WorldWideScience

Sample records for human brain learns

  1. Using human brain activity to guide machine learning.

    Science.gov (United States)

    Fong, Ruth C; Scheirer, Walter J; Cox, David D

    2018-03-29

    Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

  2. Human-like brain hemispheric dominance in birdsong learning.

    Science.gov (United States)

    Moorman, Sanne; Gobes, Sharon M H; Kuijpers, Maaike; Kerkhofs, Amber; Zandbergen, Matthijs A; Bolhuis, Johan J

    2012-07-31

    Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca's area in the frontal lobe and Wernicke's area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke's area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms.

  3. Convergent transcriptional specializations in the brains of humans and song-learning birds

    DEFF Research Database (Denmark)

    Pfenning, Andreas R.; Hara, Erina; Whitney, Osceola

    2014-01-01

    Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified...... convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production...... and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes....

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

    Science.gov (United States)

    Caine, Renate N.; Caine, Geoffrey

    2011-01-01

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

  5. Human Behavior, Learning, and the Developing Brain: Typical Development

    Science.gov (United States)

    Coch, Donna, Ed.; Fischer, Kurt W., Ed.; Dawson, Geraldine, Ed.

    2010-01-01

    This volume brings together leading authorities from multiple disciplines to examine the relationship between brain development and behavior in typically developing children. Presented are innovative cross-sectional and longitudinal studies that shed light on brain-behavior connections in infancy and toddlerhood through adolescence. Chapters…

  6. Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

    Directory of Open Access Journals (Sweden)

    Guangjun Zhao

    2016-01-01

    Full Text Available Cryosection brain images in Chinese Visible Human (CVH dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel. Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

  7. Learning-dependent plasticity with and without training in the human brain.

    Science.gov (United States)

    Zhang, Jiaxiang; Kourtzi, Zoe

    2010-07-27

    Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience with statistical regularities may facilitate opportunistic learning of collinear contours, whereas learning to integrate discontinuities entails bootstrap-based training for the detection of contours in clutter. These findings provide insights in understanding how long-term experience and short-term training interact to shape the optimization of visual recognition processes.

  8. Learning-related human brain activations reflecting individual finances.

    Science.gov (United States)

    Tobler, Philippe N; Fletcher, Paul C; Bullmore, Edward T; Schultz, Wolfram

    2007-04-05

    A basic tenet of microeconomics suggests that the subjective value of financial gains decreases with increasing assets of individuals ("marginal utility"). Using concepts from learning theory and microeconomics, we assessed the capacity of financial rewards to elicit behavioral and neuronal changes during reward-predictive learning in participants with different financial backgrounds. Behavioral learning speed during both acquisition and extinction correlated negatively with the assets of the participants, irrespective of education and age. Correspondingly, response changes in midbrain and striatum measured with functional magnetic resonance imaging were slower during both acquisition and extinction with increasing assets and income of the participants. By contrast, asymptotic magnitudes of behavioral and neuronal responses after learning were unrelated to personal finances. The inverse relationship of behavioral and neuronal learning speed with personal finances is compatible with the general concept of decreasing marginal utility with increasing wealth.

  9. Neural Computations Mediating One-Shot Learning in the Human Brain

    Science.gov (United States)

    Lee, Sang Wan; O’Doherty, John P.; Shimojo, Shinsuke

    2015-01-01

    Incremental learning, in which new knowledge is acquired gradually through trial and error, can be distinguished from one-shot learning, in which the brain learns rapidly from only a single pairing of a stimulus and a consequence. Very little is known about how the brain transitions between these two fundamentally different forms of learning. Here we test a computational hypothesis that uncertainty about the causal relationship between a stimulus and an outcome induces rapid changes in the rate of learning, which in turn mediates the transition between incremental and one-shot learning. By using a novel behavioral task in combination with functional magnetic resonance imaging (fMRI) data from human volunteers, we found evidence implicating the ventrolateral prefrontal cortex and hippocampus in this process. The hippocampus was selectively “switched” on when one-shot learning was predicted to occur, while the ventrolateral prefrontal cortex was found to encode uncertainty about the causal association, exhibiting increased coupling with the hippocampus for high-learning rates, suggesting this region may act as a “switch,” turning on and off one-shot learning as required. PMID:25919291

  10. Neural computations mediating one-shot learning in the human brain.

    Directory of Open Access Journals (Sweden)

    Sang Wan Lee

    2015-04-01

    Full Text Available Incremental learning, in which new knowledge is acquired gradually through trial and error, can be distinguished from one-shot learning, in which the brain learns rapidly from only a single pairing of a stimulus and a consequence. Very little is known about how the brain transitions between these two fundamentally different forms of learning. Here we test a computational hypothesis that uncertainty about the causal relationship between a stimulus and an outcome induces rapid changes in the rate of learning, which in turn mediates the transition between incremental and one-shot learning. By using a novel behavioral task in combination with functional magnetic resonance imaging (fMRI data from human volunteers, we found evidence implicating the ventrolateral prefrontal cortex and hippocampus in this process. The hippocampus was selectively "switched" on when one-shot learning was predicted to occur, while the ventrolateral prefrontal cortex was found to encode uncertainty about the causal association, exhibiting increased coupling with the hippocampus for high-learning rates, suggesting this region may act as a "switch," turning on and off one-shot learning as required.

  11. Hedging Your Bets by Learning Reward Correlations in the Human Brain

    Science.gov (United States)

    Wunderlich, Klaus; Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J.

    2011-01-01

    Summary Human subjects are proficient at tracking the mean and variance of rewards and updating these via prediction errors. Here, we addressed whether humans can also learn about higher-order relationships between distinct environmental outcomes, a defining ecological feature of contexts where multiple sources of rewards are available. By manipulating the degree to which distinct outcomes are correlated, we show that subjects implemented an explicit model-based strategy to learn the associated outcome correlations and were adept in using that information to dynamically adjust their choices in a task that required a minimization of outcome variance. Importantly, the experimentally generated outcome correlations were explicitly represented neuronally in right midinsula with a learning prediction error signal expressed in rostral anterior cingulate cortex. Thus, our data show that the human brain represents higher-order correlation structures between rewards, a core adaptive ability whose immediate benefit is optimized sampling. PMID:21943609

  12. Social learning, culture and the 'socio-cultural brain' of human and non-human primates.

    Science.gov (United States)

    Whiten, Andrew; van de Waal, Erica

    2017-11-01

    Noting important recent discoveries, we review primate social learning, traditions and culture, together with associated findings about primate brains. We survey our current knowledge of primate cultures in the wild, and complementary experimental diffusion studies testing species' capacity to sustain traditions. We relate this work to theories that seek to explain the enlarged brain size of primates as specializations for social intelligence, that have most recently extended to learning from others and the cultural transmission this permits. We discuss alternative theories and review a variety of recent findings that support cultural intelligence hypotheses for primate encephalization. At a more fine-grained neuroscientific level we focus on the underlying processes of social learning, especially emulation and imitation. Here, our own and others' recent research has established capacities for bodily imitation in both monkeys and apes, results that are consistent with a role for the mirror neuron system in social learning. We review important convergences between behavioural findings and recent non-invasive neuroscientific studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Two spatiotemporally distinct value systems shape reward-based learning in the human brain.

    Science.gov (United States)

    Fouragnan, Elsa; Retzler, Chris; Mullinger, Karen; Philiastides, Marios G

    2015-09-08

    Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants' switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning.

  14. Quality of clinical brain tumor MR spectra judged by humans and machine learning tools.

    Science.gov (United States)

    Kyathanahally, Sreenath P; Mocioiu, Victor; Pedrosa de Barros, Nuno; Slotboom, Johannes; Wright, Alan J; Julià-Sapé, Margarida; Arús, Carles; Kreis, Roland

    2018-05-01

    To investigate and compare human judgment and machine learning tools for quality assessment of clinical MR spectra of brain tumors. A very large set of 2574 single voxel spectra with short and long echo time from the eTUMOUR and INTERPRET databases were used for this analysis. Original human quality ratings from these studies as well as new human guidelines were used to train different machine learning algorithms for automatic quality control (AQC) based on various feature extraction methods and classification tools. The performance was compared with variance in human judgment. AQC built using the RUSBoost classifier that combats imbalanced training data performed best. When furnished with a large range of spectral and derived features where the most crucial ones had been selected by the TreeBagger algorithm it showed better specificity (98%) in judging spectra from an independent test-set than previously published methods. Optimal performance was reached with a virtual three-class ranking system. Our results suggest that feature space should be relatively large for the case of MR tumor spectra and that three-class labels may be beneficial for AQC. The best AQC algorithm showed a performance in rejecting spectra that was comparable to that of a panel of human expert spectroscopists. Magn Reson Med 79:2500-2510, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  15. Associative learning in humans--conditioning of sensory-evoked brain activity.

    Science.gov (United States)

    Skrandies, W; Jedynak, A

    2000-01-01

    A classical conditioning paradigm was employed in two experiments performed on 35 human volunteers. In nine subjects, the presentation of Landolt rings (conditioned stimuli, CS + ) was paired with an electric stimulus (unconditioned stimuli, UCS) applied to the left median nerve. Neutral visual control stimuli were full circles (CS -) that were not paired with the UCS. The skin conductance response (SCR) was determined in a time interval of 5 s after onset of the visual stimuli, and it was measured in the acquisition and test phase. Associative learning was reflected by a SCR occurring selectively with CS +. The same experiment was repeated with another group of 26 adults while electroencephalogram (EEG) was recorded from 30 electrodes. For each subject, mean evoked potentials were computed. In 13 of the subjects, a conditioning paradigm was followed while the other subjects served as the control group (non-contingent stimulation). There were somatosensory and visual brain activity evoked by the stimuli. Conditioned components were identified by computing cross-correlation between evoked somatosensory components and the averaged EEG. In the visual evoked brain activity, three components with mean latencies of 105.4, 183.2, and 360.3 ms were analyzed. Somatosensory stimuli were followed by major components that occurred at mean latencies of 48.8, 132.5, 219.7, 294.8, and 374.2 ms latency after the shock. All components were analyzed in terms of latency, field strength, and topographic characteristics, and were compared between groups and experimental conditions. Both visual and somatosensory brain activity was significantly affected by classical conditioning. Our data illustrate how associative learning affects the topography of brain electrical activity elicited by presentation of conditioned visual stimuli.

  16. Nonlocal atlas-guided multi-channel forest learning for human brain labeling

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Guangkai [Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China and Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong; Wu, Guorong [Department of Computer Science, Department of Radiology, and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States); Wu, Ligang [Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 02841 (Korea, Republic of)

    2016-02-15

    Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the

  17. Nonlocal atlas-guided multi-channel forest learning for human brain labeling

    International Nuclear Information System (INIS)

    Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

    2016-01-01

    Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the

  18. Nonlocal atlas-guided multi-channel forest learning for human brain labeling.

    Science.gov (United States)

    Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

    2016-02-01

    It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient

  19. New learning following reactivation in the human brain: targeting emotional memories through rapid serial visual presentation.

    Science.gov (United States)

    Wirkner, Janine; Löw, Andreas; Hamm, Alfons O; Weymar, Mathias

    2015-03-01

    Once reactivated, previously consolidated memories destabilize and have to be reconsolidated to persist, a process that might be altered non-invasively by interfering learning immediately after reactivation. Here, we investigated the influence of interference on brain correlates of reactivated episodic memories for emotional and neutral scenes using event-related potentials (ERPs). To selectively target emotional memories we applied a new reactivation method: rapid serial visual presentation (RSVP). RSVP leads to enhanced implicit processing (pop out) of the most salient memories making them vulnerable to disruption. In line, interference after reactivation of previously encoded pictures disrupted recollection particularly for emotional events. Furthermore, memory impairments were reflected in a reduced centro-parietal ERP old/new difference during retrieval of emotional pictures. These results provide neural evidence that emotional episodic memories in humans can be selectively altered through behavioral interference after reactivation, a finding with further clinical implications for the treatment of anxiety disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Cingulate neglect in humans: disruption of contralesional reward learning in right brain damage.

    Science.gov (United States)

    Lecce, Francesca; Rotondaro, Francesca; Bonnì, Sonia; Carlesimo, Augusto; Thiebaut de Schotten, Michel; Tomaiuolo, Francesco; Doricchi, Fabrizio

    2015-01-01

    Motivational valence plays a key role in orienting spatial attention. Nonetheless, clinical documentation and understanding of motivationally based deficits of spatial orienting in the human is limited. Here in a series of one group-study and two single-case studies, we have examined right brain damaged patients (RBD) with and without left spatial neglect in a spatial reward-learning task, in which the motivational valence of the left contralesional and the right ipsilesional space was contrasted. In each trial two visual boxes were presented, one to the left and one to the right of central fixation. In one session monetary rewards were released more frequently in the box on the left side (75% of trials) whereas in another session they were released more frequently on the right side. In each trial patients were required to: 1) point to each one of the two boxes; 2) choose one of the boxes for obtaining monetary reward; 3) report explicitly the position of reward and whether this position matched or not the original choice. Despite defective spontaneous allocation of attention toward the contralesional space, RBD patients with left spatial neglect showed preserved contralesional reward learning, i.e., comparable to ipsilesional learning and to reward learning displayed by patients without neglect. A notable exception in the group of neglect patients was L.R., who showed no sign of contralesional reward learning in a series of 120 consecutive trials despite being able of reaching learning criterion in only 20 trials in the ipsilesional space. L.R. suffered a cortical-subcortical brain damage affecting the anterior components of the parietal-frontal attentional network and, compared with all other neglect and non-neglect patients, had additional lesion involvement of the medial anterior cingulate cortex (ACC) and of the adjacent sectors of the corpus callosum. In contrast to his lateralized motivational learning deficit, L.R. had no lateral bias in the early phases of

  1. Brain Research: Implications for Learning.

    Science.gov (United States)

    Soares, Louise M.; Soares, Anthony T.

    Brain research has illuminated several areas of the learning process: (1) learning as association; (2) learning as reinforcement; (3) learning as perception; (4) learning as imitation; (5) learning as organization; (6) learning as individual style; and (7) learning as brain activity. The classic conditioning model developed by Pavlov advanced…

  2. Brain Research and Learning.

    Science.gov (United States)

    Claycomb, Mary

    Current research on brain activity has many implications for educators. The triune brain concept and the left and right hemisphere concepts are among the many complex theories evolving from experimentation and observation. The triune brain concept suggests that the human forebrain has expanded while retaining three structurally unique formations…

  3. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain.

    Science.gov (United States)

    Niv, Yael; Edlund, Jeffrey A; Dayan, Peter; O'Doherty, John P

    2012-01-11

    Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric-psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms.

  4. Visual learning alters the spontaneous activity of the resting human brain: an fNIRS study.

    Science.gov (United States)

    Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

    2014-01-01

    Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning.

  5. Neuroplasticity as a function of second language learning: anatomical changes in the human brain.

    Science.gov (United States)

    Li, Ping; Legault, Jennifer; Litcofsky, Kaitlyn A

    2014-09-01

    The brain has an extraordinary ability to functionally and physically change or reconfigure its structure in response to environmental stimulus, cognitive demand, or behavioral experience. This property, known as neuroplasticity, has been examined extensively in many domains. But how does neuroplasticity occur in the brain as a function of an individual's experience with a second language? It is not until recently that we have gained some understanding of this question by examining the anatomical changes as well as functional neural patterns that are induced by the learning and use of multiple languages. In this article we review emerging evidence regarding how structural neuroplasticity occurs in the brain as a result of one's bilingual experience. Our review aims at identifying the processes and mechanisms that drive experience-dependent anatomical changes, and integrating structural imaging evidence with current knowledge of functional neural plasticity of language and other cognitive skills. The evidence reviewed so far portrays a picture that is highly consistent with structural neuroplasticity observed for other domains: second language experience-induced brain changes, including increased gray matter (GM) density and white matter (WM) integrity, can be found in children, young adults, and the elderly; can occur rapidly with short-term language learning or training; and are sensitive to age, age of acquisition, proficiency or performance level, language-specific characteristics, and individual differences. We conclude with a theoretical perspective on neuroplasticity in language and bilingualism, and point to future directions for research. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

    Science.gov (United States)

    Bassett, Danielle S; Mattar, Marcelo G

    2017-04-01

    Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand

    Science.gov (United States)

    Garrido, Marta Isabel; Teng, Chee Leong James; Taylor, Jeremy Alexander; Rowe, Elise Genevieve; Mattingley, Jason Brett

    2016-06-01

    The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode statistical regularities and detect violations therein, as reflected in neuronal responses to unpredictable events that carry a unique prediction error signature. In the real world, however, learning about regularities will often occur in the context of competing cognitive demands. Here we asked whether learning of statistical regularities is modulated by concurrent cognitive load. We compared electroencephalographic metrics associated with responses to pure-tone sounds with frequencies sampled from narrow or wide Gaussian distributions. We showed that outliers evoked a larger response than those in the centre of the stimulus distribution (i.e., an effect of surprise) and that this difference was greater for physically identical outliers in the narrow than in the broad distribution. These results demonstrate an early neurophysiological marker of the brain's ability to implicitly encode complex statistical structure in the environment. Moreover, we manipulated concurrent cognitive load by having participants perform a visual working memory task while listening to these streams of sounds. We again observed greater prediction error responses in the narrower distribution under both low and high cognitive load. Furthermore, there was no reliable reduction in prediction error magnitude under high-relative to low-cognitive load. Our findings suggest that statistical learning is not a capacity limited process, and that it proceeds automatically even when cognitive resources are taxed by concurrent demands.

  8. Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design

    Directory of Open Access Journals (Sweden)

    Fabien eLotte

    2013-09-01

    Full Text Available While recent research on Brain-Computer Interfaces (BCI has highlighted their potential for many applications, they remain barely used outside laboratories. The main reason is their lack of robustness. Indeed, with current BCI, mental state recognition is usually slow and often incorrect. Spontaneous BCI (i.e., mental imagery-based BCI often rely on mutual learning efforts by the user and the machine, with BCI users learning to produce stable EEG patterns (spontaneous BCI control being widely acknowledged as a skill while the computer learns to automatically recognize these EEG patterns, using signal processing. Most research so far was focused on signal processing, mostly neglecting the human in the loop. However, how well the user masters the BCI skill is also a key element explaining BCI robustness. Indeed, if the user is not able to produce stable and distinct EEG patterns, then no signal processing algorithm would be able to recognize them. Unfortunately, despite the importance of BCI training protocols, they have been scarcely studied so far, and used mostly unchanged for years.In this paper, we advocate that current human training approaches for spontaneous BCI are most likely inappropriate. We notably study instructional design literature in order to identify the key requirements and guidelines for a successful training procedure that promotes a good and efficient skill learning. This literature study highlights that current spontaneous BCI user training procedures satisfy very few of these requirements and hence are likely to be suboptimal. We therefore identify the flaws in BCI training protocols according to instructional design principles, at several levels: in the instructions provided to the user, in the tasks he/she has to perform, and in the feedback provided. For each level, we propose new research directions that are theoretically expected to address some of these flaws and to help users learn the BCI skill more efficiently.

  9. Phosphatidylserine and the human brain.

    Science.gov (United States)

    Glade, Michael J; Smith, Kyl

    2015-06-01

    The aim of this study was to assess the roles and importance of phosphatidylserine (PS), an endogenous phospholipid and dietary nutrient, in human brain biochemistry, physiology, and function. A scientific literature search was conducted on MEDLINE for relevant articles regarding PS and the human brain published before June 2014. Additional publications were identified from references provided in original papers; 127 articles were selected for inclusion in this review. A large body of scientific evidence describes the interactions among PS, cognitive activity, cognitive aging, and retention of cognitive functioning ability. Phosphatidylserine is required for healthy nerve cell membranes and myelin. Aging of the human brain is associated with biochemical alterations and structural deterioration that impair neurotransmission. Exogenous PS (300-800 mg/d) is absorbed efficiently in humans, crosses the blood-brain barrier, and safely slows, halts, or reverses biochemical alterations and structural deterioration in nerve cells. It supports human cognitive functions, including the formation of short-term memory, the consolidation of long-term memory, the ability to create new memories, the ability to retrieve memories, the ability to learn and recall information, the ability to focus attention and concentrate, the ability to reason and solve problems, language skills, and the ability to communicate. It also supports locomotor functions, especially rapid reactions and reflexes. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Human brain imaging

    International Nuclear Information System (INIS)

    Kuhar, M.J.

    1987-01-01

    Just as there have been dramatic advances in the molecular biology of the human brain in recent years, there also have been remarkable advances in brain imaging. This paper reports on the development and broad application of microscopic imaging techniques which include the autoradiographic localization of receptors and the measurement of glucose utilization by autoradiography. These approaches provide great sensitivity and excellent anatomical resolution in exploring brain organization and function. The first noninvasive external imaging of receptor distributions in the living human brain was achieved by positron emission tomography (PET) scanning. Developments, techniques and applications continue to progress. Magnetic resonance imaging (MRI) is also becoming important. Its initial clinical applications were in examining the structure and anatomy of the brain. However, more recent uses, such as MRI spectroscopy, indicate the feasibility of exploring biochemical pathways in the brain, the metabolism of drugs in the brain, and also of examining some of these procedures at an anatomical resolution which is substantially greater than that obtainable by PET scanning. The issues will be discussed in greater detail

  11. Human Machine Learning Symbiosis

    Science.gov (United States)

    Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

    2017-01-01

    Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

  12. Prolonged rote learning produces delayed memory facilitation and metabolic changes in the hippocampus of the ageing human brain.

    LENUS (Irish Health Repository)

    Roche, Richard Ap

    2009-01-01

    BACKGROUND: Repeated rehearsal is one method by which verbal material may be transferred from short- to long-term memory. We hypothesised that extended engagement of memory structures through prolonged rehearsal would result in enhanced efficacy of recall and also of brain structures implicated in new learning. Twenty-four normal participants aged 55-70 (mean = 60.1) engaged in six weeks of rote learning, during which they learned 500 words per week every week (prose, poetry etc.). An extensive battery of memory tests was administered on three occasions, each six weeks apart. In addition, proton magnetic resonance spectroscopy (1H-MRS) was used to measure metabolite levels in seven voxels of interest (VOIs) (including hippocampus) before and after learning. RESULTS: Results indicate a facilitation of new learning that was evident six weeks after rote learning ceased. This facilitation occurred for verbal\\/episodic material only, and was mirrored by a metabolic change in left posterior hippocampus, specifically an increase in NAA\\/(Cr+Cho) ratio. CONCLUSION: Results suggest that repeated activation of memory structures facilitates anamnesis and may promote neuronal plasticity in the ageing brain, and that compliance is a key factor in such facilitation as the effect was confined to those who engaged fully with the training.

  13. Prolonged rote learning produces delayed memory facilitation and metabolic changes in the hippocampus of the ageing human brain

    Directory of Open Access Journals (Sweden)

    Prendergast Julie

    2009-11-01

    Full Text Available Abstract Background Repeated rehearsal is one method by which verbal material may be transferred from short- to long-term memory. We hypothesised that extended engagement of memory structures through prolonged rehearsal would result in enhanced efficacy of recall and also of brain structures implicated in new learning. Twenty-four normal participants aged 55-70 (mean = 60.1 engaged in six weeks of rote learning, during which they learned 500 words per week every week (prose, poetry etc.. An extensive battery of memory tests was administered on three occasions, each six weeks apart. In addition, proton magnetic resonance spectroscopy (1H-MRS was used to measure metabolite levels in seven voxels of interest (VOIs (including hippocampus before and after learning. Results Results indicate a facilitation of new learning that was evident six weeks after rote learning ceased. This facilitation occurred for verbal/episodic material only, and was mirrored by a metabolic change in left posterior hippocampus, specifically an increase in NAA/(Cr+Cho ratio. Conclusion Results suggest that repeated activation of memory structures facilitates anamnesis and may promote neuronal plasticity in the ageing brain, and that compliance is a key factor in such facilitation as the effect was confined to those who engaged fully with the training.

  14. Prolonged rote learning produces delayed memory facilitation and metabolic changes in the hippocampus of the ageing human brain.

    Science.gov (United States)

    Roche, Richard Ap; Mullally, Sinéad L; McNulty, Jonathan P; Hayden, Judy; Brennan, Paul; Doherty, Colin P; Fitzsimons, Mary; McMackin, Deirdre; Prendergast, Julie; Sukumaran, Sunita; Mangaoang, Maeve A; Robertson, Ian H; O'Mara, Shane M

    2009-11-20

    Repeated rehearsal is one method by which verbal material may be transferred from short- to long-term memory. We hypothesised that extended engagement of memory structures through prolonged rehearsal would result in enhanced efficacy of recall and also of brain structures implicated in new learning. Twenty-four normal participants aged 55-70 (mean = 60.1) engaged in six weeks of rote learning, during which they learned 500 words per week every week (prose, poetry etc.). An extensive battery of memory tests was administered on three occasions, each six weeks apart. In addition, proton magnetic resonance spectroscopy (1H-MRS) was used to measure metabolite levels in seven voxels of interest (VOIs) (including hippocampus) before and after learning. Results indicate a facilitation of new learning that was evident six weeks after rote learning ceased. This facilitation occurred for verbal/episodic material only, and was mirrored by a metabolic change in left posterior hippocampus, specifically an increase in NAA/(Cr+Cho) ratio. Results suggest that repeated activation of memory structures facilitates anamnesis and may promote neuronal plasticity in the ageing brain, and that compliance is a key factor in such facilitation as the effect was confined to those who engaged fully with the training.

  15. Learning-related brain hemispheric dominance in sleeping songbirds

    NARCIS (Netherlands)

    Moorman, Sanne; Gobes, Sharon M H; van de Kamp, Ferdinand C; Zandbergen, Matthijs A; Bolhuis, Johan J

    2015-01-01

    There are striking behavioural and neural parallels between the acquisition of speech in humans and song learning in songbirds. In humans, language-related brain activation is mostly lateralised to the left hemisphere. During language acquisition in humans, brain hemispheric lateralisation develops

  16. Learning after acquired brain injury. Learning the hard way

    NARCIS (Netherlands)

    Boosman, H.

    2015-01-01

    Background: When the brain has suffered damage, the learning process can be considerably disturbed. Brain damage can influence what is learned, but also how learning takes place. What patients can learn can be viewed in terms of ‘learning ability’ and how patients learn in terms of ‘learning style’.

  17. The Credentials of Brain-Based Learning

    Science.gov (United States)

    Davis, Andrew

    2004-01-01

    This paper discusses the current fashion for brain-based learning, in which value-laden claims about learning are grounded in neurophysiology. It argues that brain science cannot have the authority about learning that some seek to give it. It goes on to discuss whether the claim that brain science is relevant to learning involves a category…

  18. Creatine synthesis and exchanges between brain cells: What can be learned from human creatine deficiencies and various experimental models?

    Science.gov (United States)

    Hanna-El-Daher, Layane; Braissant, Olivier

    2016-08-01

    While it has long been thought that most of cerebral creatine is of peripheral origin, the last 20 years has provided evidence that the creatine synthetic pathway (AGAT and GAMT enzymes) is expressed in the brain together with the creatine transporter (SLC6A8). It has also been shown that SLC6A8 is expressed by microcapillary endothelial cells at the blood-brain barrier, but is absent from surrounding astrocytes, raising the concept that the blood-brain barrier has a limited permeability for peripheral creatine. The first creatine deficiency syndrome in humans was also discovered 20 years ago (GAMT deficiency), followed later by AGAT and SLC6A8 deficiencies, all three diseases being characterized by creatine deficiency in the CNS and essentially affecting the brain. By reviewing the numerous and latest experimental studies addressing creatine transport and synthesis in the CNS, as well as the clinical and biochemical characteristics of creatine-deficient patients, our aim was to delineate a clearer view of the roles of the blood-brain and blood-cerebrospinal fluid barriers in the transport of creatine and guanidinoacetate between periphery and CNS, and on the intracerebral synthesis and transport of creatine. This review also addresses the question of guanidinoacetate toxicity for brain cells, as probably found under GAMT deficiency.

  19. Brain and learning in adolescence

    DEFF Research Database (Denmark)

    Gerlach, Christian; Evans, Karen

    2007-01-01

    neurons. For a long time it was assumed that such changes primarily happened in childhood because the brain is already 90 percent of the adult size by the age of six. Today this belief has clearly changed. It is now evident that the brain undergoes significant changes throughout life. In this writing we......, decision-making abilities and development of independence. The ultimate objective will be to consider what implications these developmental changes have for learning, teaching and education. Before we embark on this we will provide some background knowledge on brain development at both the microscopic...

  20. Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI.

    Science.gov (United States)

    Colas, Jaron T; Pauli, Wolfgang M; Larsen, Tobias; Tyszka, J Michael; O'Doherty, John P

    2017-10-01

    Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models-namely, "actor/critic" models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.

  1. The Human Brain Does Not Need High Levels of Motivation to Learn a Foreign Language: Motivation Has Had Its Day

    Science.gov (United States)

    Green, Kieran

    2016-01-01

    Language is nature in action and something humans do. This literature review presents evidence from the literature that suggests that learning a foreign language in a classroom situation does not require high levels of student motivation. It is instead suggested that high levels of motivation are needed to make progress when a teacher is using…

  2. Hacking Our Brains for Learning

    Directory of Open Access Journals (Sweden)

    Alex Tillas

    2018-05-01

    Full Text Available Observational learning is ubiquitous. We very often observe and pick up information about how others behave and subsequently replicate similar behaviours in one way or another. Focusing on observational learning, I investigate human imitation, the mechanisms that underpin it as well as the processes that complement it, in order to assess its contribution to learning and education. Furthermore, I construe emotion as a scaffold for observational learning and bring together evidence about its influence on selective attention. Finally, I flesh out possible ways in which the insights about the role of imitation in learning could help design a more effective and equally rewarding learning environment. Specifically, I suggest that perhaps the simplest and most effective way to foster learning via promoting imitation is through letting learners of various ages co-exist. The benefits of learning in a mixed-age group are assessed.

  3. Educating the Human Brain. Human Brain Development Series

    Science.gov (United States)

    Posner, Michael I.; Rothbart, Mary K.

    2006-01-01

    "Educating the Human Brain" is the product of a quarter century of research. This book provides an empirical account of the early development of attention and self regulation in infants and young children. It examines the brain areas involved in regulatory networks, their connectivity, and how their development is influenced by genes and…

  4. Brain mechanisms of flavor learning.

    Science.gov (United States)

    Yamamoto, Takashi; Ueji, Kayoko

    2011-01-01

    Once the flavor of the ingested food (conditioned stimulus, CS) is associated with a preferable (e.g., good taste or nutritive satisfaction) or aversive (e.g., malaise with displeasure) signal (unconditioned stimulus, US), animals react to its subsequent exposure by increasing or decreasing ingestion to the food. These two types of association learning (preference learning vs. aversion learning) are known as classical conditioned reactions which are basic learning and memory phenomena, leading selection of food and proper food intake. Since the perception of flavor is generated by interaction of taste and odor during food intake, taste and/or odor are mainly associated with bodily signals in the flavor learning. After briefly reviewing flavor learning in general, brain mechanisms of conditioned taste aversion is described in more detail. The CS-US association leading to long-term potentiation in the amygdala, especially in its basolateral nucleus, is the basis of establishment of conditioned taste aversion. The novelty of the CS detected by the cortical gustatory area may be supportive in CS-US association. After the association, CS input is conveyed through the amygdala to different brain regions including the hippocampus for contextual fear formation, to the supramammillary and thalamic paraventricular nuclei for stressful anxiety or memory dependent fearful or stressful emotion, to the reward system to induce aversive expression to the CS, or hedonic shift from positive to negative, and to the CS-responsive neurons in the gustatory system to enhance the responsiveness to facilitate to detect the harmful stimulus.

  5. Learning Predictive Statistics: Strategies and Brain Mechanisms.

    Science.gov (United States)

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

    2017-08-30

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

  6. Early Language Learning and the Social Brain.

    Science.gov (United States)

    Kuhl, Patricia K

    2014-01-01

    Explaining how every typically developing child acquires language is one of the grand challenges of cognitive neuroscience. Historically, language learning provoked classic debates about the contributions of innately specialized as opposed to general learning mechanisms. Now, new data are being brought to bear from studies that employ magnetoencephalograph (MEG), electroencephalograph (EEG), magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI) studies on young children. These studies examine the patterns of association between brain and behavioral measures. The resulting data offer both expected results and surprises that are altering theory. As we uncover what it means to be human through the lens of young children, and their ability to speak, what we learn will not only inform theories of human development, but also lead to the discovery of neural biomarkers, early in life, that indicate risk for language impairment and allow early intervention for children with developmental disabilities involving language. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

  7. Brain mechanisms of flavor learning

    Directory of Open Access Journals (Sweden)

    Takashi eYamamoto

    2011-09-01

    Full Text Available Once the flavor of the ingested food (conditioned stimulus, CS is associated with a preferable (e.g., good taste or nutritive satisfaction or aversive (e.g., malaise with displeasure signal (unconditioned stimulus, US, animals react to its subsequent exposure by increasing or decreasing ingestion to the food. These two types of association learning (preference learning vs. aversion learning are known as classical conditioned reactions which are basic learning and memory phenomena, leading selection of food and proper food intake. Since the perception of flavor is generated by interaction of taste and odor during food intake, taste and/or odor are mainly associated with bodily signals in the flavor learning. After briefly reviewing flavor learning in general, brain mechanisms of conditioned taste aversion is described in more detail. The CS-US association leading to long-term potentiation in the amygdala, especially in its basolateral nucleus, is the basis of establishment of conditioned taste aversion. The novelty of the CS detected by the cortical gustatory area may be supportive in CS-US association. After the association, CS input is conveyed through the amygdala to different brain regions including the hippocampus for contextual fear formation, to the supramammilary and thalamic paraventricular nuclei for stressful anxiety or memory dependent fearful or stressful emotion, to the reward system to induce aversive expression to the CS, or hedonic shift from positive to negative, and to the CS-responsive neurons in the gustatory system to enhance the responsiveness to facilitate to detect the harmful stimulus.

  8. Can machine learning explain human learning?

    NARCIS (Netherlands)

    Vahdat, M.; Oneto, L.; Anguita, D.; Funk, M.; Rauterberg, G.W.M.

    2016-01-01

    Learning Analytics (LA) has a major interest in exploring and understanding the learning process of humans and, for this purpose, benefits from both Cognitive Science, which studies how humans learn, and Machine Learning, which studies how algorithms learn from data. Usually, Machine Learning is

  9. Left Brain/Right Brain Learning for Adult Education.

    Science.gov (United States)

    Garvin, Barbara

    1986-01-01

    Contrasts and compares the theory and practice of adult education as it relates to the issue of right brain/left brain learning. The author stresses the need for a whole-brain approach to teaching and suggests that adult educators, given their philosophical directions, are the perfect potential users of this integrated system. (Editor/CT)

  10. Why did humans develop a large brain?

    OpenAIRE

    Muscat Baron, Yves

    2012-01-01

    "Of all animals, man has the largest brain in proportion to his size"- Aristotle. Dr Yves Muscat Baron shares his theory on how humans evolved large brains. The theory outlines how gravity could have helped humans develop a large brain- the author has named the theory 'The Gravitational Vascular Theory'. http://www.um.edu.mt/think/why-did-humans-develop-a-large-brain/

  11. A Study of Human Computing on Solving Process of Basic Problems in Exercises for learning by Brain Wave

    OpenAIRE

    山口, 有美; 山口, 晴久

    2001-01-01

    In this paper, we describe the comparative experiments to the students on solving process of problems on typical school teaching material knowledge (caluculation, geometry, Kanji dictations, typewriting, drawing ) in exercises in both in VDT works and on desktop works by frequency analysis of Brain Wave. The cognitive states of each mental working were compared on brain waves. And α reduction rate in brain waves in each mental work (calculation, geometry, Kanji dictations, typewriting, drawin...

  12. Brain-Based Learning. Research Brief

    Science.gov (United States)

    Walker, Karen

    2005-01-01

    What does brain-based research say about how adolescents learn? The 1990s was declared as the Decade of the Brain by President Bush and Congress. With the advancement of MRIs (Magnetic Resonance Imagining) and PET (positron emission tomography) scans, it has become much easier to study live healthy brains. As a result, the concept of…

  13. Common genetic variants influence human subcortical brain structures

    NARCIS (Netherlands)

    Hibar, D.P.; Stein, J.L.; Renteria, M.E.; Arias-Vasquez, A.; Desrivières, S.; Jahanshad, N.; Toro, R.; Wittfeld, K.; Abramovic, L.; Andersson, M.; Aribisala, B.S.; Armstrong, N.J.; Bernard, M.; Bohlken, M.M.; Biks, M.P.; Bralten, J.; Brown, A.A.; Chakravarty, M.M.; Chen, Q.; Ching, C.R.K.; Cuellar-Partida, G.; den Braber, A.; Giddaluru, S.; Goldman, A.L.; Grimm, O.; Guadalupe, T.; Hass, J.; Woldehawariat, G.; Holmes, A.J.; Hoogman, M.; Janowitz, D.; Jia, T.; Kim, S.; Klein, M.; Kraemer, B.; Lee, P.H.; Olde Loohuis, L.M.; Luciano, M.; Macare, C.; Mather, K.A.; Mattheisen, M.; Milaneschi, Y.; Nho, K.; Papmeyer, M.; Ramasamy, A.; Risacher, S.L.; Roiz-Santiañez, R.; Rose, E.J.; Salami, A.; Sämann, P.G.; Schmaal, L.; Schork, A.J.; Shin, J.; Strike, L.T.; Teumer, A.; Donkelaar, M.M.J.; van Eijk, K.R.; Walters, R.K.; Westlye, L.T.; Welan, C.D.; Winkler, A.M.; Zwiers, M.P.; Alhusaini, S.; Athanasiu, L.; Ehrlich, S.; Hakobjan, M.M.H.; Hartberg, C.B.; Haukvik, U.K.; Heister, A.J.G.A.M.; Hoehn, D.; Kasperaviciute, D.; Liewald, D.C.M.; Lopez, L.M.; Makkinje, R.R.; Matarin, M.; Naber, M.A.M.; Reese McKay, D.; Needham, M.; Nugent, A.C.; Pütz, B.; Royle, N.A.; Shen, L.; Sprooten, E.; Trabzuni, D.; van der Marel, S.S.L.; van Hulzen, K.J.E.; Walton, E.; Wolf, C.; Almasy, L.; Ames, D.; Arepalli, S.; Assareh, A.A.; Bastin, M.E.; Brodaty, H.; Bulayeva, K.B.; Carless, M.A.; Cichon, S.; Corvin, A.; Curran, J.E.; Czisch, M.; de Zubicaray, G.I.; Dillman, A.; Duggirala, R.; Dyer, T.D.; Erk, S.; Fedko, I.O.; Ferrucci, L.; Foroud, T.M.; Fox, P.T.; Fukunaga, M.; Gibbs, J.R.; Göring, H.H.H.; Green, R.C.; Guelfi, S.; Hansell, N.K.; Hartman, C.A.; Hegenscheid, K.; Heinz, A.; Hernandez, D.G.; Heslenfeld, D.J.; Hoekstra, P.J.; Holsboer, F.; Homuth, G.; Hottenga, J.J.; Ikeda, M.; Jack, C.R., Jr.; Jenkinson, M.; Johnson, R.; Kanai, R.; Keil, M.; Kent, J.W. Jr.; Kochunov, P.; Kwok, J.B.; Lawrie, S.M.; Liu, X.; Longo, D.L.; McMahon, K.L.; Meisenzahl, E.; Melle, I.; Mohnke, S.; Montgomery, G.W.; Mostert, J.C.; Mühleisen, T.W.; Nalls, M.A.; Nichols, T.E.; Nilsson, L.G.; Nöthen, M.M.; Ohi, K.; Olvera, R.L.; Perez-Iglesias, R.; Pike, G.B.; Potkin, S.G.; Reinvang, I.; Reppermund, S.; Rietschel, M.; Romanczuk-Seiferth, N.; Rosen, G.D.; Rujescu, D.; Schnell, K.; Schofield, P.R.; Smith, C.; Steen, V.M.; Sussmann, J.E.; Thalamuthu, A.; Toga, A.W.; Traynor, B.J.; Troncoso, J.; Turner, J.A.; Valdés Hernández, M.C.; van t Ent, D.; van der Brug, M.; van der Wee, N.J.A.; van Tol, M.J.; Veltman, D.J.; Wassink, T.H.; Westmann, E.; Zielke, R.H.; Zonderman, A.B.; Ashbrook, D.G.; Hager, R.; Lu, L.; McMahon, F.J.; Morris, D.W.; Williams, R.W.; Brunner, H.G.; Buckner, R.L.; Buitelaar, J.K.; Cahn, W.; Calhoun, V.D.; Cavalleri, G.L.; Crespo-Facorro, B.; Dale, A.M.; Davies, G.E.; Delanty, N.; Depondt, C.; Djurovic, S.; Drevets, W.C.; Espeseth, T.; Gollub, R.L.; Ho, B.C.; Hoffmann, W.; Hosten, N.; Kahn, R.S.; Le Hellard, S.; Meyer-Lindenberg, A.; Müller-Myhsok, B.; Nauck, M.; Nyberg, L.; Pandolfo, M.; Penninx, B.W.J.H.; Roffman, J.L.; Sisodiya, SM; Smoller, J.W.; van Bokhoven, H.; van Haren, N.E.M.; Völzke, H.; Walter, H.; Weiner, M.W.; Wen, W.; White, T.; Agartz, I.; Andreassen, O.A.; Blangero, J.; Boomsma, D.I.; Brouwer, R.M.; Cannon, D.M.; Cookson, M.R.; de Geus, E.J.C.; Deary, I.J.; Donohoe, G.; Fernandez, G.; Fisher, S.E.; Francks, C.; Glahn, D.C.; Grabe, H.J.; Gruber, O.; Hardy, J.; Hashimoto, R.; Hulshoff Pol, H.E.; Jönsson, E.G.; Kloszewska, I.; Lovestone, S.; Mattay, V.S.; Mecocci, P.; McDonald, C.; McIntosh, A.M.; Ophoff, R.A.; Paus, T.; Pausova, Z.; Ryten, M.; Sachdev, P.S.; Saykin, A.J.; Simmons, A.; Singleton, A.; Soininen, H.; Wardlaw, J.M.; Weale, M.E.; Weinberger, D.R.; Adams, H.H.H.; Launer, L.J.; Seiler, S.; Schmidt, R.; Chauhan, G.; Satizabal, C.L.; Becker, J.T.; Yanek, L.; van der Lee, S.J.; Ebling, M.; Fischl, B.; Longstreth, Jr. W.T.; Greve, D.; Schmidt, H.; Nyquist, P.; Vinke, L.N.; van Duijn, C.M.; Xue, L.; Mazoyer, B.; Bis, J.C.; Gudnason, V.; Seshadri, S.; Arfan Ikram, M.; Martin, N.G.; Wright, M.J.; Schumann, G.; Franke, B.; Thompson, P.M.; Medland, S.E.

    2015-01-01

    The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common

  14. Common genetic variants influence human subcortical brain structures

    NARCIS (Netherlands)

    D.P. Hibar (Derrek); J.L. Stein; M.E. Rentería (Miguel); A. Arias-Vásquez (Alejandro); S. Desrivières (Sylvane); N. Jahanshad (Neda); R. Toro (Roberto); K. Wittfeld (Katharina); L. Abramovic (Lucija); M. Andersson (Micael); B. Aribisala (Benjamin); N.J. Armstrong (Nicola J.); M. Bernard (Manon); M.M. Bohlken (Marc M.); M.P.M. Boks (Marco); L.B.C. Bralten (Linda); A.A. Brown (Andrew); M.M. Chakravarty (M. Mallar); Q. Chen (Qiang); C.R.K. Ching (Christopher); G. Cuellar-Partida (Gabriel); A. den Braber (Anouk); S. Giddaluru (Sudheer); A.L. Goldman (Aaron L.); O. Grimm (Oliver); T. Guadalupe (Tulio); J. Hass (Johanna); G. Woldehawariat (Girma); A.J. Holmes (Avram); M. Hoogman (Martine); D. Janowitz (Deborah); T. Jia (Tianye); S. Kim (Shinseog); M. Klein (Marieke); B. Kraemer (Bernd); P.H. Lee (Phil H.); L.M. Olde Loohuis (Loes M.); M. Luciano (Michelle); C. MacAre (Christine); R. Mather; M. Mattheisen (Manuel); Y. Milaneschi (Yuri); K. Nho (Kwangsik); M. Papmeyer (Martina); A. Ramasamy (Adaikalavan); S.L. Risacher (Shannon); R. Roiz-Santiañez (Roberto); E.J. Rose (Emma); A. Salami (Alireza); P.G. Sämann (Philipp); L. Schmaal (Lianne); N.J. Schork (Nicholas); J. Shin (Jean); L.T. Strike (Lachlan); A. Teumer (Alexander); M.M.J. Van Donkelaar (Marjolein M. J.); K.R. van Eijk (Kristel); R.K. Walters (Raymond); L.T. Westlye (Lars); C.D. Whelan (Christopher); A.M. Winkler (Anderson); M.P. Zwiers (Marcel); S. Alhusaini (Saud); L. Athanasiu (Lavinia); S.M. Ehrlich (Stefan); M. Hakobjan (Marina); C.B. Hartberg (Cecilie B.); U.K. Haukvik (Unn); A.J.G.A.M. Heister (Angelien J. G. A. M.); D. Hoehn (David); D. Kasperaviciute (Dalia); D.C. Liewald (David C.); L.M. Lopez (Lorna); R.R.R. Makkinje (Remco R. R.); M. Matarin (Mar); M.A.M. Naber (Marlies A. M.); D. Reese McKay; M. Needham (Margaret); A.C. Nugent (Allison); B. Pütz (Benno); N.A. Royle (Natalie); L. Shen (Li); R. Sprooten (Roy); D. Trabzuni (Danyah); S.S.L. Van Der Marel (Saskia S. L.); K.J.E. Van Hulzen (Kimm J. E.); E. Walton (Esther); A. Björnsson (Asgeir); L. Almasy (Laura); D.J. Ames (David); S. Arepalli (Sampath); A.A. Assareh; M.E. Bastin (Mark); H. Brodaty (Henry); K. Bulayeva (Kazima); M.A. Carless (Melanie); S. Cichon (Sven); A. Corvin (Aiden); J.E. Curran (Joanne); M. Czisch (Michael); G.I. de Zubicaray (Greig); A. Dillman (Allissa); A. Duggirala (Aparna); M.D. Dyer (Matthew); S. Erk; I. Fedko (Iryna); L. Ferrucci (Luigi); T. Foroud (Tatiana); P.T. Fox (Peter); M. Fukunaga (Masaki); J. Raphael Gibbs; H.H.H. Göring (Harald H.); R.C. Green (Robert C.); S. Guelfi (Sebastian); N.K. Hansell (Narelle); C.A. Hartman (Catharina); K. Hegenscheid (Katrin); J. Heinz (Judith); D.G. Hernandez (Dena); D.J. Heslenfeld (Dirk); P.J. Hoekstra (Pieter); F. Holsboer; G. Homuth (Georg); J.J. Hottenga (Jouke Jan); M. Ikeda (Masashi); C.R. Jack Jr. (Clifford); S. Jenkinson (Sarah); R. Johnson (Robert); R. Kanai (Ryota); M. Keil (Maria); J.W. Kent (Jack W.); P. Kochunov (Peter); J.B. Kwok (John B.); S. Lawrie (Stephen); X. Liu (Xinmin); D.L. Longo (Dan L.); K.L. Mcmahon (Katie); E. Meisenzahl (Eva); I. Melle (Ingrid); S. Mohnke (Sebastian); G.W. Montgomery (Grant); J.C. Mostert (Jeanette C.); T.W. Mühleisen (Thomas); M.A. Nalls (Michael); T.E. Nichols (Thomas); L.G. Nilsson; M.M. Nöthen (Markus); K. Ohi (Kazutaka); R.L. Olvera (Rene); R. Perez-Iglesias (Rocio); G. Bruce Pike; S.G. Potkin (Steven); I. Reinvang (Ivar); S. Reppermund; M. Rietschel (Marcella); N. Seiferth (Nina); G.D. Rosen (Glenn D.); D. Rujescu (Dan); K. Schnell (Kerry); C.J. Schofield (Christopher); C. Smith (Colin); V.M. Steen (Vidar); J. Sussmann (Jessika); A. Thalamuthu (Anbupalam); A.W. Toga (Arthur W.); B. Traynor (Bryan); J.C. Troncoso (Juan); J. Turner (Jessica); M.C. Valdés Hernández (Maria); D. van 't Ent (Dennis); M.P. van der Brug (Marcel); N.J. van der Wee (Nic); M.J.D. van Tol (Marie-José); D.J. Veltman (Dick); A.M.J. Wassink (Annemarie); E. Westman (Eric); R.H. Zielke (Ronald H.); A.B. Zonderman (Alan B.); D.G. Ashbrook (David G.); R. Hager (Reinmar); L. Lu (Lu); F.J. Mcmahon (Francis J); D.W. Morris (Derek W); R.W. Williams (Robert W.); H.G. Brunner; M. Buckner; J.K. Buitelaar (Jan K.); W. Cahn (Wiepke); V.D. Calhoun Vince D. (V.); G. Cavalleri (Gianpiero); B. Crespo-Facorro (Benedicto); A.M. Dale (Anders); G.E. Davies (Gareth); N. Delanty; C. Depondt (Chantal); S. Djurovic (Srdjan); D.A. Drevets (Douglas); T. Espeseth (Thomas); R.L. Gollub (Randy); B.C. Ho (Beng ); W. Hoffmann (Wolfgang); N. Hosten (Norbert); R. Kahn (René); S. Le Hellard (Stephanie); A. Meyer-Lindenberg; B. Müller-Myhsok (B.); M. Nauck (Matthias); L. Nyberg (Lars); M. Pandolfo (Massimo); B.W.J.H. Penninx (Brenda); J.L. Roffman (Joshua); S.M. Sisodiya (Sanjay); J.W. Smoller; H. van Bokhoven (Hans); N.E.M. van Haren (Neeltje E.); H. Völzke (Henry); H.J. Walter (Henrik); M.W. Weiner (Michael); W. Wen (Wei); T.J.H. White (Tonya); I. Agartz (Ingrid); O.A. Andreassen (Ole); J. Blangero (John); D.I. Boomsma (Dorret); R.M. Brouwer (Rachel); D.M. Cannon (Dara); M.R. Cookson (Mark); E.J.C. de Geus (Eco); I.J. Deary (Ian J.); D.J. Donohoe (Dennis); G. Fernandez (Guillén); S.E. Fisher (Simon); C. Francks (Clyde); D.C. Glahn (David); H.J. Grabe (Hans Jörgen); O. Gruber (Oliver); J. Hardy (John); R. Hashimoto (Ryota); H.E. Hulshoff Pol (Hilleke); E.G. Jönsson (Erik); I. Kloszewska (Iwona); S. Lovestone (Simon); V.S. Mattay (Venkata S.); P. Mecocci (Patrizia); C. McDonald (Colm); A.M. McIntosh (Andrew); R.A. Ophoff (Roel); T. Paus (Tomas); Z. Pausova (Zdenka); M. Ryten (Mina); P.S. Sachdev (Perminder); A.J. Saykin (Andrew); A. Simmons (Andrew); A. Singleton (Andrew); H. Soininen (H.); J.M. Wardlaw (J.); M.E. Weale (Michael); D.R. Weinberger (Daniel); H.H.H. Adams (Hieab); L.J. Launer (Lenore); S. Seiler (Stephan); R. Schmidt (Reinhold); G. Chauhan (Ganesh); C.L. Satizabal (Claudia L.); J.T. Becker (James); L.R. Yanek (Lisa); S.J. van der Lee (Sven); M. Ebling (Maritza); B. Fischl (Bruce); W.T. Longstreth Jr; D. Greve (Douglas); R. Schmidt (Reinhold); P. Nyquist (Paul); L.N. Vinke (Louis N.); C.M. van Duijn (Cornelia); L. Xue (Luting); B. Mazoyer (Bernard); J.C. Bis (Joshua); V. Gudnason (Vilmundur); S. Seshadri (Sudha); M.A. Ikram (Arfan); N.G. Martin (Nicholas); M.J. Wright (Margaret); G. Schumann (Gunter); B. Franke (Barbara); P.M. Thompson (Paul); S.E. Medland (Sarah Elizabeth)

    2015-01-01

    textabstractThe highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate

  15. Common genetic variants influence human subcortical brain structures

    NARCIS (Netherlands)

    Hibar, Derrek P.; Stein, Jason L.; Renteria, Miguel E.; Arias-Vasquez, Alejandro; Desrivieres, Sylvane; Jahanshad, Neda; Toro, Roberto; Wittfeld, Katharina; Abramovic, Lucija; Andersson, Micael; Aribisala, Benjamin S.; Armstrong, Nicola J.; Bernard, Manon; Bohlken, Marc M.; Boks, Marco P.; Bralten, Janita; Brown, Andrew A.; Chakravarty, M. Mallar; Chen, Qiang; Ching, Christopher R. K.; Cuellar-Partida, Gabriel; den Braber, Anouk; Giddaluru, Sudheer; Goldman, Aaron L.; Grimm, Oliver; Guadalupe, Tulio; Hass, Johanna; Woldehawariat, Girma; Holmes, Avram J.; Hoogman, Martine; Janowitz, Deborah; Jia, Tianye; Kim, Sungeun; Klein, Marieke; Kraemer, Bernd; Lee, Phil H.; Loohuis, Loes M. Olde; Luciano, Michelle; Macare, Christine; Mather, Karen A.; Mattheisen, Manuel; Milaneschi, Yuri; Nho, Kwangsik; Papmeyer, Martina; Ramasamy, Adaikalavan; Risacher, Shannon L.; Roiz-Santianez, Roberto; Rose, Emma J.; Salami, Alireza; Saemann, Philipp G.; Schmaal, Lianne; Schork, Andrew J.; Shin, Jean; Strike, Lachlan T.; Teumer, Alexander; van Donkelaar, Marjolein M. J.; van Eijk, Kristel R.; Walters, Raymond K.; Westlye, Lars T.; Whelan, Christopher D.; Winkler, Anderson M.; Zwiers, Marcel P.; Alhusaini, Saud; Athanasiu, Lavinia; Ehrlich, Stefan; Hakobjan, Marina M. H.; Hartberg, Cecilie B.; Haukvik, Unn K.; Heister, Angelien J. G. A. M.; Hoehn, David; Kasperaviciute, Dalia; Liewald, David C. M.; Lopez, Lorna M.; Makkinje, Remco R. R.; Matarin, Mar; Naber, Marlies A. M.; McKay, D. Reese; Needham, Margaret; Nugent, Allison C.; Puetz, Benno; Royle, Natalie A.; Shen, Li; Sprooten, Emma; Trabzuni, Daniah; van der Marel, Saskia S. L.; van Hulzen, Kimm J. E.; Walton, Esther; Wolf, Christiane; Almasy, Laura; Ames, David; Arepalli, Sampath; Assareh, Amelia A.; Bastin, Mark E.; Brodaty, Henry; Bulayeva, Kazima B.; Carless, Melanie A.; Cichon, Sven; Corvin, Aiden; Curran, Joanne E.; Czisch, Michael; de Zubicaray, Greig I.; Dillman, Allissa; Duggirala, Ravi; Dyer, Thomas D.; Erk, Susanne; Fedko, Iryna O.; Ferrucci, Luigi; Foroud, Tatiana M.; Fox, Peter T.; Fukunaga, Masaki; Gibbs, J. Raphael; Goering, Harald H. H.; Green, Robert C.; Guelfi, Sebastian; Hansell, Narelle K.; Hartman, Catharina A.; Hegenscheid, Katrin; Heinz, Andreas; Hernandez, Dena G.; Heslenfeld, Dirk J.; Hoekstra, Pieter J.; Holsboer, Florian; Homuth, Georg; Hottenga, Jouke-Jan; Ikeda, Masashi; Jack, Clifford R.; Jenkinson, Mark; Johnson, Robert; Kanai, Ryota; Keil, Maria; Kent, Jack W.; Kochunov, Peter; Kwok, John B.; Lawrie, Stephen M.; Liu, Xinmin; Longo, Dan L.; McMahon, Katie L.; Meisenzah, Eva; Melle, Ingrid; Mahnke, Sebastian; Montgomery, Grant W.; Mostert, Jeanette C.; Muehleisen, Thomas W.; Nalls, Michael A.; Nichols, Thomas E.; Nilsson, Lars G.; Noethen, Markus M.; Ohi, Kazutaka; Olvera, Rene L.; Perez-Iglesias, Rocio; Pike, G. Bruce; Potkin, Steven G.; Reinvang, Ivar; Reppermund, Simone; Rietschel, Marcella; Romanczuk-Seiferth, Nina; Rosen, Glenn D.; Rujescu, Dan; Schnell, Knut; Schofield, Peter R.; Smith, Colin; Steen, Vidar M.; Sussmann, Jessika E.; Thalamuthu, Anbupalam; Toga, Arthur W.; Traynor, Bryan J.; Troncoso, Juan; Turner, Jessica A.; Valdes Hernandez, Maria C.; van't Ent, Dennis; van der Brug, Marcel; van der Wee, Nic J. A.; van Tol, Marie-Jose; Veltman, Dick J.; Wassink, Thomas H.; Westman, Eric; Zielke, Ronald H.; Zonderman, Alan B.; Ashbrook, David G.; Hager, Reinmar; Lu, Lu; McMahon, Francis J.; Morris, Derek W.; Williams, Robert W.; Brunner, Han G.; Buckner, Randy L.; Buitelaar, Jan K.; Cahn, Wiepke; Calhoun, Vince D.; Cavalleri, Gianpiero L.; Crespo-Facorro, Benedicto; Dale, Anders M.; Davies, Gareth E.; Delanty, Norman; Depondt, Chantal; Djurovic, Srdjan; Drevets, Wayne C.; Espeseth, Thomas; Gollub, Randy L.; Ho, Beng-Choon; Hoffman, Wolfgang; Hosten, Norbert; Kahn, Rene S.; Le Hellard, Stephanie; Meyer-Lindenberg, Andreas; Mueller-Myhsok, Bertram; Nauck, Matthias; Nyberg, Lars; Pandolfo, Massimo; Penninx, Brenda W. J. H.; Roffman, Joshua L.; Sisodiya, Sanjay M.; Smoller, Jordan W.; van Bokhoven, Hans; van Haren, Neeltje E. M.; Voelzke, Henry; Walter, Henrik; Weiner, Michael W.; Wen, Wei; White, Tonya; Agartz, Ingrid; Andreassen, Ole A.; Blangero, John; Boomsma, Dorret I.; Brouwer, Rachel M.; Cannon, Dara M.; Cookson, Mark R.; de Geus, Eco J. C.; Deary, Ian J.; Donohoe, Gary; Fernandez, Guillen; Fisher, Simon E.; Francks, Clyde; Glahn, David C.; Grabe, Hans J.; Gruber, Oliver; Hardy, John; Hashimoto, Ryota; Pol, Hilleke E. Hulshoff; Joensson, Erik G.; Kloszewska, Iwona; Lovestone, Simon; Mattay, Venkata S.; Mecocci, Patrizia; McDonald, Colm; McIntosh, Andrew M.; Ophoff, Roel A.; Paus, Tomas; Pausova, Zdenka; Ryten, Mina; Sachdev, Perminder S.; Saykin, Andrew J.; Simmons, Andy; Singleton, Andrew; Soininen, Hilkka; Wardlaw, Joanna M.; Weale, Michael E.; Weinberger, Daniel R.; Adams, Hieab H. H.; Launer, Lenore J.; Seiler, Stephan; Schmidt, Reinhold; Chauhan, Ganesh; Satizabal, Claudia L.; Becker, James T.; Yanek, Lisa; van der Lee, Sven J.; Ebling, Maritza; Fischl, Bruce; Longstreth, W. T.; Greve, Douglas; Schmidt, Helena; Nyquist, Paul; Vinke, Louis N.; van Duijn, Cornelia M.; Xue, Luting; Mazoyer, Bernard; Bis, Joshua C.; Gudnason, Vilmundur; Seshadri, Sudha; Ikram, M. Arfan; Martin, Nicholas G.; Wright, Margaret J.; Schumann, Gunter; Franke, Barbara; Thompson, Paul M.; Medland, Sarah E.

