Inference in the brain: Statistics flowing in redundant population codes

PubMed Central

Pitkow, Xaq; Angelaki, Dora E

2017-01-01

It is widely believed that the brain performs approximate probabilistic inference to estimate causal variables in the world from ambiguous sensory data. To understand these computations, we need to analyze how information is represented and transformed by the actions of nonlinear recurrent neural networks. We propose that these probabilistic computations function by a message-passing algorithm operating at the level of redundant neural populations. To explain this framework, we review its underlying concepts, including graphical models, sufficient statistics, and message-passing, and then describe how these concepts could be implemented by recurrently connected probabilistic population codes. The relevant information flow in these networks will be most interpretable at the population level, particularly for redundant neural codes. We therefore outline a general approach to identify the essential features of a neural message-passing algorithm. Finally, we argue that to reveal the most important aspects of these neural computations, we must study large-scale activity patterns during moderately complex, naturalistic behaviors. PMID:28595050

Neural dynamics of reward probability coding: a Magnetoencephalographic study in humans

PubMed Central

Thomas, Julie; Vanni-Mercier, Giovanna; Dreher, Jean-Claude

2013-01-01

Prediction of future rewards and discrepancy between actual and expected outcomes (prediction error) are crucial signals for adaptive behavior. In humans, a number of fMRI studies demonstrated that reward probability modulates these two signals in a large brain network. Yet, the spatio-temporal dynamics underlying the neural coding of reward probability remains unknown. Here, using magnetoencephalography, we investigated the neural dynamics of prediction and reward prediction error computations while subjects learned to associate cues of slot machines with monetary rewards with different probabilities. We showed that event-related magnetic fields (ERFs) arising from the visual cortex coded the expected reward value 155 ms after the cue, demonstrating that reward value signals emerge early in the visual stream. Moreover, a prediction error was reflected in ERF peaking 300 ms after the rewarded outcome and showing decreasing amplitude with higher reward probability. This prediction error signal was generated in a network including the anterior and posterior cingulate cortex. These findings pinpoint the spatio-temporal characteristics underlying reward probability coding. Together, our results provide insights into the neural dynamics underlying the ability to learn probabilistic stimuli-reward contingencies. PMID:24302894

Exploring the motivational brain: effects of implicit power motivation on brain activation in response to facial expressions of emotion.

PubMed

Schultheiss, Oliver C; Wirth, Michelle M; Waugh, Christian E; Stanton, Steven J; Meier, Elizabeth A; Reuter-Lorenz, Patricia

2008-12-01

This study tested the hypothesis that implicit power motivation (nPower), in interaction with power incentives, influences activation of brain systems mediating motivation. Twelve individuals low (lowest quartile) and 12 individuals high (highest quartile) in nPower, as assessed per content coding of picture stories, were selected from a larger initial participant pool and participated in a functional magnetic resonance imaging study during which they viewed high-dominance (angry faces), low-dominance (surprised faces) and control stimuli (neutral faces, gray squares) under oddball-task conditions. Consistent with hypotheses, high-power participants showed stronger activation in response to emotional faces in brain structures involved in emotion and motivation (insula, dorsal striatum, orbitofrontal cortex) than low-power participants.

Central neural coding of sky polarization in insects.

PubMed

Homberg, Uwe; Heinze, Stanley; Pfeiffer, Keram; Kinoshita, Michiyo; el Jundi, Basil

2011-03-12

Many animals rely on a sun compass for spatial orientation and long-range navigation. In addition to the Sun, insects also exploit the polarization pattern and chromatic gradient of the sky for estimating navigational directions. Analysis of polarization-vision pathways in locusts and crickets has shed first light on brain areas involved in sky compass orientation. Detection of sky polarization relies on specialized photoreceptor cells in a small dorsal rim area of the compound eye. Brain areas involved in polarization processing include parts of the lamina, medulla and lobula of the optic lobe and, in the central brain, the anterior optic tubercle, the lateral accessory lobe and the central complex. In the optic lobe, polarization sensitivity and contrast are enhanced through convergence and opponency. In the anterior optic tubercle, polarized-light signals are integrated with information on the chromatic contrast of the sky. Tubercle neurons combine responses to the UV/green contrast and e-vector orientation of the sky and compensate for diurnal changes of the celestial polarization pattern associated with changes in solar elevation. In the central complex, a topographic representation of e-vector tunings underlies the columnar organization and suggests that this brain area serves as an internal compass coding for spatial directions.

Central neural coding of sky polarization in insects

PubMed Central

Homberg, Uwe; Heinze, Stanley; Pfeiffer, Keram; Kinoshita, Michiyo; el Jundi, Basil

2011-01-01

Many animals rely on a sun compass for spatial orientation and long-range navigation. In addition to the Sun, insects also exploit the polarization pattern and chromatic gradient of the sky for estimating navigational directions. Analysis of polarization–vision pathways in locusts and crickets has shed first light on brain areas involved in sky compass orientation. Detection of sky polarization relies on specialized photoreceptor cells in a small dorsal rim area of the compound eye. Brain areas involved in polarization processing include parts of the lamina, medulla and lobula of the optic lobe and, in the central brain, the anterior optic tubercle, the lateral accessory lobe and the central complex. In the optic lobe, polarization sensitivity and contrast are enhanced through convergence and opponency. In the anterior optic tubercle, polarized-light signals are integrated with information on the chromatic contrast of the sky. Tubercle neurons combine responses to the UV/green contrast and e-vector orientation of the sky and compensate for diurnal changes of the celestial polarization pattern associated with changes in solar elevation. In the central complex, a topographic representation of e-vector tunings underlies the columnar organization and suggests that this brain area serves as an internal compass coding for spatial directions. PMID:21282171

Theory of Mind: A Neural Prediction Problem

PubMed Central

Koster-Hale, Jorie; Saxe, Rebecca

2014-01-01

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others’ goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind. PMID:24012000

The central nervous system transcriptome of the weakly electric brown ghost knifefish (Apteronotus leptorhynchus): de novo assembly, annotation, and proteomics validation.

PubMed

Salisbury, Joseph P; Sîrbulescu, Ruxandra F; Moran, Benjamin M; Auclair, Jared R; Zupanc, Günther K H; Agar, Jeffrey N

2015-03-11

The brown ghost knifefish (Apteronotus leptorhynchus) is a weakly electric teleost fish of particular interest as a versatile model system for a variety of research areas in neuroscience and biology. The comprehensive information available on the neurophysiology and neuroanatomy of this organism has enabled significant advances in such areas as the study of the neural basis of behavior, the development of adult-born neurons in the central nervous system and their involvement in the regeneration of nervous tissue, as well as brain aging and senescence. Despite substantial scientific interest in this species, no genomic resources are currently available. Here, we report the de novo assembly and annotation of the A. leptorhynchus transcriptome. After evaluating several trimming and transcript reconstruction strategies, de novo assembly using Trinity uncovered 42,459 unique contigs containing at least a partial protein-coding sequence based on alignment to a reference set of known Actinopterygii sequences. As many as 11,847 of these contigs contained full or near-full length protein sequences, providing broad coverage of the proteome. A variety of non-coding RNA sequences were also identified and annotated, including conserved long intergenic non-coding RNA and other long non-coding RNA observed previously to be expressed in adult zebrafish (Danio rerio) brain, as well as a variety of miRNA, snRNA, and snoRNA. Shotgun proteomics confirmed translation of open reading frames from over 2,000 transcripts, including alternative splice variants. Assignment of tandem mass spectra was greatly improved by use of the assembly compared to databases of sequences from closely related organisms. The assembly and raw reads have been deposited at DDBJ/EMBL/GenBank under the accession number GBKR00000000. Tandem mass spectrometry data is available via ProteomeXchange with identifier PXD001285. Presented here is the first release of an annotated de novo transcriptome assembly from Apteronotus leptorhynchus, providing a broad overview of RNA expressed in central nervous system tissue. The assembly, which includes substantial coverage of a wide variety of both protein coding and non-coding transcripts, will allow the development of better tools to understand the mechanisms underlying unique characteristics of the knifefish model system, such as their tremendous regenerative capacity and negligible brain senescence.

Qualitatively different coding of symbolic and nonsymbolic numbers in the human brain.

PubMed

Lyons, Ian M; Ansari, Daniel; Beilock, Sian L

2015-02-01

Are symbolic and nonsymbolic numbers coded differently in the brain? Neuronal data indicate that overlap in numerical tuning curves is a hallmark of the approximate, analogue nature of nonsymbolic number representation. Consequently, patterns of fMRI activity should be more correlated when the representational overlap between two numbers is relatively high. In bilateral intraparietal sulci (IPS), for nonsymbolic numbers, the pattern of voxelwise correlations between pairs of numbers mirrored the amount of overlap in their tuning curves under the assumption of approximate, analogue coding. In contrast, symbolic numbers showed a flat field of modest correlations more consistent with discrete, categorical representation (no systematic overlap between numbers). Directly correlating activity patterns for a given number across formats (e.g., the numeral "6" with six dots) showed no evidence of shared symbolic and nonsymbolic number-specific representations. Overall (univariate) activity in bilateral IPS was well fit by the log of the number being processed for both nonsymbolic and symbolic numbers. IPS activity is thus sensitive to numerosity regardless of format; however, the nature in which symbolic and nonsymbolic numbers are encoded is fundamentally different. © 2014 Wiley Periodicals, Inc.

Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum.

PubMed

Diederen, Kelly M J; Ziauddeen, Hisham; Vestergaard, Martin D; Spencer, Tom; Schultz, Wolfram; Fletcher, Paul C

2017-02-15

Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness. SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that are modulated by the brain chemical dopamine are sensitive to reward variability. Here, we aimed to directly relate dopamine to learning about variable rewards, and the neural encoding of associated teaching signals. We perturbed dopamine in healthy individuals using dopaminergic medication and asked them to predict variable rewards while we made brain scans. Dopamine perturbations impaired learning and the neural encoding of reward variability, thus establishing a direct link between dopamine and adaptation to reward variability. These results aid our understanding of clinical conditions associated with dopaminergic dysfunction, such as psychosis. Copyright © 2017 Diederen et al.

Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity.

PubMed

Koyluoglu, Onur Ozan; Pertzov, Yoni; Manohar, Sanjay; Husain, Masud; Fiete, Ila R

2017-09-07

It is widely believed that persistent neural activity underlies short-term memory. Yet, as we show, the degradation of information stored directly in such networks behaves differently from human short-term memory performance. We build a more general framework where memory is viewed as a problem of passing information through noisy channels whose degradation characteristics resemble those of persistent activity networks. If the brain first encoded the information appropriately before passing the information into such networks, the information can be stored substantially more faithfully. Within this framework, we derive a fundamental lower-bound on recall precision, which declines with storage duration and number of stored items. We show that human performance, though inconsistent with models involving direct (uncoded) storage in persistent activity networks, can be well-fit by the theoretical bound. This finding is consistent with the view that if the brain stores information in patterns of persistent activity, it might use codes that minimize the effects of noise, motivating the search for such codes in the brain.

