mechanosensitive receptors are involved in detecting changes in the signals that reflect the status of body fluids and of blood pressure. These receptors are located in the systemic circulatory system and in the sensory circumventricular organs of the brain. Under conditions of body fluid deficit or of marked changes in fluid distribution, multiple inputs derived from these humoral and neural receptors converge on key areas of the brain where the information is integrated. The result of this central processing is the mobilization of homeostatic behaviors (thirst and salt appetite), hormone release, autonomic changes, and cardiovascular adjustments. This review discusses the current understanding of the nature and role of the central and systemic receptors involved in the facilitation and inhibition of thirst and salt appetite and on particular components of the central neural network that receive and process input derived from fluid- and cardiovascular-related sensory systems. Special attention is paid to the structures of the lamina terminalis, the area postrema, the lateral parabrachial nucleus, and their association with the central nucleus of the amygdala and the bed nucleus of the stria terminalis in controlling the behaviors that participate in maintaining body fluid and cardiovascular homeostasis.

Potential Involvement of Draxin in the Axonal Projection of Cranial Nerves, Especially Cranial Nerve X, in the Chick Hindbrain.

PubMed

Zhang, Sanbing; Cui, Huixian; Wang, Lei; Kang, Lin; Huang, Guannan; Du, Juan; Li, Sha; Tanaka, Hideaki; Su, Yuhong

2016-07-01

The appropriate projection of axons within the nervous system is a crucial component of the establishment of neural circuitry. Draxin is a repulsive axon guidance protein. Draxin has important functions in the guidance of three commissures in the central nervous system and in the migration of neural crest cells and dI3 interneurons in the chick spinal cord. Here, we report that the distribution of the draxin protein and the location of 23C10-positive areas have a strong temporal and spatial correlation. The overexpression of draxin, especially transmembrane draxin, caused 23C10-positive axon bundles to misproject in the dorsal hindbrain. In addition, the overexpression of transmembrane draxin caused abnormal formation of the ganglion crest of the IX and X cranial nerves, misprojection of some anti-human natural killer-1 (HNK-1)-stained structures in the dorsal roof of the hindbrain, and a simultaneous reduction in the efferent nerves of some motoneuron axons inside the hindbrain. Our data reveal that draxin might be involved in the fascicular projection of cranial nerves in the hindbrain. © 2016 The Histochemical Society.

Physiological changes in neurodegeneration - mechanistic insights and clinical utility.

PubMed

Ahmed, Rebekah M; Ke, Yazi D; Vucic, Steve; Ittner, Lars M; Seeley, William; Hodges, John R; Piguet, Olivier; Halliday, Glenda; Kiernan, Matthew C

2018-05-01

The effects of neurodegenerative syndromes extend beyond cognitive function to involve key physiological processes, including eating and metabolism, autonomic nervous system function, sleep, and motor function. Changes in these physiological processes are present in several conditions, including frontotemporal dementia, amyotrophic lateral sclerosis, Alzheimer disease and the parkinsonian plus conditions. Key neural structures that mediate physiological changes across these conditions include neuroendocrine and hypothalamic pathways, reward pathways, motor systems and the autonomic nervous system. In this Review, we highlight the key changes in physiological processing in neurodegenerative syndromes and the similarities in these changes between different progressive neurodegenerative brain conditions. The changes and similarities between disorders might provide novel insights into the human neural correlates of physiological functioning. Given the evidence that physiological changes can arise early in the neurodegenerative process, these changes could provide biomarkers to aid in the early diagnosis of neurodegenerative diseases and in treatment trials.

Flexibility of movement organization in piano performance

PubMed Central

Furuya, Shinichi; Altenmüller, Eckart

2013-01-01

Piano performance involves a large repertoire of highly skilled movements. The acquisition of these exceptional skills despite innate neural and biomechanical constraints requires a sophisticated interaction between plasticity of the neural system and organization of a redundant number of degrees of freedom (DOF) in the motor system. Neuroplasticity subserving virtuosity of pianists has been documented in neuroimaging studies investigating effects of long-term piano training on structure and function of the cortical and subcortical regions. By contrast, recent behavioral studies have advanced the understanding of neuromuscular strategies and biomechanical principles behind the movement organization that enables skilled piano performance. Here we review the motor control and biomechanics literature, introducing the importance of describing motor behaviors not only for understanding mechanisms responsible for skillful motor actions in piano playing, but also for advancing diagnosis and rehabilitation of movement disorders caused by extensive piano practice. PMID:23882199

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.

Behavioral and genetic correlates of the neural response to infant crying among human fathers

PubMed Central

Mascaro, Jennifer S.; Hackett, Patrick D.; Gouzoules, Harold; Lori, Adriana

2014-01-01

Although evolution has shaped human infant crying and the corresponding response from caregivers, there is marked variation in paternal involvement and caretaking behavior, highlighting the importance of understanding the neurobiology supporting optimal paternal responses to cries. We explored the neural response to infant cries in fathers of children aged 1–2, and its relationship with hormone levels, variation in the androgen receptor (AR) gene, parental attitudes and parental behavior. Although number of AR CAG trinucleotide repeats was positively correlated with neural activity in brain regions important for empathy (anterior insula and inferior frontal gyrus), restrictive attitudes were inversely correlated with neural activity in these regions and with regions involved with emotion regulation (orbitofrontal cortex). Anterior insula activity had a non-linear relationship with paternal caregiving, such that fathers with intermediate activation were most involved. These results suggest that restrictive attitudes may be associated with decreased empathy and emotion regulation in response to a child in distress, and that moderate anterior insula activity reflects an optimal level of arousal that supports engaged fathering. PMID:24336349

Neural correlates of early-closure garden-path processing: Effects of prosody and plausibility.

PubMed

den Ouden, Dirk-Bart; Dickey, Michael Walsh; Anderson, Catherine; Christianson, Kiel

2016-01-01

Functional magnetic resonance imaging (fMRI) was used to investigate neural correlates of early-closure garden-path sentence processing and use of extrasyntactic information to resolve temporary syntactic ambiguities. Sixteen participants performed an auditory picture verification task on sentences presented with natural versus flat intonation. Stimuli included sentences in which the garden-path interpretation was plausible, implausible because of a late pragmatic cue, or implausible because of a semantic mismatch between an optionally transitive verb and the following noun. Natural sentence intonation was correlated with left-hemisphere temporal activation, but also with activation that suggests the allocation of more resources to interpretation when natural prosody is provided. Garden-path processing was associated with upregulation in bilateral inferior parietal and right-hemisphere dorsolateral prefrontal and inferior frontal cortex, while differences between the strength and type of plausibility cues were also reflected in activation patterns. Region of interest (ROI) analyses in regions associated with complex syntactic processing are consistent with a role for posterior temporal cortex supporting access to verb argument structure. Furthermore, ROI analyses within left-hemisphere inferior frontal gyrus suggest a division of labour, with the anterior-ventral part primarily involved in syntactic-semantic mismatch detection, the central part supporting structural reanalysis, and the posterior-dorsal part showing a general structural complexity effect.

[Forensic neuropsychology at the challenge of the relationship between cognition and emotion in psychopathy].

PubMed

Alcázar-Córcoles, M A; Verdejo-García, A; Bouso-Saiz, J C

The relationship between frontal lobe damage and criminality is especially complex. The neural substrates of psychopathic behavior seem to involve structural and functional abnormalities in the frontal lobes and the limbic system. AIM. To analyze the repercussions that brain structural and functional abnormalities in psychopathic individuals may have for forensic neuropsychology. Consistent evidence indicate that response inhibition problems in psychopathic subjects are linked to structural or functional damage in the frontal cortex. Furthermore, the prefrontal cortex, along with the amygdala and the hippocampus forms the limbic system, which is an important neural substrate of emotion processing; therefore the psychopath's capacity of affective processing could also be impaired. The theoretical frameworks of the somatic marker and mirror neuron hypotheses, along with the empirical study of executive functions may contribute to explain the inability of the psychopathic subjects to feel empathy, which is one of the main inhibitors of violence and antisocial behavior. The relationship between frontal lobe dysfunction and antisocial behavior arises an important legal issue. In order to consider some type of minor liability in the case of psychopaths it is suggested to gather further research data about the relationship between frontal lobe dysfunction and the ability to inhibit antisocial behavior by making an adequate use of empathy and emotional ties.

Using Motor Imagery to Study the Neural Substrates of Dynamic Balance

PubMed Central

Ferraye, Murielle Ursulla; Debû, Bettina; Heil, Lieke; Carpenter, Mark; Bloem, Bastiaan Roelof; Toni, Ivan

2014-01-01

This study examines the cerebral structures involved in dynamic balance using a motor imagery (MI) protocol. We recorded cerebral activity with functional magnetic resonance imaging while subjects imagined swaying on a balance board along the sagittal plane to point a laser at target pairs of different sizes (small, large). We used a matched visual imagery (VI) control task and recorded imagery durations during scanning. MI and VI durations were differentially influenced by the sway accuracy requirement, indicating that MI of balance is sensitive to the increased motor control necessary to point at a smaller target. Compared to VI, MI of dynamic balance recruited additional cortical and subcortical portions of the motor system, including frontal cortex, basal ganglia, cerebellum and mesencephalic locomotor region, the latter showing increased effective connectivity with the supplementary motor area. The regions involved in MI of dynamic balance were spatially distinct but contiguous to those involved in MI of gait (Bakker et al., 2008; Snijders et al., 2011; Crémers et al., 2012), in a pattern consistent with existing somatotopic maps of the trunk (for balance) and legs (for gait). These findings validate a novel, quantitative approach for studying the neural control of balance in humans. This approach extends previous reports on MI of static stance (Jahn et al., 2004, 2008), and opens the way for studying gait and balance impairments in patients with neurodegenerative disorders. PMID:24663383

Using motor imagery to study the neural substrates of dynamic balance.

PubMed

Ferraye, Murielle Ursulla; Debû, Bettina; Heil, Lieke; Carpenter, Mark; Bloem, Bastiaan Roelof; Toni, Ivan

2014-01-01

This study examines the cerebral structures involved in dynamic balance using a motor imagery (MI) protocol. We recorded cerebral activity with functional magnetic resonance imaging while subjects imagined swaying on a balance board along the sagittal plane to point a laser at target pairs of different sizes (small, large). We used a matched visual imagery (VI) control task and recorded imagery durations during scanning. MI and VI durations were differentially influenced by the sway accuracy requirement, indicating that MI of balance is sensitive to the increased motor control necessary to point at a smaller target. Compared to VI, MI of dynamic balance recruited additional cortical and subcortical portions of the motor system, including frontal cortex, basal ganglia, cerebellum and mesencephalic locomotor region, the latter showing increased effective connectivity with the supplementary motor area. The regions involved in MI of dynamic balance were spatially distinct but contiguous to those involved in MI of gait (Bakker et al., 2008; Snijders et al., 2011; Crémers et al., 2012), in a pattern consistent with existing somatotopic maps of the trunk (for balance) and legs (for gait). These findings validate a novel, quantitative approach for studying the neural control of balance in humans. This approach extends previous reports on MI of static stance (Jahn et al., 2004, 2008), and opens the way for studying gait and balance impairments in patients with neurodegenerative disorders.

Stability analysis of fractional-order Hopfield neural networks with time delays.

PubMed

Wang, Hu; Yu, Yongguang; Wen, Guoguang

2014-07-01

This paper investigates the stability for fractional-order Hopfield neural networks with time delays. Firstly, the fractional-order Hopfield neural networks with hub structure and time delays are studied. Some sufficient conditions for stability of the systems are obtained. Next, two fractional-order Hopfield neural networks with different ring structures and time delays are developed. By studying the developed neural networks, the corresponding sufficient conditions for stability of the systems are also derived. It is shown that the stability conditions are independent of time delays. Finally, numerical simulations are given to illustrate the effectiveness of the theoretical results obtained in this paper. Copyright © 2014 Elsevier Ltd. All rights reserved.

Natural language acquisition in large scale neural semantic networks

NASA Astrophysics Data System (ADS)

Ealey, Douglas

This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

Hippocampal coupling with cortical and subcortical structures in the context of memory consolidation.

PubMed

Skelin, Ivan; Kilianski, Scott; McNaughton, Bruce L

2018-04-13

Memory consolidation is a gradual process through which episodic memories become incorporated into long-term 'semantic' representations. It likely involves reactivation of neural activity encoding the recent experience during non-REM sleep. A critical prerequisite for memory consolidation is precise coordination of reactivation events between the hippocampus and cortical/subcortical structures, facilitated by the coupling of local field potential (LFP) oscillations (slow oscillations, sleep spindles and sharp wave/ripples) between these structures. We review the rapidly expanding literature on the qualitative and quantitative aspects of hippocampal oscillatory and neuronal coupling with cortical/subcortical structures in the context of memory reactivation. Reactivation in the hippocampus and cortical/subcortical structures is tightly coupled with sharp wave/ripples. Hippocampal-cortical/subcortical coupling is rich in dimensionality and this dimensionality is likely underestimated due to the limitations of the current methodology. Copyright © 2018 Elsevier Inc. All rights reserved.

Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

NASA Astrophysics Data System (ADS)

Vafaei, Mohammadreza; Alih, Sophia C.; Shad, Hossein; Falah, Ali; Halim, Nur Hajarul Falahi Abdul

2018-03-01

The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set.

Involvement of Brain-Derived Neurotrophic Factor in Late-Life Depression

PubMed Central

Dwivedi, Yogesh

2013-01-01

Brain-derived neurotrophic factor (BDNF), one of the major neurotrophic factors, plays an important role in the maintenance and survival of neurons, synaptic integrity, and synaptic plasticity. Evidence suggests that BDNF is involved in major depression, such that the level of BDNF is decreased in depressed patients and that antidepressants reverse this decrease. Stress, a major factor in depression, also modulates BDNF expression. These studies have led to the proposal of the neurotrophin hypothesis of depression. Late-life depression is associated with disturbances in structural and neural plasticity as well as impairments in cognitive behavior. Stress and aging also play a crucial role in late-life depression. Many recent studies have suggested that not only expression of BDNF is decreased in the serum/plasma of patients with late-life depression, but structural abnormalities in the brain of these patients may be associated with a polymorphism in the BDNF gene, and that there is a relationship between a BDNF polymorphism and antidepressant remission rates. This review provides a critical review of the involvement of BDNF in major depression, in general, and in late-life depression, in particular. PMID:23570887

Cre-driver lines used for genetic fate mapping of neural crest cells in the mouse: An overview.

PubMed

Debbache, Julien; Parfejevs, Vadims; Sommer, Lukas

2018-04-19

The neural crest is one of the embryonic structures with the broadest developmental potential in vertebrates. Morphologically, neural crest cells emerge during neurulation in the dorsal folds of the neural tube before undergoing an epithelial-to-mesenchymal transition (EMT), delaminating from the neural tube, and migrating to multiple sites in the growing embryo. Neural crest cells generate cell types as diverse as peripheral neurons and glia, melanocytes, and so-called mesectodermal derivatives that include craniofacial bone and cartilage and smooth muscle cells in cardiovascular structures. In mice, the fate of neural crest cells has been determined mainly by means of transgenesis and genome editing technologies. The most frequently used method relies on the Cre-loxP system, in which expression of Cre-recombinase in neural crest cells or their derivatives genetically enables the expression of a Cre-reporter allele, thus permanently marking neural crest-derived cells. Here, we provide an overview of the Cre-driver lines used in the field and discuss to what extent these lines allow precise neural crest stage and lineage-specific fate mapping. © 2018 The Authors Genesis: The Journal of Genetics and Development Published by Wiley Periodicals, Inc.

Insect Responses to Linearly Polarized Reflections: Orphan Behaviors Without Neural Circuits.

PubMed

Heinloth, Tanja; Uhlhorn, Juliane; Wernet, Mathias F

2018-01-01

The e-vector orientation of linearly polarized light represents an important visual stimulus for many insects. Especially the detection of polarized skylight by many navigating insect species is known to improve their orientation skills. While great progress has been made towards describing both the anatomy and function of neural circuit elements mediating behaviors related to navigation, relatively little is known about how insects perceive non-celestial polarized light stimuli, like reflections off water, leaves, or shiny body surfaces. Work on different species suggests that these behaviors are not mediated by the "Dorsal Rim Area" (DRA), a specialized region in the dorsal periphery of the adult compound eye, where ommatidia contain highly polarization-sensitive photoreceptor cells whose receptive fields point towards the sky. So far, only few cases of polarization-sensitive photoreceptors have been described in the ventral periphery of the insect retina. Furthermore, both the structure and function of those neural circuits connecting to these photoreceptor inputs remain largely uncharacterized. Here we review the known data on non-celestial polarization vision from different insect species (dragonflies, butterflies, beetles, bugs and flies) and present three well-characterized examples for functionally specialized non-DRA detectors from different insects that seem perfectly suited for mediating such behaviors. Finally, using recent advances from circuit dissection in Drosophila melanogaster , we discuss what types of potential candidate neurons could be involved in forming the underlying neural circuitry mediating non-celestial polarization vision.

Neural dissociation of food- and money-related reward processing using an abstract incentive delay task.

PubMed

Simon, Joe J; Skunde, Mandy; Wu, Mudan; Schnell, Knut; Herpertz, Sabine C; Bendszus, Martin; Herzog, Wolfgang; Friederich, Hans-Christoph

2015-08-01

Food is an innate reward stimulus related to energy homeostasis and survival, whereas money is considered a more general reward stimulus that gains a rewarding value through learning experiences. Although the underlying neural processing for both modalities of reward has been investigated independently from one another, a more detailed investigation of neural similarities and/or differences between food and monetary reward is still missing. Here, we investigated the neural processing of food compared with monetary-related rewards in 27 healthy, normal-weight women using functional magnetic resonance imaging. We developed a task distinguishing between the anticipation and the receipt of either abstract food or monetary reward. Both tasks activated the ventral striatum during the expectation of a reward. Compared with money, greater food-related activations were observed in prefrontal, parietal and central midline structures during the anticipation and lateral orbitofrontal cortex (lOFC) during the receipt of food reward. Furthermore, during the receipt of food reward, brain activation in the secondary taste cortex was positively related to the body mass index. These results indicate that food-dependent activations encompass to a greater extent brain regions involved in self-control and self-reflection during the anticipation and phylogenetically older parts of the lOFC during the receipt of reward. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Pleiotrophin promotes perineural invasion in pancreatic cancer.

PubMed

Yao, Jun; Hu, Xiu-Feng; Feng, Xiao-Shan; Gao, She-Gan

2013-10-21

Perineural invasion (PNI) in pancreatic cancer is an important cause of local recurrence, but little is known about its mechanism. Pleiotrophin (PTN) is an important neurotrophic factor. It is of interest that our recent experimental data showed its involvement in PNI of pancreatic cancer. PTN strongly presents in the cytoplasm of pancreatic cancer cells, and high expression of PTN and its receptor may contribute to the high PNI of pancreatic cancer. Correspondingly, PNI is prone to happen in PTN-positive tumors. We thus hypothesize that, as a neurite growth-promoting factor, PTN may promote PNI in pancreatic cancer. PTN is released at the time of tumor cell necrosis, and binds with its high-affinity receptor, N-syndecan on pancreatic nerves, to promote neural growth in pancreatic cancer. Furthermore, neural destruction leads to a distorted neural homeostasis. Neurons and Schwann cells produce more N-syndecan in an effort to repair the pancreatic nerves. However, the abundance of N-syndecan attracts further PTN-positive cancer cells to the site of injury, creating a vicious cycle. Ultimately, increased PTN and N-syndecan levels, due to the continuous nerve injury, may promote cancer invasion and propagation along the neural structures. Therefore, it is meaningful to discuss the relationship between PTN/N-syndecan signaling and PNI in pancreatic cancer, which may lead to a better understanding of the mechanism of PNI in pancreatic cancer.

Pleiotrophin promotes perineural invasion in pancreatic cancer

PubMed Central

Yao, Jun; Hu, Xiu-Feng; Feng, Xiao-Shan; Gao, She-Gan

2013-01-01

Perineural invasion (PNI) in pancreatic cancer is an important cause of local recurrence, but little is known about its mechanism. Pleiotrophin (PTN) is an important neurotrophic factor. It is of interest that our recent experimental data showed its involvement in PNI of pancreatic cancer. PTN strongly presents in the cytoplasm of pancreatic cancer cells, and high expression of PTN and its receptor may contribute to the high PNI of pancreatic cancer. Correspondingly, PNI is prone to happen in PTN-positive tumors. We thus hypothesize that, as a neurite growth-promoting factor, PTN may promote PNI in pancreatic cancer. PTN is released at the time of tumor cell necrosis, and binds with its high-affinity receptor, N-syndecan on pancreatic nerves, to promote neural growth in pancreatic cancer. Furthermore, neural destruction leads to a distorted neural homeostasis. Neurons and Schwann cells produce more N-syndecan in an effort to repair the pancreatic nerves. However, the abundance of N-syndecan attracts further PTN-positive cancer cells to the site of injury, creating a vicious cycle. Ultimately, increased PTN and N-syndecan levels, due to the continuous nerve injury, may promote cancer invasion and propagation along the neural structures. Therefore, it is meaningful to discuss the relationship between PTN/N-syndecan signaling and PNI in pancreatic cancer, which may lead to a better understanding of the mechanism of PNI in pancreatic cancer. PMID:24151381

Fully integrated silicon probes for high-density recording of neural activity.

PubMed

Jun, James J; Steinmetz, Nicholas A; Siegle, Joshua H; Denman, Daniel J; Bauza, Marius; Barbarits, Brian; Lee, Albert K; Anastassiou, Costas A; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L; Gutnisky, Diego A; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P Dylan; Rossant, Cyrille; Sun, Wei-Lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D; Koch, Christof; O'Keefe, John; Harris, Timothy D

2017-11-08

Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca 2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.

Fully Integrated Silicon Probes for High-Density Recording of Neural Activity

PubMed Central

Jun, James J.; Steinmetz, Nicholas A.; Siegle, Joshua H.; Denman, Daniel J.; Bauza, Marius; Barbarits, Brian; Lee, Albert K.; Anastassiou, Costas A.; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J.; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L.; Gutnisky, Diego A.; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P. Dylan; Rossant, Cyrille; Sun, Wei-lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D.; Koch, Christof; O'Keefe, John; Harris, Timothy D.