    2015-01-01

    The highly complex structure of the human brain is strongly shaped by genetic influences(1). Subcortical brain regions form circuits with cortical areas to coordinate movement(2), learning, memory(3) and motivation(4), and altered circuits can lead to abnormal behaviour and disease(5). To

  16. Human Learning and Memory

    Science.gov (United States)

    Lieberman, David A.

    2012-01-01

    This innovative textbook is the first to integrate learning and memory, behaviour, and cognition. It focuses on fascinating human research in both memory and learning (while also bringing in important animal studies) and brings the reader up to date with the latest developments in the subject. Students are encouraged to think critically: key…

  17. Spontaneous brain activity predicts learning ability of foreign sounds.

    Science.gov (United States)

    Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

    2013-05-29

    Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

  18. [Evolution of human brain and intelligence].

    Science.gov (United States)

    Lakatos, László; Janka, Zoltán

    2008-07-30

    The biological evolution, including human evolution is mainly driven by environmental changes. Accidental genetic modifications and their innovative results make the successful adaptation possible. As we know the human evolution started 7-8 million years ago in the African savannah, where upright position and bipedalism were significantly advantageous. The main drive of improving manual actions and tool making could be to obtain more food. Our ancestor got more meat due to more successful hunting, resulting in more caloric intake, more protein and essential fatty acid in the meal. The nervous system uses disproportionally high level of energy, so better quality of food was a basic condition for the evolution of huge human brain. The size of human brain was tripled during 3.5 million years, it increased from the average of 450 cm3 of Australopithecinae to the average of 1350 cm3 of Homo sapiens. A genetic change in the system controlling gene expression could happen about 200 000 years ago, which influenced the development of nervous system, the sensorimotor function and learning ability for motor processes. The appearance and stabilisation of FOXP2 gene structure as feature of modern man coincided with the first presence and quick spread of Homo sapiens on the whole Earth. This genetic modification made opportunity for human language, as the basis of abrupt evolution of human intelligence. The brain region being responsible for human language is the left planum temporale, which is much larger in left hemisphere. This shows the most typical human brain asymmetry. In this case the anatomical asymmetry means a clearly defined functional asymmetry as well, where the brain hemispheres act differently. The preference in using hands, the lateralised using of tools resulted in the brain asymmetry, which is the precondition of human language and intelligence. However, it cannot be held anymore, that only humans make tools, because our closest relatives, the chimpanzees are

  19. Learning-related brain hemispheric dominance in sleeping songbirds.

    Science.gov (United States)

    Moorman, Sanne; Gobes, Sharon M H; van de Kamp, Ferdinand C; Zandbergen, Matthijs A; Bolhuis, Johan J

    2015-03-12

    There are striking behavioural and neural parallels between the acquisition of speech in humans and song learning in songbirds. In humans, language-related brain activation is mostly lateralised to the left hemisphere. During language acquisition in humans, brain hemispheric lateralisation develops as language proficiency increases. Sleep is important for the formation of long-term memory, in humans as well as in other animals, including songbirds. Here, we measured neuronal activation (as the expression pattern of the immediate early gene ZENK) during sleep in juvenile zebra finch males that were still learning their songs from a tutor. We found that during sleep, there was learning-dependent lateralisation of spontaneous neuronal activation in the caudomedial nidopallium (NCM), a secondary auditory brain region that is involved in tutor song memory, while there was right hemisphere dominance of neuronal activation in HVC (used as a proper name), a premotor nucleus that is involved in song production and sensorimotor learning. Specifically, in the NCM, birds that imitated their tutors well were left dominant, while poor imitators were right dominant, similar to language-proficiency related lateralisation in humans. Given the avian-human parallels, lateralised neural activation during sleep may also be important for speech and language acquisition in human infants.

  20. Learning-related brain hemispheric dominance in sleeping songbirds

    Science.gov (United States)

    Moorman, Sanne; Gobes, Sharon M. H.; van de Kamp, Ferdinand C.; Zandbergen, Matthijs A.; Bolhuis, Johan J.

    2015-01-01

    There are striking behavioural and neural parallels between the acquisition of speech in humans and song learning in songbirds. In humans, language-related brain activation is mostly lateralised to the left hemisphere. During language acquisition in humans, brain hemispheric lateralisation develops as language proficiency increases. Sleep is important for the formation of long-term memory, in humans as well as in other animals, including songbirds. Here, we measured neuronal activation (as the expression pattern of the immediate early gene ZENK) during sleep in juvenile zebra finch males that were still learning their songs from a tutor. We found that during sleep, there was learning-dependent lateralisation of spontaneous neuronal activation in the caudomedial nidopallium (NCM), a secondary auditory brain region that is involved in tutor song memory, while there was right hemisphere dominance of neuronal activation in HVC (used as a proper name), a premotor nucleus that is involved in song production and sensorimotor learning. Specifically, in the NCM, birds that imitated their tutors well were left dominant, while poor imitators were right dominant, similar to language-proficiency related lateralisation in humans. Given the avian-human parallels, lateralised neural activation during sleep may also be important for speech and language acquisition in human infants. PMID:25761654

  1. Sexual differences of human brain

    Directory of Open Access Journals (Sweden)

    Masoud Pezeshki Rad

    2014-04-01

    Full Text Available During the last decades there has been an increasing interest in studying the differences between males and females. These differences extend from behavioral to cognitive to micro- and macro- neuro-anatomical aspects of human biology. There have been many methods to evaluate these differences and explain their determinants. The most studied cause of this dimorphism is the prenatal sex hormones and their organizational effect on brain and behavior. However, there have been new and recent attentions to hormone's activational influences in puberty and also the effects of genomic imprinting. In this paper, we reviewed the sex differences of brain, the evidences for possible determinants of these differences and also the methods that have been used to discover them. We reviewed the most conspicuous findings with specific attention to macro-anatomical differences based on Magnetic Resonance Imaging (MRI data. We finally reviewed the findings and the many opportunities for future studies.

  2. Brain mechanisms underlying human communication

    Directory of Open Access Journals (Sweden)

    Matthijs L Noordzij

    2009-07-01

    Full Text Available Human communication has been described as involving the coding-decoding of a conventional symbol system, which could be supported by parts of the human motor system (i.e. the “mirror neurons system”. However, this view does not explain how these conventions could develop in the first place. Here we target the neglected but crucial issue of how people organize their non-verbal behavior to communicate a given intention without pre-established conventions. We have measured behavioral and brain responses in pairs of subjects during communicative exchanges occurring in a real, interactive, on-line social context. In two fMRI studies, we found robust evidence that planning new communicative actions (by a sender and recognizing the communicative intention of the same actions (by a receiver relied on spatially overlapping portions of their brains (the right posterior superior temporal sulcus. The response of this region was lateralized to the right hemisphere, modulated by the ambiguity in meaning of the communicative acts, but not by their sensorimotor complexity. These results indicate that the sender of a communicative signal uses his own intention recognition system to make a prediction of the intention recognition performed by the receiver. This finding supports the notion that our communicative abilities are distinct from both sensorimotor processes and language abilities.

  3. Brain mechanisms underlying human communication.

    Science.gov (United States)

    Noordzij, Matthijs L; Newman-Norlund, Sarah E; de Ruiter, Jan Peter; Hagoort, Peter; Levinson, Stephen C; Toni, Ivan

    2009-01-01

    Human communication has been described as involving the coding-decoding of a conventional symbol system, which could be supported by parts of the human motor system (i.e. the "mirror neurons system"). However, this view does not explain how these conventions could develop in the first place. Here we target the neglected but crucial issue of how people organize their non-verbal behavior to communicate a given intention without pre-established conventions. We have measured behavioral and brain responses in pairs of subjects during communicative exchanges occurring in a real, interactive, on-line social context. In two fMRI studies, we found robust evidence that planning new communicative actions (by a sender) and recognizing the communicative intention of the same actions (by a receiver) relied on spatially overlapping portions of their brains (the right posterior superior temporal sulcus). The response of this region was lateralized to the right hemisphere, modulated by the ambiguity in meaning of the communicative acts, but not by their sensorimotor complexity. These results indicate that the sender of a communicative signal uses his own intention recognition system to make a prediction of the intention recognition performed by the receiver. This finding supports the notion that our communicative abilities are distinct from both sensorimotor processes and language abilities.

  4. Brain Evolution and Human Neuropsychology: The Inferential Brain Hypothesis

    Science.gov (United States)

    Koscik, Timothy R.; Tranel, Daniel

    2013-01-01

    Collaboration between human neuropsychology and comparative neuroscience has generated invaluable contributions to our understanding of human brain evolution and function. Further cross-talk between these disciplines has the potential to continue to revolutionize these fields. Modern neuroimaging methods could be applied in a comparative context, yielding exciting new data with the potential of providing insight into brain evolution. Conversely, incorporating an evolutionary base into the theoretical perspectives from which we approach human neuropsychology could lead to novel hypotheses and testable predictions. In the spirit of these objectives, we present here a new theoretical proposal, the Inferential Brain Hypothesis, whereby the human brain is thought to be characterized by a shift from perceptual processing to inferential computation, particularly within the social realm. This shift is believed to be a driving force for the evolution of the large human cortex. PMID:22459075

  5. Lipid transport and human brain development.

    Science.gov (United States)

    Betsholtz, Christer

    2015-07-01

    How the human brain rapidly builds up its lipid content during brain growth and maintains its lipids in adulthood has remained elusive. Two new studies show that inactivating mutations in MFSD2A, known to be expressed specifically at the blood-brain barrier, lead to microcephaly, thereby offering a simple and surprising solution to an old enigma.

  6. Implicit learning of predictable sound sequences modulates human brain responses at different levels of the auditory hierarchy

    Directory of Open Access Journals (Sweden)

    Françoise eLecaignard

    2015-09-01

    Full Text Available Deviant stimuli, violating regularities in a sensory environment, elicit the Mismatch Negativity (MMN, largely described in the Event-Related Potential literature. While it is widely accepted that the MMN reflects more than basic change detection, a comprehensive description of mental processes modulating this response is still lacking. Within the framework of predictive coding, deviance processing is part of an inference process where prediction errors (the mismatch between incoming sensations and predictions established through experience are minimized. In this view, the MMN is a measure of prediction error, which yields specific expectations regarding its modulations by various experimental factors. In particular, it predicts that the MMN should decrease as the occurrence of a deviance becomes more predictable. We conducted a passive oddball EEG study and manipulated the predictability of sound sequences by means of different temporal structures. Importantly, our design allows comparing mismatch responses elicited by predictable and unpredictable violations of a simple repetition rule and therefore departs from previous studies that investigate violations of different time-scale regularities. We observed a decrease of the MMN with predictability and interestingly, a similar effect at earlier latencies, within 70 ms after deviance onset. Following these pre-attentive responses, a reduced P3a was measured in the case of predictable deviants. We conclude that early and late deviance responses reflect prediction errors, triggering belief updating within the auditory hierarchy. Beside, in this passive study, such perceptual inference appears to be modulated by higher-level implicit learning of sequence statistical structures. Our findings argue for a hierarchical model of auditory processing where predictive coding enables implicit extraction of environmental regularities.

  7. Human brain lesion-deficit inference remapped.

    Science.gov (United States)

    Mah, Yee-Haur; Husain, Masud; Rees, Geraint; Nachev, Parashkev

    2014-09-01

    . Positively, we show that novel machine learning techniques employing high-dimensional inference can nonetheless accurately converge on the true locus. We conclude that current inferences about human brain function and deficits based on lesion mapping must be re-evaluated with methodology that adequately captures the high-dimensional structure of lesion data. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

  8. Introduction to machine learning for brain imaging.

    Science.gov (United States)

    Lemm, Steven; Blankertz, Benjamin; Dickhaus, Thorsten; Müller, Klaus-Robert

    2011-05-15

    Machine learning and pattern recognition algorithms have in the past years developed to become a working horse in brain imaging and the computational neurosciences, as they are instrumental for mining vast amounts of neural data of ever increasing measurement precision and detecting minuscule signals from an overwhelming noise floor. They provide the means to decode and characterize task relevant brain states and to distinguish them from non-informative brain signals. While undoubtedly this machinery has helped to gain novel biological insights, it also holds the danger of potential unintentional abuse. Ideally machine learning techniques should be usable for any non-expert, however, unfortunately they are typically not. Overfitting and other pitfalls may occur and lead to spurious and nonsensical interpretation. The goal of this review is therefore to provide an accessible and clear introduction to the strengths and also the inherent dangers of machine learning usage in the neurosciences. Copyright © 2010 Elsevier Inc. All rights reserved.

  9. Dissociable Learning Processes Underlie Human Pain Conditioning.

    Science.gov (United States)

    Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben

    2016-01-11

    Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection [1], escape and avoidance learning [2], and endogenous analgesia [3]. Although a central role for the amygdala is well established [4], both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum [5]. It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Brain Activity and Human Unilateral Chewing

    Science.gov (United States)

    Quintero, A.; Ichesco, E.; Myers, C.; Schutt, R.; Gerstner, G.E.

    2012-01-01

    Brain mechanisms underlying mastication have been studied in non-human mammals but less so in humans. We used functional magnetic resonance imaging (fMRI) to evaluate brain activity in humans during gum chewing. Chewing was associated with activations in the cerebellum, motor cortex and caudate, cingulate, and brainstem. We also divided the 25-second chew-blocks into 5 segments of equal 5-second durations and evaluated activations within and between each of the 5 segments. This analysis revealed activation clusters unique to the initial segment, which may indicate brain regions involved with initiating chewing. Several clusters were uniquely activated during the last segment as well, which may represent brain regions involved with anticipatory or motor events associated with the end of the chew-block. In conclusion, this study provided evidence for specific brain areas associated with chewing in humans and demonstrated that brain activation patterns may dynamically change over the course of chewing sequences. PMID:23103631

  11. Quantitative Machine Learning Analysis of Brain MRI Morphology throughout Aging.

    Science.gov (United States)

    Shamir, Lior; Long, Joe

    2016-01-01

    While cognition is clearly affected by aging, it is unclear whether the process of brain aging is driven solely by accumulation of environmental damage, or involves biological pathways. We applied quantitative image analysis to profile the alteration of brain tissues during aging. A dataset of 463 brain MRI images taken from a cohort of 416 subjects was analyzed using a large set of low-level numerical image content descriptors computed from the entire brain MRI images. The correlation between the numerical image content descriptors and the age was computed, and the alterations of the brain tissues during aging were quantified and profiled using machine learning. The comprehensive set of global image content descriptors provides high Pearson correlation of ~0.9822 with the chronological age, indicating that the machine learning analysis of global features is sensitive to the age of the subjects. Profiling of the predicted age shows several periods of mild changes, separated by shorter periods of more rapid alterations. The periods with the most rapid changes were around the age of 55, and around the age of 65. The results show that the process of brain aging of is not linear, and exhibit short periods of rapid aging separated by periods of milder change. These results are in agreement with patterns observed in cognitive decline, mental health status, and general human aging, suggesting that brain aging might not be driven solely by accumulation of environmental damage. Code and data used in the experiments are publicly available.

  12. Brain anatomical networks in early human brain development.

    Science.gov (United States)

    Fan, Yong; Shi, Feng; Smith, Jeffrey Keith; Lin, Weili; Gilmore, John H; Shen, Dinggang

    2011-02-01

    Recent neuroimaging studies have demonstrated that human brain networks have economic small-world topology and modular organization, enabling efficient information transfer among brain regions. However, it remains largely unknown how the small-world topology and modular organization of human brain networks emerge and develop. Using longitudinal MRI data of 28 healthy pediatric subjects, collected at their ages of 1 month, 1 year, and 2 years, we analyzed development patterns of brain anatomical networks derived from morphological correlations of brain regional volumes. The results show that the brain network of 1-month-olds has the characteristically economic small-world topology and nonrandom modular organization. The network's cost efficiency increases with the brain development to 1 year and 2 years, so does the modularity, providing supportive evidence for the hypothesis that the small-world topology and the modular organization of brain networks are established during early brain development to support rapid synchronization and information transfer with minimal rewiring cost, as well as to balance between local processing and global integration of information. Copyright © 2010. Published by Elsevier Inc.

  13. Computational Intelligence in a Human Brain Model

    Directory of Open Access Journals (Sweden)

    Viorel Gaftea

    2016-06-01

    Full Text Available This paper focuses on the current trends in brain research domain and the current stage of development of research for software and hardware solutions, communication capabilities between: human beings and machines, new technologies, nano-science and Internet of Things (IoT devices. The proposed model for Human Brain assumes main similitude between human intelligence and the chess game thinking process. Tactical & strategic reasoning and the need to follow the rules of the chess game, all are very similar with the activities of the human brain. The main objective for a living being and the chess game player are the same: securing a position, surviving and eliminating the adversaries. The brain resolves these goals, and more, the being movement, actions and speech are sustained by the vital five senses and equilibrium. The chess game strategy helps us understand the human brain better and easier replicate in the proposed ‘Software and Hardware’ SAH Model.

  14. A Well Designed School Environment Facilitates Brain Learning.

    Science.gov (United States)

    Chan, Tak Cheung; Petrie, Garth

    2000-01-01

    Examines how school design facilitates learning by complementing how the brain learns. How the brain learns is discussed and how an artistic environment, spaciousness in the learning areas, color and lighting, and optimal thermal and acoustical environments aid student learning. School design suggestions conclude the article. (GR)

  15. Applying Brain-Based Learning Principles to Athletic Training Education

    Science.gov (United States)

    Craig, Debbie I.

    2007-01-01

    Objective: To present different concepts and techniques related to the application of brain-based learning principles to Athletic Training clinical education. Background: The body of knowledge concerning how our brains physically learn continues to grow. Brain-based learning principles, developed by numerous authors, offer advice on how to…

  16. The bilingual brain: Flexibility and control in the human cortex

    Science.gov (United States)

    Buchweitz, Augusto; Prat, Chantel

    2013-12-01

    The goal of the present review is to discuss recent cognitive neuroscientific findings concerning bilingualism. Three interrelated questions about the bilingual brain are addressed: How are multiple languages represented in the brain? how are languages controlled in the brain? and what are the real-world implications of experience with multiple languages? The review is based on neuroimaging research findings about the nature of bilingual processing, namely, how the brain adapts to accommodate multiple languages in the bilingual brain and to control which language should be used, and when. We also address how this adaptation results in differences observed in the general cognition of bilingual individuals. General implications for models of human learning, plasticity, and cognitive control are discussed.

  17. Male microchimerism in the human female brain.

    Directory of Open Access Journals (Sweden)

    William F N Chan

    Full Text Available In humans, naturally acquired microchimerism has been observed in many tissues and organs. Fetal microchimerism, however, has not been investigated in the human brain. Microchimerism of fetal as well as maternal origin has recently been reported in the mouse brain. In this study, we quantified male DNA in the human female brain as a marker for microchimerism of fetal origin (i.e. acquisition of male DNA by a woman while bearing a male fetus. Targeting the Y-chromosome-specific DYS14 gene, we performed real-time quantitative PCR in autopsied brain from women without clinical or pathologic evidence of neurologic disease (n=26, or women who had Alzheimer's disease (n=33. We report that 63% of the females (37 of 59 tested harbored male microchimerism in the brain. Male microchimerism was present in multiple brain regions. Results also suggested lower prevalence (p=0.03 and concentration (p=0.06 of male microchimerism in the brains of women with Alzheimer's disease than the brains of women without neurologic disease. In conclusion, male microchimerism is frequent and widely distributed in the human female brain.

  18. Decade of the Brain 1990--2000: Maximizing human potential

    Energy Technology Data Exchange (ETDEWEB)

    1991-04-01

    The US Decade of the Brain offers scientists throughout the Federal Government a unique opportunity to advance and apply scientific knowledge about the brain and nervous system. During the next 10 years, scientists hope to maximize human potential through studies of human behavior, senses and communication, learning and memory, genetic/chemical alterations, and environmental interactions. Progress in these areas should lead to reductions in mortality from brain and nervous system disorders and to improvements in the quality of life. This report identifies nine research areas that could form the basis of an integrated program in the brain and behavioral sciences. A chart summarizing the Federal activities in these nine areas may be found at the back of the report. In addition, three areas that span the nine research areas -- basic research, technology and international activities -- are considered.

  19. Learning and motivation in the human striatum.

    Science.gov (United States)

    Shohamy, Daphna

    2011-06-01

    The past decade has seen a dramatic change in our understanding of the role of the striatum in behavior. Early perspectives emphasized a role for the striatum in habitual learning of stimulus-response associations and sequences of actions. Recent advances from human neuroimaging research suggest a broader role for the striatum in motivated learning. New findings demonstrate that the striatum represents multiple learning signals and highlight the contribution of the striatum across many cognitive domains and contexts. Recent findings also emphasize interactions between the striatum and other specialized brain systems for learning. Together, these findings suggest that the striatum contributes to a distributed network that learns to select actions based on their predicted value in order to optimize behavior. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Social learning through prediction error in the brain

    Science.gov (United States)

    Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

    2017-06-01

    Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

  1. Protein phosphorylation systems in postmortem human brain

    International Nuclear Information System (INIS)

    Walaas, S.I.; Perdahl-Wallace, E.; Winblad, B.; Greengard, P.

    1989-01-01

    Protein phosphorylation systems regulated by cyclic adenosine 3',5'-monophosphate (cyclic AMP), or calcium in conjunction with calmodulin or phospholipid/diacylglycerol, have been studied by phosphorylation in vitro of particulate and soluble fractions from human postmortem brain samples. One-dimensional or two-dimensional gel electrophoretic protein separations were used for analysis. Protein phosphorylation catalyzed by cyclic AMP-dependent protein kinase was found to be highly active in both particulate and soluble preparations throughout the human CNS, with groups of both widely distributed and region-specific substrates being observed in different brain nuclei. Dopamine-innervated parts of the basal ganglia and cerebral cortex contained the phosphoproteins previously observed in rodent basal ganglia. In contrast, calcium/phospholipid-dependent and calcium/calmodulin-dependent protein phosphorylation systems were less prominent in human postmortem brain than in rodent brain, and only a few widely distributed substrates for these protein kinases were found. Protein staining indicated that postmortem proteolysis, particularly of high-molecular-mass proteins, was prominent in deeply located, subcortical regions in the human brain. Our results indicate that it is feasible to use human postmortem brain samples, when obtained under carefully controlled conditions, for qualitative studies on brain protein phosphorylation. Such studies should be of value in studies on human neurological and/or psychiatric disorders

  2. Transcranial magnetic stimulation and the human brain

    Science.gov (United States)

    Hallett, Mark

    2000-07-01

    Transcranial magnetic stimulation (TMS) is rapidly developing as a powerful, non-invasive tool for studying the human brain. A pulsed magnetic field creates current flow in the brain and can temporarily excite or inhibit specific areas. TMS of motor cortex can produce a muscle twitch or block movement; TMS of occipital cortex can produce visual phosphenes or scotomas. TMS can also alter the functioning of the brain beyond the time of stimulation, offering potential for therapy.

  3. A hypothesis on improving foreign accents by optimizing variability in vocal learning brain circuits

    OpenAIRE

    Simmonds, Anna J.

    2015-01-01

    Rapid vocal motor learning is observed when acquiring a language in early childhood, or learning to speak another language later in life. Accurate pronunciation is one of the hardest things for late learners to master and they are almost always left with a non-native accent. Here, I propose a novel hypothesis that this accent could be improved by optimizing variability in vocal learning brain circuits during learning. Much of the neurobiology of human vocal motor learning has been inferred fr...

  4. The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI.

    Science.gov (United States)

    Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar

    2017-06-15

    Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one. High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005). The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided. The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method. Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. An introduction to human brain anatomy

    NARCIS (Netherlands)

    Forstmann, B.U.; Keuken, M.C.; Alkemade, A.; Forstmann, B.U.; Wagenmakers, E.-J.

    2015-01-01

    This tutorial chapter provides an overview of the human brain anatomy. Knowledge of brain anatomy is fundamental to our understanding of cognitive processes in health and disease; moreover, anatomical constraints are vital for neurocomputational models and can be important for psychological

  6. Tolerances of the human brain to concussion.

    Science.gov (United States)

    1971-03-01

    The report reviews the pertinent literature and adds additional evidence indicating that the human brain may be able to tolerate head impact forces in the range of 300 to 400 g's without evidence of concussion or other detectable neurologic sequelae,...

  7. Ionising radiation and the developing human brain

    International Nuclear Information System (INIS)

    Schull, W.J.

    1991-01-01

    This article reviews the effects of radiation exposure of the developing human brain. Much of the evidence has come from the prenatally exposed in Hiroshima and Nagasaki. The effects on development age, mental retardation, head size, neuromuscular performance, intelligence tests, school performance and the occurrence of convulsions are discussed. Other topics covered include the biological nature of the damage to the brain, risk estimates in human and problems in radiation protection. (UK)

  8. Supervised dictionary learning for inferring concurrent brain networks.

    Science.gov (United States)

    Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

    2015-10-01

    Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

  9. Analysis of a human brain transcriptome map

    Directory of Open Access Journals (Sweden)

    Greene Jonathan R

    2002-04-01

    Full Text Available Abstract Background Genome wide transcriptome maps can provide tools to identify candidate genes that are over-expressed or silenced in certain disease tissue and increase our understanding of the structure and organization of the genome. Expressed Sequence Tags (ESTs from the public dbEST and proprietary Incyte LifeSeq databases were used to derive a transcript map in conjunction with the working draft assembly of the human genome sequence. Results Examination of ESTs derived from brain tissues (excluding brain tumor tissues suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors. Conclusions This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.

  10. Dichoptic training enables the adult amblyopic brain to learn.

    Science.gov (United States)

    Li, Jinrong; Thompson, Benjamin; Deng, Daming; Chan, Lily Y L; Yu, Minbin; Hess, Robert F

    2013-04-22

    Adults with amblyopia, a common visual cortex disorder caused primarily by binocular disruption during an early critical period, do not respond to conventional therapy involving occlusion of one eye. But it is now clear that the adult human visual cortex has a significant degree of plasticity, suggesting that something must be actively preventing the adult brain from learning to see through the amblyopic eye. One possibility is an inhibitory signal from the contralateral eye that suppresses cortical inputs from the amblyopic eye. Such a gating mechanism could explain the apparent lack of plasticity within the adult amblyopic visual cortex. Here we provide direct evidence that alleviating suppression of the amblyopic eye through dichoptic stimulus presentation induces greater levels of plasticity than forced use of the amblyopic eye alone. This indicates that suppression is a key gating mechanism that prevents the amblyopic brain from learning to see. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Model brain based learning (BBL and whole brain teaching (WBT in learning

    Directory of Open Access Journals (Sweden)

    Baiq Sri Handayani

    2017-08-01

    Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical

  12. Human semi-supervised learning.

    Science.gov (United States)

    Gibson, Bryan R; Rogers, Timothy T; Zhu, Xiaojin

    2013-01-01

    Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and machine learning research, we explain how these semi-supervised techniques can be applied to human learning. A series of experiments are described which show that semi-supervised learning models prove useful for explaining human behavior when exposed to both labeled and unlabeled data. We then discuss some machine learning models that do not have familiar human categorization counterparts. Finally, we discuss some challenges yet to be addressed in the use of semi-supervised models for modeling human categorization. Copyright © 2013 Cognitive Science Society, Inc.

  13. Brain-Based Learning and Standards-Based Elementary Science.

    Science.gov (United States)

    Konecki, Loretta R.; Schiller, Ellen

    This paper explains how brain-based learning has become an area of interest to elementary school science teachers, focusing on the possible relationships between, and implications of, research on brain-based learning to the teaching of science education standards. After describing research on the brain, the paper looks at three implications from…

  14. Perceptual learning and human expertise.

    Science.gov (United States)

    Kellman, Philip J; Garrigan, Patrick

    2009-06-01

    We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

  15. Perceptual learning and human expertise

    Science.gov (United States)

    Kellman, Philip J.; Garrigan, Patrick

    2009-06-01

    We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

  16. The evolution of modern human brain shape.

    Science.gov (United States)

    Neubauer, Simon; Hublin, Jean-Jacques; Gunz, Philipp

    2018-01-01

    Modern humans have large and globular brains that distinguish them from their extinct Homo relatives. The characteristic globularity develops during a prenatal and early postnatal period of rapid brain growth critical for neural wiring and cognitive development. However, it remains unknown when and how brain globularity evolved and how it relates to evolutionary brain size increase. On the basis of computed tomographic scans and geometric morphometric analyses, we analyzed endocranial casts of Homo sapiens fossils ( N = 20) from different time periods. Our data show that, 300,000 years ago, brain size in early H. sapiens already fell within the range of present-day humans. Brain shape, however, evolved gradually within the H. sapiens lineage, reaching present-day human variation between about 100,000 and 35,000 years ago. This process started only after other key features of craniofacial morphology appeared modern and paralleled the emergence of behavioral modernity as seen from the archeological record. Our findings are consistent with important genetic changes affecting early brain development within the H. sapiens lineage since the origin of the species and before the transition to the Later Stone Age and the Upper Paleolithic that mark full behavioral modernity.

  17. The evolution of modern human brain shape

    Science.gov (United States)

    Neubauer, Simon; Hublin, Jean-Jacques; Gunz, Philipp

    2018-01-01

    Modern humans have large and globular brains that distinguish them from their extinct Homo relatives. The characteristic globularity develops during a prenatal and early postnatal period of rapid brain growth critical for neural wiring and cognitive development. However, it remains unknown when and how brain globularity evolved and how it relates to evolutionary brain size increase. On the basis of computed tomographic scans and geometric morphometric analyses, we analyzed endocranial casts of Homo sapiens fossils (N = 20) from different time periods. Our data show that, 300,000 years ago, brain size in early H. sapiens already fell within the range of present-day humans. Brain shape, however, evolved gradually within the H. sapiens lineage, reaching present-day human variation between about 100,000 and 35,000 years ago. This process started only after other key features of craniofacial morphology appeared modern and paralleled the emergence of behavioral modernity as seen from the archeological record. Our findings are consistent with important genetic changes affecting early brain development within the H. sapiens lineage since the origin of the species and before the transition to the Later Stone Age and the Upper Paleolithic that mark full behavioral modernity. PMID:29376123

  18. Robot learning from human teachers

    CERN Document Server

    Chernova, Sonia

    2014-01-01

    Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn f

  19. The Brain Prize 2014: complex human functions.

    Science.gov (United States)

    Grigaityte, Kristina; Iacoboni, Marco

    2014-11-01

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

  20. Lactate fuels the human brain during exercise

    DEFF Research Database (Denmark)

    Quistorff, Bjørn; Secher, Niels H; Van Lieshout, Johannes J

    2008-01-01

    The human brain releases a small amount of lactate at rest, and even an increase in arterial blood lactate during anesthesia does not provoke a net cerebral lactate uptake. However, during cerebral activation associated with exercise involving a marked increase in plasma lactate, the brain takes up......)] from a resting value of 6 to exercise, cerebral activation associated with mental activity, or exposure to a stressful situation. The CMR decrease is prevented with combined beta(1)- and beta(2)-adrenergic receptor...

  1. Development of a model for whole brain learning of physiology.

    Science.gov (United States)

    Eagleton, Saramarie; Muller, Anton

    2011-12-01

    In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed elaborates on these layers by relating the personality traits central to learning to the different quadrants of brain preference, as described by Neethling's brain profile, as the inner layer of the onion. This layer is encircled by the learning styles that describe different information-processing preferences for each brain quadrant. For the middle layer, the different stages of Kolb's learning cycle are classified into the four brain quadrants associated with the different brain processing strategies within the information processing circle. Each of the stages of Kolb's learning cycle is also associated with a specific cognitive learning strategy. These two inner circles are enclosed by the circle representing the role of the environment and instruction on learning. It relates environmental factors that affect learning and distinguishes between face-to-face and technology-assisted learning. This model informs on the design of instructional interventions for physiology to encourage whole brain learning.

  2. Common genetic variants influence human subcortical brain structures.

    Science.gov (United States)

    Hibar, Derrek P; Stein, Jason L; Renteria, Miguel E; Arias-Vasquez, Alejandro; Desrivières, Sylvane; Jahanshad, Neda; Toro, Roberto; Wittfeld, Katharina; Abramovic, Lucija; Andersson, Micael; Aribisala, Benjamin S; Armstrong, Nicola J; Bernard, Manon; Bohlken, Marc M; Boks, Marco P; Bralten, Janita; Brown, Andrew A; Chakravarty, M Mallar; Chen, Qiang; Ching, Christopher R K; Cuellar-Partida, Gabriel; den Braber, Anouk; Giddaluru, Sudheer; Goldman, Aaron L; Grimm, Oliver; Guadalupe, Tulio; Hass, Johanna; Woldehawariat, Girma; Holmes, Avram J; Hoogman, Martine; Janowitz, Deborah; Jia, Tianye; Kim, Sungeun; Klein, Marieke; Kraemer, Bernd; Lee, Phil H; Olde Loohuis, Loes M; Luciano, Michelle; Macare, Christine; Mather, Karen A; Mattheisen, Manuel; Milaneschi, Yuri; Nho, Kwangsik; Papmeyer, Martina; Ramasamy, Adaikalavan; Risacher, Shannon L; Roiz-Santiañez, Roberto; Rose, Emma J; Salami, Alireza; Sämann, Philipp G; Schmaal, Lianne; Schork, Andrew J; Shin, Jean; Strike, Lachlan T; Teumer, Alexander; van Donkelaar, Marjolein M J; van Eijk, Kristel R; Walters, Raymond K; Westlye, Lars T; Whelan, Christopher D; Winkler, Anderson M; Zwiers, Marcel P; Alhusaini, Saud; Athanasiu, Lavinia; Ehrlich, Stefan; Hakobjan, Marina M H; Hartberg, Cecilie B; Haukvik, Unn K; Heister, Angelien J G A M; Hoehn, David; Kasperaviciute, Dalia; Liewald, David C M; Lopez, Lorna M; Makkinje, Remco R R; Matarin, Mar; Naber, Marlies A M; McKay, D Reese; Needham, Margaret; Nugent, Allison C; Pütz, Benno; Royle, Natalie A; Shen, Li; Sprooten, Emma; Trabzuni, Daniah; van der Marel, Saskia S L; van Hulzen, Kimm J E; Walton, Esther; Wolf, Christiane; Almasy, Laura; Ames, David; Arepalli, Sampath; Assareh, Amelia A; Bastin, Mark E; Brodaty, Henry; Bulayeva, Kazima B; Carless, Melanie A; Cichon, Sven; Corvin, Aiden; Curran, Joanne E; Czisch, Michael; de Zubicaray, Greig I; Dillman, Allissa; Duggirala, Ravi; Dyer, Thomas D; Erk, Susanne; Fedko, Iryna O; Ferrucci, Luigi; Foroud, Tatiana M; Fox, Peter T; Fukunaga, Masaki; Gibbs, J Raphael; Göring, Harald H H; Green, Robert C; Guelfi, Sebastian; Hansell, Narelle K; Hartman, Catharina A; Hegenscheid, Katrin; Heinz, Andreas; Hernandez, Dena G; Heslenfeld, Dirk J; Hoekstra, Pieter J; Holsboer, Florian; Homuth, Georg; Hottenga, Jouke-Jan; Ikeda, Masashi; Jack, Clifford R; Jenkinson, Mark; Johnson, Robert; Kanai, Ryota; Keil, Maria; Kent, Jack W; Kochunov, Peter; Kwok, John B; Lawrie, Stephen M; Liu, Xinmin; Longo, Dan L; McMahon, Katie L; Meisenzahl, Eva; Melle, Ingrid; Mohnke, Sebastian; Montgomery, Grant W; Mostert, Jeanette C; Mühleisen, Thomas W; Nalls, Michael A; Nichols, Thomas E; Nilsson, Lars G; Nöthen, Markus M; Ohi, Kazutaka; Olvera, Rene L; Perez-Iglesias, Rocio; Pike, G Bruce; Potkin, Steven G; Reinvang, Ivar; Reppermund, Simone; Rietschel, Marcella; Romanczuk-Seiferth, Nina; Rosen, Glenn D; Rujescu, Dan; Schnell, Knut; Schofield, Peter R; Smith, Colin; Steen, Vidar M; Sussmann, Jessika E; Thalamuthu, Anbupalam; Toga, Arthur W; Traynor, Bryan J; Troncoso, Juan; Turner, Jessica A; Valdés Hernández, Maria C; van 't Ent, Dennis; van der Brug, Marcel; van der Wee, Nic J A; van Tol, Marie-Jose; Veltman, Dick J; Wassink, Thomas H; Westman, Eric; Zielke, Ronald H; Zonderman, Alan B; Ashbrook, David G; Hager, Reinmar; Lu, Lu; McMahon, Francis J; Morris, Derek W; Williams, Robert W; Brunner, Han G; Buckner, Randy L; Buitelaar, Jan K; Cahn, Wiepke; Calhoun, Vince D; Cavalleri, Gianpiero L; Crespo-Facorro, Benedicto; Dale, Anders M; Davies, Gareth E; Delanty, Norman; Depondt, Chantal; Djurovic, Srdjan; Drevets, Wayne C; Espeseth, Thomas; Gollub, Randy L; Ho, Beng-Choon; Hoffmann, Wolfgang; Hosten, Norbert; Kahn, René S; Le Hellard, Stephanie; Meyer-Lindenberg, Andreas; Müller-Myhsok, Bertram; Nauck, Matthias; Nyberg, Lars; Pandolfo, Massimo; Penninx, Brenda W J H; Roffman, Joshua L; Sisodiya, Sanjay M; Smoller, Jordan W; van Bokhoven, Hans; van Haren, Neeltje E M; Völzke, Henry; Walter, Henrik; Weiner, Michael W; Wen, Wei; White, Tonya; Agartz, Ingrid; Andreassen, Ole A; Blangero, John; Boomsma, Dorret I; Brouwer, Rachel M; Cannon, Dara M; Cookson, Mark R; de Geus, Eco J C; Deary, Ian J; Donohoe, Gary; Fernández, Guillén; Fisher, Simon E; Francks, Clyde; Glahn, David C; Grabe, Hans J; Gruber, Oliver; Hardy, John; Hashimoto, Ryota; Hulshoff Pol, Hilleke E; Jönsson, Erik G; Kloszewska, Iwona; Lovestone, Simon; Mattay, Venkata S; Mecocci, Patrizia; McDonald, Colm; McIntosh, Andrew M; Ophoff, Roel A; Paus, Tomas; Pausova, Zdenka; Ryten, Mina; Sachdev, Perminder S; Saykin, Andrew J; Simmons, Andy; Singleton, Andrew; Soininen, Hilkka; Wardlaw, Joanna M; Weale, Michael E; Weinberger, Daniel R; Adams, Hieab H H; Launer, Lenore J; Seiler, Stephan; Schmidt, Reinhold; Chauhan, Ganesh; Satizabal, Claudia L; Becker, James T; Yanek, Lisa; van der Lee, Sven J; Ebling, Maritza; Fischl, Bruce; Longstreth, W T; Greve, Douglas; Schmidt, Helena; Nyquist, Paul; Vinke, Louis N; van Duijn, Cornelia M; Xue, Luting; Mazoyer, Bernard; Bis, Joshua C; Gudnason, Vilmundur; Seshadri, Sudha; Ikram, M Arfan; Martin, Nicholas G; Wright, Margaret J; Schumann, Gunter; Franke, Barbara; Thompson, Paul M; Medland, Sarah E

    2015-04-09

    The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

  3. Brain mechanisms underlying human communication

    NARCIS (Netherlands)

    Noordzij, Matthijs Leendert; Newman-Norlund, Sarah E.; de Ruiter, Jan Peter; Hagoort, Peter; Levinson, Stephen C.; Toni, Ivan

    2009-01-01

    Human communication has been described as involving the coding-decoding of a conventional symbol system, which could be supported by parts of the human motor system (i.e. the “mirror neurons system”). However, this view does not explain how these conventions could develop in the first place. Here we

  4. Brain mechanisms underlying human communication

    NARCIS (Netherlands)

    Noordzij, M.L.; Newman-Norlund, S.E.; Ruiter, J.P.A. de; Hagoort, P.; Levinson, S.C.; Toni, I.

    2009-01-01

    Human communication has been described as involving the coding-decoding of a conventional symbol system, which could be supported by parts of the human motor system (i.e. the "mirror neurons system"). However, this view does not explain how these conventions could develop in the first place. Here we

  5. Unveiling the mystery of visual information processing in human brain.

    Science.gov (United States)

    Diamant, Emanuel

    2008-08-15

    It is generally accepted that human vision is an extremely powerful information processing system that facilitates our interaction with the surrounding world. However, despite extended and extensive research efforts, which encompass many exploration fields, the underlying fundamentals and operational principles of visual information processing in human brain remain unknown. We still are unable to figure out where and how along the path from eyes to the cortex the sensory input perceived by the retina is converted into a meaningful object representation, which can be consciously manipulated by the brain. Studying the vast literature considering the various aspects of brain information processing, I was surprised to learn that the respected scholarly discussion is totally indifferent to the basic keynote question: "What is information?" in general or "What is visual information?" in particular. In the old days, it was assumed that any scientific research approach has first to define its basic departure points. Why was it overlooked in brain information processing research remains a conundrum. In this paper, I am trying to find a remedy for this bizarre situation. I propose an uncommon definition of "information", which can be derived from Kolmogorov's Complexity Theory and Chaitin's notion of Algorithmic Information. Embracing this new definition leads to an inevitable revision of traditional dogmas that shape the state of the art of brain information processing research. I hope this revision would better serve the challenging goal of human visual information processing modeling.

  6. The human brain. Prenatal development and structure

    International Nuclear Information System (INIS)

    Marin-Padilla, Miguel

    2011-01-01

    This book is unique among the current literature in that it systematically documents the prenatal structural development of the human brain. It is based on lifelong study using essentially a single staining procedure, the classic rapid Golgi procedure, which ensures an unusual and desirable uniformity in the observations. The book is amply illustrated with 81 large, high-quality color photomicrographs never previously reproduced. These photomicrographs, obtained at 6, 7, 11, 15, 18, 20, 25, 30, 35, and 40 weeks of gestation, offer a fascinating insight into the sequential prenatal development of neurons, blood vessels, and glia in the human brain. (orig.)

  7. The human brain. Prenatal development and structure

    Energy Technology Data Exchange (ETDEWEB)

    Marin-Padilla, Miguel

    2011-07-01

    This book is unique among the current literature in that it systematically documents the prenatal structural development of the human brain. It is based on lifelong study using essentially a single staining procedure, the classic rapid Golgi procedure, which ensures an unusual and desirable uniformity in the observations. The book is amply illustrated with 81 large, high-quality color photomicrographs never previously reproduced. These photomicrographs, obtained at 6, 7, 11, 15, 18, 20, 25, 30, 35, and 40 weeks of gestation, offer a fascinating insight into the sequential prenatal development of neurons, blood vessels, and glia in the human brain. (orig.)

  8. Revisiting Glycogen Content in the Human Brain.

    Science.gov (United States)

    Öz, Gülin; DiNuzzo, Mauro; Kumar, Anjali; Moheet, Amir; Seaquist, Elizabeth R

    2015-12-01

    Glycogen provides an important glucose reservoir in the brain since the concentration of glucosyl units stored in glycogen is several fold higher than free glucose available in brain tissue. We have previously reported 3-4 µmol/g brain glycogen content using in vivo (13)C magnetic resonance spectroscopy (MRS) in conjunction with [1-(13)C]glucose administration in healthy humans, while higher levels were reported in the rodent brain. Due to the slow turnover of bulk brain glycogen in humans, complete turnover of the glycogen pool, estimated to take 3-5 days, was not observed in these prior studies. In an attempt to reach complete turnover and thereby steady state (13)C labeling in glycogen, here we administered [1-(13)C]glucose to healthy volunteers for 80 h. To eliminate any net glycogen synthesis during this period and thereby achieve an accurate estimate of glycogen concentration, volunteers were maintained at euglycemic blood glucose levels during [1-(13)C]glucose administration and (13)C-glycogen levels in the occipital lobe were measured by (13)C MRS approximately every 12 h. Finally, we fitted the data with a biophysical model that was recently developed to take into account the tiered structure of the glycogen molecule and additionally incorporated blood glucose levels and isotopic enrichments as input function in the model. We obtained excellent fits of the model to the (13)C-glycogen data, and glycogen content in the healthy human brain tissue was found to be 7.8 ± 0.3 µmol/g, a value substantially higher than previous estimates of glycogen content in the human brain.

  9. Brain-Computer Interfaces Revolutionizing Human-Computer Interaction

    CERN Document Server

    Graimann, Bernhard; Allison, Brendan

    2010-01-01

    A brain-computer interface (BCI) establishes a direct output channel between the human brain and external devices. BCIs infer user intent via direct measures of brain activity and thus enable communication and control without movement. This book, authored by experts in the field, provides an accessible introduction to the neurophysiological and signal-processing background required for BCI, presents state-of-the-art non-invasive and invasive approaches, gives an overview of current hardware and software solutions, and reviews the most interesting as well as new, emerging BCI applications. The book is intended not only for students and young researchers, but also for newcomers and other readers from diverse backgrounds keen to learn about this vital scientific endeavour.

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

    Science.gov (United States)

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

    2016-08-26

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

  11. Development of a Model for Whole Brain Learning of Physiology

    Science.gov (United States)

    Eagleton, Saramarie; Muller, Anton

    2011-01-01

    In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed…

  12. Brain activation during human male ejaculation

    NARCIS (Netherlands)

    Holstege, Ger; Georgiadis, Janniko R.; Paans, Anne M.J.; Meiners, Linda C.; Graaf, Ferdinand H.C.E. van der; Reinders, A.A.T.Simone

    2003-01-01

    Brain mechanisms that control human sexual behavior in general, and ejaculation in particular, are poorly understood. We used positron emission tomography to measure increases in regional cerebral blood flow (rCBF) during ejaculation compared with sexual stimulation in heterosexual male volunteers.