Navigating the Neural Space in Search of the Neural Code.

PubMed

Jazayeri, Mehrdad; Afraz, Arash

2017-03-08

The advent of powerful perturbation tools, such as optogenetics, has created new frontiers for probing causal dependencies in neural and behavioral states. These approaches have significantly enhanced the ability to characterize the contribution of different cells and circuits to neural function in health and disease. They have shifted the emphasis of research toward causal interrogations and increased the demand for more precise and powerful tools to control and manipulate neural activity. Here, we clarify the conditions under which measurements and perturbations support causal inferences. We note that the brain functions at multiple scales and that causal dependencies may be best inferred with perturbation tools that interface with the system at the appropriate scale. Finally, we develop a geometric framework to facilitate the interpretation of causal experiments when brain perturbations do or do not respect the intrinsic patterns of brain activity. We describe the challenges and opportunities of applying perturbations in the presence of dynamics, and we close with a general perspective on navigating the activity space of neurons in the search for neural codes. Copyright © 2017 Elsevier Inc. All rights reserved.

Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity

PubMed Central

Pertzov, Yoni; Manohar, Sanjay; Husain, Masud; Fiete, Ila R

2017-01-01

It is widely believed that persistent neural activity underlies short-term memory. Yet, as we show, the degradation of information stored directly in such networks behaves differently from human short-term memory performance. We build a more general framework where memory is viewed as a problem of passing information through noisy channels whose degradation characteristics resemble those of persistent activity networks. If the brain first encoded the information appropriately before passing the information into such networks, the information can be stored substantially more faithfully. Within this framework, we derive a fundamental lower-bound on recall precision, which declines with storage duration and number of stored items. We show that human performance, though inconsistent with models involving direct (uncoded) storage in persistent activity networks, can be well-fit by the theoretical bound. This finding is consistent with the view that if the brain stores information in patterns of persistent activity, it might use codes that minimize the effects of noise, motivating the search for such codes in the brain. PMID:28879851

Energy coding in biological neural networks

PubMed Central

Zhang, Zhikang

2007-01-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, we present a brand new scientific theory that offers an unique mechanism for brain information processing. We demonstrate that the neural coding produced by the activity of the brain is well described by our theory of energy coding. Due to the energy coding model’s ability to reveal mechanisms of brain information processing based upon known biophysical properties, we can not only reproduce various experimental results of neuro-electrophysiology, but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, we estimate that the theory has very important consequences for quantitative research of cognitive function. PMID:19003513

On initial Brain Activity Mapping of episodic and semantic memory code in the hippocampus.

PubMed

Tsien, Joe Z; Li, Meng; Osan, Remus; Chen, Guifen; Lin, Longian; Wang, Phillip Lei; Frey, Sabine; Frey, Julietta; Zhu, Dajiang; Liu, Tianming; Zhao, Fang; Kuang, Hui

2013-10-01

It has been widely recognized that the understanding of the brain code would require large-scale recording and decoding of brain activity patterns. In 2007 with support from Georgia Research Alliance, we have launched the Brain Decoding Project Initiative with the basic idea which is now similarly advocated by BRAIN project or Brain Activity Map proposal. As the planning of the BRAIN project is currently underway, we share our insights and lessons from our efforts in mapping real-time episodic memory traces in the hippocampus of freely behaving mice. We show that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics. We also provide an example of how the carefully designed, sometime thinking-outside-the-box, behavioral paradigms can be highly instrumental to the unraveling of memory-coding cell assembly organizing principle in the hippocampus. Our observations to date have led us to conclude that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

On Initial Brain Activity Mapping of Associative Memory Code in the Hippocampus

PubMed Central

Tsien, Joe Z.; Li, Meng; Osan, Remus; Chen, Guifen; Lin, Longian; Lei Wang, Phillip; Frey, Sabine; Frey, Julietta; Zhu, Dajiang; Liu, Tianming; Zhao, Fang; Kuang, Hui

2013-01-01

It has been widely recognized that the understanding of the brain code would require large-scale recording and decoding of brain activity patterns. In 2007 with support from Georgia Research Alliance, we have launched the Brain Decoding Project Initiative with the basic idea which is now similarly advocated by BRAIN project or Brain Activity Map proposal. As the planning of the BRAIN project is currently underway, we share our insights and lessons from our efforts in mapping real-time episodic memory traces in the hippocampus of freely behaving mice. We show that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics. We also provide an example of how the carefully designed, sometime thinking-outside-the-box, behavioral paradigms can be highly instrumental to the unraveling of memory-coding cell assembly organizing principle in the hippocampus. Our observations to date have led us to conclude that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination. PMID:23838072

Evolvix BEST Names for semantic reproducibility across code2brain interfaces

PubMed Central

Scheuer, Katherine S.; Keel, Seth A.; Vyas, Vaibhav; Liblit, Ben; Hanlon, Bret; Ferris, Michael C.; Yin, John; Dutra, Inês; Pietsch, Anthony; Javid, Christine G.; Moog, Cecilia L.; Meyer, Jocelyn; Dresel, Jerdon; McLoone, Brian; Loberger, Sonya; Movaghar, Arezoo; Gilchrist‐Scott, Morgaine; Sabri, Yazeed; Sescleifer, Dave; Pereda‐Zorrilla, Ivan; Zietlow, Andrew; Smith, Rodrigo; Pietenpol, Samantha; Goldfinger, Jacob; Atzen, Sarah L.; Freiberg, Erika; Waters, Noah P.; Nusbaum, Claire; Nolan, Erik; Hotz, Alyssa; Kliman, Richard M.; Mentewab, Ayalew; Fregien, Nathan; Loewe, Martha

2016-01-01

Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general‐purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long‐term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder‐brains to reader‐brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core. PMID:27918836

Effects of isoflurane anesthesia on ensemble patterns of Ca2+ activity in mouse v1: reduced direction selectivity independent of increased correlations in cellular activity.

PubMed

Goltstein, Pieter M; Montijn, Jorrit S; Pennartz, Cyriel M A

2015-01-01

Anesthesia affects brain activity at the molecular, neuronal and network level, but it is not well-understood how tuning properties of sensory neurons and network connectivity change under its influence. Using in vivo two-photon calcium imaging we matched neuron identity across episodes of wakefulness and anesthesia in the same mouse and recorded spontaneous and visually evoked activity patterns of neuronal ensembles in these two states. Correlations in spontaneous patterns of calcium activity between pairs of neurons were increased under anesthesia. While orientation selectivity remained unaffected by anesthesia, this treatment reduced direction selectivity, which was attributable to an increased response to the null-direction. As compared to anesthesia, populations of V1 neurons coded more mutual information on opposite stimulus directions during wakefulness, whereas information on stimulus orientation differences was lower. Increases in correlations of calcium activity during visual stimulation were correlated with poorer population coding, which raised the hypothesis that the anesthesia-induced increase in correlations may be causal to degrading directional coding. Visual stimulation under anesthesia, however, decorrelated ongoing activity patterns to a level comparable to wakefulness. Because visual stimulation thus appears to 'break' the strength of pairwise correlations normally found in spontaneous activity under anesthesia, the changes in correlational structure cannot explain the awake-anesthesia difference in direction coding. The population-wide decrease in coding for stimulus direction thus occurs independently of anesthesia-induced increments in correlations of spontaneous activity.

Effects of Isoflurane Anesthesia on Ensemble Patterns of Ca2+ Activity in Mouse V1: Reduced Direction Selectivity Independent of Increased Correlations in Cellular Activity

PubMed Central

Goltstein, Pieter M.; Montijn, Jorrit S.; Pennartz, Cyriel M. A.

2015-01-01

Anesthesia affects brain activity at the molecular, neuronal and network level, but it is not well-understood how tuning properties of sensory neurons and network connectivity change under its influence. Using in vivo two-photon calcium imaging we matched neuron identity across episodes of wakefulness and anesthesia in the same mouse and recorded spontaneous and visually evoked activity patterns of neuronal ensembles in these two states. Correlations in spontaneous patterns of calcium activity between pairs of neurons were increased under anesthesia. While orientation selectivity remained unaffected by anesthesia, this treatment reduced direction selectivity, which was attributable to an increased response to the null-direction. As compared to anesthesia, populations of V1 neurons coded more mutual information on opposite stimulus directions during wakefulness, whereas information on stimulus orientation differences was lower. Increases in correlations of calcium activity during visual stimulation were correlated with poorer population coding, which raised the hypothesis that the anesthesia-induced increase in correlations may be causal to degrading directional coding. Visual stimulation under anesthesia, however, decorrelated ongoing activity patterns to a level comparable to wakefulness. Because visual stimulation thus appears to ‘break’ the strength of pairwise correlations normally found in spontaneous activity under anesthesia, the changes in correlational structure cannot explain the awake-anesthesia difference in direction coding. The population-wide decrease in coding for stimulus direction thus occurs independently of anesthesia-induced increments in correlations of spontaneous activity. PMID:25706867

Connectivity in the human brain dissociates entropy and complexity of auditory inputs☆

PubMed Central

Nastase, Samuel A.; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-01-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. PMID:25536493

Graph analysis of functional brain networks: practical issues in translational neuroscience

PubMed Central

De Vico Fallani, Fabrizio; Richiardi, Jonas; Chavez, Mario; Achard, Sophie

2014-01-01

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. PMID:25180301

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Beyond Molecular Codes: Simple Rules to Wire Complex Brains

PubMed Central

Hassan, Bassem A.; Hiesinger, P. Robin

2015-01-01

Summary Molecular codes, like postal zip codes, are generally considered a robust way to ensure the specificity of neuronal target selection. However, a code capable of unambiguously generating complex neural circuits is difficult to conceive. Here, we re-examine the notion of molecular codes in the light of developmental algorithms. We explore how molecules and mechanisms that have been considered part of a code may alternatively implement simple pattern formation rules sufficient to ensure wiring specificity in neural circuits. This analysis delineates a pattern-based framework for circuit construction that may contribute to our understanding of brain wiring. PMID:26451480

The mismatch negativity: A review of underlying mechanisms

PubMed Central

Garrido, Marta I.; Kilner, James M.; Stephan, Klaas E.; Friston, Karl J.