2018-01-01

Summary Paragraph Sensory, motor, and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures1,2. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution but from only a few dozen neurons per shank. Optical Ca2+ imaging3–5 offers more coverage but lacks the temporal resolution to reliably distinguish individual spikes and does not measure local field potentials. To date, no technology compatible with unrestrained animals has combined high spatiotemporal resolution with large volume coverage. To satisfy this need, we designed, fabricated, and tested a new silicon probe called Neuropixels. Each probe has 384 recording channels that can programmably address 960 CMOS processing-compatible low-impedance TiN6 sites that tile a single 10 mm long, 70x20 µm cross section shank. The 6x9 mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed, and digitized on the base, allowing noise-free digital data transmission directly from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were simultaneously recorded from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed recording large populations of neurons from multiple brain structures in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens the path to record brain-wide neural activity during behavior. PMID:29120427

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.

The Medial Ventrothalamic Circuitry: Cells Implicated in a Bimodal Network

PubMed Central

Vega-Zuniga, Tomas; Trost, Dominik; Schicker, Katrin; Bogner, Eva M.; Luksch, Harald

2018-01-01

Previous avian thalamic studies have shown that the medial ventral thalamus is composed of several nuclei located close to the lateral wall of the third ventricle. Although the general connectivity is known, detailed morphology and connectivity pattern in some regions are still elusive. Here, using the intracellular filling technique in the chicken, we focused on two neural structures, namely, the retinorecipient neuropil of the n. geniculatus lateralis pars ventralis (GLv), and the adjacent n. intercalatus thalami (ICT). We found that the GLv-ne cells showed two different neuronal types: projection cells and horizontal interneurons. The projection cells showed variable morphologies and dendritic arborizations with axons that targeted the n. lentiformis mesencephali (LM), griseum tectale (GT), ICT, n. principalis precommissuralis (PPC), and optic tectum (TeO). The horizontal cells showed a widespread mediolateral neural process throughout the retinorecipient GLv-ne. The ICT cells, on the other hand, had multipolar somata with wide dendritic fields that extended toward the lamina interna of the GLv, and a projection pattern that targeted the n. laminaris precommissuralis (LPC). Together, these results elucidate the rich complexity of the connectivity pattern so far described between the GLv, ICT, pretectum, and tectum. Interestingly, the implication of some of these neural structures in visuomotor and somatosensory roles strongly suggests that the GLv and ICT are part of a bimodal circuit that may be involved in the generation/modulation of saccades, gaze control, and space perception. PMID:29479309

Neural-Network Simulator

NASA Technical Reports Server (NTRS)

Mitchell, Paul H.

1991-01-01

F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

Neural network based system for equipment surveillance

DOEpatents

Vilim, Richard B.; Gross, Kenneth C.; Wegerich, Stephan W.

1998-01-01

A method and system for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process.

Neural network based system for equipment surveillance

DOEpatents

Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

1998-04-28

A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database

PubMed Central

Avdagic, Zikrija; Purisevic, Elvir; Omanovic, Samir; Coralic, Zlatan

2009-01-01

In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513. PMID:21347158

The neural network to determine the mechanical properties of the steels

NASA Astrophysics Data System (ADS)

Yemelyanov, Vitaliy; Yemelyanova, Nataliya; Safonova, Marina; Nedelkin, Aleksey

2018-04-01

The authors describe the neural network structure and software that is designed and developed to determine the mechanical properties of steels. The neural network is developed to refine upon the values of the steels properties. The results of simulations of the developed neural network are shown. The authors note the low standard error of the proposed neural network. To realize the proposed neural network the specialized software has been developed.

Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

PubMed

Panzeri, Stefano; Harvey, Christopher D; Piasini, Eugenio; Latham, Peter E; Fellin, Tommaso

2017-02-08

The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task. Copyright © 2017 Elsevier Inc. All rights reserved.

Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

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

Zhang, Xuesong; Liang, Faming; Yu, Beibei

2011-11-09

Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework to incorporate the uncertainties associated with input, model structure, and parameter into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform the BNNs that only consider uncertainties associatedmore » with parameter and model structure. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters show that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of different uncertainty sources and including output error into the MCMC framework are expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting.« less

Decoding the dynamic representation of musical pitch from human brain activity.

PubMed

Sankaran, N; Thompson, W F; Carlile, S; Carlson, T A

2018-01-16

In music, the perception of pitch is governed largely by its tonal function given the preceding harmonic structure of the music. While behavioral research has advanced our understanding of the perceptual representation of musical pitch, relatively little is known about its representational structure in the brain. Using Magnetoencephalography (MEG), we recorded evoked neural responses to different tones presented within a tonal context. Multivariate Pattern Analysis (MVPA) was applied to "decode" the stimulus that listeners heard based on the underlying neural activity. We then characterized the structure of the brain's representation using decoding accuracy as a proxy for representational distance, and compared this structure to several well established perceptual and acoustic models. The observed neural representation was best accounted for by a model based on the Standard Tonal Hierarchy, whereby differences in the neural encoding of musical pitches correspond to their differences in perceived stability. By confirming that perceptual differences honor those in the underlying neuronal population coding, our results provide a crucial link in understanding the cognitive foundations of musical pitch across psychological and neural domains.

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Application of artificial neural networks to the design optimization of aerospace structural components

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Patnaik, Surya N.; Murthy, Pappu L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated by using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network with the code NETS. Optimum designs for new design conditions were predicted by using the trained network. Neural net prediction of optimum designs was found to be satisfactory for most of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Optimum Design of Aerospace Structural Components Using Neural Networks

NASA Technical Reports Server (NTRS)

Berke, L.; Patnaik, S. N.; Murthy, P. L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires a trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network using the code NETS. Optimum designs for new design conditions were predicted using the trained network. Neural net prediction of optimum designs was found to be satisfactory for the majority of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks.

PubMed

Erfanian Saeedi, Nafise; Blamey, Peter J; Burkitt, Anthony N; Grayden, David B

2016-04-01

Pitch perception is important for understanding speech prosody, music perception, recognizing tones in tonal languages, and perceiving speech in noisy environments. The two principal pitch perception theories consider the place of maximum neural excitation along the auditory nerve and the temporal pattern of the auditory neurons' action potentials (spikes) as pitch cues. This paper describes a biophysical mechanism by which fine-structure temporal information can be extracted from the spikes generated at the auditory periphery. Deriving meaningful pitch-related information from spike times requires neural structures specialized in capturing synchronous or correlated activity from amongst neural events. The emergence of such pitch-processing neural mechanisms is described through a computational model of auditory processing. Simulation results show that a correlation-based, unsupervised, spike-based form of Hebbian learning can explain the development of neural structures required for recognizing the pitch of simple and complex tones, with or without the fundamental frequency. The temporal code is robust to variations in the spectral shape of the signal and thus can explain the phenomenon of pitch constancy.

Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks

PubMed Central

Erfanian Saeedi, Nafise; Blamey, Peter J.; Burkitt, Anthony N.; Grayden, David B.

2016-01-01

Pitch perception is important for understanding speech prosody, music perception, recognizing tones in tonal languages, and perceiving speech in noisy environments. The two principal pitch perception theories consider the place of maximum neural excitation along the auditory nerve and the temporal pattern of the auditory neurons’ action potentials (spikes) as pitch cues. This paper describes a biophysical mechanism by which fine-structure temporal information can be extracted from the spikes generated at the auditory periphery. Deriving meaningful pitch-related information from spike times requires neural structures specialized in capturing synchronous or correlated activity from amongst neural events. The emergence of such pitch-processing neural mechanisms is described through a computational model of auditory processing. Simulation results show that a correlation-based, unsupervised, spike-based form of Hebbian learning can explain the development of neural structures required for recognizing the pitch of simple and complex tones, with or without the fundamental frequency. The temporal code is robust to variations in the spectral shape of the signal and thus can explain the phenomenon of pitch constancy. PMID:27049657

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

PubMed

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

NASA Astrophysics Data System (ADS)

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-01

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Differentiation of mesenchymal stem cells into neuronal cells on fetal bovine acellular dermal matrix as a tissue engineered nerve scaffold

PubMed Central

Feng, Yuping; Wang, Jiao; Ling, Shixin; Li, Zhuo; Li, Mingsheng; Li, Qiongyi; Ma, Zongren; Yu, Sijiu

2014-01-01

The purpose of this study was to assess fetal bovine acellular dermal matrix as a scaffold for supporting the differentiation of bone marrow mesenchymal stem cells into neural cells following induction with neural differentiation medium. We performed long-term, continuous observation of cell morphology, growth, differentiation, and neuronal development using several microscopy techniques in conjunction with immunohistochemistry. We examined specific neuronal proteins and Nissl bodies involved in the differentiation process in order to determine the neuronal differentiation of bone marrow mesenchymal stem cells. The results show that bone marrow mesenchymal stem cells that differentiate on fetal bovine acellular dermal matrix display neuronal morphology with unipolar and bi/multipolar neurite elongations that express neuronal-specific proteins, including βIII tubulin. The bone marrow mesenchymal stem cells grown on fetal bovine acellular dermal matrix and induced for long periods of time with neural differentiation medium differentiated into a multilayered neural network-like structure with long nerve fibers that was composed of several parallel microfibers and neuronal cells, forming a complete neural circuit with dendrite-dendrite to axon-dendrite to dendrite-axon synapses. In addition, growth cones with filopodia were observed using scanning electron microscopy. Paraffin sectioning showed differentiated bone marrow mesenchymal stem cells with the typical features of neuronal phenotype, such as a large, round nucleus and a cytoplasm full of Nissl bodies. The data suggest that the biological scaffold fetal bovine acellular dermal matrix is capable of supporting human bone marrow mesenchymal stem cell differentiation into functional neurons and the subsequent formation of tissue engineered nerve. PMID:25598779

Knowing what and where: TMS evidence for the dual neural basis of geographical knowledge.

PubMed

Hoffman, Paul; Crutch, Sebastian

2016-02-01

All animals acquire knowledge about the topography of their immediate environment through direct exploration. Uniquely, humans also acquire geographical knowledge indirectly through exposure to maps and verbal information, resulting in a rich database of global geographical knowledge. We used transcranial magnetic stimulation to investigate the structure and neural basis of this critical but poorly understood component of semantic knowledge. Participants completed tests of geographical knowledge that probed either information about spatial locations (e.g., France borders Spain) or non-spatial taxonomic information (e.g., France is a country). TMS applied to the anterior temporal lobe, a region that codes conceptual knowledge for words and objects, had a general disruptive effect on the geographical tasks. In contrast, stimulation of the intraparietal sulcus (IPS), a region involved in the coding of spatial and numerical information, had a highly selective effect on spatial geographical decisions but no effect on taxonomic judgements. Our results establish that geographical concepts lie at the intersection of two distinct neural representation systems, and provide insights into how the interaction of these systems shape our understanding of the world. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A spectral element method with adaptive segmentation for accurately simulating extracellular electrical stimulation of neurons.

PubMed

Eiber, Calvin D; Dokos, Socrates; Lovell, Nigel H; Suaning, Gregg J

2017-05-01

The capacity to quickly and accurately simulate extracellular stimulation of neurons is essential to the design of next-generation neural prostheses. Existing platforms for simulating neurons are largely based on finite-difference techniques; due to the complex geometries involved, the more powerful spectral or differential quadrature techniques cannot be applied directly. This paper presents a mathematical basis for the application of a spectral element method to the problem of simulating the extracellular stimulation of retinal neurons, which is readily extensible to neural fibers of any kind. The activating function formalism is extended to arbitrary neuron geometries, and a segmentation method to guarantee an appropriate choice of collocation points is presented. Differential quadrature may then be applied to efficiently solve the resulting cable equations. The capacity for this model to simulate action potentials propagating through branching structures and to predict minimum extracellular stimulation thresholds for individual neurons is demonstrated. The presented model is validated against published values for extracellular stimulation threshold and conduction velocity for realistic physiological parameter values. This model suggests that convoluted axon geometries are more readily activated by extracellular stimulation than linear axon geometries, which may have ramifications for the design of neural prostheses.

Dynamic facial expressions evoke distinct activation in the face perception network: a connectivity analysis study.

PubMed

Foley, Elaine; Rippon, Gina; Thai, Ngoc Jade; Longe, Olivia; Senior, Carl

2012-02-01

Very little is known about the neural structures involved in the perception of realistic dynamic facial expressions. In the present study, a unique set of naturalistic dynamic facial emotional expressions was created. Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend Haxby et al.'s [Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223-233, 2000] distributed neural system for face perception. This network includes early visual regions, such as the inferior occipital gyrus, which is identified as insensitive to motion or affect but sensitive to the visual stimulus, the STS, identified as specifically sensitive to motion, and the amygdala, recruited to process affect. Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as the inferior occipital gyrus and the STS, along with coupling between the STS and the amygdala, as well as the inferior frontal gyrus. These findings support the presence of a distributed network of cortical regions that mediate the perception of different dynamic facial expressions.

Neurofunctional Correlates of Environmental Cognition: An fMRI Study with Images from Episodic Memory

PubMed Central

Gutyrchik, Evgeny; Bao, Yan; Blautzik, Janusch; Pöppel, Ernst; Zaytseva, Yuliya; Russell, Edmund

2015-01-01

This study capitalizes on individual episodic memories to investigate the question, how dif-ferent environments affect us on a neural level. Instead of using predefined environmental stimuli, this study relied on individual representations of beauty and pleasure. Drawing upon episodic memories we conducted two experiments. Healthy subjects imagined pleasant and non-pleasant environments, as well as beautiful and non-beautiful environments while neural activity was measured by using functional Magnetic Resonance Imaging. Although subjects found the different conditions equally simple to visualize, our results revealed more distribut-ed brain activations for non-pleasant and non-beautiful environments than for pleasant and beautiful environments. The additional regions activated in non-pleasant (left lateral prefrontal cortex) and non-beautiful environments (supplementary motor area, anterior cortical midline structures) are involved in self-regulation and top-down cognitive control. Taken together, the results show that perceptual experiences and emotional evaluations of environments within a positive and a negative frame of reference are based on distinct patterns of neural activity. We interpret the data in terms of a different cognitive and processing load placed by exposure to different environments. The results hint at the efficiency of subject-generated representations as stimulus material. PMID:25875000

Neurofunctional correlates of environmental cognition: an FMRI study with images from episodic memory.

PubMed

Vedder, Aline; Smigielski, Lukasz; Gutyrchik, Evgeny; Bao, Yan; Blautzik, Janusch; Pöppel, Ernst; Zaytseva, Yuliya; Russell, Edmund

2015-01-01

This study capitalizes on individual episodic memories to investigate the question, how dif-ferent environments affect us on a neural level. Instead of using predefined environmental stimuli, this study relied on individual representations of beauty and pleasure. Drawing upon episodic memories we conducted two experiments. Healthy subjects imagined pleasant and non-pleasant environments, as well as beautiful and non-beautiful environments while neural activity was measured by using functional Magnetic Resonance Imaging. Although subjects found the different conditions equally simple to visualize, our results revealed more distribut-ed brain activations for non-pleasant and non-beautiful environments than for pleasant and beautiful environments. The additional regions activated in non-pleasant (left lateral prefrontal cortex) and non-beautiful environments (supplementary motor area, anterior cortical midline structures) are involved in self-regulation and top-down cognitive control. Taken together, the results show that perceptual experiences and emotional evaluations of environments within a positive and a negative frame of reference are based on distinct patterns of neural activity. We interpret the data in terms of a different cognitive and processing load placed by exposure to different environments. The results hint at the efficiency of subject-generated representations as stimulus material.

Neural basis of stereotype-induced shifts in women's mental rotation performance

PubMed Central

Helt, Molly; Jacobs, Emily; Sullivan, Kerry

2007-01-01

Recent negative focus on women's academic abilities has fueled disputes over gender disparities in the sciences. The controversy derives, in part, from women's relatively poorer performance in aptitude tests, many of which require skills of spatial reasoning. We used functional magnetic imaging to examine the neural structure underlying shifts in women's performance of a spatial reasoning task induced by positive and negative stereotypes. Three groups of participants performed a task involving imagined rotations of the self. Prior to scanning, the positive stereotype group was exposed to a false but plausible stereotype of women's superior perspective-taking abilities; the negative stereotype group was exposed to the pervasive stereotype that men outperform women on spatial tasks; and the control group received neutral information. The significantly poorer performance we found in the negative stereotype group corresponded to increased activation in brain regions associated with increased emotional load. In contrast, the significantly improved performance we found in the positive stereotype group was associated with increased activation in visual processing areas and, to a lesser degree, complex working memory processes. These findings suggest that stereotype messages affect the brain selectively, with positive messages producing relatively more efficient neural strategies than negative messages. PMID:18985116

Toward Model Building for Visual Aesthetic Perception

PubMed Central

Lughofer, Edwin; Zeng, Xianyi

2017-01-01

Several models of visual aesthetic perception have been proposed in recent years. Such models have drawn on investigations into the neural underpinnings of visual aesthetics, utilizing neurophysiological techniques and brain imaging techniques including functional magnetic resonance imaging, magnetoencephalography, and electroencephalography. The neural mechanisms underlying the aesthetic perception of the visual arts have been explained from the perspectives of neuropsychology, brain and cognitive science, informatics, and statistics. Although corresponding models have been constructed, the majority of these models contain elements that are difficult to be simulated or quantified using simple mathematical functions. In this review, we discuss the hypotheses, conceptions, and structures of six typical models for human aesthetic appreciation in the visual domain: the neuropsychological, information processing, mirror, quartet, and two hierarchical feed-forward layered models. Additionally, the neural foundation of aesthetic perception, appreciation, or judgement for each model is summarized. The development of a unified framework for the neurobiological mechanisms underlying the aesthetic perception of visual art and the validation of this framework via mathematical simulation is an interesting challenge in neuroaesthetics research. This review aims to provide information regarding the most promising proposals for bridging the gap between visual information processing and brain activity involved in aesthetic appreciation. PMID:29270194

Neural basis of stereotype-induced shifts in women's mental rotation performance.

PubMed

Wraga, Maryjane; Helt, Molly; Jacobs, Emily; Sullivan, Kerry

2007-03-01

Recent negative focus on women's academic abilities has fueled disputes over gender disparities in the sciences. The controversy derives, in part, from women's relatively poorer performance in aptitude tests, many of which require skills of spatial reasoning. We used functional magnetic imaging to examine the neural structure underlying shifts in women's performance of a spatial reasoning task induced by positive and negative stereotypes. Three groups of participants performed a task involving imagined rotations of the self. Prior to scanning, the positive stereotype group was exposed to a false but plausible stereotype of women's superior perspective-taking abilities; the negative stereotype group was exposed to the pervasive stereotype that men outperform women on spatial tasks; and the control group received neutral information. The significantly poorer performance we found in the negative stereotype group corresponded to increased activation in brain regions associated with increased emotional load. In contrast, the significantly improved performance we found in the positive stereotype group was associated with increased activation in visual processing areas and, to a lesser degree, complex working memory processes. These findings suggest that stereotype messages affect the brain selectively, with positive messages producing relatively more efficient neural strategies than negative messages.

The relationship of neurogenesis and growth of brain regions to song learning

PubMed Central

Kirn, John R.

2009-01-01

Song learning, maintenance and production require coordinated activity across multiple auditory, sensory-motor, and neuromuscular structures. Telencephalic components of the sensory-motor circuitry are unique to avian species that engage in song learning. The song system shows protracted development that begins prior to hatching but continues well into adulthood. The staggered developmental timetable for construction of the song system provides clues of subsystems involved in specific stages of song learning and maintenance. Progressive events, including neurogenesis and song system growth, as well as regressive events such as apoptosis and synapse elimination, occur during periods of song learning and the transitions between stereotyped and variable song during both development and adulthood. There is clear evidence that gonadal steroids influence the development of song attributes and shape the underlying neural circuitry. Some aspects of song system development are influenced by sensory, motor and social experience, while other aspects of neural development appear to be experience-independent. Although there are species differences in the extent to which song learning continues into adulthood, growing evidence suggests that despite differences in learning trajectories, adult refinement of song motor control and song maintenance can require remarkable behavioral and neural flexibility reminiscent of sensory-motor learning. PMID:19853905

False recognition depends on depth of prior word processing: a magnetoencephalographic (MEG) study.

PubMed

Walla, P; Hufnagl, B; Lindinger, G; Deecke, L; Imhof, H; Lang, W

2001-04-01

Brain activity was measured with a whole head magnetoencephalograph (MEG) during the test phases of word recognition experiments. Healthy young subjects had to discriminate between previously presented and new words. During prior study phases two different levels of word processing were provided according to two different kinds of instructions (shallow and deep encoding). Event-related fields (ERFs) associated with falsely recognized words (false alarms) were found to depend on the depth of processing during the prior study phase. False alarms elicited higher brain activity (as reflected by dipole strength) in case of prior deep encoding as compared to shallow encoding between 300 and 500 ms after stimulus onset at temporal brain areas. Between 500 and 700 ms we found evidence for differences in the involvement of neural structures related to both conditions of false alarms. Furthermore, the number of false alarms was found to depend on depth of processing. Shallow encoding led to a higher number of false alarms than deep encoding. All data are discussed as strong support for the ideas that a certain level of word processing is performed by a distinct set of neural systems and that the same neural systems which encode information are reactivated during the retrieval.

Structural qualia: a solution to the hard problem of consciousness.

PubMed

Loorits, Kristjan

2014-01-01

The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has) something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved.

Structural qualia: a solution to the hard problem of consciousness

PubMed Central

Loorits, Kristjan

2014-01-01

The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has) something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved. PMID:24672510

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

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

Modular, Hierarchical Learning By Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Baldi, Pierre F.; Toomarian, Nikzad

1996-01-01

Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

Shades of grey; Assessing the contribution of the magno- and parvocellular systems to neural processing of the retinal input in the human visual system from the influence of neural population size and its discharge activity on the VEP.

PubMed

Marcar, Valentine L; Baselgia, Silvana; Lüthi-Eisenegger, Barbara; Jäncke, Lutz

2018-03-01

Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components. We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner. When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series. This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.