  13. Common genetic variants influence human subcortical brain structures

    Science.gov (United States)

    Hibar, Derrek P.; Stein, Jason L.; Renteria, Miguel E.; Arias-Vasquez, Alejandro; Desrivières, Sylvane; Jahanshad, Neda; Toro, Roberto; Wittfeld, Katharina; Abramovic, Lucija; Andersson, Micael; Aribisala, Benjamin S.; Armstrong, Nicola J.; Bernard, Manon; Bohlken, Marc M.; Boks, Marco P.; Bralten, Janita; Brown, Andrew A.; Chakravarty, M. Mallar; Chen, Qiang; Ching, Christopher R. K.; Cuellar-Partida, Gabriel; den Braber, Anouk; Giddaluru, Sudheer; Goldman, Aaron L.; Grimm, Oliver; Guadalupe, Tulio; Hass, Johanna; Woldehawariat, Girma; Holmes, Avram J.; Hoogman, Martine; Janowitz, Deborah; Jia, Tianye; Kim, Sungeun; Klein, Marieke; Kraemer, Bernd; Lee, Phil H.; Olde Loohuis, Loes M.; Luciano, Michelle; Macare, Christine; Mather, Karen A.; Mattheisen, Manuel; Milaneschi, Yuri; Nho, Kwangsik; Papmeyer, Martina; Ramasamy, Adaikalavan; Risacher, Shannon L.; Roiz-Santiañez, Roberto; Rose, Emma J.; Salami, Alireza; Sämann, Philipp G.; Schmaal, Lianne; Schork, Andrew J.; Shin, Jean; Strike, Lachlan T.; Teumer, Alexander; van Donkelaar, Marjolein M. J.; van Eijk, Kristel R.; Walters, Raymond K.; Westlye, Lars T.; Whelan, Christopher D.; Winkler, Anderson M.; Zwiers, Marcel P.; Alhusaini, Saud; Athanasiu, Lavinia; Ehrlich, Stefan; Hakobjan, Marina M. H.; Hartberg, Cecilie B.; Haukvik, Unn K.; Heister, Angelien J. G. A. M.; Hoehn, David; Kasperaviciute, Dalia; Liewald, David C. M.; Lopez, Lorna M.; Makkinje, Remco R. R.; Matarin, Mar; Naber, Marlies A. M.; McKay, D. Reese; Needham, Margaret; Nugent, Allison C.; Pütz, Benno; Royle, Natalie A.; Shen, Li; Sprooten, Emma; Trabzuni, Daniah; van der Marel, Saskia S. L.; van Hulzen, Kimm J. E.; Walton, Esther; Wolf, Christiane; Almasy, Laura; Ames, David; Arepalli, Sampath; Assareh, Amelia A.; Bastin, Mark E.; Brodaty, Henry; Bulayeva, Kazima B.; Carless, Melanie A.; Cichon, Sven; Corvin, Aiden; Curran, Joanne E.; Czisch, Michael; de Zubicaray, Greig I.; Dillman, Allissa; Duggirala, Ravi; Dyer, Thomas D.; Erk, Susanne; Fedko, Iryna O.; Ferrucci, Luigi; Foroud, Tatiana M.; Fox, Peter T.; Fukunaga, Masaki; Gibbs, J. Raphael; Göring, Harald H. H.; Green, Robert C.; Guelfi, Sebastian; Hansell, Narelle K.; Hartman, Catharina A.; Hegenscheid, Katrin; Heinz, Andreas; Hernandez, Dena G.; Heslenfeld, Dirk J.; Hoekstra, Pieter J.; Holsboer, Florian; Homuth, Georg; Hottenga, Jouke-Jan; Ikeda, Masashi; Jack, Clifford R.; Jenkinson, Mark; Johnson, Robert; Kanai, Ryota; Keil, Maria; Kent, Jack W.; Kochunov, Peter; Kwok, John B.; Lawrie, Stephen M.; Liu, Xinmin; Longo, Dan L.; McMahon, Katie L.; Meisenzahl, Eva; Melle, Ingrid; Mohnke, Sebastian; Montgomery, Grant W.; Mostert, Jeanette C.; Mühleisen, Thomas W.; Nalls, Michael A.; Nichols, Thomas E.; Nilsson, Lars G.; Nöthen, Markus M.; Ohi, Kazutaka; Olvera, Rene L.; Perez-Iglesias, Rocio; Pike, G. Bruce; Potkin, Steven G.; Reinvang, Ivar; Reppermund, Simone; Rietschel, Marcella; Romanczuk-Seiferth, Nina; Rosen, Glenn D.; Rujescu, Dan; Schnell, Knut; Schofield, Peter R.; Smith, Colin; Steen, Vidar M.; Sussmann, Jessika E.; Thalamuthu, Anbupalam; Toga, Arthur W.; Traynor, Bryan J.; Troncoso, Juan; Turner, Jessica A.; Valdés Hernández, Maria C.; van ’t Ent, Dennis; van der Brug, Marcel; van der Wee, Nic J. A.; van Tol, Marie-Jose; Veltman, Dick J.; Wassink, Thomas H.; Westman, Eric; Zielke, Ronald H.; Zonderman, Alan B.; Ashbrook, David G.; Hager, Reinmar; Lu, Lu; McMahon, Francis J.; Morris, Derek W.; Williams, Robert W.; Brunner, Han G.; Buckner, Randy L.; Buitelaar, Jan K.; Cahn, Wiepke; Calhoun, Vince D.; Cavalleri, Gianpiero L.; Crespo-Facorro, Benedicto; Dale, Anders M.; Davies, Gareth E.; Delanty, Norman; Depondt, Chantal; Djurovic, Srdjan; Drevets, Wayne C.; Espeseth, Thomas; Gollub, Randy L.; Ho, Beng-Choon; Hoffmann, Wolfgang; Hosten, Norbert; Kahn, René S.; Le Hellard, Stephanie; Meyer-Lindenberg, Andreas; Müller-Myhsok, Bertram; Nauck, Matthias; Nyberg, Lars; Pandolfo, Massimo; Penninx, Brenda W. J. H.; Roffman, Joshua L.; Sisodiya, Sanjay M.; Smoller, Jordan W.; van Bokhoven, Hans; van Haren, Neeltje E. M.; Völzke, Henry; Walter, Henrik; Weiner, Michael W.; Wen, Wei; White, Tonya; Agartz, Ingrid; Andreassen, Ole A.; Blangero, John; Boomsma, Dorret I.; Brouwer, Rachel M.; Cannon, Dara M.; Cookson, Mark R.; de Geus, Eco J. C.; Deary, Ian J.; Donohoe, Gary; Fernández, Guillén; Fisher, Simon E.; Francks, Clyde; Glahn, David C.; Grabe, Hans J.; Gruber, Oliver; Hardy, John; Hashimoto, Ryota; Hulshoff Pol, Hilleke E.; Jönsson, Erik G.; Kloszewska, Iwona; Lovestone, Simon; Mattay, Venkata S.; Mecocci, Patrizia; McDonald, Colm; McIntosh, Andrew M.; Ophoff, Roel A.; Paus, Tomas; Pausova, Zdenka; Ryten, Mina; Sachdev, Perminder S.; Saykin, Andrew J.; Simmons, Andy; Singleton, Andrew; Soininen, Hilkka; Wardlaw, Joanna M.; Weale, Michael E.; Weinberger, Daniel R.; Adams, Hieab H. H.; Launer, Lenore J.; Seiler, Stephan; Schmidt, Reinhold; Chauhan, Ganesh; Satizabal, Claudia L.; Becker, James T.; Yanek, Lisa; van der Lee, Sven J.; Ebling, Maritza; Fischl, Bruce; Longstreth, W. T.; Greve, Douglas; Schmidt, Helena; Nyquist, Paul; Vinke, Louis N.; van Duijn, Cornelia M.; Xue, Luting; Mazoyer, Bernard; Bis, Joshua C.; Gudnason, Vilmundur; Seshadri, Sudha; Ikram, M. Arfan; Martin, Nicholas G.; Wright, Margaret J.; Schumann, Gunter; Franke, Barbara; Thompson, Paul M.; Medland, Sarah E.

    2015-01-01

    The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability inhuman brain development, and may help to determine mechanisms of neuropsychiatric dysfunction. PMID:25607358

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

    Science.gov (United States)

    Rodriguez, Vanessa

    2013-01-01

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

  15. Imaging visual function of the human brain

    International Nuclear Information System (INIS)

    Marg, E.

    1988-01-01

    Imaging of human brain structure and activity with particular reference to visual function is reviewed along with methods of obtaining the data including computed tomographic (CT) scan, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET). The literature is reviewed and the potential for a new understanding of brain visual function is discussed. PET is reviewed from basic physical principles to the most recent visual brain findings with oxygen-15. It is shown that there is a potential for submillimeter localization of visual functions with sequentially different visual stimuli designed for the temporal separation of the responses. Single photon emission computed tomography (SPECT), a less expensive substitute for PET, is also discussed. MRS is covered from basic physical principles to the current state of the art of in vivo biochemical analysis. Future possible clinical applications are discussed. Improved understanding of the functional neural organization of vision and brain will open a window to maps and circuits of human brain function.119 references

  16. Enhancing Student Learning with Brain-Based Research

    Science.gov (United States)

    Bonnema, Ted R.

    2009-01-01

    This paper discusses brain-based learning and its relation to classroom instruction. A rapidly growing quantity of research currently exists regarding how the brain perceives, processes, and ultimately learns new information. In order to maximize their teaching efficacy, educators should have a basic understanding of key memory functions in the…

  17. Poverty and Brain Development in Children: Implications for Learning

    Science.gov (United States)

    Dike, Victor E.

    2017-01-01

    Debates on the effect of poverty on brain development in children and its implications for learning have been raging for decades. Research suggests that poverty affects brain development in children and that the implications for learning are more compelling today given the attention the issue has attracted. For instance, studies in the fields of…

  18. Signifikansi Brain Based Learning Pendidikan Anak Usia Dini

    OpenAIRE

    Jazariyah

    2017-01-01

    This study based on the reality of learning in the early childhood level and the system has not noticed the potential of the brain learners. The potential and the working system of the brain is very important in early childhood. This paper aims to reveal the importance of brain-based learning in Early Childhood Education (ECD). The problem in this study is what the nature of early childhood education and how to use the potential and work system of the brain in early childhood learning. This s...

  19. What Does the Brain Have to Do with Learning?

    Science.gov (United States)

    Worden, Jennifer M.; Hinton, Christina; Fischer, Kurt W.

    2011-01-01

    There are several myths about neuroscientific findings that are widespread in education. Some of these myths are left brain/right brain, critical periods for learning, and gender differences in the brain. Belief in these "neuromyths" can negatively affect how we teach children. But ignoring important findings from neuroscience can be just as…

  20. Puberty and structural brain development in humans.

    Science.gov (United States)

    Herting, Megan M; Sowell, Elizabeth R

    2017-01-01

    Adolescence is a transitional period of physical and behavioral development between childhood and adulthood. Puberty is a distinct period of sexual maturation that occurs during adolescence. Since the advent of magnetic resonance imaging (MRI), human studies have largely examined neurodevelopment in the context of age. A breadth of animal findings suggest that sex hormones continue to influence the brain beyond the prenatal period, with both organizational and activational effects occurring during puberty. Given the animal evidence, human MRI research has also set out to determine how puberty may influence otherwise known patterns of age-related neurodevelopment. Here we review structural-based MRI studies and show that pubertal maturation is a key variable to consider in elucidating sex- and individual- based differences in patterns of human brain development. We also highlight the continuing challenges faced, as well as future considerations, for this vital avenue of research. Copyright © 2016. Published by Elsevier Inc.

  1. Connectome imaging for mapping human brain pathways.

    Science.gov (United States)

    Shi, Y; Toga, A W

    2017-09-01

    With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research.

  2. Theoretical Implications of Contemporary Brain Science for Japanese EFL Learning

    Science.gov (United States)

    Clayton, John Lloyd

    2015-01-01

    Recent advances in brain science show that adult native Japanese speakers utilize a different balance of language processing routes in the brain as compared to native English speakers. Biologically this represents the remarkable flexibility of the human brain to adapt universal human cognitive processes to fit the specific needs of linguistic and…

  3. Increased expression of aquaporin-4 in human traumatic brain injury and brain tumors

    Institute of Scientific and Technical Information of China (English)

    HuaHu; Wei-PingZhang; LeiZhang; ZhongChen; Er-QingWei

    2004-01-01

    Aquaporin-4 (AQP4) is one of the aquaporins (AQPs), a water channel family. In the brain, AQP4 is expressed in astroeyte foot processes, and plays an important role in water homeostasis and in the formation of brain edema. In our study, AQP4 expression in human brain specimens from patients with traumatic brain injury or different brain tumors was detected

  4. Infrasounds and biorhythms of the human brain

    Science.gov (United States)

    Panuszka, Ryszard; Damijan, Zbigniew; Kasprzak, Cezary; McGlothlin, James

    2002-05-01

    Low Frequency Noise (LFN) and infrasound has begun a new public health hazard. Evaluations of annoyance of (LFN) on human occupational health were based on standards where reactions of human auditory system and vibrations of parts of human body were small. Significant sensitivity has been observed on the central nervous system from infrasonic waves especially below 10 Hz. Observed follow-up effects in the brain gives incentive to study the relationship between parameters of waves and reactions obtained of biorhythms (EEG) and heart action (EKG). New results show the impact of LFN on the electrical potentials of the brain are dependent on the pressure waves on the human body. Electrical activity of circulatory system was also affected. Signals recorded in industrial workplaces were duplicated by loudspeakers and used to record data from a typical LFN spectra with 5 and 7 Hz in a laboratory chamber. External noise, electromagnetic fields, temperature, dust, and other elements were controlled. Results show not only a follow-up effect in the brain but also a result similar to arrhythmia in the heart. Relaxations effects were observed of people impacted by waves generated from natural sources such as streams and waterfalls.

  5. Imaging Monoamine Oxidase in the Human Brain

    Energy Technology Data Exchange (ETDEWEB)

    Fowler, J. S.; Volkow, N. D.; Wang, G-J.; Logan, Jean

    1999-11-10

    Positron emission tomography (PET) studies mapping monoamine oxidase in the human brain have been used to measure the turnover rate for MAO B; to determine the minimum effective dose of a new MAO inhibitor drug lazabemide and to document MAO inhibition by cigarette smoke. These studies illustrate the power of PET and radiotracer chemistry to measure normal biochemical processes and to provide information on the effect of drug exposure on specific molecular targets.

  6. Imaging Monoamine Oxidase in the Human Brain

    International Nuclear Information System (INIS)

    Fowler, J. S.; Volkow, N. D.; Wang, G-J.; Logan, Jean

    1999-01-01

    Positron emission tomography (PET) studies mapping monoamine oxidase in the human brain have been used to measure the turnover rate for MAO B; to determine the minimum effective dose of a new MAO inhibitor drug lazabemide and to document MAO inhibition by cigarette smoke. These studies illustrate the power of PET and radiotracer chemistry to measure normal biochemical processes and to provide information on the effect of drug exposure on specific molecular targets

  7. Increased expression of aquaporin-4 in human traumatic brain injury and brain tumors

    Institute of Scientific and Technical Information of China (English)

    HU Hua; YAO Hong-tian; ZHANG Wei-ping; ZHANG LEI; DING Wei; ZHANG Shi-hong; CHEN Zhong; WEI Er-qing

    2005-01-01

    Objective: To characterize the expression of aquaporin-4 (AQP4), one of the aquaporins (AQPs), in human brain specimens from patients with traumatic brain injury or brain tumors. Methods: Nineteen human brain specimens were obtained from the patients with traumatic brain injury, brain tumors, benign meningioma or early stage hemorrhagic stroke. MRI or CT imaging was used to assess brain edema. Hematoxylin and eosin staining were used to evaluate cell damage. Immunohistochemistry was used to detect the AQP4 expression. Results: AQP4 expression was increased from 15h to at least 8 d after injury. AQP4immunoreactivity was strong around astrocytomas, ganglioglioma and metastatic adenocarcinoma. However, AQP4 immunoreactivity was only found in the centers of astrocytomas and ganglioglioma, but not in metastatic adenocarcinoma derived from lung.Conclusion: AQP4 expression increases in human brains after traumatic brain injury, within brain-derived tumors, and around brain tumors.

  8. The Global Aspects of Brain-Based Learning

    Science.gov (United States)

    Connell, J. Diane

    2009-01-01

    Brain-Based Learning (BBL) can be viewed as techniques gleaned from research in neurology and cognitive science used to enhance teacher instruction. These strategies can also be used to enhance students' ability to learn using ways in which they feel most comfortable, neurologically speaking. Jensen (1995/2000) defines BBL as "learning in…

  9. Effect of Teaching Using Whole Brain Instruction on Accounting Learning

    Science.gov (United States)

    Lee, Li-Tze; Hung, Jason C.

    2009-01-01

    McCarthy (1985) constructed the 4MAT teaching model, an eight step instrument developed in 1980, by synthesizing Dewey's experiential learning, Kolb's four learning styles, Jung's personality types, as well as Bogen's left mode and right mode of brain processing preferences. An important implication of this model is that learning retention is…

  10. Radiation effects on the developing human brain

    International Nuclear Information System (INIS)

    1993-01-01

    The developing human brain has been shown to be especially sensitive to ionizing radiation. Mental retardation has been observed in the survivors of the atomic bombings in Japan exposed in utero during sensitive periods, and clinical studies of pelvically irradiated pregnant women have demonstrated damaging effects on the fetus. In this annex the emphasis is on reviewing the results of the study of the survivors of the atomic bombings in Japan, although the results of other human epidemiological investigations and of pertinent experimental studies are also considered. Refs, 3 figs, 10 tabs

  11. Towards Developmental Connectomics of the Human Brain

    Directory of Open Access Journals (Sweden)

    Miao eCao

    2016-03-01

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

  12. Toward Developmental Connectomics of the Human Brain.

    Science.gov (United States)

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

    2016-01-01

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

  13. Toward Developmental Connectomics of the Human Brain

    Science.gov (United States)

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

    2016-01-01

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

  14. Brain structures in the sciences and humanities.

    Science.gov (United States)

    Takeuchi, Hikaru; Taki, Yasuyuki; Sekiguchi, Atsushi; Nouchi, Rui; Kotozaki, Yuka; Nakagawa, Seishu; Miyauchi, Carlos Makoto; Iizuka, Kunio; Yokoyama, Ryoichi; Shinada, Takamitsu; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Hashizume, Hiroshi; Sassa, Yuko; Kawashima, Ryuta

    2015-11-01

    The areas of academic interest (sciences or humanities) and area of study have been known to be associated with a number of factors associated with autistic traits. However, despite the vast amount of literature on the psychological and physiological characteristics associated with faculty membership, brain structural characteristics associated with faculty membership have never been investigated directly. In this study, we used voxel-based morphometry to investigate differences in regional gray matter volume (rGMV)/regional white matter volume (rWMV) between science and humanities students to test our hypotheses that brain structures previously robustly shown to be altered in autistic subjects are related to differences in faculty membership. We examined 312 science students (225 males and 87 females) and 179 humanities students (105 males and 74 females). Whole-brain analyses of covariance revealed that after controlling for age, sex, and total intracranial volume, the science students had significantly larger rGMV in an anatomical cluster around the medial prefrontal cortex and the frontopolar area, whereas the humanities students had significantly larger rWMV in an anatomical cluster mainly concentrated around the right hippocampus. These anatomical structures have been linked to autism in previous studies and may mediate cognitive functions that characterize differences in faculty membership. The present results may support the ideas that autistic traits and characteristics of the science students compared with the humanities students share certain characteristics from neuroimaging perspectives. This study improves our understanding of differences in faculty membership which is the link among cognition, biological factors, disorders, and education (academia).

  15. Memory-related brain lateralisation in birds and humans.

    Science.gov (United States)

    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.

  16. Social Rewards and Social Networks in the Human Brain.

    Science.gov (United States)

    Fareri, Dominic S; Delgado, Mauricio R

    2014-08-01

    The rapid development of social media and social networking sites in human society within the past decade has brought about an increased focus on the value of social relationships and being connected with others. Research suggests that we pursue socially valued or rewarding outcomes-approval, acceptance, reciprocity-as a means toward learning about others and fulfilling social needs of forming meaningful relationships. Focusing largely on recent advances in the human neuroimaging literature, we review findings highlighting the neural circuitry and processes that underlie pursuit of valued rewarding outcomes across non-social and social domains. We additionally discuss emerging human neuroimaging evidence supporting the idea that social rewards provide a gateway to establishing relationships and forming social networks. Characterizing the link between social network, brain, and behavior can potentially identify contributing factors to maladaptive influences on decision making within social situations. © The Author(s) 2014.

  17. Segmentation and Visualisation of Human Brain Structures

    Energy Technology Data Exchange (ETDEWEB)

    Hult, Roger

    2003-10-01

    In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give.

  18. Segmentation and Visualisation of Human Brain Structures

    International Nuclear Information System (INIS)

    Hult, Roger

    2003-01-01

    In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give

  19. Vicarious Learning from Human Models in Monkeys

    OpenAIRE

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...

  20. Deconstructing Anger in the Human Brain.

    Science.gov (United States)

    Gilam, Gadi; Hendler, Talma

    2017-01-01

    Anger may be caused by a wide variety of triggers, and though it has negative consequences on health and well-being, it is also crucial in motivating to take action and approach rather than avoid a confrontation. While anger is considered a survival response inherent in all living creatures, humans are endowed with the mental flexibility that enables them to control and regulate their anger, and adapt it to socially accepted norms. Indeed, a profound interpersonal nature is apparent in most events which evoke anger among humans. Since anger consists of physiological, cognitive, subjective, and behavioral components, it is a contextualized multidimensional construct that poses theoretical and operational difficulties in defining it as a single psychobiological phenomenon. Although most neuroimaging studies have neglected the multidimensionality of anger and thus resulted in brain activations dispersed across the entire brain, there seems to be several reoccurring neural circuits subserving the subjective experience of human anger. Nevertheless, to capture the large variety in the forms and fashions in which anger is experienced, expressed, and regulated, and thus to better portray the related underlying neural substrates, neurobehavioral investigations of human anger should aim to further embed realistic social interactions within their anger induction paradigms.

  1. Visualization of monoamine oxidase in human brain

    Energy Technology Data Exchange (ETDEWEB)

    Fowler, J.S.; Volkow, N.D.; Wang, G.J.; Pappas, N.; Shea, C.; MacGregor, R.R.; Logan, J.

    1996-12-31

    Monoamine oxidase is a flavin enzyme which exists in two subtypes, MAO A and MAO B. In human brain MAO B predominates and is largely compartmentalized in cell bodies of serotonergic neurons and glia. Regional distribution of MAO B was determined by positron computed tomography with volunteers after the administration of deuterium substituted [11C]L-deprenyl. The basal ganglia and thalamus exhibited the greatest concentrations of MAO B with intermediate levels in the frontal cortex and cingulate gyrus while lowest levels were observed in the parietal and temporal cortices and cerebellum. We observed that brain MAO B increases with are in health normal subjects, however the increases were generally smaller than those revealed with post-mortem studies.

  2. Learning Computational Models of Video Memorability from fMRI Brain Imaging.

    Science.gov (United States)

    Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

    2015-08-01

    Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

  3. Positive selection on gene expression in the human brain

    DEFF Research Database (Denmark)

    Khaitovich, Philipp; Tang, Kun; Franz, Henriette

    2006-01-01

    Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

  4. Physical biology of human brain development

    Directory of Open Access Journals (Sweden)

    Silvia eBudday

    2015-07-01

    Full Text Available Neurodevelopment is a complex, dynamic process that involves a precisely orchestrated sequence of genetic, environmental, biochemical, and physical events. Developmental biology and genetics have shaped our understanding of the molecular and cellular mechanisms during neurodevelopment. Recent studies suggest that physical forces play a central role in translating these cellular mechanisms into the complex surface morphology of the human brain. However, the precise impact of neuronal differentiation, migration, and connection on the physical forces during cortical folding remains unknown. Here we review the cellular mechanisms of neurodevelopment with a view towards surface morphogenesis, pattern selection, and evolution of shape. We revisit cortical folding as the instability problem of constrained differential growth in a multi-layered system. To identify the contributing factors of differential growth, we map out the timeline of neurodevelopment in humans and highlight the cellular events associated with extreme radial and tangential expansion. We demonstrate how computational modeling of differential growth can bridge the scales-from phenomena on the cellular level towards form and function on the organ level-to make quantitative, personalized predictions. Physics-based models can quantify cortical stresses, identify critical folding conditions, rationalize pattern selection, and predict gyral wavelengths and gyrification indices. We illustrate that physical forces can explain cortical malformations as emergent properties of developmental disorders. Combining biology and physics holds promise to advance our understanding of human brain development and enable early diagnostics of cortical malformations with the ultimate goal to improve treatment of neurodevelopmental disorders including epilepsy, autism spectrum disorders, and schizophrenia.

  5. Understanding How the Brain Learns Should Inform Our Teaching Practices

    Directory of Open Access Journals (Sweden)

    Alix Darden

    2012-08-01

    Full Text Available Comparative review of: The Brain-Targeted Teaching Model for 21st-Century Schools; Mariale Hardiman; (2012. Corwin, Thousand Oaks, CA. 223 pages; and How the Brain Learns, 4th ed.; David A. Sousa; (2011. Corwin, Thousand Oaks, CA. 321 pages.

  6. Vicarious learning from human models in monkeys.

    Science.gov (United States)

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

  7. Vicarious learning from human models in monkeys.

    Directory of Open Access Journals (Sweden)

    Rossella Falcone

    Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

  8. Brain networks for confidence weighting and hierarchical inference during probabilistic learning.

    Science.gov (United States)

    Meyniel, Florent; Dehaene, Stanislas

    2017-05-09

    Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences.

  9. Loss of Brain Aerobic Glycolysis in Normal Human Aging.

    Science.gov (United States)

    Goyal, Manu S; Vlassenko, Andrei G; Blazey, Tyler M; Su, Yi; Couture, Lars E; Durbin, Tony J; Bateman, Randall J; Benzinger, Tammie L-S; Morris, John C; Raichle, Marcus E

    2017-08-01

    The normal aging human brain experiences global decreases in metabolism, but whether this affects the topography of brain metabolism is unknown. Here we describe PET-based measurements of brain glucose uptake, oxygen utilization, and blood flow in cognitively normal adults from 20 to 82 years of age. Age-related decreases in brain glucose uptake exceed that of oxygen use, resulting in loss of brain aerobic glycolysis (AG). Whereas the topographies of total brain glucose uptake, oxygen utilization, and blood flow remain largely stable with age, brain AG topography changes significantly. Brain regions with high AG in young adults show the greatest change, as do regions with prolonged developmental transcriptional features (i.e., neoteny). The normal aging human brain thus undergoes characteristic metabolic changes, largely driven by global loss and topographic changes in brain AG. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Managing Human Resource Learning for Innovation

    DEFF Research Database (Denmark)

    Nielsen, Peter

    Managing human resource learning for innovation develops a systemic understanding of building innovative capabilities. Building innovative capabilities require active creation, coordination and absorption of useful knowledge and thus a cohesive management approach to learning. Often learning...... in organizations and work is approached without considerations on how to integrate it in the management of human resources. The book investigates the empirical conditions for managing human resources learning for innovation. With focus on innovative performance the importance of modes of innovation, clues...

  11. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  12. Distribution of melatonin receptor in human fetal brain

    Institute of Scientific and Technical Information of China (English)

    WANG Guo-quan; SHAO Fu-yuan; ZHAO Ying; LIU Zhi-min

    2001-01-01

    Objective: To study the distribution of 2 kinds of melatonin receptor subtypes (mtl and MT2) in human fetal brain. Methods: The fetal brain tissues were sliced and the distribution ofmelatonin receptors in human fetal brain were detected using immunohistochemistry and in situ hybridization. Results: Melatonin receptor mtl existed in the cerebellun and hypothalamus, melatonin receptor MT2 exists in hypothalamus, occipital and medulla. Conclusion: Two kinds of melatonin receptors, mtl and MT2 exist in the membrane and cytosol of brain cells, indicating that human fetal brain is a target organ of melatonin.

  13. 20 Ways To Promote Brain-Based Teaching and Learning.

    Science.gov (United States)

    Prigge, Debra J.

    2002-01-01

    Based on current knowledge about cognitive processes, this article presents strategies for preparing the learner, managing the environment to motivate students, gaining and keeping learner attention, and increasing memory and recall by making learning personally relevant to students. Resources are listed for brain-based teaching and learning. (CR)

  14. Brain Plasticity and the Art of Teaching to Learn

    Science.gov (United States)

    Martinez, Margaret

    2005-01-01

    "Everyone thinks of changing the world, but no one thinks of changing himself, "wrote Leo Tolstoy. Have you ever thought about how learning changes your brain? If yes, this paper may help you explore the research that will change our learning landscape in the next few years! Recent developers in the neurosciences and education research…

  15. Dynamic functional brain networks involved in simple visual discrimination learning.

    Science.gov (United States)

    Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

    2014-10-01

    Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Localized brain activation related to the strength of auditory learning in a parrot.

    Directory of Open Access Journals (Sweden)

    Hiroko Eda-Fujiwara

    Full Text Available Parrots and songbirds learn their vocalizations from a conspecific tutor, much like human infants acquire spoken language. Parrots can learn human words and it has been suggested that they can use them to communicate with humans. The caudomedial pallium in the parrot brain is homologous with that of songbirds, and analogous to the human auditory association cortex, involved in speech processing. Here we investigated neuronal activation, measured as expression of the protein product of the immediate early gene ZENK, in relation to auditory learning in the budgerigar (Melopsittacus undulatus, a parrot. Budgerigar males successfully learned to discriminate two Japanese words spoken by another male conspecific. Re-exposure to the two discriminanda led to increased neuronal activation in the caudomedial pallium, but not in the hippocampus, compared to untrained birds that were exposed to the same words, or were not exposed to words. Neuronal activation in the caudomedial pallium of the experimental birds was correlated significantly and positively with the percentage of correct responses in the discrimination task. These results suggest that in a parrot, the caudomedial pallium is involved in auditory learning. Thus, in parrots, songbirds and humans, analogous brain regions may contain the neural substrate for auditory learning and memory.

  17. [Neuroethics: Ethical Endowments of Human Brain].

    Science.gov (United States)

    López Moratalla, Natalia

    2015-01-01

    The neurobiological processes underlying moral judgement have been the focus of Neuroethics. Neurosciences demonstrate which cerebral areas are active and inactive whilst people decide how to act when facing a moral dilemma; in this way we know the correlation between determined cerebral areas and our human acts. We can explain how the ″ethical endowments″ of each person, common to all human beings, is ″embedded″ in the dynamic of cerebral flows. Of central interest is whether emotions play a causal role in moral judgement, and, in parallel, how emotion related areas of the brain contribute to moral judgement. The outcome of man's natural inclinations is on one hand linked to instinctive systems of animal survival and to basic emotions, and on the other, to the life of each individual human uninhibited by automatism of the biological laws, because he is governed by the laws of freedom. The capacity to formulate an ethical judgement is an innate asset of the human mind.

  18. Human simulations of vocabulary learning.

    Science.gov (United States)

    Gillette, J; Gleitman, H; Gleitman, L; Lederer, A

    1999-12-07

    The work reported here experimentally investigates a striking generalization about vocabulary acquisition: Noun learning is superior to verb learning in the earliest moments of child language development. The dominant explanation of this phenomenon in the literature invokes differing conceptual requirements for items in these lexical categories: Verbs are cognitively more complex than nouns and so their acquisition must await certain mental developments in the infant. In the present work, we investigate an alternative hypothesis; namely, that it is the information requirements of verb learning, not the conceptual requirements, that crucially determine the acquisition order. Efficient verb learning requires access to structural features of the exposure language and thus cannot take place until a scaffolding of noun knowledge enables the acquisition of clause-level syntax. More generally, we experimentally investigate the hypothesis that vocabulary acquisition takes place via an incremental constraint-satisfaction procedure that bootstraps itself into successively more sophisticated linguistic representations which, in turn, enable new kinds of vocabulary learning. If the experimental subjects were young children, it would be difficult to distinguish between this information-centered hypothesis and the conceptual change hypothesis. Therefore the experimental "learners" are adults. The items to be "acquired" in the experiments were the 24 most frequent nouns and 24 most frequent verbs from a sample of maternal speech to 18-24-month-old infants. The various experiments ask about the kinds of information that will support identification of these words as they occur in mother-to-child discourse. Both the proportion correctly identified and the type of word that is identifiable changes significantly as a function of information type. We discuss these results as consistent with the incremental construction of a highly lexicalized grammar by cognitively and pragmatically

  19. Sticking with the nice guy: trait warmth information impairs learning and modulates person perception brain network activity.

    Science.gov (United States)

    Lee, Victoria K; Harris, Lasana T

    2014-12-01

    Social learning requires inferring social information about another person, as well as evaluating outcomes. Previous research shows that prior social information biases decision making and reduces reliance on striatal activity during learning (Delgado, Frank, & Phelps, Nature Neuroscience 8 (11): 1611-1618, 2005). A rich literature in social psychology on person perception demonstrates that people spontaneously infer social information when viewing another person (Fiske & Taylor, 2013) and engage a network of brain regions, including the medial prefrontal cortex, temporal parietal junction, superior temporal sulcus, and precuneus (Amodio & Frith, Nature Reviews Neuroscience, 7(4), 268-277, 2006; Haxby, Gobbini, & Montgomery, 2004; van Overwalle Human Brain Mapping, 30, 829-858, 2009). We investigate the role of these brain regions during social learning about well-established dimensions of person perception-trait warmth and trait competence. We test the hypothesis that activity in person perception brain regions interacts with learning structures during social learning. Participants play an investment game where they must choose an agent to invest on their behalf. This choice is guided by cues signaling trait warmth or trait competence based on framing of monetary returns. Trait warmth information impairs learning about human but not computer agents, while trait competence information produces similar learning rates for human and computer agents. We see increased activation to warmth information about human agents in person perception brain regions. Interestingly, activity in person perception brain regions during the decision phase negatively predicts activity in the striatum during feedback for trait competence inferences about humans. These results suggest that social learning may engage additional processing within person perception brain regions that hampers learning in economic contexts.

  20. Encoding of Physics Concepts: Concreteness and Presentation Modality Reflected by Human Brain Dynamics

    OpenAIRE

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

    2012-01-01

    Previous research into working memory has focused on activations in different brain areas accompanying either different presentation modalities (verbal vs. non-verbal) or concreteness (abstract vs. concrete) of non-science concepts. Less research has been conducted investigating how scientific concepts are learned and further processed in working memory. To bridge this gap, the present study investigated human brain dynamics associated with encoding of physics concepts, taking both presentati...

  1. Brain 3M--A New Approach to Learning about Brain, Behavior, and Cognition

    Science.gov (United States)

    Li, Ping; Chaby, Lauren E.; Legault, Jennifer; Braithwaite, Victoria A.

    2015-01-01

    By combining emerging technologies with cognitive and education theories, we are capitalizing on recent findings from adaptive exploration and embodied learning research to address significant gaps in the education of brain sciences for school children and college level students. Through the development of virtual learning tools in combination…

  2. Left Brain to Right Brain: Notes from the Human Laboratory.

    Science.gov (United States)

    Baumli, Francis

    1982-01-01

    Examines the implications of the left brain-right brain theory on communications styles in male-female relationships. The author contends that women tend to use the vagueness of their emotional responses manipulatively. Men need to apply rational approaches to increase clarity in communication. (AM)

  3. Brain networks for confidence weighting and hierarchical inference during probabilistic learning

    Science.gov (United States)

    Meyniel, Florent; Dehaene, Stanislas

    2017-01-01

    Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This “confidence weighting” implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain’s learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences. PMID:28439014

  4. Brain-Based Teaching/Learning and Implications for Religious Education.

    Science.gov (United States)

    Weber, Jean Marie

    2002-01-01

    Argues that physical activity and water can increase brain activity, and hence, learning. Findings of neuroscientists regarding the brain can inform educators. Brain-based teaching emphasizes teamwork, cooperative learning, and global responsibility. Argues against gathering information without relevance. Connects brain-based learning concepts to…

  5. Thresholding magnetic resonance images of human brain

    Institute of Scientific and Technical Information of China (English)

    Qing-mao HU; Wieslaw L NOWINSKI

    2005-01-01

    In this paper, methods are proposed and validated to determine low and high thresholds to segment out gray matter and white matter for MR images of different pulse sequences of human brain. First, a two-dimensional reference image is determined to represent the intensity characteristics of the original three-dimensional data. Then a region of interest of the reference image is determined where brain tissues are present. The non-supervised fuzzy c-means clustering is employed to determine: the threshold for obtaining head mask, the low threshold for T2-weighted and PD-weighted images, and the high threshold for T1-weighted, SPGR and FLAIR images. Supervised range-constrained thresholding is employed to determine the low threshold for T1-weighted, SPGR and FLAIR images. Thresholding based on pairs of boundary pixels is proposed to determine the high threshold for T2- and PD-weighted images. Quantification against public data sets with various noise and inhomogeneity levels shows that the proposed methods can yield segmentation robust to noise and intensity inhomogeneity. Qualitatively the proposed methods work well with real clinical data.

  6. Neocortical glial cell numbers in human brains

    DEFF Research Database (Denmark)

    Pelvig, D.P.; Pakkenberg, H.; Stark, A.K.

    2008-01-01

    Stereological cell counting was applied to post-mortem neocortices of human brains from 31 normal individuals, age 18-93 years, 18 females (average age 65 years, range 18-93) and 13 males (average age 57 years, range 19-87). The cells were differentiated in astrocytes, oligodendrocytes, microglia...... while the total astrocyte number is constant through life; finally males have a 28% higher number of neocortical glial cells and a 19% higher neocortical neuron number than females. The overall total number of neocortical neurons and glial cells was 49.3 billion in females and 65.2 billion in males...... and neurons and counting were done in each of the four lobes. The study showed that the different subpopulations of glial cells behave differently as a function of age; the number of oligodendrocytes showed a significant 27% decrease over adult life and a strong correlation to the total number of neurons...

  7. Sensorimotor learning configures the human mirror system.

    Science.gov (United States)

    Catmur, Caroline; Walsh, Vincent; Heyes, Cecilia

    2007-09-04

    Cells in the "mirror system" fire not only when an individual performs an action but also when one observes the same action performed by another agent [1-4]. The mirror system, found in premotor and parietal cortices of human and monkey brains, is thought to provide the foundation for social understanding and to enable the development of theory of mind and language [5-9]. However, it is unclear how mirror neurons acquire their mirror properties -- how they derive the information necessary to match observed with executed actions [10]. We address this by showing that it is possible to manipulate the selectivity of the human mirror system, and thereby make it operate as a countermirror system, by giving participants training to perform one action while observing another. Before this training, participants showed event-related muscle-specific responses to transcranial magnetic stimulation over motor cortex during observation of little- and index-finger movements [11-13]. After training, this normal mirror effect was reversed. These results indicate that the mirror properties of the mirror system are neither wholly innate [14] nor fixed once acquired; instead they develop through sensorimotor learning [15, 16]. Our findings indicate that the human mirror system is, to some extent, both a product and a process of social interaction.

  8. "Messing with the Mind: Evolutionary Challenges to Human Brain Augmentation

    Directory of Open Access Journals (Sweden)

    ARTHUR eSANIOTIS

    2014-09-01

    Full Text Available The issue of brain augmentation has received considerable scientific attention over the last two decades. A key factor to brain augmentation that has been widely overlooked are the complex evolutionary processes which have taken place in evolving the human brain to its current state of functioning. Like other bodily organs, the human brain has been subject to the forces of biological adaptation. The structure and function of the brain, is very complex and only now we are beginning to understand some of the basic concepts of cognition. Therefore, this article proposes that brain-machine interfacing and nootropics are not going to produce augmented brains because we do not understand enough about how evolutionary pressures have informed the neural networks which support human cognitive faculties.

  9. From reverse transcription to human brain tumors

    Directory of Open Access Journals (Sweden)

    Dmitrenko V. V.

    2013-05-01

    Full Text Available Reverse transcriptase from avian myeloblastosis virus (AMV was the subject of the study, from which the investi- gations of the Department of biosynthesis of nucleic acids were started. Production of AMV in grams quantities and isolation of AMV reverse transcriptase were established in the laboratory during the seventies of the past cen- tury and this initiated research on the cDNA synthesis, cloning and investigation of the structure and functions of the eukaryotic genes. Structures of salmon insulin and insulin-like growth factor (IGF family genes and their transcripts were determined during long-term investigations. Results of two modern techniques, microarray-ba- sed hybridization and SAGE, were used for the identification of the genes differentially expressed in astrocytic gliomas and human normal brain. Comparison of SAGE results on the genes overexpressed in glioblastoma with the results of microarray analysis revealed a limited number of common genes. 105 differentially expressed genes, common to both methods, can be included in the list of candidates for the molecular typing of glioblastoma. The first experiments on the classification of glioblastomas based on the data of the 20 genes expression were conducted by using of artificial neural network analysis. The results of these experiments showed that the expression profiles of these genes in 224 glioblastoma samples and 74 normal brain samples could be according to the Koho- nen’s maps. The CHI3L1 and CHI3L2 genes of chitinase-like cartilage protein were revealed among the most overexpressed genes in glioblastoma, which could have prognostic and diagnostic potential. Results of in vitro experiments demonstrated that both proteins, CHI3L1 and CHI3L2, may initiate the phosphorylation of ERK1/ ERK2 and AKT kinases leading to the activation of MAPK/ERK1/2 and PI3K/AKT signaling cascades in human embryonic kidney 293 cells, human glioblastoma U87MG, and U373 cells. The new human cell line

  10. Abstract representations of associated emotions in the human brain.

    Science.gov (United States)

    Kim, Junsuk; Schultz, Johannes; Rohe, Tim; Wallraven, Christian; Lee, Seong-Whan; Bülthoff, Heinrich H

    2015-04-08

    Emotions can be aroused by various kinds of stimulus modalities. Recent neuroimaging studies indicate that several brain regions represent emotions at an abstract level, i.e., independently from the sensory cues from which they are perceived (e.g., face, body, or voice stimuli). If emotions are indeed represented at such an abstract level, then these abstract representations should also be activated by the memory of an emotional event. We tested this hypothesis by asking human participants to learn associations between emotional stimuli (videos of faces or bodies) and non-emotional stimuli (fractals). After successful learning, fMRI signals were recorded during the presentations of emotional stimuli and emotion-associated fractals. We tested whether emotions could be decoded from fMRI signals evoked by the fractal stimuli using a classifier trained on the responses to the emotional stimuli (and vice versa). This was implemented as a whole-brain searchlight, multivoxel activation pattern analysis, which revealed successful emotion decoding in four brain regions: posterior cingulate cortex (PCC), precuneus, MPFC, and angular gyrus. The same analysis run only on responses to emotional stimuli revealed clusters in PCC, precuneus, and MPFC. Multidimensional scaling analysis of the activation patterns revealed clear clustering of responses by emotion across stimulus types. Our results suggest that PCC, precuneus, and MPFC contain representations of emotions that can be evoked by stimuli that carry emotional information themselves or by stimuli that evoke memories of emotional stimuli, while angular gyrus is more likely to take part in emotional memory retrieval. Copyright © 2015 the authors 0270-6474/15/355655-09$15.00/0.

  11. Sex differences in brain organization: implications for human communication.

    Science.gov (United States)

    Hanske-Petitpierre, V; Chen, A C

    1985-12-01

    This article reviews current knowledge in two major research domains: sex differences in neuropsychophysiology, and in human communication. An attempt was made to integrate knowledge from several areas of brain research with human communication and to clarify how such a cooperative effort may be beneficial to both fields of study. By combining findings from the area of brain research, a communication paradigm was developed which contends that brain-related sex differences may reside largely in the area of communication of emotion.

  12. Lipidomics of human brain aging and Alzheimer's disease pathology.

    Science.gov (United States)

    Naudí, Alba; Cabré, Rosanna; Jové, Mariona; Ayala, Victoria; Gonzalo, Hugo; Portero-Otín, Manuel; Ferrer, Isidre; Pamplona, Reinald

    2015-01-01

    Lipids stimulated and favored the evolution of the brain. Adult human brain contains a large amount of lipids, and the largest diversity of lipid classes and lipid molecular species. Lipidomics is defined as "the full characterization of lipid molecular species and of their biological roles with respect to expression of proteins involved in lipid metabolism and function, including gene regulation." Therefore, the study of brain lipidomics can help to unravel the diversity and to disclose the specificity of these lipid traits and its alterations in neural (neurons and glial) cells, groups of neural cells, brain, and fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of human brain aging and Alzheimer disease. This review will discuss the lipid composition of the adult human brain. We first consider a brief approach to lipid definition, classification, and tools for analysis from the new point of view that has emerged with lipidomics, and then turn to the lipid profiles in human brain and how lipids affect brain function. Finally, we focus on the current status of lipidomics findings in human brain aging and Alzheimer's disease pathology. Neurolipidomics will increase knowledge about physiological and pathological functions of brain cells and will place the concept of selective neuronal vulnerability in a lipid context. © 2015 Elsevier Inc. All rights reserved.

  13. Brain signal complexity rises with repetition suppression in visual learning.

    Science.gov (United States)

    Lafontaine, Marc Philippe; Lacourse, Karine; Lina, Jean-Marc; McIntosh, Anthony R; Gosselin, Frédéric; Théoret, Hugo; Lippé, Sarah

    2016-06-21

    Neuronal activity associated with visual processing of an unfamiliar face gradually diminishes when it is viewed repeatedly. This process, known as repetition suppression (RS), is involved in the acquisition of familiarity. Current models suggest that RS results from interactions between visual information processing areas located in the occipito-temporal cortex and higher order areas, such as the dorsolateral prefrontal cortex (DLPFC). Brain signal complexity, which reflects information dynamics of cortical networks, has been shown to increase as unfamiliar faces become familiar. However, the complementarity of RS and increases in brain signal complexity have yet to be demonstrated within the same measurements. We hypothesized that RS and brain signal complexity increase occur simultaneously during learning of unfamiliar faces. Further, we expected alteration of DLPFC function by transcranial direct current stimulation (tDCS) to modulate RS and brain signal complexity over the occipito-temporal cortex. Participants underwent three tDCS conditions in random order: right anodal/left cathodal, right cathodal/left anodal and sham. Following tDCS, participants learned unfamiliar faces, while an electroencephalogram (EEG) was recorded. Results revealed RS over occipito-temporal electrode sites during learning, reflected by a decrease in signal energy, a measure of amplitude. Simultaneously, as signal energy decreased, brain signal complexity, as estimated with multiscale entropy (MSE), increased. In addition, prefrontal tDCS modulated brain signal complexity over the right occipito-temporal cortex during the first presentation of faces. These results suggest that although RS may reflect a brain mechanism essential to learning, complementary processes reflected by increases in brain signal complexity, may be instrumental in the acquisition of novel visual information. Such processes likely involve long-range coordinated activity between prefrontal and lower order visual

  14. Neocortical glial cell numbers in human brains.

    Science.gov (United States)

    Pelvig, D P; Pakkenberg, H; Stark, A K; Pakkenberg, B

    2008-11-01

    Stereological cell counting was applied to post-mortem neocortices of human brains from 31 normal individuals, age 18-93 years, 18 females (average age 65 years, range 18-93) and 13 males (average age 57 years, range 19-87). The cells were differentiated in astrocytes, oligodendrocytes, microglia and neurons and counting were done in each of the four lobes. The study showed that the different subpopulations of glial cells behave differently as a function of age; the number of oligodendrocytes showed a significant 27% decrease over adult life and a strong correlation to the total number of neurons while the total astrocyte number is constant through life; finally males have a 28% higher number of neocortical glial cells and a 19% higher neocortical neuron number than females. The overall total number of neocortical neurons and glial cells was 49.3 billion in females and 65.2 billion in males, a difference of 24% with a high biological variance. These numbers can serve as reference values in quantitative studies of the human neocortex.

  15. The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

    Science.gov (United States)

    Mekarina, M.; Ningsih, Y. P.

    2017-09-01

    This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.

  16. Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

    Science.gov (United States)

    Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

    2017-09-01

    The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

  17. Macroscopic networks in the human brain: mapping connectivity in healthy and damaged brains

    NARCIS (Netherlands)

    Nijhuis, E.H.J.

    2013-01-01

    The human brain contains a network of interconnected neurons. Recent advances in functional and structural in-vivo magnetic resonance neuroimaging (MRI) techniques have provided opportunities to model the networks of the human brain on a macroscopic scale. This dissertation investigates the

  18. mRNA Transcriptomics of Galectins Unveils Heterogeneous Organization in Mouse and Human Brain

    Directory of Open Access Journals (Sweden)

    Sebastian John

    2016-12-01

    Full Text Available Background: Galectins, a family of non-classically secreted, β-galactoside binding proteins is involved in several brain disorders; however no systematic knowledge on the normal neuroanatomical distribution and functions of galectins exits. Hence, the major purpose of this study was to understand spatial distribution and predict functions of galectins in brain and also compare the degree of conservation vs. divergence between mouse and human species. The latter objective was required to determine the relevance and appropriateness of studying galectins in mouse brain which may ultimately enable us to extrapolate the findings to human brain physiology and pathologies.Results: In order to fill this crucial gap in our understanding of brain galectins, we analyzed the in situ hybridization (ISH and microarray data of adult mouse and human brain respectively, from the Allen Brain Atlas, to resolve each galectin-subtype’s spatial distribution across brain distinct cytoarchitecture. Next, transcription factors (TFs that may regulate galectins were identified using TRANSFAC software and the list obtained was further curated to sort TFs on their confirmed transcript expression in the adult brain. Galectin-TF cluster analysis, gene-ontology annotations and co-expression networks were then extrapolated to predict distinct functional relevance of each galectin in the neuronal processes. Data shows that galectins have highly heterogeneous expression within and across brain sub-structures and are predicted to be the crucial targets of brain enriched TFs. Lgals9 had maximal spatial distribution across mouse brain with inferred predominant roles in neurogenesis while LGALS1 was ubiquitously expressed in human. Limbic region associated with learning, memory and emotions and substantia nigra associated with motor movements showed strikingly high expression of LGALS1 and LGALS8 in human vs. mouse brain. The overall expression profile of galectin-8 was most

  19. Structured brain computing and its learning

    International Nuclear Information System (INIS)

    Ae, Tadashi; Araki, Hiroyuki; Sakai, Keiichi

    1999-01-01

    We have proposed a two-level architecture for brain computing, where two levels are introduced for processing of meta-symbol. At level 1 a conventional pattern recognition is performed, where neural computation is included, and its output gives the meta-symbol which is a symbol enlarged from a symbol to a kind of pattern. At Level 2 an algorithm acquisition is made by using a machine for abstract states. We are also developing the VLSI chips at each level for SBC (Structured Brain Computer) Ver.1.0

  20. A Culture-Behavior-Brain Loop Model of Human Development.

    Science.gov (United States)

    Han, Shihui; Ma, Yina

    2015-11-01

    Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Critical brain circuits at the intersection between stress and learning.

    Science.gov (United States)

    Bangasser, Debra A; Shors, Tracey J

    2010-07-01

    The effects of stressful life experience on learning are pervasive and vary greatly both within and between individuals. It is therefore unlikely that any one mechanism will underlie these complicated processes. Nonetheless, without identifying the necessary and sufficient circuitry, no complete mechanism or set of mechanisms can be identified. In this review, we provide two anatomical frameworks through which stressful life experience can influence processes related to learning and memory. In the first, stressful experience releases stress hormones, primarily from the adrenals, which directly impact brain areas engaged in learning. In the second, stressful experience indirectly alters the circuits used in learning via intermediary brain regions. Importantly, these intermediary brain regions are not integral to the stress response or learning itself, but rather link the consequences of a stressful experience with circuits used to learn associations. As reviewed, the existing literature provides support for both frameworks, with somewhat more support for the first but sufficient evidence for the latter which involves intermediary structures. Once we determine the circumstances that engage each framework and identify which one is most predominant, we can begin to focus our efforts on describing the neuronal and hormonal mechanisms that operate within these circuits to influence cognitive processes after stressful life experience.

  2. Human brain networks function in connectome-specific harmonic waves.

    Science.gov (United States)

    Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

    2016-01-21

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

  3. Correlation of Students' Brain Types to Their Conceptions of Learning Science and Approaches to Learning Science

    Science.gov (United States)

    Park, Jiyeon; Jeon, Dongryul

    2015-01-01

    The systemizing and empathizing brain type represent two contrasted students' characteristics. The present study investigated differences in the conceptions and approaches to learning science between the systemizing and empathizing brain type students. The instruments are questionnaires on the systematizing and empathizing, questionnaires on the…

  4. Mapping human whole-brain structural networks with diffusion MRI.

    Directory of Open Access Journals (Sweden)

    Patric Hagmann

    Full Text Available Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

  5. Analysis of brain CT on 120 patients of human cysticercosis

    International Nuclear Information System (INIS)

    Ma, J.; To, R.; Ri, T.; Ra, S.; Inomata, Taiten; Ogawa, Yasuhiro; Maeda, Tomoo.

    1990-01-01

    A study on brain CT was made in 120 patients of human cysticercosis, which is a rare disease in Japan and clinical symptoms and laboratory data for the diagnosis were also discussed. From the point of therapeutic view, we proposed a new differentiation on brain CT of human cysticercosis, which is divided into two groups according to the alve or dead parasite. Furthermore, we proposed a new type named multiple large and small cysts type on brain CT. The idea of diagnostic standard was made integrating brain CT image, clinical symptoms and labolatory data. (author)

  6. The progress of radiosensitive genes of human brain glioma

    International Nuclear Information System (INIS)

    Wang Xi; Liu Qiang

    2008-01-01

    Human gliomas are one of the most aggressive tumors in brain which grow infiltrativly. Surgery is the mainstay of treatment. But as the tumor could not be entirely cut off, it is easy to relapse. Radiotherapy plays an important role for patients with gliomas after surgery. The efficacy of radiotherapy is associated with radio sensitivity of human gliomas. This paper makes a summary of current situation and progress for radiosensitive genes of human brain gliomas. (authors)

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

    Science.gov (United States)

    Hari, Riitta

    2017-06-07

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

  8. Brain-Based Learning and Educational Neuroscience: Boundary Work

    NARCIS (Netherlands)

    Edelenbosch, R.M.; Kupper, J.F.H.; Krabbendam, A.C.; Broerse, J.E.W.

    2015-01-01

    Much attention has been given to "bridging the gap" between neuroscience and educational practice. In order to gain better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning

  9. Brain-Based Learning and Educational Neuroscience: Boundary Work

    Science.gov (United States)

    Edelenbosch, Rosanne; Kupper, Frank; Krabbendam, Lydia; Broerse, Jacqueline E. W.

    2015-01-01

    Much attention has been given to "bridging the gap" between neuroscience and educational practice. In order to gain better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning approach, focusing on…

  10. Toward discovery science of human brain function

    DEFF Research Database (Denmark)

    Biswal, Bharat B; Mennes, Maarten; Zuo, Xi-Nian

    2010-01-01

    Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints...... individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships...... in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/....

  11. Astrocyte calcium signal and gliotransmission in human brain tissue.

    Science.gov (United States)

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

    2013-05-01

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

  12. Brain-Computer Interface Controlled Cyborg: Establishing a Functional Information Transfer Pathway from Human Brain to Cockroach Brain.

    Science.gov (United States)

    Li, Guangye; Zhang, Dingguo

    2016-01-01

    An all-chain-wireless brain-to-brain system (BTBS), which enabled motion control of a cyborg cockroach via human brain, was developed in this work. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) was used in this system for recognizing human motion intention and an optimization algorithm was proposed in SSVEP to improve online performance of the BCI. The cyborg cockroach was developed by surgically integrating a portable microstimulator that could generate invasive electrical nerve stimulation. Through Bluetooth communication, specific electrical pulse trains could be triggered from the microstimulator by BCI commands and were sent through the antenna nerve to stimulate the brain of cockroach. Serial experiments were designed and conducted to test overall performance of the BTBS with six human subjects and three cockroaches. The experimental results showed that the online classification accuracy of three-mode BCI increased from 72.86% to 78.56% by 5.70% using the optimization algorithm and the mean response accuracy of the cyborgs using this system reached 89.5%. Moreover, the results also showed that the cyborg could be navigated by the human brain to complete walking along an S-shape track with the success rate of about 20%, suggesting the proposed BTBS established a feasible functional information transfer pathway from the human brain to the cockroach brain.

  13. Individual differences in the learning potential of human beings

    Science.gov (United States)

    Stern, Elsbeth

    2017-01-01

    To the best of our knowledge, the genetic foundations that guide human brain development have not changed fundamentally during the past 50,000 years. However, because of their cognitive potential, humans have changed the world tremendously in the past centuries. They have invented technical devices, institutions that regulate cooperation and competition, and symbol systems, such as script and mathematics, that serve as reasoning tools. The exceptional learning ability of humans allows newborns to adapt to the world they are born into; however, there are tremendous individual differences in learning ability among humans that become obvious in school at the latest. Cognitive psychology has developed models of memory and information processing that attempt to explain how humans learn (general perspective), while the variation among individuals (differential perspective) has been the focus of psychometric intelligence research. Although both lines of research have been proceeding independently, they increasingly converge, as both investigate the concepts of working memory and knowledge construction. This review begins with presenting state-of-the-art research on human information processing and its potential in academic learning. Then, a brief overview of the history of psychometric intelligence research is combined with presenting recent work on the role of intelligence in modern societies and on the nature-nurture debate. Finally, promising approaches to integrating the general and differential perspective will be discussed in the conclusion of this review.