2009-01-01

The mismatch negativity (MMN) is a brain response to violations of a rule, established by a sequence of sensory stimuli (typically in the auditory domain) [Näätänen R. Attention and brain function. Hillsdale, NJ: Lawrence Erlbaum; 1992]. The MMN reflects the brain’s ability to perform automatic comparisons between consecutive stimuli and provides an electrophysiological index of sensory learning and perceptual accuracy. Although the MMN has been studied extensively, the neurophysiological mechanisms underlying the MMN are not well understood. Several hypotheses have been put forward to explain the generation of the MMN; amongst these accounts, the “adaptation hypothesis” and the “model adjustment hypothesis” have received the most attention. This paper presents a review of studies that focus on neuronal mechanisms underlying the MMN generation, discusses the two major explanatory hypotheses, and proposes predictive coding as a general framework that attempts to unify both. PMID:19181570

Multiple Primary and Histology Coding Rules - SEER

Cancer.gov

Download the coding manual and training resources for cases diagnosed from 2007 to 2017. Sites included are lung, breast, colon, melanoma of the skin, head and neck, kidney, renal pelvis/ureter/bladder, benign brain, and malignant brain.

Defining traumatic brain injury in children and youth using international classification of diseases version 10 codes: a systematic review protocol.

PubMed

Chan, Vincy; Thurairajah, Pravheen; Colantonio, Angela

2013-11-13

Although healthcare administrative data are commonly used for traumatic brain injury research, there is currently no consensus or consistency on using the International Classification of Diseases version 10 codes to define traumatic brain injury among children and youth. This protocol is for a systematic review of the literature to explore the range of International Classification of Diseases version 10 codes that are used to define traumatic brain injury in this population. The databases MEDLINE, MEDLINE In-Process, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Database of Systematic Reviews will be systematically searched. Grey literature will be searched using Grey Matters and Google. Reference lists of included articles will also be searched. Articles will be screened using predefined inclusion and exclusion criteria and all full-text articles that meet the predefined inclusion criteria will be included for analysis. The study selection process and reasons for exclusion at the full-text level will be presented using a PRISMA study flow diagram. Information on the data source of included studies, year and location of study, age of study population, range of incidence, and study purpose will be abstracted into a separate table and synthesized for analysis. All International Classification of Diseases version 10 codes will be listed in tables and the codes that are used to define concussion, acquired traumatic brain injury, head injury, or head trauma will be identified. The identification of the optimal International Classification of Diseases version 10 codes to define this population in administrative data is crucial, as it has implications for policy, resource allocation, planning of healthcare services, and prevention strategies. It also allows for comparisons across countries and studies. This protocol is for a review that identifies the range and most common diagnoses used to conduct surveillance for traumatic brain injury in children and youth. This is an important first step in reaching an appropriate definition using International Classification of Diseases version 10 codes and can inform future work on reaching consensus on the codes to define traumatic brain injury for this vulnerable population.

Coherent activity between brain regions that code for value is linked to the malleability of human behavior

PubMed Central

Cooper, Nicole; Bassett, Danielle S.; Falk, Emily B.

2017-01-01

Brain activity in medial prefrontal cortex (MPFC) during exposure to persuasive messages can predict health behavior change. This brain-behavior relationship has been linked to areas of MPFC previously associated with self-related processing; however, the mechanism underlying this relationship is unclear. We explore two components of self-related processing – self-reflection and subjective valuation – and examine coherent activity between relevant networks of brain regions during exposure to health messages encouraging exercise and discouraging sedentary behaviors. We find that objectively logged reductions in sedentary behavior in the following month are linked to functional connectivity within brain regions associated with positive valuation, but not within regions associated with self-reflection on personality traits. Furthermore, functional connectivity between valuation regions contributes additional information compared to average brain activation within single brain regions. These data support an account in which MPFC integrates the value of messages to the self during persuasive health messaging and speak to broader questions of how humans make decisions about how to behave. PMID:28240271

A novel Morse code-inspired method for multiclass motor imagery brain-computer interface (BCI) design.

PubMed

Jiang, Jun; Zhou, Zongtan; Yin, Erwei; Yu, Yang; Liu, Yadong; Hu, Dewen

2015-11-01

Motor imagery (MI)-based brain-computer interfaces (BCIs) allow disabled individuals to control external devices voluntarily, helping us to restore lost motor functions. However, the number of control commands available in MI-based BCIs remains limited, limiting the usability of BCI systems in control applications involving multiple degrees of freedom (DOF), such as control of a robot arm. To address this problem, we developed a novel Morse code-inspired method for MI-based BCI design to increase the number of output commands. Using this method, brain activities are modulated by sequences of MI (sMI) tasks, which are constructed by alternately imagining movements of the left or right hand or no motion. The codes of the sMI task was detected from EEG signals and mapped to special commands. According to permutation theory, an sMI task with N-length allows 2 × (2(N)-1) possible commands with the left and right MI tasks under self-paced conditions. To verify its feasibility, the new method was used to construct a six-class BCI system to control the arm of a humanoid robot. Four subjects participated in our experiment and the averaged accuracy of the six-class sMI tasks was 89.4%. The Cohen's kappa coefficient and the throughput of our BCI paradigm are 0.88 ± 0.060 and 23.5bits per minute (bpm), respectively. Furthermore, all of the subjects could operate an actual three-joint robot arm to grasp an object in around 49.1s using our approach. These promising results suggest that the Morse code-inspired method could be used in the design of BCIs for multi-DOF control. Copyright © 2015 Elsevier Ltd. All rights reserved.

SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing.

PubMed

Tsuchiya, Mariko; Amano, Kojiro; Abe, Masaya; Seki, Misato; Hase, Sumitaka; Sato, Kengo; Sakakibara, Yasubumi

2016-06-15

Deep sequencing of the transcripts of regulatory non-coding RNA generates footprints of post-transcriptional processes. After obtaining sequence reads, the short reads are mapped to a reference genome, and specific mapping patterns can be detected called read mapping profiles, which are distinct from random non-functional degradation patterns. These patterns reflect the maturation processes that lead to the production of shorter RNA sequences. Recent next-generation sequencing studies have revealed not only the typical maturation process of miRNAs but also the various processing mechanisms of small RNAs derived from tRNAs and snoRNAs. We developed an algorithm termed SHARAKU to align two read mapping profiles of next-generation sequencing outputs for non-coding RNAs. In contrast with previous work, SHARAKU incorporates the primary and secondary sequence structures into an alignment of read mapping profiles to allow for the detection of common processing patterns. Using a benchmark simulated dataset, SHARAKU exhibited superior performance to previous methods for correctly clustering the read mapping profiles with respect to 5'-end processing and 3'-end processing from degradation patterns and in detecting similar processing patterns in deriving the shorter RNAs. Further, using experimental data of small RNA sequencing for the common marmoset brain, SHARAKU succeeded in identifying the significant clusters of read mapping profiles for similar processing patterns of small derived RNA families expressed in the brain. The source code of our program SHARAKU is available at http://www.dna.bio.keio.ac.jp/sharaku/, and the simulated dataset used in this work is available at the same link. Accession code: The sequence data from the whole RNA transcripts in the hippocampus of the left brain used in this work is available from the DNA DataBank of Japan (DDBJ) Sequence Read Archive (DRA) under the accession number DRA004502. yasu@bio.keio.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Los Angeles study of residential magnetic fields and childhood brain tumors.

PubMed

Preston-Martin, S; Navidi, W; Thomas, D; Lee, P J; Bowman, J; Pogoda, J

1996-01-15

A measurement study of residential magnetic fields and brain tumors in children that was added onto an ongoing case-control interview study in Los Angeles County, California, include 298 children under age 20 years with a primary brain tumor diagnosed from 1984 to 1991 and 298 control children identified by random digit dialing. Magnetic fields were determined for all Los Angeles homes where these 596 children lived from conception to diagnosis (1,131 homes) by mapping and coding the wiring configurations outside the home and by taking a series of exterior spot and profile measurements. In addition, for a subset of subjects (35%; 211 homes) 24-hour measurements were taken in the child's room and one other room. Although measured fields are consistently highest in the highest of the five wire code categories, fields in homes in this category are much lower in Los Angeles than in Denver, where the code originated. Brain tumor risk appears not to relate to measured fields inside (p for trend for child's room = 0.98) or outside (p for trend for front wall = 0.82) the home. An apparent increase in risk among children living at diagnosis in homes with underground wiring appears to be an artifact introduced by using current controls for historical cases because this apparent excess risk disappeared in an analysis restricted to the later years of the study when cases and controls were accrued concurrently. Our study does not show an overall association of pediatric brain tumors with measured fields, with "very high" wiring configurations, or with any of several other potential sources of exposure, such as use of various electrical appliances, but the prevalence of high fields (> 2 mG) and very high fields (> 3 mG) in Los Angeles homes was too low to detect a moderate effect of the magnitude reported in other studies.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs.

PubMed

Nastase, Samuel A; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

Improving the sensitivity and specificity of the abbreviated injury scale coding system.

PubMed Central

Kramer, C F; Barancik, J I; Thode, H C

1990-01-01

The Abbreviated Injury Scale with Epidemiologic Modifications (AIS 85-EM) was developed to make it possible to code information about anatomic injury types and locations that, although generally available from medical records, is not codable under the standard Abbreviated Injury Scale, published by the American Association for Automotive Medicine in 1985 (AIS 85). In a population-based sample of 3,223 motor vehicle trauma cases, 68 percent of the patients had one or more injuries that were coded to the AIS 85 body region nonspecific category external. When the same patients' injuries were coded using the AIS 85-EM coding procedure, only 15 percent of the patients had injuries that could not be coded to a specific body region. With AIS 85-EM, the proportion of codable head injury cases increased from 16 percent to 37 percent, thereby improving the potential for identifying cases with head and threshold brain injury. The data suggest that body region coding of all injuries is necessary to draw valid and reliable conclusions about changes in injury patterns and their sequelae. The increased specificity of body region coding improves assessments of the efficacy of injury intervention strategies and countermeasure programs using epidemiologic methodology. PMID:2116633

Evolvix BEST Names for semantic reproducibility across code2brain interfaces.