Early print-tuned ERP response with minimal involvement of linguistic processing in Japanese Hiragana strings.

PubMed

Okumura, Yasuko; Kasai, Tetsuko; Murohashi, Harumitsu

2014-04-16

The act of reading leads to the development of specific neural responses for print, the most frequently reported of which is the left occipitotemporal N170 component of event-related potentials. However, it remains unclear whether this electrophysiological response solely involves print-tuned neural activities. The present study examined an early print-tuned event-related potential response with minimal involvement of linguistic processing in a nonalphabetic language. Japanese Hiragana words, nonwords, and alphanumeric symbol strings were presented rapidly and the task was to detect the change in color of a fixation cross to restrict linguistic processing. As a result, Hiragana words and nonwords elicited a larger posterior N1 than alphanumeric symbol strings bilaterally, irrespective of intercharacter spacing. The fact that this N1 was enhanced specifically for rapidly presented Hiragana strings suggests the existence of print-tuned neural processes that are relatively independent of the influence of linguistic processing.

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.

Variable Neural Adaptive Robust Control: A Switched System Approach

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

Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

2015-05-01

Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less

Theory of mind, social development, and psychosis.

PubMed

Casacchia, Massimo; Mazza, Monica; Roncone, Rita

2004-06-01

The difficulty in interpreting other people's mental states found in children with autism and in people affected by schizophrenia may be explained in terms of a unique mental process called Theory of Mind. The paper discusses the main operational issues of such a peculiar aspect of social cognition, the Theory of Mind, and its implication in schizophrenia, including a review of its related neural structures. Theory of Mind abilities may be a relevant aspect of social interaction involving people affected by schizophrenia, and they need to be further investigated in clinical research.

The role of networks and artificial intelligence in nanotechnology design and analysis.

PubMed

Hudson, D L; Cohen, M E

2004-05-01

Techniques with their origins in artificial intelligence have had a great impact on many areas of biomedicine. Expert-based systems have been used to develop computer-assisted decision aids. Neural networks have been used extensively in disease classification and more recently in many bioinformatics applications including genomics and drug design. Network theory in general has proved useful in modeling all aspects of biomedicine from healthcare organizational structure to biochemical pathways. These methods show promise in applications involving nanotechnology both in the design phase and in interpretation of system functioning.

Application of neural nets in structural optimization

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Hajela, Prabhat

1993-01-01

The biological motivation for Artificial Neural Net developments is briefly discussed, and the most popular paradigm, the feedforward supervised learning net with error back propagation training algorithm, is introduced. Possible approaches for utilization in structural optimization is illustrated through simple examples. Other currently ongoing developments for application in structural mechanics are also mentioned.

Detection of Structural Abnormalities Using Neural Nets

NASA Technical Reports Server (NTRS)

Zak, M.; Maccalla, A.; Daggumati, V.; Gulati, S.; Toomarian, N.

1996-01-01

This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

Lunar Circular Structure Classification from Chang 'e 2 High Resolution Lunar Images with Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Zeng, X. G.; Liu, J. J.; Zuo, W.; Chen, W. L.; Liu, Y. X.

2018-04-01

Circular structures are widely distributed around the lunar surface. The most typical of them could be lunar impact crater, lunar dome, et.al. In this approach, we are trying to use the Convolutional Neural Network to classify the lunar circular structures from the lunar images.

Neural responses to ambiguity involve domain-general and domain-specific emotion processing systems.

PubMed

Neta, Maital; Kelley, William M; Whalen, Paul J

2013-04-01

Extant research has examined the process of decision making under uncertainty, specifically in situations of ambiguity. However, much of this work has been conducted in the context of semantic and low-level visual processing. An open question is whether ambiguity in social signals (e.g., emotional facial expressions) is processed similarly or whether a unique set of processors come on-line to resolve ambiguity in a social context. Our work has examined ambiguity using surprised facial expressions, as they have predicted both positive and negative outcomes in the past. Specifically, whereas some people tended to interpret surprise as negatively valenced, others tended toward a more positive interpretation. Here, we examined neural responses to social ambiguity using faces (surprise) and nonface emotional scenes (International Affective Picture System). Moreover, we examined whether these effects are specific to ambiguity resolution (i.e., judgments about the ambiguity) or whether similar effects would be demonstrated for incidental judgments (e.g., nonvalence judgments about ambiguously valenced stimuli). We found that a distinct task control (i.e., cingulo-opercular) network was more active when resolving ambiguity. We also found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence. Taken together, there is a complex neural architecture that supports decision making in the presence of ambiguity: (a) a core set of cortical structures engaged for explicit ambiguity processing across stimulus boundaries and (b) other dedicated circuits for biologically relevant learning situations involving faces.

Mitochondrial metabolism in early neural fate and its relevance for neuronal disease modeling.

PubMed

Lorenz, Carmen; Prigione, Alessandro

2017-12-01

Modulation of energy metabolism is emerging as a key aspect associated with cell fate transition. The establishment of a correct metabolic program is particularly relevant for neural cells given their high bioenergetic requirements. Accordingly, diseases of the nervous system commonly involve mitochondrial impairment. Recent studies in animals and in neural derivatives of human pluripotent stem cells (PSCs) highlighted the importance of mitochondrial metabolism for neural fate decisions in health and disease. The mitochondria-based metabolic program of early neurogenesis suggests that PSC-derived neural stem cells (NSCs) may be used for modeling neurological disorders. Understanding how metabolic programming is orchestrated during neural commitment may provide important information for the development of therapies against conditions affecting neural functions, including aging and mitochondrial disorders. Copyright © 2017. Published by Elsevier Ltd.

Cadherin-6B is proteolytically processed during epithelial-to-mesenchymal transitions of the cranial neural crest

PubMed Central

Schiffmacher, Andrew T.; Padmanabhan, Rangarajan; Jhingory, Sharon; Taneyhill, Lisa A.

2014-01-01

The epithelial-to-mesenchymal transition (EMT) is a highly coordinated process underlying both development and disease. Premigratory neural crest cells undergo EMT, migrate away from the neural tube, and differentiate into diverse cell types during vertebrate embryogenesis. Adherens junction disassembly within premigratory neural crest cells is one component of EMT and, in chick cranial neural crest cells, involves cadherin-6B (Cad6B) down-regulation. Whereas Cad6B transcription is repressed by Snail2, the rapid loss of Cad6B protein during EMT is suggestive of posttranslational mechanisms that promote Cad6B turnover. For the first time in vivo, we demonstrate Cad6B proteolysis during neural crest cell EMT, which generates a Cad6B N-terminal fragment (NTF) and two C-terminal fragments (CTF1/2). Coexpression of relevant proteases with Cad6B in vitro shows that a disintegrin and metalloproteinases (ADAMs) ADAM10 and ADAM19, together with γ-secretase, cleave Cad6B to produce the NTF and CTFs previously observed in vivo. Of importance, both ADAMs and γ-secretase are expressed in the appropriate spatiotemporal pattern in vivo to proteolytically process Cad6B. Overexpression or depletion of either ADAM within premigratory neural crest cells prematurely reduces or maintains Cad6B, respectively. Collectively these results suggest a dual mechanism for Cad6B proteolysis involving two ADAMs, along with γ-secretase, during cranial neural crest cell EMT. PMID:24196837

Hearing, feeling or seeing a beat recruits a supramodal network in the auditory dorsal stream.

PubMed

Araneda, Rodrigo; Renier, Laurent; Ebner-Karestinos, Daniela; Dricot, Laurence; De Volder, Anne G

2017-06-01

Hearing a beat recruits a wide neural network that involves the auditory cortex and motor planning regions. Perceiving a beat can potentially be achieved via vision or even touch, but it is currently not clear whether a common neural network underlies beat processing. Here, we used functional magnetic resonance imaging (fMRI) to test to what extent the neural network involved in beat processing is supramodal, that is, is the same in the different sensory modalities. Brain activity changes in 27 healthy volunteers were monitored while they were attending to the same rhythmic sequences (with and without a beat) in audition, vision and the vibrotactile modality. We found a common neural network for beat detection in the three modalities that involved parts of the auditory dorsal pathway. Within this network, only the putamen and the supplementary motor area (SMA) showed specificity to the beat, while the brain activity in the putamen covariated with the beat detection speed. These results highlighted the implication of the auditory dorsal stream in beat detection, confirmed the important role played by the putamen in beat detection and indicated that the neural network for beat detection is mostly supramodal. This constitutes a new example of convergence of the same functional attributes into one centralized representation in the brain. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Use long short-term memory to enhance Internet of Things for combined sewer overflow monitoring

NASA Astrophysics Data System (ADS)

Zhang, Duo; Lindholm, Geir; Ratnaweera, Harsha

2018-01-01

Combined sewer overflow causes severe water pollution, urban flooding and reduced treatment plant efficiency. Understanding the behavior of CSO structures is vital for urban flooding prevention and overflow control. Neural networks have been extensively applied in water resource related fields. In this study, we collect data from an Internet of Things monitoring CSO structure and build different neural network models for simulating and predicting the water level of the CSO structure. Through a comparison of four different neural networks, namely multilayer perceptron (MLP), wavelet neural network (WNN), long short-term memory (LSTM) and gated recurrent unit (GRU), the LSTM and GRU present superior capabilities for multi-step-ahead time series prediction. Furthermore, GRU achieves prediction performances similar to LSTM with a quicker learning curve.

Nested Neural Networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1992-01-01

Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

Recycling signals in the neural crest.

PubMed

Taneyhill, Lisa A; Bronner-Fraser, Marianne

2005-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

Neural entrainment to the rhythmic structure of music.

PubMed

Tierney, Adam; Kraus, Nina

2015-02-01

The neural resonance theory of musical meter explains musical beat tracking as the result of entrainment of neural oscillations to the beat frequency and its higher harmonics. This theory has gained empirical support from experiments using simple, abstract stimuli. However, to date there has been no empirical evidence for a role of neural entrainment in the perception of the beat of ecologically valid music. Here we presented participants with a single pop song with a superimposed bassoon sound. This stimulus was either lined up with the beat of the music or shifted away from the beat by 25% of the average interbeat interval. Both conditions elicited a neural response at the beat frequency. However, although the on-the-beat condition elicited a clear response at the first harmonic of the beat, this frequency was absent in the neural response to the off-the-beat condition. These results support a role for neural entrainment in tracking the metrical structure of real music and show that neural meter tracking can be disrupted by the presentation of contradictory rhythmic cues.

Neural Crest-Derived Mesenchymal Cells Require Wnt Signaling for Their Development and Drive Invagination of the Telencephalic Midline

PubMed Central

Choe, Youngshik; Zarbalis, Konstantinos S.; Pleasure, Samuel J.

2014-01-01

Embryonic neural crest cells contribute to the development of the craniofacial mesenchyme, forebrain meninges and perivascular cells. In this study, we investigated the function of ß-catenin signaling in neural crest cells abutting the dorsal forebrain during development. In the absence of ß-catenin signaling, neural crest cells failed to expand in the interhemispheric region and produced ectopic smooth muscle cells instead of generating dermal and calvarial mesenchyme. In contrast, constitutive expression of stabilized ß-catenin in neural crest cells increased the number of mesenchymal lineage precursors suggesting that ß-catenin signaling is necessary for the expansion of neural crest-derived mesenchymal cells. Interestingly, the loss of neural crest-derived mesenchymal stem cells (MSCs) leads to failure of telencephalic midline invagination and causes ventricular system defects. This study shows that ß-catenin signaling is required for the switch of neural crest cells to MSCs and mediates the expansion of MSCs to drive the formation of mesenchymal structures of the head. Furthermore, loss of these structures causes striking defects in forebrain morphogenesis. PMID:24516524

Establishing a Dynamic Self-Adaptation Learning Algorithm of the BP Neural Network and Its Applications

NASA Astrophysics Data System (ADS)

Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min

2015-12-01

In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.

Structural organization of the inactive X chromosome in the mouse

PubMed Central

Giorgetti, Luca; Lajoie, Bryan R.; Carter, Ava C.; Attia, Mikael; Zhan, Ye; Xu, Jin; Chen, Chong Jian; Kaplan, Noam; Chang, Howard Y.; Heard, Edith; Dekker, Job

2017-01-01

X-chromosome inactivation (XCI) involves major reorganization of the X chromosome as it becomes silent and heterochromatic. During female mammalian development, XCI is triggered by upregulation of the non-coding Xist RNA from one of the two X chromosomes. Xist coats the chromosome in cis and induces silencing of almost all genes via its A-repeat region1,2, although some genes (constitutive escapees) avoid silencing in most cell types, and others (facultative escapees) escape XCI only in specific contexts3. A role for Xist in organizing the inactive X (Xi) chromosome has been proposed4–6. Recent chromosome conformation capture approaches have revealed global loss of local structure on the Xi chromosome and formation of large mega-domains, separated by a region containing the DXZ4 macrosatellite7–10. However, the molecular architecture of the Xi chromosome, in both the silent and expressed regions, remains unclear. Here we investigate the structure, chromatin accessibility and expression status of the mouse Xi chromosome in highly polymorphic clonal neural progenitors (NPCs) and embryonic stem cells. We demonstrate a crucial role for Xist and the DXZ4-containing boundary in shaping Xi chromosome structure using allele-specific genome-wide chromosome conformation capture (Hi-C) analysis, an assay for transposase-accessible chromatin with high throughput sequencing (ATAC–seq) and RNA sequencing. Deletion of the boundary disrupts mega-domain formation, and induction of Xist RNA initiates formation of the boundary and the loss of DNA accessibility. We also show that in NPCs, the Xi chromosome lacks active/inactive compartments and topologically associating domains (TADs), except around genes that escape XCI. Escapee gene clusters display TAD-like structures and retain DNA accessibility at promoter-proximal and CTCF-binding sites. Furthermore, altered patterns of facultative escape genes in different neural progenitor clones are associated with the presence of different TAD-like structures after XCI. These findings suggest a key role for transcription and CTCF in the formation of TADs in the context of the Xi chromosome in neural progenitors. PMID:27437574

Systems biological approach to investigate the lack of familial link between Down's Syndrome & Neural Tube Disorders.

PubMed

Ragunath, Pk; Abhinand, Pa

2013-01-01

Systems Biology involves the study of the interactions of biological systems and ultimately their functions. Down's syndrome (DS) is one of the most common genetic disorders which are caused by complete, or occasionally partial, triplication of chromosome 21, characterized by cognitive and language dysfunction coupled with sensory and neuromotor deficits. Neural Tube Disorders (NTDs) are a group of congenital malformations of the central nervous system and neighboring structures related to defective neural tube closure during the first trimester of pregnancy usually occurring between days 18-29 of gestation. Several studies in the past have provided considerable evidence that abnormal folate and methyl metabolism are associated with onset of DS & NTDs. There is a possible common etiological pathway for both NTDs and Down's syndrome. But, various research studies over the years have indicated very little evidence for familial link between the two disorders. Our research aimed at the gene expression profiling of microarray datasets pertaining to the two disorders to identify genes whose expression levels are significantly altered in these conditions. The genes which were 1.5 fold unregulated and having a p-value <0.05 were filtered out and gene interaction network were constructed for both NTDs and DS. The top ranked dense clique for both the disorders were recognized and over representation analysis was carried out for each of the constituent genes. The comprehensive manual analysis of these genes yields a hypothetical understanding of the lack of familial link between DS and NTDs. There were no genes involved with folic acid present in the dense cliques. Only - CBL, EGFR genes were commonly present, which makes the allelic variants of these genes - good candidates for future studies regarding the familial link between DS and NTDs. NTD - Neural Tube Disorders, DS - Down's Syndrome, MTHFR - Methylenetetrahydrofolate reductase, MTRR- 5 - methyltetrahydrofolate-homocysteine methyltransferase reductase.

Neural underpinnings of divergent production of rules in numerical analogical reasoning.

PubMed

Wu, Xiaofei; Jung, Rex E; Zhang, Hao

2016-05-01

Creativity plays an important role in numerical problem solving. Although the neural underpinnings of creativity have been studied over decades, very little is known about neural mechanisms of the creative process that relates to numerical problem solving. In the present study, we employed a numerical analogical reasoning task with functional Magnetic Resonance Imaging (fMRI) to investigate the neural correlates of divergent production of rules in numerical analogical reasoning. Participants performed two tasks: a multiple solution analogical reasoning task and a single solution analogical reasoning task. Results revealed that divergent production of rules involves significant activations at Brodmann area (BA) 10 in the right middle frontal cortex, BA 40 in the left inferior parietal lobule, and BA 8 in the superior frontal cortex. The results suggest that right BA 10 and left BA 40 are involved in the generation of novel rules, and BA 8 is associated with the inhibition of initial rules in numerical analogical reasoning. The findings shed light on the neural mechanisms of creativity in numerical processing. Copyright © 2016 Elsevier B.V. All rights reserved.

The neural bases of the multiplication problem-size effect across countries

PubMed Central

Prado, Jérôme; Lu, Jiayan; Liu, Li; Dong, Qi; Zhou, Xinlin; Booth, James R.

2013-01-01

Multiplication problems involving large numbers (e.g., 9 × 8) are more difficult to solve than problems involving small numbers (e.g., 2 × 3). Behavioral research indicates that this problem-size effect might be due to different factors across countries and educational systems. However, there is no neuroimaging evidence supporting this hypothesis. Here, we compared the neural correlates of the multiplication problem-size effect in adults educated in China and the United States. We found a greater neural problem-size effect in Chinese than American participants in bilateral superior temporal regions associated with phonological processing. However, we found a greater neural problem-size effect in American than Chinese participants in right intra-parietal sulcus (IPS) associated with calculation procedures. Therefore, while the multiplication problem-size effect might be a verbal retrieval effect in Chinese as compared to American participants, it may instead stem from the use of calculation procedures in American as compared to Chinese participants. Our results indicate that differences in educational practices might affect the neural bases of symbolic arithmetic. PMID:23717274

Computational modeling of neural plasticity for self-organization of neural networks.

PubMed

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Cost-benefit decision circuitry: proposed modulatory role for acetylcholine.

PubMed

Fobbs, Wambura C; Mizumori, Sheri J Y

2014-01-01

In order to select which action should be taken, an animal must weigh the costs and benefits of possible outcomes associate with each action. Such decisions, called cost-benefit decisions, likely involve several cognitive processes (including memory) and a vast neural circuitry. Rodent models have allowed research to begin to probe the neural basis of three forms of cost-benefit decision making: effort-, delay-, and risk-based decision making. In this review, we detail the current understanding of the functional circuits that subserve each form of decision making. We highlight the extensive literature by detailing the ability of dopamine to influence decisions by modulating structures within these circuits. Since acetylcholine projects to all of the same important structures, we propose several ways in which the cholinergic system may play a local modulatory role that will allow it to shape these behaviors. A greater understanding of the contribution of the cholinergic system to cost-benefit decisions will permit us to better link the decision and memory processes, and this will help us to better understand and/or treat individuals with deficits in a number of higher cognitive functions including decision making, learning, memory, and language. © 2014 Elsevier Inc. All rights reserved.

The effect of the neural activity on topological properties of growing neural networks.

PubMed

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Colour or shape: examination of neural processes underlying mental flexibility in posttraumatic stress disorder.

PubMed

Pang, E W; Sedge, P; Grodecki, R; Robertson, A; MacDonald, M J; Jetly, R; Shek, P N; Taylor, M J

2014-08-05

Posttraumatic stress disorder (PTSD) is a mental disorder that stems from exposure to one or more traumatic events. While PTSD is thought to result from a dysregulation of emotional neurocircuitry, neurocognitive difficulties are frequently reported. Mental flexibility is a core executive function that involves the ability to shift and adapt to new information. It is essential for appropriate social-cognitive behaviours. Magnetoencephalography (MEG), a neuroimaging modality with high spatial and temporal resolution, has been used to track the progression of brain activation during tasks of mental flexibility called set-shifting. We hypothesized that the sensitivity of MEG would be able to capture the abnormal neurocircuitry implicated in PTSD and this would negatively impact brain regions involved in set-shifting. Twenty-two soldiers with PTSD and 24 matched control soldiers completed a colour-shape set-shifting task. MEG data were recorded and source localized to identify significant brain regions involved in the task. Activation latencies were obtained by analysing the time course of activation in each region. The control group showed a sequence of activity that involved dorsolateral frontal cortex, insula and posterior parietal cortices. The soldiers with PTSD showed these activations but they were interrupted by activations in paralimbic regions. This is consistent with models of PTSD that suggest dysfunctional neurocircuitry is driven by hyper-reactive limbic areas that are not appropriately modulated by prefrontal cortical control regions. This is the first study identifying the timing and location of atypical neural responses in PTSD with set-shifting and supports the model that hyperactive limbic structures negatively impact cognitive function.

Application of machine learning methods for traffic signs recognition

NASA Astrophysics Data System (ADS)

Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.

2018-02-01

This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.

Neural networks for structural design - An integrated system implementation

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Hafez, Wassim; Pao, Yoh-Han

1992-01-01

The development of powerful automated procedures to aid the creative designer is becoming increasingly critical for complex design tasks. In the work described here Artificial Neural Nets are applied to acquire structural analysis and optimization domain expertise. Based on initial instructions from the user an automated procedure generates random instances of structural analysis and/or optimization 'experiences' that cover a desired domain. It extracts training patterns from the created instances, constructs and trains an appropriate network architecture and checks the accuracy of net predictions. The final product is a trained neural net that can estimate analysis and/or optimization results instantaneously.