  14. "Celebration of the Neurons": The Application of Brain Based Learning in Classroom Environment

    Science.gov (United States)

    Duman, Bilal

    2007-01-01

    The purpose of this study is to investigate approaches and techniques related to how brain based learning used in classroom atmosphere. This general purpose were answered following the questions: (1) What is the aim of brain based learning? (2) What are general approaches and techniques that brain based learning used? and (3) How should be used…

  15. Toward Developmental Connectomics of the Human Brain

    OpenAIRE

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

    2016-01-01

    Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorder...

  16. Towards Developmental Connectomics of the Human Brain

    OpenAIRE

    Miao eCao; Hao eHuang; Hao eHuang; Yun ePeng; Qi eDong; Yong eHe

    2016-01-01

    Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders...

  17. Brain based learning with contextual approach to mathematics achievement

    Directory of Open Access Journals (Sweden)

    V Kartikaningtyas

    2017-12-01

    Full Text Available The aim of this study was to know the effect of Brain Based Learning (BBL with a contextual approach to mathematics achievement. BBL-contextual is the learning model that designed to develop and optimize the brain ability for getting a new concept and solving the real life problem. This study method was a quasi-experiment. The population was the junior high school students. The sample chosen by using stratified cluster random sampling. The sample was 109 students. The data collected through a mathematics achievement test that was given after the treatment. The data analyzed by using one way ANOVA. The results of the study showed that BBL-contextual is better than direct learning on mathematics achievement. It means BBL-contextual could be an effective and innovative model.

  18. Service Learning to Promote Brain-Based Learning in Undergraduate Teaching

    Science.gov (United States)

    Nwokah, Eva E.; Leafblad, Stefanie

    2013-01-01

    In this study 44 undergraduate students in a language development course participated in service learning with preschool homeless and low-income children as a course requirement. Students completed a survey, questionnaires, reflective journaling, and small-group debriefing sessions. Based on current views on brain-based learning from cortical…

  19. Classification of CT brain images based on deep learning networks.

    Science.gov (United States)

    Gao, Xiaohong W; Hui, Rui; Tian, Zengmin

    2017-01-01

    While computerised tomography (CT) may have been the first imaging tool to study human brain, it has not yet been implemented into clinical decision making process for diagnosis of Alzheimer's disease (AD). On the other hand, with the nature of being prevalent, inexpensive and non-invasive, CT does present diagnostic features of AD to a great extent. This study explores the significance and impact on the application of the burgeoning deep learning techniques to the task of classification of CT brain images, in particular utilising convolutional neural network (CNN), aiming at providing supplementary information for the early diagnosis of Alzheimer's disease. Towards this end, three categories of CT images (N = 285) are clustered into three groups, which are AD, lesion (e.g. tumour) and normal ageing. In addition, considering the characteristics of this collection with larger thickness along the direction of depth (z) (~3-5 mm), an advanced CNN architecture is established integrating both 2D and 3D CNN networks. The fusion of the two CNN networks is subsequently coordinated based on the average of Softmax scores obtained from both networks consolidating 2D images along spatial axial directions and 3D segmented blocks respectively. As a result, the classification accuracy rates rendered by this elaborated CNN architecture are 85.2%, 80% and 95.3% for classes of AD, lesion and normal respectively with an average of 87.6%. Additionally, this improved CNN network appears to outperform the others when in comparison with 2D version only of CNN network as well as a number of state of the art hand-crafted approaches. As a result, these approaches deliver accuracy rates in percentage of 86.3, 85.6 ± 1.10, 86.3 ± 1.04, 85.2 ± 1.60, 83.1 ± 0.35 for 2D CNN, 2D SIFT, 2D KAZE, 3D SIFT and 3D KAZE respectively. The two major contributions of the paper constitute a new 3-D approach while applying deep learning technique to extract signature information

  20. The Complex Functioning of the Human Brain: The Two Hemispheres

    Directory of Open Access Journals (Sweden)

    Iulia Cristina Timofti

    2010-04-01

    Full Text Available The present study reveals just a glimpse of the possible functions and reactions that the human brain can have. I considered as good examples different situations characteristic both of a normal person and a split-brain one. These situations prove that the brain, although divided in two, works as a unit, as an amazing computer that has data processing as a main goal.

  1. Neuroglobin and Cytoglobin expression in the human brain

    DEFF Research Database (Denmark)

    Hundahl, Christian Ansgar; Kelsen, Jesper; Hay-Schmidt, Anders

    2013-01-01

    Neuroglobin and Cytoglobin are new members of the heme-globin family. Both globins are primarily expressed in neurons of the brain and retina. Neuroglobin and Cytoglobin have been suggested as novel therapeutic targets in various neurodegenerative diseases based on their oxygen binding and cell...... protecting properties. However, findings in Neuroglobin-deficient mice question the endogenous neuroprotective properties. The expression pattern of Neuroglobin and Cytoglobin in the rodent brain is also in contradiction to a major role of neuronal protection. In a recent study, Neuroglobin was ubiquitously...... expressed and up-regulated following stroke in the human brain. The present study aimed at confirming our previous observations in rodents using two post-mortem human brains. The anatomical localization of Neuroglobin and Cytoglobin in the human brain is much like what has been described for the rodent...

  2. Task-based core-periphery organization of human brain dynamics.

    Directory of Open Access Journals (Sweden)

    Danielle S Bassett

    Full Text Available As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain's putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior.

  3. Measurement of P-31 MR relaxation times and concentrations in human brain and brain tumors

    International Nuclear Information System (INIS)

    Roth, K.; Naruse, S.; Hubesch, B.; Gober, I.; Lawry, T.; Boska, M.; Matson, G.B.; Weiner, M.W.

    1987-01-01

    Measurements of high-energy phosphates and pH were made in human brain and brain tumors using P-31 MR imaging. Using a Philips Gyroscan 1.5-T MRMRS, MR images were used to select a cuboidal volume of interest and P-31 MR spectra were obtained from that volume using the ISIS technique. An external quantitation standard was used. T 1 s were measured by inversion recovery. Quantitative values for metabolites were calculated using B 1 field plot of the head coil. The results for normal brain phosphates are as follows; adenosine triphosphate, 2.2 mM; phosphocreatin, 5.3 mM; inorganic phosphate, 1.6 mM. Preliminary studies with human brain tumors show a decrease of all phosphate compounds. These experiments are the first to quantitate metabolites in human brain

  4. Injury Response of Resected Human Brain Tissue In Vitro

    NARCIS (Netherlands)

    Verwer, Ronald W. H.; Sluiter, Arja A.; Balesar, Rawien A.; Baaijen, Johannes C.; de Witt Hamer, Philip C.; Speijer, Dave; Li, Yichen; Swaab, Dick F.

    2015-01-01

    Brain injury affects a significant number of people each year. Organotypic cultures from resected normal neocortical tissue provide unique opportunities to study the cellular and neuropathological consequences of severe injury of adult human brain tissue in vitro. The in vitro injuries caused by

  5. Neuronal substrates of sensory gating within the human brain.

    NARCIS (Netherlands)

    Grunwald, T.; Boutros, N.N.; Pezer, N.; Oertzen, J. von; Fernandez, G.S.E.; Schaller, C.; Elger, C.E.

    2003-01-01

    BACKGROUND: For the human brain, habituation to irrelevant sensory input is an important function whose failure is associated with behavioral disturbances. Sensory gating can be studied by recording the brain's electrical responses to repeated clicks: the P50 potential is normally reduced to the

  6. Function of insulin in snail brain in associative learning.

    Science.gov (United States)

    Kojima, S; Sunada, H; Mita, K; Sakakibara, M; Lukowiak, K; Ito, E

    2015-10-01

    Insulin is well known as a hormone regulating glucose homeostasis across phyla. Although there are insulin-independent mechanisms for glucose uptake in the mammalian brain, which had contributed to a perception of the brain as an insulin-insensitive organ for decades, the finding of insulin and its receptors in the brain revolutionized the concept of insulin signaling in the brain. However, insulin's role in brain functions, such as cognition, attention, and memory, remains unknown. Studies using invertebrates with their open blood-vascular system have the promise of promoting a better understanding of the role played by insulin in mediating/modulating cognitive functions. In this review, the relationship between insulin and its impact on long-term memory (LTM) is discussed particularly in snails. The pond snail Lymnaea stagnalis has the ability to undergo conditioned taste aversion (CTA), that is, it associatively learns and forms LTM not to respond with a feeding response to a food that normally elicits a robust feeding response. We show that molluscan insulin-related peptides are up-regulated in snails exhibiting CTA-LTM and play a key role in the causal neural basis of CTA-LTM. We also survey the relevant literature of the roles played by insulin in learning and memory in other phyla.

  7. Quantitation of glial fibrillary acidic protein in human brain tumours

    DEFF Research Database (Denmark)

    Rasmussen, S; Bock, E; Warecka, K

    1980-01-01

    The glial fibrillary acidic protein (GFA) content of 58 human brain tumours was determined by quantitative immunoelectrophoresis, using monospecific antibody against GFA. Astrocytomas, glioblastomas, oligodendrogliomas, spongioblastomas, ependymomas and medulloblastomas contained relatively high...

  8. Sex beyond the genitalia: The human brain mosaic

    Science.gov (United States)

    Joel, Daphna; Berman, Zohar; Tavor, Ido; Wexler, Nadav; Gaber, Olga; Stein, Yaniv; Shefi, Nisan; Pool, Jared; Urchs, Sebastian; Margulies, Daniel S.; Liem, Franziskus; Hänggi, Jürgen; Jäncke, Lutz; Assaf, Yaniv

    2015-01-01

    Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains (“female brain” or “male brain”). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only “male” or only “female” features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the “maleness-femaleness” continuum are rare. Rather, most brains are comprised of unique “mosaics” of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain. PMID:26621705

  9. Noninvasive Stimulation of the Human Brain

    DEFF Research Database (Denmark)

    Di Lazzaro, Vincenzo; Rothwell, John; Capogna, Marco

    2017-01-01

    Noninvasive brain stimulation methods, such as transcranial electric stimulation and transcranial magnetic stimulation are widely used tools for both basic research and clinical applications. However, the cortical circuits underlying their effects are poorly defined. Here we review the current...

  10. Short parietal lobe connections of the human and monkey brain

    DEFF Research Database (Denmark)

    Catani, Marco; Robertsson, Naianna; Beyh, Ahmad

    2017-01-01

    projections were reconstructed for both species and results compared to identify similarities or differences in tract anatomy (i.e., trajectories and cortical projections). In addition, post-mortem dissections were performed in a human brain. The largest tract identified in both human and monkey brains...... and angular gyri of the inferior parietal lobule in humans but only to the supramarginal gyrus in the monkey brain. The third tract connects the postcentral gyrus to the anterior region of the superior parietal lobule and is more prominent in monkeys compared to humans. Finally, short U-shaped fibres...... and monkeys with some differences for those areas that have cytoarchitectonically distinct features in humans. The overall pattern of intraparietal connectivity supports the special role of the inferior parietal lobule in cognitive functions characteristic of humans....

  11. Optogenetic control of human neurons in organotypic brain cultures

    DEFF Research Database (Denmark)

    Andersson, My; Avaliani, Natalia; Svensson, Andreas

    2016-01-01

    Optogenetics is one of the most powerful tools in neuroscience, allowing for selective control of specific neuronal populations in the brain of experimental animals, including mammals. We report, for the first time, the application of optogenetic tools to human brain tissue providing a proof......-of-concept for the use of optogenetics in neuromodulation of human cortical and hippocampal neurons as a possible tool to explore network mechanisms and develop future therapeutic strategies....

  12. Default, Cognitive, and Affective Brain Networks in Human Tinnitus

    Science.gov (United States)

    2015-10-01

    AWARD NUMBER: W81XWH-13-1-0491 TITLE: Default, Cognitive, and Affective Brain Networks in Human Tinnitus PRINCIPAL INVESTIGATOR: Jennifer R...SUBTITLE 5a. CONTRACT NUMBER Default, Cognitive and Affective Brain Networks in Human Tinnitus 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Tinnitus is a major health problem among those currently and formerly in military

  13. The evolutionary basis of human social learning.

    Science.gov (United States)

    Morgan, T J H; Rendell, L E; Ehn, M; Hoppitt, W; Laland, K N

    2012-02-22

    Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.

  14. Genetic contributions to human brain morphology and intelligence

    DEFF Research Database (Denmark)

    Hulshoff Pol, HE; Schnack, HG; Posthuma, D

    2006-01-01

    Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology...... of specific GM areas in the brain have been studied, the heritability of focal WM is unknown. Similarly, it is unresolved whether there is a common genetic origin of focal GM and WM structures with intelligence. We explored the genetic influence on focal GM and WM densities in magnetic resonance brain images...

  15. Outer brain barriers in rat and human development

    DEFF Research Database (Denmark)

    Brøchner, Christian B; Holst, Camilla Bjørnbak; Møllgård, Kjeld

    2015-01-01

    Complex barriers at the brain's surface, particularly in development, are poorly defined. In the adult, arachnoid blood-cerebrospinal fluid (CSF) barrier separates the fenestrated dural vessels from the CSF by means of a cell layer joined by tight junctions. Outer CSF-brain barrier provides...... diffusion restriction between brain and subarachnoid CSF through an initial radial glial end feet layer covered with a pial surface layer. To further characterize these interfaces we examined embryonic rat brains from E10 to P0 and forebrains from human embryos and fetuses (6-21st weeks post...

  16. Centrality of Social Interaction in Human Brain Function.

    Science.gov (United States)

    Hari, Riitta; Henriksson, Linda; Malinen, Sanna; Parkkonen, Lauri

    2015-10-07

    People are embedded in social interaction that shapes their brains throughout lifetime. Instead of emerging from lower-level cognitive functions, social interaction could be the default mode via which humans communicate with their environment. Should this hypothesis be true, it would have profound implications on how we think about brain functions and how we dissect and simulate them. We suggest that the research on the brain basis of social cognition and interaction should move from passive spectator science to studies including engaged participants and simultaneous recordings from the brains of the interacting persons. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Reflectance diffuse optical tomography. Its application to human brain mapping

    International Nuclear Information System (INIS)

    Ueda, Yukio; Yamanaka, Takeshi; Yamashita, Daisuke; Suzuki, Toshihiko; Ohmae, Etsuko; Oda, Motoki; Yamashita, Yutaka

    2005-01-01

    We report the successful application of reflectance diffuse optical tomography (DOT) using near-infrared light with the new reconstruction algorithm that we developed to the observation of regional hemodynamic changes in the brain under specific mental tasks. Our results reveal the heterogeneous distribution of oxyhemoglobin and deoxyhemoglobin in the brain, showing complementary images of oxyhemoglobin and deoxyhemoglobin changes in certain regions. We conclude that our reflectance DOT has practical potential for human brain mapping, as well as in the diagnostic imaging of brain diseases. (author)

  18. A hypothesis on improving foreign accents by optimizing variability in vocal learning brain circuits.

    Science.gov (United States)

    Simmonds, Anna J

    2015-01-01

    Rapid vocal motor learning is observed when acquiring a language in early childhood, or learning to speak another language later in life. Accurate pronunciation is one of the hardest things for late learners to master and they are almost always left with a non-native accent. Here, I propose a novel hypothesis that this accent could be improved by optimizing variability in vocal learning brain circuits during learning. Much of the neurobiology of human vocal motor learning has been inferred from studies on songbirds. Jarvis (2004) proposed the hypothesis that as in songbirds there are two pathways in humans: one for learning speech (the striatal vocal learning pathway), and one for production of previously learnt speech (the motor pathway). Learning new motor sequences necessary for accurate non-native pronunciation is challenging and I argue that in late learners of a foreign language the vocal learning pathway becomes inactive prematurely. The motor pathway is engaged once again and learners maintain their original native motor patterns for producing speech, resulting in speaking with a foreign accent. Further, I argue that variability in neural activity within vocal motor circuitry generates vocal variability that supports accurate non-native pronunciation. Recent theoretical and experimental work on motor learning suggests that variability in the motor movement is necessary for the development of expertise. I propose that there is little trial-by-trial variability when using the motor pathway. When using the vocal learning pathway variability gradually increases, reflecting an exploratory phase in which learners try out different ways of pronouncing words, before decreasing and stabilizing once the "best" performance has been identified. The hypothesis proposed here could be tested using behavioral interventions that optimize variability and engage the vocal learning pathway for longer, with the prediction that this would allow learners to develop new motor

  19. The immune response of the human brain to abdominal surgery

    DEFF Research Database (Denmark)

    Forsberg, Anton; Cervenka, Simon; Jonsson Fagerlund, Malin

    2017-01-01

    OBJECTIVE: Surgery launches a systemic inflammatory reaction that reaches the brain and associates with immune activation and cognitive decline. Although preclinical studies have in part described this systemic-to-brain signaling pathway, we lack information on how these changes appear in humans....... This study examines the short- and long-term impact of abdominal surgery on the human brain immune system by positron emission tomography (PET) in relation to blood immune reactivity, plasma inflammatory biomarkers, and cognitive function. METHODS: Eight males undergoing prostatectomy under general...... anesthesia were included. Prior to surgery (baseline), at postoperative days 3 to 4, and after 3 months, patients were examined using [11C]PBR28 brain PET imaging to assess brain immune cell activation. Concurrently, systemic inflammatory biomarkers, ex vivo blood tests on immunoreactivity...

  20. Human Spaceflight Conjunction Assessment: Lessons Learned

    Science.gov (United States)

    Smith, Jason T.

    2011-01-01

    This viewgraph presentation reviews the process of a human space flight conjunction assessment and lessons learned from the more than twelve years of International Space Station (ISS) operations. Also, the application of these lessons learned to a recent ISS conjunction assessment with object 84180 on July 16, 2009 is also presented.

  1. An Annotated Bibliography of the Literature Dealing with the Incorporation of Right Brain Learning into Left Brain Oriented Schools.

    Science.gov (United States)

    Lewallen, Martha

    Articles and documents concerning brain growth and hemispheric specialization, theories of cognitive style, educational implications of brain research, and right-brain learning activities are cited in this annotated bibliography. Citations are preceded by a glossary of terms and followed by a brief review of the assembled literature. Educational…

  2. Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

    Science.gov (United States)

    Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

    2009-10-28

    Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

  3. Do glutathione levels decline in aging human brain?

    Science.gov (United States)

    Tong, Junchao; Fitzmaurice, Paul S; Moszczynska, Anna; Mattina, Katie; Ang, Lee-Cyn; Boileau, Isabelle; Furukawa, Yoshiaki; Sailasuta, Napapon; Kish, Stephen J

    2016-04-01

    For the past 60 years a major theory of "aging" is that age-related damage is largely caused by excessive uncompensated oxidative stress. The ubiquitous tripeptide glutathione is a major antioxidant defense mechanism against reactive free radicals and has also served as a marker of changes in oxidative stress. Some (albeit conflicting) animal data suggest a loss of glutathione in brain senescence, which might compromise the ability of the aging brain to meet the demands of oxidative stress. Our objective was to establish whether advancing age is associated with glutathione deficiency in human brain. We measured reduced glutathione (GSH) levels in multiple regions of autopsied brain of normal subjects (n=74) aged one day to 99 years. Brain GSH levels during the infancy/teenage years were generally similar to those in the oldest examined adult group (76-99 years). During adulthood (23-99 years) GSH levels remained either stable (occipital cortex) or increased (caudate nucleus, frontal and cerebellar cortices). To the extent that GSH levels represent glutathione antioxidant capacity, our postmortem data suggest that human brain aging is not associated with declining glutathione status. We suggest that aged healthy human brains can maintain antioxidant capacity related to glutathione and that an age-related increase in GSH levels in some brain regions might possibly be a compensatory response to increased oxidative stress. Since our findings, although suggestive, suffer from the generic limitations of all postmortem brain studies, we also suggest the need for "replication" investigations employing the new (1)H MRS imaging procedures in living human brain. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Maze learning by a hybrid brain-computer system.

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-13

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  5. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  6. Effects of Sex Steroids in the Human Brain.

    Science.gov (United States)

    Nguyen, Tuong-Vi; Ducharme, Simon; Karama, Sherif

    2017-11-01

    Sex steroids are thought to play a critical developmental role in shaping both cortical and subcortical structures in the human brain. Periods of profound changes in sex steroids invariably coincide with the onset of sex differences in mental health vulnerability, highlighting the importance of sex steroids in determining sexual differentiation of the brain. Yet, most of the evidence for the central effects of sex steroids relies on non-human studies, as several challenges have limited our understanding of these effects in humans: the lack of systematic assessment of the human sex steroid metabolome, the different developmental trajectories of specific sex steroids, the impact of genetic variation and epigenetic changes, and the plethora of interactions between sex steroids, sex chromosomes, neurotransmitters, and other hormonal systems. Here we review how multimodal strategies may be employed to bridge the gap between the basic and clinical understanding of sex steroid-related changes in the human brain.

  7. Conscious brain-to-brain communication in humans using non-invasive technologies.

    Science.gov (United States)

    Grau, Carles; Ginhoux, Romuald; Riera, Alejandro; Nguyen, Thanh Lam; Chauvat, Hubert; Berg, Michel; Amengual, Julià L; Pascual-Leone, Alvaro; Ruffini, Giulio

    2014-01-01

    Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

  8. Conscious brain-to-brain communication in humans using non-invasive technologies.

    Directory of Open Access Journals (Sweden)

    Carles Grau

    Full Text Available Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI. These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B communication between subjects (hyperinteraction. Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG changes with a CBI inducing the conscious perception of phosphenes (light flashes through neuronavigated, robotized transcranial magnetic stimulation (TMS, with special care taken to block sensory (tactile, visual or auditory cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

  9. How does a specific learning and memory system in the mammalian brain gain control of behavior?

    Science.gov (United States)

    McDonald, Robert J; Hong, Nancy S

    2013-11-01

    This review addresses a fundamental, yet poorly understood set of issues in systems neuroscience. The issues revolve around conceptualizations of the organization of learning and memory in the mammalian brain. One intriguing, and somewhat popular, conceptualization is the idea that there are multiple learning and memory systems in the mammalian brain and they interact in different ways to influence and/or control behavior. This approach has generated interesting empirical and theoretical work supporting this view. One issue that needs to be addressed is how these systems influence or gain control of voluntary behavior. To address this issue, we clearly specify what we mean by a learning and memory system. We then review two types of processes that might influence which memory system gains control of behavior. One set of processes are external factors that can affect which system controls behavior in a given situation including task parameters like the kind of information available to the subject, types of training experience, and amount of training. The second set of processes are brain mechanisms that might influence what memory system controls behavior in a given situation including executive functions mediated by the prefrontal cortex; switching mechanisms mediated by ascending neurotransmitter systems, the unique role of the hippocampus during learning. The issue of trait differences in control of different learning and memory systems will also be considered in which trait differences in learning and memory function are thought to potentially emerge from differences in level of prefrontal influence, differences in plasticity processes, differences in ascending neurotransmitter control, differential access to effector systems like motivational and motor systems. Finally, we present scenarios in which different mechanisms might interact. This review was conceived to become a jumping off point for new work directed at understanding these issues. The outcome of

  10. Learning-based meta-algorithm for MRI brain extraction.

    Science.gov (United States)

    Shi, Feng; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

    2011-01-01

    Multiple-segmentation-and-fusion method has been widely used for brain extraction, tissue segmentation, and region of interest (ROI) localization. However, such studies are hindered in practice by their computational complexity, mainly coming from the steps of template selection and template-to-subject nonlinear registration. In this study, we address these two issues and propose a novel learning-based meta-algorithm for MRI brain extraction. Specifically, we first use exemplars to represent the entire template library, and assign the most similar exemplar to the test subject. Second, a meta-algorithm combining two existing brain extraction algorithms (BET and BSE) is proposed to conduct multiple extractions directly on test subject. Effective parameter settings for the meta-algorithm are learned from the training data and propagated to subject through exemplars. We further develop a level-set based fusion method to combine multiple candidate extractions together with a closed smooth surface, for obtaining the final result. Experimental results show that, with only a small portion of subjects for training, the proposed method is able to produce more accurate and robust brain extraction results, at Jaccard Index of 0.956 +/- 0.010 on total 340 subjects under 6-fold cross validation, compared to those by the BET and BSE even using their best parameter combinations.

  11. Neurofeedback Control of the Human GABAergic System Using Non-invasive Brain Stimulation.

    Science.gov (United States)

    Koganemaru, Satoko; Mikami, Yusuke; Maezawa, Hitoshi; Ikeda, Satoshi; Ikoma, Katsunori; Mima, Tatsuya

    2018-06-01

    Neurofeedback has been a powerful method for self-regulating brain activities to elicit potential ability of human mind. GABA is a major inhibitory neurotransmitter in the central nervous system. Transcranial magnetic stimulation (TMS) is a tool that can evaluate the GABAergic system within the primary motor cortex (M1) using paired-pulse stimuli, short intracortical inhibition (SICI). Herein we investigated whether neurofeedback learning using SICI enabled us to control the GABAergic system within the M1 area. Forty-five healthy subjects were randomly divided into two groups: those receiving SICI neurofeedback learning or those receiving no neurofeedback (control) learning. During both learning periods, subjects made attempts to change the size of a circle, which was altered according to the degree of SICI in the SICI neurofeedback learning group, and which was altered independent of the degree of SICI in the control learning group. Results demonstrated that the SICI neurofeedback learning group showed a significant enhancement in SICI. Moreover, this group showed a significant reduction in choice reaction time compared to the control group. Our findings indicate that humans can intrinsically control the intracortical GABAergic system within M1 and can thus improve motor behaviors by SICI neurofeedback learning. SICI neurofeedback learning is a novel and promising approach to control our neural system and potentially represents a new therapy for patients with abnormal motor symptoms caused by CNS disorders. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

  12. Cyto- and receptor architectonic mapping of the human brain.

    Science.gov (United States)

    Palomero-Gallagher, Nicola; Zilles, Karl

    2018-01-01

    Mapping of the human brain is more than the generation of an atlas-based parcellation of brain regions using histologic or histochemical criteria. It is the attempt to provide a topographically informed model of the structural and functional organization of the brain. To achieve this goal a multimodal atlas of the detailed microscopic and neurochemical structure of the brain must be registered to a stereotaxic reference space or brain, which also serves as reference for topographic assignment of functional data, e.g., functional magnet resonance imaging, electroencephalography, or magnetoencephalography, as well as metabolic imaging, e.g., positron emission tomography. Although classic maps remain pioneering steps, they do not match recent concepts of the functional organization in many regions, and suffer from methodic drawbacks. This chapter provides a summary of the recent status of human brain mapping, which is based on multimodal approaches integrating results of quantitative cyto- and receptor architectonic studies with focus on the cerebral cortex in a widely used reference brain. Descriptions of the methods for observer-independent and statistically testable cytoarchitectonic parcellations, quantitative multireceptor mapping, and registration to the reference brain, including the concept of probability maps and a toolbox for using the maps in functional neuroimaging studies, are provided. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. The intrinsic geometry of the human brain connectome.

    Science.gov (United States)

    Ye, Allen Q; Ajilore, Olusola A; Conte, Giorgio; GadElkarim, Johnson; Thomas-Ramos, Galen; Zhan, Liang; Yang, Shaolin; Kumar, Anand; Magin, Richard L; G Forbes, Angus; Leow, Alex D

    2015-12-01

    This paper describes novel methods for constructing the intrinsic geometry of the human brain connectome using dimensionality-reduction techniques. We posit that the high-dimensional, complex geometry that represents this intrinsic topology can be mathematically embedded into lower dimensions using coupling patterns encoded in the corresponding brain connectivity graphs. We tested both linear and nonlinear dimensionality-reduction techniques using the diffusion-weighted structural connectome data acquired from a sample of healthy subjects. Results supported the nonlinearity of brain connectivity data, as linear reduction techniques such as the multidimensional scaling yielded inferior lower-dimensional embeddings. To further validate our results, we demonstrated that for tractography-derived structural connectome more influential regions such as rich-club members of the brain are more centrally mapped or embedded. Further, abnormal brain connectivity can be visually understood by inspecting the altered geometry of these three-dimensional (3D) embeddings that represent the topology of the human brain, as illustrated using simulated lesion studies of both targeted and random removal. Last, in order to visualize brain's intrinsic topology we have developed software that is compatible with virtual reality technologies, thus allowing researchers to collaboratively and interactively explore and manipulate brain connectome data.

  14. Ecology of the aging human brain.

    Science.gov (United States)

    Sonnen, Joshua A; Santa Cruz, Karen; Hemmy, Laura S; Woltjer, Randall; Leverenz, James B; Montine, Kathleen S; Jack, Clifford R; Kaye, Jeffrey; Lim, Kelvin; Larson, Eric B; White, Lon; Montine, Thomas J

    2011-08-01

    Alzheimer disease, cerebral vascular brain injury, and isocortical Lewy body disease (LBD) are the major contributors to dementia in community- and population-based studies. To estimate the prevalence of clinically silent forms of these diseases in cognitively normal (CN) adults. Autopsy study. Community- and population based. A total of 1672 brain autopsies from the Adult Changes in Thought study, Honolulu-Asia Aging Study, Nun Study, and Oregon Brain Aging Study, of which 424 met the criteria for CN. Of these, 336 cases had a comprehensive neuropathologic examination of neuritic plaque density, Braak stage for neurofibrillary tangles, LB distribution, and number of cerebral microinfarcts. Forty-seven percent of CN cases had moderate or frequent neuritic plaque density; of these, 6% also had Braak stage V or VI for neurofibrillary tangles. Fifteen percent of CN cases had medullary LBD; 8% also had nigral and 4% isocortical LBD. The presence of any cerebral microinfarcts was identified in 33% and of high-level cerebral microinfarcts in 10% of CN individuals. Overall, the burden of lesions in each individual and their comorbidity varied widely within each study but were similar across studies. These data show an individually varying complex convergence of subclinical diseases in the brain of older CN adults. Appreciating this ecology should help guide future biomarker and neuroimaging studies and clinical trials that focus on community- and population-based cohorts.

  15. Insulin action in the human brain: evidence from neuroimaging studies.

    Science.gov (United States)

    Kullmann, S; Heni, M; Fritsche, A; Preissl, H

    2015-06-01

    Thus far, little is known about the action of insulin in the human brain. Nonetheless, recent advances in modern neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) or magnetoencephalography (MEG), have made it possible to investigate the action of insulin in the brain in humans, providing new insights into the pathogenesis of brain insulin resistance and obesity. Using MEG, the clinical relevance of the action of insulin in the brain was first identified, linking cerebral insulin resistance with peripheral insulin resistance, genetic predisposition and weight loss success in obese adults. Although MEG is a suitable tool for measuring brain activity mainly in cortical areas, fMRI provides high spatial resolution for cortical as well as subcortical regions. Thus, the action of insulin can be detected within all eating behaviour relevant regions, which include regions deeply located within the brain, such as the hypothalamus, midbrain and brainstem, as well as regions within the striatum. In this review, we outline recent advances in the field of neuroimaging aiming to investigate the action of insulin in the human brain using different routes of insulin administration. fMRI studies have shown a significant insulin-induced attenuation predominantly in the occipital and prefrontal cortical regions and the hypothalamus, successfully localising insulin-sensitive brain regions in healthy, mostly normal-weight individuals. However, further studies are needed to localise brain areas affected by insulin resistance in obese individuals, which is an important prerequisite for selectively targeting brain insulin resistance in obesity. © 2015 British Society for Neuroendocrinology.

  16. Cognitive genomics: Linking genes to behavior in the human brain

    Directory of Open Access Journals (Sweden)

    Genevieve Konopka

    2017-02-01

    Full Text Available Correlations of genetic variation in DNA with functional brain activity have already provided a starting point for delving into human cognitive mechanisms. However, these analyses do not provide the specific genes driving the associations, which are complicated by intergenic localization as well as tissue-specific epigenetics and expression. The use of brain-derived expression datasets could build upon the foundation of these initial genetic insights and yield genes and molecular pathways for testing new hypotheses regarding the molecular bases of human brain development, cognition, and disease. Thus, coupling these human brain gene expression data with measurements of brain activity may provide genes with critical roles in brain function. However, these brain gene expression datasets have their own set of caveats, most notably a reliance on postmortem tissue. In this perspective, I summarize and examine the progress that has been made in this realm to date, and discuss the various frontiers remaining, such as the inclusion of cell-type-specific information, additional physiological measurements, and genomic data from patient cohorts.

  17. Decision theory, reinforcement learning, and the brain.

    Science.gov (United States)

    Dayan, Peter; Daw, Nathaniel D

    2008-12-01

    Decision making is a core competence for animals and humans acting and surviving in environments they only partially comprehend, gaining rewards and punishments for their troubles. Decision-theoretic concepts permeate experiments and computational models in ethology, psychology, and neuroscience. Here, we review a well-known, coherent Bayesian approach to decision making, showing how it unifies issues in Markovian decision problems, signal detection psychophysics, sequential sampling, and optimal exploration and discuss paradigmatic psychological and neural examples of each problem. We discuss computational issues concerning what subjects know about their task and how ambitious they are in seeking optimal solutions; we address algorithmic topics concerning model-based and model-free methods for making choices; and we highlight key aspects of the neural implementation of decision making.

  18. Sibling rivalry among paralogs promotes evolution of the human brain.

    Science.gov (United States)

    Tyler-Smith, Chris; Xue, Yali

    2012-05-11

    Geneticists have long sought to identify the genetic changes that made us human, but pinpointing the functionally relevant changes has been challenging. Two papers in this issue suggest that partial duplication of SRGAP2, producing an incomplete protein that antagonizes the original, contributed to human brain evolution. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. Shortcomings of the Human Brain and Remedial Action by Religion

    Science.gov (United States)

    Reich, K. Helmut

    2010-01-01

    There is no consensus as to whether, and if so, in which regard and to what extent science and religion is needed for human survival. Here a circumscribed domain is taken up: the sovereignty and sufficiency of the human brain in this context. Several of its shortcomings are pointed out. Religion and other aspects of culture are needed for remedial…

  20. Gene expression in the aging human brain: an overview.

    Science.gov (United States)

    Mohan, Adith; Mather, Karen A; Thalamuthu, Anbupalam; Baune, Bernhard T; Sachdev, Perminder S

    2016-03-01

    The review aims to provide a summary of recent developments in the study of gene expression in the aging human brain. Profiling differentially expressed genes or 'transcripts' in the human brain over the course of normal aging has provided valuable insights into the biological pathways that appear activated or suppressed in late life. Genes mediating neuroinflammation and immune system activation in particular, show significant age-related upregulation creating a state of vulnerability to neurodegenerative and neuropsychiatric disease in the aging brain. Cellular ionic dyshomeostasis and age-related decline in a host of molecular influences on synaptic efficacy may underlie neurocognitive decline in later life. Critically, these investigations have also shed light on the mobilization of protective genetic responses within the aging human brain that help determine health and disease trajectories in older age. There is growing interest in the study of pre and posttranscriptional regulators of gene expression, and the role of noncoding RNAs in particular, as mediators of the phenotypic diversity that characterizes human brain aging. Gene expression studies in healthy brain aging offer an opportunity to unravel the intricately regulated cellular underpinnings of neurocognitive aging as well as disease risk and resiliency in late life. In doing so, new avenues for early intervention in age-related neurodegenerative disease could be investigated with potentially significant implications for the development of disease-modifying therapies.

  1. Development of human brain structural networks through infancy and childhood.

    Science.gov (United States)

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

    2015-05-01

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

  2. Development of Human Brain Structural Networks Through Infancy and Childhood

    Science.gov (United States)

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

    2015-01-01

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

  3. BrainNet Viewer: a network visualization tool for human brain connectomics.

    Science.gov (United States)

    Xia, Mingrui; Wang, Jinhui; He, Yong

    2013-01-01

    The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

  4. BrainNet Viewer: a network visualization tool for human brain connectomics.

    Directory of Open Access Journals (Sweden)

    Mingrui Xia

    Full Text Available The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI, we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/.

  5. Public School Teachers' Knowledge, Perception, and Implementation of Brain-Based Learning Practices

    Science.gov (United States)

    Wachob, David A.

    2012-01-01

    The purpose of this study was to determine K-12 teachers' knowledge, beliefs, and practices of brain-based learning strategies in western Pennsylvania schools. The following five research questions were explored: (a) What is the extent of knowledge K-12 public school teachers have about the indicators of brain-based learning and Brain Gym?; (b) To…

  6. Connecting Learning: Brain-Based Strategies for Linking Prior Knowledge in the Library Media Center

    Science.gov (United States)

    Vanderbilt, Kathi L.

    2005-01-01

    The brain is a complex organ and learning is a complex process. While there is not complete agreement among researchers about brain-based learning and its direct connection to neuroscience, knowledge about the brain as well as the examination of cognitive psychology, anthropology, professional experience, and educational research can provide…

  7. How we learn to make decisions: rapid propagation of reinforcement learning prediction errors in humans.

    Science.gov (United States)

    Krigolson, Olav E; Hassall, Cameron D; Handy, Todd C

    2014-03-01

    Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. E., Pierce, L. J., Holroyd, C. B., & Tanaka, J. W. Learning to become an expert: Reinforcement learning and the acquisition of perceptual expertise. Journal of Cognitive Neuroscience, 21, 1833-1840, 2009; Bayer, H. M., & Glimcher, P. W. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141, 2005; O'Doherty, J. P. Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology, 14, 769-776, 2004; Holroyd, C. B., & Coles, M. G. H. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709, 2002]. Here, we used the brain ERP technique to demonstrate that not only do rewards elicit a neural response akin to a prediction error but also that this signal rapidly diminished and propagated to the time of choice presentation with learning. Specifically, in a simple, learnable gambling task, we show that novel rewards elicited a feedback error-related negativity that rapidly decreased in amplitude with learning. Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward

  8. PENDEKATAN BRAIN BASED LEARNING DALAM PENANAMAN NILAI BUDAYA MELALUI PENDIDIKAN FORMAL

    Directory of Open Access Journals (Sweden)

    Zulfikri Anas

    2013-04-01

    Full Text Available Tujuan penelitian ini adalah untuk mengeksplorasi gagasan penggunaan pendekatan brain based learning dalam penanaman nilai budaya melalui pendidikan formal. Undang-Undang  menyatakan dengan tegas bahwa pendidikan adalah upaya sadar untuk mengembangkan potensi setiap siswa agar menjadi warga negara yang cerdas, kreatif dan berakhlak mulia.  Nilai-nilai budaya  mengkondisikan manusia untuk hidup saling menghargai dengan berbagai nilai-nilai yang diyakini bersama. Seyogyanya kehidupan menjadi harmonis karena semua yang melingkupi kehidupan manusia menggiring ke arah sana. Akan tetapi mengapa tatakrama, kreatifitas, kemandirian dan ciri-ciri kemanusiaan lainnya menjadi memudar? Dunia pendidikan termasuk yang paling disoroti. Berbagai pendapat ekstrim menyatakan, pendidikan telah mencabut anak dari akar budayanya. Penyebabnya adalah pembelajaran yang monoton, mengekang, dan mempoisisikan anak sebagai obyek pembelajaran, bukan subyek yang aktif. Untuk mengembalikan fungsi pendidikan ke arah yang diharapkan, harus diciptakan iklim pembelajaran yang semirip mungkin dengan kehidupan nyata serta pengintegrasian kurikulum dengan hal-hal nyata dalam kehidupan. Kondisi ini akan mendorong  peserta didik  untuk berkembang dan menjadi anak-anak yang cerdas, kreatif, dan berakhlak mulia. Hal inilah yang menjadi salah satu sasaran penerapan brain based learning. The objective of this study is to explore ​​the use of brain based learning approach in character education ​​through formal education. Law insists that education is a conscious effort to develop the potential of every student to become a smart, creative, and noble citizen. Cultural values suggest human condition to live with mutual respect with different values ​​shared together. If this condition is achieved, a harmonious life for all human life can be realized. However, why manners, creativity, independence and other human traits is fading

  9. Expression of iron-related genes in human brain and brain tumors

    Directory of Open Access Journals (Sweden)

    Britton Robert S

    2009-04-01

    Full Text Available Abstract Background Defective iron homeostasis may be involved in the development of some diseases within the central nervous system. Although the expression of genes involved in normal iron balance has been intensively studied in other tissues, little is known about their expression in the brain. We investigated the mRNA levels of hepcidin (HAMP, HFE, neogenin (NEO1, transferrin receptor 1 (TFRC, transferrin receptor 2 (TFR2, and hemojuvelin (HFE2 in normal human brain, brain tumors, and astrocytoma cell lines. The specimens included 5 normal brain tissue samples, 4 meningiomas, one medulloblastoma, 3 oligodendrocytic gliomas, 2 oligoastrocytic gliomas, 8 astrocytic gliomas, and 3 astrocytoma cell lines. Results Except for hemojuvelin, all genes studied had detectable levels of mRNA. In most tumor types, the pattern of gene expression was diverse. Notable findings include high expression of transferrin receptor 1 in the hippocampus and medulla oblongata compared to other brain regions, low expression of HFE in normal brain with elevated HFE expression in meningiomas, and absence of hepcidin mRNA in astrocytoma cell lines despite expression in normal brain and tumor specimens. Conclusion These results indicate that several iron-related genes are expressed in normal brain, and that their expression may be dysregulated in brain tumors.

  10. Electrical Guidance of Human Stem Cells in the Rat Brain

    Directory of Open Access Journals (Sweden)

    Jun-Feng Feng

    2017-07-01

    Full Text Available Limited migration of neural stem cells in adult brain is a roadblock for the use of stem cell therapies to treat brain diseases and injuries. Here, we report a strategy that mobilizes and guides migration of stem cells in the brain in vivo. We developed a safe stimulation paradigm to deliver directional currents in the brain. Tracking cells expressing GFP demonstrated electrical mobilization and guidance of migration of human neural stem cells, even against co-existing intrinsic cues in the rostral migration stream. Transplanted cells were observed at 3 weeks and 4 months after stimulation in areas guided by the stimulation currents, and with indications of differentiation. Electrical stimulation thus may provide a potential approach to facilitate brain stem cell therapies.

  11. Three-dimensional morphology of the human embryonic brain

    Directory of Open Access Journals (Sweden)

    N. Shiraishi

    2015-09-01

    Full Text Available The morphogenesis of the cerebral vesicles and ventricles was visualized in 3D movies using images derived from human embryo specimens between Carnegie stage 13 and 23 from the Kyoto Collection. These images were acquired with a magnetic resonance microscope equipped with a 2.35-T superconducting magnet. Three-dimensional images using the same scale demonstrated brain development and growth effectively. The non-uniform thickness of the brain tissue, which may indicate brain differentiation, was visualized with thickness-based surface color mapping. A closer view was obtained of the unique and complicated differentiation of the rhombencephalon, especially with regard to the internal view and thickening of the brain tissue. The present data contribute to a better understanding of brain and cerebral ventricle development.

  12. The maternal brain and its plasticity in humans

    Science.gov (United States)

    Kim, Pilyoung; Strathearn, Lane; Swain, James E.

    2015-01-01

    Early mother-infant relationships play important roles in infants’ optimal development. New mothers undergo neurobiological changes that support developing mother-infant relationships regardless of great individual differences in those relationships. In this article, we review the neural plasticity in human mothers’ brains based on functional magnetic resonance imaging (fMRI) studies. First, we review the neural circuits that are involved in establishing and maintaining mother-infant relationships. Second, we discuss early postpartum factors (e.g., birth and feeding methods, hormones, and parental sensitivity) that are associated with individual differences in maternal brain neuroplasticity. Third, we discuss abnormal changes in the maternal brain related to psychopathology (i.e., postpartum depression, posttraumatic stress disorder, substance abuse) and potential brain remodeling associated with interventions. Last, we highlight potentially important future research directions to better understand normative changes in the maternal brain and risks for abnormal changes that may disrupt early mother-infant relationships. PMID:26268151

  13. Dissociation of Category-Learning Systems via Brain Potentials

    Directory of Open Access Journals (Sweden)

    Robert G Morrison

    2015-07-01

    Full Text Available Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (i.e., Gabor patches that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit rule-based process and the other an implicit information-integration process. We monitored brain activity with scalp electroencephalography (EEG while each participant (1 passively observed stimuli represented of both distributions, (2 categorized stimuli from one distribution, and, one week later, (3 categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs for correct and incorrect trials were used to identify neural differences in rule-based and information-integration categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150 - 250 ms, likely reflecting the degree of holistic processing. A stimulus-locked late positive complex associated with explicit memory updating was modulated by accuracy in the rule-based, but not the information-integration task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the rule-based, but not the information-integration condition. These results provide additional evidence for distinct brain mechanisms supporting rule-based versus implicit information-integration category learning and use.

  14. Addiction Circuitry in the Human Brain*

    OpenAIRE

    Volkow, Nora D.; Wang, Gene-Jack; Fowler, Joanna S.; Tomasi, Dardo

    2011-01-01

    A major challenge in understanding substance-use disorders lies in uncovering why some individuals become addicted when exposed to drugs, whereas others do not. Although genetic, developmental, and environmental factors are recognized as major contributors to a person’s risk of becoming addicted, the neurobiological processes that underlie this vulnerability are still poorly understood. Imaging studies suggest that individual variations in key dopamine-modulated brain circuits, including circ...

  15. A family of hyperelastic models for human brain tissue

    Science.gov (United States)

    Mihai, L. Angela; Budday, Silvia; Holzapfel, Gerhard A.; Kuhl, Ellen; Goriely, Alain

    2017-09-01

    Experiments on brain samples under multiaxial loading have shown that human brain tissue is both extremely soft when compared to other biological tissues and characterized by a peculiar elastic response under combined shear and compression/tension: there is a significant increase in shear stress with increasing axial compression compared to a moderate increase with increasing axial tension. Recent studies have revealed that many widely used constitutive models for soft biological tissues fail to capture this characteristic response. Here, guided by experiments of human brain tissue, we develop a family of modeling approaches that capture the elasticity of brain tissue under varying simple shear superposed on varying axial stretch by exploiting key observations about the behavior of the nonlinear shear modulus, which can be obtained directly from the experimental data.

  16. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

    Science.gov (United States)

    Neftci, Emre O.; Pedroni, Bruno U.; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert

    2016-01-01

    Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware. PMID:27445650

  18. Fundamental Dynamical Modes Underlying Human Brain Synchronization

    Directory of Open Access Journals (Sweden)

    Catalina Alvarado-Rojas

    2012-01-01

    Full Text Available Little is known about the long-term dynamics of widely interacting cortical and subcortical networks during the wake-sleep cycle. Using large-scale intracranial recordings of epileptic patients during seizure-free periods, we investigated local- and long-range synchronization between multiple brain regions over several days. For such high-dimensional data, summary information is required for understanding and modelling the underlying dynamics. Here, we suggest that a compact yet useful representation is given by a state space based on the first principal components. Using this representation, we report, with a remarkable similarity across the patients with different locations of electrode placement, that the seemingly complex patterns of brain synchrony during the wake-sleep cycle can be represented by a small number of characteristic dynamic modes. In this space, transitions between behavioral states occur through specific trajectories from one mode to another. These findings suggest that, at a coarse level of temporal resolution, the different brain states are correlated with several dominant synchrony patterns which are successively activated across wake-sleep states.

  19. Functional organization of the transcriptome in human brain

    Science.gov (United States)

    Oldham, Michael C; Konopka, Genevieve; Iwamoto, Kazuya; Langfelder, Peter; Kato, Tadafumi; Horvath, Steve; Geschwind, Daniel H

    2009-01-01

    The enormous complexity of the human brain ultimately derives from a finite set of molecular instructions encoded in the human genome. These instructions can be directly studied by exploring the organization of the brain’s transcriptome through systematic analysis of gene coexpression relationships. We analyzed gene coexpression relationships in microarray data generated from specific human brain regions and identified modules of coexpressed genes that correspond to neurons, oligodendrocytes, astrocytes and microglia. These modules provide an initial description of the transcriptional programs that distinguish the major cell classes of the human brain and indicate that cell type–specific information can be obtained from whole brain tissue without isolating homogeneous populations of cells. Other modules corresponded to additional cell types, organelles, synaptic function, gender differences and the subventricular neurogenic niche. We found that subventricular zone astrocytes, which are thought to function as neural stem cells in adults, have a distinct gene expression pattern relative to protoplasmic astrocytes. Our findings provide a new foundation for neurogenetic inquiries by revealing a robust and previously unrecognized organization to the human brain transcriptome. PMID:18849986

  20. Small-world human brain networks: Perspectives and challenges.

    Science.gov (United States)

    Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

    2017-06-01

    Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. NMR relaxation times in human brain tumors (preliminary results)

    International Nuclear Information System (INIS)

    Benoist, L.; Certaines, J. de; Chatel, M.; Menault, F.

    1981-01-01

    Since the early work of Damadian in 1971, proton NMR studies of tumors has been well documented. Present study concerns the spin-lattice T 1 and spin-spin T 2 relaxation times of normal dog brain according to the histological differentiation and of 35 human benignant or malignant tumors. The results principally show T 2 important variations between white and gray substance in normal brain but no discrimination between malignant and benignant tumors [fr

  2. Chemotherapy disrupts learning, neurogenesis and theta activity in the adult brain.

    Science.gov (United States)

    Nokia, Miriam S; Anderson, Megan L; Shors, Tracey J

    2012-12-01

    Chemotherapy, especially if prolonged, disrupts attention, working memory and speed of processing in humans. Most cancer drugs that cross the blood-brain barrier also decrease adult neurogenesis. Because new neurons are generated in the hippocampus, this decrease may contribute to the deficits in working memory and related thought processes. The neurophysiological mechanisms that underlie these deficits are generally unknown. A possible mediator is hippocampal oscillatory activity within the theta range (3-12 Hz). Theta activity predicts and promotes efficient learning in healthy animals and humans. Here, we hypothesised that chemotherapy disrupts learning via decreases in hippocampal adult neurogenesis and theta activity. Temozolomide was administered to adult male Sprague-Dawley rats in a cyclic manner for several weeks. Treatment was followed by training with different types of eyeblink classical conditioning, a form of associative learning. Chemotherapy reduced both neurogenesis and endogenous theta activity, as well as disrupted learning and related theta-band responses to the conditioned stimulus. The detrimental effects of temozolomide only occurred after several weeks of treatment, and only on a task that requires the association of events across a temporal gap and not during training with temporally overlapping stimuli. Chemotherapy did not disrupt the memory for previously learned associations, a memory independent of (new neurons in) the hippocampus. In conclusion, prolonged systemic chemotherapy is associated with a decrease in hippocampal adult neurogenesis and theta activity that may explain the selective deficits in processes of learning that describe the 'chemobrain'. © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  3. A psychology of the human brain-gut-microbiome axis.

    Science.gov (United States)

    Allen, Andrew P; Dinan, Timothy G; Clarke, Gerard; Cryan, John F

    2017-04-01

    In recent years, we have seen increasing research within neuroscience and biopsychology on the interactions between the brain, the gastrointestinal tract, the bacteria within the gastrointestinal tract, and the bidirectional relationship between these systems: the brain-gut-microbiome axis. Although research has demonstrated that the gut microbiota can impact upon cognition and a variety of stress-related behaviours, including those relevant to anxiety and depression, we still do not know how this occurs. A deeper understanding of how psychological development as well as social and cultural factors impact upon the brain-gut-microbiome axis will contextualise the role of the axis in humans and inform psychological interventions that improve health within the brain-gut-microbiome axis. Interventions ostensibly aimed at ameliorating disorders in one part of the brain-gut-microbiome axis (e.g., psychotherapy for depression) may nonetheless impact upon other parts of the axis (e.g., microbiome composition and function), and functional gastrointestinal disorders such as irritable bowel syndrome represent a disorder of the axis, rather than an isolated problem either of psychology or of gastrointestinal function. The discipline of psychology needs to be cognisant of these interactions and can help to inform the future research agenda in this emerging field of research. In this review, we outline the role psychology has to play in understanding the brain-gut-microbiome axis, with a focus on human psychology and the use of research in laboratory animals to model human psychology.

  4. Distribution of vesicular glutamate transporters in the human brain

    Directory of Open Access Journals (Sweden)

    Erika eVigneault

    2015-03-01

    Full Text Available Glutamate is the major excitatory transmitter in the brain. Vesicular glutamate transporters (VGLUT1-3 are responsible for uploading glutamate into synaptic vesicles. VGLUT1 and VGLUT2 are considered as specific markers of canonical glutamatergic neurons, while VGLUT3 is found in neurons previously shown to use other neurotransmitters than glutamate. Although there exists a rich literature on the localization of these glutamatergic markers in the rodent brain, little is currently known about the distribution of VGLUT1-3 in the human brain. In the present study, using subtype specific probes and antisera, we examined the localization of the three vesicular glutamate transporters in the human brain by in situ hybridization, immunoautoradiography and immunohistochemistry. We found that the VGLUT1 transcript was highly expressed in the cerebral cortex, hippocampus and cerebellum, whereas VGLUT2 mRNA was mainly found in the thalamus and brainstem. VGLUT3 mRNA was localized in scarce neurons within the cerebral cortex, hippocampus, striatum and raphe nuclei. Following immunoautoradiographic labeling, intense VGLUT1- and VGLUT2-immunoreactivities were observed in all regions investigated (cerebral cortex, hippocampus, caudate-putamen, cerebellum, thalamus, amygdala, substantia nigra, raphe while VGLUT3 was absent from the thalamus and cerebellum. This extensive mapping of VGLUT1-3 in human brain reveals distributions that correspond for the most part to those previously described in rodent brains.

  5. Regional distribution of serotonin transporter protein in postmortem human brain

    Energy Technology Data Exchange (ETDEWEB)

    Kish, Stephen J. [Human Neurochemical Pathology Laboratory, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada)]. E-mail: Stephen_Kish@CAMH.net; Furukawa, Yoshiaki [Human Neurochemical Pathology Laboratory, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada); Chang Lijan [Human Neurochemical Pathology Laboratory, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada); Tong Junchao [Human Neurochemical Pathology Laboratory, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada); Ginovart, Nathalie [PET Centre, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada); Wilson, Alan [PET Centre, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada); Houle, Sylvain [PET Centre, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada); Meyer, Jeffrey H. [PET Centre, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8 (Canada)

    2005-02-01

    Introduction: The primary approach in assessing the status of brain serotonin neurons in human conditions such as major depression and exposure to the illicit drug ecstasy has been the use of neuroimaging procedures involving radiotracers that bind to the serotonin transporter (SERT). However, there has been no consistency in the selection of a 'SERT-free' reference region for the estimation of free and nonspecific binding, as occipital cortex, cerebellum and white matter have all been employed. Objective and Methods: To identify areas of human brain that might have very low SERT levels, we measured, by a semiquantitative Western blotting procedure, SERT protein immunoreactivity throughout the postmortem brain of seven normal adult subjects. Results: Serotonin transporter could be quantitated in all examined brain areas. However, the SERT concentration in cerebellar cortex and white matter were only at trace values, being approximately 20% of average cerebral cortex and 5% of average striatum values. Conclusion: Although none of the examined brain areas are completely free of SERT, human cerebellar cortex has low SERT binding as compared to other examined brain regions, with the exception of white matter. Since the cerebellar cortical SERT binding is not zero, this region will not be a suitable reference region for SERT radioligands with very low free and nonspecific binding. For SERT radioligands with reasonably high free and nonspecific binding, the cerebellar cortex should be a useful reference region, provided other necessary radioligand assumptions are met.