PubMed

Loewe, Laurence; Scheuer, Katherine S; Keel, Seth A; Vyas, Vaibhav; Liblit, Ben; Hanlon, Bret; Ferris, Michael C; Yin, John; Dutra, Inês; Pietsch, Anthony; Javid, Christine G; Moog, Cecilia L; Meyer, Jocelyn; Dresel, Jerdon; McLoone, Brian; Loberger, Sonya; Movaghar, Arezoo; Gilchrist-Scott, Morgaine; Sabri, Yazeed; Sescleifer, Dave; Pereda-Zorrilla, Ivan; Zietlow, Andrew; Smith, Rodrigo; Pietenpol, Samantha; Goldfinger, Jacob; Atzen, Sarah L; Freiberg, Erika; Waters, Noah P; Nusbaum, Claire; Nolan, Erik; Hotz, Alyssa; Kliman, Richard M; Mentewab, Ayalew; Fregien, Nathan; Loewe, Martha

2017-01-01

Names in programming are vital for understanding the meaning of code and big data. We define code2brain (C2B) interfaces as maps in compilers and brains between meaning and naming syntax, which help to understand executable code. While working toward an Evolvix syntax for general-purpose programming that makes accurate modeling easy for biologists, we observed how names affect C2B quality. To protect learning and coding investments, C2B interfaces require long-term backward compatibility and semantic reproducibility (accurate reproduction of computational meaning from coder-brains to reader-brains by code alone). Semantic reproducibility is often assumed until confusing synonyms degrade modeling in biology to deciphering exercises. We highlight empirical naming priorities from diverse individuals and roles of names in different modes of computing to show how naming easily becomes impossibly difficult. We present the Evolvix BEST (Brief, Explicit, Summarizing, Technical) Names concept for reducing naming priority conflicts, test it on a real challenge by naming subfolders for the Project Organization Stabilizing Tool system, and provide naming questionnaires designed to facilitate C2B debugging by improving names used as keywords in a stabilizing programming language. Our experiences inspired us to develop Evolvix using a flipped programming language design approach with some unexpected features and BEST Names at its core. © 2016 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

A review on functional and structural brain connectivity in numerical cognition

PubMed Central

Moeller, Korbinian; Willmes, Klaus; Klein, Elise

2015-01-01

Only recently has the complex anatomo-functional system underlying numerical cognition become accessible to evaluation in the living brain. We identified 27 studies investigating brain connectivity in numerical cognition. Despite considerable heterogeneity regarding methodological approaches, populations investigated, and assessment procedures implemented, the results provided largely converging evidence regarding the underlying brain connectivity involved in numerical cognition. Analyses of both functional/effective as well as structural connectivity have consistently corroborated the assumption that numerical cognition is subserved by a fronto-parietal network including (intra)parietal as well as (pre)frontal cortex sites. Evaluation of structural connectivity has indicated the involvement of fronto-parietal association fibers encompassing the superior longitudinal fasciculus dorsally and the external capsule/extreme capsule system ventrally. Additionally, commissural fibers seem to connect the bilateral intraparietal sulci when number magnitude information is processed. Finally, the identification of projection fibers such as the superior corona radiata indicates connections between cortex and basal ganglia as well as the thalamus in numerical cognition. Studies on functional/effective connectivity further indicated a specific role of the hippocampus. These specifications of brain connectivity augment the triple-code model of number processing and calculation with respect to how gray matter areas associated with specific number-related representations may work together. PMID:26029075

A Plastic Temporal Brain Code for Conscious State Generation

PubMed Central

Dresp-Langley, Birgitta; Durup, Jean

2009-01-01

Consciousness is known to be limited in processing capacity and often described in terms of a unique processing stream across a single dimension: time. In this paper, we discuss a purely temporal pattern code, functionally decoupled from spatial signals, for conscious state generation in the brain. Arguments in favour of such a code include Dehaene et al.'s long-distance reverberation postulate, Ramachandran's remapping hypothesis, evidence for a temporal coherence index and coincidence detectors, and Grossberg's Adaptive Resonance Theory. A time-bin resonance model is developed, where temporal signatures of conscious states are generated on the basis of signal reverberation across large distances in highly plastic neural circuits. The temporal signatures are delivered by neural activity patterns which, beyond a certain statistical threshold, activate, maintain, and terminate a conscious brain state like a bar code would activate, maintain, or inactivate the electronic locks of a safe. Such temporal resonance would reflect a higher level of neural processing, independent from sensorial or perceptual brain mechanisms. PMID:19644552

Functional Interplay between Small Non-Coding RNAs and RNA Modification in the Brain.

PubMed

Leighton, Laura J; Bredy, Timothy W

2018-06-07

Small non-coding RNAs are essential for transcription, translation and gene regulation in all cell types, but are particularly important in neurons, with known roles in neurodevelopment, neuroplasticity and neurological disease. Many small non-coding RNAs are directly involved in the post-transcriptional modification of other RNA species, while others are themselves substrates for modification, or are functionally modulated by modification of their target RNAs. In this review, we explore the known and potential functions of several distinct classes of small non-coding RNAs in the mammalian brain, focusing on the newly recognised interplay between the epitranscriptome and the activity of small RNAs. We discuss the potential for this relationship to influence the spatial and temporal dynamics of gene activation in the brain, and predict that further research in the field of epitranscriptomics will identify interactions between small RNAs and RNA modifications which are essential for higher order brain functions such as learning and memory.

Software for Brain Network Simulations: A Comparative Study

PubMed Central

Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.

2017-01-01

Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with simplified neural and synaptic models and a small network with detailed models. These two case studies allow us to avoid any bias toward a particular software package. The results indicate that BRIAN provides the most concise language for both cases considered. Furthermore, as expected, NEST mostly favors large network models, while NEURON is better suited for detailed models. Overall, the case studies reinforce our general observation that simulators have a bias in the computational performance toward specific types of the brain network models. PMID:28775687

Orthographic Coding: Brain Activation for Letters, Symbols, and Digits.

PubMed

Carreiras, Manuel; Quiñones, Ileana; Hernández-Cabrera, Juan Andrés; Duñabeitia, Jon Andoni

2015-12-01

The present experiment investigates the input coding mechanisms of 3 common printed characters: letters, numbers, and symbols. Despite research in this area, it is yet unclear whether the identity of these 3 elements is processed through the same or different brain pathways. In addition, some computational models propose that the position-in-string coding of these elements responds to general flexible mechanisms of the visual system that are not character-specific, whereas others suggest that the position coding of letters responds to specific processes that are different from those that guide the position-in-string assignment of other types of visual objects. Here, in an fMRI study, we manipulated character position and character identity through the transposition or substitution of 2 internal elements within strings of 4 elements. Participants were presented with 2 consecutive visual strings and asked to decide whether they were the same or different. The results showed: 1) that some brain areas responded more to letters than to numbers and vice versa, suggesting that processing may follow different brain pathways; 2) that the left parietal cortex is involved in letter identity, and critically in letter position coding, specifically contributing to the early stages of the reading process; and that 3) a stimulus-specific mechanism for letter position coding is operating during orthographic processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

PubMed

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

2018-01-16

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

Olfaction

PubMed Central

Pinto1, Jayant M.

2011-01-01

Olfaction represents an ancient, evolutionarily critical physiologic system. In humans, chemosensation mediates safety, nutrition, sensation of pleasure, and general well-being. Factors that affect human olfaction included structural aspects of the nasal cavity that can modulate airflow and therefore odorant access to the olfactory cleft, and inflammatory disease, which can affect both airflow as well as olfactory nerve function. After signals are generated, olfactory information is processed and coded in the olfactory bulb and disseminated to several areas in the brain. The discovery of olfactory receptors by Axel and Buck sparked greater understanding of the molecular basis of olfaction. However, the precise mechanisms used by this system are still under great scrutiny due to the complexity of understanding how an enormous number of chemically diverse odorant molecules are coded into signals understood by the brain. Additionally, it has been challenging to dissect olfactory sensation due to the multiple areas of areas of the brain that receive and modulate this information. Consequently, our knowledge of olfactory dysfunction in humans remains primitive. Aging represents the major cause of loss of smell, although a number of clinical and environmental factors are thought to affect chemosensory function. Treatment options focus on reducing sinonasal inflammation when present, ruling out other treatable causes, and counseling patients on safety measures. PMID:21364221

Non-coding RNA networks underlying cognitive disorders across the lifespan

PubMed Central

Qureshi, Irfan A.; Mehler, Mark F.

2011-01-01

Non-coding RNAs (ncRNAs) and their associated regulatory networks are increasingly being implicated in mediating a complex repertoire of neurobiological functions. Cognitive and behavioral processes are proving to be no exception. Here, we discuss the emergence of many novel, diverse, and rapidly expanding classes and subclasses of short and long ncRNAs. We briefly review the life cycles and molecular functions of these ncRNAs. We also examine how ncRNA circuitry mediates brain development, plasticity, stress responses, and aging and highlight its potential roles in the pathophysiology of cognitive disorders, including neural developmental and age-associated neurodegenerative diseases as well as those that manifest throughout the lifespan. PMID:21411369

Reward Motivation Enhances Task Coding in Frontoparietal Cortex

PubMed Central

Etzel, Joset A.; Cole, Michael W.; Zacks, Jeffrey M.; Kay, Kendrick N.; Braver, Todd S.

2016-01-01

Reward motivation often enhances task performance, but the neural mechanisms underlying such cognitive enhancement remain unclear. Here, we used a multivariate pattern analysis (MVPA) approach to test the hypothesis that motivation-related enhancement of cognitive control results from improved encoding and representation of task set information. Participants underwent two fMRI sessions of cued task switching, the first under baseline conditions, and the second with randomly intermixed reward incentive and no-incentive trials. Information about the upcoming task could be successfully decoded from cue-related activation patterns in a set of frontoparietal regions typically associated with task control. More critically, MVPA classifiers trained on the baseline session had significantly higher decoding accuracy on incentive than non-incentive trials, with decoding improvement mediating reward-related enhancement of behavioral performance. These results strongly support the hypothesis that reward motivation enhances cognitive control, by improving the discriminability of task-relevant information coded and maintained in frontoparietal brain regions. PMID:25601237

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

PubMed

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

2017-02-08

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

Phase-amplitude coupling supports phase coding in human ECoG

PubMed Central

Watrous, Andrew J; Deuker, Lorena; Fell, Juergen; Axmacher, Nikolai

2015-01-01

Prior studies have shown that high-frequency activity (HFA) is modulated by the phase of low-frequency activity. This phenomenon of phase-amplitude coupling (PAC) is often interpreted as reflecting phase coding of neural representations, although evidence for this link is still lacking in humans. Here, we show that PAC indeed supports phase-dependent stimulus representations for categories. Six patients with medication-resistant epilepsy viewed images of faces, tools, houses, and scenes during simultaneous acquisition of intracranial recordings. Analyzing 167 electrodes, we observed PAC at 43% of electrodes. Further inspection of PAC revealed that category specific HFA modulations occurred at different phases and frequencies of the underlying low-frequency rhythm, permitting decoding of categorical information using the phase at which HFA events occurred. These results provide evidence for categorical phase-coded neural representations and are the first to show that PAC coincides with phase-dependent coding in the human brain. DOI: http://dx.doi.org/10.7554/eLife.07886.001 PMID:26308582

Regulating Cortical Oscillations in an Inhibition-Stabilized Network.