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Podocalyxin Is a Novel Polysialylated Neural Adhesion Protein with Multiple Roles in Neural Development and Synapse Formation

PubMed Central

Vitureira, Nathalia; Andrés, Rosa; Pérez-Martínez, Esther; Martínez, Albert; Bribián, Ana; Blasi, Juan; Chelliah, Shierley; López-Doménech, Guillermo; De Castro, Fernando; Burgaya, Ferran; McNagny, Kelly; Soriano, Eduardo

2010-01-01

Neural development and plasticity are regulated by neural adhesion proteins, including the polysialylated form of NCAM (PSA-NCAM). Podocalyxin (PC) is a renal PSA-containing protein that has been reported to function as an anti-adhesin in kidney podocytes. Here we show that PC is widely expressed in neurons during neural development. Neural PC interacts with the ERM protein family, and with NHERF1/2 and RhoA/G. Experiments in vitro and phenotypic analyses of podxl-deficient mice indicate that PC is involved in neurite growth, branching and axonal fasciculation, and that PC loss-of-function reduces the number of synapses in the CNS and in the neuromuscular system. We also show that whereas some of the brain PC functions require PSA, others depend on PC per se. Our results show that PC, the second highly sialylated neural adhesion protein, plays multiple roles in neural development. PMID:20706633

A New Module in Neural Differentiation Control: Two MicroRNAs Upregulated by Retinoic Acid, miR-9 and -103, Target the Differentiation Inhibitor ID2

PubMed Central

Savino, Mauro; Laneve, Pietro; Caffarelli, Elisa; Nasi, Sergio

2012-01-01

The transcription factor ID2 is an important repressor of neural differentiation strongly implicated in nervous system cancers. MicroRNAs (miRNAs) are increasingly involved in differentiation control and cancer development. Here we show that two miRNAs upregulated on differentiation of neuroblastoma cells – miR-9 and miR-103 – restrain ID2 expression by directly targeting the coding sequence and 3′ untranslated region of the ID2 encoding messenger RNA, respectively. Notably, the two miRNAs show an inverse correlation with ID2 during neuroblastoma cell differentiation induced by retinoic acid. Overexpression of miR-9 and miR-103 in neuroblastoma cells reduces proliferation and promotes differentiation, as it was shown to occur upon ID2 inhibition. Conversely, an ID2 mutant that cannot be targeted by either miRNA prevents retinoic acid-induced differentiation more efficient than wild-type ID2. These findings reveal a new regulatory module involving two microRNAs upregulated during neural differentiation that directly target expression of the key differentiation inhibitor ID2, suggesting that its alteration may be involved in neural cancer development. PMID:22848373

A new module in neural differentiation control: two microRNAs upregulated by retinoic acid, miR-9 and -103, target the differentiation inhibitor ID2.

PubMed

Annibali, Daniela; Gioia, Ubaldo; Savino, Mauro; Laneve, Pietro; Caffarelli, Elisa; Nasi, Sergio

2012-01-01

The transcription factor ID2 is an important repressor of neural differentiation strongly implicated in nervous system cancers. MicroRNAs (miRNAs) are increasingly involved in differentiation control and cancer development. Here we show that two miRNAs upregulated on differentiation of neuroblastoma cells--miR-9 and miR-103--restrain ID2 expression by directly targeting the coding sequence and 3' untranslated region of the ID2 encoding messenger RNA, respectively. Notably, the two miRNAs show an inverse correlation with ID2 during neuroblastoma cell differentiation induced by retinoic acid. Overexpression of miR-9 and miR-103 in neuroblastoma cells reduces proliferation and promotes differentiation, as it was shown to occur upon ID2 inhibition. Conversely, an ID2 mutant that cannot be targeted by either miRNA prevents retinoic acid-induced differentiation more efficient than wild-type ID2. These findings reveal a new regulatory module involving two microRNAs upregulated during neural differentiation that directly target expression of the key differentiation inhibitor ID2, suggesting that its alteration may be involved in neural cancer development.

Behavioral and genetic correlates of the neural response to infant crying among human fathers.

PubMed

Mascaro, Jennifer S; Hackett, Patrick D; Gouzoules, Harold; Lori, Adriana; Rilling, James K

2014-11-01

Although evolution has shaped human infant crying and the corresponding response from caregivers, there is marked variation in paternal involvement and caretaking behavior, highlighting the importance of understanding the neurobiology supporting optimal paternal responses to cries. We explored the neural response to infant cries in fathers of children aged 1-2, and its relationship with hormone levels, variation in the androgen receptor (AR) gene, parental attitudes and parental behavior. Although number of AR CAG trinucleotide repeats was positively correlated with neural activity in brain regions important for empathy (anterior insula and inferior frontal gyrus), restrictive attitudes were inversely correlated with neural activity in these regions and with regions involved with emotion regulation (orbitofrontal cortex). Anterior insula activity had a non-linear relationship with paternal caregiving, such that fathers with intermediate activation were most involved. These results suggest that restrictive attitudes may be associated with decreased empathy and emotion regulation in response to a child in distress, and that moderate anterior insula activity reflects an optimal level of arousal that supports engaged fathering. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Bio-inspired spiking neural network for nonlinear systems control.

PubMed

Pérez, Javier; Cabrera, Juan A; Castillo, Juan J; Velasco, Juan M

2018-08-01

Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more complex computation. As demonstrated by biological organisms, they are a potentially good approach to designing controllers for highly nonlinear dynamic systems in which the performance of controllers developed by conventional techniques is not satisfactory or difficult to implement. SNN-based controllers exploit their ability for online learning and self-adaptation to evolve when transferred from simulations to the real world. SNN's inherent binary and temporary way of information codification facilitates their hardware implementation compared to analog neurons. Biological neural networks often require a lower number of neurons compared to other controllers based on artificial neural networks. In this work, these neuronal systems are imitated to perform the control of non-linear dynamic systems. For this purpose, a control structure based on spiking neural networks has been designed. Particular attention has been paid to optimizing the structure and size of the neural network. The proposed structure is able to control dynamic systems with a reduced number of neurons and connections. A supervised learning process using evolutionary algorithms has been carried out to perform controller training. The efficiency of the proposed network has been verified in two examples of dynamic systems control. Simulations show that the proposed control based on SNN exhibits superior performance compared to other approaches based on Neural Networks and SNNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Neural Network Model of the Structure and Dynamics of Human Personality

ERIC Educational Resources Information Center

Read, Stephen J.; Monroe, Brian M.; Brownstein, Aaron L.; Yang, Yu; Chopra, Gurveen; Miller, Lynn C.

2010-01-01

We present a neural network model that aims to bridge the historical gap between dynamic and structural approaches to personality. The model integrates work on the structure of the trait lexicon, the neurobiology of personality, temperament, goal-based models of personality, and an evolutionary analysis of motives. It is organized in terms of two…

Behavioral and multimodal neuroimaging evidence for a deficit in brain timing networks in stuttering: a hypothesis and theory

PubMed Central

Etchell, Andrew C.; Johnson, Blake W.; Sowman, Paul F.

2014-01-01

The fluent production of speech requires accurately timed movements. In this article, we propose that a deficit in brain timing networks is one of the core neurophysiological deficits in stuttering. We first discuss the experimental evidence supporting the involvement of the basal ganglia and supplementary motor area (SMA) in stuttering and the involvement of the cerebellum as a possible mechanism for compensating for the neural deficits that underlie stuttering. Next, we outline the involvement of the right inferior frontal gyrus (IFG) as another putative compensatory locus in stuttering and suggest a role for this structure in an expanded core timing-network. Subsequently, we review behavioral studies of timing in people who stutter and examine their behavioral performance as compared to people who do not stutter. Finally, we highlight challenges to existing research and provide avenues for future research with specific hypotheses. PMID:25009487

Neural control of muscle

NASA Technical Reports Server (NTRS)

Max, S. R.; Markelonis, G. J.

1983-01-01

Cholinergic innervation regulates the physiological and biochemical properties of skeletal muscle. The mechanisms that appear to be involved in this regulation include soluble, neurally-derived polypeptides, transmitter-evoked muscle activity and the neurotransmitter, acetylcholine, itself. Despite extensive research, the interacting neural mechanisms that control such macromolecules as acetylcholinesterase, the acetylcholine receptor and glucose 6-phosphate dehydrogenase remain unclear. It may be that more simplified in vitro model systems coupled with recent dramatic advances in the molecular biology of neurally-regulated proteins will begin to allow researchers to unravel the mechanisms controlling the expression and maintenance of these macromolecules.

The optimization of force inputs for active structural acoustic control using a neural network

NASA Technical Reports Server (NTRS)

Cabell, R. H.; Lester, H. C.; Silcox, R. J.

1992-01-01

This paper investigates the use of a neural network to determine which force actuators, of a multi-actuator array, are best activated in order to achieve structural-acoustic control. The concept is demonstrated using a cylinder/cavity model on which the control forces, produced by piezoelectric actuators, are applied with the objective of reducing the interior noise. A two-layer neural network is employed and the back propagation solution is compared with the results calculated by a conventional, least-squares optimization analysis. The ability of the neural network to accurately and efficiently control actuator activation for interior noise reduction is demonstrated.

Neural Schematics as a unified formal graphical representation of large-scale Neural Network Structures.

PubMed

Ehrlich, Matthias; Schüffny, René

2013-01-01

One of the major outcomes of neuroscientific research are models of Neural Network Structures (NNSs). Descriptions of these models usually consist of a non-standardized mixture of text, figures, and other means of visual information communication in print media. However, as neuroscience is an interdisciplinary domain by nature, a standardized way of consistently representing models of NNSs is required. While generic descriptions of such models in textual form have recently been developed, a formalized way of schematically expressing them does not exist to date. Hence, in this paper we present Neural Schematics as a concept inspired by similar approaches from other disciplines for a generic two dimensional representation of said structures. After introducing NNSs in general, a set of current visualizations of models of NNSs is reviewed and analyzed for what information they convey and how their elements are rendered. This analysis then allows for the definition of general items and symbols to consistently represent these models as Neural Schematics on a two dimensional plane. We will illustrate the possibilities an agreed upon standard can yield on sampled diagrams transformed into Neural Schematics and an example application for the design and modeling of large-scale NNSs.

An improved protocol that induces human embryonic stem cells to differentiate into neural cells in vitro.

PubMed

Zhou, Jun-Mei; Chu, Jian-Xin; Chen, Xue-Jin

2008-01-01

Human embryonic stem (ES) cells have the capacity for self-renewal and are able to differentiate into any cell type. However, obtaining high-efficient neural differentiation from human ES cells remains a challenge. This study describes an improved 4-stage protocol to induce a human ES cell line derived from a Chinese population to differentiate into neural cells. At the first stage, embryonic bodies (EBs) were formed in a chemically-defined neural inducing medium rather than in traditional serum or serum-replacement medium. At the second stage, rosette-like structures were formed. At the third stage, the rosette-like structures were manually selected rather than enzymatically digested to form floating neurospheres. At the fourth stage, the neurospheres were further differentiated into neurons. The results show that, at the second stage, the rate of the formation of rosette-like structures from EBs induced by noggin was 88+/-6.32%, higher than that of retinoic acid 55+/-5.27%. Immunocytochemistry staining was used to confirm the neural identity of the cells. These results show a major improvement in obtaining efficient neural differentiation of human ES cells.

Artificial neural network prediction of aircraft aeroelastic behavior

NASA Astrophysics Data System (ADS)

Pesonen, Urpo Juhani

An Artificial Neural Network that predicts aeroelastic behavior of aircraft is presented. The neural net was designed to predict the shape of a flexible wing in static flight conditions using results from a structural analysis and an aerodynamic analysis performed with traditional computational tools. To generate reliable training and testing data for the network, an aeroelastic analysis code using these tools as components was designed and validated. To demonstrate the advantages and reliability of Artificial Neural Networks, a network was also designed and trained to predict airfoil maximum lift at low Reynolds numbers where wind tunnel data was used for the training. Finally, a neural net was designed and trained to predict the static aeroelastic behavior of a wing without the need to iterate between the structural and aerodynamic solvers.

Zebrafish narrowminded suggests a genetic link between formation of neural crest and primary sensory neurons

PubMed Central

Bruk Artinger, Kristin; Chitnis, Ajay B.; Mercola, Mark; Driever, Wolfgang

2014-01-01

SUMMARY In the developing vertebrate nervous system, both neural crest and sensory neurons form at the boundary between non-neural ectoderm and the neural plate. From an in situ hybridization based expression analysis screen, we have identified a novel zebrafish mutation, narrowminded (nrd), which reduces the number of early neural crest cells and eliminates Rohon-Beard (RB) sensory neurons. Mosaic analysis has shown that the mutation acts cell autonomously suggesting that nrd is involved in either the reception or interpretation of signals at the lateral neural plate boundary. Characterization of the mutant phenotype indicates that nrd is required for a primary wave of neural crest cell formation during which progenitors generate both RB sensory neurons and neural crest cells. Moreover, the early deficit in neural crest cells in nrd homozygotes is compensated later in development. Thus, we propose that a later wave can compensate for the loss of early neural crest cells but, interestingly, not the RB sensory neurons. We discuss the implications of these findings for the possibility that RB sensory neurons and neural crest cells share a common evolutionary origin. PMID:10457007

The neural correlates of highly iconic structures and topographic discourse in French Sign Language as observed in six hearing native signers.

PubMed

Courtin, C; Hervé, P-Y; Petit, L; Zago, L; Vigneau, M; Beaucousin, V; Jobard, G; Mazoyer, B; Mellet, E; Tzourio-Mazoyer, N

2010-09-01

"Highly iconic" structures in Sign Language enable a narrator to act, switch characters, describe objects, or report actions in four-dimensions. This group of linguistic structures has no real spoken-language equivalent. Topographical descriptions are also achieved in a sign-language specific manner via the use of signing-space and spatial-classifier signs. We used functional magnetic resonance imaging (fMRI) to compare the neural correlates of topographic discourse and highly iconic structures in French Sign Language (LSF) in six hearing native signers, children of deaf adults (CODAs), and six LSF-naïve monolinguals. LSF materials consisted of videos of a lecture excerpt signed without spatially organized discourse or highly iconic structures (Lect LSF), a tale signed using highly iconic structures (Tale LSF), and a topographical description using a diagrammatic format and spatial-classifier signs (Topo LSF). We also presented texts in spoken French (Lect French, Tale French, Topo French) to all participants. With both languages, the Topo texts activated several different regions that are involved in mental navigation and spatial working memory. No specific correlate of LSF spatial discourse was evidenced. The same regions were more activated during Tale LSF than Lect LSF in CODAs, but not in monolinguals, in line with the presence of signing-space structure in both conditions. Motion processing areas and parts of the fusiform gyrus and precuneus were more active during Tale LSF in CODAs; no such effect was observed with French or in LSF-naïve monolinguals. These effects may be associated with perspective-taking and acting during personal transfers. 2010 Elsevier Inc. All rights reserved.

Chondroitin Sulfate (CS) Lyases: Structure, Function and Application in Therapeutics.

PubMed

Rani, Aruna; Patel, Seema; Goyal, Arun

2018-01-01

Glycosaminoglycans (GAGs) such as chondroitin sulfate (CS) are the chief natural polysaccharides which reside in biological tissues mainly in extracellular matrix. These CS along with adhesion molecules and growth factors are involved in central nervous system (CNS) development, cell progression and pathogenesis. The chondroitin lyases are the enzyme that degrade and alter the CS chains and hence modify various signalling pathways involving CS chains. These CS lyases are substrate specific, can precisely manipulate the CS polysaccharides and have various biotechnological, medical and therapeutic applications. These enzymes can be used to produce the unsaturated oligosaccharides, which have immune-modulatory, anti-inflammatory and neuroprotective properties. This review focuses on the major breakthrough of the chondroitin sulfate degrading enzymes, their structures and functioning mechanism. This also provides comprehensive information regarding production, purification, characterization of CS lyases and their major applications, both established as well as emerging ones such as neural development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Neural circuits in anxiety and stress disorders: a focused review

PubMed Central

Duval, Elizabeth R; Javanbakht, Arash; Liberzon, Israel

2015-01-01

Anxiety and stress disorders are among the most prevalent neuropsychiatric disorders. In recent years, multiple studies have examined brain regions and networks involved in anxiety symptomatology in an effort to better understand the mechanisms involved and to develop more effective treatments. However, much remains unknown regarding the specific abnormalities and interactions between networks of regions underlying anxiety disorder presentations. We examined recent neuroimaging literature that aims to identify neural mechanisms underlying anxiety, searching for patterns of neural dysfunction that might be specific to different anxiety disorder categories. Across different anxiety and stress disorders, patterns of hyperactivation in emotion-generating regions and hypoactivation in prefrontal/regulatory regions are common in the literature. Interestingly, evidence of differential patterns is also emerging, such that within a spectrum of disorders ranging from more fear-based to more anxiety-based, greater involvement of emotion-generating regions is reported in panic disorder and specific phobia, and greater involvement of prefrontal regions is reported in generalized anxiety disorder and posttraumatic stress disorder. We summarize the pertinent literature and suggest areas for continued investigation. PMID:25670901

Perception for Outdoor Navigation

DTIC Science & Technology

1990-11-01

without lane marktings. Our perception modules use a variety of techniques for video processing (clusering theory, symbolic feature detection, neural nets...on gravel and dirt roads, as expected. The most difficult case involved a dirt road in a forest, which was mainly distinguishable in the video images...in that estimate. u bIsrshigl Neural Nets. Under separate funding, we have driven the Naviab using neural nets to track the road in video iages. We ame

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

Pathobiology and genetics of neural tube defects.

PubMed

Finnell, Richard H; Gould, Amy; Spiegelstein, Ofer

2003-01-01

Neural tube defects (NTDs), including spina bifida and anencephaly, are common congenital malformations that occur when the neural tube fails to achieve proper closure during early embryogenesis. Based on epidemiological and clinical data obtained over the last few decades, it is apparent that these multifactorial defects have a significant genetic component to their etiology that interacts with specific environmental risk factors. The purpose of this review article is to synthesize the existing literature on the genetic factors contributing to NTD risk. To date, there is evidence that closure of the mammalian neural tube initiates and fuses intermittently at four discrete locations. Disruption of this process at any of these four sites may lead to an NTD, possibly arising through closure site-specific genetic mechanisms. Candidate genes involved in neural tube closure include genes of the folate metabolic pathway, as well as those involved in folate transport. Although extensive efforts have focused on elucidating the genetic risk factors contributing to the etiology of NTDs, the population burden for these malformations remains unknown. One group at high risk for having children with NTDs is epileptic women receiving antiepileptic medications during pregnancy. Efforts to better understand the genetic factors that may contribute to their heightened risk, as well as the pathogenesis of neural tube closure defects, are reviewed herein.

Race modulates neural activity during imitation

PubMed Central

Losin, Elizabeth A. Reynolds; Iacoboni, Marco; Martin, Alia; Cross, Katy A.; Dapretto, Mirella

2014-01-01

Imitation plays a central role in the acquisition of culture. People preferentially imitate others who are self-similar, prestigious or successful. Because race can indicate a person's self-similarity or status, race influences whom people imitate. Prior studies of the neural underpinnings of imitation have not considered the effects of race. Here we measured neural activity with fMRI while European American participants imitated meaningless gestures performed by actors of their own race, and two racial outgroups, African American, and Chinese American. Participants also passively observed the actions of these actors and their portraits. Frontal, parietal and occipital areas were differentially activated while participants imitated actors of different races. More activity was present when imitating African Americans than the other racial groups, perhaps reflecting participants' reported lack of experience with and negative attitudes towards this group, or the group's lower perceived social status. This pattern of neural activity was not found when participants passively observed the gestures of the actors or simply looked at their faces. Instead, during face-viewing neural responses were overall greater for own-race individuals, consistent with prior race perception studies not involving imitation. Our findings represent a first step in elucidating neural mechanisms involved in cultural learning, a process that influences almost every aspect of our lives but has thus far received little neuroscientific study. PMID:22062193

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory

PubMed Central

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high–low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. PMID:25146374

Neural network to diagnose lining condition

NASA Astrophysics Data System (ADS)

Yemelyanov, V. A.; Yemelyanova, N. Y.; Nedelkin, A. A.; Zarudnaya, M. V.

2018-03-01

The paper presents data on the problem of diagnosing the lining condition at the iron and steel works. The authors describe the neural network structure and software that are designed and developed to determine the lining burnout zones. The simulation results of the proposed neural networks are presented. The authors note the low learning and classification errors of the proposed neural networks. To realize the proposed neural network, the specialized software has been developed.

ER fluid applications to vibration control devices and an adaptive neural-net controller

NASA Astrophysics Data System (ADS)

Morishita, Shin; Ura, Tamaki

1993-07-01

Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

The neural system of metacognition accompanying decision-making in the prefrontal cortex

PubMed Central

Qiu, Lirong; Su, Jie; Ni, Yinmei; Bai, Yang; Zhang, Xuesong; Li, Xiaoli

2018-01-01

Decision-making is usually accompanied by metacognition, through which a decision maker monitors uncertainty regarding a decision and may then consequently revise the decision. These metacognitive processes can occur prior to or in the absence of feedback. However, the neural mechanisms of metacognition remain controversial. One theory proposes an independent neural system for metacognition in the prefrontal cortex (PFC); the other, that metacognitive processes coincide and overlap with the systems used for the decision-making process per se. In this study, we devised a novel “decision–redecision” paradigm to investigate the neural metacognitive processes involved in redecision as compared to the initial decision-making process. The participants underwent a perceptual decision-making task and a rule-based decision-making task during functional magnetic resonance imaging (fMRI). We found that the anterior PFC, including the dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were more extensively activated after the initial decision. The dACC activity in redecision positively scaled with decision uncertainty and correlated with individual metacognitive uncertainty monitoring abilities—commonly occurring in both tasks—indicating that the dACC was specifically involved in decision uncertainty monitoring. In contrast, the lFPC activity seen in redecision processing was scaled with decision uncertainty reduction and correlated with individual accuracy changes—positively in the rule-based decision-making task and negatively in the perceptual decision-making task. Our results show that the lFPC was specifically involved in metacognitive control of decision adjustment and was subject to different control demands of the tasks. Therefore, our findings support that a separate neural system in the PFC is essentially involved in metacognition and further, that functions of the PFC in metacognition are dissociable. PMID:29684004

Memory-related brain lateralisation in birds and humans.

PubMed

Moorman, Sanne; Nicol, Alister U

2015-03-01

Visual imprinting in chicks and song learning in songbirds are prominent model systems for the study of the neural mechanisms of memory. In both systems, neural lateralisation has been found to be involved in memory formation. Although many processes in the human brain are lateralised--spatial memory and musical processing involves mostly right hemisphere dominance, whilst language is mostly left hemisphere dominant--it is unclear what the function of lateralisation is. It might enhance brain capacity, make processing more efficient, or prevent occurrence of conflicting signals. In both avian paradigms we find memory-related lateralisation. We will discuss avian lateralisation findings and propose that birds provide a strong model for studying neural mechanisms of memory-related lateralisation. Copyright © 2014. Published by Elsevier Ltd.