  6. Regional distribution of serotonin transporter protein in postmortem human brain

    International Nuclear Information System (INIS)

    Kish, Stephen J.; Furukawa, Yoshiaki; Chang Lijan; Tong Junchao; Ginovart, Nathalie; Wilson, Alan; Houle, Sylvain; Meyer, Jeffrey H.

    2005-01-01

    Introduction: The primary approach in assessing the status of brain serotonin neurons in human conditions such as major depression and exposure to the illicit drug ecstasy has been the use of neuroimaging procedures involving radiotracers that bind to the serotonin transporter (SERT). However, there has been no consistency in the selection of a 'SERT-free' reference region for the estimation of free and nonspecific binding, as occipital cortex, cerebellum and white matter have all been employed. Objective and Methods: To identify areas of human brain that might have very low SERT levels, we measured, by a semiquantitative Western blotting procedure, SERT protein immunoreactivity throughout the postmortem brain of seven normal adult subjects. Results: Serotonin transporter could be quantitated in all examined brain areas. However, the SERT concentration in cerebellar cortex and white matter were only at trace values, being approximately 20% of average cerebral cortex and 5% of average striatum values. Conclusion: Although none of the examined brain areas are completely free of SERT, human cerebellar cortex has low SERT binding as compared to other examined brain regions, with the exception of white matter. Since the cerebellar cortical SERT binding is not zero, this region will not be a suitable reference region for SERT radioligands with very low free and nonspecific binding. For SERT radioligands with reasonably high free and nonspecific binding, the cerebellar cortex should be a useful reference region, provided other necessary radioligand assumptions are met

  7. Tracing Trajectories of Audio-Visual Learning in the Infant Brain

    Science.gov (United States)

    Kersey, Alyssa J.; Emberson, Lauren L.

    2017-01-01

    Although infants begin learning about their environment before they are born, little is known about how the infant brain changes during learning. Here, we take the initial steps in documenting how the neural responses in the brain change as infants learn to associate audio and visual stimuli. Using functional near-infrared spectroscopy (fNRIS) to…

  8. Brain Activation During Singing: "Clef de Sol Activation" Is the "Concert" of the Human Brain.

    Science.gov (United States)

    Mavridis, Ioannis N; Pyrgelis, Efstratios-Stylianos

    2016-03-01

    Humans are the most complex singers in nature, and the human voice is thought by many to be the most beautiful musical instrument. Aside from spoken language, singing represents a second mode of acoustic communication in humans. The purpose of this review article is to explore the functional anatomy of the "singing" brain. Methodologically, the existing literature regarding activation of the human brain during singing was carefully reviewed, with emphasis on the anatomic localization of such activation. Relevant human studies are mainly neuroimaging studies, namely functional magnetic resonance imaging and positron emission tomography studies. Singing necessitates activation of several cortical, subcortical, cerebellar, and brainstem areas, served and coordinated by multiple neural networks. Functionally vital cortical areas of the frontal, parietal, and temporal lobes bilaterally participate in the brain's activation process during singing, confirming the latter's role in human communication. Perisylvian cortical activity of the right hemisphere seems to be the most crucial component of this activation. This also explains why aphasic patients due to left hemispheric lesions are able to sing but not speak the same words. The term clef de sol activation is proposed for this crucial perisylvian cortical activation due to the clef de sol shape of the topographical distribution of these cortical areas around the sylvian fissure. Further research is needed to explore the connectivity and sequence of how the human brain activates to sing.

  9. Multilayer modeling and analysis of human brain networks

    Science.gov (United States)

    2017-01-01

    Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916

  10. Data integration through brain atlasing: Human Brain Project tools and strategies.

    Science.gov (United States)

    Bjerke, Ingvild E; Øvsthus, Martin; Papp, Eszter A; Yates, Sharon C; Silvestri, Ludovico; Fiorilli, Julien; Pennartz, Cyriel M A; Pavone, Francesco S; Puchades, Maja A; Leergaard, Trygve B; Bjaalie, Jan G

    2018-04-01

    The Human Brain Project (HBP), an EU Flagship Initiative, is currently building an infrastructure that will allow integration of large amounts of heterogeneous neuroscience data. The ultimate goal of the project is to develop a unified multi-level understanding of the brain and its diseases, and beyond this to emulate the computational capabilities of the brain. Reference atlases of the brain are one of the key components in this infrastructure. Based on a new generation of three-dimensional (3D) reference atlases, new solutions for analyzing and integrating brain data are being developed. HBP will build services for spatial query and analysis of brain data comparable to current online services for geospatial data. The services will provide interactive access to a wide range of data types that have information about anatomical location tied to them. The 3D volumetric nature of the brain, however, introduces a new level of complexity that requires a range of tools for making use of and interacting with the atlases. With such new tools, neuroscience research groups will be able to connect their data to atlas space, share their data through online data systems, and search and find other relevant data through the same systems. This new approach partly replaces earlier attempts to organize research data based only on a set of semantic terminologies describing the brain and its subdivisions. Copyright © 2018 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

  11. Brain shape in human microcephalics and Homo floresiensis.

    Science.gov (United States)

    Falk, Dean; Hildebolt, Charles; Smith, Kirk; Morwood, M J; Sutikna, Thomas; Jatmiko; Saptomo, E Wayhu; Imhof, Herwig; Seidler, Horst; Prior, Fred

    2007-02-13

    Because the cranial capacity of LB1 (Homo floresiensis) is only 417 cm(3), some workers propose that it represents a microcephalic Homo sapiens rather than a new species. This hypothesis is difficult to assess, however, without a clear understanding of how brain shape of microcephalics compares with that of normal humans. We compare three-dimensional computed tomographic reconstructions of the internal braincases (virtual endocasts that reproduce details of external brain morphology, including cranial capacities and shape) from a sample of 9 microcephalic humans and 10 normal humans. Discriminant and canonical analyses are used to identify two variables that classify normal and microcephalic humans with 100% success. The classification functions classify the virtual endocast from LB1 with normal humans rather than microcephalics. On the other hand, our classification functions classify a pathological H. sapiens specimen that, like LB1, represents an approximately 3-foot-tall adult female and an adult Basuto microcephalic woman that is alleged to have an endocast similar to LB1's with the microcephalic humans. Although microcephaly is genetically and clinically variable, virtual endocasts from our highly heterogeneous sample share similarities in protruding and proportionately large cerebella and relatively narrow, flattened orbital surfaces compared with normal humans. These findings have relevance for hypotheses regarding the genetic substrates of hominin brain evolution and may have medical diagnostic value. Despite LB1's having brain shape features that sort it with normal humans rather than microcephalics, other shape features and its small brain size are consistent with its assignment to a separate species.

  12. Proposed link rates in the human brain.

    Science.gov (United States)

    van Putten, Michael J A M

    2003-07-15

    There is increasing experimental evidence that neuronal synchronization is necessary for the large-scale integration of distributed neuronal activity to realize various time-dependent coherent neuronal assemblies in the brain. Phase synchronization seems a promising candidate to quantify the time-dependent, frequency specific, synchrony between simultaneously recorded electroencephalogram (EEG) signals that may partially reflect this former process. We introduce a link rate (LR) as a measure of the spatial-temporal incidence of phase synchronization and phase de-synchronization. The concept is exemplified in its application to the analysis of spontaneous phase synchronization. To this end, three scalp EEG recordings are used: a normal control, a patient suffering from epileptic seizures and a patient with diffuse brain damage due to anoxia, showing a burst-suppression EEG. In addition, the method is applied to surrogate data (white noise). We find in the normal control that LR(control)=13.90+/-0.04 (mean+/-S.E.M.), which is different from the surrogate data, where we find that LR(surr)=15.36+/-0.05. In the two pathological conditions, the LR is significantly and strongly reduced to LR(burst)=4.52+/-0.05 and LR(seizure)=5.40+/-0.08. The derived LR seems a sensitive measure to relevant changes in synchronization, as these occur in the dynamic process of generating different spatial-temporal networks, both in physiological and pathological conditions.

  13. Message processing in the human brain. III

    Energy Technology Data Exchange (ETDEWEB)

    Gerke, P

    1983-10-07

    For pt.II see ibid., no.19, p.95-100 (1983). The general problem of the possibly achievable super brain is discussed, and subtle differences between various linkages leading to selective processes, creativity decision making and speculative assessments are pointed out and translated into possible approaches to the making of machine intelligence. Generally, associative sequences for processing of large data flows cannot be attempted without the provision of generally valid linkage rules. Such coordination steps are considered first, the brain-machine simulation being built-up vertically on 6 levels and horizontally as recognition stages in an event. These six levels are: repertoire (i.e. vocabulary); definition; scene; happenings; spatial linkages; temporal linkages. Event simulation proceeds from the descriptive to the cognitive situation. Speculative discussions continue with the gradual introduction of computer hardware and software concepts to be adapted for intelligence simulation; thus, the simplest associative process could start with an adder network and proceed to a virtual expert system, which would include teaching by example, autonomous control, non-procedural language, all these governed by schedules.

  14. Optimizing full-brain coverage in human brain MRI through population distributions of brain size

    NARCIS (Netherlands)

    Mennes, M.; Jenkinson, M.; Valabregue, R.; Buitelaar, J.K.; Beckmann, C.F.; Smith, S.

    2014-01-01

    When defining an MRI protocol, brain researchers need to set multiple interdependent parameters that define repetition time (TR), voxel size, field-of-view (FOV), etc. Typically, researchers aim to image the full brain, making the expected FOV an important parameter to consider. Especially in 2D-EPI

  15. Measuring dopamine release in the human brain with PET

    Energy Technology Data Exchange (ETDEWEB)

    Volkow, N.D. [Brookhaven National Lab., Upton, NY (United States)]|[State Univ. of New York at Stony Brook, Stony Brook, NY (United States). Dept. of Psychiatry; Fowler, J.S.; Logan, J.; Wang, G.J. [Brookhaven National Lab., Upton, NY (United States)

    1995-12-01

    The dopamine system is involved in the regulation of brain regions that subserve motor, cognitive and motivational behaviors. Disruptions of dopamine (DA) function have ben implicated in neurological and psychiatric illnesses including substance abuse as well as on some of the deficits associated with aging of the human brain. This has made the DA system an important topic in research in the neurosciences and neuroimaging as well as an important molecular target for drug development. Positron Emission Tomography (PET), was the first technology that enabled direct measurement of components of the DA system in the living human brain. Imaging studies of DA in the living brain have been indirect, relying on the development of radiotracers to label DA receptors, DA transporters, compounds which have specificity for the enzymes which degrade synaptic DA. Additionally, through the use of tracers that provide information on regional brain activity (ie brain glucose metabolism and cerebral blood flow) and of appropriate pharmacological interventions, it has been possible to assess the functional consequences of changes in brain DA activity. DA specific ligands have been useful in the evaluation of patients with neuropsychiatric illnesses as well as to investigate receptor blockade by antipsychotic drugs. A limitation of strategies that rely on the use of DA specific ligands is that the measures do not necessarily reflect the functional state of the dopaminergic system and that there use to study the effects of drugs is limited to the investigation of receptor or transporter occupancy. Newer strategies have been developed in an attempt to provide with information on dopamine release and on the functional responsivity of the DA system in the human brain. This in turn allows to investigate the effects of pharmacological agent in an analogous way to what is done with microdialysis techniques.

  16. Working memory and new learning following pediatric traumatic brain injury.

    Science.gov (United States)

    Mandalis, Anna; Kinsella, Glynda; Ong, Ben; Anderson, Vicki

    2007-01-01

    Working memory (WM), the ability to monitor, process and maintain task relevant information on-line to respond to immediate environmental demands, is controlled by frontal systems (D'Esposito et al., 2006), which are particularly vulnerable to damage from a traumatic brain injury (TBI). This study employed the adult-based Working Memory model of Baddeley and Hitch (1974) to examine the relationship between working memory function and new verbal learning in children with TBI. A cross-sectional sample of 36 school-aged children with a moderate to severe TBI was compared to age-matched healthy Controls on a series of tasks assessing working memory subsystems: the Phonological Loop (PL) and Central Executive (CE). The TBI group performed significantly more poorly than Controls on the PL measure and the majority of CE tasks. On new learning tasks, the TBI group consistently produced fewer words than Controls across the learning and delayed recall phases. Results revealed impaired PL function related to poor encoding and acquisition on a new verbal learning task in the TBI group. CE retrieval deficits in the TBI group contributed to general memory dysfunction in acquisition, retrieval and recognition memory. These results suggest that the nature of learning and memory deficits in children with TBI is related to working memory impairment.

  17. "Wide-Awake Learning": Integrative Learning and Humanities Education

    Science.gov (United States)

    Booth, Alan

    2011-01-01

    This article reviews the development of integrative learning and argues that it has an important role to play in broader conceptions of the undergraduate curriculum recently advanced in the UK. It suggests that such a focus might also provide arts and humanities educators with a hopeful prospect in difficult times: a means by which the distinctive…

  18. Gender development and the human brain.

    Science.gov (United States)

    Hines, Melissa

    2011-01-01

    Convincing evidence indicates that prenatal exposure to the gonadal hormone, testosterone, influences the development of children's sex-typical toy and activity interests. In addition, growing evidence shows that testosterone exposure contributes similarly to the development of other human behaviors that show sex differences, including sexual orientation, core gender identity, and some, though not all, sex-related cognitive and personality characteristics. In addition to these prenatal hormonal influences, early infancy and puberty may provide additional critical periods when hormones influence human neurobehavioral organization. Sex-linked genes could also contribute to human gender development, and most sex-related characteristics are influenced by socialization and other aspects of postnatal experience, as well. Neural mechanisms underlying the influences of gonadal hormones on human behavior are beginning to be identified. Although the neural mechanisms underlying experiential influences remain largely uninvestigated, they could involve the same neural circuitry as that affected by hormones.

  19. Thrombin binding to human brain and spinal cord

    International Nuclear Information System (INIS)

    McKinney, M.; Snider, R.M.; Richelson, E.

    1983-01-01

    Thrombin, a serine protease that regulates hemostasis, has been shown to stimulate the formation of cGMP in murine neuroblastoma cells. The nervous system in vivo thus may be postulated to respond to this blood-borne factor after it breaches the blood-brain barrier, as in trauma. Human alpha-thrombin was radiolabeled with 125I and shown to bind rapidly, reversibly, and with high affinity to human brain and spinal cord. These findings indicate the presence of specific thrombin-binding sites in nervous tissue and may have important clinical implications

  20. Simplified detection system for neuroreceptor studies in the human brain

    International Nuclear Information System (INIS)

    Bice, A.N.; Wagner, H.N. Jr.; Frost, J.J.

    1986-01-01

    A simple, inexpensive dual-detector system has been developed for measurement of positronemitting receptor-binding drugs in the human brain. This high efficiency coincidence counting system requires that only a few hundred microcuries of labeled drug be administered to the subject, thereby allowing for multiple studies without an excessive radiation dose. Measurement of the binding of [11C]carfentanil, a high affinity synthetic opiate, to opiate receptors in the presence and in the absence of a competitive opiate antagonist indicates the potential utility of this system for estimating different degrees of receptor occupation in the human brain

  1. Mu opioid receptor binding sites in human brain

    International Nuclear Information System (INIS)

    Pilapil, C.; Welner, S.; Magnan, J.; Zamir, N.; Quirion, R.

    1986-01-01

    Our experiments focused on the examination of the distribution of mu opioid receptor binding sites in normal human brain using the highly selective ligand [ 3 H]DAGO, in both membrane binding assay and in vitro receptor autoradiography. Mu opioid binding sites are very discretely distributed in human brain with high densities of sites found in the posterior amygdala, caudate, putamen, hypothalamus and certain cortical areas. Moreover the autoradiographic distribution of [ 3 H]DAGO binding sites clearly reveals the discrete lamination (layers I and III-IV) of mu sites in cortical areas

  2. Glucose transporter of the human brain and blood-brain barrier

    International Nuclear Information System (INIS)

    Kalaria, R.N.; Gravina, S.A.; Schmidley, J.W.; Perry, G.; Harik, S.I.

    1988-01-01

    We identified and characterized the glucose transporter in the human cerebral cortex, cerebral microvessels, and choroid plexus by specific D-glucose-displaceable [3H]cytochalasin B binding. The binding was saturable, with a dissociation constant less than 1 microM. Maximal binding capacity was approximately 7 pmol/mg protein in the cerebral cortex, approximately 42 pmol/mg protein in brain microvessels, and approximately 27 pmol/mg protein in the choroid plexus. Several hexoses displaced specific [3H]cytochalasin B binding to microvessels in a rank-order that correlated well with their known ability to cross the blood-brain barrier; the only exception was 2-deoxy-D-glucose, which had much higher affinity for the glucose transporter than the natural substrate, D-glucose. Irreversible photoaffinity labeling of the glucose transporter of microvessels with [3H]cytochalasin B, followed by solubilization and polyacrylamide gel electrophoresis, labeled a protein band with an average molecular weight of approximately 55,000. Monoclonal and polyclonal antibodies specific to the human erythrocyte glucose transporter immunocytochemically stained brain blood vessels and the few trapped erythrocytes in situ, with minimal staining of the neuropil. In the choroid plexus, blood vessels did not stain, but the epithelium reacted positively. We conclude that human brain microvessels are richly endowed with a glucose transport moiety similar in molecular weight and antigenic characteristics to that of human erythrocytes and brain microvessels of other mammalian species

  3. Magnetic resonance elastography in normal human brain: preliminary study

    International Nuclear Information System (INIS)

    Xu Lei; Gao Peiyi; Lin Yan; Han Jiancheng; Xi Zhinong; Shen Hao

    2007-01-01

    Objective: To study the application of magnetic resonance elastography (MRE) in the human brain. Methods: An external force actuator was developed. The actuator was fixed to the head coil. During MRE scan, one side of the actuator was attached to the volunteers' head. Low frequency oscillation was produced by the actuator and generated shear waves propagating into brain tissue. The pulse sequence of MRE was designed. A modified gradient echo sequence was developed with motion sensitizing gradient (MSG) imposed along X, Y or Z direction. Cyclic displacement within brain tissue induced by shear waves caused a measurable phase shift in the received MR signal. From the measured phase shift, the displacement at each voxel could be calculated, and the shear waves within the brain were directly imaged. By adjusting the phase offset, the dynamic propagation of shear waves in a wave cycle was obtained. Phase images were processed with local frequency estimation (LFE) technique to obtain the elasticity images. Shear waves at 100 Hz, 150 Hz, and 200 Hz were applied. Results: The phase images of MRE directly imaged the propagating shear waves within the brain. The direction of the propagation was from surface of the brain to the center. The wavelength of shear waves varied with the change of actuating frequency. The change of wavelength of shear waves in gray and white matter of the brain was identified. The wavelength of shear waves in gray matter was shorter than that in white matter. The elasticity image of the brain revealed that the shear modulus of the white matter was higher than that of gray matter. Conclusion: The phase images of MRE can directly visualize the propagation of shear waves in the brain tissue. The elasticity image of the brain can demonstrate the change of elasticity between gray and white matter. (authors)

  4. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

    Science.gov (United States)

    Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

    2017-08-01

    Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.

  5. Measuring and Reconstructing the Brain at the Synaptic Scale: Towards a Biofidelic Human Brain in silico

    OpenAIRE

    NeuroData; CE, Priebe; Burns, R.; RJ, Vogelstein

    2015-01-01

    Vogelstein JT, Priebe CE, Burns R, Vogelstein RJ, Lichtman J. Measuring and Reconstructing the Brain at the Synaptic Scale: Towards a Biofidelic Human Brain in silico. DARPA Neural Engineering, Science and Technology Forum, 2010

  6. Neurospin Seminar: From the Proton to the Human Brain

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    From the Proton to the Human Brain Speaker: Prof Denis Le Bihan Abstract: The understanding of the human brain is one of the main scientific challenges of the 21st century. In the early 2000s the French Atomic Energy Commission (CEA) launched a program to conceive and build a “human brain explorer”, the first human MRI scanner operating at 11.7T. This scanner was envisioned to be part of the ambitious Iseult project, bridging together industrial and academic partners to push the limits of molecular neuroimaging, from mouse to man, using Ultra-High Field (UHF) MRI. In this seminar a summary of the main features of this magnet, and the neuroscience and medical targets of NeuroSpin where this outstanding instrument will be installed in 2017 will be surveyed. The unprecedented resolution and the new contrasts allowed by such UHF magnets, in combination with innovative concepts in physics and neurobiology, will allow to explore the human brain at a mesoscale at which everything remains to d...

  7. Brain white matter structure and COMT gene are linked to second-language learning in adults.

    Science.gov (United States)

    Mamiya, Ping C; Richards, Todd L; Coe, Bradley P; Eichler, Evan E; Kuhl, Patricia K

    2016-06-28

    Adult human brains retain the capacity to undergo tissue reorganization during second-language learning. Brain-imaging studies show a relationship between neuroanatomical properties and learning for adults exposed to a second language. However, the role of genetic factors in this relationship has not been investigated. The goal of the current study was twofold: (i) to characterize the relationship between brain white matter fiber-tract properties and second-language immersion using diffusion tensor imaging, and (ii) to determine whether polymorphisms in the catechol-O-methyltransferase (COMT) gene affect the relationship. We recruited incoming Chinese students enrolled in the University of Washington and scanned their brains one time. We measured the diffusion properties of the white matter fiber tracts and correlated them with the number of days each student had been in the immersion program at the time of the brain scan. We found that higher numbers of days in the English immersion program correlated with higher fractional anisotropy and lower radial diffusivity in the right superior longitudinal fasciculus. We show that fractional anisotropy declined once the subjects finished the immersion program. The relationship between brain white matter fiber-tract properties and immersion varied in subjects with different COMT genotypes. Subjects with the Methionine (Met)/Valine (Val) and Val/Val genotypes showed higher fractional anisotropy and lower radial diffusivity during immersion, which reversed immediately after immersion ended, whereas those with the Met/Met genotype did not show these relationships. Statistical modeling revealed that subjects' grades in the language immersion program were best predicted by fractional anisotropy and COMT genotype.

  8. Human brain functional MRI and DTI visualization with virtual reality.

    Science.gov (United States)

    Chen, Bin; Moreland, John; Zhang, Jingyu

    2011-12-01

    Magnetic resonance diffusion tensor imaging (DTI) and functional MRI (fMRI) are two active research areas in neuroimaging. DTI is sensitive to the anisotropic diffusion of water exerted by its macromolecular environment and has been shown useful in characterizing structures of ordered tissues such as the brain white matter, myocardium, and cartilage. The diffusion tensor provides two new types of information of water diffusion: the magnitude and the spatial orientation of water diffusivity inside the tissue. This information has been used for white matter fiber tracking to review physical neuronal pathways inside the brain. Functional MRI measures brain activations using the hemodynamic response. The statistically derived activation map corresponds to human brain functional activities caused by neuronal activities. The combination of these two methods provides a new way to understand human brain from the anatomical neuronal fiber connectivity to functional activities between different brain regions. In this study, virtual reality (VR) based MR DTI and fMRI visualization with high resolution anatomical image segmentation and registration, ROI definition and neuronal white matter fiber tractography visualization and fMRI activation map integration is proposed. Rationale and methods for producing and distributing stereoscopic videos are also discussed.

  9. Mathematical logic in the human brain: syntax.

    Directory of Open Access Journals (Sweden)

    Roland Friedrich

    Full Text Available Theory predicts a close structural relation of formal languages with natural languages. Both share the aspect of an underlying grammar which either generates (hierarchically structured expressions or allows us to decide whether a sentence is syntactically correct or not. The advantage of rule-based communication is commonly believed to be its efficiency and effectiveness. A particularly important class of formal languages are those underlying the mathematical syntax. Here we provide brain-imaging evidence that the syntactic processing of abstract mathematical formulae, written in a first order language, is, indeed efficient and effective as a rule-based generation and decision process. However, it is remarkable, that the neural network involved, consisting of intraparietal and prefrontal regions, only involves Broca's area in a surprisingly selective way. This seems to imply that despite structural analogies of common and current formal languages, at the neural level, mathematics and natural language are processed differently, in principal.

  10. Addiction circuitry in the human brain (*).

    Energy Technology Data Exchange (ETDEWEB)

    Volkow, N.D.; Wang, G.; Volkow, N.D.; Wang, G.-J.; Fowler, J.S.; Tomasi, D.

    2011-09-27

    A major challenge in understanding substance-use disorders lies in uncovering why some individuals become addicted when exposed to drugs, whereas others do not. Although genetic, developmental, and environmental factors are recognized as major contributors to a person's risk of becoming addicted, the neurobiological processes that underlie this vulnerability are still poorly understood. Imaging studies suggest that individual variations in key dopamine-modulated brain circuits, including circuits involved in reward, memory, executive function, and motivation, contribute to some of the differences in addiction vulnerability. A better understanding of the main circuits affected by chronic drug use and the influence of social stressors, developmental trajectories, and genetic background on these circuits is bound to lead to a better understanding of addiction and to more effective strategies for the prevention and treatment of substance-use disorders.

  11. The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas.

    Science.gov (United States)

    Ecker, Joseph R; Geschwind, Daniel H; Kriegstein, Arnold R; Ngai, John; Osten, Pavel; Polioudakis, Damon; Regev, Aviv; Sestan, Nenad; Wickersham, Ian R; Zeng, Hongkui

    2017-11-01

    A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Artificial agents learning human fairness

    NARCIS (Netherlands)

    Jong, de S.; Tuyls, K.P.; Verbeeck, K.; Padgham, xx; Parkes, xx

    2008-01-01

    Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually rational agents, according to the principles of classical game theory. However, research in the field of behavioral

  13. Quantifying anisotropy and fiber orientation in human brain histological sections

    Directory of Open Access Journals (Sweden)

    Matthew D Budde

    2013-02-01

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

  14. Kisspeptin modulates sexual and emotional brain processing in humans.

    Science.gov (United States)

    Comninos, Alexander N; Wall, Matthew B; Demetriou, Lysia; Shah, Amar J; Clarke, Sophie A; Narayanaswamy, Shakunthala; Nesbitt, Alexander; Izzi-Engbeaya, Chioma; Prague, Julia K; Abbara, Ali; Ratnasabapathy, Risheka; Salem, Victoria; Nijher, Gurjinder M; Jayasena, Channa N; Tanner, Mark; Bassett, Paul; Mehta, Amrish; Rabiner, Eugenii A; Hönigsperger, Christoph; Silva, Meire Ribeiro; Brandtzaeg, Ole Kristian; Lundanes, Elsa; Wilson, Steven Ray; Brown, Rachel C; Thomas, Sarah A; Bloom, Stephen R; Dhillo, Waljit S

    2017-02-01

    Sex, emotion, and reproduction are fundamental and tightly entwined aspects of human behavior. At a population level in humans, both the desire for sexual stimulation and the desire to bond with a partner are important precursors to reproduction. However, the relationships between these processes are incompletely understood. The limbic brain system has key roles in sexual and emotional behaviors, and is a likely candidate system for the integration of behavior with the hormonal reproductive axis. We investigated the effects of kisspeptin, a recently identified key reproductive hormone, on limbic brain activity and behavior. Using a combination of functional neuroimaging and hormonal and psychometric analyses, we compared the effects of kisspeptin versus vehicle administration in 29 healthy heterosexual young men. We demonstrated that kisspeptin administration enhanced limbic brain activity specifically in response to sexual and couple-bonding stimuli. Furthermore, kisspeptin's enhancement of limbic brain structures correlated with psychometric measures of reward, drive, mood, and sexual aversion, providing functional significance. In addition, kisspeptin administration attenuated negative mood. Collectively, our data provide evidence of an undescribed role for kisspeptin in integrating sexual and emotional brain processing with reproduction in humans. These results have important implications for our understanding of reproductive biology and are highly relevant to the current pharmacological development of kisspeptin as a potential therapeutic agent for patients with common disorders of reproductive function. National Institute for Health Research (NIHR), Wellcome Trust (Ref 080268), and the Medical Research Council (MRC).

  15. Main-, minor- and trace elements distribution in human brain

    International Nuclear Information System (INIS)

    Zoeger, N.; Streli, C.; Wobrauschek, P.; Jokubonis, C.; Pepponi, G.; Roschger, P.; Bohic, S.; Osterode, W.

    2004-01-01

    Lead (Pb) is known to induce adverse health effects in humans. In fact, cognitive deficits are repeatedly described with Pb exposure, but little is known about the distribution of lead in brain. Measurements of the distribution of Pb in human brain and to study if Pb is associated with the distribution of other chemical elements such as zinc (Zn), iron (Fe) is of great interest and could reveal some hints about the metabolism of Pb in brain. To determine the local distribution of lead (Pb) and other trace elements x-ray fluorescence spectroscopy (XRF) measurements have been performed, using a microbeam setup and highest flux synchrotron radiation. Experiments have been carried out at ID-22, ESRF, Grenoble, France. The installed microprobe setup provides a monochromatic beam (17 keV) from an undulator station focused by Kirkpatrick-Baez x-ray optics to a spot size of 5 μm x 3μm. Brain slices (20 μm thickness, imbedded in paraffin and mounted on Kapton foils) from areas of the frontal cortex, thalamus and hippocampus have been investigated. Generally no significant increase in fluorescence intensities could be detected in one of the investigated brain compartments. However Pb and other (trace) elements (e.g. S, Ca, Fe, Cu, Zn, Br) could be detected in all samples and showed strong inhomogeneities across the analyzed areas. While S, Ca, Fe, Cu, Zn and Br could be clearly assigned to the investigated brain structures (vessels, etc.) Pb showed a very different behavior. In some cases (e.g. plexus choroidei) Pb was located at the walls of the vessel, whereas with other structures (e.g. blood vessel) this correlation was not found. Moreover, the detected Pb in different brain areas was individually correlated with various elements. The local distribution of the detected elements in various brain structures will be discussed in this work. (author)

  16. Uncovering intrinsic modular organization of spontaneous brain activity in humans.

    Directory of Open Access Journals (Sweden)

    Yong He

    Full Text Available The characterization of topological architecture of complex brain networks is one of the most challenging issues in neuroscience. Slow (<0.1 Hz, spontaneous fluctuations of the blood oxygen level dependent (BOLD signal in functional magnetic resonance imaging are thought to be potentially important for the reflection of spontaneous neuronal activity. Many studies have shown that these fluctuations are highly coherent within anatomically or functionally linked areas of the brain. However, the underlying topological mechanisms responsible for these coherent intrinsic or spontaneous fluctuations are still poorly understood. Here, we apply modern network analysis techniques to investigate how spontaneous neuronal activities in the human brain derived from the resting-state BOLD signals are topologically organized at both the temporal and spatial scales. We first show that the spontaneous brain functional networks have an intrinsically cohesive modular structure in which the connections between regions are much denser within modules than between them. These identified modules are found to be closely associated with several well known functionally interconnected subsystems such as the somatosensory/motor, auditory, attention, visual, subcortical, and the "default" system. Specifically, we demonstrate that the module-specific topological features can not be captured by means of computing the corresponding global network parameters, suggesting a unique organization within each module. Finally, we identify several pivotal network connectors and paths (predominantly associated with the association and limbic/paralimbic cortex regions that are vital for the global coordination of information flow over the whole network, and we find that their lesions (deletions critically affect the stability and robustness of the brain functional system. Together, our results demonstrate the highly organized modular architecture and associated topological properties in

  17. Learned helplessness is independent of levels of brain-derived neurotrophic factor in the hippocampus.

    Science.gov (United States)

    Greenwood, B N; Strong, P V; Foley, T E; Thompson, R S; Fleshner, M

    2007-02-23

    Reduced levels of brain-derived neurotrophic factor (BDNF) in the hippocampus have been implicated in human affective disorders and behavioral stress responses. The current studies examined the role of BDNF in the behavioral consequences of inescapable stress, or learned helplessness. Inescapable stress decreased BDNF mRNA and protein in the hippocampus of sedentary rats. Rats allowed voluntary access to running wheels for either 3 or 6 weeks prior to exposure to stress were protected against stress-induced reductions of hippocampal BDNF protein. The observed prevention of stress-induced deceases in BDNF, however, occurred in a time course inconsistent with the prevention of learned helplessness by wheel running, which is evident following 6 weeks, but not 3 weeks, of wheel running. BDNF suppression in physically active rats was produced by administering a single injection of the selective serotonin reuptake inhibitor fluoxetine (10 mg/kg) just prior to stress. Despite reduced levels of hippocampal BDNF mRNA following stress, physically active rats given the combination of fluoxetine and stress remained resistant against learned helplessness. Sedentary rats given both fluoxetine and stress still demonstrated typical learned helplessness behaviors. Fluoxetine by itself reduced BDNF mRNA in sedentary rats only, but did not affect freezing or escape learning 24 h later. Finally, bilateral injections of BDNF (1 mug) into the dentate gyrus prior to stress prevented stress-induced reductions of hippocampal BDNF but did not prevent learned helplessness in sedentary rats. These data indicate that learned helplessness behaviors are independent of the presence or absence of hippocampal BDNF because blocking inescapable stress-induced BDNF suppression does not always prevent learned helplessness, and learned helplessness does not always occur in the presence of reduced BDNF. Results also suggest that the prevention of stress-induced hippocampal BDNF suppression is not

  18. Consumption of seaweeds and the human brain

    DEFF Research Database (Denmark)

    Cornish, M. Lynn; Critchley, Alan T.; Mouritsen, Ole G.

    2017-01-01

    , and the impacts of anti-oxidant activities in neuroprotection. These elements have the capacity to help in the defense of human cognitive disorders, such as dementia, Alzheimer’s disease, depression, bipolar diseases, and adverse conditions characterized by progressive neurodegeneration. Psychological benefits...

  19. Visual dictionaries as intermediate features in the human brain

    Directory of Open Access Journals (Sweden)

    Kandan eRamakrishnan

    2015-01-01

    Full Text Available The human visual system is assumed to transform low level visual features to object and scene representations via features of intermediate complexity. How the brain computationally represents intermediate features is still unclear. To further elucidate this, we compared the biologically plausible HMAX model and Bag of Words (BoW model from computer vision. Both these computational models use visual dictionaries, candidate features of intermediate complexity, to represent visual scenes, and the models have been proven effective in automatic object and scene recognition. These models however differ in the computation of visual dictionaries and pooling techniques. We investigated where in the brain and to what extent human fMRI responses to short video can be accounted for by multiple hierarchical levels of the HMAX and BoW models. Brain activity of 20 subjects obtained while viewing a short video clip was analyzed voxel-wise using a distance-based variation partitioning method. Results revealed that both HMAX and BoW explain a significant amount of brain activity in early visual regions V1, V2 and V3. However BoW exhibits more consistency across subjects in accounting for brain activity compared to HMAX. Furthermore, visual dictionary representations by HMAX and BoW explain significantly some brain activity in higher areas which are believed to process intermediate features. Overall our results indicate that, although both HMAX and BoW account for activity in the human visual system, the BoW seems to more faithfully represent neural responses in low and intermediate level visual areas of the brain.

  20. Human Brain inspired Artificial Intelligence & Developmental Robotics: A Review

    Directory of Open Access Journals (Sweden)

    Suresh Kumar

    2017-06-01

    Full Text Available Along with the developments in the field of the robotics, fascinating contributions and developments can be seen in the field of Artificial intelligence (AI. In this paper we will discuss about the developments is the field of artificial intelligence focusing learning algorithms inspired from the field of Biology, particularly large scale brain simulations, and developmental Psychology. We will focus on the emergence of the Developmental robotics and its significance in the field of AI.

  1. Simple instrument for biochemical studies of the living human brain

    International Nuclear Information System (INIS)

    Bice, A.N.; Wagner, H.N. Jr.; Lee, M.C.; Frost, J.J.

    1986-01-01

    A simple, relatively inexpensive radiation detection system was developed for measurement of positron-emitting receptor-binding drugs in the human brain. This high-efficiency coincidence counting system requires that only a few hundred microcuries of labeled drug be administered to the subject, thereby allowing for multiple studies without an excessive radiation dose. Measurement of the binding of [ 11 C]-carfentanil, a high-affinity synthetic opiate, to opiate receptors in the presence and in the absence of a competitive opiate antagonist exemplifies the use of this system for estimating different degrees of receptor binding of drugs in the human brain. The instrument has also been used for measurement of the transport into the brain of other positron-emitting radiotracers, such as large neutral amino acids

  2. Kinetic modeling of 11C-SB207145 binding to 5-HT4 receptors in the human brain in vivo

    DEFF Research Database (Denmark)

    Marner, Lisbeth; Gillings, Nic; Comley, Robert A

    2009-01-01

    The serotonin 4 receptor (5-HT(4) receptor) is known to be involved in learning and memory. We evaluated for the first time the quantification of a novel 5-HT(4) receptor radioligand, (11)C-SB207145, for in vivo brain imaging with PET in humans. METHODS: For evaluation of reproducibility, 6...

  3. Exercise, learned helplessness, and the stress-resistant brain.

    Science.gov (United States)

    Greenwood, Benjamin N; Fleshner, Monika

    2008-01-01

    Exercise can prevent the development of stress-related mood disorders, such as depression and anxiety. The underlying neurobiological mechanisms of this effect, however, remain unknown. Recently, researchers have used animal models to begin to elucidate the potential mechanisms underlying the protective effects of physical activity. Using the behavioral consequences of uncontrollable stress or "learned helplessness" as an animal analog of depression- and anxiety-like behaviors in rats, we are investigating factors that could be important for the antidepressant and anxiolytic properties of exercise (i.e., wheel running). The current review focuses on the following: (1) the effect of exercise on the behavioral consequences of uncontrollable stress and the implications of these effects on the specificity of the "learned helplessness" animal model; (2) the neurocircuitry of learned helplessness and the role of serotonin; and (3) exercise-associated neural adaptations and neural plasticity that may contribute to the stress-resistant brain. Identifying the mechanisms by which exercise prevents learned helplessness could shed light on the complex neurobiology of depression and anxiety and potentially lead to novel strategies for the prevention of stress-related mood disorders.

  4. Hemispheric dissociation of reward processing in humans: insights from deep brain stimulation.

    Science.gov (United States)

    Palminteri, Stefano; Serra, Giulia; Buot, Anne; Schmidt, Liane; Welter, Marie-Laure; Pessiglione, Mathias

    2013-01-01

    Rewards have various effects on human behavior and multiple representations in the human brain. Behaviorally, rewards notably enhance response vigor in incentive motivation paradigms and bias subsequent choices in instrumental learning paradigms. Neurally, rewards affect activity in different fronto-striatal regions attached to different motor effectors, for instance in left and right hemispheres for the two hands. Here we address the question of whether manipulating reward-related brain activity has local or general effects, with respect to behavioral paradigms and motor effectors. Neuronal activity was manipulated in a single hemisphere using unilateral deep brain stimulation (DBS) in patients with Parkinson's disease. Results suggest that DBS amplifies the representation of reward magnitude within the targeted hemisphere, so as to affect the behavior of the contralateral hand specifically. These unilateral DBS effects on behavior include both boosting incentive motivation and biasing instrumental choices. Furthermore, using computational modeling we show that DBS effects on incentive motivation can predict DBS effects on instrumental learning (or vice versa). Thus, we demonstrate the feasibility of causally manipulating reward-related neuronal activity in humans, in a manner that is specific to a class of motor effectors but that generalizes to different computational processes. As these findings proved independent from therapeutic effects on parkinsonian motor symptoms, they might provide insight into DBS impact on non-motor disorders, such as apathy or hypomania. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Cholinergic Modulation of Cortical Microcircuits Is Layer-Specific: Evidence from Rodent, Monkey and Human Brain

    Directory of Open Access Journals (Sweden)

    Joshua Obermayer

    2017-12-01

    Full Text Available Acetylcholine (ACh signaling shapes neuronal circuit development and underlies specific aspects of cognitive functions and behaviors, including attention, learning, memory and motivation. During behavior, activation of muscarinic and nicotinic acetylcholine receptors (mAChRs and nAChRs by ACh alters the activation state of neurons, and neuronal circuits most likely process information differently with elevated levels of ACh. In several brain regions, ACh has been shown to alter synaptic strength as well. By changing the rules for synaptic plasticity, ACh can have prolonged effects on and rearrange connectivity between neurons that outlasts its presence. From recent discoveries in the mouse, rat, monkey and human brain, a picture emerges in which the basal forebrain (BF cholinergic system targets the neocortex with much more spatial and temporal detail than previously considered. Fast cholinergic synapses acting on a millisecond time scale are abundant in the mammalian cerebral cortex, and provide BF cholinergic neurons with the possibility to rapidly alter information flow in cortical microcircuits. Finally, recent studies have outlined novel mechanisms of how cholinergic projections from the BF affect synaptic strength in several brain areas of the rodent brain, with behavioral consequences. This review highlights these exciting developments and discusses how these findings translate to human brain circuitries.

  6. Effects of Diet on Brain Plasticity in Animal and Human Studies: Mind the Gap

    Directory of Open Access Journals (Sweden)

    Tytus Murphy

    2014-01-01

    Full Text Available Dietary interventions have emerged as effective environmental inducers of brain plasticity. Among these dietary interventions, we here highlight the impact of caloric restriction (CR: a consistent reduction of total daily food intake, intermittent fasting (IF, every-other-day feeding, and diet supplementation with polyphenols and polyunsaturated fatty acids (PUFAs on markers of brain plasticity in animal studies. Moreover, we also discuss epidemiological and intervention studies reporting the effects of CR, IF and dietary polyphenols and PUFAs on learning, memory, and mood. In particular, we evaluate the gap in mechanistic understanding between recent findings from animal studies and those human studies reporting that these dietary factors can benefit cognition, mood, and anxiety, aging, and Alzheimer’s disease—with focus on the enhancement of structural and functional plasticity markers in the hippocampus, such as increased expression of neurotrophic factors, synaptic function and adult neurogenesis. Lastly, we discuss some of the obstacles to harnessing the promising effects of diet on brain plasticity in animal studies into effective recommendations and interventions to promote healthy brain function in humans. Together, these data reinforce the important translational concept that diet, a modifiable lifestyle factor, holds the ability to modulate brain health and function.

  7. Sequential causal learning in humans and rats

    NARCIS (Netherlands)

    Lu, H.; Rojas, R.R.; Beckers, T.; Yuille, A.; Love, B.C.; McRae, K.; Sloutsky, V.M.

    2008-01-01

    Recent experiments (Beckers, De Houwer, Pineño, & Miller, 2005;Beckers, Miller, De Houwer, & Urushihara, 2006) have shown that pretraining with unrelated cues can dramatically influence the performance of humans in a causal learning paradigm and rats in a standard Pavlovian conditioning paradigm.

  8. Modeling human learning involved in car driving

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1994-01-01

    In this paper, car driving is considered at the level of human tracking and maneuvering in the context of other traffic. A model analysis revealed the most salient features determining driving performance and safety. Learning car driving is modelled based on a system theoretical approach and based

  9. Sodium MR imaging of human brain neoplasms

    International Nuclear Information System (INIS)

    Kobayashi, Shu; Yoshikawa, Kohki; Takakura, Kintomo; Iio, Masahiro

    1988-01-01

    We reported the experience of the sodium magnetic resonance imaging of 5 patients with brain tumors (4 astrocytomas and 1 craniopharyngioma), using a Siemens 1.5 Tesla superconductive magnet. We used two-dimensional Fourier imaging with a spin-echo scanning sequence (and with the repetition time of 140 msec and the echo time of 11 - 14 msec). The radiofrequency was maintained at 17 MHz. Sodium MR imaging was achieved with a 64 x 64 data acquisition (30 mm slice thickness) in 19.1 min. On the sodium MRI, all four astrocytomas, along with the eye balls and the cerebrospinal fluid spaces, appeared as high-intensity areas. Peritumoral edema is also visualized as highly intense, so that it is difficult to discriminate tumor extent from the surrounding edema. Our comparative studies with malignant glioma cases using the same equipment are needed to clarify the relationship between sodium signal intensities and the malignancy of gliomas, and to evaluate the potential clinical utility of sodium MRI. A craniopharyngioma than contained a yellowish cystic fluid with a sodium concentration as high as CSF was shown on sodium MRI as a mass with highly intense signals. The ability to differentiate extracellular from intracellular sodium, that has been studied by several investigators, would greatly augment the clinical specificity of MR imaging. (author)

  10. Patient specific 3D visualisation of human brain | Baichoo ...

    African Journals Online (AJOL)

    University of Mauritius Research Journal. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 15, No 1 (2009) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Patient specific 3D visualisation of human brain.

  11. Development of BOLD signal hemodynamic responses in the human brain

    NARCIS (Netherlands)

    Arichi, T.; Varela, M.; Melendez-Calderon, A.; Allievi, A.; Merchant, N.; Tusor, N.; Counsell, S.J.; Burdet, E.; Beckmann, Christian; Edwards, A.D.

    2012-01-01

    In the rodent brain the hemodynamic response to a brief external stimulus changes significantly during development. Analogous changes in human infants would complicate the determination and use of the hemodynamic response function (HRF) for functional magnetic resonance imaging (fMRI) in developing

  12. Human brain evolution, theories of innovation, and lessons from the ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Biosciences; Volume 29; Issue 3. Human brain evolution, theories of innovation, and lessons from the history of technology. Alfred Gierer. Perspectives Volume 29 Issue 3 September 2004 pp 235-244. Fulltext. Click here to view fulltext PDF. Permanent link:

  13. Effect of Simulated Microgravity on Human Brain Gray Matter and White Matter--Evidence from MRI.

    Directory of Open Access Journals (Sweden)

    Ke Li

    Full Text Available There is limited and inconclusive evidence that space environment, especially microgravity condition, may affect microstructure of human brain. This experiment hypothesized that there would be modifications in gray matter (GM and white matter (WM of the brain due to microgravity.Eighteen male volunteers were recruited and fourteen volunteers underwent -6° head-down bed rest (HDBR for 30 days simulated microgravity. High-resolution brain anatomical imaging data and diffusion tensor imaging images were collected on a 3T MR system before and after HDBR. We applied voxel-based morphometry and tract-based spatial statistics analysis to investigate the structural changes in GM and WM of brain.We observed significant decreases of GM volume in the bilateral frontal lobes, temporal poles, parahippocampal gyrus, insula and right hippocampus, and increases of GM volume in the vermis, bilateral paracentral lobule, right precuneus gyrus, left precentral gyrus and left postcentral gyrus after HDBR. Fractional anisotropy (FA changes were also observed in multiple WM tracts.These regions showing GM changes are closely associated with the functional domains of performance, locomotion, learning, memory and coordination. Regional WM alterations may be related to brain function decline and adaption. Our findings provide the neuroanatomical evidence of brain dysfunction or plasticity in microgravity condition and a deeper insight into the cerebral mechanisms in microgravity condition.

  14. [Stem Cells in the Brain of Mammals and Human: Fundamental and Applied Aspects].

    Science.gov (United States)

    Aleksandrova, M A; Marey, M V

    2015-01-01

    Brain stem cells represent an extremely intriguing phenomenon. The aim of our review is to present an integrity vision of their role in the brain of mammals and humans, and their clinical perspectives. Over last two decades, investigations of biology of the neural stem cells produced significant changes in general knowledge about the processes of development and functioning of the brain. Researches on the cellular and molecular mechanisms of NSC differentiation and behavior led to new understanding of their involvement in learning and memory. In the regenerative medicine, original therapeutic approaches to neurodegenerative brain diseases have been elaborated due to fundamental achievements in this field. They are based on specific regenerative potential of neural stem cells and progenitor cells, which possess the ability to replace dead cells and express crucially significant biologically active factors that are missing in the pathological brain. For the needs of cell substitution therapy in the neural diseases, adequate methods of maintaining stem cells in culture and their differentiation into different types of neurons and glial cells, have been developed currently. The success of modern cellular technologies has significantly expanded the range of cells used for cell therapy. The near future may bring new perspective and distinct progress in brain cell therapy due to optimizing the cells types most promising for medical needs.

  15. Intellectual enrichment lessens the effect of brain atrophy on learning and memory in multiple sclerosis.

    Science.gov (United States)

    Sumowski, James F; Wylie, Glenn R; Chiaravalloti, Nancy; DeLuca, John

    2010-06-15

    Learning and memory impairments are prevalent among persons with multiple sclerosis (MS); however, such deficits are only weakly associated with MS disease severity (brain atrophy). The cognitive reserve hypothesis states that greater lifetime intellectual enrichment lessens the negative impact of brain disease on cognition, thereby helping to explain the incomplete relationship between brain disease and cognitive status in neurologic populations. The literature on cognitive reserve has focused mainly on Alzheimer disease. The current research examines whether greater intellectual enrichment lessens the negative effect of brain atrophy on learning and memory in patients with MS. Forty-four persons with MS completed neuropsychological measures of verbal learning and memory, and a vocabulary-based estimate of lifetime intellectual enrichment. Brain atrophy was estimated with third ventricle width measured from 3-T magnetization-prepared rapid gradient echo MRIs. Hierarchical regression was used to predict learning and memory with brain atrophy, intellectual enrichment, and the interaction between brain atrophy and intellectual enrichment. Brain atrophy predicted worse learning and memory, and intellectual enrichment predicted better learning; however, these effects were moderated by interactions between brain atrophy and intellectual enrichment. Specifically, higher intellectual enrichment lessened the negative impact of brain atrophy on both learning and memory. These findings help to explain the incomplete relationship between multiple sclerosis disease severity and cognition, as the effect of disease on cognition is attenuated among patients with higher intellectual enrichment. As such, intellectual enrichment is supported as a protective factor against disease-related cognitive impairment in persons with multiple sclerosis.

  16. Human astrocytes: structure and functions in the healthy brain.

    Science.gov (United States)

    Vasile, Flora; Dossi, Elena; Rouach, Nathalie

    2017-07-01

    Data collected on astrocytes' physiology in the rodent have placed them as key regulators of synaptic, neuronal, network, and cognitive functions. While these findings proved highly valuable for our awareness and appreciation of non-neuronal cell significance in brain physiology, early structural and phylogenic investigations of human astrocytes hinted at potentially different astrocytic properties. This idea sparked interest to replicate rodent-based studies on human samples, which have revealed an analogous but enhanced involvement of astrocytes in neuronal function of the human brain. Such evidence pointed to a central role of human astrocytes in sustaining more complex information processing. Here, we review the current state of our knowledge of human astrocytes regarding their structure, gene profile, and functions, highlighting the differences with rodent astrocytes. This recent insight is essential for assessment of the relevance of findings using animal models and for comprehending the functional significance of species-specific properties of astrocytes. Moreover, since dysfunctional astrocytes have been described in many brain disorders, a more thorough understanding of human-specific astrocytic properties is crucial for better-adapted translational applications.

  17. Social learning in humans and other animals.

    Directory of Open Access Journals (Sweden)

    Jean-François eGariépy

    2014-03-01

    Full Text Available Decisions made by individuals can be influenced by what others think and do. Social learning includes a wide array of behaviors such as imitation, observational learning of novel foraging techniques, peer or parental influences on individual preferences, as well as outright teaching. These processes are believed to underlie an important part of cultural variation among human populations and may also explain intraspecific variation in behavior between geographically distinct populations of animals. Recent neurobiological studies have begun to uncover the neural basis of social learning. Here we review experimental evidence from the past few decades showing that social learning is a widespread set of skills present in multiple animal species. In mammals, the temporoparietal junction, the dorsomedial and dorsolateral prefrontal cortex, as well as the anterior cingulate gyrus, appear to play critical roles in social learning. Birds, fish and insects also learn from others, but the underlying neural mechanisms remain poorly understood. We discuss the evolutionary implications of these findings and highlight the importance of emerging animal models that permit precise modification of neural circuit function for elucidating the neural basis of social learning.

  18. Visualization of specific binding sites of benzodiazepine in human brain

    International Nuclear Information System (INIS)

    Shinotoh, H.; Yamasaki, T.; Inoue, O.; Itoh, T.; Suzuki, K.; Hashimoto, K.; Tateno, Y.; Ikehira, H.

    1986-01-01

    Using 11C-labeled Ro15-1788 and positron emission tomography, studies of benzodiazepine binding sites in the human brain were performed on four normal volunteers. Rapid and high accumulation of 11C activity was observed in the brain after i.v. injection of [11C]Ro15-1788, the maximum of which was within 12 min. Initial distribution of 11C activity in the brain was similar to the distribution of the normal cerebral blood flow. Ten minutes after injection, however, a high uptake of 11C activity was observed in the cerebral cortex and moderate uptake was seen in the cerebellar cortex, the basal ganglia, and the thalamus. The accumulation of 11C activity was low in the brain stem. This distribution of 11C activity was approximately parallel to the known distribution of benzodiazepine receptors. Saturation experiments were performed on four volunteers with oral administration of 0.3-1.8 mg/kg of cold Ro15-1788 prior to injection. Initial distribution of 11C activity following injection peaked within 2 min and then the accumulation of 11C activity decreased rapidly and remarkably throughout the brain. The results indicated that [11C] Ro15-1788 associates and dissociates to specific and nonspecific binding sites rapidly and has a high ratio of specific receptor binding to nonspecific binding in vivo. Carbon-11 Ro15-1788 is a suitable radioligand for the study of benzodiazepine receptors in vivo in humans

  19. Complex Trajectories of Brain Development in the Healthy Human Fetus.

    Science.gov (United States)

    Andescavage, Nickie N; du Plessis, Adre; McCarter, Robert; Serag, Ahmed; Evangelou, Iordanis; Vezina, Gilbert; Robertson, Richard; Limperopoulos, Catherine

    2017-11-01

    This study characterizes global and hemispheric brain growth in healthy human fetuses during the second half of pregnancy using three-dimensional MRI techniques. We studied 166 healthy fetuses that underwent MRI between 18 and 39 completed weeks gestation. We created three-dimensional high-resolution reconstructions of the brain and calculated volumes for left and right cortical gray matter (CGM), fetal white matter (FWM), deep subcortical structures (DSS), and the cerebellum. We calculated the rate of growth for each tissue class according to gestational age and described patterns of hemispheric growth. Each brain region demonstrated major increases in volume during the second half of gestation, the most pronounced being the cerebellum (34-fold), followed by FWM (22-fold), CGM (21-fold), and DSS (10-fold). The left cerebellar hemisphere, CGM, and DSS had larger volumes early in gestation, but these equalized by term. It has been increasingly recognized that brain asymmetry evolves throughout the human life span. Advanced quantitative MRI provides noninvasive measurements of early structural asymmetry between the left and right fetal brain that may inform functional and behavioral laterality differences seen in children and young adulthood. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. Direct Electrical Stimulation in the Human Brain Disrupts Melody Processing.