PubMed

Jadi, Monika P; Sejnowski, Terrence J

2014-04-21

Understanding the anatomical and functional architecture of the brain is essential for designing neurally inspired intelligent systems. Theoretical and empirical studies suggest a role for narrowband oscillations in shaping the functional architecture of the brain through their role in coding and communication of information. Such oscillations are ubiquitous signals in the electrical activity recorded from the brain. In the cortex, oscillations detected in the gamma range (30-80 Hz) are modulated by behavioral states and sensory features in complex ways. How is this regulation achieved? Although several underlying principles for the genesis of these oscillations have been proposed, a unifying account for their regulation has remained elusive. In a network of excitatory and inhibitory neurons operating in an inhibition-stabilized regime, we show that strongly superlinear responses of inhibitory neurons facilitate bidirectional regulation of oscillation frequency and power. In such a network, the balance of drives to the excitatory and inhibitory populations determines how the power and frequency of oscillations are modulated. The model accounts for the puzzling increase in their frequency with the salience of visual stimuli, and a decrease with their size. Oscillations in our model grow stronger as the mean firing level is reduced, accounting for the size dependence of visually evoked gamma rhythms, and suggesting a role for oscillations in improving the signal-to-noise ratio (SNR) of signals in the brain. Empirically testing such predictions is still challenging, and implementing the proposed coding and communication strategies in neuromorphic systems could assist in our understanding of the biological system.

Optical manipulation for optogenetics: otoliths manipulation in zebrafish (Conference Presentation)

NASA Astrophysics Data System (ADS)

Favre-Bulle, Itia A.; Scott, Ethan; Rubinsztein-Dunlop, Halina

2016-03-01

Otoliths play an important role in Zebrafish in terms of hearing and sense of balance. Many studies have been conducted to understand its structure and function, however the encoding of its movement in the brain remains unknown. Here we developed a noninvasive system capable of manipulating the otolith using optical trapping while we image its behavioral response and brain activity. We'll also present our tools for behavioral response detection and brain activity mapping. Acceleration is sensed through movements of the otoliths in the inner ear. Because experimental manipulations involve movements, electrophysiology and fluorescence microscopy are difficult. As a result, the neural codes underlying acceleration sensation are poorly understood. We have developed a technique for optically trapping otoliths, allowing us to simulate acceleration in stationary larval zebrafish. By applying forces to the otoliths, we can elicit behavioral responses consistent with compensation for perceived acceleration. Since the animal is stationary, we can use calcium imaging in these animals' brains to identify the functional circuits responsible for mediating responses to acceleration in natural settings.

Robust Nonlinear Neural Codes

NASA Astrophysics Data System (ADS)

Yang, Qianli; Pitkow, Xaq

2015-03-01

Most interesting natural sensory stimuli are encoded in the brain in a form that can only be decoded nonlinearly. But despite being a core function of the brain, nonlinear population codes are rarely studied and poorly understood. Interestingly, the few existing models of nonlinear codes are inconsistent with known architectural features of the brain. In particular, these codes have information content that scales with the size of the cortical population, even if that violates the data processing inequality by exceeding the amount of information entering the sensory system. Here we provide a valid theory of nonlinear population codes by generalizing recent work on information-limiting correlations in linear population codes. Although these generalized, nonlinear information-limiting correlations bound the performance of any decoder, they also make decoding more robust to suboptimal computation, allowing many suboptimal decoders to achieve nearly the same efficiency as an optimal decoder. Although these correlations are extremely difficult to measure directly, particularly for nonlinear codes, we provide a simple, practical test by which one can use choice-related activity in small populations of neurons to determine whether decoding is suboptimal or optimal and limited by correlated noise. We conclude by describing an example computation in the vestibular system where this theory applies. QY and XP was supported by a grant from the McNair foundation.

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System.

PubMed

Lesko, Mehdi M; Woodford, Maralyn; White, Laura; O'Brien, Sarah J; Childs, Charmaine; Lecky, Fiona E

2010-08-06

The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data.

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System

PubMed Central

2010-01-01

Background The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Methods Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. Results The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. Conclusion This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data. PMID:20691038

Entracking as a Brain Stem Code for Pitch: The Butte Hypothesis.

PubMed

Joris, Philip X

2016-01-01

The basic nature of pitch is much debated. A robust code for pitch exists in the auditory nerve in the form of an across-fiber pooled interspike interval (ISI) distribution, which resembles the stimulus autocorrelation. An unsolved question is how this representation can be "read out" by the brain. A new view is proposed in which a known brain-stem property plays a key role in the coding of periodicity, which I refer to as "entracking", a contraction of "entrained phase-locking". It is proposed that a scalar rather than vector code of periodicity exists by virtue of coincidence detectors that code the dominant ISI directly into spike rate through entracking. Perfect entracking means that a neuron fires one spike per stimulus-waveform repetition period, so that firing rate equals the repetition frequency. Key properties are invariance with SPL and generalization across stimuli. The main limitation in this code is the upper limit of firing (~ 500 Hz). It is proposed that entracking provides a periodicity tag which is superimposed on a tonotopic analysis: at low SPLs and fundamental frequencies > 500 Hz, a spectral or place mechanism codes for pitch. With increasing SPL the place code degrades but entracking improves and first occurs in neurons with low thresholds for the spectral components present. The prediction is that populations of entracking neurons, extended across characteristic frequency, form plateaus ("buttes") of firing rate tied to periodicity.

Brain disorders and the biological role of music.

PubMed

Clark, Camilla N; Downey, Laura E; Warren, Jason D

2015-03-01

Despite its evident universality and high social value, the ultimate biological role of music and its connection to brain disorders remain poorly understood. Recent findings from basic neuroscience have shed fresh light on these old problems. New insights provided by clinical neuroscience concerning the effects of brain disorders promise to be particularly valuable in uncovering the underlying cognitive and neural architecture of music and for assessing candidate accounts of the biological role of music. Here we advance a new model of the biological role of music in human evolution and the link to brain disorders, drawing on diverse lines of evidence derived from comparative ethology, cognitive neuropsychology and neuroimaging studies in the normal and the disordered brain. We propose that music evolved from the call signals of our hominid ancestors as a means mentally to rehearse and predict potentially costly, affectively laden social routines in surrogate, coded, low-cost form: essentially, a mechanism for transforming emotional mental states efficiently and adaptively into social signals. This biological role of music has its legacy today in the disordered processing of music and mental states that characterizes certain developmental and acquired clinical syndromes of brain network disintegration. © The Author (2014). Published by Oxford University Press.

Brain disorders and the biological role of music

PubMed Central

Clark, Camilla N.; Downey, Laura E.

2015-01-01

Despite its evident universality and high social value, the ultimate biological role of music and its connection to brain disorders remain poorly understood. Recent findings from basic neuroscience have shed fresh light on these old problems. New insights provided by clinical neuroscience concerning the effects of brain disorders promise to be particularly valuable in uncovering the underlying cognitive and neural architecture of music and for assessing candidate accounts of the biological role of music. Here we advance a new model of the biological role of music in human evolution and the link to brain disorders, drawing on diverse lines of evidence derived from comparative ethology, cognitive neuropsychology and neuroimaging studies in the normal and the disordered brain. We propose that music evolved from the call signals of our hominid ancestors as a means mentally to rehearse and predict potentially costly, affectively laden social routines in surrogate, coded, low-cost form: essentially, a mechanism for transforming emotional mental states efficiently and adaptively into social signals. This biological role of music has its legacy today in the disordered processing of music and mental states that characterizes certain developmental and acquired clinical syndromes of brain network disintegration. PMID:24847111

Short-term synaptic plasticity and heterogeneity in neural systems

NASA Astrophysics Data System (ADS)

Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

2013-01-01

We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

Tau mRNA 3'UTR-to-CDS ratio is increased in Alzheimer disease.

PubMed

García-Escudero, Vega; Gargini, Ricardo; Martín-Maestro, Patricia; García, Esther; García-Escudero, Ramón; Avila, Jesús

2017-08-10

Neurons frequently show an imbalance in expression of the 3' untranslated region (3'UTR) relative to the coding DNA sequence (CDS) region of mature messenger RNAs (mRNA). The ratio varies among different cells or parts of the brain. The Map2 protein levels per cell depend on the 3'UTR-to-CDS ratio rather than the total mRNA amount, which suggests powerful regulation of protein expression by 3'UTR sequences. Here we found that MAPT (the microtubule-associated protein tau gene) 3'UTR levels are particularly high with respect to other genes; indeed, the 3'UTR-to-CDS ratio of MAPT is balanced in healthy brain in mouse and human. The tau protein accumulates in Alzheimer diseased brain. We nonetheless observed that the levels of RNA encoding MAPT/tau were diminished in these patients' brains. To explain this apparently contradictory result, we studied MAPT mRNA stoichiometry in coding and non-coding regions, and found that the 3'UTR-to-CDS ratio was higher in the hippocampus of Alzheimer disease patients, with higher tau protein but lower total mRNA levels. Our data indicate that changes in the 3'UTR-to-CDS ratio have a regulatory role in the disease. Future research should thus consider not only mRNA levels, but also the ratios between coding and non-coding regions. Copyright © 2017 Elsevier B.V. All rights reserved.

Revealing representational content with pattern-information fMRI--an introductory guide.

PubMed

Mur, Marieke; Bandettini, Peter A; Kriegeskorte, Nikolaus

2009-03-01

Conventional statistical analysis methods for functional magnetic resonance imaging (fMRI) data are very successful at detecting brain regions that are activated as a whole during specific mental activities. The overall activation of a region is usually taken to indicate involvement of the region in the task. However, such activation analysis does not consider the multivoxel patterns of activity within a brain region. These patterns of activity, which are thought to reflect neuronal population codes, can be investigated by pattern-information analysis. In this framework, a region's multivariate pattern information is taken to indicate representational content. This tutorial introduction motivates pattern-information analysis, explains its underlying assumptions, introduces the most widespread methods in an intuitive way, and outlines the basic sequence of analysis steps.