Neurophysiology and neural engineering: a review.

PubMed

Prochazka, Arthur

2017-08-01

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

Underlying Mechanisms of Tinnitus: Review and Clinical Implications

PubMed Central

Henry, James A.; Roberts, Larry E.; Caspary, Donald M.; Theodoroff, Sarah M.; Salvi, Richard J.

2016-01-01

Background The study of tinnitus mechanisms has increased tenfold in the last decade. The common denominator for all of these studies is the goal of elucidating the underlying neural mechanisms of tinnitus with the ultimate purpose of finding a cure. While these basic science findings may not be immediately applicable to the clinician who works directly with patients to assist them in managing their reactions to tinnitus, a clear understanding of these findings is needed to develop the most effective procedures for alleviating tinnitus. Purpose The goal of this review is to provide audiologists and other health-care professionals with a basic understanding of the neurophysiological changes in the auditory system likely to be responsible for tinnitus. Results It is increasingly clear that tinnitus is a pathology involving neuroplastic changes in central auditory structures that take place when the brain is deprived of its normal input by pathology in the cochlea. Cochlear pathology is not always expressed in the audiogram but may be detected by more sensitive measures. Neural changes can occur at the level of synapses between inner hair cells and the auditory nerve and within multiple levels of the central auditory pathway. Long-term maintenance of tinnitus is likely a function of a complex network of structures involving central auditory and nonauditory systems. Conclusions Patients often have expectations that a treatment exists to cure their tinnitus. They should be made aware that research is increasing to discover such a cure and that their reactions to tinnitus can be mitigated through the use of evidence-based behavioral interventions. PMID:24622858

Ultrasonic vocalizations in mouse models for speech and socio-cognitive disorders: insights into the evolution of vocal communication

PubMed Central

Fischer, J; Hammerschmidt, K

2011-01-01

Comparative analyses used to reconstruct the evolution of traits associated with the human language faculty, including its socio-cognitive underpinnings, highlight the importance of evolutionary constraints limiting vocal learning in non-human primates. After a brief overview of this field of research and the neural basis of primate vocalizations, we review studies that have addressed the genetic basis of usage and structure of ultrasonic communication in mice, with a focus on the gene FOXP2 involved in specific language impairments and neuroligin genes (NL-3 and NL-4) involved in autism spectrum disorders. Knockout of FoxP2 leads to reduced vocal behavior and eventually premature death. Introducing the human variant of FoxP2 protein into mice, in contrast, results in shifts in frequency and modulation of pup ultrasonic vocalizations. Knockout of NL-3 and NL-4 in mice diminishes social behavior and vocalizations. Although such studies may provide insights into the molecular and neural basis of social and communicative behavior, the structure of mouse vocalizations is largely innate, limiting the suitability of the mouse model to study human speech, a learned mode of production. Although knockout or replacement of single genes has perceptible effects on behavior, these genes are part of larger networks whose functions remain poorly understood. In humans, for instance, deficiencies in NL-4 can lead to a broad spectrum of disorders, suggesting that further factors (experiential and/or genetic) contribute to the variation in clinical symptoms. The precise nature as well as the interaction of these factors is yet to be determined. PMID:20579107

An Empirical Review of the Neural Underpinnings of Receiving and Giving Social Support: Implications for Health

PubMed Central

Eisenberger, Naomi I.

2013-01-01

Decades of research have demonstrated strong links between social ties and health. Although considerable evidence has shown that social support can attenuate downstream physiological stress responses that are relevant to health, the neurocognitive mechanisms that translate perceptions of social ties into altered physiological responses are still not fully understood. This review integrates research from social and affective neuroscience to illuminate some of the neural mechanisms involved in social support processes, which may further our understanding of the ways in which social support influence health. This review focuses on two types of social support that have been shown to relate to health: receiving and giving social support. As the neural basis of receiving support, this article reviews the hypothesis that receiving support may benefit health through the activation of neural regions that respond to safety and inhibit threat-related neural and physiological responding. This article will then review neuroimaging studies in which subjects were primed with or received support during a negative experience as well as studies in which self-reports of perceived support were correlated with neural responses to a negative experience. As the neural basis of giving support, this article reviews the hypothesis that neural regions involved in maternal caregiving behavior may be critical for the health benefits of support-giving through the inhibition of threat-related neural and physiological responding. Neuroimaging studies in which subjects provided support to others or engaged in other related forms of prosocial behavior will then be reviewed. Implications of these findings for furthering our understanding of the relationships between social support and health are discussed. PMID:23804014

Crystal structure of tandem type III fibronectin domains from Drosophila neuroglian at 2.0 A.

PubMed

Huber, A H; Wang, Y M; Bieber, A J; Bjorkman, P J

1994-04-01

We report the crystal structure of two adjacent fibronectin type III repeats from the Drosophila neural cell adhesion molecule neuroglian. Each domain consists of two antiparallel beta sheets and is folded topologically identically to single fibronectin type III domains from the extracellular matrix proteins tenascin and fibronectin. beta bulges and left-handed polyproline II helices disrupt the regular beta sheet structure of both neuroglian domains. The hydrophobic interdomain interface includes a metal-binding site, presumably involved in stabilizing the relative orientation between domains and predicted by sequence comparision to be present in the vertebrate homolog molecule L1. The neuroglian domains are related by a near perfect 2-fold screw axis along the longest molecular dimension. Using this relationship, a model for arrays of tandem fibronectin type III repeats in neuroglian and other molecules is proposed.

Flexible deep brain neural probes based on a parylene tube structure

NASA Astrophysics Data System (ADS)

Zhao, Zhiguo; Kim, Eric; Luo, Hao; Zhang, Jinsheng; Xu, Yong

2018-01-01

Most microfabricated neural probes have limited shank length, which prevents them from reaching many deep brain structures. This paper reports deep brain neural probes with ultra-long penetrating shanks based on a simple but novel parylene tube structure. The mechanical strength of the parylene tube shank is temporarily enhanced during implantation by inserting a metal wire. The metal wire can be removed after implantation, making the implanted probe very flexible and thus minimizing the stress caused by micromotions of brain tissues. Optogenetic stimulation and chemical delivery capabilities can be potentially integrated by taking advantage of the tube structure. Single-shank prototypes with a shank length of 18.2 mm have been developed. The microfabrication process comprises of deep reactive ion etching (DRIE) of silicon, parylene conformal coating/refilling, and XeF2 isotropic silicon etching. In addition to bench-top insertion characterization, the functionality of developed probes has been preliminarily demonstrated by implanting into the amygdala of a rat and recording neural signals.

Neural Network Development Tool (NETS)

NASA Technical Reports Server (NTRS)

Baffes, Paul T.

1990-01-01

Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

PubMed

Daniel, Reka; Pollmann, Stefan

2010-01-06

The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

Brain structures and neurotransmitters regulating aggression in cats: implications for human aggression.

PubMed

Gregg, T R; Siegel, A

2001-01-01

1. Violence and aggression are major public health problems. 2. The authors have used techniques of electrical brain stimulation, anatomical-immunohistochemical techniques, and behavioral pharmacology to investigate the neural systems and circuits underlying aggressive behavior in the cat. 3. The medial hypothalamus and midbrain periaqueductal gray are the most important structures mediating defensive rage behavior, and the perifornical lateral hypothalamus clearly mediates predatory attack behavior. The hippocampus, amygdala, bed nucleus of the stria terminalis, septal area, cingulate gyrus, and prefrontal cortex project to these structures directly or indirectly and thus can modulate the intensity of attack and rage. 4. Evidence suggests that several neurotransmitters facilitate defensive rage within the PAG and medial hypothalamus, including glutamate, Substance P, and cholecystokinin, and that opioid peptides suppress it; these effects usually depend on the subtype of receptor that is activated. 5. A key recent discovery was a GABAergic projection that may underlie the often-observed reciprocally inhibitory relationship between these two forms of aggression. 6. Recently, Substance P has come under scrutiny as a possible key neurotransmitter involved in defensive rage, and the mechanism by which it plays a role in aggression and rage is under investigation. 7. It is hoped that this line of research will provide a better understanding of the neural mechanisms and substrates regulating aggression and rage and thus establish a rational basis for treatment of disorders associated with these forms of aggression.

The control of male sexual responses.

PubMed

Courtois, Frédérique; Carrier, Serge; Charvier, Kathleen; Guertin, Pierre A; Journel, Nicolas Morel

2013-01-01

Male sexual responses are reflexes mediated by the spinal cord and modulated by neural circuitries involving both the peripheral and central nervous system. While the brain interact with the reflexes to allow perception of sexual sensations and to exert excitatory or inhibitory influences, penile reflexes can occur despite complete transections of the spinal cord, as demonstrated by the reviewed animal studies on spinalization and human studies on spinal cord injury. Neurophysiological and neuropharmacological substrates of the male sexual responses will be discussed in this review, starting with the spinal mediation of erection and its underlying mechanism with nitric oxide (NO), followed by the description of the ejaculation process, its neural mediation and its coordination by the spinal generator of ejaculation (SGE), followed by the occurrence of climax as a multisegmental sympathetic reflex discharge. Brain modulation of these reflexes will be discussed through neurophysiological evidence involving structures such as the medial preoptic area of hypothalamus (MPOA), the paraventricular nucleus (PVN), the periaqueductal gray (PAG), and the nucleus para-gigantocellularis (nPGI), and through neuropharmacological evidence involving neurotransmitters such as serotonin (5-HT), dopamine and oxytocin. The pharmacological developments based on these mechanisms to treat male sexual dysfunctions will complete this review, including phosphodiesterase (PDE-5) inhibitors and intracavernous injections (ICI) for the treatment of erectile dysfunctions (ED), selective serotonin reuptake inhibitor (SSRI) for the treatment of premature ejaculation, and cholinesterase inhibitors as well as alpha adrenergic drugs for the treatment of anejaculation and retrograde ejaculation. Evidence from spinal cord injured studies will be highlighted upon each step.

Dynamics of cortico-subcortical cross-modal operations involved in audio-visual object detection in humans.

PubMed

Fort, Alexandra; Delpuech, Claude; Pernier, Jacques; Giard, Marie-Hélène

2002-10-01

Very recently, a number of neuroimaging studies in humans have begun to investigate the question of how the brain integrates information from different sensory modalities to form unified percepts. Already, intermodal neural processing appears to depend on the modalities of inputs or the nature (speech/non-speech) of information to be combined. Yet, the variety of paradigms, stimuli and technics used make it difficult to understand the relationships between the factors operating at the perceptual level and the underlying physiological processes. In a previous experiment, we used event-related potentials to describe the spatio-temporal organization of audio-visual interactions during a bimodal object recognition task. Here we examined the network of cross-modal interactions involved in simple detection of the same objects. The objects were defined either by unimodal auditory or visual features alone, or by the combination of the two features. As expected, subjects detected bimodal stimuli more rapidly than either unimodal stimuli. Combined analysis of potentials, scalp current densities and dipole modeling revealed several interaction patterns within the first 200 micro s post-stimulus: in occipito-parietal visual areas (45-85 micro s), in deep brain structures, possibly the superior colliculus (105-140 micro s), and in right temporo-frontal regions (170-185 micro s). These interactions differed from those found during object identification in sensory-specific areas and possibly in the superior colliculus, indicating that the neural operations governing multisensory integration depend crucially on the nature of the perceptual processes involved.

The amygdala and decision-making.

PubMed

Gupta, Rupa; Koscik, Timothy R; Bechara, Antoine; Tranel, Daniel

2011-03-01

Decision-making is a complex process that requires the orchestration of multiple neural systems. For example, decision-making is believed to involve areas of the brain involved in emotion (e.g., amygdala, ventromedial prefrontal cortex) and memory (e.g., hippocampus, dorsolateral prefrontal cortex). In this article, we will present findings related to the amygdala's role in decision-making, and differentiate the contributions of the amygdala from those of other structurally and functionally connected neural regions. Decades of research have shown that the amygdala is involved in associating a stimulus with its emotional value. This tradition has been extended in newer work, which has shown that the amygdala is especially important for decision-making, by triggering autonomic responses to emotional stimuli, including monetary reward and punishment. Patients with amygdala damage lack these autonomic responses to reward and punishment, and consequently, cannot utilize "somatic marker" type cues to guide future decision-making. Studies using laboratory decision-making tests have found deficient decision-making in patients with bilateral amygdala damage, which resembles their real-world difficulties with decision-making. Additionally, we have found evidence for an interaction between sex and laterality of amygdala functioning, such that unilateral damage to the right amygdala results in greater deficits in decision-making and social behavior in men, while left amygdala damage seems to be more detrimental for women. We have posited that the amygdala is part of an "impulsive," habit type system that triggers emotional responses to immediate outcomes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Culture Wires the Brain: A Cognitive Neuroscience Perspective

PubMed Central

Park, Denise C.; Huang, Chih-Mao

2012-01-01

There is clear evidence that sustained experiences may affect both brain structure and function. Thus, it is quite reasonable to posit that sustained exposure to a set of cultural experiences and behavioral practices will affect neural structure and function. The burgeoning field of cultural psychology has often demonstrated the subtle differences in the way individuals process information—differences that appear to be a product of cultural experiences. We review evidence that the collectivistic and individualistic biases of East Asian and Western cultures, respectively, affect neural structure and function. We conclude that there is limited evidence that cultural experiences affect brain structure and considerably more evidence that neural function is affected by culture, particularly activations in ventral visual cortex—areas associated with perceptual processing. PMID:22866061

Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

PubMed

Aguiar, Manuela A D; Dias, Ana Paula S; Ferreira, Flora

2017-01-01

We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

Automatic processing of semantic relations in fMRI: neural activation during semantic priming of taxonomic and thematic categories.

PubMed

Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

2008-07-07

Most current models of knowledge organization are based on hierarchical or taxonomic categories (animals, tools). Another important organizational pattern is thematic categorization, i.e. categories held together by external relations, a unifying scene or event (car and garage). The goal of this study was to compare the neural correlates of these categories under automatic processing conditions that minimize strategic influences. We used fMRI to examine neural correlates of semantic priming for category members with a short stimulus onset asynchrony (SOA) of 200 ms as subjects performed a lexical decision task. Four experimental conditions were compared: thematically related words (car-garage); taxonomically related (car-bus); unrelated (car-spoon); non-word trials (car-derf). We found faster reaction times for related than for unrelated prime-target pairs for both thematic and taxonomic categories. However, the size of the thematic priming effect was greater than that of the taxonomic. The imaging data showed signal changes for the taxonomic priming effects in the right precuneus, postcentral gyrus, middle frontal and superior frontal gyri and thematic priming effects in the right middle frontal gyrus and anterior cingulate. The contrast of neural priming effects showed larger signal changes in the right precuneus associated with the taxonomic but not with thematic priming response. We suggest that the greater involvement of precuneus in the processing of taxonomic relations indicates their reduced salience in the knowledge structure compared to more prominent thematic relations.

Intergroup relationships do not reduce racial bias in empathic neural responses to pain.

PubMed

Contreras-Huerta, Luis Sebastian; Hielscher, Emily; Sherwell, Chase S; Rens, Natalie; Cunnington, Ross

2014-11-01

Perceiving the pain of others activates similar neural structures to those involved in the direct experience of pain, including sensory and affective-motivational areas. Empathic responses can be modulated by race, such that stronger neural activation is elicited by the perception of pain in people of the same race compared with another race. In the present study, we aimed to identify when racial bias occurs in the time course of neural empathic responses to pain. We also investigated whether group affiliation could modulate the race effect. Using the minimal group paradigm, we assigned participants to one of two mixed-race teams. We examined event-related potentials from participants when viewing members of their own and the other team receiving painful or non-painful touch. We identified a significant racial bias in early ERP components at N1 over frontal electrodes, where Painful stimuli elicited a greater negative shift relative to Non-Painful stimuli in response to own race faces only. A long latency empathic response was also found at P3, where there was significant differentiation between Painful and Non-Painful stimuli regardless of Race or Group. There was no evidence that empathy-related brain activity was modulated by minimal group manipulation. These results support a model of empathy for pain that consists of early, automatic bias towards own-race empathic responses and a later top-down cognitive evaluation that does not differentiate between races and may ultimately lead to unbiased behaviour. Copyright © 2014 Elsevier Ltd. All rights reserved.

Insect Responses to Linearly Polarized Reflections: Orphan Behaviors Without Neural Circuits

PubMed Central

Heinloth, Tanja; Uhlhorn, Juliane; Wernet, Mathias F.

2018-01-01

The e-vector orientation of linearly polarized light represents an important visual stimulus for many insects. Especially the detection of polarized skylight by many navigating insect species is known to improve their orientation skills. While great progress has been made towards describing both the anatomy and function of neural circuit elements mediating behaviors related to navigation, relatively little is known about how insects perceive non-celestial polarized light stimuli, like reflections off water, leaves, or shiny body surfaces. Work on different species suggests that these behaviors are not mediated by the “Dorsal Rim Area” (DRA), a specialized region in the dorsal periphery of the adult compound eye, where ommatidia contain highly polarization-sensitive photoreceptor cells whose receptive fields point towards the sky. So far, only few cases of polarization-sensitive photoreceptors have been described in the ventral periphery of the insect retina. Furthermore, both the structure and function of those neural circuits connecting to these photoreceptor inputs remain largely uncharacterized. Here we review the known data on non-celestial polarization vision from different insect species (dragonflies, butterflies, beetles, bugs and flies) and present three well-characterized examples for functionally specialized non-DRA detectors from different insects that seem perfectly suited for mediating such behaviors. Finally, using recent advances from circuit dissection in Drosophila melanogaster, we discuss what types of potential candidate neurons could be involved in forming the underlying neural circuitry mediating non-celestial polarization vision. PMID:29615868

The embodiment of emotion: language use during the feeling of social emotions predicts cortical somatosensory activity.

PubMed

Saxbe, Darby E; Yang, Xiao-Fei; Borofsky, Larissa A; Immordino-Yang, Mary Helen

2013-10-01

Complex social emotions involve both abstract cognitions and bodily sensations, and individuals may differ on their relative reliance on these. We hypothesized that individuals' descriptions of their feelings during a semi-structured emotion induction interview would reveal two distinct psychological styles-a more abstract, cognitive style and a more body-based, affective style-and that these would be associated with somatosensory neural activity. We examined 28 participants' open-ended verbal responses to admiration- and compassion-provoking narratives in an interview and BOLD activity to the same narratives during subsequent functional magnetic resonance imaging scanning. Consistent with hypotheses, individuals' affective and cognitive word use were stable across emotion conditions, negatively correlated and unrelated to reported emotion strength in the scanner. Greater use of affective relative to cognitive words predicted more activation in SI, SII, middle anterior cingulate cortex and insula during emotion trials. The results suggest that individuals' verbal descriptions of their feelings reflect differential recruitment of neural regions supporting physical body awareness. Although somatosensation has long been recognized as an important component of emotion processing, these results offer 'proof of concept' that individual differences in open-ended speech reflect different processing styles at the neurobiological level. This study also demonstrates SI involvement during social emotional experience.

5-HTTLPR, anxiety and gender interaction moderates right amygdala volume in healthy subjects

PubMed Central

Cerasa, Antonio; Quattrone, Aldo; Piras, Fabrizio; Mangone, Graziella; Magariello, Angela; Fagioli, Sabrina; Girardi, Paolo; Muglia, Maria; Caltagirone, Carlo

2014-01-01

Genetic variants within the serotonin transporter gene (5-HTTLPR) impact the neurobiology and risk for anxiety-related behaviours. There are also gender differences in the prevalence of anxiety-related behaviours. Although numerous studies have investigated the influence of 5-HTTLPR genotype on the neural systems involved in emotional regulation, none have investigated how these effects are modulated by gender and anxiety. We investigated this issue using two complementary region of interest-based structural neuroimaging approaches (voxel-based morphometry and Freesurfer) in 138 healthy individuals categorized into ‘no anxiety’ and ‘subclinical anxiety’ groups based on the Hamilton Rating Scale for Anxiety (HAM-A). Preliminarily, using anxiety as a continuous variable, we found a significant interaction effect of genotype by gender on anxiety. Females homozygous for the Short allele showed the highest HAM-A scores and males the lowest. In addition, a three-way significant interaction among genotype, gender and anxiety category was found for the right amygdala volume. Post hoc tests revealed that homozygous females carrying the Short variant with a subclinical anxiety condition had larger volume. The reported interaction effects demonstrate that gender strongly modulates the relationship between 5-HTTLPR genotype and subclinical expression of anxiety acting on amygdala, one region of the emotional neural network specifically involved in the anxiety-like behaviours. PMID:23986266

Rhythmic cognition in humans and animals: distinguishing meter and pulse perception

PubMed Central

Fitch, W. Tecumseh

2013-01-01

This paper outlines a cognitive and comparative perspective on human rhythmic cognition that emphasizes a key distinction between pulse perception and meter perception. Pulse perception involves the extraction of a regular pulse or “tactus” from a stream of events. Meter perception involves grouping of events into hierarchical trees with differing levels of “strength”, or perceptual prominence. I argue that metrically-structured rhythms are required to either perform or move appropriately to music (e.g., to dance). Rhythms, from this metrical perspective, constitute “trees in time.” Rhythmic syntax represents a neglected form of musical syntax, and warrants more thorough neuroscientific investigation. The recent literature on animal entrainment clearly demonstrates the capacity to extract the pulse from rhythmic music, and to entrain periodic movements to this pulse, in several parrot species and a California sea lion, and a more limited ability to do so in one chimpanzee. However, the ability of these or other species to infer hierarchical rhythmic trees remains, for the most part, unexplored (with some apparent negative results from macaques). The results from this animal comparative research, combined with new methods to explore rhythmic cognition neurally, provide exciting new routes for understanding not just rhythmic cognition, but hierarchical cognition more generally, from a biological and neural perspective. PMID:24198765

Adaptive fuzzy system for 3-D vision

NASA Technical Reports Server (NTRS)

Mitra, Sunanda

1993-01-01

An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

The embodiment of emotion: language use during the feeling of social emotions predicts cortical somatosensory activity

PubMed Central

Saxbe, Darby E.; Yang, Xiao-Fei; Borofsky, Larissa A.