    Science.gov (United States)

    Garcea, Frank E; Chernoff, Benjamin L; Diamond, Bram; Lewis, Wesley; Sims, Maxwell H; Tomlinson, Samuel B; Teghipco, Alexander; Belkhir, Raouf; Gannon, Sarah B; Erickson, Steve; Smith, Susan O; Stone, Jonathan; Liu, Lynn; Tollefson, Trenton; Langfitt, John; Marvin, Elizabeth; Pilcher, Webster H; Mahon, Bradford Z

    2017-09-11

    Prior research using functional magnetic resonance imaging (fMRI) [1-4] and behavioral studies of patients with acquired or congenital amusia [5-8] suggest that the right posterior superior temporal gyrus (STG) in the human brain is specialized for aspects of music processing (for review, see [9-12]). Intracranial electrical brain stimulation in awake neurosurgery patients is a powerful means to determine the computations supported by specific brain regions and networks [13-21] because it provides reversible causal evidence with high spatial resolution (for review, see [22, 23]). Prior intracranial stimulation or cortical cooling studies have investigated musical abilities related to reading music scores [13, 14] and singing familiar songs [24, 25]. However, individuals with amusia (congenitally, or from a brain injury) have difficulty humming melodies but can be spared for singing familiar songs with familiar lyrics [26]. Here we report a detailed study of a musician with a low-grade tumor in the right temporal lobe. Functional MRI was used pre-operatively to localize music processing to the right STG, and the patient subsequently underwent awake intraoperative mapping using direct electrical stimulation during a melody repetition task. Stimulation of the right STG induced "music arrest" and errors in pitch but did not affect language processing. These findings provide causal evidence for the functional segregation of music and language processing in the human brain and confirm a specific role of the right STG in melody processing. VIDEO ABSTRACT. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Ex-vivo MR Volumetry of Human Brain Hemispheres

    Science.gov (United States)

    Kotrotsou, Aikaterini; Bennett, David A.; Schneider, Julie A.; Dawe, Robert J.; Golak, Tom; Leurgans, Sue E.; Yu, Lei; Arfanakis, Konstantinos

    2013-01-01

    Purpose The aims of this work were to: a) develop an approach for ex-vivo MR volumetry of human brain hemispheres that does not contaminate the results of histopathological examination, b) longitudinally assess regional brain volumes postmortem, and c) investigate the relationship between MR volumetric measurements performed in-vivo and ex-vivo. Methods An approach for ex-vivo MR volumetry of human brain hemispheres was developed. Five hemispheres from elderly subjects were imaged ex-vivo longitudinally. All datasets were segmented. The longitudinal behavior of volumes measured ex-vivo was assessed. The relationship between in-vivo and ex-vivo volumetric measurements was investigated in seven elderly subjects imaged both ante-mortem and postmortem. Results The presented approach for ex-vivo MR volumetry did not contaminate the results of histopathological examination. For a period of 6 months postmortem, within-subject volume variation across time points was substantially smaller than inter-subject volume variation. A close linear correspondence was detected between in-vivo and ex-vivo volumetric measurements. Conclusion Regional brain volumes measured with the presented approach for ex-vivo MR volumetry remain relatively unchanged for a period of 6 months postmortem. Furthermore, the linear relationship between in-vivo and ex-vivo MR volumetric measurements suggests that the presented approach captures information linked to ante-mortem macrostructural brain characteristics. PMID:23440751

  2. Ex vivo MR volumetry of human brain hemispheres.

    Science.gov (United States)

    Kotrotsou, Aikaterini; Bennett, David A; Schneider, Julie A; Dawe, Robert J; Golak, Tom; Leurgans, Sue E; Yu, Lei; Arfanakis, Konstantinos

    2014-01-01

    The aims of this work were to (a) develop an approach for ex vivo MR volumetry of human brain hemispheres that does not contaminate the results of histopathological examination, (b) longitudinally assess regional brain volumes postmortem, and (c) investigate the relationship between MR volumetric measurements performed in vivo and ex vivo. An approach for ex vivo MR volumetry of human brain hemispheres was developed. Five hemispheres from elderly subjects were imaged ex vivo longitudinally. All datasets were segmented. The longitudinal behavior of volumes measured ex vivo was assessed. The relationship between in vivo and ex vivo volumetric measurements was investigated in seven elderly subjects imaged both antemortem and postmortem. This approach for ex vivo MR volumetry did not contaminate the results of histopathological examination. For a period of 6 months postmortem, within-subject volume variation across time points was substantially smaller than intersubject volume variation. A close linear correspondence was detected between in vivo and ex vivo volumetric measurements. Regional brain volumes measured with this approach for ex vivo MR volumetry remain relatively unchanged for a period of 6 months postmortem. Furthermore, the linear relationship between in vivo and ex vivo MR volumetric measurements suggests that this approach captures information linked to antemortem macrostructural brain characteristics. Copyright © 2013 Wiley Periodicals, Inc.

  3. Topological isomorphisms of human brain and financial market networks

    Directory of Open Access Journals (Sweden)

    Petra E Vértes

    2011-09-01

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

  4. Topological isomorphisms of human brain and financial market networks.

    Science.gov (United States)

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

    2011-01-01

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

  5. Brain lactate metabolism in humans with subarachnoid hemorrhage.

    Science.gov (United States)

    Oddo, Mauro; Levine, Joshua M; Frangos, Suzanne; Maloney-Wilensky, Eileen; Carrera, Emmanuel; Daniel, Roy T; Levivier, Marc; Magistretti, Pierre J; LeRoux, Peter D

    2012-05-01

    Lactate is central for the regulation of brain metabolism and is an alternative substrate to glucose after injury. Brain lactate metabolism in patients with subarachnoid hemorrhage has not been fully elucidated. Thirty-one subarachnoid hemorrhage patients monitored with cerebral microdialysis (CMD) and brain oxygen (PbtO(2)) were studied. Samples with elevated CMD lactate (>4 mmol/L) were matched to PbtO(2) and CMD pyruvate and categorized as hypoxic (PbtO(2) 119 μmol/L) versus nonhyperglycolytic. Median per patient samples with elevated CMD lactate was 54% (interquartile range, 11%-80%). Lactate elevations were more often attributable to cerebral hyperglycolysis (78%; interquartile range, 5%-98%) than brain hypoxia (11%; interquartile range, 4%-75%). Mortality was associated with increased percentage of samples with elevated lactate and brain hypoxia (28% [interquartile range 9%-95%] in nonsurvivors versus 9% [interquartile range 3%-17%] in survivors; P=0.02) and lower percentage of elevated lactate and cerebral hyperglycolysis (13% [interquartile range, 1%-87%] versus 88% [interquartile range, 27%-99%]; P=0.07). Cerebral hyperglycolytic lactate production predicted good 6-month outcome (odds ratio for modified Rankin Scale score, 0-3 1.49; CI, 1.08-2.05; P=0.016), whereas increased lactate with brain hypoxia was associated with a reduced likelihood of good outcome (OR, 0.78; CI, 0.59-1.03; P=0.08). Brain lactate is frequently elevated in subarachnoid hemorrhage patients, predominantly because of hyperglycolysis rather than hypoxia. A pattern of increased cerebral hyperglycolytic lactate was associated with good long-term recovery. Our data suggest that lactate may be used as an aerobic substrate by the injured human brain.

  6. Xanthine oxidase activity regulates human embryonic brain cells growth

    Directory of Open Access Journals (Sweden)

    Kevorkian G. A.

    2011-10-01

    Full Text Available Aim. Involvement of Xanthine Oxidase (XO; EC1.1.3.22 in cellular proliferation and differentiation has been suggested by the numerous investigations. We have proposed that XO might have undoubtedly important role during the development, maturation as well as the death of human embryos brain cells. Methods. Human abortion material was utilized for the cultivation of brain cells (E90. XO activity was measured by the formation of uric acid in tissue. Cell death was detected by the utility of Trypan Blue dye. Results. Allopurinol suppressed the XO activity in the brain tissue (0.12 ± 0.02; 0.20 ± 0.03 resp., p < 0.05. On day 12th the number of cells in the culture treated with the Allopurinol at the early stage of development was higher in comparison with the Control (2350.1 ± 199.0 vs 2123 ± 96 and higher in comparison with the late period of treatment (1479.6 ± 103.8, p < < 0.05. In all groups, the number of the dead cells was less than in Control, indicating the protective nature of Allopurinol as an inhibitor of XO. Conclusions. Allopurinol initiates cells proliferation in case of the early treatment of the human brain derived cell culture whereas at the late stages it has an opposite effect.

  7. Cross-hemispheric functional connectivity in the human fetal brain.

    Science.gov (United States)

    Thomason, Moriah E; Dassanayake, Maya T; Shen, Stephen; Katkuri, Yashwanth; Alexis, Mitchell; Anderson, Amy L; Yeo, Lami; Mody, Swati; Hernandez-Andrade, Edgar; Hassan, Sonia S; Studholme, Colin; Jeong, Jeong-Won; Romero, Roberto

    2013-02-20

    Compelling evidence indicates that psychiatric and developmental disorders are generally caused by disruptions in the functional connectivity (FC) of brain networks. Events occurring during development, and in particular during fetal life, have been implicated in the genesis of such disorders. However, the developmental timetable for the emergence of neural FC during human fetal life is unknown. We present the results of resting-state functional magnetic resonance imaging performed in 25 healthy human fetuses in the second and third trimesters of pregnancy (24 to 38 weeks of gestation). We report the presence of bilateral fetal brain FC and regional and age-related variation in FC. Significant bilateral connectivity was evident in half of the 42 areas tested, and the strength of FC between homologous cortical brain regions increased with advancing gestational age. We also observed medial to lateral gradients in fetal functional brain connectivity. These findings improve understanding of human fetal central nervous system development and provide a basis for examining the role of insults during fetal life in the subsequent development of disorders in neural FC.

  8. Dystrophic microglia in the aging human brain.

    Science.gov (United States)

    Streit, Wolfgang J; Sammons, Nicole W; Kuhns, Amanda J; Sparks, D Larry

    2004-01-15

    We have studied microglial morphology in the human cerebral cortex of two nondemented subjects using high-resolution LN-3 immunohistochemistry. Several abnormalities in microglial cytoplasmic structure, including deramification, spheroid formation, gnarling, and fragmentation of processes, were identified. These changes were determined to be different from the morphological changes that occur during microglial activation and they were designated collectively as microglial dystrophy. Quantitative evaluation of dystrophic changes in microglia revealed that these were much more prevalent in the older subject (68-year-old) than in the younger one (38-year-old). Thus, we conclude that microglial dystrophy is a sign of microglial cell senescence. We hypothesize that microglial senescence could be important for understanding age-related declines in cognitive function. Copyright 2003 Wiley-Liss, Inc.

  9. Mapping the calcitonin receptor in human brain stem

    DEFF Research Database (Denmark)

    Bower, Rebekah L; Eftekhari, Sajedeh; Waldvogel, Henry J

    2016-01-01

    understanding of these hormone systems by mapping CTR expression in the human brain stem, specifically the medulla oblongata. Widespread CTR-like immunoreactivity was observed throughout the medulla. Dense CTR staining was noted in several discrete nuclei, including the nucleus of the solitary tract...... receptors (AMY) are a heterodimer formed by the coexpression of CTR with receptor activity-modifying proteins (RAMPs). CTR with RAMP1 responds potently to both amylin and CGRP. The brain stem is a major site of action for circulating amylin and is a rich site of CGRP binding. This study aimed to enhance our...

  10. Dynamic reconfiguration of human brain functional networks through neurofeedback.

    Science.gov (United States)

    Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

    2013-11-01

    Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Accounting for individual differences in human associative learning

    OpenAIRE

    Byrom, Nicola C.

    2013-01-01

    Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility ...

  12. A human-specific de novo protein-coding gene associated with human brain functions.

    Directory of Open Access Journals (Sweden)

    Chuan-Yun Li

    2010-03-01

    Full Text Available To understand whether any human-specific new genes may be associated with human brain functions, we computationally screened the genetic vulnerable factors identified through Genome-Wide Association Studies and linkage analyses of nicotine addiction and found one human-specific de novo protein-coding gene, FLJ33706 (alternative gene symbol C20orf203. Cross-species analysis revealed interesting evolutionary paths of how this gene had originated from noncoding DNA sequences: insertion of repeat elements especially Alu contributed to the formation of the first coding exon and six standard splice junctions on the branch leading to humans and chimpanzees, and two subsequent substitutions in the human lineage escaped two stop codons and created an open reading frame of 194 amino acids. We experimentally verified FLJ33706's mRNA and protein expression in the brain. Real-Time PCR in multiple tissues demonstrated that FLJ33706 was most abundantly expressed in brain. Human polymorphism data suggested that FLJ33706 encodes a protein under purifying selection. A specifically designed antibody detected its protein expression across human cortex, cerebellum and midbrain. Immunohistochemistry study in normal human brain cortex revealed the localization of FLJ33706 protein in neurons. Elevated expressions of FLJ33706 were detected in Alzheimer's brain samples, suggesting the role of this novel gene in human-specific pathogenesis of Alzheimer's disease. FLJ33706 provided the strongest evidence so far that human-specific de novo genes can have protein-coding potential and differential protein expression, and be involved in human brain functions.

  13. From Design to Implementation to Practice a Learning by Teaching System: Betty's Brain

    Science.gov (United States)

    Biswas, Gautam; Segedy, James R.; Bunchongchit, Kritya

    2016-01-01

    This paper presents an overview of 10 years of research with the "Betty's Brain" computer-based learning environment. We discuss the theoretical basis for "Betty's Brain" and the learning-by-teaching paradigm. We also highlight our key research findings, and discuss how these findings have shaped subsequent research. Throughout…

  14. Brain Based Learning in Science Education in Turkey: Descriptive Content and Meta Analysis of Dissertations

    Science.gov (United States)

    Yasar, M. Diyaddin

    2017-01-01

    This study aimed at performing content analysis and meta-analysis on dissertations related to brain-based learning in science education to find out the general trend and tendency of brain-based learning in science education and find out the effect of such studies on achievement and attitude of learners with the ultimate aim of raising awareness…

  15. From Neurons to Brainpower: Cognitive Neuroscience and Brain-Based Learning

    Science.gov (United States)

    Phillips, Janet M.

    2005-01-01

    We have learned more about the brain in the past five years than the previous 100. Neuroimaging, lesion studies, and animal studies have revealed the intricate inner workings of the brain and learning. Synaptogenesis, pruning, sensitive periods, and plasticity have all become accepted concepts of cognitive neuroscience that are now being applied…

  16. Assessing a Faculty Development Program for the Adoption of Brain-Based Learning Strategies

    Science.gov (United States)

    Lavis, Catherine C.; Williams, Kimberly A.; Fallin, Jana; Barnes, Pamela K.; Fishback, Sarah J.; Thien, Stephen

    2016-01-01

    Kansas State University designed a 20-month faculty development program with the goal of fostering broad, institution-wide adoption of teaching practices that focus on brain-based learning. Components of the program included annual teaching and learning workshops, reading and discussion groups based on content of a book about how the brain learns…

  17. Brain Behavior Evolution during Learning: Emergence of Hierarchical Temporal Memory

    Science.gov (United States)

    2013-08-30

    by genetic information and implemented in each organism (includ- ing humans) in an environment of proteins and enzymes. However, the equivalent of a...process of learning. Implementation of the genetic code specifies the types and number of neurons as well as the general patterns of connections, but...well. This has come to be described by the rubric “Neurons that fire together wire together” [19]. Synaptic strengths are also weakened as a result of

  18. Cells in human postmortem brain tissue slices remain alive for several weeks in culture

    NARCIS (Netherlands)

    Verwer, Ronald W. H.; Hermens, Wim T. J. M. C.; Dijkhuizen, PaulaA; ter Brake, Olivier; Baker, Robert E.; Salehi, Ahmad; Sluiter, Arja A.; Kok, Marloes J. M.; Muller, Linda J.; Verhaagen, Joost; Swaab, Dick F.

    2002-01-01

    Animal models for human neurological and psychiatric diseases only partially mimic the underlying pathogenic processes. Therefore, we investigated the potential use of cultured postmortem brain tissue from adult neurological patients and controls. The present study shows that human brain tissue

  19. EEG potentials associated with artificial grammar learning in the primate brain.

    Science.gov (United States)

    Attaheri, Adam; Kikuchi, Yukiko; Milne, Alice E; Wilson, Benjamin; Alter, Kai; Petkov, Christopher I

    2015-09-01

    Electroencephalography (EEG) has identified human brain potentials elicited by Artificial Grammar (AG) learning paradigms, which present participants with rule-based sequences of stimuli. Nonhuman animals are sensitive to certain AGs; therefore, evaluating which EEG Event Related Potentials (ERPs) are associated with AG learning in nonhuman animals could identify evolutionarily conserved processes. We recorded EEG potentials during an auditory AG learning experiment in two Rhesus macaques. The animals were first exposed to sequences of nonsense words generated by the AG. Then surface-based ERPs were recorded in response to sequences that were 'consistent' with the AG and 'violation' sequences containing illegal transitions. The AG violations strongly modulated an early component, potentially homologous to the Mismatch Negativity (mMMN), a P200 and a late frontal positivity (P500). The macaque P500 is similar in polarity and time of occurrence to a late EEG positivity reported in human AG learning studies but might differ in functional role. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Mind Boggling! Considering the Possibilities of Brain Gym in Learning to Play an Instrument

    Science.gov (United States)

    Moore, Hilary; Hibbert, Fiona

    2005-01-01

    This paper is one of the first presentations of research into brain gym's effectiveness in learning musical instruments. Brain gym (or Edu-K) is the popular, over-arching name for a system of exercises, approaches, and techniques intended to improve mental and physical performance. We explain the basic concepts and activities of brain gym and…

  1. The neural encoding of guesses in the human brain.

    Science.gov (United States)

    Bode, Stefan; Bogler, Carsten; Soon, Chun Siong; Haynes, John-Dylan

    2012-01-16

    Human perception depends heavily on the quality of sensory information. When objects are hard to see we often believe ourselves to be purely guessing. Here we investigated whether such guesses use brain networks involved in perceptual decision making or independent networks. We used a combination of fMRI and pattern classification to test how visibility affects the signals, which determine choices. We found that decisions regarding clearly visible objects are predicted by signals in sensory brain regions, whereas different regions in parietal cortex became predictive when subjects were shown invisible objects and believed themselves to be purely guessing. This parietal network was highly overlapping with regions, which have previously been shown to encode free decisions. Thus, the brain might use a dedicated network for determining choices when insufficient sensory information is available. Copyright © 2011 Elsevier Inc. All rights reserved.

  2. Listening to humans walking together activates the social brain circuitry.

    Science.gov (United States)

    Saarela, Miiamaaria V; Hari, Riitta

    2008-01-01

    Human footsteps carry a vast amount of social information, which is often unconsciously noted. Using functional magnetic resonance imaging, we analyzed brain networks activated by footstep sounds of one or two persons walking. Listening to two persons walking together activated brain areas previously associated with affective states and social interaction, such as the subcallosal gyrus bilaterally, the right temporal pole, and the right amygdala. These areas seem to be involved in the analysis of persons' identity and complex social stimuli on the basis of auditory cues. Single footsteps activated only the biological motion area in the posterior STS region. Thus, hearing two persons walking together involved a more widespread brain network than did hearing footsteps from a single person.

  3. Interleukin-6 release from the human brain during prolonged exercise

    DEFF Research Database (Denmark)

    Nybo, Lars; Nielsen, Bodil; Pedersen, Bente Klarlund

    2002-01-01

    Interleukin (IL)-6 is a pleiotropic cytokine, which has a variety of physiological roles including functions within the central nervous system. Circulating IL-6 increases markedly during exercise, partly due to the release of IL-6 from the contracting skeletal muscles, and exercise-induced IL-6 m...... influence of hyperthermia. In conclusion, IL-6 is released from the brain during prolonged exercise in humans and it appears that the duration of the exercise rather than the increase in body temperature dictates the cerebral IL-6 response....... in the brain at rest or after 15 min of exercise, but a small release of IL-6 was observed after 60 min of exercise in the first bout (0.06 +/- 0.03 ng min(-1)). This release of IL-6 from the brain was five-fold greater at the end of the second bout (0.30 +/- 0.08 ng min(-1); P

  4. Endurance training enhances BDNF release from the human brain

    DEFF Research Database (Denmark)

    Seifert, Thomas; Brassard, Patrice; Wissenberg, Mads

    2010-01-01

    The circulating level of brain-derived neurotrophic factor (BDNF) is reduced in patients with major depression and type-2 diabetes. Because acute exercise increases BDNF production in the hippocampus and cerebral cortex, we hypothesized that endurance training would enhance the release of BDNF from...... the human brain as detected from arterial and internal jugular venous blood samples. In a randomized controlled study, 12 healthy sedentary males carried out 3 mo of endurance training (n = 7) or served as controls (n = 5). Before and after the intervention, blood samples were obtained at rest and during...... exercise. At baseline, the training group (58 + or - 106 ng x 100 g(-1) x min(-1), means + or - SD) and the control group (12 + or - 17 ng x 100 g(-1) x min(-1)) had a similar release of BDNF from the brain at rest. Three months of endurance training enhanced the resting release of BDNF to 206 + or - 108...

  5. Midsagittal Brain Variation among Non-Human Primates: Insights into Evolutionary Expansion of the Human Precuneus.

    Science.gov (United States)

    Pereira-Pedro, Ana Sofia; Rilling, James K; Chen, Xu; Preuss, Todd M; Bruner, Emiliano

    2017-01-01

    The precuneus is a major element of the superior parietal lobule, positioned on the medial side of the hemisphere and reaching the dorsal surface of the brain. It is a crucial functional region for visuospatial integration, visual imagery, and body coordination. Previously, we argued that the precuneus expanded in recent human evolution, based on a combination of paleontological, comparative, and intraspecific evidence from fossil and modern human endocasts as well as from human and chimpanzee brains. The longitudinal proportions of this region are a major source of anatomical variation among adult humans and, being much larger in Homo sapiens, is the main characteristic differentiating human midsagittal brain morphology from that of our closest living primate relative, the chimpanzee. In the current shape analysis, we examine precuneus variation in non-human primates through landmark-based models, to evaluate the general pattern of variability in non-human primates, and to test whether precuneus proportions are influenced by allometric effects of brain size. Results show that precuneus proportions do not covary with brain size, and that the main difference between monkeys and apes involves a vertical expansion of the frontal and occipital regions in apes. Such differences might reflect differences in brain proportions or differences in cranial architecture. In this sample, precuneus variation is apparently not influenced by phylogenetic or allometric factors, but does vary consistently within species, at least in chimpanzees and macaques. This result further supports the hypothesis that precuneus expansion in modern humans is not merely a consequence of increasing brain size or of allometric scaling, but rather represents a species-specific morphological change in our lineage. © 2017 S. Karger AG, Basel.

  6. Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals.

    Science.gov (United States)

    Lancaster, Thomas M; Ihssen, Niklas; Brindley, Lisa M; Tansey, Katherine E; Mantripragada, Kiran; O'Donovan, Michael C; Owen, Michael J; Linden, David E J

    2016-02-01

    A substantial proportion of schizophrenia liability can be explained by additive genetic factors. Risk profile scores (RPS) directly index risk using a summated total of common risk variants weighted by their effect. Previous studies suggest that schizophrenia RPS predict alterations to neural networks that support working memory and verbal fluency. In this study, we apply schizophrenia RPS to fMRI data to elucidate the effects of polygenic risk on functional brain networks during a probabilistic-learning neuroimaging paradigm. The neural networks recruited during this paradigm have previously been shown to be altered to unmedicated schizophrenia patients and relatives of schizophrenia patients, which may reflect genetic susceptibility. We created schizophrenia RPS using summary data from the Psychiatric Genetic Consortium (Schizophrenia Working Group) for 83 healthy individuals and explore associations between schizophrenia RPS and blood oxygen level dependency (BOLD) during periods of choice behavior (switch-stay) and reflection upon choice outcome (reward-punishment). We show that schizophrenia RPS is associated with alterations in the frontal pole (PWHOLE-BRAIN-CORRECTED  = 0.048) and the ventral striatum (PROI-CORRECTED  = 0.036), during choice behavior, but not choice outcome. We suggest that the common risk variants that increase susceptibility to schizophrenia can be associated with alterations in the neural circuitry that support the processing of changing reward contingencies. Hum Brain Mapp 37:491-500, 2016. © 2015 Wiley Periodicals, Inc. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  7. Sigma and opioid receptors in human brain tumors

    International Nuclear Information System (INIS)

    Thomas, G.E.; Szuecs, M.; Mamone, J.Y.; Bem, W.T.; Rush, M.D.; Johnson, F.E.; Coscia, C.J.

    1990-01-01

    Human brain tumors and nude mouse-borne human neuroblastomas and gliomas were analyzed for sigma and opioid receptor content. Sigma binding was assessed using [ 3 H] 1, 3-di-o-tolylguanidine (DTG), whereas opioid receptor subtypes were measured with tritiated forms of the following: μ, [D-ala 2 , mePhe 4 , gly-ol 5 ] enkephalin (DAMGE); κ, ethylketocyclazocine (EKC) or U69,593; δ, [D-pen 2 , D-pen 5 ] enkephalin (DPDPE) or [D-ala 2 , D-leu 5 ] enkephalin (DADLE) with μ suppressor present. Binding parameters were estimated by homologous displacement assays followed by analysis using the LIGAND program. Sigma binding was detected in 15 of 16 tumors examined with very high levels found in a brain metastasis from an adenocarcinoma of lung and a human neuroblastoma (SK-N-MC) passaged in nude mice. κ opioid receptor binding was detected in 4 of 4 glioblastoma multiforme specimens and 2 of 2 human astrocytoma cell lines tested but not in the other brain tumors analyzed

  8. Sigma and opioid receptors in human brain tumors

    Energy Technology Data Exchange (ETDEWEB)

    Thomas, G.E.; Szuecs, M.; Mamone, J.Y.; Bem, W.T.; Rush, M.D.; Johnson, F.E.; Coscia, C.J. (St. Louis Univ. School of Medicine, MO (USA))

    1990-01-01

    Human brain tumors and nude mouse-borne human neuroblastomas and gliomas were analyzed for sigma and opioid receptor content. Sigma binding was assessed using ({sup 3}H) 1, 3-di-o-tolylguanidine (DTG), whereas opioid receptor subtypes were measured with tritiated forms of the following: {mu}, (D-ala{sup 2}, mePhe{sup 4}, gly-ol{sup 5}) enkephalin (DAMGE); {kappa}, ethylketocyclazocine (EKC) or U69,593; {delta}, (D-pen{sup 2}, D-pen{sup 5}) enkephalin (DPDPE) or (D-ala{sup 2}, D-leu{sup 5}) enkephalin (DADLE) with {mu} suppressor present. Binding parameters were estimated by homologous displacement assays followed by analysis using the LIGAND program. Sigma binding was detected in 15 of 16 tumors examined with very high levels found in a brain metastasis from an adenocarcinoma of lung and a human neuroblastoma (SK-N-MC) passaged in nude mice. {kappa} opioid receptor binding was detected in 4 of 4 glioblastoma multiforme specimens and 2 of 2 human astrocytoma cell lines tested but not in the other brain tumors analyzed.

  9. Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

    Science.gov (United States)

    Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

    2015-09-01

    Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

  10. Distribution of cellular HSV-1 receptor expression in human brain.

    Science.gov (United States)

    Lathe, Richard; Haas, Juergen G

    2017-06-01

    Herpes simplex virus type 1 (HSV-1) is a neurotropic virus linked to a range of acute and chronic neurological disorders affecting distinct regions of the brain. Unusually, HSV-1 entry into cells requires the interaction of viral proteins glycoprotein D (gD) and glycoprotein B (gB) with distinct cellular receptor proteins. Several different gD and gB receptors have been identified, including TNFRSF14/HVEM and PVRL1/nectin 1 as gD receptors and PILRA, MAG, and MYH9 as gB receptors. We investigated the expression of these receptor molecules in different areas of the adult and developing human brain using online transcriptome databases. Whereas all HSV-1 receptors showed distinct expression patterns in different brain areas, the Allan Brain Atlas (ABA) reported increased expression of both gD and gB receptors in the hippocampus. Specifically, for PVRL1, TNFRFS14, and MYH9, the differential z scores for hippocampal expression, a measure of relative levels of increased expression, rose to 2.9, 2.9, and 2.5, respectively, comparable to the z score for the archetypical hippocampus-enriched mineralocorticoid receptor (NR3C2, z = 3.1). These data were confirmed at the Human Brain Transcriptome (HBT) database, but HBT data indicate that MAG expression is also enriched in hippocampus. The HBT database allowed the developmental pattern of expression to be investigated; we report that all HSV1 receptors markedly increase in expression levels between gestation and the postnatal/adult periods. These results suggest that differential receptor expression levels of several HSV-1 gD and gB receptors in the adult hippocampus are likely to underlie the susceptibility of this brain region to HSV-1 infection.

  11. Is the social brain theory applicable to human individual differences? Relationship between sociability personality dimension and brain size.

    Science.gov (United States)

    Horváth, Klára; Martos, János; Mihalik, Béla; Bódizs, Róbert

    2011-06-17

    Our study intends to examine whether the social brain theory is applicable to human individual differences. According to the social brain theory primates have larger brains as it could be expected from their body sizes due to the adaptation to a more complex social life. Regarding humans there were few studies about the relationship between theory of mind and frontal and temporal brain lobes. We hypothesized that these brain lobes, as well as the whole cerebrum and neocortex are in connection with the Sociability personality dimension that is associated with individuals' social lives. Our findings support this hypothesis as Sociability correlated positively with the examined brain structures if we control the effects of body size differences and age. These results suggest that the social brain theory can be extended to human interindividual differences and they have some implications to personality psychology too.

  12. Music mnemonics aid Verbal Memory and Induce Learning – Related Brain Plasticity in Multiple Sclerosis

    OpenAIRE

    Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker

    2014-01-01

    Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during ...

  13. Sensitivity analysis of human brain structural network construction

    Directory of Open Access Journals (Sweden)

    Kuang Wei

    2017-12-01

    Full Text Available Network neuroscience leverages diffusion-weighted magnetic resonance imaging and tractography to quantify structural connectivity of the human brain. However, scientists and practitioners lack a clear understanding of the effects of varying tractography parameters on the constructed structural networks. With diffusion images from the Human Connectome Project (HCP, we characterize how structural networks are impacted by the spatial resolution of brain atlases, total number of tractography streamlines, and grey matter dilation with various graph metrics. We demonstrate how injudicious combinations of highly refined brain parcellations and low numbers of streamlines may inadvertently lead to disconnected network models with isolated nodes. Furthermore, we provide solutions to significantly reduce the likelihood of generating disconnected networks. In addition, for different tractography parameters, we investigate the distributions of values taken by various graph metrics across the population of HCP subjects. Analyzing the ranks of individual subjects within the graph metric distributions, we find that the ranks of individuals are affected differently by atlas scale changes. Our work serves as a guideline for researchers to optimize the selection of tractography parameters and illustrates how biological characteristics of the brain derived in network neuroscience studies can be affected by the choice of atlas parcellation schemes. Diffusion tractography has been proven to be a promising noninvasive technique to study the network properties of the human brain. However, how various tractography and network construction parameters affect network properties has not been studied using a large cohort of high-quality data. We utilize data provided by the Human Connectome Project to characterize the changes to network properties induced by varying the brain parcellation atlas scales, the number of reconstructed tractography tracks, and the degree of grey

  14. Motor sequence learning-induced neural efficiency in functional brain connectivity.

    Science.gov (United States)

    Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

    2017-02-15

    Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Sex differences in the structural connectome of the human brain.

    Science.gov (United States)

    Ingalhalikar, Madhura; Smith, Alex; Parker, Drew; Satterthwaite, Theodore D; Elliott, Mark A; Ruparel, Kosha; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

    2014-01-14

    Sex differences in human behavior show adaptive complementarity: Males have better motor and spatial abilities, whereas females have superior memory and social cognition skills. Studies also show sex differences in human brains but do not explain this complementarity. In this work, we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged 8-22 y, 428 males and 521 females) and discovered unique sex differences in brain connectivity during the course of development. Connection-wise statistical analysis, as well as analysis of regional and global network measures, presented a comprehensive description of network characteristics. In all supratentorial regions, males had greater within-hemispheric connectivity, as well as enhanced modularity and transitivity, whereas between-hemispheric connectivity and cross-module participation predominated in females. However, this effect was reversed in the cerebellar connections. Analysis of these changes developmentally demonstrated differences in trajectory between males and females mainly in adolescence and in adulthood. Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.

  16. Multiscale neural connectivity during human sensory processing in the brain

    Science.gov (United States)

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

    2018-05-01

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

  17. In Vivo H MR spectroscopic imaging of human brain

    International Nuclear Information System (INIS)

    Choe, Bo Young; Suh, Tae Suk; Choi, Kyo Ho; Bahk, Yong Whee; Shinn, Kyung Sub

    1994-01-01

    To evaluate the spatial distribution of various proton metabolites in the human brain with use of water-suppressed in vivo H MR spectroscopic imaging (MRSI) technique. All of water-suppressed in vivo H MRSI were performed on 1.5 T whole-body MRI/MRS system using Stimulated Echo Acquisition Method (STEAM) Chemical Shift Imaging (CSI) pulse sequence. T1-weighted MR images were used for CSI field of view (FOV; 24 cm). Voxel size of 1.5 cm 3 was designated from the periphery of the brain which was divided by 1024 X 16 X 16 data points. Metabolite images of N-acetylaspartate (NAA), creatine/ phosphocreatine (Cr) + choline/phosphocholine (Cho), and complex of γ-aminobutyric acid (GABA) + glutamate (Glu) were obtained on the human brain. Our preliminary study suggests that in vivo H MRSI could provide the metabolite imaging to compensate for hypermetabolism on Positron Emission Tomography (PET) scans on the basis of the metabolic informations on brain tissues. The unique ability of in vivo H MRSI to offer noninvasive information about tissue biochemistry in disease states will stimulate on clinical research and disease diagnosis

  18. Drug delivery to the human brain via the cerebrospinal fluid

    Energy Technology Data Exchange (ETDEWEB)

    Howden, L.; Aroussi, A. [Univ. of Nottingham, School of Mechanical, Material, Manufacturing Engineering and Managements, Nottingham (United Kingdom)]. E-mail: eaxljh@nottingham.ac.uk; Vloeberghs, M. [Queens Medical Centre, Dept. of Child Health, Nottingham (United Kingdom)

    2003-07-01

    This Study investigates the flow of Cerebrospinal Fluid (CSF) inside the human ventricular system with particular emphasis on drug path flow for the purpose of medical drug injections. The investigation is conducted using the computational fluid dynamics package FLUENT. The role of the ventricular system is very important in protecting the brain from injury by cushioning it against the cranium during sudden movements. If for any reason the passage of CSF through the ventricular system is blocked (usually by stenosis) then a condition known as Hydrocephalus occurs, where by the blocked CSF causes the Intra Cranial Pressure (ICP) inside the brain to rise. If this is not treated then severe brain damage and death can occur. Previous work conducted by the authors on this subject has focused on the technique of ventriculostomy to treat hydrocephalus. The present study carries on from the previous work but focuses on delivering medical drugs to treat brain tumors that are conventionally not accessible and which require complicated surgical procedures to remove them. The study focuses on the possible paths for delivering drugs to tumors in the human nervous system through conventionally accessible locations without major surgery. The results of the investigation have shown that it is possible to reach over 95% of the ventricular system by injection of drugs however the results also show that there are many factors that can affect the drug flow paths through the ventricular system and thus the areas reachable, by these drugs. (author)

  19. Drug delivery to the human brain via the cerebrospinal fluid

    International Nuclear Information System (INIS)

    Howden, L.; Aroussi, A.; Vloeberghs, M.

    2003-01-01

    This Study investigates the flow of Cerebrospinal Fluid (CSF) inside the human ventricular system with particular emphasis on drug path flow for the purpose of medical drug injections. The investigation is conducted using the computational fluid dynamics package FLUENT. The role of the ventricular system is very important in protecting the brain from injury by cushioning it against the cranium during sudden movements. If for any reason the passage of CSF through the ventricular system is blocked (usually by stenosis) then a condition known as Hydrocephalus occurs, where by the blocked CSF causes the Intra Cranial Pressure (ICP) inside the brain to rise. If this is not treated then severe brain damage and death can occur. Previous work conducted by the authors on this subject has focused on the technique of ventriculostomy to treat hydrocephalus. The present study carries on from the previous work but focuses on delivering medical drugs to treat brain tumors that are conventionally not accessible and which require complicated surgical procedures to remove them. The study focuses on the possible paths for delivering drugs to tumors in the human nervous system through conventionally accessible locations without major surgery. The results of the investigation have shown that it is possible to reach over 95% of the ventricular system by injection of drugs however the results also show that there are many factors that can affect the drug flow paths through the ventricular system and thus the areas reachable, by these drugs. (author)

  20. The Speculative Neuroscience of the Future Human Brain

    Directory of Open Access Journals (Sweden)

    Robert A. Dielenberg

    2013-05-01

    Full Text Available The hallmark of our species is our ability to hybridize symbolic thinking with behavioral output. We began with the symmetrical hand axe around 1.7 mya and have progressed, slowly at first, then with greater rapidity, to producing increasingly more complex hybridized products. We now live in the age where our drive to hybridize has pushed us to the brink of a neuroscientific revolution, where for the first time we are in a position to willfully alter the brain and hence, our behavior and evolution. Nootropics, transcranial direct current stimulation (tDCS, transcranial magnetic stimulation (TMS, deep brain stimulation (DBS and invasive brain mind interface (BMI technology are allowing humans to treat previously inaccessible diseases as well as open up potential vistas for cognitive enhancement. In the future, the possibility exists for humans to hybridize with BMIs and mobile architectures. The notion of self is becoming increasingly extended. All of this to say: are we in control of our brains, or are they in control of us?

  1. Proactive Interference in Human Predictive Learning

    OpenAIRE

    Castro, Leyre; Ortega, Nuria; Matute, Helena

    2002-01-01

    The impairment in responding to a secondly trained association because of the prior training of another (i.e., proactive interference) is a well-established effect in human and animal research, and it has been demonstrated in many paradigms. However, learning theories have been concerned with proactive interference only when the competing stimuli have been presented in compound at some moment of the training phase. In this experiment we investigated the possibility of proactive interference b...

  2. Neurological impressions on the organization of language networks in the human brain.

    Science.gov (United States)

    Oliveira, Fabricio Ferreira de; Marin, Sheilla de Medeiros Correia; Bertolucci, Paulo Henrique Ferreira

    2017-01-01

    More than 95% of right-handed individuals, as well as almost 80% of left-handed individuals, have left hemisphere dominance for language. The perisylvian networks of the dominant hemisphere tend to be the most important language systems in human brains, usually connected by bidirectional fibres originated from the superior longitudinal fascicle/arcuate fascicle system and potentially modifiable by learning. Neuroplasticity mechanisms take place to preserve neural functions after brain injuries. Language is dependent on a hierarchical interlinkage of serial and parallel processing areas in distinct brain regions considered to be elementary processing units. Whereas aphasic syndromes typically result from injuries to the dominant hemisphere, the extent of the distribution of language functions seems to be variable for each individual. Review of the literature Results: Several theories try to explain the organization of language networks in the human brain from a point of view that involves either modular or distributed processing or sometimes both. The most important evidence for each approach is discussed under the light of modern theories of organization of neural networks. Understanding the connectivity patterns of language networks may provide deeper insights into language functions, supporting evidence-based rehabilitation strategies that focus on the enhancement of language organization for patients with aphasic syndromes.

  3. Prediction of stroke thrombolysis outcome using CT brain machine learning

    Directory of Open Access Journals (Sweden)

    Paul Bentley

    2014-01-01

    Full Text Available A critical decision-step in the emergency treatment of ischemic stroke is whether or not to administer thrombolysis — a treatment that can result in good recovery, or deterioration due to symptomatic intracranial haemorrhage (SICH. Certain imaging features based upon early computerized tomography (CT, in combination with clinical variables, have been found to predict SICH, albeit with modest accuracy. In this proof-of-concept study, we determine whether machine learning of CT images can predict which patients receiving tPA will develop SICH as opposed to showing clinical improvement with no haemorrhage. Clinical records and CT brains of 116 acute ischemic stroke patients treated with intravenous thrombolysis were collected retrospectively (including 16 who developed SICH. The sample was split into training (n = 106 and test sets (n = 10, repeatedly for 1760 different combinations. CT brain images acted as inputs into a support vector machine (SVM, along with clinical severity. Performance of the SVM was compared with established prognostication tools (SEDAN and HAT scores; original, or after adaptation to our cohort. Predictive performance, assessed as area under receiver-operating-characteristic curve (AUC, of the SVM (0.744 compared favourably with that of prognostic scores (original and adapted versions: 0.626–0.720; p < 0.01. The SVM also identified 9 out of 16 SICHs, as opposed to 1–5 using prognostic scores, assuming a 10% SICH frequency (p < 0.001. In summary, machine learning methods applied to acute stroke CT images offer automation, and potentially improved performance, for prediction of SICH following thrombolysis. Larger-scale cohorts, and incorporation of advanced imaging, should be tested with such methods.

  4. A Novel Human Body Area Network for Brain Diseases Analysis.

    Science.gov (United States)

    Lin, Kai; Xu, Tianlang

    2016-10-01

    Development of wireless sensor and mobile communication technology provide an unprecedented opportunity for realizing smart and interactive healthcare systems. Designing such systems aims to remotely monitor the health and diagnose the diseases for users. In this paper, we design a novel human body area network for brain diseases analysis, which is named BABDA. Considering the brain is one of the most complex organs in the human body, the BABDA system provides four function modules to ensure the high quality of the analysis result, which includes initial data collection, data correction, data transmission and comprehensive data analysis. The performance evaluation conducted in a realistic environment with several criteria shows the availability and practicability of the BABDA system.

  5. From Disabled Students to Disabled Brains: The Medicalizing Power of Rhetorical Images in the Israeli Learning Disabilities Field.

    Science.gov (United States)

    Katchergin, Ofer

    2017-09-01

    The neurocentric worldview that identifies the essence of the human being with the material brain has become a central paradigm in current academic discourse. Israeli researchers also seek to understand educational principles and processes via neuroscientific models. On this background, the article uncovers the central role that visual brain images play in the learning-disabilities field in Israel. It examines the place brain images have in the professional imagination of didactic-diagnosticians as well as their influence on the diagnosticians' clinical attitudes. It relies on two theoretical fields: sociology and anthropology of the body and sociology of neuromedical knowledge. The research consists of three methodologies: ethnographic observations, in-depth interviews, and rhetorical analysis of visual and verbal texts. It uncovers the various rhetorical and ideological functions of brain images in the field. It also charts the repertoire of rhetorical devices which are utilized to strengthen the neuroreducionist messages contained in the images.

  6. Extendable supervised dictionary learning for exploring diverse and concurrent brain activities in task-based fMRI.

    Science.gov (United States)

    Zhao, Shijie; Han, Junwei; Hu, Xintao; Jiang, Xi; Lv, Jinglei; Zhang, Tuo; Zhang, Shu; Guo, Lei; Liu, Tianming

    2018-06-01

    Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional magnetic resonance imaging (tfMRI) analysis approach, i.e., the general linear model (GLM), might have difficulty in discovering those diverse and concurrent brain responses sufficiently. This subtraction-based model-driven approach focuses on the brain activities evoked directly from the task paradigm, thus likely overlooks other possible concurrent brain activities evoked during the information processing. To deal with this problem, in this paper, we propose a novel hybrid framework, called extendable supervised dictionary learning (E-SDL), to explore diverse and concurrent brain activities under task conditions. A critical difference between E-SDL framework and previous methods is that we systematically extend the basic task paradigm regressor into meaningful regressor groups to account for possible regressor variation during the information processing procedure in the brain. Applications of the proposed framework on five independent and publicly available tfMRI datasets from human connectome project (HCP) simultaneously revealed more meaningful group-wise consistent task-evoked networks and common intrinsic connectivity networks (ICNs). These results demonstrate the advantage of the proposed framework in identifying the diversity of concurrent brain activities in tfMRI datasets.

  7. Two distinct forms of functional lateralization in the human brain

    OpenAIRE

    Gotts, Stephen J.; Jo, Hang Joon; Wallace, Gregory L.; Saad, Ziad S.; Cox, Robert W.; Martin, Alex

    2013-01-01

    This study alters our fundamental understanding of the functional interactions between the cerebral hemispheres of the human brain by establishing that the left and right hemispheres have qualitatively different biases in how they dynamically interact with one another. Left-hemisphere regions are biased to interact more strongly within the same hemisphere, whereas right-hemisphere regions interact more strongly with both hemispheres. These two different patterns of interaction are associated ...

  8. Investigation of G72 (DAOA expression in the human brain

    Directory of Open Access Journals (Sweden)

    Hirsch Steven

    2008-12-01

    Full Text Available Abstract Background Polymorphisms at the G72/G30 locus on chromosome 13q have been associated with schizophrenia or bipolar disorder in more than ten independent studies. Even though the genetic findings are very robust, the physiological role of the predicted G72 protein has thus far not been resolved. Initial reports suggested G72 as an activator of D-amino acid oxidase (DAO, supporting the glutamate dysfunction hypothesis of schizophrenia. However, these findings have subsequently not been reproduced and reports of endogenous human G72 mRNA and protein expression are extremely limited. In order to better understand the function of this putative schizophrenia susceptibility gene, we attempted to demonstrate G72 mRNA and protein expression in relevant human brain regions. Methods The expression of G72 mRNA was studied by northern blotting and semi-quantitative SYBR-Green and Taqman RT-PCR. Protein expression in human tissue lysates was investigated by western blotting using two custom-made specific anti-G72 peptide antibodies. An in-depth in silico analysis of the G72/G30 locus was performed in order to try and identify motifs or regulatory elements that provide insight to G72 mRNA expression and transcript stability. Results Despite using highly sensitive techniques, we failed to identify significant levels of G72 mRNA in a variety of human tissues (e.g. adult brain, amygdala, caudate nucleus, fetal brain, spinal cord and testis human cell lines or schizophrenia/control post mortem BA10 samples. Furthermore, using western blotting in combination with sensitive detection methods, we were also unable to detect G72 protein in a number of human brain regions (including cerebellum and amygdala, spinal cord or testis. A detailed in silico analysis provides several lines of evidence that support the apparent low or absent expression of G72. Conclusion Our results suggest that native G72 protein is not normally present in the tissues that we analysed

  9. Structural Graphical Lasso for Learning Mouse Brain Connectivity

    KAUST Repository

    Yang, Sen; Sun, Qian; Ji, Shuiwang; Wonka, Peter; Davidson, Ian; Ye, Jieping

    2015-01-01

    Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability

  10. “Messing with the mind”: evolutionary challenges to human brain augmentation

    OpenAIRE

    Saniotis, Arthur; Henneberg, Maciej; Kumaratilake, Jaliya; Grantham, James P.

    2014-01-01

    The issue of brain augmentation has received considerable scientific attention over the last two decades. A key factor to brain augmentation that has been widely overlooked are the complex evolutionary processes which have taken place in evolving the human brain to its current state of functioning. Like other bodily organs, the human brain has been subject to the forces of biological adaptation. The structure and function of the brain, is very complex and only now we are beginning to understa...

  11. Progress in Application of the Neurosciences to an Understanding of Human Learning: The Challenge of Finding a Middle-Ground Neuroeducational Theory

    Science.gov (United States)

    Anderson, O. Roger

    2014-01-01

    Modern neuroscientific research has substantially enhanced our understanding of the human brain. However, many challenges remain in developing a strong, brain-based theory of human learning, especially in complex environments such as educational settings. Some of the current issues and challenges in our progress toward developing comprehensive…

  12. Imitative learning as a connector of collective brains.

    Directory of Open Access Journals (Sweden)

    José F Fontanari

    Full Text Available The notion that cooperation can aid a group of agents to solve problems more efficiently than if those agents worked in isolation is prevalent in computer science and business circles. Here we consider a primordial form of cooperation - imitative learning - that allows an effective exchange of information between agents, which are viewed as the processing units of a social intelligence system or collective brain. In particular, we use agent-based simulations to study the performance of a group of agents in solving a cryptarithmetic problem. An agent can either perform local random moves to explore the solution space of the problem or imitate a model agent - the best performing agent in its influence network. There is a trade-off between the number of agents N and the imitation probability p, and for the optimal balance between these parameters we observe a thirtyfold diminution in the computational cost to find the solution of the cryptarithmetic problem as compared with the independent search. If those parameters are chosen far from the optimal setting, however, then imitative learning can impair greatly the performance of the group.

  13. Even More Brain-Powered Science: Teaching and Learning with Discrepant Events. Brain-Powered Science Series

    Science.gov (United States)

    O'Brien, Thomas

    2011-01-01

    How can water and a penny demonstrate the power of mathematics and molecular theory? Do spelling and punctuation really matter to the human brain? The third of Thomas O'Brien's books designed for 5-12 grade science teachers, "Even More Brain-Powered Science" uses the questions above and 11 other inquiry-oriented discrepant events--experiments or…

  14. Mineralocorticoid receptor blockade prevents stress-induced modulation of multiple memory systems in the human brain.

    Science.gov (United States)

    Schwabe, Lars; Tegenthoff, Martin; Höffken, Oliver; Wolf, Oliver T

    2013-12-01

    Accumulating evidence suggests that stress may orchestrate the engagement of multiple memory systems in the brain. In particular, stress is thought to favor dorsal striatum-dependent procedural over hippocampus-dependent declarative memory. However, the neuroendocrine mechanisms underlying these modulatory effects of stress remain elusive, especially in humans. Here, we targeted the role of the mineralocorticoid receptor (MR) in the stress-induced modulation of dorsal striatal and hippocampal memory systems in the human brain using a combination of event-related functional magnetic resonance imaging and pharmacologic blockade of the MR. Eighty healthy participants received the MR antagonist spironolactone (300 mg) or a placebo and underwent a stressor or control manipulation before they performed, in the scanner, a classification task that can be supported by the hippocampus and the dorsal striatum. Stress after placebo did not affect learning performance but reduced explicit task knowledge and led to a relative increase in the use of more procedural learning strategies. At the neural level, stress promoted striatum-based learning at the expense of hippocampus-based learning. Functional connectivity analyses showed that this shift was associated with altered coupling of the amygdala with the hippocampus and dorsal striatum. Mineralocorticoid receptor blockade before stress prevented the stress-induced shift toward dorsal striatal procedural learning, same as the stress-induced alterations of amygdala connectivity with hippocampus and dorsal striatum, but resulted in significantly impaired performance. Our findings indicate that the stress-induced shift from hippocampal to dorsal striatal memory systems is mediated by the amygdala, required to preserve performance after stress, and dependent on the MR. © 2013 Society of Biological Psychiatry.

  15. Habit learning and brain-machine interfaces (BMI): a tribute to Valentino Braitenberg's "Vehicles".

    Science.gov (United States)

    Birbaumer, Niels; Hummel, Friedhelm C

    2014-10-01

    Brain-Machine Interfaces (BMI) allow manipulation of external devices and computers directly with brain activity without involvement of overt motor actions. The neurophysiological principles of such robotic brain devices and BMIs follow Hebbian learning rules as described and realized by Valentino Braitenberg in his book "Vehicles," in the concept of a "thought pump" residing in subcortical basal ganglia structures. We describe here the application of BMIs for brain communication in totally locked-in patients and argue that the thought pump may extinguish-at least partially-in those people because of extinction of instrumentally learned cognitive responses and brain responses. We show that Pavlovian semantic conditioning may allow brain communication even in the completely paralyzed who does not show response-effect contingencies. Principles of skill learning and habit acquisition as formulated by Braitenberg are the building blocks of BMIs and neuroprostheses.

  16. A Video Game for Learning Brain Evolution: A Resource or a Strategy?

    Science.gov (United States)

    Barbosa Gomez, Luisa Fernanda; Bohorquez Sotelo, Maria Cristina; Roja Higuera, Naydu Shirley; Rodriguez Mendoza, Brigitte Julieth

    2016-01-01

    Learning resources are part of the educational process of students. However, how video games act as learning resources in a population that has not selected the virtual formation as their main methodology? The aim of this study was to identify the influence of a video game in the learning process of brain evolution. For this purpose, the opinions…

  17. Medical humanities: a closer look at learning.

    Science.gov (United States)

    Patterson, A; Sharek, D; Hennessy, M; Phillips, M; Schofield, S

    2016-06-01

    The inclusion of medical humanities with medical curricula is a question that has been the focus of attention for many within the evolving field. This study addressed the question from a medical education perspective and aimed to investigate what students at Trinity College Dublin learned from participating in a short medical humanities student-selected module in their first year of an undergraduate medical programme. A total of 156 students provided a written reflection on a memorable event that occurred during their student-selected module. The reflections were analysed using the Reflection Evaluation for Learners' Enhanced Competencies Tool (REFLECT) and through qualitative thematic analysis of the written reflections. Evidence of learning from the REFLECT quantitative analysis showed that 50% of students displayed higher levels of reflection when describing their experience. The reflection content analysis supported the heterogeneous nature of learning outcome for students, with evidence to support the idea that the module provided opportunities for students to explore their beliefs, ideas and feelings regarding a range of areas outside their current experience or world view, to consider the views of others that they may have not previously been aware of, to reflect on their current views, and to consider their future professional practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  18. Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning.