Transcriptomics Profiling of Alzheimer’s Disease Reveal Neurovascular Defects, Altered Amyloid-β Homeostasis, and Deregulated Expression of Long Noncoding RNAs

PubMed Central

Magistri, Marco; Velmeshev, Dmitry; Makhmutova, Madina; Faghihi, Mohammad Ali

2015-01-01

Abstract The underlying genetic variations of late-onset Alzheimer’s disease (LOAD) cases remain largely unknown. A combination of genetic variations with variable penetrance and lifetime epigenetic factors may converge on transcriptomic alterations that drive LOAD pathological process. Transcriptome profiling using deep sequencing technology offers insight into common altered pathways regardless of underpinning genetic or epigenetic factors and thus represents an ideal tool to investigate molecular mechanisms related to the pathophysiology of LOAD. We performed directional RNA sequencing on high quality RNA samples extracted from hippocampi of LOAD and age-matched controls. We further validated our data using qRT-PCR on a larger set of postmortem brain tissues, confirming downregulation of the gene encoding substance P (TAC1) and upregulation of the gene encoding the plasminogen activator inhibitor-1 (SERPINE1). Pathway analysis indicates dysregulation in neural communication, cerebral vasculature, and amyloid-β clearance. Beside protein coding genes, we identified several annotated and non-annotated long noncoding RNAs that are differentially expressed in LOAD brain tissues, three of them are activity-dependent regulated and one is induced by Aβ1 - 42 exposure of human neural cells. Our data provide a comprehensive list of transcriptomics alterations in LOAD hippocampi and warrant holistic approach including both coding and non-coding RNAs in functional studies aimed to understand the pathophysiology of LOAD. PMID:26402107

A thesaurus for a neural population code

PubMed Central

Ganmor, Elad; Segev, Ronen; Schneidman, Elad

2015-01-01

Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns. DOI: http://dx.doi.org/10.7554/eLife.06134.001 PMID:26347983

Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction

PubMed Central

Watanabe, Eiji; Kitaoka, Akiyoshi; Sakamoto, Kiwako; Yasugi, Masaki; Tanaka, Kenta

2018-01-01

The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research. PMID:29599739

Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction.

PubMed

Watanabe, Eiji; Kitaoka, Akiyoshi; Sakamoto, Kiwako; Yasugi, Masaki; Tanaka, Kenta

2018-01-01

The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.

A Neurosemantic Theory of Concrete Noun Representation Based on the Underlying Brain Codes

PubMed Central

Just, Marcel Adam; Cherkassky, Vladimir L.; Aryal, Sandesh; Mitchell, Tom M.

2010-01-01

This article describes the discovery of a set of biologically-driven semantic dimensions underlying the neural representation of concrete nouns, and then demonstrates how a resulting theory of noun representation can be used to identify simple thoughts through their fMRI patterns. We use factor analysis of fMRI brain imaging data to reveal the biological representation of individual concrete nouns like apple, in the absence of any pictorial stimuli. From this analysis emerge three main semantic factors underpinning the neural representation of nouns naming physical objects, which we label manipulation, shelter, and eating. Each factor is neurally represented in 3–4 different brain locations that correspond to a cortical network that co-activates in non-linguistic tasks, such as tool use pantomime for the manipulation factor. Several converging methods, such as the use of behavioral ratings of word meaning and text corpus characteristics, provide independent evidence of the centrality of these factors to the representations. The factors are then used with machine learning classifier techniques to show that the fMRI-measured brain representation of an individual concrete noun like apple can be identified with good accuracy from among 60 candidate words, using only the fMRI activity in the 16 locations associated with these factors. To further demonstrate the generativity of the proposed account, a theory-based model is developed to predict the brain activation patterns for words to which the algorithm has not been previously exposed. The methods, findings, and theory constitute a new approach of using brain activity for understanding how object concepts are represented in the mind. PMID:20084104

A neurosemantic theory of concrete noun representation based on the underlying brain codes.

PubMed

Just, Marcel Adam; Cherkassky, Vladimir L; Aryal, Sandesh; Mitchell, Tom M

2010-01-13

This article describes the discovery of a set of biologically-driven semantic dimensions underlying the neural representation of concrete nouns, and then demonstrates how a resulting theory of noun representation can be used to identify simple thoughts through their fMRI patterns. We use factor analysis of fMRI brain imaging data to reveal the biological representation of individual concrete nouns like apple, in the absence of any pictorial stimuli. From this analysis emerge three main semantic factors underpinning the neural representation of nouns naming physical objects, which we label manipulation, shelter, and eating. Each factor is neurally represented in 3-4 different brain locations that correspond to a cortical network that co-activates in non-linguistic tasks, such as tool use pantomime for the manipulation factor. Several converging methods, such as the use of behavioral ratings of word meaning and text corpus characteristics, provide independent evidence of the centrality of these factors to the representations. The factors are then used with machine learning classifier techniques to show that the fMRI-measured brain representation of an individual concrete noun like apple can be identified with good accuracy from among 60 candidate words, using only the fMRI activity in the 16 locations associated with these factors. To further demonstrate the generativity of the proposed account, a theory-based model is developed to predict the brain activation patterns for words to which the algorithm has not been previously exposed. The methods, findings, and theory constitute a new approach of using brain activity for understanding how object concepts are represented in the mind.

View-Independent Working Memory Representations of Artificial Shapes in Prefrontal and Posterior Regions of the Human Brain.

PubMed

Christophel, Thomas B; Allefeld, Carsten; Endisch, Christian; Haynes, John-Dylan

2018-06-01

Traditional views of visual working memory postulate that memorized contents are stored in dorsolateral prefrontal cortex using an adaptive and flexible code. In contrast, recent studies proposed that contents are maintained by posterior brain areas using codes akin to perceptual representations. An important question is whether this reflects a difference in the level of abstraction between posterior and prefrontal representations. Here, we investigated whether neural representations of visual working memory contents are view-independent, as indicated by rotation-invariance. Using functional magnetic resonance imaging and multivariate pattern analyses, we show that when subjects memorize complex shapes, both posterior and frontal brain regions maintain the memorized contents using a rotation-invariant code. Importantly, we found the representations in frontal cortex to be localized to the frontal eye fields rather than dorsolateral prefrontal cortices. Thus, our results give evidence for the view-independent storage of complex shapes in distributed representations across posterior and frontal brain regions.

The Analysis of Visual Motion: From Computational Theory to Neuronal Mechanisms.

DTIC Science & Technology

1986-12-01

neuronb. Brain Res. 151:599-603. Frost, B . J., Nakayama, K . 1983. Single visual neurons code opposing motion independent JW of direction. Science 220:744...Biol. Cybern. 42:195-204. llolden, A. 1. 1977. Responses of directional ganglion cells in the pigeon retina. J. Physiol., 270:2,53 269. Horn. B . K . P...R. Soc. Iond. B . 223:165-175. 51 % Computations Underlying Motion ttildret ik Koch %V. Longuet-Iliggins, H. C., Prazdny. K . 1981. The interpretation

Bridging the Gap between Brain and Behavior: Cognitive and Neural Mechanisms of Episodic Memory

PubMed Central

Eichenbaum, Howard; Fortin, Norbert J

2005-01-01

The notion that non-human animals are capable of episodic memory is highly controversial. Here, we review recent behavioral work from our laboratory showing that the fundamental features of episodic memory can be observed in rats and that, as in humans, this capacity relies on the hippocampus. We also discuss electrophysiological evidence, from our laboratory and that of others, pointing to associative and sequential coding in hippocampal cells as potential neural mechanisms underlying episodic memory. PMID:16596982

Corticonic models of brain mechanisms underlying cognition and intelligence

NASA Astrophysics Data System (ADS)

Farhat, Nabil H.

The concern of this review is brain theory or more specifically, in its first part, a model of the cerebral cortex and the way it: (a) interacts with subcortical regions like the thalamus and the hippocampus to provide higher-level-brain functions that underlie cognition and intelligence, (b) handles and represents dynamical sensory patterns imposed by a constantly changing environment, (c) copes with the enormous number of such patterns encountered in a lifetime by means of dynamic memory that offers an immense number of stimulus-specific attractors for input patterns (stimuli) to select from, (d) selects an attractor through a process of “conjugation” of the input pattern with the dynamics of the thalamo-cortical loop, (e) distinguishes between redundant (structured) and non-redundant (random) inputs that are void of information, (f) can do categorical perception when there is access to vast associative memory laid out in the association cortex with the help of the hippocampus, and (g) makes use of “computation” at the edge of chaos and information driven annealing to achieve all this. Other features and implications of the concepts presented for the design of computational algorithms and machines with brain-like intelligence are also discussed. The material and results presented suggest, that a Parametrically Coupled Logistic Map network (PCLMN) is a minimal model of the thalamo-cortical complex and that marrying such a network to a suitable associative memory with re-entry or feedback forms a useful, albeit, abstract model of a cortical module of the brain that could facilitate building a simple artificial brain. In the second part of the review, the results of numerical simulations and drawn conclusions in the first part are linked to the most directly relevant works and views of other workers. What emerges is a picture of brain dynamics on the mesoscopic and macroscopic scales that gives a glimpse of the nature of the long sought after brain code underlying intelligence and other higher level brain functions.

The problem with brain GUTs: conflation of different senses of "prediction" threatens metaphysical disaster.

PubMed

Anderson, Michael L; Chemero, Tony

2013-06-01

Clark appears to be moving toward epistemic internalism, which he once rightly rejected. This results from a double over-interpretation of predictive coding's significance. First, Clark argues that predictive coding offers a Grand Unified Theory (GUT) of brain function. Second, he over-reads its epistemic import, perhaps even conflating causal and epistemic mediators. We argue instead for a plurality of neurofunctional principles.

Representational geometry: integrating cognition, computation, and the brain

PubMed Central

Kriegeskorte, Nikolaus; Kievit, Rogier A.

2013-01-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. PMID:23876494

Prediction of brain deformations and risk of traumatic brain injury due to closed-head impact: quantitative analysis of the effects of boundary conditions and brain tissue constitutive model.

PubMed

Wang, Fang; Han, Yong; Wang, Bingyu; Peng, Qian; Huang, Xiaoqun; Miller, Karol; Wittek, Adam

2018-05-12

In this study, we investigate the effects of modelling choices for the brain-skull interface (layers of tissues between the brain and skull that determine boundary conditions for the brain) and the constitutive model of brain parenchyma on the brain responses under violent impact as predicted using computational biomechanics model. We used the head/brain model from Total HUman Model for Safety (THUMS)-extensively validated finite element model of the human body that has been applied in numerous injury biomechanics studies. The computations were conducted using a well-established nonlinear explicit dynamics finite element code LS-DYNA. We employed four approaches for modelling the brain-skull interface and four constitutive models for the brain tissue in the numerical simulations of the experiments on post-mortem human subjects exposed to violent impacts reported in the literature. The brain-skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney-Rivlin hyperviscoelastic, neo-Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain-skull interface and the constitutive model of the brain parenchyma tissues. The results suggest that accurate prediction of deformations within the brain and risk of brain injury due to violent impact using computational biomechanics models may require representation of the meninges and subarachnoidal space with cerebrospinal fluid in the model and application of hyperviscoelastic (preferably Ogden-type) constitutive model for the brain tissue.