2013-01-01

Complex social emotions involve both abstract cognitions and bodily sensations, and individuals may differ on their relative reliance on these. We hypothesized that individuals’ descriptions of their feelings during a semi-structured emotion induction interview would reveal two distinct psychological styles—a more abstract, cognitive style and a more body-based, affective style—and that these would be associated with somatosensory neural activity. We examined 28 participants’ open-ended verbal responses to admiration- and compassion-provoking narratives in an interview and BOLD activity to the same narratives during subsequent functional magnetic resonance imaging scanning. Consistent with hypotheses, individuals’ affective and cognitive word use were stable across emotion conditions, negatively correlated and unrelated to reported emotion strength in the scanner. Greater use of affective relative to cognitive words predicted more activation in SI, SII, middle anterior cingulate cortex and insula during emotion trials. The results suggest that individuals’ verbal descriptions of their feelings reflect differential recruitment of neural regions supporting physical body awareness. Although somatosensation has long been recognized as an important component of emotion processing, these results offer ‘proof of concept’ that individual differences in open-ended speech reflect different processing styles at the neurobiological level. This study also demonstrates SI involvement during social emotional experience. PMID:22798396

Neural predictors of individual differences in response to math tutoring in primary-grade school children

PubMed Central

Supekar, Kaustubh; Swigart, Anna G.; Tenison, Caitlin; Jolles, Dietsje D.; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2013-01-01

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8–9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures. PMID:23630286

Neural predictors of individual differences in response to math tutoring in primary-grade school children.

PubMed

Supekar, Kaustubh; Swigart, Anna G; Tenison, Caitlin; Jolles, Dietsje D; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2013-05-14

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8-9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures.

Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations

PubMed Central

Safavynia, Seyed A.

2012-01-01

Recent evidence suggests that complex spatiotemporal patterns of muscle activity can be explained with a low-dimensional set of muscle synergies or M-modes. While it is clear that both spatial and temporal aspects of muscle coordination may be low dimensional, constraints on spatial versus temporal features of muscle coordination likely involve different neural control mechanisms. We hypothesized that the low-dimensional spatial and temporal features of muscle coordination are independent of each other. We further hypothesized that in reactive feedback tasks, spatially fixed muscle coordination patterns—or muscle synergies—are hierarchically recruited via time-varying neural commands based on delayed task-level feedback. We explicitly compared the ability of spatially fixed (SF) versus temporally fixed (TF) muscle synergies to reconstruct the entire time course of muscle activity during postural responses to anterior-posterior support-surface translations. While both SF and TF muscle synergies could account for EMG variability in a postural task, SF muscle synergies produced more consistent and physiologically interpretable results than TF muscle synergies during postural responses to perturbations. Moreover, a majority of SF muscle synergies were consistent in structure when extracted from epochs throughout postural responses. Temporal patterns of SF muscle synergy recruitment were well-reconstructed by delayed feedback of center of mass (CoM) kinematics and reproduced EMG activity of multiple muscles. Consistent with the idea that independent and hierarchical low-dimensional neural control structures define spatial and temporal patterns of muscle activity, our results suggest that CoM kinematics are a task variable used to recruit SF muscle synergies for feedback control of balance. PMID:21957219

Neuronal cell fate specification in Drosophila.

PubMed

Jan, Y N; Jan, L Y

1994-02-01

Recent work indicates that the Drosophila nervous system develops in a progressive process of cell fate specification. Expression of specific proneural genes in clusters of cells (the proneural clusters) in the cellular blastoderm endows these cells with the potential to form certain types of neural precursors. Intercellular interactions that involve both proneural genes and neurogenic genes then allow the neural precursors to be singled out from the proneural clusters. Expression of neural precursor genes in all neural precursors is likely to account for the universal aspects of neuronal differentiation, such as axonal outgrowth. Selective expression of certain neuronal-type selector genes further specifies the type of neuron(s) that a neural precursor will produce.

Distinct neural substrates for visual short-term memory of actions.

PubMed

Cai, Ying; Urgolites, Zhisen; Wood, Justin; Chen, Chuansheng; Li, Siyao; Chen, Antao; Xue, Gui

2018-06-26

Fundamental theories of human cognition have long posited that the short-term maintenance of actions is supported by one of the "core knowledge" systems of human visual cognition, yet its neural substrates are still not well understood. In particular, it is unclear whether the visual short-term memory (VSTM) of actions has distinct neural substrates or, as proposed by the spatio-object architecture of VSTM, shares them with VSTM of objects and spatial locations. In two experiments, we tested these two competing hypotheses by directly contrasting the neural substrates for VSTM of actions with those for objects and locations. Our results showed that the bilateral middle temporal cortex (MT) was specifically involved in VSTM of actions because its activation and its functional connectivity with the frontal-parietal network (FPN) were only modulated by the memory load of actions, but not by that of objects/agents or locations. Moreover, the brain regions involved in the maintenance of spatial location information (i.e., superior parietal lobule, SPL) was also recruited during the maintenance of actions, consistent with the temporal-spatial nature of actions. Meanwhile, the frontoparietal network (FPN) was commonly involved in all types of VSTM and showed flexible functional connectivity with the domain-specific regions, depending on the current working memory tasks. Together, our results provide clear evidence for a distinct neural system for maintaining actions in VSTM, which supports the core knowledge system theory and the domain-specific and domain-general architectures of VSTM. © 2018 Wiley Periodicals, Inc.

Murine craniofacial development requires Hdac3-mediated repression of Msx gene expression

PubMed Central

Singh, Nikhil; Gupta, Mudit; Trivedi, Chinmay M.; Singh, Manvendra K.; Li, Li; Epstein, Jonathan A.

2013-01-01

Craniofacial development is characterized by reciprocal interactions between neural crest cells and neighboring cell populations of ectodermal, endodermal and mesodermal origin. Various genetic pathways play critical roles in coordinating the development of cranial structures by modulating the growth, survival and differentiation of neural crest cells. However, the regulation of these pathways, particularly at the epigenomic level, remains poorly understood. Using murine genetics, we show that neural crest cells exhibit a requirement for the class I histone deacetylase Hdac3 during craniofacial development. Mice in which Hdac3 has been conditionally deleted in neural crest demonstrate fully penetrant craniofacial abnormalities, including microcephaly, cleft secondary palate and dental hypoplasia. Consistent with these abnormalities, we observe dysregulation of cell cycle genes and increased apoptosis in neural crest structures in mutant embryos. Known regulators of cell cycle progression and apoptosis in neural crest, including Msx1, Msx2 and Bmp4, are upregulated in Hdac3-deficient cranial mesenchyme. These results suggest that Hdac3 serves as a critical regulator of craniofacial morphogenesis, in part by repressing core apoptotic pathways in cranial neural crest cells. PMID:23506836

The Laplacian spectrum of neural networks

PubMed Central

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

2014-01-01

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

Neural Correlates of Verb Argument Structure Processing

PubMed Central

Thompson, Cynthia K.; Bonakdarpour, Borna; Fix, Stephen C.; Blumenfeld, Henrike K.; Parrish, Todd B.; Gitelman, Darren R.; Mesulam, M.-Marsel

2008-01-01

Neuroimaging and lesion studies suggest that processing of word classes, such as verbs and nouns, is associated with distinct neural mechanisms. Such studies also suggest that subcategories within these broad word class categories are differentially processed in the brain. Within the class of verbs, argument structure provides one linguistic dimension that distinguishes among verb exemplars, with some requiring more complex argument structure entries than others. This study examined the neural instantiation of verbs by argument structure complexity: one-, two-, and three-argument verbs. Stimuli of each type, along with nouns and pseudowords, were presented for lexical decision using an event-related functional magnetic resonance imaging design. Results for 14 young normal participants indicated largely overlapping activation maps for verbs and nouns, with no areas of significant activation for verbs compared to nouns, or vice versa. Pseudowords also engaged neural tissue overlapping with that for both word classes, with more widespread activation noted in visual, motor, and peri-sylvian regions. Examination of verbs by argument structure revealed activation of the supramarginal and angular gyri, limited to the left hemisphere only when verbs with two obligatory arguments were compared to verbs with a single argument. However, bilateral activation was noted when both two- and three-argument verbs were compared to one-argument verbs. These findings suggest that posterior peri-sylvian regions are engaged for processing argument structure information associated with verbs, with increasing neural tissue in the inferior parietal region associated with increasing argument structure complexity. These findings are consistent with processing accounts, which suggest that these regions are crucial for semantic integration. PMID:17958479

Real-Time Adaptive Color Segmentation by Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2004-01-01

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

LKB1 signaling in cephalic neural crest cells is essential for vertebrate head development.

PubMed

Creuzet, Sophie E; Viallet, Jean P; Ghawitian, Maya; Torch, Sakina; Thélu, Jacques; Alrajeh, Moussab; Radu, Anca G; Bouvard, Daniel; Costagliola, Floriane; Borgne, Maïlys Le; Buchet-Poyau, Karine; Aznar, Nicolas; Buschlen, Sylvie; Hosoya, Hiroshi; Thibert, Chantal; Billaud, Marc

2016-10-15

Head development in vertebrates proceeds through a series of elaborate patterning mechanisms and cell-cell interactions involving cephalic neural crest cells (CNCC). These cells undergo extensive migration along stereotypical paths after their separation from the dorsal margins of the neural tube and they give rise to most of the craniofacial skeleton. Here, we report that the silencing of the LKB1 tumor suppressor affects the delamination of pre-migratory CNCC from the neural primordium as well as their polarization and survival, thus resulting in severe facial and brain defects. We further show that LKB1-mediated effects on the development of CNCC involve the sequential activation of the AMP-activated protein kinase (AMPK), the Rho-dependent kinase (ROCK) and the actin-based motor protein myosin II. Collectively, these results establish that the complex morphogenetic processes governing head formation critically depends on the activation of the LKB1 signaling network in CNCC. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural substrates of sublexical processing for spelling.

PubMed

DeMarco, Andrew T; Wilson, Stephen M; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

2017-01-01

We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural Substrates of Sublexical Processing for Spelling

PubMed Central

Wilson, Stephen M.; Rising, Kindle; Rapcsak, Steven Z.; Beeson, Pélagie M.

2016-01-01

We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. PMID:27838547

Brain machine interfaces combining microelectrode arrays with nanostructured optical biochemical sensors

NASA Astrophysics Data System (ADS)

Hajj-Hassan, Mohamad; Gonzalez, Timothy; Ghafer-Zadeh, Ebrahim; Chodavarapu, Vamsy; Musallam, Sam; Andrews, Mark

2009-02-01

Neural microelectrodes are an important component of neural prosthetic systems which assist paralyzed patients by allowing them to operate computers or robots using their neural activity. These microelectrodes are also used in clinical settings to localize the locus of seizure initiation in epilepsy or to stimulate sub-cortical structures in patients with Parkinson's disease. In neural prosthetic systems, implanted microelectrodes record the electrical potential generated by specific thoughts and relay the signals to algorithms trained to interpret these thoughts. In this paper, we describe novel elongated multi-site neural electrodes that can record electrical signals and specific neural biomarkers and that can reach depths greater than 8mm in the sulcus of non-human primates (monkeys). We hypothesize that additional signals recorded by the multimodal probes will increase the information yield when compared to standard probes that record just electropotentials. We describe integration of optical biochemical sensors with neural microelectrodes. The sensors are made using sol-gel derived xerogel thin films that encapsulate specific biomarker responsive luminophores in their nanostructured pores. The desired neural biomarkers are O2, pH, K+, and Na+ ions. As a prototype, we demonstrate direct-write patterning to create oxygen-responsive xerogel waveguide structures on the neural microelectrodes. The recording of neural biomarkers along with electrical activity could help the development of intelligent and more userfriendly neural prosthesis/brain machine interfaces as well as aid in providing answers to complex brain diseases and disorders.

Reducing neural network training time with parallel processing

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Lamarsh, William J., II

1995-01-01

Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.

Generalised Transfer Functions of Neural Networks

NASA Astrophysics Data System (ADS)

Fung, C. F.; Billings, S. A.; Zhang, H.

1997-11-01

When artificial neural networks are used to model non-linear dynamical systems, the system structure which can be extremely useful for analysis and design, is buried within the network architecture. In this paper, explicit expressions for the frequency response or generalised transfer functions of both feedforward and recurrent neural networks are derived in terms of the network weights. The derivation of the algorithm is established on the basis of the Taylor series expansion of the activation functions used in a particular neural network. This leads to a representation which is equivalent to the non-linear recursive polynomial model and enables the derivation of the transfer functions to be based on the harmonic expansion method. By mapping the neural network into the frequency domain information about the structure of the underlying non-linear system can be recovered. Numerical examples are included to demonstrate the application of the new algorithm. These examples show that the frequency response functions appear to be highly sensitive to the network topology and training, and that the time domain properties fail to reveal deficiencies in the trained network structure.

Emotional Intent Modulates The Neural Substrates Of Creativity: An fMRI Study of Emotionally Targeted Improvisation in Jazz Musicians

PubMed Central

McPherson, Malinda J.; Barrett, Frederick S.; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J.

2016-01-01

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. PMID:26725925

The Neural Basis of Typewriting: A Functional MRI Study.

PubMed

Higashiyama, Yuichi; Takeda, Katsuhiko; Someya, Yoshiaki; Kuroiwa, Yoshiyuki; Tanaka, Fumiaki

2015-01-01

To investigate the neural substrate of typewriting Japanese words and to detect the difference between the neural substrate of typewriting and handwriting, we conducted a functional magnetic resonance imaging (fMRI) study in 16 healthy volunteers. All subjects were skillful touch typists and performed five tasks: a typing task, a writing task, a reading task, and two control tasks. Three brain regions were activated during both the typing and the writing tasks: the left superior parietal lobule, the left supramarginal gyrus, and the left premotor cortex close to Exner's area. Although typing and writing involved common brain regions, direct comparison between the typing and the writing task revealed greater left posteromedial intraparietal cortex activation in the typing task. In addition, activity in the left premotor cortex was more rostral in the typing task than in the writing task. These findings suggest that, although the brain circuits involved in Japanese typewriting are almost the same as those involved in handwriting, there are brain regions that are specific for typewriting.

The Neural Basis of Typewriting: A Functional MRI Study

PubMed Central

Higashiyama, Yuichi; Takeda, Katsuhiko; Someya, Yoshiaki; Kuroiwa, Yoshiyuki; Tanaka, Fumiaki

2015-01-01

To investigate the neural substrate of typewriting Japanese words and to detect the difference between the neural substrate of typewriting and handwriting, we conducted a functional magnetic resonance imaging (fMRI) study in 16 healthy volunteers. All subjects were skillful touch typists and performed five tasks: a typing task, a writing task, a reading task, and two control tasks. Three brain regions were activated during both the typing and the writing tasks: the left superior parietal lobule, the left supramarginal gyrus, and the left premotor cortex close to Exner’s area. Although typing and writing involved common brain regions, direct comparison between the typing and the writing task revealed greater left posteromedial intraparietal cortex activation in the typing task. In addition, activity in the left premotor cortex was more rostral in the typing task than in the writing task. These findings suggest that, although the brain circuits involved in Japanese typewriting are almost the same as those involved in handwriting, there are brain regions that are specific for typewriting. PMID:26218431

Selection of neural network structure for system error correction of electro-optical tracker system with horizontal gimbal

NASA Astrophysics Data System (ADS)

Liu, Xing-fa; Cen, Ming

2007-12-01

Neural Network system error correction method is more precise than lest square system error correction method and spheric harmonics function system error correction method. The accuracy of neural network system error correction method is mainly related to the frame of Neural Network. Analysis and simulation prove that both BP neural network system error correction method and RBF neural network system error correction method have high correction accuracy; it is better to use RBF Network system error correction method than BP Network system error correction method for little studying stylebook considering training rate and neural network scale.

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

PubMed Central

Hétu, Sébastien; Luo, Yi; D’Ardenne, Kimberlee; Lohrenz, Terry

2017-01-01

Abstract As models of shared expectations, social norms play an essential role in our societies. Since our social environment is changing constantly, our internal models of it also need to change. In humans, there is mounting evidence that neural structures such as the insula and the ventral striatum are involved in detecting norm violation and updating internal models. However, because of methodological challenges, little is known about the possible involvement of midbrain structures in detecting norm violation and updating internal models of our norms. Here, we used high-resolution cardiac-gated functional magnetic resonance imaging and a norm adaptation paradigm in healthy adults to investigate the role of the substantia nigra/ventral tegmental area (SN/VTA) complex in tracking signals related to norm violation that can be used to update internal norms. We show that the SN/VTA codes for the norm’s variance prediction error (PE) and norm PE with spatially distinct regions coding for negative and positive norm PE. These results point to a common role played by the SN/VTA complex in supporting both simple reward-based and social decision making. PMID:28981876

Memory consolidation in humans: new evidence and opportunities

PubMed Central

Maguire, Eleanor A

2014-01-01

We are endlessly fascinated by memory; we desire to improve it and fear its loss. While it has long been recognized that brain regions such as the hippocampus are vital for supporting memories of our past experiences (autobiographical memories), we still lack fundamental knowledge about the mechanisms involved. This is because the study of specific neural signatures of autobiographical memories in vivo in humans presents a significant challenge. However, recent developments in high-resolution structural and functional magnetic resonance imaging coupled with advanced analytical methods now permit access to the neural substrates of memory representations that has hitherto been precluded in humans. Here, I describe how the application of ‘decoding’ techniques to brain-imaging data is beginning to disclose how individual autobiographical memory representations evolve over time, deepening our understanding of systems-level consolidation. In particular, this prompts new questions about the roles of the hippocampus and ventromedial prefrontal cortex and offers new opportunities to interrogate the elusive memory trace that has for so long confounded neuroscientists. PMID:24414174

Loss of autophagy in pro-opiomelanocortin neurons perturbs axon growth and causes metabolic dysregulation.

PubMed

Coupé, Bérengère; Ishii, Yuko; Dietrich, Marcelo O; Komatsu, Masaaki; Horvath, Tamas L; Bouret, Sebastien G

2012-02-08

The hypothalamic melanocortin system, which includes neurons that produce pro-opiomelanocortin (POMC)-derived peptides, is a major negative regulator of energy balance. POMC neurons begin to acquire their unique properties during neonatal life. The formation of functional neural systems requires massive cytoplasmic remodeling that may involve autophagy, an important intracellular mechanism for the degradation of damaged proteins and organelles. Here we investigated the functional and structural effects of the deletion of an essential autophagy gene, Atg7, in POMC neurons. Lack of Atg7 in POMC neurons caused higher postweaning body weight, increased adiposity, and glucose intolerance. These metabolic impairments were associated with an age-dependent accumulation of ubiquitin/p62-positive aggregates in the hypothalamus and a disruption in the maturation of POMC-containing axonal projections. Together, these data provide direct genetic evidence that Atg7 in POMC neurons is required for normal metabolic regulation and neural development, and they implicate hypothalamic autophagy deficiency in the pathogenesis of obesity. Copyright © 2012 Elsevier Inc. All rights reserved.

Neural networks engaged in short-term memory rehearsal are disrupted by irrelevant speech in human subjects.

PubMed

Kopp, Franziska; Schröger, Erich; Lipka, Sigrid

2004-01-02

Rehearsal mechanisms in human short-term memory are increasingly understood in the light of both behavioural and neuroanatomical findings. However, little is known about the cooperation of participating brain structures and how such cooperations are affected when memory performance is disrupted. In this paper we use EEG coherence as a measure of synchronization to investigate rehearsal processes and their disruption by irrelevant speech in a delayed serial recall paradigm. Fronto-central and fronto-parietal theta (4-7.5 Hz), beta (13-20 Hz), and gamma (35-47 Hz) synchronizations are shown to be involved in our short-term memory task. Moreover, the impairment in serial recall due to irrelevant speech was preceded by a reduction of gamma band coherence. Results suggest that the irrelevant speech effect has its neural basis in the disruption of left-lateralized fronto-central networks. This stresses the importance of gamma band activity for short-term memory operations.

The functional neuroanatomy of object agnosia: a case study.

PubMed

Konen, Christina S; Behrmann, Marlene; Nishimura, Mayu; Kastner, Sabine

2011-07-14

Cortical reorganization of visual and object representations following neural injury was examined using fMRI and behavioral investigations. We probed the visual responsivity of the ventral visual cortex of an agnosic patient who was impaired at object recognition following a lesion to the right lateral fusiform gyrus. In both hemispheres, retinotopic mapping revealed typical topographic organization and visual activation of early visual cortex. However, visual responses, object-related, and -selective responses were reduced in regions immediately surrounding the lesion in the right hemisphere, and also, surprisingly, in corresponding locations in the structurally intact left hemisphere. In contrast, hV4 of the right hemisphere showed expanded response properties. These findings indicate that the right lateral fusiform gyrus is critically involved in object recognition and that an impairment to this region has widespread consequences for remote parts of cortex. Finally, functional neural plasticity is possible even when a cortical lesion is sustained in adulthood. Copyright © 2011 Elsevier Inc. All rights reserved.

Loss of Autophagy in Proopiomelanocortin Neurons Perturbs Axon Growth and Causes Metabolic Dysregulation

PubMed Central

Coupé, Bérengère; Ishii, Yuko; Dietrich, Marcelo O; Komatsu, Masaaki; Horvath, Tamas L.; Bouret, Sebastien G.

2012-01-01

Summary The hypothalamic melanocortin system, which includes neurons that produce proopiomelanocortin (POMC)-derived peptides, is a major negative regulator of energy balance. POMC neurons begin to acquire their unique properties during neonatal life. The formation of functional neural systems requires massive cytoplasmic remodeling that may involve autophagy, an important intracellular mechanism for the degradation of damaged proteins and organelles. Here we investigated the functional and structural effects of the deletion of an essential autophagy gene, Atg7, in POMC neurons. Lack of Atg7 in POMC neurons caused higher post-weaning body weight, increased adiposity, and glucose intolerance. These metabolic impairments were associated with an age-dependant accumulation of ubiquitin/p62-positive aggregates in the hypothalamus and a disruption in the maturation of POMC-containing axonal projections. Together, these data provide direct genetic evidence that Atg7 in POMC neurons is required for normal metabolic regulation and neural development, and they implicate hypothalamic autophagy deficiency in the pathogenesis of obesity. PMID:22285542

Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

PubMed

Lopopolo, Alessandro; Frank, Stefan L; van den Bosch, Antal; Willems, Roel M

2017-01-01

Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.