    Science.gov (United States)

    Davatzikos, Christos

    2016-10-01

    The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain parcellation, voxel-based morphometric analyses, and multivariate pattern analyses using machine learning approaches. The evolution of these 3 types of analyses over the years has overcome many challenges. We present the evolution of our work in these 3 directions, which largely follows the evolution of this field. We discuss the progression from single-atlas, single-registration brain parcellation work to current ensemble-based parcellation; from relatively basic mass-univariate t-tests to optimized regional pattern analyses combining deformations and residuals; and from basic application of support vector machines to generative-discriminative formulations of multivariate pattern analyses, and to methods dealing with heterogeneity of neuroanatomical patterns. We conclude with discussion of some of the future directions and challenges. Copyright © 2016. Published by Elsevier B.V.

  19. Human midsagittal brain shape variation: patterns, allometry and integration

    Science.gov (United States)

    Bruner, Emiliano; Martin-Loeches, Manuel; Colom, Roberto

    2010-01-01

    Midsagittal cerebral morphology provides a homologous geometrical reference for brain shape and cortical vs. subcortical spatial relationships. In this study, midsagittal brain shape variation is investigated in a sample of 102 humans, in order to describe and quantify the major patterns of correlation between morphological features, the effect of size and sex on general anatomy, and the degree of integration between different cortical and subcortical areas. The only evident pattern of covariation was associated with fronto-parietal cortical bulging. The allometric component was weak for the cortical profile, but more robust for the posterior subcortical areas. Apparent sex differences were evidenced in size but not in brain shape. Cortical and subcortical elements displayed scarcely integrated changes, suggesting a modular separation between these two areas. However, a certain correlation was found between posterior subcortical and parietal cortical variations. These results should be directly integrated with information ranging from functional craniology to wiring organization, and with hypotheses linking brain shape and the mechanical properties of neurons during morphogenesis. PMID:20345859

  20. A new microcontroller-based human brain hypothermia system.

    Science.gov (United States)

    Kapidere, Metin; Ahiska, Raşit; Güler, Inan

    2005-10-01

    Many studies show that artificial hypothermia of brain in conditions of anesthesia with the rectal temperature lowered down to 33 degrees C produces pronounced prophylactic effect protecting the brain from anoxia. Out of the methods employed now in clinical practice for reducing the oxygen consumption by the cerebral tissue, the most efficacious is craniocerebral hypothermia (CCH). It is finding even more extensive application in cardiovascular surgery, neurosurgery, neurorenimatology and many other fields of medical practice. In this study, a microcontroller-based designed human brain hypothermia system (HBHS) is designed and constructed. The system is intended for cooling and heating the brain. HBHS consists of a thermoelectric hypothermic helmet, a control and a power unit. Helmet temperature is controlled by 8-bit PIC16F877 microcontroller which is programmed using MPLAB editor. Temperature is converted to 10-bit digital and is controlled automatically by the preset values which have been already entered in the microcontroller. Calibration is controlled and the working range is tested. Temperature of helmet is controlled between -5 and +46 degrees C by microcontroller, with the accuracy of +/-0.5 degrees C.

  1. Dissociable brain systems mediate vicarious learning of stimulus-response and action-outcome contingencies.

    Science.gov (United States)

    Liljeholm, Mimi; Molloy, Ciara J; O'Doherty, John P

    2012-07-18

    Two distinct strategies have been suggested to support action selection in humans and other animals on the basis of experiential learning: a goal-directed strategy that generates decisions based on the value and causal antecedents of action outcomes, and a habitual strategy that relies on the automatic elicitation of actions by environmental stimuli. In the present study, we investigated whether a similar dichotomy exists for actions that are acquired vicariously, through observation of other individuals rather than through direct experience, and assessed whether these strategies are mediated by distinct brain regions. We scanned participants with functional magnetic resonance imaging while they performed an observational learning task designed to encourage either goal-directed encoding of the consequences of observed actions, or a mapping of observed actions to conditional discriminative cues. Activity in different parts of the action observation network discriminated between the two conditions during observational learning and correlated with the degree of insensitivity to outcome devaluation in subsequent performance. Our findings suggest that, in striking parallel to experiential learning, neural systems mediating the observational acquisition of actions may be dissociated into distinct components: a goal-directed, outcome-sensitive component and a less flexible stimulus-response component.

  2. Accounting for individual differences in human associative learning.

    Science.gov (United States)

    Byrom, Nicola C

    2013-09-04

    Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

  3. Accounting for Individual Differences in Human Associative Learning.

    Directory of Open Access Journals (Sweden)

    Nicola C Byrom

    2013-09-01

    Full Text Available Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

  4. ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

    Directory of Open Access Journals (Sweden)

    Maria Kyrarini

    2017-08-01

    Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model.  In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.

  5. Insulin and C-peptide in human brain neurons (insulin/C-peptide/brain peptides/immunohistochemistry/radioimmunoassay)

    International Nuclear Information System (INIS)

    Dorn, A.; Bernstein, H.G.; Rinne, A.; Hahn, H.J.; Ziegler, M.

    1983-01-01

    The regional distribution and cellular localization of insulin and C-peptide immunoreactivities were studied in human cadaver brains using the indirect immunofluorescence method, the peroxidase-antiperoxidase technique, and radioimmunoassay. Products of the immune reactions to both polypeptides were observed in most nerve cells in all areas of the brain examined. Immunostaining was mainly restricted to the cell soma and proximal dendrites. Radioimmunoassay revealed that human brain contains insulin and C-peptide in concentrations much higher than the blood, the highest being in the hypothalamus. These findings support the hypothesis that the 'brain insulin' is - at least in part - produced in the CNS. (author)

  6. Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

    Science.gov (United States)

    Oudeyer, Pierre-Yves

    2017-01-01

    Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.

  7. Application of machine learning on brain cancer multiclass classification

    Science.gov (United States)

    Panca, V.; Rustam, Z.

    2017-07-01

    Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

  8. Two distinct forms of functional lateralization in the human brain

    Science.gov (United States)

    Gotts, Stephen J.; Jo, Hang Joon; Wallace, Gregory L.; Saad, Ziad S.; Cox, Robert W.; Martin, Alex

    2013-01-01

    The hemispheric lateralization of certain faculties in the human brain has long been held to be beneficial for functioning. However, quantitative relationships between the degree of lateralization in particular brain regions and the level of functioning have yet to be established. Here we demonstrate that two distinct forms of functional lateralization are present in the left vs. the right cerebral hemisphere, with the left hemisphere showing a preference to interact more exclusively with itself, particularly for cortical regions involved in language and fine motor coordination. In contrast, right-hemisphere cortical regions involved in visuospatial and attentional processing interact in a more integrative fashion with both hemispheres. The degree of lateralization present in these distinct systems selectively predicted behavioral measures of verbal and visuospatial ability, providing direct evidence that lateralization is associated with enhanced cognitive ability. PMID:23959883

  9. Brain-Based Aspects of Cognitive Learning Approaches in Second Language Learning

    Science.gov (United States)

    Moghaddam, Alireza Navid; Araghi, Seyed Mahdi

    2013-01-01

    Language learning process is one of the complicated behaviors of human beings which has called many scholars and experts' attention especially after the middle of last century by the advent of cognitive psychology that later on we see its implication to education. Unlike previous thought of schools, cognitive psychology deals with the way in which…

  10. "Brain drain, brain gain. . . Brain sustain?" : Challenges in building Portuguese human research capacity

    NARCIS (Netherlands)

    Hasanefendic, Sandra

    2017-01-01

    This paper presents a systematic but essentially descriptive account of the policy measure of stimulating human research capacity development under the policy program "Commitment to Science" in Portugal in the period 2006-2009. It explores the conditions that contributed to the development of the

  11. [Isolation and identification of brain tumor stem cells from human brain neuroepithelial tumors].

    Science.gov (United States)

    Fang, Jia-sheng; Deng, Yong-wen; Li, Ming-chu; Chen, Feng-Hua; Wang, Yan-jin; Lu, Ming; Fang, Fang; Wu, Jun; Yang, Zhuan-yi; Zhou, Xang-yang; Wang, Fei; Chen, Cheng

    2007-01-30

    To establish a simplified culture system for the isolation of brain tumor stem cells (BTSCs) from the tumors of human neuroepithelial tissue, to observe the growth and differentiation pattern of BTSCs, and to investigate their expression of the specific markers. Twenty-six patients with brain neuroepithelial tumors underwent tumor resection. Two pieces of tumor tissues were taken from each tumor to be dissociated, triturated into single cells in sterile DMEM-F12 medium, and then filtered. The tumor cells were seeded at a concentration of 200,000 viable cells per mL into serum-free DMEM-F12 medium simply supplemented with B27, human basic fibroblast growth factor (20 microg/L), human epidermal growth factor (20 microg /L), insulin (4 U/L), L-glutamine, penicillin and streptomycin. After the primary brain tumor spheres (BTSs) were generated, they were triturated again and passed in fresh medium. Limiting dilution assay was performed to observe the monoclone formation. 5-bromodeoxyuridine (BrdU) incorporation test was performed to observe the proliferation of the BTS. The BTSCs were cultured in mitogen-free DMEM-F12 medium supplemented with 10% fetal bovine serum to observe their differentiation. Immunocytochemistry was used to examine the expression of CD133 and nestin, specific markers of BTSC, and the rate of CD133 positive cells. Only a minority of subsets of cells from the tumors of neuroepithelial tissue had the capacity to survive, proliferate, and generate free-floating neurosphere-like BTSs in the simplified serum-free medium. These cells attached to the poly-L-lysine coated coverslips in the serum-supplemented medium and differentiated. The BTSCs were CD133 and nestin positive. The rate of CD133 positive cells in the tumor specimens was (21 +/- 6.2)% - (38 +/- 7.0)%. A new simplified culture system for the isolation of BTSCs is established. The tumors of human neuroepithelial tissue contain CD133 and nestin positive tumor stem cells which can be isolated

  12. The brain-tumor related protein podoplanin regulates synaptic plasticity and hippocampus-dependent learning and memory.

    Science.gov (United States)

    Cicvaric, Ana; Yang, Jiaye; Krieger, Sigurd; Khan, Deeba; Kim, Eun-Jung; Dominguez-Rodriguez, Manuel; Cabatic, Maureen; Molz, Barbara; Acevedo Aguilar, Juan Pablo; Milicevic, Radoslav; Smani, Tarik; Breuss, Johannes M; Kerjaschki, Dontscho; Pollak, Daniela D; Uhrin, Pavel; Monje, Francisco J

    2016-12-01

    Podoplanin is a cell-surface glycoprotein constitutively expressed in the brain and implicated in human brain tumorigenesis. The intrinsic function of podoplanin in brain neurons remains however uncharacterized. Using an established podoplanin-knockout mouse model and electrophysiological, biochemical, and behavioral approaches, we investigated the brain neuronal role of podoplanin. Ex-vivo electrophysiology showed that podoplanin deletion impairs dentate gyrus synaptic strengthening. In vivo, podoplanin deletion selectively impaired hippocampus-dependent spatial learning and memory without affecting amygdala-dependent cued fear conditioning. In vitro, neuronal overexpression of podoplanin promoted synaptic activity and neuritic outgrowth whereas podoplanin-deficient neurons exhibited stunted outgrowth and lower levels of p-Ezrin, TrkA, and CREB in response to nerve growth factor (NGF). Surface Plasmon Resonance data further indicated a physical interaction between podoplanin and NGF. This work proposes podoplanin as a novel component of the neuronal machinery underlying neuritogenesis, synaptic plasticity, and hippocampus-dependent memory functions. The existence of a relevant cross-talk between podoplanin and the NGF/TrkA signaling pathway is also for the first time proposed here, thus providing a novel molecular complex as a target for future multidisciplinary studies of the brain function in the physiology and the pathology. Key messages Podoplanin, a protein linked to the promotion of human brain tumors, is required in vivo for proper hippocampus-dependent learning and memory functions. Deletion of podoplanin selectively impairs activity-dependent synaptic strengthening at the neurogenic dentate-gyrus and hampers neuritogenesis and phospho Ezrin, TrkA and CREB protein levels upon NGF stimulation. Surface plasmon resonance data indicates a physical interaction between podoplanin and NGF. On these grounds, a relevant cross-talk between podoplanin and NGF as well

  13. Infection and upregulation of proinflammatory cytokines in human brain vascular pericytes by human cytomegalovirus

    Directory of Open Access Journals (Sweden)

    Alcendor Donald J

    2012-05-01

    Full Text Available Abstract Background Congenital human cytomegalovirus (HCMV infections can result in CNS abnormalities in newborn babies including vision loss, mental retardation, motor deficits, seizures, and hearing loss. Brain pericytes play an essential role in the development and function of the blood–brain barrier yet their unique role in HCMV dissemination and neuropathlogy has not been reported. Methods Primary human brain vascular pericytes were exposed to a primary clinical isolate of HCMV designated ‘SBCMV’. Infectivity was analyzed by microscopy, immunofluorescence, Western blot, and qRT-PCR. Microarrays were performed to identify proinflammatory cytokines upregulated after SBCMV exposure, and the results validated by real-time quantitative polymerase chain reaction (qPCR methodology. In situ cytokine expression of pericytes after exposure to HCMV was examined by ELISA and in vivo evidence of HCMV infection of brain pericytes was shown by dual-labeled immunohistochemistry. Results HCMV-infected human brain vascular pericytes as evidenced by several markers. Using a clinical isolate of HCMV (SBCMV, microscopy of infected pericytes showed virion production and typical cytomegalic cytopathology. This finding was confirmed by the expression of major immediate early and late virion proteins and by the presence of HCMV mRNA. Brain pericytes were fully permissive for CMV lytic replication after 72 to 96 hours in culture compared to human astrocytes or human brain microvascular endothelial cells (BMVEC. However, temporal transcriptional expression of pp65 virion protein after SBCMV infection was lower than that seen with the HCMV Towne laboratory strain. Using RT-PCR and dual-labeled immunofluorescence, proinflammatory cytokines CXCL8/IL-8, CXCL11/ITAC, and CCL5/Rantes were upregulated in SBCMV-infected cells, as were tumor necrosis factor-alpha (TNF-alpha, interleukin-1 beta (IL-1beta, and interleukin-6 (IL-6. Pericytes exposed to SBCMV elicited

  14. The Effects of Brain-Based Learning on the Academic Achievement of Students with Different Learning Styles

    Science.gov (United States)

    Duman, Bilal

    2010-01-01

    The purpose of the present study is to investigate the effects of Brain-based learning (BBL) on the academic achievement of students with different learning styles. The study group consists of students from the department of Social Sciences Teacher Education in the Faculty of Education at Mugla University (N=68). In the study, a pre-test-post-test…

  15. Why our brains cherish humanity: Mirror neurons and colamus humanitatem

    Directory of Open Access Journals (Sweden)

    John R. Skoyles

    2008-06-01

    Full Text Available Commonsense says we are isolated. After all, our bodies are physically separate. But Seneca’s colamus humanitatem, and John Donne’s observation that “no man is an island” suggests we are neither entirely isolated nor separate. A recent discovery in neuroscience—that of mirror neurons—argues that the brain and the mind is neither built nor functions remote from what happens in other individuals. What are mirror neurons? They are brain cells that process both what happens to or is done by an individual, and, as it were, its perceived “refl ection,” when that same thing happens or is done by another individual. Thus, mirror neurons are both activated when an individual does a particular action, and when that individual perceives that same action done by another. The discovery of mirror neurons suggests we need to radically revise our notions of human nature since they offer a means by which we may not be so separated as we think. Humans unlike other apes are adapted to mirror interact nonverbally when together. Notably, our faces have been evolved to display agile and nimble movements. While this is usually explained as enabling nonverbal communication, a better description would be nonverbal commune based upon mirror neurons. I argue we cherish humanity, colamus humanitatem, because mirror neurons and our adapted mirror interpersonal interface blur the physical boundaries that separate us.

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

    Directory of Open Access Journals (Sweden)

    Kevin Lai

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

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

    Science.gov (United States)

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

    2012-01-01

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

  18. Imaging neuroreceptors in the human brain in health and disease

    International Nuclear Information System (INIS)

    Wagner, H.N. Jr.; Dannals, R.F.; Frost, J.J.

    1985-01-01

    For nearly a century it has been known that chemical activity accompanies mental activity, but only recently has it been possible to begin to examine its exact nature. Positron-emitting radioactive tracers have made it possible to study the chemistry of the human brain in health and disease, using chiefly cyclotron-produced radionuclides, carbon-11, fluorine-18 and oxygen-15. It is now well established that measurable increases in regional cerebral blood flow, and glucose and oxygen metabolism accompany the mental functions of perception, cognition, emotion and motion. On 25 May 1983 the first imaging of a neuroreceptor in the human brain was accomplished with carbon-11 N-methyl spiperone, a ligand that binds preferentially to dopamine-2 receptors, 80% of which are located in the caudate nucleus and putamen. Quantitative imaging of serotonin-2, opiate, benzodiazapine and muscarinic cholinergic receptors has subsequently been accomplished. In studies of normal men and women, it has been found that dopamine and serotonin receptor activity decreases dramatically with age, such a decrease being more pronounced in men than in women and greater in the case of dopamine-2 receptors than in serotonin-2 receptors. Preliminary studies of patients with neuropsychiatric disorders suggest that dopamine-2 receptor activity is diminished in the caudate nucleus of patients with Huntington's disease. Positron tomography permits a quantitative assay of picomolar quantities of neuroreceptors within the living human brain. Studies of patients with Parkinson's disease, Alzheimer's disease, depression, anxiety, schizophrenia, acute and chronic pain states and drug addiction are now in progress. (author)

  19. Brain cDNA clone for human cholinesterase

    International Nuclear Information System (INIS)

    McTiernan, C.; Adkins, S.; Chatonnet, A.; Vaughan, T.A.; Bartels, C.F.; Kott, M.; Rosenberry, T.L.; La Du, B.N.; Lockridge, O.

    1987-01-01

    A cDNA library from human basal ganglia was screened with oligonucleotide probes corresponding to portions of the amino acid sequence of human serum cholinesterase. Five overlapping clones, representing 2.4 kilobases, were isolated. The sequenced cDNA contained 207 base pairs of coding sequence 5' to the amino terminus of the mature protein in which there were four ATG translation start sites in the same reading frame as the protein. Only the ATG coding for Met-(-28) lay within a favorable consensus sequence for functional initiators. There were 1722 base pairs of coding sequence corresponding to the protein found circulating in human serum. The amino acid sequence deduced from the cDNA exactly matched the 574 amino acid sequence of human serum cholinesterase, as previously determined by Edman degradation. Therefore, our clones represented cholinesterase rather than acetylcholinesterase. It was concluded that the amino acid sequences of cholinesterase from two different tissues, human brain and human serum, were identical. Hybridization of genomic DNA blots suggested that a single gene, or very few genes coded for cholinesterase

  20. On the applicability of brain reading for predictive human-machine interfaces in robotics.

    Science.gov (United States)

    Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

    2013-01-01

    The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors.

  1. On the applicability of brain reading for predictive human-machine interfaces in robotics.

    Directory of Open Access Journals (Sweden)

    Elsa Andrea Kirchner

    Full Text Available The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR, a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors.

  2. The Lifespan and Turnover of Microglia in the Human Brain

    Directory of Open Access Journals (Sweden)

    Pedro Réu

    2017-07-01

    Full Text Available The hematopoietic system seeds the CNS with microglial progenitor cells during the fetal period, but the subsequent cell generation dynamics and maintenance of this population have been poorly understood. We report that microglia, unlike most other hematopoietic lineages, renew slowly at a median rate of 28% per year, and some microglia last for more than two decades. Furthermore, we find no evidence for the existence of a substantial population of quiescent long-lived cells, meaning that the microglia population in the human brain is sustained by continuous slow turnover throughout adult life.

  3. Accelerated evolution of the ASPM gene controlling brain size begins prior to human brain expansion.

    Directory of Open Access Journals (Sweden)

    Natalay Kouprina

    2004-05-01

    Full Text Available Primary microcephaly (MCPH is a neurodevelopmental disorder characterized by global reduction in cerebral cortical volume. The microcephalic brain has a volume comparable to that of early hominids, raising the possibility that some MCPH genes may have been evolutionary targets in the expansion of the cerebral cortex in mammals and especially primates. Mutations in ASPM, which encodes the human homologue of a fly protein essential for spindle function, are the most common known cause of MCPH. Here we have isolated large genomic clones containing the complete ASPM gene, including promoter regions and introns, from chimpanzee, gorilla, orangutan, and rhesus macaque by transformation-associated recombination cloning in yeast. We have sequenced these clones and show that whereas much of the sequence of ASPM is substantially conserved among primates, specific segments are subject to high Ka/Ks ratios (nonsynonymous/synonymous DNA changes consistent with strong positive selection for evolutionary change. The ASPM gene sequence shows accelerated evolution in the African hominoid clade, and this precedes hominid brain expansion by several million years. Gorilla and human lineages show particularly accelerated evolution in the IQ domain of ASPM. Moreover, ASPM regions under positive selection in primates are also the most highly diverged regions between primates and nonprimate mammals. We report the first direct application of TAR cloning technology to the study of human evolution. Our data suggest that evolutionary selection of specific segments of the ASPM sequence strongly relates to differences in cerebral cortical size.

  4. Intrinsic Functional Connectivity in the Adult Brain and Success in Second-Language Learning.

    Science.gov (United States)

    Chai, Xiaoqian J; Berken, Jonathan A; Barbeau, Elise B; Soles, Jennika; Callahan, Megan; Chen, Jen-Kai; Klein, Denise

    2016-01-20

    There is considerable variability in an individual's ability to acquire a second language (L2) during adulthood. Using resting-state fMRI data acquired before training in English speakers who underwent a 12 week intensive French immersion training course, we investigated whether individual differences in intrinsic resting-state functional connectivity relate to a person's ability to acquire an L2. We focused on two key aspects of language processing--lexical retrieval in spontaneous speech and reading speed--and computed whole-brain functional connectivity from two regions of interest in the language network, namely the left anterior insula/frontal operculum (AI/FO) and the visual word form area (VWFA). Connectivity between the left AI/FO and left posterior superior temporal gyrus (STG) and between the left AI/FO and dorsal anterior cingulate cortex correlated positively with improvement in L2 lexical retrieval in spontaneous speech. Connectivity between the VWFA and left mid-STG correlated positively with improvement in L2 reading speed. These findings are consistent with the different language functions subserved by subcomponents of the language network and suggest that the human capacity to learn an L2 can be predicted by an individual's intrinsic functional connectivity within the language network. Significance statement: There is considerable variability in second-language learning abilities during adulthood. We investigated whether individual differences in intrinsic functional connectivity in the adult brain relate to success in second-language learning, using resting-state functional magnetic resonance imaging in English speakers who underwent a 12 week intensive French immersion training course. We found that pretraining functional connectivity within two different language subnetworks correlated strongly with learning outcome in two different language skills: lexical retrieval in spontaneous speech and reading speed. Our results suggest that the human

  5. Unmasking Language Lateralization in Human Brain Intrinsic Activity

    Science.gov (United States)

    McAvoy, Mark; Mitra, Anish; Coalson, Rebecca S.; d'Avossa, Giovanni; Keidel, James L.; Petersen, Steven E.; Raichle, Marcus E.

    2016-01-01

    Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal. PMID:25636911

  6. The structure of creative cognition in the human brain

    Directory of Open Access Journals (Sweden)

    Rex Eugene Jung

    2013-07-01

    Full Text Available Creativity is a vast construct, seemingly intractable to scientific inquiry – perhaps due to the vague concepts applied to the field of research. One attempt to limit the purview of creative cognition formulates the construct in terms of evolutionary constraints, namely that of blind variation and selective retention (BVSR. Behaviorally, one can limit the blind variation component to idea generation tests as manifested by measures of divergent thinking. The selective retention component can be represented by measures of convergent thinking, as represented by measures of remote associates. We summarize results from measures of creative cognition, correlated with structural neuroimaging measures including structural magnetic resonance imaging (sMRI, Diffusion Tensor Imaging (DTI, and proton magnetic resonance imaging (1H-MRS. We also review lesion studies, considered to be the gold standard of brain-behavioral studies. What emerges is a picture consistent with theories of disinhibitory brain features subserving creative cognition, as described previously (Martindale, 1981. We provide a perspective, involving aspects of the default mode network, which might provide a first approximation regarding how creative cognition might map on to the human brain.

  7. Mobile phone types and SAR characteristics of the human brain

    Science.gov (United States)

    Lee, Ae-Kyoung; Hong, Seon-Eui; Kwon, Jong-Hwa; Choi, Hyung-Do; Cardis, Elisabeth

    2017-04-01

    Mobile phones differ in terms of their operating frequency, outer shape, and form and location of the antennae, all of which affect the spatial distributions of their electromagnetic field and the level of electromagnetic absorption in the human head or brain. For this paper, the specific absorption rate (SAR) was calculated for four anatomical head models at different ages using 11 numerical phone models of different shapes and antenna configurations. The 11 models represent phone types accounting for around 86% of the approximately 1400 commercial phone models released into the Korean market since 2002. Seven of the phone models selected have an internal dual-band antenna, and the remaining four possess an external antenna. Each model was intended to generate an average absorption level equivalent to that of the same type of commercial phone model operating at the maximum available output power. The 1 g peak spatial SAR and ipsilateral and contralateral brain-averaged SARs were reported for all 11 phone models. The effects of the phone type, phone position, operating frequency, and age of head models on the brain SAR were comprehensively determined.

  8. Amplifying human ability through autonomics and machine learning in IMPACT

    Science.gov (United States)

    Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

    2017-05-01

    Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

  9. Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness

    DEFF Research Database (Denmark)

    Bozek, Katarzyna; Wei, Yuning; Yan, Zheng

    2014-01-01

    Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees,...

  10. Contribution Of Brain Tissue Oxidative Damage In Hypothyroidism-associated Learning and Memory Impairments

    Directory of Open Access Journals (Sweden)

    Yousef Baghcheghi

    2017-01-01

    Full Text Available The brain is a critical target organ for thyroid hormones, and modifications in memory and cognition happen with thyroid dysfunction. The exact mechanisms underlying learning and memory impairments due to hypothyroidism have not been understood yet. Therefore, this review was aimed to compress the results of previous studies which have examined the contribution of brain tissues oxidative damage in hypothyroidism-associated learning and memory impairments.

  11. Spectral Transfer Learning using Information Geometry for a User-Independent Brain-Computer Interface

    OpenAIRE

    Nicholas Roy Waytowich; Nicholas Roy Waytowich; Vernon Lawhern; Vernon Lawhern; Addison Bohannon; Addison Bohannon; Kenneth Ball; Brent Lance

    2016-01-01

    Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry and recreation. However, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter- individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this p...

  12. Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

    OpenAIRE

    Waytowich, Nicholas R.; Lawhern, Vernon J.; Bohannon, Addison W.; Ball, Kenneth R.; Lance, Brent J.

    2016-01-01

    Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this p...

  13. Using Brain Electrical Activity Mapping to Diagnose Learning Disabilities.

    Science.gov (United States)

    Torello, Michael, W.; Duffy, Frank H.

    1985-01-01

    Cognitive neuroscience assumes that measurement of brain electrical activity should relate to cognition. Brain Electrical Activity Mapping (BEAM), a non-invasive technique, is used to record changes in activity from one brain area to another and is 80 to 90 percent successful in classifying subjects as dyslexic or normal. (MT)

  14. Correlating learning and memory improvements to long-term potentiation in patients with brain injury

    Institute of Scientific and Technical Information of China (English)

    Xingfu Peng; Qian Yu

    2008-01-01

    BACKGROUND:Brain injury patients often exhibit learning and memory functional deficits.Long-term potentiation(LTP)is a representative index for studying learning and memory cellular models; the LTP index correlates to neural plasticity. OBJECTIVE:This study was designed to investigate correlations of learning and memory functions to LTP in brain injury patients,and to summarize the research advancements in mechanisms underlying brain functional improvements after rehabilitation intervention. RETRIEVAL STRATEGY:Using the terms "brain injuries,rehabilitation,learning and memory,long-term potentiation",manuscripts that were published from 2000-2007 were retrieved from the PubMed database.At the same time,manuscripts published from 2000-2007 were also retrieved from the Database of Chinese Scientific and Technical Periodicals with the same terms in the Chinese language.A total of 64 manuscripts were obtained and primarily screened.Inclusion criteria:studies on learning and memory,as well as LTP in brain injury patients,and studies focused on the effects of rehabilitation intervention on the two indices; studies that were recently published or in high-impact journals.Exclusion criteria:repetitive studies.LITERATURE EVALUATION:The included manuscripts primarily focused on correlations between learning and memory and LTP,the effects of brain injury on learning and memory,as well as LTP,and the effects of rehabilitation intervention on learning and memory after brain injury.The included 39 manuscripts were clinical,basic experimental,or review studies. DATA SYNTHESIS:Learning and memory closely correlates to LTP.The neurobiological basis of learning and memory is central nervous system plasticity,which involves neural networks,neural circuits,and synaptic connections,in particular,synaptic plasticity.LTP is considered to be an ideal model for studying synaptic plasticity,and it is also a classic model for studying neural plasticity of learning and memory.Brain injury

  15. Telomere length modulation in human astroglial brain tumors.

    Directory of Open Access Journals (Sweden)

    Domenico La Torre

    Full Text Available BACKGROUND: Telomeres alteration during carcinogenesis and tumor progression has been described in several cancer types. Telomeres length is stabilized by telomerase (h-TERT and controlled by several proteins that protect telomere integrity, such as the Telomere Repeat-binding Factor (TRF 1 and 2 and the tankyrase-poli-ADP-ribose polymerase (TANKs-PARP complex. OBJECTIVE: To investigate telomere dysfunction in astroglial brain tumors we analyzed telomeres length, telomerase activity and the expression of a panel of genes controlling the length and structure of telomeres in tissue samples obtained in vivo from astroglial brain tumors with different grade of malignancy. MATERIALS AND METHODS: Eight Low Grade Astrocytomas (LGA, 11 Anaplastic Astrocytomas (AA and 11 Glioblastoma Multiforme (GBM samples were analyzed. Three samples of normal brain tissue (NBT were used as controls. Telomeres length was assessed through Southern Blotting. Telomerase activity was evaluated by a telomere repeat amplification protocol (TRAP assay. The expression levels of TRF1, TRF2, h-TERT and TANKs-PARP complex were determined through Immunoblotting and RT-PCR. RESULTS: LGA were featured by an up-regulation of TRF1 and 2 and by shorter telomeres. Conversely, AA and GBM were featured by a down-regulation of TRF1 and 2 and an up-regulation of both telomerase and TANKs-PARP complex. CONCLUSIONS: In human astroglial brain tumours, up-regulation of TRF1 and TRF2 occurs in the early stages of carcinogenesis determining telomeres shortening and genomic instability. In a later stage, up-regulation of PARP-TANKs and telomerase activation may occur together with an ADP-ribosylation of TRF1, causing a reduced ability to bind telomeric DNA, telomeres elongation and tumor malignant progression.

  16. The brain's silent messenger: using selective attention to decode human thought for brain-based communication.

    Science.gov (United States)

    Naci, Lorina; Cusack, Rhodri; Jia, Vivian Z; Owen, Adrian M

    2013-05-29

    The interpretation of human thought from brain activity, without recourse to speech or action, is one of the most provoking and challenging frontiers of modern neuroscience. In particular, patients who are fully conscious and awake, yet, due to brain damage, are unable to show any behavioral responsivity, expose the limits of the neuromuscular system and the necessity for alternate forms of communication. Although it is well established that selective attention can significantly enhance the neural representation of attended sounds, it remains, thus far, untested as a response modality for brain-based communication. We asked whether its effect could be reliably used to decode answers to binary (yes/no) questions. Fifteen healthy volunteers answered questions (e.g., "Do you have brothers or sisters?") in the fMRI scanner, by selectively attending to the appropriate word ("yes" or "no"). Ninety percent of the answers were decoded correctly based on activity changes within the attention network. The majority of volunteers conveyed their answers with less than 3 min of scanning, suggesting that this technique is suited for communication in a reasonable amount of time. Formal comparison with the current best-established fMRI technique for binary communication revealed improved individual success rates and scanning times required to detect responses. This novel fMRI technique is intuitive, easy to use in untrained participants, and reliably robust within brief scanning times. Possible applications include communication with behaviorally nonresponsive patients.

  17. Selectively altering belief formation in the human brain

    Science.gov (United States)

    Sharot, Tali; Kanai, Ryota; Marston, David; Korn, Christoph W.; Rees, Geraint; Dolan, Raymond J.

    2012-01-01

    Humans form beliefs asymmetrically; we tend to discount bad news but embrace good news. This reduced impact of unfavorable information on belief updating may have important societal implications, including the generation of financial market bubbles, ill preparedness in the face of natural disasters, and overly aggressive medical decisions. Here, we selectively improved people’s tendency to incorporate bad news into their beliefs by disrupting the function of the left (but not right) inferior frontal gyrus using transcranial magnetic stimulation, thereby eliminating the engrained “good news/bad news effect.” Our results provide an instance of how selective disruption of regional human brain function paradoxically enhances the ability to incorporate unfavorable information into beliefs of vulnerability. PMID:23011798

  18. Neural correlates of learning in an electrocorticographic motor-imagery brain-computer interface

    Science.gov (United States)

    Blakely, Tim M.; Miller, Kai J.; Rao, Rajesh P. N.; Ojemann, Jeffrey G.

    2014-01-01

    Human subjects can learn to control a one-dimensional electrocorticographic (ECoG) brain-computer interface (BCI) using modulation of primary motor (M1) high-gamma activity (signal power in the 75–200 Hz range). However, the stability and dynamics of the signals over the course of new BCI skill acquisition have not been investigated. In this study, we report 3 characteristic periods in evolution of the high-gamma control signal during BCI training: initial, low task accuracy with corresponding low power modulation in the gamma spectrum, followed by a second period of improved task accuracy with increasing average power separation between activity and rest, and a final period of high task accuracy with stable (or decreasing) power separation and decreasing trial-to-trial variance. These findings may have implications in the design and implementation of BCI control algorithms. PMID:25599079

  19. Hypnosis and imaging of the living human brain.

    Science.gov (United States)

    Landry, Mathieu; Raz, Amir

    2015-01-01

    Over more than two decades, studies using imaging techniques of the living human brain have begun to explore the neural correlates of hypnosis. The collective findings provide a gripping, albeit preliminary, account of the underlying neurobiological mechanisms involved in hypnotic phenomena. While substantial advances lend support to different hypotheses pertaining to hypnotic modulation of attention, control, and monitoring processes, the complex interactions among the many mediating variables largely hinder our ability to isolate robust commonalities across studies. The present account presents a critical integrative synthesis of neuroimaging studies targeting hypnosis as a function of suggestion. Specifically, hypnotic induction without task-specific suggestion is examined, as well as suggestions concerning sensation and perception, memory, and ideomotor response. The importance of carefully designed experiments is highlighted to better tease apart the neural correlates that subserve hypnotic phenomena. Moreover, converging findings intimate that hypnotic suggestions seem to induce specific neural patterns. These observations propose that suggestions may have the ability to target focal brain networks. Drawing on evidence spanning several technological modalities, neuroimaging studies of hypnosis pave the road to a more scientific understanding of a dramatic, yet largely evasive, domain of human behavior.

  20. Mapping human brain networks with cortico-cortical evoked potentials

    Science.gov (United States)

    Keller, Corey J.; Honey, Christopher J.; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D.

    2014-01-01

    The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. PMID:25180306

  1. Endogenous neurogenesis in the human brain following cerebral infarction.

    Science.gov (United States)

    Minger, Stephen L; Ekonomou, Antigoni; Carta, Eloisa M; Chinoy, Amish; Perry, Robert H; Ballard, Clive G

    2007-01-01

    Increased endogenous neurogenesis has a significant regenerative role in many experimental models of cerebrovascular diseases, but there have been very few studies in humans. We therefore examined whether there was evidence of altered endogenous neurogenesis in an 84-year-old patient who suffered a cerebrovascular accident 1 week prior to death. Using antibodies that specifically label neural stem/neural progenitor cells, we examined the presence of immunopositive cells around and distant from the infarcted area, and compared this with a control, age-matched individual. Interestingly, a large number of neural stem cells, vascular endothelial growth factor-immunopositive cells and new blood vessels were observed only around the region of infarction, and none in the corresponding brain areas of the healthy control. In addition, an increased number of neural stem cells was observed in the neurogenic region of the lateral ventricle wall. Our results suggest increased endogenous neurogenesis associated with neovascularization and migration of newly-formed cells towards a region of cerebrovascular damage in the adult human brain and highlight possible mechanisms underlying this process.

  2. Flow distributions and spatial correlations in human brain capillary networks

    Science.gov (United States)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  3. Gaze-and-brain-controlled interfaces for human-computer and human-robot interaction

    Directory of Open Access Journals (Sweden)

    Shishkin S. L.

    2017-09-01

    Full Text Available Background. Human-machine interaction technology has greatly evolved during the last decades, but manual and speech modalities remain single output channels with their typical constraints imposed by the motor system’s information transfer limits. Will brain-computer interfaces (BCIs and gaze-based control be able to convey human commands or even intentions to machines in the near future? We provide an overview of basic approaches in this new area of applied cognitive research. Objective. We test the hypothesis that the use of communication paradigms and a combination of eye tracking with unobtrusive forms of registering brain activity can improve human-machine interaction. Methods and Results. Three groups of ongoing experiments at the Kurchatov Institute are reported. First, we discuss the communicative nature of human-robot interaction, and approaches to building a more e cient technology. Specifically, “communicative” patterns of interaction can be based on joint attention paradigms from developmental psychology, including a mutual “eye-to-eye” exchange of looks between human and robot. Further, we provide an example of “eye mouse” superiority over the computer mouse, here in emulating the task of selecting a moving robot from a swarm. Finally, we demonstrate a passive, noninvasive BCI that uses EEG correlates of expectation. This may become an important lter to separate intentional gaze dwells from non-intentional ones. Conclusion. The current noninvasive BCIs are not well suited for human-robot interaction, and their performance, when they are employed by healthy users, is critically dependent on the impact of the gaze on selection of spatial locations. The new approaches discussed show a high potential for creating alternative output pathways for the human brain. When support from passive BCIs becomes mature, the hybrid technology of the eye-brain-computer (EBCI interface will have a chance to enable natural, fluent, and the

  4. ''Brain-science and education''. Towards human security and well-being

    International Nuclear Information System (INIS)

    Koizumi, Hideaki

    2005-01-01

    This lecture discusses concepts of learning and education that have been expressed in terms of the viewpoint of natural science, and proposes a new way of studying learning and education based on functional brain imaging such as fMRI, MEG, and OT (Optical Topography). From a biological viewpoint, they are related to brain development because the brain is an adaptable information processor that is open to environmental stimuli. Stimuli cause new neuronal connections to form, which allow better adaptation to the environment. Thus, education should be designed to guide and inspire the construction of the basic architecture for information processing in the brain by preparing and controlling the input stimuli given to the learners. Education is the process in which learning is guided to provide an optimal environment. This new approach to study of learning and education is called brain science and education.'' (S. Ohno)

  5. Multimodal communication in animals, humans and robots: an introduction to perspectives in brain-inspired informatics.

    Science.gov (United States)

    Wermter, S; Page, M; Knowles, M; Gallese, V; Pulvermüller, F; Taylor, J

    2009-03-01

    Recent years have seen convergence in research on brain mechanisms and neurocomputational approaches, culminating in the creation of a new generation of robots whose artificial "brains" respect neuroscience principles and whose "cognitive" systems venture into higher cognitive domains such as planning and action sequencing, complex object and concept processing, and language. The present article gives an overview of selected projects in this general multidisciplinary field. The work reviewed centres on research funded by the EU in the context of the New and Emergent Science and Technology, NEST, funding scheme highlighting the topic "What it means to be human". Examples of such projects include learning by imitation (Edici project), examining the origin of human rule-based reasoning (Far), studying the neural origins of language (Neurocom), exploring the evolutionary origins of the human mind (Pkb140404), researching into verbal and non-verbal communication (Refcom), using and interpreting signs (Sedsu), characterising human language by structural complexity (Chlasc), and representing abstract concepts (Abstract). Each of the communication-centred research projects revealed individual insights; however, there had been little overall analysis of results and hypotheses. In the Specific Support Action Nestcom, we proposed to analyse some NEST projects focusing on the central question "What it means to communicate" and to review, understand and integrate the results of previous communication-related research, in order to develop and communicate multimodal experimental hypotheses for investigation by future projects. The present special issue includes a range of papers on the interplay between neuroinformatics, brain science and robotics in the general area of higher cognitive functions and multimodal communication. These papers extend talks given at the NESTCOM workshops, at ICANN (http://www.his.sunderland.ac.uk/nestcom/workshop/icann.html) in Porto and at the first

  6. The Radical Plasticity Thesis: How the Brain Learns to be Conscious.

    Science.gov (United States)

    Cleeremans, Axel

    2011-01-01

    In this paper, I explore the idea that consciousness is something that the brain learns to do rather than an intrinsic property of certain neural states and not others. Starting from the idea that neural activity is inherently unconscious, the question thus becomes: How does the brain learn to be conscious? I suggest that consciousness arises as a result of the brain's continuous attempts at predicting not only the consequences of its actions on the world and on other agents, but also the consequences of activity in one cerebral region on activity in other regions. By this account, the brain continuously and unconsciously learns to redescribe its own activity to itself, so developing systems of meta-representations that characterize and qualify the target first-order representations. Such learned redescriptions, enriched by the emotional value associated with them, form the basis of conscious experience. Learning and plasticity are thus central to consciousness, to the extent that experiences only occur in experiencers that have learned to know they possess certain first-order states and that have learned to care more about certain states than about others. This is what I call the "Radical Plasticity Thesis." In a sense thus, this is the enactive perspective, but turned both inwards and (further) outwards. Consciousness involves "signal detection on the mind"; the conscious mind is the brain's (non-conceptual, implicit) theory about itself. I illustrate these ideas through neural network models that simulate the relationships between performance and awareness in different tasks.

  7. The Radical Plasticity Thesis: How the brain learns to be conscious

    Directory of Open Access Journals (Sweden)

    Axel eCleeremans

    2011-05-01

    Full Text Available In this paper, I explore the idea that consciousness is something that the brain learns to do rather than an intrinsic property of certain neural states and not others. Starting from the idea that neural activity is inherently unconscious, the question thus becomes: How does the brain learn to be conscious? I suggest that consciousness arises as a result of the brain's continuous attempts at predicting not only the consequences of its actions on the world and on other agents, but also the consequences of activity in one cerebral region on activity in other regions. By this account, the brain continuously and unconsciously learns to redescribe its own activity to itself, so developing systems of meta-representations that characterise and qualify the target first-order representations. Such learned redescriptions, enriched by the emotional value associated with them, form the basis of conscious experience. Learning and plasticity are thus central to consciousness, to the extent that experiences only occur in experiencers that have learned to know they possess certain first-order states and that have learned to care more about certain states than about others. This is what I call the Radical Plasticity Thesis. In a sense thus, this is the enactive perspective, but turned both inwards and (further outwards. Consciousness involves signal detection on the mind; the mind is the brain's (non-conceptual, implicit theory about itself. I illustrate these ideas through neural network models that simulate the relationships between performance and awareness in different tasks.

  8. Teaching About "Brain and Learning" in High School Biology Classes: Effects on Teachers' Knowledge and Students' Theory of Intelligence.

    Science.gov (United States)

    Dekker, Sanne; Jolles, Jelle

    2015-01-01

    This study evaluated a new teaching module about "Brain and Learning" using a controlled design. The module was implemented in high school biology classes and comprised three lessons: (1) brain processes underlying learning; (2) neuropsychological development during adolescence; and (3) lifestyle factors that influence learning performance. Participants were 32 biology teachers who were interested in "Brain and Learning" and 1241 students in grades 8-9. Teachers' knowledge and students' beliefs about learning potential were examined using online questionnaires. Results indicated that before intervention, biology teachers were significantly less familiar with how the brain functions and develops than with its structure and with basic neuroscientific concepts (46 vs. 75% correct answers). After intervention, teachers' knowledge of "Brain and Learning" had significantly increased (64%), and more students believed that intelligence is malleable (incremental theory). This emphasizes the potential value of a short teaching module, both for improving biology teachers' insights into "Brain and Learning," and for changing students' beliefs about intelligence.

  9. Long distance communication in the human brain: timing constraints for inter-hemispheric synchrony and the origin of brain lateralization

    Directory of Open Access Journals (Sweden)

    FRANCISCO ABOITIZ

    2003-01-01

    Full Text Available Analysis of corpus callosum fiber composition reveals that inter-hemispheric transmission time may put constraints on the development of inter-hemispheric synchronic ensembles, especially in species with large brains like humans. In order to overcome this limitation, a subset of large-diameter callosal fibers are specialized for fast inter-hemispheric transmission, particularly in large-brained species. Nevertheless, the constraints on fast inter-hemispheric communication in large-brained species can somehow contribute to the development of ipsilateral, intrahemispheric networks, which might promote the development of brain lateralization.

  10. The role of positron emission tomography in neuropharmacology in the living human brain and drug development

    International Nuclear Information System (INIS)

    Yanai, Kazuhiko

    1999-01-01

    Neuroimaging is a powerful and innovative tool for studying the pathology of psychiatric and neurological diseases and, more recently, for studying the drugs used in their treatment. Technological advances in imaging have made it possible to noninvasively extract information from the human brain regarding a drug's mechanism and site of action. Until now, our understanding of human brain pharmacology has depended primarily on indirect assessments or models derived from animal studies. However, the advent of multiple techniques for human brain imaging allows researchers to focus directly on human pharmacology and brain function. In this review article, our PET studies on the histaminergic neuron system were presented as an example. We have developed and used the PET techniques for 10 years in order to examine the H 1 receptors in the living human brain. This review outlines available PET techniques and examine how these various methods have already been applied to the drug development process and neuropharmacology in the living human brain. (author)

  11. Differences in distribution and regulation of astrocytic aquaporin-4 in human and rat hydrocephalic brain

    DEFF Research Database (Denmark)

    Skjolding, Anders Daehli; Holst, Anders Vedel; Broholm, Helle

    2013-01-01

    findings to human pathophysiology. This study compares expression of aquaporin-4 in hydrocephalic human brain with human controls and hydrocephalic rat brain. Methods:  Cortical biopsies from patients with chronic hydrocephalus (n=29) were sampled secondary to planned surgical intervention. Aquaporin-4...

  12. A digital interactive human brain atlas based on Chinese visible human datasets for anatomy teaching.

    Science.gov (United States)

    Li, Qiyu; Ran, Xu; Zhang, Shaoxiang; Tan, Liwen; Qiu, Mingguo

    2014-01-01

    As we know, the human brain is one of the most complicated organs in the human body, which is the key and difficult point in neuroanatomy and sectional anatomy teaching. With the rapid development and extensive application of imaging technology in clinical diagnosis, doctors are facing higher and higher requirement on their anatomy knowledge. Thus, to cultivate medical students to meet the needs of medical development today and to improve their ability to read and understand radiographic images have become urgent challenges for the medical teachers. In this context, we developed a digital interactive human brain atlas based on the Chinese visible human datasets for anatomy teaching (available for free download from http://www.chinesevisiblehuman.com/down/DHBA.rar). The atlas simultaneously provides views in all 3 primary planes of section. The main structures of the human brain have been anatomically labeled in all 3 views. It is potentially useful for anatomy browsing, user self-testing, and automatic student assessment. In a word, it is interactive, 3D, user friendly, and free of charge, which can provide a new, intuitive means for anatomy teaching.

  13. Human Development XII: A Theory for the Structure and Function of the Human Brain

    Directory of Open Access Journals (Sweden)

    Søren Ventegodt

    2008-01-01

    Full Text Available The human brain is probably the most complicated single structure in the biological universe. The cerebral cortex that is traditionally connected with consciousness is extremely complex. The brain contains approximately 1,000,000 km of nerve fibers, indicating its enormous complexity and which makes it difficult for scientists to reveal the function of the brain. In this paper, we propose a new model for brain functions, i.e., information-guided self-organization of neural patterns, where information is provided from the abstract wholeness of the biophysical system of an organism (often called the true self, or the “soul””. We present a number of arguments in favor of this model that provide self-conscious control over the thought process or cognition. Our arguments arise from analyzing experimental data from different research fields: histology, anatomy, electroencephalography (EEG, cerebral blood flow, neuropsychology, evolutionary studies, and mathematics. We criticize the popular network theories as the consequence of a simplistic, mechanical interpretation of reality (philosophical materialism applied to the brain. We demonstrate how viewing brain functions as information-guided self-organization of neural patterns can explain the structure of conscious mentation; we seem to have a dual hierarchical representation in the cerebral cortex: one for sensation-perception and one for will-action. The model explains many of our unique mental abilities to think, memorize, associate, discriminate, and make abstractions. The presented model of the conscious brain also seems to be able to explain the function of the simpler brains, such as those of insects and hydra.

  14. Activation analysis study on subcellular distribution of trace elements in human brain tumor

    International Nuclear Information System (INIS)

    Zheng Jian; Zhuan Guisun; Wang Yongji; Dong Mo; Zhang Fulin

    1992-01-01

    The concentrations of up to 11 elements in subcellular fractions of human brain (normal and malignant tumor) have been determined by a combination of gradient centrifugation and INAA methods. Samples of human brain were homogenized in a glass homogenizer tube, the homogenate was separated into nuclei, mitochondrial, myelin, synaptosome fractions, and these fractions were then analyzed using the INAA method. The discussions of elemental subcelleular distributions in human brain malignant tumor are presented in this paper. (author) 11 refs.; 2 figs.; 4 tabs

  15. Machine Learning.

    Science.gov (United States)

    Kirrane, Diane E.

    1990-01-01

    As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

  16. Engaging ESP Students with Brain-Based Learning for Improved Listening Skills, Vocabulary Retention and Motivation

    Science.gov (United States)

    Salem, Ashraf Atta Mohamed Safein

    2017-01-01

    The concept of teaching and learning has changed drastically over the past few years by the virtue of both research results carried out in the fields of second/foreign language learning and acquisition. Of all these researches, findings related to the brain structure and functions in cooperation with cognitive aspects of the education process,…

  17. Brain-Wide Maps of "Fos" Expression during Fear Learning and Recall

    Science.gov (United States)

    Cho, Jin-Hyung; Rendall, Sam D.; Gray, Jesse M.

    2017-01-01

    "Fos" induction during learning labels neuronal ensembles in the hippocampus that encode a specific physical environment, revealing a memory trace. In the cortex and other regions, the extent to which "Fos" induction during learning reveals specific sensory representations is unknown. Here we generate high-quality brain-wide…

  18. Reliability of the Motor Learning Strategy Rating Instrument for Children and Youth with Acquired Brain Injury

    Science.gov (United States)

    Kamath, Trishna; Pfeifer, Megan; Banerjee-Guenette, Priyanka; Hunter, Theresa; Ito, Julia; Salbach, Nancy M.; Wright, Virginia; Levac, Danielle

    2012-01-01

    Purpose: To evaluate reliability and feasibility of the Motor Learning Strategy Rating Instrument (MLSRI) in children with acquired brain injury (ABI). The MLSRI quantifies the extent to which motor learning strategies (MLS) are used within physiotherapy (PT) interventions. Methods: PT sessions conducted by ABI team physiotherapists with a…

  19. Implicit Memory Influences on Metamemory during Verbal Learning after Traumatic Brain Injury

    Science.gov (United States)

    Ramanathan, Pradeep; Kennedy, Mary R. T.; Marsolek, Chad J.

    2014-01-01

    Purpose: Prior research has shown that individuals with traumatic brain injury (TBI) may be overconfident in their judgments of learning (JOLs; online measures of self-monitoring of learning and memory). JOLs had been presumed to be driven by explicit processes, but recent research has also revealed implicit memory involvement. Given that implicit…

  20. Strategic Learning in Youth with Traumatic Brain Injury: Evidence for Stall in Higher-Order Cognition

    Science.gov (United States)

    Gamino, Jacquelyn F.; Chapman, Sandra B.; Cook, Lori G.

    2009-01-01

    Little is known about strategic learning ability in preteens and adolescents with traumatic brain injury (TBI). Strategic learning is the ability to combine and synthesize details to form abstracted gist-based meanings, a higher-order cognitive skill associated with frontal lobe functions and higher classroom performance. Summarization tasks were…

  1. Greasing the Skids of the Musical Mind: Connecting Music Learning to Mind Brain Education

    Science.gov (United States)

    Bugos, Jennifer A.

    2015-01-01

    Researchers suggest that musical training prepares the mind for learning; however, there are many obstacles to the implementation of research to practice in music education. The purpose of this article is to apply key principles of mind brain education to music education and to evaluate how music prepares the mind for learning. Practical teaching…

  2. Sleeping brain, learning brain. The role of sleep for memory systems.

    Science.gov (United States)

    Peigneux, P; Laureys, S; Delbeuck, X; Maquet, P

    2001-12-21

    The hypothesis that sleep participates in the consolidation of recent memory traces has been investigated using four main paradigms: (1) effects of post-training sleep deprivation on memory consolidation, (2) effects of learning on post-training sleep, (3) effects of within sleep stimulation on the sleep pattern and on overnight memories, and (4) re-expression of behavior-specific neural patterns during post-training sleep. These studies convincingly support the idea that sleep is deeply involved in memory functions in humans and animals. However, the available data still remain too scarce to confirm or reject unequivocally the recently upheld hypothesis that consolidations of non-declarative and declarative memories are respectively dependent upon REM and NREM sleep processes.

  3. Matrix metalloproteinase (MMP) 9 transcription in mouse brain induced by fear learning.

    Science.gov (United States)

    Ganguly, Krishnendu; Rejmak, Emilia; Mikosz, Marta; Nikolaev, Evgeni; Knapska, Ewelina; Kaczmarek, Leszek

    2013-07-19

    Memory formation requires learning-based molecular and structural changes in neurons, whereas matrix metalloproteinase (MMP) 9 is involved in the synaptic plasticity by cleaving extracellular matrix proteins and, thus, is associated with learning processes in the mammalian brain. Because the mechanisms of MMP-9 transcription in the brain are poorly understood, this study aimed to elucidate regulation of MMP-9 gene expression in the mouse brain after fear learning. We show here that contextual fear conditioning markedly increases MMP-9 transcription, followed by enhanced enzymatic levels in the three major brain structures implicated in fear learning, i.e. the amygdala, hippocampus, and prefrontal cortex. To reveal the role of AP-1 transcription factor in MMP-9 gene expression, we have used reporter gene constructs with specifically mutated AP-1 gene promoter sites. The constructs were introduced into the medial prefrontal cortex of neonatal mouse pups by electroporation, and the regulation of MMP-9 transcription was studied after contextual fear conditioning in the adult animals. Specifically, -42/-50- and -478/-486-bp AP-1 binding motifs of the mouse MMP-9 promoter sequence have been found to play a major role in MMP-9 gene activation. Furthermore, increases in MMP-9 gene promoter binding by the AP-1 transcription factor proteins c-Fos and c-Jun have been demonstrated in all three brain structures under investigation. Hence, our results suggest that AP-1 acts as a positive regulator of MMP-9 transcription in the brain following fear learning.