Incidence of Traumatic Brain Injury Across the Full Disease Spectrum: A Population-Based Medical Record Review Study

PubMed Central

Leibson, Cynthia L.; Brown, Allen W.; Ransom, Jeanine E.; Diehl, Nancy N.; Perkins, Patricia K.; Mandrekar, Jay; Malec, James F.

2012-01-01

Background Extremely few objective estimates of traumatic brain injury incidence include all ages, both sexes, all injury mechanisms, and the full spectrum from very mild to fatal events. Methods We used unique Rochester Epidemiology Project medical records-linkage resources, including highly sensitive and specific diagnostic coding, to identify all Olmsted County, MN, residents with diagnoses suggestive of traumatic brain injury regardless of age, setting, insurance, or injury mechanism. Provider-linked medical records for a 16% random sample were reviewed for confirmation as definite, probable, possible (symptomatic), or no traumatic brain injury. We estimated incidence per 100,000 person-years for 1987–2000 and compared these record-review rates with rates obtained using Centers for Disease Control and Prevention (CDC) data-systems approach. For the latter, we identified all Olmsted County residents with any CDC-specified diagnosis codes recorded on hospital/emergency department administrative claims or death certificates 1987–2000. Results Of sampled individuals, 1257 met record-review criteria for incident traumatic brain injury; 56% were ages 16–64 years, 56% were male, 53% were symptomatic. Mechanism, sex, and diagnostic certainty differed by age. The incidence rate per 100,000 person-years was 558 (95% confidence interval = 528–590) versus 341 (331–350) using the CDC data system approach. The CDC approach captured only 40% of record-review cases. Seventy-four percent of missing cases presented to hospital/emergency department; none had CDC-specified codes assigned on hospital/emergency department administrative claims or death certificates; 66% were symptomatic. Conclusions Capture of symptomatic traumatic brain injuries requires a wider range of diagnosis codes, plus sampling strategies to avoid high rates of false-positive events. PMID:21968774

Defining pediatric traumatic brain injury using International Classification of Diseases Version 10 Codes: a systematic review.

PubMed

Chan, Vincy; Thurairajah, Pravheen; Colantonio, Angela

2015-02-04

Although healthcare administrative data are commonly used for traumatic brain injury (TBI) research, there is currently no consensus or consistency on the International Classification of Diseases Version 10 (ICD-10) codes used to define TBI among children and youth internationally. This study systematically reviewed the literature to explore the range of ICD-10 codes that are used to define TBI in this population. The identification of the range of ICD-10 codes to define this population in administrative data is crucial, as it has implications for policy, resource allocation, planning of healthcare services, and prevention strategies. The databases MEDLINE, MEDLINE In-Process, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Database of Systematic Reviews were systematically searched. Grey literature was searched using Grey Matters and Google. Reference lists of included articles were also searched for relevant studies. Two reviewers independently screened all titles and abstracts using pre-defined inclusion and exclusion criteria. A full text screen was conducted on articles that met the first screen inclusion criteria. All full text articles that met the pre-defined inclusion criteria were included for analysis in this systematic review. A total of 1,326 publications were identified through the predetermined search strategy and 32 articles/reports met all eligibility criteria for inclusion in this review. Five articles specifically examined children and youth aged 19 years or under with TBI. ICD-10 case definitions ranged from the broad injuries to the head codes (ICD-10 S00 to S09) to concussion only (S06.0). There was overwhelming consensus on the inclusion of ICD-10 code S06, intracranial injury, while codes S00 (superficial injury of the head), S03 (dislocation, sprain, and strain of joints and ligaments of head), and S05 (injury of eye and orbit) were only used by articles that examined head injury, none of which specifically examined children and youth. This review provides evidence for discussion on how best to use ICD codes for different goals. This is an important first step in reaching an appropriate definition and can inform future work on reaching consensus on the ICD-10 codes to define TBI for this vulnerable population.

Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain

PubMed Central

2012-01-01

Background Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. Results By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns. Conclusions Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function. PMID:22651826

Neural underpinnings of music: the polyrhythmic brain.

PubMed

Vuust, Peter; Gebauer, Line K; Witek, Maria A G

2014-01-01

Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has the remarkable ability to move our minds and bodies. Why do certain rhythms make us want to tap our feet, bop our heads or even get up and dance? And how does the brain process rhythmically complex rhythms during our experiences of music? In this chapter, we describe some common forms of rhythmic complexity in music and propose that the theory of predictive coding can explain how rhythm and rhythmic complexity are processed in the brain. We also consider how this theory may reveal why we feel so compelled by rhythmic tension in music. First, musical-theoretical and neuroscientific frameworks of rhythm are presented, in which rhythm perception is conceptualized as an interaction between what is heard ('rhythm') and the brain's anticipatory structuring of music ('the meter'). Second, three different examples of tension between rhythm and meter in music are described: syncopation, polyrhythm and groove. Third, we present the theory of predictive coding of music, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain's Bayesian minimization of the error between the input to the brain and the brain's prior expectations. Fourth, empirical studies of neural and behavioral effects of syncopation, polyrhythm and groove will be reported, and we propose how these studies can be seen as special cases of the predictive coding theory. Finally, we argue that musical rhythm exploits the brain's general principles of anticipation and propose that pleasure from musical rhythm may be a result of such anticipatory mechanisms.

Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology.

PubMed

Schultz, Wolfram

2004-04-01

Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

Revealing pathologies in the liquid crystalline structures of the brain by polarimetric studies (Presentation Recording)

NASA Astrophysics Data System (ADS)

Bakhshetyan, Karen; Melkonyan, Gurgen G.; Galstian, Tigran V.; Saghatelyan, Armen

2015-10-01

Natural or "self" alignment of molecular complexes in living tissue represents many similarities with liquid crystals (LC), which are anisotropic liquids. The orientational characteristics of those complexes may be related to many important functional parameters and their study may reveal important pathologies. The know-how, accumulated thanks to the study of LC materials, may thus be used to this end. One of the traditionally used methods, to characterize those materials, is the polarized light imaging (PLI) that allows for label-free analysis of anisotropic structures in the brain tissue and can be used, for example, for the analysis of myelinated fiber bundles. In the current work, we first attempted to apply the PLI on the mouse histological brain sections to create a map of anisotropic structures using cross-polarizer transmission light. Then we implemented the PLI for comparative study of histological sections of human postmortem brain samples under normal and pathological conditions, such as Parkinson's disease (PD). Imaging the coronal, sagittal and horizontal sections of mouse brain allowed us to create a false color-coded fiber orientation map under polarized light. In human brain datasets for both control and PD groups we measured the pixel intensities in myelin-rich subregions of internal capsule and normalized these to non-myelinated background signal from putamen and caudate nucleus. Quantification of intensities revealed a statistically significant reduction of fiber intensity of PD compared to control subjects (2.801 +/- 0.303 and 3.724 +/- 0.07 respectively; *p < 0.05). Our study confirms the validity of PLI method for visualizing myelinated axonal fibers. This relatively simple technique can become a promising tool for study of neurodegenerative diseases where labeling-free imaging is an important benefit.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

PubMed Central

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

PubMed

Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

The θ-γ neural code.

PubMed

Lisman, John E; Jensen, Ole

2013-03-20

Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes. Copyright © 2013 Elsevier Inc. All rights reserved.

Representational geometry: integrating cognition, computation, and the brain.

PubMed

Kriegeskorte, Nikolaus; Kievit, Rogier A

2013-08-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. Copyright © 2013 Elsevier Ltd. All rights reserved.

Activity of striatal neurons reflects social action and own reward.

PubMed

Báez-Mendoza, Raymundo; Harris, Christopher J; Schultz, Wolfram

2013-10-08

Social interactions provide agents with the opportunity to earn higher benefits than when acting alone and contribute to evolutionary stable strategies. A basic requirement for engaging in beneficial social interactions is to recognize the actor whose movement results in reward. Despite the recent interest in the neural basis of social interactions, the neurophysiological mechanisms identifying the actor in social reward situations are unknown. A brain structure well suited for exploring this issue is the striatum, which plays a role in movement, reward, and goal-directed behavior. In humans, the striatum is involved in social processes related to reward inequity, donations to charity, and observational learning. We studied the neurophysiology of social action for reward in rhesus monkeys performing a reward-giving task. The behavioral data showed that the animals distinguished between their own and the conspecific's reward and knew which individual acted. Striatal neurons coded primarily own reward but rarely other's reward. Importantly, the activations occurred preferentially, and in approximately similar fractions, when either the own or the conspecific's action was followed by own reward. Other striatal neurons showed social action coding without reward. Some of the social action coding disappeared when the conspecific's role was simulated by a computer, confirming a social rather than observational relationship. These findings demonstrate a role of striatal neurons in identifying the social actor and own reward in a social setting. These processes may provide basic building blocks underlying the brain's function in social interactions.

Schaltenbrand-Wahren-Talairach-Tournoux brain atlas registration

NASA Astrophysics Data System (ADS)

Nowinski, Wieslaw L.; Fang, Anthony; Nguyen, Bonnie T.

1995-04-01

The CIeMed electronic brain atlas system contains electronic versions of multiple paper brain atlases with 3D extensions; some other 3D brain atlases are under development. Its primary goal is to provide automatic labeling and quantification of brains. The atlas data are digitized, enhanced, color coded, labeled, and organized into volumes. The atlas system provides several tools for registration, 3D display and real-time manipulation, object extraction/editing, quantification, image processing and analysis, reformatting, anatomical index operations, and file handling. The two main stereotactic atlases provided by the system are electronic and enhanced versions of Atlas of Stereotaxy of the Human Brain by Schaltenbrand and Wahren and Co-Planar Stereotactic Atlas of the Human Brain by Talairach and Tournoux. Each of these atlases has its own strengths and their combination has several advantages. First, a complementary information is merged and provided to the user. Second, the user can register data with a single atlas only, as the Schaltenbrand-Wahren-Talairach-Tournoux registration is data-independent. And last but not least, a direct registration of the Schaltenbrand-Wahren microseries with MRI data may not be feasible, since cerebral deep structures are usually not clearly discernible on MRI images. This paper addresses registration of the Schaltenbrand- Wahren and Talairach-Tournoux brain atlases. A modified proportional grid system transformation is introduced and suitable sets of landmarks identifiable in both atlases are defined. The accuracy of registration is discussed. A continuous navigation in the multi- atlas/patient data space is presented.

The AIS-2005 Revision in Severe Traumatic Brain Injury: Mission Accomplished or Problems for Future Research?

PubMed Central

Carroll, Christopher P.; Cochran, Joseph A.; Price, Janet P.; Guse, Clare E.; Wang, Marjorie C.