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.

Ion track based tunable device as humidity sensor: a neural network approach

NASA Astrophysics Data System (ADS)

Sharma, Mamta; Sharma, Anuradha; Bhattacherjee, Vandana

2013-01-01

Artificial Neural Network (ANN) has been applied in statistical model development, adaptive control system, pattern recognition in data mining, and decision making under uncertainty. The nonlinear dependence of any sensor output on the input physical variable has been the motivation for many researchers to attempt unconventional modeling techniques such as neural networks and other machine learning approaches. Artificial neural network (ANN) is a computational tool inspired by the network of neurons in biological nervous system. It is a network consisting of arrays of artificial neurons linked together with different weights of connection. The states of the neurons as well as the weights of connections among them evolve according to certain learning rules.. In the present work we focus on the category of sensors which respond to electrical property changes such as impedance or capacitance. Recently, sensor materials have been embedded in etched tracks due to their nanometric dimensions and high aspect ratio which give high surface area available for exposure to sensing material. Various materials can be used for this purpose to probe physical (light intensity, temperature etc.), chemical (humidity, ammonia gas, alcohol etc.) or biological (germs, hormones etc.) parameters. The present work involves the application of TEMPOS structures as humidity sensors. The sample to be studied was prepared using the polymer electrolyte (PEO/NH4ClO4) with CdS nano-particles dispersed in the polymer electrolyte. In the present research we have attempted to correlate the combined effects of voltage and frequency on impedance of humidity sensors using a neural network model and results have indicated that the mean absolute error of the ANN Model for the training data was 3.95% while for the validation data it was 4.65%. The corresponding values for the LR model were 8.28% and 8.35% respectively. It was also demonstrated the percentage improvement of the ANN Model with respect to the linear regression model. This demonstrates the suitability of neural networks to perform such modeling.

Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network.

PubMed

Wolf, Dhana; Rekittke, Linn-Marlen; Mittelberg, Irene; Klasen, Martin; Mathiak, Klaus

2017-01-01

Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language) relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake) or less so (e.g., self-grooming). We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area) and the posterior superior temporal gyrus (pSTG, Wernicke's area) and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI) experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC) in fMRI even without involving a stimulus (model-free analysis). The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations). Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension.

Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network

PubMed Central

Wolf, Dhana; Rekittke, Linn-Marlen; Mittelberg, Irene; Klasen, Martin; Mathiak, Klaus

2017-01-01

Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language) relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake) or less so (e.g., self-grooming). We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area) and the posterior superior temporal gyrus (pSTG, Wernicke's area) and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI) experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC) in fMRI even without involving a stimulus (model-free analysis). The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations). Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension. PMID:29249945

c-Fos expression in the paternal mouse brain induced by communicative interaction with maternal mates.

PubMed

Zhong, Jing; Liang, Mingkun; Akther, Shirin; Higashida, Chiharu; Tsuji, Takahiro; Higashida, Haruhiro

2014-09-11

Appropriate parental care by fathers greatly facilitates health in human family life. Much less is known from animal studies regarding the factors and neural circuitry that affect paternal behavior compared with those affecting maternal behavior. We recently reported that ICR mouse sires displayed maternal-like retrieval behavior when they were separated from pups and caged with their mates (co-housing) because the sires receive communicative interactions via ultrasonic and pheromone signals from the dams. We investigated the brain structures involved in regulating this activity by quantifying c-Fos-immunoreactive cells as neuronal activation markers in the neural pathway of male parental behavior. c-Fos expression in the medial preoptic area (mPOA) was significantly higher in sires that exhibited retrieval behavior (retrievers) than those with no such behavior (non-retrievers). Identical increased expression was found in the mPOA region in the retrievers stimulated by ultrasonic vocalizations or pheromones from their mates. Such increases in expression were not observed in the ventral tegmental area (VTA), nucleus accumbens (NAcc) or ventral palladium (VP). On the following day that we identified the families of the retrievers or non-retrievers, c-Fos expression in neuronal subsets in the mPOA, VTA, NAcc and VP was much higher in the retriever sires when they isolated together with their mates in new cages. This difference was not observed in the singly isolated retriever sires in new cages. The non-retriever sires did not display expression changes in the four brain regions that were assessed. The mPOA neurons appeared to be activated by direct communicative interactions with mate dams, including ultrasonic vocalizations and pheromones. The mPOA-VTA-NAcc-VP neural circuit appears to be involved in paternal retrieval behavior.

Intranasal oxytocin, but not vasopressin, augments neural responses to toddlers in human fathers.

PubMed

Li, Ting; Chen, Xu; Mascaro, Jennifer; Haroon, Ebrahim; Rilling, James K

2017-07-01

This study investigates paternal brain function with the hope of better understanding the neural basis for variation in caregiving involvement among men. The neuropeptides oxytocin (OT) and vasopressin (AVP) are implicated in paternal caregiving in humans and other species. In a double-blind, placebo-controlled, within-subject pharmaco-functional MRI experiment, we randomized 30 fathers of 1-2year old children to receive either 24IU intranasal OT before one scan and placebo before the other scan (n=15) or 20IU intranasal AVP before one scan and placebo before the other scan (n=15). Brain function was measured with fMRI as the fathers viewed pictures of their children, unknown children and unknown adults, and as they listened to unknown infant cry stimuli. Intranasal OT, but not AVP, significantly increased the BOLD fMRI response to viewing pictures of own children within the caudate nucleus, a target of midbrain dopamine projections, as well as the dorsal anterior cingulate (dACC) and visual cortex, suggesting that intranasal oxytocin augments activation in brain regions involved in reward, empathy and attention in human fathers. OT effects also varied as a function of order of administration such that when OT was given before placebo, it increased activation within several reward-related structures (substantia nigra, ventral tegmental area, putamen) more than when it was given after placebo. Neither OT nor AVP had significant main effects on the neural response to cries. Our findings suggest that the hormonal changes associated with the transition to fatherhood are likely to facilitate increased approach motivation and empathy for children, and call for future research that evaluates the potential of OT to normalize deficits in paternal motivation, as might be found among men suffering from post-partum depression. Copyright © 2017 Elsevier Inc. All rights reserved.

An equal start: absence of group differences in cognitive, social, and neural measures prior to music or sports training in children.

PubMed

Habibi, Assal; Ilari, Beatriz; Crimi, Kevin; Metke, Michael; Kaplan, Jonas T; Joshi, Anand A; Leahy, Richard M; Shattuck, David W; Choi, So Y; Haldar, Justin P; Ficek, Bronte; Damasio, Antonio; Damasio, Hanna

2014-01-01

Several studies comparing adult musicians and non-musicians have provided compelling evidence for functional and anatomical differences in the brain systems engaged by musical training. It is not known, however, whether those differences result from long-term musical training or from pre-existing traits favoring musicality. In an attempt to begin addressing this question, we have launched a longitudinal investigation of the effects of childhood music training on cognitive, social and neural development. We compared a group of 6- to 7-year old children at the start of intense after-school musical training, with two groups of children: one involved in high intensity sports training but not musical training, another not involved in any systematic training. All children were tested with a comprehensive battery of cognitive, motor, musical, emotional, and social assessments and underwent magnetic resonance imaging and electroencephalography. Our first objective was to determine whether children who participate in musical training were different, prior to training, from children in the control groups in terms of cognitive, motor, musical, emotional, and social behavior measures as well as in structural and functional brain measures. Our second objective was to determine whether musical skills, as measured by a music perception assessment prior to training, correlates with emotional and social outcome measures that have been shown to be associated with musical training. We found no neural, cognitive, motor, emotional, or social differences among the three groups. In addition, there was no correlation between music perception skills and any of the social or emotional measures. These results provide a baseline for an ongoing longitudinal investigation of the effects of music training.

An equal start: absence of group differences in cognitive, social, and neural measures prior to music or sports training in children

PubMed Central

Habibi, Assal; Ilari, Beatriz; Crimi, Kevin; Metke, Michael; Kaplan, Jonas T.; Joshi, Anand A.; Leahy, Richard M.; Shattuck, David W.; Choi, So Y.; Haldar, Justin P.; Ficek, Bronte; Damasio, Antonio; Damasio, Hanna

2014-01-01

Several studies comparing adult musicians and non-musicians have provided compelling evidence for functional and anatomical differences in the brain systems engaged by musical training. It is not known, however, whether those differences result from long-term musical training or from pre-existing traits favoring musicality. In an attempt to begin addressing this question, we have launched a longitudinal investigation of the effects of childhood music training on cognitive, social and neural development. We compared a group of 6- to 7-year old children at the start of intense after-school musical training, with two groups of children: one involved in high intensity sports training but not musical training, another not involved in any systematic training. All children were tested with a comprehensive battery of cognitive, motor, musical, emotional, and social assessments and underwent magnetic resonance imaging and electroencephalography. Our first objective was to determine whether children who participate in musical training were different, prior to training, from children in the control groups in terms of cognitive, motor, musical, emotional, and social behavior measures as well as in structural and functional brain measures. Our second objective was to determine whether musical skills, as measured by a music perception assessment prior to training, correlates with emotional and social outcome measures that have been shown to be associated with musical training. We found no neural, cognitive, motor, emotional, or social differences among the three groups. In addition, there was no correlation between music perception skills and any of the social or emotional measures. These results provide a baseline for an ongoing longitudinal investigation of the effects of music training. PMID:25249961

Limbic Justice—Amygdala Involvement in Immediate Rejection in the Ultimatum Game

PubMed Central

Fransson, Peter; Petrovic, Predrag; Johannesson, Magnus; Ingvar, Martin

2011-01-01

Imaging studies have revealed a putative neural account of emotional bias in decision making. However, it has been difficult in previous studies to identify the causal role of the different sub-regions involved in decision making. The Ultimatum Game (UG) is a game to study the punishment of norm-violating behavior. In a previous influential paper on UG it was suggested that frontal insular cortex has a pivotal role in the rejection response. This view has not been reconciled with a vast literature that attributes a crucial role in emotional decision making to a subcortical structure (i.e., amygdala). In this study we propose an anatomy-informed model that may join these views. We also present a design that detects the functional anatomical response to unfair proposals in a subcortical network that mediates rapid reactive responses. We used a functional MRI paradigm to study the early components of decision making and challenged our paradigm with the introduction of a pharmacological intervention to perturb the elicited behavioral and neural response. Benzodiazepine treatment decreased the rejection rate (from 37.6% to 19.0%) concomitantly with a diminished amygdala response to unfair proposals, and this in spite of an unchanged feeling of unfairness and unchanged insular response. In the control group, rejection was directly linked to an increase in amygdala activity. These results allow a functional anatomical detection of the early neural components of rejection associated with the initial reactive emotional response. Thus, the act of immediate rejection seems to be mediated by the limbic system and is not solely driven by cortical processes, as previously suggested. Our results also prompt an ethical discussion as we demonstrated that a commonly used drug influences core functions in the human brain that underlie individual autonomy and economic decision making. PMID:21559322

What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic PPA

PubMed Central

Wilson, Stephen M.; DeMarco, Andrew T.; Henry, Maya L.; Gesierich, Benno; Babiak, Miranda; Mandelli, Maria Luisa; Miller, Bruce L.; Gorno-Tempini, Maria Luisa

2014-01-01

Neuroimaging and neuropsychological studies have implicated the anterior temporal lobe (ATL) in sentence-level processing, with syntactic structure-building and/or combinatorial semantic processing suggested as possible roles. A potential challenge to the view that the ATL is involved in syntactic aspects of sentence processing comes from the clinical syndrome of semantic variant primary progressive aphasia (semantic PPA, also known as semantic dementia). In semantic PPA, bilateral neurodegeneration of the anterior temporal lobes is associated with profound lexical semantic deficits, yet syntax is strikingly spared. The goal of this study was to investigate the neural correlates of syntactic processing in semantic PPA, in order to determine which regions normally involved in syntactic processing are damaged in semantic PPA, and whether spared syntactic processing depends on preserved functionality of intact regions, preserved functionality of atrophic regions, or compensatory functional reorganization. We scanned 20 individuals with semantic PPA and 24 age-matched controls using structural and functional MRI. Participants performed a sentence comprehension task that emphasized syntactic processing and minimized lexical semantic demands. We found that in controls, left inferior frontal and left posterior temporal regions were modulated by syntactic processing, while anterior temporal regions were not significantly modulated. In the semantic PPA group, atrophy was most severe in the anterior temporal lobes, but extended to the posterior temporal regions involved in syntactic processing. Functional activity for syntactic processing was broadly similar in patients and controls; in particular, whole-brain analyses revealed no significant differences between patients and controls in the regions modulated by syntactic processing. The atrophic left anterior temporal lobe did show abnormal functionality in semantic PPA patients, however this took the unexpected form of a failure to deactivate. Taken together, our findings indicate that spared syntactic processing in semantic PPA depends on preserved functionality of structurally intact left frontal regions and moderately atrophic left posterior temporal regions, but no functional reorganization was apparent as a consequence of anterior temporal atrophy and dysfunction. These results suggest that the role of the anterior temporal lobe in sentence processing is less likely to relate to syntactic structure-building, and more likely to relate to higher level processes such as combinatorial semantic processing. PMID:24345172

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

Novel four-sided neural probe fabricated by a thermal lamination process of polymer films.

PubMed

Shin, Soowon; Kim, Jae-Hyun; Jeong, Joonsoo; Gwon, Tae Mok; Lee, Seung-Hee; Kim, Sung June

2017-02-15

Ideally, neural probes should have channels with a three-dimensional (3-D) configuration to record the activities of 3-D neural circuits. Many types of 3-D neural probes have been developed; however, most of them were designed as an array of multiple shanks with electrodes located along one side of the shanks. We developed a novel liquid crystal polymer (LCP)-based neural probe with four-sided electrodes. This probe has electrodes on four sides of the shank, i.e., the front, back and two sidewalls. To generate the proposed configuration of the electrodes, we used a thermal lamination process involving LCP films and laser micromachining. The proposed novel four-sided neural probe, was used to successfully perform in vivo multichannel neural recording in the mouse primary somatosensory cortex. The multichannel neural recording showed that the proposed four-sided neural probe can record spiking activities from a more diverse neuronal population than single-sided probes. This was confirmed by a pairwise Pearson correlation coefficient (Pearson's r) analysis and a cross-correlation analysis. The developed four-sided neural probe can be used to record various signals from a complex neural network. Copyright © 2016 Elsevier B.V. All rights reserved.

Optoelectronic Inner-Product Neural Associative Memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1993-01-01

Optoelectronic apparatus acts as artificial neural network performing associative recall of binary images. Recall process is iterative one involving optical computation of inner products between binary input vector and one or more reference binary vectors in memory. Inner-product method requires far less memory space than matrix-vector method.

Modeling Developmental Transitions in Adaptive Resonance Theory

ERIC Educational Resources Information Center

Raijmakers, Maartje E. J.; Molenaar, Peter C. M.

2004-01-01

Neural networks are applied to a theoretical subject in developmental psychology: modeling developmental transitions. Two issues that are involved will be discussed: discontinuities and acquiring qualitatively new knowledge. We will argue that by the appearance of a bifurcation, a neural network can show discontinuities and may acquire…

Neural Architecture of Selective Stopping Strategies: Distinct Brain Activity Patterns Are Associated with Attentional Capture But Not with Outright Stopping.

PubMed

Sebastian, Alexandra; Rössler, Kora; Wibral, Michael; Mobascher, Arian; Lieb, Klaus; Jung, Patrick; Tüscher, Oliver

2017-10-04

In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy). Alternatively, the discrimination process of the critical signal (stop vs attentional capture signal) may interact with the go process (dependent discriminate then stop strategy). Those different strategies might differentially involve attention- and stopping-related processes that might be implemented by divergent neural networks. This should lead to divergent activation patterns and, if disregarded, interfere with analyses in neuroimaging studies. To clarify this crucial issue, we studied 87 human participants of both sexes during a stimulus-selective stop-signal task and performed strategy-dependent functional magnetic resonance imaging analyses. We found that, regardless of the strategy applied, outright stopping displayed indistinguishable brain activation patterns. However, during attentional capture different strategies resulted in divergent neural activation patterns with variable activation of right IFJ and bilateral VLPFC. In conclusion, the neural network involved in outright stopping is ubiquitous and independent of strategy, while different strategies impact on attention-related processes and underlying neural network usage. Strategic differences should therefore be taken into account particularly when studying attention-related processes in stimulus-selective stopping. SIGNIFICANCE STATEMENT Dissociating inhibition from attention has been a major challenge for the cognitive neuroscience of executive functions. Selective stopping tasks have been instrumental in addressing this question. However, recent theoretical, cognitive and behavioral research suggests that different strategies are applied in successful execution of the task. The underlying strategy-dependent neural networks might differ substantially. Here, we show evidence that, regardless of the strategy used, the neural network involved in outright stopping is ubiquitous. However, significant differences can only be found in the attention-related processes underlying those different strategies. Thus, when studying attentional processing of salient stop signals, strategic differences should be considered. In contrast, the neural networks implementing outright stopping seem less or not at all affected by strategic differences. Copyright © 2017 the authors 0270-6474/17/379786-10$15.00/0.

Machine learning prediction for classification of outcomes in local minimisation

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-01-01

Machine learning schemes are employed to predict which local minimum will result from local energy minimisation of random starting configurations for a triatomic cluster. The input data consists of structural information at one or more of the configurations in optimisation sequences that converge to one of four distinct local minima. The ability to make reliable predictions, in terms of the energy or other properties of interest, could save significant computational resources in sampling procedures that involve systematic geometry optimisation. Results are compared for two energy minimisation schemes, and for neural network and quadratic functions of the inputs.

Progressive and regressive developmental changes in neural substrates for face processing: Testing specific predictions of the Interactive Specialization account

PubMed Central

Joseph, Jane E.; Gathers, Ann D.; Bhatt, Ramesh S.

2010-01-01

Face processing undergoes a fairly protracted developmental time course but the neural underpinnings are not well understood. Prior fMRI studies have only examined progressive changes (i.e., increases in specialization in certain regions with age), which would be predicted by both the Interactive Specialization (IS) and maturational theories of neural development. To differentiate between these accounts, the present study also examined regressive changes (i.e., decreases in specialization in certain regions with age), which is predicted by the IS but not maturational account. The fMRI results show that both progressive and regressive changes occur, consistent with IS. Progressive changes mostly occurred in occipital-fusiform and inferior frontal cortex whereas regressive changes largely emerged in parietal and lateral temporal cortices. Moreover, inconsistent with the maturational account, all of the regions involved in face viewing in adults were active in children, with some regions already specialized for face processing by 5 years of age and other regions activated in children but not specifically for faces. Thus, neurodevelopment of face processing involves dynamic interactions among brain regions including age-related increases and decreases in specialization and the involvement of different regions at different ages. These results are more consistent with IS than maturational models of neural development. PMID:21399706

Identifying a Network of Brain Regions Involved in Aversion-Related Processing: A Cross-Species Translational Investigation

PubMed Central

Hayes, Dave J.; Northoff, Georg

2011-01-01

The ability to detect and respond appropriately to aversive stimuli is essential for all organisms, from fruit flies to humans. This suggests the existence of a core neural network which mediates aversion-related processing. Human imaging studies on aversion have highlighted the involvement of various cortical regions, such as the prefrontal cortex, while animal studies have focused largely on subcortical regions like the periaqueductal gray and hypothalamus. However, whether and how these regions form a core neural network of aversion remains unclear. To help determine this, a translational cross-species investigation in humans (i.e., meta-analysis) and other animals (i.e., systematic review of functional neuroanatomy) was performed. Our results highlighted the recruitment of the anterior cingulate cortex, the anterior insula, and the amygdala as well as other subcortical (e.g., thalamus, midbrain) and cortical (e.g., orbitofrontal) regions in both animals and humans. Importantly, involvement of these regions remained independent of sensory modality. This study provides evidence for a core neural network mediating aversion in both animals and humans. This not only contributes to our understanding of the trans-species neural correlates of aversion but may also carry important implications for psychiatric disorders where abnormal aversive behavior can often be observed. PMID:22102836

Neural systems for social cognition in Klinefelter syndrome (47,XXY): evidence from fMRI.

PubMed

van Rijn, Sophie; Swaab, Hanna; Baas, Daan; de Haan, Edward; Kahn, René S; Aleman, André

2012-08-01

Klinefelter syndrome (KS) is a chromosomal condition (47, XXY) that may help us to unravel gene-brain behavior pathways to psychopathology. The phenotype includes social cognitive impairments and increased risk for autism traits. We used functional MRI to study neural mechanisms underlying social information processing. Eighteen nonclinical controls and thirteen men with XXY were scanned during judgments of faces with regard to trustworthiness and age. While judging faces as untrustworthy in comparison to trustworthy, men with XXY displayed less activation than controls in (i) the amygdala, which plays a key role in screening information for socio-emotional significance, (ii) the insula, which plays a role in subjective emotional experience, as well as (iii) the fusiform gyrus and (iv) the superior temporal sulcus, which are both involved in the perceptual processing of faces and which were also less involved during age judgments in men with XXY. This is the first study showing that KS can be associated with reduced involvement of the neural network subserving social cognition. Studying KS may increase our understanding of the genetic and hormonal basis of neural dysfunctions contributing to abnormalities in social cognition and behavior, which are considered core abnormalities in psychiatric disorders such as autism and schizophrenia.

Socioeconomic disadvantages and neural sensitivity to infant cry: role of maternal distress.