  4. Deep brain stimulation, brain maps and personalized medicine: lessons from the human genome project.

    Science.gov (United States)

    Fins, Joseph J; Shapiro, Zachary E

    2014-01-01

    Although the appellation of personalized medicine is generally attributed to advanced therapeutics in molecular medicine, deep brain stimulation (DBS) can also be so categorized. Like its medical counterpart, DBS is a highly personalized intervention that needs to be tailored to a patient's individual anatomy. And because of this, DBS like more conventional personalized medicine, can be highly specific where the object of care is an N = 1. But that is where the similarities end. Besides their differing medical and surgical provenances, these two varieties of personalized medicine have had strikingly different impacts. The molecular variant, though of a more recent vintage has thrived and is experiencing explosive growth, while DBS still struggles to find a sustainable therapeutic niche. Despite its promise, and success as a vetted treatment for drug resistant Parkinson's Disease, DBS has lagged in broadening its development, often encountering regulatory hurdles and financial barriers necessary to mount an adequate number of quality trials. In this paper we will consider why DBS-or better yet neuromodulation-has encountered these challenges and contrast this experience with the more successful advance of personalized medicine. We will suggest that personalized medicine and DBS's differential performance can be explained as a matter of timing and complexity. We believe that DBS has struggled because it has been a journey of scientific exploration conducted without a map. In contrast to molecular personalized medicine which followed the mapping of the human genome and the Human Genome Project, DBS preceded plans for the mapping of the human brain. We believe that this sequence has given personalized medicine a distinct advantage and that the fullest potential of DBS will be realized both as a cartographical or electrophysiological probe and as a modality of personalized medicine.

  5. From "Where" to "What": Distributed Representations of Brand Associations in the Human Brain.

    Science.gov (United States)

    Chen, Yu-Ping; Nelson, Leif D; Hsu, Ming

    2015-08-01

    Considerable attention has been given to the notion that there exists a set of human-like characteristics associated with brands, referred to as brand personality. Here we combine newly available machine learning techniques with functional neuroimaging data to characterize the set of processes that give rise to these associations. We show that brand personality traits can be captured by the weighted activity across a widely distributed set of brain regions previously implicated in reasoning, imagery, and affective processing. That is, as opposed to being constructed via reflective processes, brand personality traits appear to exist a priori inside the minds of consumers, such that we were able to predict what brand a person is thinking about based solely on the relationship between brand personality associations and brain activity. These findings represent an important advance in the application of neuroscientific methods to consumer research, moving from work focused on cataloguing brain regions associated with marketing stimuli to testing and refining mental constructs central to theories of consumer behavior.

  6. Using repetitive transcranial magnetic stimulation to study the underlying neural mechanisms of human motor learning and memory.

    Science.gov (United States)

    Censor, Nitzan; Cohen, Leonardo G

    2011-01-01

    In the last two decades, there has been a rapid development in the research of the physiological brain mechanisms underlying human motor learning and memory. While conventional memory research performed on animal models uses intracellular recordings, microfusion of protein inhibitors to specific brain areas and direct induction of focal brain lesions, human research has so far utilized predominantly behavioural approaches and indirect measurements of neural activity. Repetitive transcranial magnetic stimulation (rTMS), a safe non-invasive brain stimulation technique, enables the study of the functional role of specific cortical areas by evaluating the behavioural consequences of selective modulation of activity (excitation or inhibition) on memory generation and consolidation, contributing to the understanding of the neural substrates of motor learning. Depending on the parameters of stimulation, rTMS can also facilitate learning processes, presumably through purposeful modulation of excitability in specific brain regions. rTMS has also been used to gain valuable knowledge regarding the timeline of motor memory formation, from initial encoding to stabilization and long-term retention. In this review, we summarize insights gained using rTMS on the physiological and neural mechanisms of human motor learning and memory. We conclude by suggesting possible future research directions, some with direct clinical implications.

  7. Structural Graphical Lasso for Learning Mouse Brain Connectivity

    KAUST Repository

    Yang, Sen

    2015-08-07

    Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability of high-resolution brain imaging data. Sparse inverse covariance estimation with lasso and group lasso penalty has been demonstrated to be a powerful approach to discover brain networks. Motivated by the hierarchical structure of the brain networks, we consider the problem of estimating a graphical model with tree-structural regularization in this paper. The regularization encourages the graphical model to exhibit a brain-like structure. Specifically, in this hierarchical structure, hundreds of thousands of voxels serve as the leaf nodes of the tree. A node in the intermediate layer represents a region formed by voxels in the subtree rooted at that node. The whole brain is considered as the root of the tree. We propose to apply the tree-structural regularized graphical model to estimate the mouse brain network. However, the dimensionality of whole-brain data, usually on the order of hundreds of thousands, poses significant computational challenges. Efficient algorithms that are capable of estimating networks from high-dimensional data are highly desired. To address the computational challenge, we develop a screening rule which can quickly identify many zero blocks in the estimated graphical model, thereby dramatically reducing the computational cost of solving the proposed model. It is based on a novel insight on the relationship between screening and the so-called proximal operator that we first establish in this paper. We perform experiments on both synthetic data and real data from the Allen Developing Mouse Brain Atlas; results demonstrate the effectiveness and efficiency of the proposed approach.

  8. Movement-related theta rhythm in humans: coordinating self-directed hippocampal learning.

    Directory of Open Access Journals (Sweden)

    Raphael Kaplan

    Full Text Available The hippocampus is crucial for episodic or declarative memory and the theta rhythm has been implicated in mnemonic processing, but the functional contribution of theta to memory remains the subject of intense speculation. Recent evidence suggests that the hippocampus might function as a network hub for volitional learning. In contrast to human experiments, electrophysiological recordings in the hippocampus of behaving rodents are dominated by theta oscillations reflecting volitional movement, which has been linked to spatial exploration and encoding. This literature makes the surprising cross-species prediction that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. We examined the links between theta, spatial exploration, and memory encoding by designing an interactive human spatial navigation paradigm combined with multimodal neuroimaging. We used both non-invasive whole-head Magnetoencephalography (MEG to look at theta oscillations and Functional Magnetic Resonance Imaging (fMRI to look at brain regions associated with volitional movement and learning. We found that theta power increases during the self-initiation of virtual movement, additionally correlating with subsequent memory performance and environmental familiarity. Performance-related hippocampal theta increases were observed during a static pre-navigation retrieval phase, where planning for subsequent navigation occurred. Furthermore, periods of the task showing movement-related theta increases showed decreased fMRI activity in the parahippocampus and increased activity in the hippocampus and other brain regions that strikingly overlap with the previously observed volitional learning network (the reverse pattern was seen for stationary periods. These fMRI changes also correlated with participant's performance. Our findings suggest that the human hippocampal theta rhythm supports memory by coordinating

  9. The functional connectivity landscape of the human brain.

    Directory of Open Access Journals (Sweden)

    Bratislav Mišić

    Full Text Available Functional brain networks emerge and dissipate over a primarily static anatomical foundation. The dynamic basis of these networks is inter-regional communication involving local and distal regions. It is assumed that inter-regional distances play a pivotal role in modulating network dynamics. Using three different neuroimaging modalities, 6 datasets were evaluated to determine whether experimental manipulations asymmetrically affect functional relationships based on the distance between brain regions in human participants. Contrary to previous assumptions, here we show that short- and long-range connections are equally likely to strengthen or weaken in response to task demands. Additionally, connections between homotopic areas are the most stable and less likely to change compared to any other type of connection. Our results point to a functional connectivity landscape characterized by fluid transitions between local specialization and global integration. This ability to mediate functional properties irrespective of spatial distance may engender a diverse repertoire of cognitive processes when faced with a dynamic environment.

  10. Giovanni Aldini: from animal electricity to human brain stimulation.

    Science.gov (United States)

    Parent, André

    2004-11-01

    Two hundred years ago, Giovanni Aldini published a highly influential book that reported experiments in which the principles of Luigi Galvani (animal electricity) and Alessandro Volta (bimetallic electricity) were used together for the first time. Aldini was born in Bologna in 1762 and graduated in physics at the University of his native town in 1782. As nephew and assistant of Galvani, he actively participated in a series of crucial experiments with frog's muscles that led to the idea that electricity was the long-sought vital force coursing from brain to muscles. Aldini became professor of experimental physics at the University of Bologna in 1798. He traveled extensively throughout Europe, spending much time defending the concept of his discreet uncle against the incessant attacks of Volta, who did not believe in animal electricity. Aldini used Volta's bimetallic pile to apply electric current to dismembered bodies of animals and humans; these spectacular galvanic reanimation experiments made a strong and enduring impression on his contemporaries. Aldini also treated patients with personality disorders and reported complete rehabilitation following transcranial administration of electric current. Aldini's work laid the ground for the development of various forms of electrotherapy that were heavily used later in the 19th century. Even today, deep brain stimulation, a procedure currently employed to relieve patients with motor or behavioral disorders, owes much to Aldini and galvanism. In recognition of his merits, Aldini was made a knight of the Iron Crown and a councillor of state at Milan, where he died in 1834.

  11. Genetic contributions to human brain morphology and intelligence

    DEFF Research Database (Denmark)

    Hulshoff Pol, HE; Schnack, HG; Posthuma, D

    2006-01-01

    the focal GM and WM densities of each twin are correlated with the psychometric intelligence quotient of his/her cotwin. Genes influenced individual differences in left and right superior occipitofrontal fascicle (heritability up to 0.79 and 0.77), corpus callosum (0.82, 0.80), optic radiation (0.69, 0.......79), corticospinal tract (0.78, 0.79), medial frontal cortex (0.78, 0.83), superior frontal cortex (0.76, 0.80), superior temporal cortex (0.80, 0.77), left occipital cortex (0.85), left postcentral cortex (0.83), left posterior cingulate cortex (0.83), right parahippocampal cortex (0.69), and amygdala (0.80, 0......Variation in gray matter (GM) and white matter (WM) volume of the adult human brain is primarily genetically determined. Moreover, total brain volume is positively correlated with general intelligence, and both share a common genetic origin. However, although genetic effects on morphology...

  12. Brain Imaging of Human Sexual Response : Recent Developments and Future Directions

    NARCIS (Netherlands)

    Ruesink, Gerben B; Georgiadis, Janniko R

    2017-01-01

    Purpose of Review: The purpose of this study is to provide a comprehensive summary of the latest developments in the experimental brain study of human sexuality, focusing on brain connectivity during the sexual response. Recent Findings: Stable patterns of brain activation have been established for

  13. Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

    NARCIS (Netherlands)

    Guadalupe, Tulio; Mathias, Samuel R.; vanErp, Theo G.M.; Whelan, Christopher D.; Zwiers, Marcel P.; Abe, Yoshinari; Abramovic, Lucija; Agartz, Ingrid; Andreassen, Ole A.; Arias-Vásquez, Alejandro; Aribisala, Benjamin S.; Armstrong, Nicola J.; Arolt, Volker; Artiges, Eric; Ayesa-Arriola, Rosa; Baboyan, Vatche G.; Banaschewski, Tobias; Barker, Gareth; Bastin, Mark E.; Baune, Bernhard T.; Blangero, John; Bokde, Arun L.W.; Boedhoe, Premika S.W.; Bose, Anushree; Brem, Silvia; Brodaty, Henry; Bromberg, Uli; Brooks, Samantha; Büchel, Christian; Buitelaar, Jan; Calhoun, Vince D.; Cannon, Dara M.; Cattrell, Anna; Cheng, Yuqi; Conrod, Patricia J.; Conzelmann, Annette; Corvin, Aiden; Crespo-Facorro, Benedicto; Crivello, Fabrice; Dannlowski, Udo; de Zubicaray, Greig I.; de Zwarte, Sonja M.C.; Deary, Ian J.; Desrivières, Sylvane; Doan, Nhat Trung; Donohoe, Gary; Dørum, Erlend S.; Ehrlich, Stefan; Espeseth, Thomas; Fernández, Guillén; Flor, Herta; Fouche, Jean Paul; Frouin, Vincent; Fukunaga, Masaki; Gallinat, Jürgen; Garavan, Hugh; Gill, Michael; Suarez, Andrea Gonzalez; Gowland, Penny; Grabe, Hans J.; Grotegerd, Dominik; Gruber, Oliver; Hagenaars, Saskia; Hashimoto, Ryota; Hauser, Tobias U.; Heinz, Andreas; Hibar, Derrek P.; Hoekstra, Pieter J.; Hoogman, Martine; Howells, Fleur M.; Hu, Hao; Hulshoff Pol, Hilleke E.; Huyser, Chaim; Ittermann, Bernd; Jahanshad, Neda; Jönsson, Erik G.; Jurk, Sarah; Kahn, Rene S.; Kelly, Sinead; Kraemer, Bernd; Kugel, Harald; Kwon, Jun Soo; Lemaitre, Herve; Lesch, Klaus Peter; Lochner, Christine; Luciano, Michelle; Marquand, Andre F.; Martin, Nicholas G.; Martínez-Zalacaín, Ignacio; Martinot, Jean Luc; Mataix-Cols, David; Mather, Karen; McDonald, Colm; McMahon, Katie L.; Medland, Sarah E.; Menchón, José M.; Morris, Derek W.; Mothersill, Omar; Maniega, Susana Munoz; Mwangi, Benson; Nakamae, Takashi; Nakao, Tomohiro; Narayanaswaamy, Janardhanan C.; Nees, Frauke; Nordvik, Jan E.; Onnink, A. Marten H.; Opel, Nils; Ophoff, Roel; Paillère Martinot, Marie Laure; Papadopoulos Orfanos, Dimitri; Pauli, Paul; Paus, Tomáš; Poustka, Luise; Reddy, Janardhan Yc; Renteria, Miguel E.; Roiz-Santiáñez, Roberto; Roos, Annerine; Royle, Natalie A.; Sachdev, Perminder; Sánchez-Juan, Pascual; Schmaal, Lianne; Schumann, Gunter; Shumskaya, Elena; Smolka, Michael N.; Soares, Jair C.; Soriano-Mas, Carles; Stein, Dan J.; Strike, Lachlan T.; Toro, Roberto; Turner, Jessica A.; Tzourio-Mazoyer, Nathalie; Uhlmann, Anne; Hernández, Maria Valdés; van den Heuvel, Odile A.; van der Meer, Dennis; van Haren, Neeltje E.M.; Veltman, Dick J.; Venkatasubramanian, Ganesan; Vetter, Nora C.; Vuletic, Daniella; Walitza, Susanne; Walter, Henrik; Walton, Esther; Wang, Zhen; Wardlaw, Joanna; Wen, Wei; Westlye, Lars T.; Whelan, Robert; Wittfeld, Katharina; Wolfers, Thomas; Wright, Margaret J.; Xu, Jian; Xu, Xiufeng; Yun, Je Yeon; Zhao, Jing Jing; Franke, Barbara; Thompson, Paul M.; Glahn, David C.; Mazoyer, Bernard; Fisher, Simon E.; Francks, Clyde

    2017-01-01

    The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain

  14. Brain derived neurotrophic factor mediated learning, fear acquisition and extinction as targets for developing novel treatments for anxiety

    Directory of Open Access Journals (Sweden)

    Karina Soares de Oliveira

    Full Text Available ABSTRACT Anxiety and obsessive-compulsive related disorders are highly prevalent and disabling disorders for which there are still treatment gaps to be explored. Fear is a core symptom of these disorders and its learning is highly dependent on the activity of the neurotrophin brain-derived neurotrophic factor (BDNF. Should BDNF-mediated fear learning be considered a target for the development of novel treatments for anxiety and obsessive-compulsive related disorders? We review the evidence that suggests that BDNF expression is necessary for the acquisition of conditioned fear, as well as for the recall of its extinction. We describe the findings related to fear learning and genetic/epigenetic manipulation of Bdnf expression in animals and BDNF allelic variants in humans. Later, we discuss how manipulation of BDNF levels represents a promising potential treatment target that may increase the benefits of therapies that extinguish previously conditioned fear.

  15. Editorial: Technology for higher education, adult learning and human performance

    OpenAIRE

    Minhong Wang; Chi-Cheng Chang; Feng Wu

    2013-01-01

    This special issue is dedicated to technology-enabled approaches for improving higher education, adult learning, and human performance. Improvement of learning and human development for sustainable development has been recognized as a key strategy for individuals, institutions, and organizations to strengthen their competitive advantages. It becomes crucial to help adult learners and knowledge workers to improve their self-directed and life-long learning capabilities. Meanwhile, advances in t...

  16. The addicted human brain viewed in the light of imaging studies: brain circuits and treatment strategies.

    Science.gov (United States)

    Volkow, Nora D; Fowler, Joanna S; Wang, Gene-Jack

    2004-01-01

    Imaging studies have provided evidence of how the human brain changes as an individual becomes addicted. Here, we integrate the findings from imaging studies to propose a model of drug addiction. The process of addiction is initiated in part by the fast and high increases in DA induced by drugs of abuse. We hypothesize that this supraphysiological effect of drugs trigger a series of adaptations in neuronal circuits involved in saliency/reward, motivation/drive, memory/conditioning, and control/disinhibition, resulting in an enhanced (and long lasting) saliency value for the drug and its associated cues at the expense of decreased sensitivity for salient events of everyday life (including natural reinforcers). Although acute drug intake increases DA neurotransmission, chronic drug consumption results in a marked decrease in DA activity, associated with, among others, dysregulation of the orbitofrontal cortex (region involved with salience attribution) and cingulate gyrus (region involved with inhibitory control). The ensuing increase in motivational drive for the drug, strengthened by conditioned responses and the decrease in inhibitory control favors emergence of compulsive drug taking. This view of how drugs of abuse affect the brain suggests strategies for intervention, which might include: (a) those that will decrease the reward value of the drug of choice; (b) interventions to increase the saliency value of non-drug reinforcers; (c) approaches to weaken conditioned drug behaviors; and (d) methods to strengthen frontal inhibitory and executive control. Though this model focuses mostly on findings from PET studies of the brain DA system it is evident that other neurotransmitters are involved and that a better understanding of their roles in addiction would expand the options for therapeutic targets.

  17. Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans.

    Science.gov (United States)

    Smirnov, Dmitry; Lachat, Fanny; Peltola, Tomi; Lahnakoski, Juha M; Koistinen, Olli-Pekka; Glerean, Enrico; Vehtari, Aki; Hari, Riitta; Sams, Mikko; Nummenmaa, Lauri

    2017-01-01

    Seeing an action may activate the corresponding action motor code in the observer. It remains unresolved whether seeing and performing an action activates similar action-specific motor codes in the observer and the actor. We used novel hyperclassification approach to reveal shared brain activation signatures of action execution and observation in interacting human subjects. In the first experiment, two "actors" performed four types of hand actions while their haemodynamic brain activations were measured with 3-T functional magnetic resonance imaging (fMRI). The actions were videotaped and shown to 15 "observers" during a second fMRI experiment. Eleven observers saw the videos of one actor, and the remaining four observers saw the videos of the other actor. In a control fMRI experiment, one of the actors performed actions with closed eyes, and five new observers viewed these actions. Bayesian canonical correlation analysis was applied to functionally realign observers' and actors' fMRI data. Hyperclassification of the seen actions was performed with Bayesian logistic regression trained on actors' data and tested with observers' data. Without the functional realignment, between-subjects accuracy was at chance level. With the realignment, the accuracy increased on average by 15 percentage points, exceeding both the chance level and the accuracy without functional realignment. The highest accuracies were observed in occipital, parietal and premotor cortices. Hyperclassification exceeded chance level also when the actor did not see her own actions. We conclude that the functional brain activation signatures underlying action execution and observation are partly shared, yet these activation signatures may be anatomically misaligned across individuals.

  18. The power of love on the human brain.

    Science.gov (United States)

    Bianchi-Demicheli, Francesco; Grafton, Scott T; Ortigue, Stephanie

    2006-01-01

    Romantic love has been the source for some of the greatest achievements of mankind throughout the ages. The recent localization of romantic love within subcortico-cortical reward, motivation and emotion systems in the human brain has suggested that love is a goal-directed drive with predictable facilitation effects on cognitive behavior, rather than a pure emotion. Here we show that the subliminal exposure of a beloved's name (romantic prime) during a lexical decision task dramatically improves performance in women in love (Experiment 1), as the subliminal presentation of a passion's descriptive noun does (Experiment 2). The parallel between love and passion allows us to interpret these facilitation effects as corresponding to cognitive top-down processes within a motivation-enhanced neural network.

  19. Adrenergic receptors in frontal cortex in human brain.

    Science.gov (United States)

    Cash, R; Raisman, R; Ruberg, M; Agid, Y

    1985-02-05

    The binding of three adrenergic ligands ([3H]prazosin, [3H]clonidine, [3H]dihydroalprenolol) was studied in the frontal cortex of human brain. alpha 1-Receptors, labeled by [3H]prazosin, predominated. [3H]Clonidine bound to two classes of sites, one of high affinity and one of low affinity. Guanosine triphosphate appeared to lower the affinity of [3H]clonidine for its receptor. [3H]Dihydroalprenolol bound to three classes of sites: the beta 1-receptor, the beta 2-receptor and a receptor with low affinity which represented about 40% of the total binding, but which was probably a non-specific site; the beta 1/beta 2 ratio was 1/2.

  20. Exclusive neuronal expression of SUCLA2 in the human brain

    DEFF Research Database (Denmark)

    Dobolyi, Arpád; Ostergaard, Elsebet; Bagó, Attila G

    2015-01-01

    associated with SUCLA2 mutations, the precise localization of SUCLA2 protein has never been investigated. Here, we show that immunoreactivity of A-SUCL-β in surgical human cortical tissue samples was present exclusively in neurons, identified by their morphology and visualized by double labeling...... was absent in glial cells, identified by antibodies directed against the glial markers GFAP and S100. Furthermore, in situ hybridization histochemistry demonstrated that SUCLA2 mRNA was present in Nissl-labeled neurons but not glial cells labeled with S100. Immunoreactivity of the GTP-forming β subunit (G......-SUCL-β) encoded by SUCLG2, or in situ hybridization histochemistry for SUCLG2 mRNA could not be demonstrated in either neurons or astrocytes. Western blotting of post mortem brain samples revealed minor G-SUCL-β immunoreactivity that was, however, not upregulated in samples obtained from diabetic versus non...

  1. Role of synchronized oscillatory brain activity for human pain perception.

    Science.gov (United States)

    Hauck, Michael; Lorenz, Jürgen; Engel, Andreas K

    2008-01-01

    The understanding of cortical pain processing in humans has significantly improved since the development of modern neuroimaging techniques. Non-invasive electrophysiological approaches such as electro- and magnetoencephalography have proven to be helpful tools for the real-time investigation of neuronal signals and synchronous communication between cortical areas. In particular, time-frequency decomposition of signals recorded with these techniques seems to be a promising approach because different pain-related oscillatory changes can be observed within different frequency bands, which are likely to be linked to specific sensory and motor functions. In this review we discuss the latest evidence on pain-induced time-frequency signals and propose that changes in oscillatory activity reflect an essential communication mechanism in the brain that is modulated during pain processing. The importance of synchronization processes for normal and pathological pain processing, such as chronic pain states, is discussed.

  2. Music mnemonics aid Verbal Memory and Induce Learning - Related Brain Plasticity in Multiple Sclerosis.

    Science.gov (United States)

    Thaut, Michael H; Peterson, David A; McIntosh, Gerald C; Hoemberg, Volker

    2014-01-01

    Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey's auditory verbal learning test. We defined the "learning-related synchronization" (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances "deep encoding" during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS.

  3. musical mnemonics aid verbal memory and induce learning related brain plasticity in multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Michael eThaut

    2014-06-01

    Full Text Available Recent research in music and brain function has suggested that the temporal pattern structure in music andrhythm can enhance cognitive functions. To further elucidate this question specifically for memory weinvestigated if a musical template can enhance verbal learning in patients with multiple sclerosis and ifmusic assisted learning will also influence short-term, system-level brain plasticity. We measuredsystems-level brain activity with oscillatory network synchronization during music assisted learning.Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG in alpha andbeta frequency bands in 54 patients with multiple sclerosis (MS. The study sample was randomlydivided into 2 groups, either hearing a spoken or musical (sung presentation of Rey’s Auditory VerbalLearning Test (RAVLT. We defined the learning-related synchronization (LRS as the percent changein EEG spectral power from the first time the word was presented to the average of the subsequent wordencoding trials. LRS differed significantly between the music and spoken conditions in low alpha andupper beta bands. Patients in the music condition showed overall better word memory and better wordorder memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. Theevidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization inprefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicitin musical stimuli enhances ‘deep encoding’ during verbal learning and sharpens the timing of neuraldynamics in brain networks degraded by demyelination in MS

  4. Implicit false-belief processing in the human brain.

    Science.gov (United States)

    Schneider, Dana; Slaughter, Virginia P; Becker, Stefanie I; Dux, Paul E

    2014-11-01

    Eye-movement patterns in 'Sally-Anne' tasks reflect humans' ability to implicitly process the mental states of others, particularly false-beliefs - a key theory of mind (ToM) operation. It has recently been proposed that an efficient ToM system, which operates in the absence of awareness (implicit ToM, iToM), subserves the analysis of belief-like states. This contrasts to consciously available belief processing, performed by the explicit ToM system (eToM). The frontal, temporal and parietal cortices are engaged when humans explicitly 'mentalize' about others' beliefs. However, the neural underpinnings of implicit false-belief processing and the extent to which they draw on networks involved in explicit general-belief processing are unknown. Here, participants watched 'Sally-Anne' movies while fMRI and eye-tracking measures were acquired simultaneously. Participants displayed eye-movements consistent with implicit false-belief processing. After independently localizing the brain areas involved in explicit general-belief processing, only the left anterior superior temporal sulcus and precuneus revealed greater blood-oxygen-level-dependent activity for false- relative to true-belief trials in our iToM paradigm. No such difference was found for the right temporal-parietal junction despite significant activity in this area. These findings fractionate brain regions that are associated with explicit general ToM reasoning and false-belief processing in the absence of awareness. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. The structural, connectomic and network covariance of the human brain.

    Science.gov (United States)

    Irimia, Andrei; Van Horn, John D

    2013-02-01

    Though it is widely appreciated that complex structural, functional and morphological relationships exist between distinct areas of the human cerebral cortex, the extent to which such relationships coincide remains insufficiently appreciated. Here we determine the extent to which correlations between brain regions are modulated by either structural, connectomic or network-theoretic properties using a structural neuroimaging data set of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) volumes acquired from N=110 healthy human adults. To identify the linear relationships between all available pairs of regions, we use canonical correlation analysis to test whether a statistically significant correlation exists between each pair of cortical parcels as quantified via structural, connectomic or network-theoretic measures. In addition to this, we investigate (1) how each group of canonical variables (whether structural, connectomic or network-theoretic) contributes to the overall correlation and, additionally, (2) whether each individual variable makes a significant contribution to the test of the omnibus null hypothesis according to which no correlation between regions exists across subjects. We find that, although region-to-region correlations are extensively modulated by structural and connectomic measures, there are appreciable differences in how these two groups of measures drive inter-regional correlation patterns. Additionally, our results indicate that the network-theoretic properties of the cortex are strong modulators of region-to-region covariance. Our findings are useful for understanding the structural and connectomic relationship between various parts of the brain, and can inform theoretical and computational models of cortical information processing. Published by Elsevier Inc.

  6. A collaborative brain-computer interface for improving human performance.

    Directory of Open Access Journals (Sweden)

    Yijun Wang

    Full Text Available Electroencephalogram (EEG based brain-computer interfaces (BCI have been studied since the 1970s. Currently, the main focus of BCI research lies on the clinical use, which aims to provide a new communication channel to patients with motor disabilities to improve their quality of life. However, the BCI technology can also be used to improve human performance for normal healthy users. Although this application has been proposed for a long time, little progress has been made in real-world practices due to technical limits of EEG. To overcome the bottleneck of low single-user BCI performance, this study proposes a collaborative paradigm to improve overall BCI performance by integrating information from multiple users. To test the feasibility of a collaborative BCI, this study quantitatively compares the classification accuracies of collaborative and single-user BCI applied to the EEG data collected from 20 subjects in a movement-planning experiment. This study also explores three different methods for fusing and analyzing EEG data from multiple subjects: (1 Event-related potentials (ERP averaging, (2 Feature concatenating, and (3 Voting. In a demonstration system using the Voting method, the classification accuracy of predicting movement directions (reaching left vs. reaching right was enhanced substantially from 66% to 80%, 88%, 93%, and 95% as the numbers of subjects increased from 1 to 5, 10, 15, and 20, respectively. Furthermore, the decision of reaching direction could be made around 100-250 ms earlier than the subject's actual motor response by decoding the ERP activities arising mainly from the posterior parietal cortex (PPC, which are related to the processing of visuomotor transmission. Taken together, these results suggest that a collaborative BCI can effectively fuse brain activities of a group of people to improve the overall performance of natural human behavior.

  7. Exploratory Metabolomic Analyses Reveal Compounds Correlated with Lutein Concentration in Frontal Cortex, Hippocampus, and Occipital Cortex of Human Infant Brain.

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    Jacqueline C Lieblein-Boff

    Full Text Available Lutein is a dietary carotenoid well known for its role as an antioxidant in the macula, and recent reports implicate a role for lutein in cognitive function. Lutein is the dominant carotenoid in both pediatric and geriatric brain tissue. In addition, cognitive function in older adults correlated with macular and postmortem brain lutein concentrations. Furthermore, lutein was found to preferentially accumulate in the infant brain in comparison to other carotenoids that are predominant in diet. While lutein is consistently related to cognitive function, the mechanisms by which lutein may influence cognition are not clear. In an effort to identify potential mechanisms through which lutein might influence neurodevelopment, an exploratory study relating metabolite signatures and lutein was completed. Post-mortem metabolomic analyses were performed on human infant brain tissues in three regions important for learning and memory: the frontal cortex, hippocampus, and occipital cortex. Metabolomic profiles were compared to lutein concentration, and correlations were identified and reported here. A total of 1276 correlations were carried out across all brain regions. Of 427 metabolites analyzed, 257 were metabolites of known identity. Unidentified metabolite correlations (510 were excluded. In addition, moderate correlations with xenobiotic relationships (2 or those driven by single outliers (3 were excluded from further study. Lutein concentrations correlated with lipid pathway metabolites, energy pathway metabolites, brain osmolytes, amino acid neurotransmitters, and the antioxidant homocarnosine. These correlations were often brain region-specific. Revealing relationships between lutein and metabolic pathways may help identify potential candidates on which to complete further analyses and may shed light on important roles of lutein in the human brain during development.

  8. Brain Computer Interface Learning for Systems Based on Electrocorticography and Intracortical Microelectrode Arrays

    Directory of Open Access Journals (Sweden)

    Shivayogi V Hiremath

    2015-06-01

    Full Text Available A brain-computer interface (BCI system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

  9. Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays.

    Science.gov (United States)

    Hiremath, Shivayogi V; Chen, Weidong; Wang, Wei; Foldes, Stephen; Yang, Ying; Tyler-Kabara, Elizabeth C; Collinger, Jennifer L; Boninger, Michael L

    2015-01-01

    A brain-computer interface (BCI) system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

  10. Steady-state cerebral glucose concentrations and transport in the human brain

    OpenAIRE

    Gruetter, R.; Ugurbil, K.; Seaquist, E. R.

    1998-01-01

    Understanding the mechanism of brain glucose transport across the blood- brain barrier is of importance to understanding brain energy metabolism. The specific kinetics of glucose transport nave been generally described using standard Michaelis-Menten kinetics. These models predict that the steady- state glucose concentration approaches an upper limit in the human brain when the plasma glucose level is well above the Michaelis-Menten constant for half-maximal transport, K(t). In experiments wh...

  11. Learning from label proportions in brain-computer interfaces: Online unsupervised learning with guarantees

    Science.gov (United States)

    Verhoeven, Thibault; Schmid, Konstantin; Müller, Klaus-Robert; Tangermann, Michael; Kindermans, Pieter-Jan

    2017-01-01

    Objective Using traditional approaches, a brain-computer interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g., by subject-to-subject transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratch and adapt over time. While such heuristics work well in practice, none of them can provide theoretical guarantees. Our objective is to modify an event-related potential (ERP) paradigm to work in unison with the machine learning decoder, and thus to achieve a reliable unsupervised calibrationless decoding with a guarantee to recover the true class means. Method We introduce learning from label proportions (LLP) to the BCI community as a new unsupervised, and easy-to-implement classification approach for ERP-based BCIs. The LLP estimates the mean target and non-target responses based on known proportions of these two classes in different groups of the data. We present a visual ERP speller to meet the requirements of LLP. For evaluation, we ran simulations on artificially created data sets and conducted an online BCI study with 13 subjects performing a copy-spelling task. Results Theoretical considerations show that LLP is guaranteed to minimize the loss function similar to a corresponding supervised classifier. LLP performed well in simulations and in the online application, where 84.5% of characters were spelled correctly on average without prior calibration. Significance The continuously adapting LLP classifier is the first unsupervised decoder for ERP BCIs guaranteed to find the optimal decoder. This makes it an ideal solution to avoid tedious calibration sessions. Additionally, LLP works on complementary principles compared to existing unsupervised methods, opening the door for their further enhancement when combined with LLP. PMID:28407016

  12. Variable ATP yields and uncoupling of oxygen consumption in human brain

    DEFF Research Database (Denmark)

    Gjedde, Albert; Aanerud, Joel; Peterson, Ericka

    2011-01-01

    normalized the metabolic rate to the population average of that region. Coefficients of variation ranged from 10 to 15% in the different regions of the human brain and the normalized regional metabolic rates ranged from 70% to 140% of the population average for each region, equal to a two-fold variation......The distribution of brain oxidative metabolism values among healthy humans is astoundingly wide for a measure that reflects normal brain function and is known to change very little with most changes of brain function. It is possible that the part of the oxygen consumption rate that is coupled...... to ATP turnover is the same in all healthy human brains, with different degrees of uncoupling explaining the variability of total oxygen consumption among people. To test the hypothesis that about 75% of the average total oxygen consumption of human brains is common to all individuals, we determined...

  13. Goal selection versus process control while learning to use a brain-computer interface

    Science.gov (United States)

    Royer, Audrey S.; Rose, Minn L.; He, Bin

    2011-06-01

    A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.

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

    Directory of Open Access Journals (Sweden)

    Laura Marchal-Crespo

    2017-09-01

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

  15. The evidence for increased L1 activity in the site of human adult brain neurogenesis.

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    Alexey A Kurnosov

    Full Text Available Retroelement activity is a common source of polymorphisms in human genome. The mechanism whereby retroelements contribute to the intraindividual genetic heterogeneity by inserting into the DNA of somatic cells is gaining increasing attention. Brain tissues are suspected to accumulate genetic heterogeneity as a result of the retroelements somatic activity. This study aims to expand our understanding of the role retroelements play in generating somatic mosaicism of neural tissues. Whole-genome Alu and L1 profiling of genomic DNA extracted from the cerebellum, frontal cortex, subventricular zone, dentate gyrus, and the myocardium revealed hundreds of somatic insertions in each of the analyzed tissues. Interestingly, the highest concentration of such insertions was detected in the dentate gyrus-the hotspot of adult neurogenesis. Insertions of retroelements and their activity could produce genetically diverse neuronal subsets, which can be involved in hippocampal-dependent learning and memory.

  16. Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness.

    Directory of Open Access Journals (Sweden)

    Katarzyna Bozek

    2014-05-01

    Full Text Available Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys.

  17. Neural mechanisms of human perceptual learning: electrophysiological evidence for a two-stage process.

    Science.gov (United States)

    Hamamé, Carlos M; Cosmelli, Diego; Henriquez, Rodrigo; Aboitiz, Francisco

    2011-04-26

    Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing. We conclude that there are reorganizations in several neural processes that contribute differently to perceptual learning in a visual search task. We propose an integrative model of neural activity reorganization, whereby perceptual learning takes place as a two-stage phenomenon including perceptual, attentional and contextual processes.

  18. Evidence of native α-synuclein conformers in the human brain.

    Science.gov (United States)

    Gould, Neal; Mor, Danielle E; Lightfoot, Richard; Malkus, Kristen; Giasson, Benoit; Ischiropoulos, Harry

    2014-03-14

    α-Synuclein aggregation is central to the pathogenesis of several brain disorders. However, the native conformations and functions of this protein in the human brain are not precisely known. The native state of α-synuclein was probed by gel filtration coupled with native gradient gel separation, an array of antibodies with non-overlapping epitopes, and mass spectrometry. The existence of metastable conformers and stable monomer was revealed in the human brain.

  19. Somatotopic Arrangement and Location of the Corticospinal Tract in the Brainstem of the Human Brain

    OpenAIRE

    Jang, Sung Ho

    2011-01-01

    The corticospinal tract (CST) is the most important motor pathway in the human brain. Detailed knowledge of CST somatotopy is important in terms of rehabilitative management and invasive procedures for patients with brain injuries. In this study, I conducted a review of nine previous studies of the somatotopical location and arrangement at the brainstem in the human brain. The results of this review indicated that the hand and leg somatotopies of the CST are arranged medio-laterally in the mi...

  20. Studying frequency processing of the brain to enhance long-term memory and develop a human brain protocol.

    Science.gov (United States)

    Friedrich, Wernher; Du, Shengzhi; Balt, Karlien

    2015-01-01

    The temporal lobe in conjunction with the hippocampus is responsible for memory processing. The gamma wave is involved with this process. To develop a human brain protocol, a better understanding of the relationship between gamma and long-term memory is vital. A more comprehensive understanding of the human brain and specific analogue waves it uses will support the development of a human brain protocol. Fifty-eight participants aged between 6 and 60 years participated in long-term memory experiments. It is envisaged that the brain could be stimulated through binaural beats (sound frequency) at 40 Hz (gamma) to enhance long-term memory capacity. EEG recordings have been transformed to sound and then to an information standard, namely ASCII. Statistical analysis showed a proportional relationship between long-term memory and gamma activity. Results from EEG recordings indicate a pattern. The pattern was obtained through the de-codification of an EEG recording to sound and then to ASCII. Stimulation of gamma should enhance long term memory capacity. More research is required to unlock the human brains' protocol key. This key will enable the processing of information directly to and from human memory via gamma, the hippocampus and the temporal lobe.

  1. Common genetic variation near MC4R has a sex-specific impact on human brain structure and eating behavior.

    Directory of Open Access Journals (Sweden)

    Annette Horstmann

    Full Text Available Obesity is associated with genetic and environmental factors but the underlying mechanisms remain poorly understood. Recent genome-wide association studies (GWAS identified obesity- and type 2 diabetes-associated genetic variants located within or near genes that modulate brain activity and development. Among the top hits is rs17782313 near MC4R, encoding for the melanocortin-4-receptor, which is expressed in brain regions that regulate eating. Here, we hypothesized rs17782313-associated changes in human brain regions that regulate eating behavior. Therefore, we examined effects of common variants at rs17782313 near MC4R on brain structure and eating behavior. Only in female homozygous carriers of the risk allele we found significant increases of gray matter volume (GMV in the right amygdala, a region known to influence eating behavior, and the right hippocampus, a structure crucial for memory formation and learning. Further, we found bilateral increases in medial orbitofrontal cortex, a multimodal brain structure encoding the subjective value of reinforcers, and bilateral prefrontal cortex, a higher order regulation area. There was no association between rs17782313 and brain structure in men. Moreover, among female subjects only, we observed a significant increase of 'disinhibition', and, more specifically, on 'emotional eating' scores of the Three Factor Eating Questionnaire in carriers of the variant rs17782313's risk allele. These findings suggest that rs17782313's effect on eating behavior is mediated by central mechanisms and that these effects are sex-specific.

  2. Noninvasive quantification of human brain antioxidant concentrations after an intravenous bolus of vitamin C

    Science.gov (United States)

    Background: Until now, antioxidant based initiatives for preventing dementia have lacked a means to detect deficiency or measure pharmacologic effect in the human brain in situ. Objective: Our objective was to apply a novel method to measure key human brain antioxidant concentrations throughout the ...

  3. The human sexual response cycle : Brain imaging evidence linking sex to other pleasures

    NARCIS (Netherlands)

    Georgiadis, J. R.; Kringelbach, M. L.

    Sexual behavior is critical to species survival, yet comparatively little is known about the neural mechanisms in the human brain. Here we systematically review the existing human brain imaging literature on sexual behavior and show that the functional neuroanatomy of sexual behavior is comparable

  4. The future of neuroepigenetics in the human brain.

    Science.gov (United States)

    Mitchell, Amanda; Roussos, Panos; Peter, Cyril; Tsankova, Nadejda; Akbarian, Schahram

    2014-01-01

    Complex mechanisms shape the genome of brain cells into transcriptional units, clusters of condensed chromatin, and many other features that distinguish between various cell types and developmental stages sharing the same genetic material. Only a few years ago, the field's focus was almost entirely on a single mark, CpG methylation; the emerging complexity of neuronal and glial epigenomes now includes multiple types of DNA cytosine methylation, more than 100 residue-specific posttranslational histone modifications and histone variants, all of which superimposed by a dynamic and highly regulated three-dimensional organization of the chromosomal material inside the cell nucleus. Here, we provide an update on the most innovative approaches in neuroepigenetics and their potential contributions to approach cognitive functions and disorders unique to human. We propose that comprehensive, cell type-specific mappings of DNA and histone modifications, chromatin-associated RNAs, and chromosomal "loopings" and other determinants of three-dimensional genome organization will critically advance insight into the pathophysiology of the disease. For example, superimposing the epigenetic landscapes of neuronal and glial genomes onto genetic maps for complex disorders, ranging from Alzheimer's disease to schizophrenia, could provide important clues about neurological function for some of the risk-associated noncoding sequences in the human genome.

  5. Morphometry of medial gaps of human brain artery branches.

    Science.gov (United States)

    Canham, Peter B; Finlay, Helen M

    2004-05-01

    The bifurcation regions of the major human cerebral arteries are vulnerable to the formation of saccular aneurysms. A consistent feature of these bifurcations is a discontinuity of the tunica media at the apex of the flow divider. The objective was to measure the 3-dimensional geometry of these medial gaps or "medial defects." Nineteen bifurcations and 2 junctions of human cerebral arteries branches (from 4 male and 2 female subjects) were formalin-fixed at physiological pressure and processed for longitudinal serial sectioning. The apex and adjacent regions were examined and measurements were made from high-magnification photomicrographs, or projection microscope images, of the gap dimensions at multiple levels through the bifurcation. Plots were made of the width of the media as a function of distance from the apex. The media at each edge of the medial gap widened over a short distance, reaching the full width of the media of the contiguous daughter vessel. Medial gap dimensions were compared with the planar angle of the bifurcation, and a strong negative correlation was found, ie, the acute angled branches have the more prominent medial gaps. A discontinuity of the media at the apex was seen in all the bifurcations examined and was also found in the junction regions of brain arteries. We determined that the gap width is continuous with well-defined dimensions throughout its length and average length-to-width ratio of 6.9. The gaps were generally centered on the prominence of the apical ridge.

  6. Evidence for Functional Networks within the Human Brain's White Matter.

    Science.gov (United States)

    Peer, Michael; Nitzan, Mor; Bick, Atira S; Levin, Netta; Arzy, Shahar

    2017-07-05

    brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders. Copyright © 2017 the authors 0270-6474/17/376394-14$15.00/0.

  7. Learned self-regulation of the lesioned brain with epidural electrocorticography

    Directory of Open Access Journals (Sweden)

    Alireza eGharabaghi

    2014-12-01

    Full Text Available Introduction: Different techniques for neurofeedback of voluntary brain activations are currently being explored for clinical application in brain-related disorders. One of the most frequently used approaches is the self-regulation of oscillatory signals recorded with electroencephalography (EEG. Many patients are, however, not in a position to use such tools. This could be due to the specific anatomical and physiological properties of the patient's brain after the lesion, as well as to methodological issues related to the technique chosen for recording brain signals.Methods: A patient with extended ischemic lesions of the cortex was unable to gain volitional control of sensorimotor oscillations when using a standard EEG-based approach. We provided him with a neurofeedback set-up with which his brain activity could be recorded from the epidural space by electrocorticography (ECoG.Results: Ipsilesional epidural recordings of field potentials facilitated learned self-regulation of brain oscillations in an online closed-loop paradigm and allowed swift and reliable neurofeedback training for a period of four weeks on a daily basis.Conclusion: Epidural implants may decode and train brain activity even when the cortical physiology is distorted following severe brain injury. Such practice would allow for reinforcement learning of preserved neural networks and may well provide restorative tools for those patients who are worst afflicted.

  8. Temperament, character and serotonin activity in the human brain

    DEFF Research Database (Denmark)

    Tuominen, L; Salo, J; Hirvonen, J

    2013-01-01

    The psychobiological model of personality by Cloninger and colleagues originally hypothesized that interindividual variability in the temperament dimension 'harm avoidance' (HA) is explained by differences in the activity of the brain serotonin system. We assessed brain serotonin transporter (5-HTT...

  9. Metabolic learning and memory formation by the brain influence systemic metabolic homeostasis.

    Science.gov (United States)

    Zhang, Yumin; Liu, Gang; Yan, Jingqi; Zhang, Yalin; Li, Bo; Cai, Dongsheng

    2015-04-07

    Metabolic homeostasis is regulated by the brain, but whether this regulation involves learning and memory of metabolic information remains unexplored. Here we use a calorie-based, taste-independent learning/memory paradigm to show that Drosophila form metabolic memories that help in balancing food choice with caloric intake; however, this metabolic learning or memory is lost under chronic high-calorie feeding. We show that loss of individual learning/memory-regulating genes causes a metabolic learning defect, leading to elevated trehalose and lipid levels. Importantly, this function of metabolic learning requires not only the mushroom body but also the hypothalamus-like pars intercerebralis, while NF-κB activation in the pars intercerebralis mimics chronic overnutrition in that it causes metabolic learning impairment and disorders. Finally, we evaluate this concept of metabolic learning/memory in mice, suggesting that the hypothalamus is involved in a form of nutritional learning and memory, which is critical for determining resistance or susceptibility to obesity. In conclusion, our data indicate that the brain, and potentially the hypothalamus, direct metabolic learning and the formation of memories, which contribute to the control of systemic metabolic homeostasis.

  10. Metabolic learning and memory formation by the brain influence systemic metabolic homeostasis

    Science.gov (United States)

    Zhang, Yumin; Liu, Gang; Yan, Jingqi; Zhang, Yalin; Li, Bo; Cai, Dongsheng

    2015-01-01

    Metabolic homeostasis is regulated by the brain, whether this regulation involves learning and memory of metabolic information remains unexplored. Here we use a calorie-based, taste-independent learning/memory paradigm to show that Drosophila form metabolic memories that help balancing food choice with caloric intake; however, this metabolic learning or memory is lost under chronic high-calorie feeding. We show that loss of individual learning/memory-regulating genes causes a metabolic learning defect, leading to elevated trehalose and lipids levels. Importantly, this function of metabolic learning requires not only the mushroom body but the hypothalamus-like pars intercerebralis, while NF-κB activation in the pars intercerebralis mimics chronic overnutrition in that it causes metabolic learning impairment and disorders. Finally, we evaluate this concept of metabolic learning/memory in mice, suggesting the hypothalamus is involved in a form of nutritional learning and memory, which is critical for determining resistance or susceptibility to obesity. In conclusion, our data indicate the brain, and potentially the hypothalamus, direct metabolic learning and the formation of memories, which contribute to the control of systemic metabolic homeostasis. PMID:25848677

  11. Human capital and human resource management to achieve ambidextrous learning: A structural perspective

    Directory of Open Access Journals (Sweden)

    Mirta Diaz-Fernandez

    2017-01-01

    Full Text Available Organisational learning has become increasingly important for strategic renewal. Ambidextrous organisations are especially successful in the current environment, where firms are required to be efficient and adapt to change. Using a structural approach, this study discusses arguments about the nature of ambidexterity and identifies the kinds of human capital that better support specific learning types and HRM practices suited to these components of human capital. Results highlight learning differences between marketing and production units, as well as different HRM practices and human capital orientations. This study points out that human capital mediates between HRM practices and learning.

  12. Associative learning and the control of human dietary behavior.

    Science.gov (United States)

    Brunstrom, Jeffrey M

    2007-07-01

    Most of our food likes and disliked are learned. Relevant forms of associative learning have been identified in animals. However, observations of the same associative processes are relatively scarce in humans. The first section of this paper outlines reasons why this might be the case. Emphasis is placed on recent research exploring individual differences and the importance or otherwise of hunger and contingency awareness. The second section briefly considers the effect of learning on meal size, and the author revisits the question of how learned associations might come to influence energy intake in humans.

  13. Incidental and intentional learning of verbal episodic material differentially modifies functional brain networks.

    Directory of Open Access Journals (Sweden)

    Marie-Therese Kuhnert

    Full Text Available Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.

  14. Applications of operant learning theory to the management of challenging behavior after traumatic brain injury.

    Science.gov (United States)

    Wood, Rodger Ll; Alderman, Nick

    2011-01-01

    For more than 3 decades, interventions derived from learning theory have been delivered within a neurobehavioral framework to manage challenging behavior after traumatic brain injury with the aim of promoting engagement in the rehabilitation process and ameliorating social handicap. Learning theory provides a conceptual structure that facilitates our ability to understand the relationship between challenging behavior and environmental contingencies, while accommodating the constraints upon learning imposed by impaired cognition. Interventions derived from operant learning theory have most frequently been described in the literature because this method of associational learning provides good evidence for the effectiveness of differential reinforcement methods. This article therefore examines the efficacy of applying operant learning theory to manage challenging behavior after TBI as well as some of the limitations of this approach. Future developments in the application of learning theory are also considered.

  15. Theobromine up-regulates cerebral brain-derived neurotrophic factor and facilitates motor learning in mice

    OpenAIRE

    Yoneda, Mitsugu; Sugimoto, Naotoshi; Katakura, Masanori; Matsuzaki, Kentaro; Tanigami, Hayate; Yachie, Akihiro; Ohno-Shosaku, Takako; Shido, Osamu

    2017-01-01

    Theobromine, which is a caffeine derivative, is the primary methylxanthine produced by Theobroma cacao. Theobromine works as a phosphodiesterase (PDE) inhibitor to increase intracellular cyclic adenosine monophosphate (cAMP). cAMP activates the cAMP-response element-binding protein (CREB), which is involved in a large variety of brain processes, including the induction of the brain-derived neurotrophic factor (BDNF). BDNF supports cell survival and neuronal functions, including learning and m...

  16. Brain Imaging of Human Sexual Response: Recent Developments and Future Directions.

    Science.gov (United States)

    Ruesink, Gerben B; Georgiadis, Janniko R

    2017-01-01

    The purpose of this study is to provide a comprehensive summary of the latest developments in the experimental brain study of human sexuality, focusing on brain connectivity during the sexual response. Stable patterns of brain activation have been established for different phases of the sexual response, especially with regard to the wanting phase, and changes in these patterns can be linked to sexual response variations, including sexual dysfunctions. From this solid basis, connectivity studies of the human sexual response have begun to add a deeper understanding of the brain network function and structure involved. The study of "sexual" brain connectivity is still very young. Yet, by approaching the brain as a connected organ, the essence of brain function is captured much more accurately, increasing the likelihood of finding useful biomarkers and targets for intervention in sexual dysfunction.

  17. Theorising Learning and Nature: Post-Human Possibilities and Problems

    Science.gov (United States)

    Quinn, Jocey

    2013-01-01

    In their predominantly theoretical turn to the material, post-humanist feminists often focus on "nature", arguing that the nature/culture binary has collapsed and that fixed distinctions between human and non-human spheres no longer hold. Conversely, outdoor learning sees nature as a space where humans act and has been more concerned…

  18. Impaired insulin action in the human brain: causes and metabolic consequences.

    Science.gov (United States)

    Heni, Martin; Kullmann, Stephanie; Preissl, Hubert; Fritsche, Andreas; Häring, Hans-Ulrich

    2015-12-01

    Over the past few years, evidence has accumulated that the human brain is an insulin-sensitive organ. Insulin regulates activity in a limited number of specific brain areas that are important for memory, reward, eating behaviour and the regulation of whole-body metabolism. Accordingly, insulin in the brain modulates cognition, food intake and body weight as well as whole-body glucose, energy and lipid metabolism. However, brain imaging studies have revealed that not everybody responds equally to insulin and that a substantial number of people are brain insulin resistant. In this Review, we provide an overview of the effects of insulin in the brain in humans and the relevance of the effects for physiology. We present emerging evidence for insulin resistance of the human brain. Factors associated with brain insulin resistance such as obesity and increasing age, as well as possible pathogenic factors such as visceral fat, saturated fatty acids, alterations at the blood-brain barrier and certain genetic polymorphisms, are reviewed. In particular, the metabolic consequences of brain insulin resistance are discussed and possible future approaches to overcome brain insulin resistance and thereby prevent or treat obesity and type 2 diabetes mellitus are outlined.

  19. Brain development in rodents and humans: Identifying benchmarks of maturation and vulnerability to injury across species

    Science.gov (United States)

    Semple, Bridgette D.; Blomgren, Klas; Gimlin, Kayleen; Ferriero, Donna M.; Noble-Haeusslein, Linda J.

    2013-01-01

    Hypoxic-ischemic and traumatic brain injuries are leading causes of long-term mortality and disability in infants and children. Although several preclinical models using rodents of different ages have been developed, species differences in the timing of key brain maturation events can render comparisons of vulnerability and regenerative capacities difficult to interpret. Traditional models of developmental brain injury have utilized rodents at postnatal day 7–10 as being roughly equivalent to a term human infant, based historically on the measurement of post-mortem brain weights during the 1970s. Here we will examine fundamental brain development processes that occur in both rodents and humans, to delineate a comparable time course of postnatal brain development across species. We consider the timing of neurogenesis, synaptogenesis, gliogenesis, oligodendrocyte maturation and age-dependent behaviors that coincide with developmentally regulated molecular and biochemical changes. In general, while the time scale is considerably different, the sequence of key events in brain maturation is largely consistent between humans and rodents. Further, there are distinct parallels in regional vulnerability as well as functional consequences in response to brain injuries. With a focus on developmental hypoxicischemic encephalopathy and traumatic brain injury, this review offers guidelines for researchers when considering the most appropriate rodent a