PubMed

Kim, Pilyoung; Capistrano, Christian; Congleton, Christina

2016-10-01

Socioeconomic disadvantage such as poverty can increase distress levels, which may further make low-income mothers more vulnerable to difficulties in the transition to parenthood. However, little is known about the neurobiological processes by which poverty and maternal distress are associated with risks for adaptations to motherhood. Thus, the current study examined the associations between income and neural responses to infant cry sounds among first-time new mothers (N = 28) during the early postpartum period. Lower income was associated with reduced responses to infant cry in the medial prefrontal gyrus (involved in evaluating emotional values of stimuli), middle prefrontal gyrus (involved in affective regulation) and superior temporal gyrus (involved in sensory information processing). When examining the role of maternal distress, we found a mediating role of perceived stress, but not depressive symptoms, in the links between income and prefrontal responses to infant cry. Reduced neural responses to infant cry in the right middle frontal gyrus and superior temporal gyrus were further associated with less positive perceptions of parenting. The results demonstrate that perceived stress associated with socioeconomic disadvantages may contribute to reduced neural responses to infant cry, which is further associated with less positive perceptions of motherhood. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

A Neural Mechanism for Nonconscious Activation of Conditioned Placebo and Nocebo Responses.

PubMed

Jensen, Karin B; Kaptchuk, Ted J; Chen, Xiaoyan; Kirsch, Irving; Ingvar, Martin; Gollub, Randy L; Kong, Jian

2015-10-01

Fundamental aspects of human behavior operate outside of conscious awareness. Yet, theories of conditioned responses in humans, such as placebo and nocebo effects on pain, have a strong emphasis on conscious recognition of contextual cues that trigger the response. Here, we investigated the neural pathways involved in nonconscious activation of conditioned pain responses, using functional magnetic resonance imaging in healthy participants. Nonconscious compared with conscious activation of conditioned placebo analgesia was associated with increased activation of the orbitofrontal cortex, a structure with direct connections to affective brain regions and basic reward processing. During nonconscious nocebo, there was increased activation of the thalamus, amygdala, and hippocampus. In contrast to previous assumptions about conditioning in humans, our results show that conditioned pain responses can be elicited independently of conscious awareness and our results suggest a hierarchical activation of neural pathways for nonconscious and conscious conditioned responses. Demonstrating that the human brain has a nonconscious mechanism for responding to conditioned cues has major implications for the role of associative learning in behavioral medicine and psychiatry. Our results may also open up for novel approaches to translational animal-to-human research since human consciousness and animal cognition is an inherent paradox in all behavioral science. © The Author 2014. Published by Oxford University Press.

An fMRI comparison of neural activity associated with recognition of familiar melodies in younger and older adults

PubMed Central

Sikka, Ritu; Cuddy, Lola L.; Johnsrude, Ingrid S.; Vanstone, Ashley D.

2015-01-01

Several studies of semantic memory in non-musical domains involving recognition of items from long-term memory have shown an age-related shift from the medial temporal lobe structures to the frontal lobe. However, the effects of aging on musical semantic memory remain unexamined. We compared activation associated with recognition of familiar melodies in younger and older adults. Recognition follows successful retrieval from the musical lexicon that comprises a lifetime of learned musical phrases. We used the sparse-sampling technique in fMRI to determine the neural correlates of melody recognition by comparing activation when listening to familiar vs. unfamiliar melodies, and to identify age differences. Recognition-related cortical activation was detected in the right superior temporal, bilateral inferior and superior frontal, left middle orbitofrontal, bilateral precentral, and left supramarginal gyri. Region-of-interest analysis showed greater activation for younger adults in the left superior temporal gyrus and for older adults in the left superior frontal, left angular, and bilateral superior parietal regions. Our study provides powerful evidence for these musical memory networks due to a large sample (N = 40) that includes older adults. This study is the first to investigate the neural basis of melody recognition in older adults and to compare the findings to younger adults. PMID:26500480

Neural correlates of reward and loss sensitivity in psychopathy.

PubMed

Pujara, Maia; Motzkin, Julian C; Newman, Joseph P; Kiehl, Kent A; Koenigs, Michael

2014-06-01

Psychopathy is a personality disorder associated with callous and impulsive behavior and criminal recidivism. It has long been theorized that psychopaths have deficits in processing reward and punishment. Here, we use structural and functional magnetic resonance imaging to examine the neural correlates of reward and loss sensitivity in a group of criminal psychopaths. Forty-one adult male prison inmates (n = 18 psychopaths and n = 23 non-psychopaths) completed a functional magnetic resonance imaging task involving the gain or loss of money. Across the entire sample of participants, monetary gains elicited robust activation within the ventral striatum (VS). Although psychopaths and non-psychopaths did not significantly differ with respect to overall levels of VS response to reward vs loss, we observed significantly different correlations between VS responses and psychopathy severity within each group. Volumetric analyses of striatal subregions revealed a similar pattern of correlations, specifically for the right accumbens area within VS. In a separate sample of inmates (n = 93 psychopaths and n = 117 non-psychopaths) who completed a self-report measure of appetitive motivation, we again found that the correlation with psychopathy severity differed between groups. These convergent results offer novel insight into the neural substrates of reward and loss processing in psychopathy. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

Design and Evaluation of a Cable-Driven fMRI-Compatible Haptic Interface to Investigate Precision Grip Control

PubMed Central

Vigaru, Bogdan; Sulzer, James; Gassert, Roger

2016-01-01

Our hands and fingers are involved in almost all activities of daily living and, as such, have a disproportionately large neural representation. Functional magnetic resonance imaging investigations into the neural control of the hand have revealed great advances, but the harsh MRI environment has proven to be a challenge to devices capable of delivering a large variety of stimuli necessary for well-controlled studies. This paper presents a fMRI-compatible haptic interface to investigate the neural mechanisms underlying precision grasp control. The interface, located at the scanner bore, is controlled remotely through a shielded electromagnetic actuation system positioned at the end of the scanner bed and then through a high stiffness, low inertia cable transmission. We present the system design, taking into account requirements defined by the biomechanics and dynamics of the human hand, as well as the fMRI environment. Performance evaluation revealed a structural stiffness of 3.3 N/mm, renderable forces up to 94 N, and a position control bandwidth of at least 19 Hz. MRI-compatibility tests showed no degradation in the operation of the haptic interface or the image quality. A preliminary fMRI experiment during a pilot study validated the usability of the haptic interface, illustrating the possibilities offered by this device. PMID:26441454

A large-scale perspective on stress-induced alterations in resting-state networks

NASA Astrophysics Data System (ADS)

Maron-Katz, Adi; Vaisvaser, Sharon; Lin, Tamar; Hendler, Talma; Shamir, Ron

2016-02-01

Stress is known to induce large-scale neural modulations. However, its neural effect once the stressor is removed and how it relates to subjective experience are not fully understood. Here we used a statistically sound data-driven approach to investigate alterations in large-scale resting-state functional connectivity (rsFC) induced by acute social stress. We compared rsfMRI profiles of 57 healthy male subjects before and after stress induction. Using a parcellation-based univariate statistical analysis, we identified a large-scale rsFC change, involving 490 parcel-pairs. Aiming to characterize this change, we employed statistical enrichment analysis, identifying anatomic structures that were significantly interconnected by these pairs. This analysis revealed strengthening of thalamo-cortical connectivity and weakening of cross-hemispheral parieto-temporal connectivity. These alterations were further found to be associated with change in subjective stress reports. Integrating report-based information on stress sustainment 20 minutes post induction, revealed a single significant rsFC change between the right amygdala and the precuneus, which inversely correlated with the level of subjective recovery. Our study demonstrates the value of enrichment analysis for exploring large-scale network reorganization patterns, and provides new insight on stress-induced neural modulations and their relation to subjective experience.

The relationship of neurogenesis and growth of brain regions to song learning.

PubMed

Kirn, John R

2010-10-01

Song learning, maintenance and production require coordinated activity across multiple auditory, sensory-motor, and neuromuscular structures. Telencephalic components of the sensory-motor circuitry are unique to avian species that engage in song learning. The song system shows protracted development that begins prior to hatching but continues well into adulthood. The staggered developmental timetable for construction of the song system provides clues of subsystems involved in specific stages of song learning and maintenance. Progressive events, including neurogenesis and song system growth, as well as regressive events such as apoptosis and synapse elimination, occur during periods of song learning and the transitions between variable and stereotyped song during both development and adulthood. There is clear evidence that gonadal steroids influence the development of song attributes and shape the underlying neural circuitry. Some aspects of song system development are influenced by sensory, motor and social experience, while other aspects of neural development appear to be experience-independent. Although there are species differences in the extent to which song learning continues into adulthood, growing evidence suggests that despite differences in learning trajectories, adult refinement of song motor control and song maintenance can require remarkable behavioral and neural flexibility reminiscent of sensory-motor learning. Copyright © 2009 Elsevier Inc. All rights reserved.

A neural mechanism for background information-gated learning based on axonal-dendritic overlaps.

PubMed

Mainetti, Matteo; Ascoli, Giorgio A

2015-03-01

Experiencing certain events triggers the acquisition of new memories. Although necessary, however, actual experience is not sufficient for memory formation. One-trial learning is also gated by knowledge of appropriate background information to make sense of the experienced occurrence. Strong neurobiological evidence suggests that long-term memory storage involves formation of new synapses. On the short time scale, this form of structural plasticity requires that the axon of the pre-synaptic neuron be physically proximal to the dendrite of the post-synaptic neuron. We surmise that such "axonal-dendritic overlap" (ADO) constitutes the neural correlate of background information-gated (BIG) learning. The hypothesis is based on a fundamental neuroanatomical constraint: an axon must pass close to the dendrites that are near other neurons it contacts. The topographic organization of the mammalian cortex ensures that nearby neurons encode related information. Using neural network simulations, we demonstrate that ADO is a suitable mechanism for BIG learning. We model knowledge as associations between terms, concepts or indivisible units of thought via directed graphs. The simplest instantiation encodes each concept by single neurons. Results are then generalized to cell assemblies. The proposed mechanism results in learning real associations better than spurious co-occurrences, providing definitive cognitive advantages.

A Neural Mechanism for Background Information-Gated Learning Based on Axonal-Dendritic Overlaps

PubMed Central

Mainetti, Matteo; Ascoli, Giorgio A.

2015-01-01

Experiencing certain events triggers the acquisition of new memories. Although necessary, however, actual experience is not sufficient for memory formation. One-trial learning is also gated by knowledge of appropriate background information to make sense of the experienced occurrence. Strong neurobiological evidence suggests that long-term memory storage involves formation of new synapses. On the short time scale, this form of structural plasticity requires that the axon of the pre-synaptic neuron be physically proximal to the dendrite of the post-synaptic neuron. We surmise that such “axonal-dendritic overlap” (ADO) constitutes the neural correlate of background information-gated (BIG) learning. The hypothesis is based on a fundamental neuroanatomical constraint: an axon must pass close to the dendrites that are near other neurons it contacts. The topographic organization of the mammalian cortex ensures that nearby neurons encode related information. Using neural network simulations, we demonstrate that ADO is a suitable mechanism for BIG learning. We model knowledge as associations between terms, concepts or indivisible units of thought via directed graphs. The simplest instantiation encodes each concept by single neurons. Results are then generalized to cell assemblies. The proposed mechanism results in learning real associations better than spurious co-occurrences, providing definitive cognitive advantages. PMID:25767887

Behavioral effects of heavy ions and protons and potential countermeasure agents

NASA Astrophysics Data System (ADS)

Vazquez, M.; Gatley, J.; Bruneus, M.; Koslosky, S.; Billups, A.

Space travel beyond the Earth's protective magnetic field (for example, to Mars) will involve exposure of astronauts to irradiation by high-energy nuclei such as 56 Fe, which are a component of galactic cosmic rays. These particles have high linear energy transfer (LET) and are expected to irreversibly damage cells they traverse. Exposure to HZE radiation may therefore cause progressive deterioration of brain function, adding to other inescapable damage involved in normal aging. We propose a study of the hypothesis that long-term behavioral alterations are induced after exposure of the brain to 1 GeV/n iron and silicon particles with fluences of 1 to 8 particles/cell targets. Previous studies support this notion but are not definitive, especially with regard to long-term effects. Our principal goal is to examine the neurological effects of high-LET radiation on C57BL/6 mice using a series of behavioral tests to unveil the temporal expression of altered behaviors in the radiation response, as well as the means, which can modulate these responses. The studies planned in this project are designed to: 1) Characterize the behavioral consequences after exposure to low-fluences of heavy ions and protons on C57BL/6 mice. The main behavioral endpoints to be used in these studies are locomotor activity to evaluate the integrity of striatal dopaminergic pathways, and spatial reference memory to probe hippocampal cholinergic pathways. 2) Characterize the neurochemical and structural changes induced by heavy ions and protons. 3) To develop countermeasures to protect neural cell populations exposed to low fluences of heavy ions and protons. The project will test methods to protect injured neural cells based on their molecular and cellular mechanisms that may regulate neural cell survival in the central nervous system. Among the methods that will be studied is the direct administration of neuroprotective molecules as well as the modulation of apoptotic pathways by pharmacological manipulation. The effects of 3 different neuro/radioprotectors (GM1, melatonin and PTF-) on the levels of radiation induced neurochemical and structural damage will be compared with the level of behavioral alterations to determine a cause/effect relationship

From prosodic structure to acoustic saliency: A fMRI investigation of speech rate, clarity, and emphasis

NASA Astrophysics Data System (ADS)

Golfinopoulos, Elisa

Acoustic variability in fluent speech can arise at many stages in speech production planning and execution. For example, at the phonological encoding stage, the grouping of phonemes into syllables determines which segments are coarticulated and, by consequence, segment-level acoustic variation. Likewise phonetic encoding, which determines the spatiotemporal extent of articulatory gestures, will affect the acoustic detail of segments. Functional magnetic resonance imaging (fMRI) was used to measure brain activity of fluent adult speakers in four speaking conditions: fast, normal, clear, and emphatic (or stressed) speech. These speech manner changes typically result in acoustic variations that do not change the lexical or semantic identity of productions but do affect the acoustic saliency of phonemes, syllables and/or words. Acoustic responses recorded inside the scanner were assessed quantitatively using eight acoustic measures and sentence duration was used as a covariate of non-interest in the neuroimaging analysis. Compared to normal speech, emphatic speech was characterized acoustically by a greater difference between stressed and unstressed vowels in intensity, duration, and fundamental frequency, and neurally by increased activity in right middle premotor cortex and supplementary motor area, and bilateral primary sensorimotor cortex. These findings are consistent with right-lateralized motor planning of prosodic variation in emphatic speech. Clear speech involved an increase in average vowel and sentence durations and average vowel spacing, along with increased activity in left middle premotor cortex and bilateral primary sensorimotor cortex. These findings are consistent with an increased reliance on feedforward control, resulting in hyper-articulation, under clear as compared to normal speech. Fast speech was characterized acoustically by reduced sentence duration and average vowel spacing, and neurally by increased activity in left anterior frontal operculum and posterior dorsal inferior frontal gyms pars opercularis -- regions thought to be involved in sequencing and phrase-level structural processing. Taken together these findings identify the acoustic and neural correlates of adjusting speech manner and underscore the different processing stages that can contribute to acoustic variability in fluent sentence production.

Stephen L. Gans Distinguished Overseas Lecture. The neural crest in pediatric surgery.

PubMed

Tovar, Juan A

2007-06-01

This review highlights the relevance of the neural crest (NC) as a developmental control mechanism involved in several pediatric surgical conditions and the investigative interest of following some of its known signaling pathways. The participation of the NC in facial clefts, ear defects, branchial fistulae and cysts, heart outflow tract and aortic arch anomalies, pigmentary disorders, abnormal enteric innervation, neural tumors, hemangiomas, and vascular anomalies is briefly reviewed. Then, the literature on clinical and experimental esophageal atresia-tracheoesophageal fistula (EA-TEF) and congenital diaphragmatic hernia (CDH) is reviewed for the presence of associated NC defects. Finally, some of the molecular signaling pathways involved in both conditions (sonic hedgehog, Hox genes, and retinoids) are summarized. The association of facial, cardiovascular, thymic, parathyroid, and C-cell defects together with anomalies of extrinsic and intrinsic esophageal innervation in babies and/or animals with both EA-TEF and CDH strongly supports the hypothesis that NC is involved in the pathogenesis of these malformative clusters. On the other hand, both EA-TEF and CDH are observed in mice mutant for genes involved in the previously mentioned signaling pathways. The investigation of NC-related molecular pathogenic pathways involved in malformative associations like EA-TEF and CDH that are induced by chromosomal anomalies, chemical teratogens, and engineered mutations is a promising way of clarifying why and how some pediatric surgical conditions occur. Pediatric surgeons should be actively involved in these investigations.

Culture Wires the Brain: A Cognitive Neuroscience Perspective.

PubMed

Park, Denise C; Huang, Chih-Mao

2010-07-01

There is clear evidence that sustained experiences may affect both brain structure and function. Thus, it is quite reasonable to posit that sustained exposure to a set of cultural experiences and behavioral practices will affect neural structure and function. The burgeoning field of cultural psychology has often demonstrated the subtle differences in the way individuals process information-differences that appear to be a product of cultural experiences. We review evidence that the collectivistic and individualistic biases of East Asian and Western cultures, respectively, affect neural structure and function. We conclude that there is limited evidence that cultural experiences affect brain structure and considerably more evidence that neural function is affected by culture, particularly activations in ventral visual cortex-areas associated with perceptual processing. © The Author(s) 2010.

Network evolution induced by asynchronous stimuli through spike-timing-dependent plasticity.

PubMed

Yuan, Wu-Jie; Zhou, Jian-Fang; Zhou, Changsong

2013-01-01

In sensory neural system, external asynchronous stimuli play an important role in perceptual learning, associative memory and map development. However, the organization of structure and dynamics of neural networks induced by external asynchronous stimuli are not well understood. Spike-timing-dependent plasticity (STDP) is a typical synaptic plasticity that has been extensively found in the sensory systems and that has received much theoretical attention. This synaptic plasticity is highly sensitive to correlations between pre- and postsynaptic firings. Thus, STDP is expected to play an important role in response to external asynchronous stimuli, which can induce segregative pre- and postsynaptic firings. In this paper, we study the impact of external asynchronous stimuli on the organization of structure and dynamics of neural networks through STDP. We construct a two-dimensional spatial neural network model with local connectivity and sparseness, and use external currents to stimulate alternately on different spatial layers. The adopted external currents imposed alternately on spatial layers can be here regarded as external asynchronous stimuli. Through extensive numerical simulations, we focus on the effects of stimulus number and inter-stimulus timing on synaptic connecting weights and the property of propagation dynamics in the resulting network structure. Interestingly, the resulting feedforward structure induced by stimulus-dependent asynchronous firings and its propagation dynamics reflect both the underlying property of STDP. The results imply a possible important role of STDP in generating feedforward structure and collective propagation activity required for experience-dependent map plasticity in developing in vivo sensory pathways and cortices. The relevance of the results to cue-triggered recall of learned temporal sequences, an important cognitive function, is briefly discussed as well. Furthermore, this finding suggests a potential application for examining STDP by measuring neural population activity in a cultured neural network.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory.

PubMed

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG.

PubMed

Duru, Adil Deniz; Assem, Moataz

2018-02-01

Neural efficiency is proposed as one of the neural mechanisms underlying elite athletic performances. Previous sports studies examined neural efficiency using tasks that involve motor functions. In this study we investigate the extent of neural efficiency beyond motor tasks by using a mental subtraction task. A group of elite karate athletes are compared to a matched group of non-athletes. Electroencephalogram is used to measure cognitive dynamics during resting and increased mental workload periods. Mainly posterior alpha band power of the karate players was found to be higher than control subjects under both tasks. Moreover, event related synchronization/desynchronization has been computed to investigate the neural efficiency hypothesis among subjects. Finally, this study is the first study to examine neural efficiency related to a cognitive task, not a motor task, in elite karate players using ERD/ERS analysis. The results suggest that the effect of neural efficiency in the brain is global rather than local and thus might be contributing to the elite athletic performances. Also the results are in line with the neural efficiency hypothesis tested for motor performance studies.

Slits Affect the Timely Migration of Neural Crest Cells via Robo Receptor

PubMed Central

Giovannone, Dion; Reyes, Michelle; Reyes, Rachel; Correa, Lisa; Martinez, Darwin; Ra, Hannah; Gomez, Gustavo; Kaiser, Josh; Ma, Le; Stein, Mary-Pat; de Bellard, Maria Elena

2013-01-01

SUMMARY Background Neural crest cells emerge by delamination from the dorsal neural tube and give rise to various components of the peripheral nervous system in vertebrate embryos. These cells change from non-motile into highly motile cells migrating to distant areas before further differentiation. Mechanisms controlling delamination and subsequent migration of neural crest cells are not fully understood. Slit2, a chemorepellant for axonal guidance that repels and stimulates motility of trunk neural crest cells away from the gut has recently been suggested to be a tumor suppressor molecule. The goal of this study was to further investigate the role of Slit2 in trunk neural crest cell migration by constitutive expression in neural crest cells. Results We found that Slit gain-of-function significantly impaired neural crest cell migration while Slit loss-of-function favored migration. In addition, we observed that the distribution of key cytoskeletal markers was disrupted in both gain and loss of function instances. Conclusions These findings suggest that Slit molecules might be involved in the processes that allow neural crest cells to begin migration and transitioning to a mesenchymal type. PMID:22689303

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.

Differential receptive field organizations give rise to nearly identical neural correlations across three parallel sensory maps in weakly electric fish

PubMed Central

2017-01-01

Understanding how neural populations encode sensory information thereby leading to perception and behavior (i.e., the neural code) remains an important problem in neuroscience. When investigating the neural code, one must take into account the fact that neural activities are not independent but are actually correlated with one another. Such correlations are seen ubiquitously and have a strong impact on neural coding. Here we investigated how differences in the antagonistic center-surround receptive field (RF) organization across three parallel sensory maps influence correlations between the activities of electrosensory pyramidal neurons. Using a model based on known anatomical differences in receptive field center size and overlap, we initially predicted large differences in correlated activity across the maps. However, in vivo electrophysiological recordings showed that, contrary to modeling predictions, electrosensory pyramidal neurons across all three segments displayed nearly identical correlations. To explain this surprising result, we incorporated the effects of RF surround in our model. By systematically varying both the RF surround gain and size relative to that of the RF center, we found that multiple RF structures gave rise to similar levels of correlation. In particular, incorporating known physiological differences in RF structure between the three maps in our model gave rise to similar levels of correlation. Our results show that RF center overlap alone does not determine correlations which has important implications for understanding how RF structure influences correlated neural activity. PMID:28863136