2010-01-01

The Abbreviated Injury Scale (AIS) is commonly used to score injury severity and describe types of injuries. In 2005, the AIS-Head section was revised to capture more detailed information about head injuries and to better reflect their clinical severity, but the impact of these changes is largely unknown. The purpose of this study was to compare AIS-1998 and AIS-2005 coding of traumatic brain injuries (TBI) using medical records at a single Level I trauma center. We included patients with severe TBI (Glasgow Coma Scale 3–8) after blunt injury, excluding those who were missing medical records. Detailed descriptions of injuries were collected, then manually coded into AIS-1998 and AIS-2005 by the same Certified AIS Specialist. Compared to AIS-1998, AIS-2005 coded the same injuries with lower severity scores [p<0.01] and with decreased mean and maximum AIS-Head scores [p<0.01]. Of the types of traumatic brain injuries, most of the changes occurred among cerebellar and cerebral injuries. Traumatic hypoxic brain injury secondary to systemic dysfunction was captured by AIS-2005 but not by AIS-1998. However, AIS-2005 captured fewer loss of consciousness cases due to changes in criteria for coding concussive injury. In conclusion, changes from AIS-1998 to AIS-2005 result in significant differences in severity scores and types of injuries captured. This may complicate future TBI research by precluding direct comparison to datasets using AIS-1998. TBIs should be coded into the same AIS-version for comparison or evaluation of trends, and specify which AIS-version is used. PMID:21050606

The AIS-2005 Revision in Severe Traumatic Brain Injury: Mission Accomplished or Problems for Future Research?

PubMed

Carroll, Christopher P; Cochran, Joseph A; Price, Janet P; Guse, Clare E; Wang, Marjorie C

2010-01-01

The Abbreviated Injury Scale (AIS) is commonly used to score injury severity and describe types of injuries. In 2005, the AIS-Head section was revised to capture more detailed information about head injuries and to better reflect their clinical severity, but the impact of these changes is largely unknown. The purpose of this study was to compare AIS-1998 and AIS-2005 coding of traumatic brain injuries (TBI) using medical records at a single Level I trauma center. We included patients with severe TBI (Glasgow Coma Scale 3-8) after blunt injury, excluding those who were missing medical records. Detailed descriptions of injuries were collected, then manually coded into AIS-1998 and AIS-2005 by the same Certified AIS Specialist. Compared to AIS-1998, AIS-2005 coded the same injuries with lower severity scores [p<0.01] and with decreased mean and maximum AIS-Head scores [p<0.01]. Of the types of traumatic brain injuries, most of the changes occurred among cerebellar and cerebral injuries. Traumatic hypoxic brain injury secondary to systemic dysfunction was captured by AIS-2005 but not by AIS-1998. However, AIS-2005 captured fewer loss of consciousness cases due to changes in criteria for coding concussive injury. In conclusion, changes from AIS-1998 to AIS-2005 result in significant differences in severity scores and types of injuries captured. This may complicate future TBI research by precluding direct comparison to datasets using AIS-1998. TBIs should be coded into the same AIS-version for comparison or evaluation of trends, and specify which AIS-version is used.

Superoxide and Nitric Oxide Mechanisms in Traumatic Brain Injury and Hemorrhagic Hypotension.

DTIC Science & Technology

1999-12-01

DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 Words) Traumatic brain injury (TBI) renders the brain vulnerable to secondary ischemia and poor outcome...cerebral blood flow (CBF) and renders the brain vulnerable to secondary ischemia. There is clinical evidence that hypotension contributes to poor...without TBI. These data indicate that even moderate TBI renders the brain sensitive to ischemic injury during relative mild levels of hypotension that

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller

NASA Astrophysics Data System (ADS)

Perdikis, S.; Leeb, R.; Williamson, J.; Ramsay, A.; Tavella, M.; Desideri, L.; Hoogerwerf, E.-J.; Al-Khodairy, A.; Murray-Smith, R.; Millán, J. d. R.

2014-06-01

Objective. While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by the end-users outside laboratory environments. To achieve this primary objective, it is necessary to augment a BCI with a series of components that allow end-users to type text effectively. Approach. This work presents the clinical evaluation of a motor imagery (MI) BCI text-speller, called BrainTree, by six severely disabled end-users and ten able-bodied users. Additionally, we define a generic model of code-based BCI applications, which serves as an analytical tool for evaluation and design. Main results. We show that all users achieved remarkable usability and efficiency outcomes in spelling. Furthermore, our model-based analysis highlights the added value of human-computer interaction techniques and hybrid BCI error-handling mechanisms, and reveals the effects of BCI performances on usability and efficiency in code-based applications. Significance. This study demonstrates the usability potential of code-based MI spellers, with BrainTree being the first to be evaluated by a substantial number of end-users, establishing them as a viable, competitive alternative to other popular BCI spellers. Another major outcome of our model-based analysis is the derivation of a 80% minimum command accuracy requirement for successful code-based application control, revising upwards previous estimates attempted in the literature.

Clinical evaluation of BrainTree, a motor imagery hybrid BCI speller.

PubMed

Perdikis, S; Leeb, R; Williamson, J; Ramsay, A; Tavella, M; Desideri, L; Hoogerwerf, E-J; Al-Khodairy, A; Murray-Smith, R; Millán, J D R

2014-06-01

While brain-computer interfaces (BCIs) for communication have reached considerable technical maturity, there is still a great need for state-of-the-art evaluation by the end-users outside laboratory environments. To achieve this primary objective, it is necessary to augment a BCI with a series of components that allow end-users to type text effectively. This work presents the clinical evaluation of a motor imagery (MI) BCI text-speller, called BrainTree, by six severely disabled end-users and ten able-bodied users. Additionally, we define a generic model of code-based BCI applications, which serves as an analytical tool for evaluation and design. We show that all users achieved remarkable usability and efficiency outcomes in spelling. Furthermore, our model-based analysis highlights the added value of human-computer interaction techniques and hybrid BCI error-handling mechanisms, and reveals the effects of BCI performances on usability and efficiency in code-based applications. This study demonstrates the usability potential of code-based MI spellers, with BrainTree being the first to be evaluated by a substantial number of end-users, establishing them as a viable, competitive alternative to other popular BCI spellers. Another major outcome of our model-based analysis is the derivation of a 80% minimum command accuracy requirement for successful code-based application control, revising upwards previous estimates attempted in the literature.

Lassa-Vesicular Stomatitis Chimeric Virus Safely Destroys Brain Tumors

PubMed Central

Wollmann, Guido; Drokhlyansky, Eugene; Davis, John N.; Cepko, Connie

2015-01-01

ABSTRACT High-grade tumors in the brain are among the deadliest of cancers. Here, we took a promising oncolytic virus, vesicular stomatitis virus (VSV), and tested the hypothesis that the neurotoxicity associated with the virus could be eliminated without blocking its oncolytic potential in the brain by replacing the neurotropic VSV glycoprotein with the glycoprotein from one of five different viruses, including Ebola virus, Marburg virus, lymphocytic choriomeningitis virus (LCMV), rabies virus, and Lassa virus. Based on in vitro infections of normal and tumor cells, we selected two viruses to test in vivo. Wild-type VSV was lethal when injected directly into the brain. In contrast, a novel chimeric virus (VSV-LASV-GPC) containing genes from both the Lassa virus glycoprotein precursor (GPC) and VSV showed no adverse actions within or outside the brain and targeted and completely destroyed brain cancer, including high-grade glioblastoma and melanoma, even in metastatic cancer models. When mice had two brain tumors, intratumoral VSV-LASV-GPC injection in one tumor (glioma or melanoma) led to complete tumor destruction; importantly, the virus moved contralaterally within the brain to selectively infect the second noninjected tumor. A chimeric virus combining VSV genes with the gene coding for the Ebola virus glycoprotein was safe in the brain and also selectively targeted brain tumors but was substantially less effective in destroying brain tumors and prolonging survival of tumor-bearing mice. A tropism for multiple cancer types combined with an exquisite tumor specificity opens a new door to widespread application of VSV-LASV-GPC as a safe and efficacious oncolytic chimeric virus within the brain. IMPORTANCE Many viruses have been tested for their ability to target and kill cancer cells. Vesicular stomatitis virus (VSV) has shown substantial promise, but a key problem is that if it enters the brain, it can generate adverse neurologic consequences, including death. We tested a series of chimeric viruses containing genes coding for VSV, together with a gene coding for the glycoprotein from other viruses, including Ebola virus, Lassa virus, LCMV, rabies virus, and Marburg virus, which was substituted for the VSV glycoprotein gene. Ebola and Lassa chimeric viruses were safe in the brain and targeted brain tumors. Lassa-VSV was particularly effective, showed no adverse side effects even when injected directly into the brain, and targeted and destroyed two different types of deadly brain cancer, including glioblastoma and melanoma. PMID:25878115

On brain activity mapping: insights and lessons from Brain Decoding Project to map memory patterns in the hippocampus.

PubMed

Tsien, Joe Z; Li, Meng; Osan, Remus; Chen, Guifen; Lin, Longnian; Wang, Phillip Lei; Frey, Sabine; Frey, Julietta; Zhu, Dajiang; Liu, Tianming; Zhao, Fang; Kuang, Hui

2013-09-01

The BRAIN project recently announced by the president Obama is the reflection of unrelenting human quest for cracking the brain code, the patterns of neuronal activity that define who we are and what we are. While the Brain Activity Mapping proposal has rightly emphasized on the need to develop new technologies for measuring every spike from every neuron, it might be helpful to consider both the theoretical and experimental aspects that would accelerate our search for the organizing principles of the brain code. Here we share several insights and lessons from the similar proposal, namely, Brain Decoding Project that we initiated since 2007. We provide a specific example in our initial mapping of real-time memory traces from one part of the memory circuit, namely, the CA1 region of the mouse hippocampus. We show how innovative behavioral tasks and appropriate mathematical analyses of large datasets can play equally, if not more, important roles in uncovering the specific-to-general feature-coding cell assembly mechanism by which episodic memory, semantic knowledge, and imagination are generated and organized. Our own experiences suggest that the bottleneck of the Brain Project is not only at merely developing additional new technologies, but also the lack of efficient avenues to disseminate cutting edge platforms and decoding expertise to neuroscience community. Therefore, we propose that in order to harness unique insights and extensive knowledge from various investigators working in diverse neuroscience subfields, ranging from perception and emotion to memory and social behaviors, the BRAIN project should create a set of International and National Brain Decoding Centers at which cutting-edge recording technologies and expertise on analyzing large datasets analyses can be made readily available to the entire community of neuroscientists who can apply and schedule to perform cutting-edge research.

Intravital imaging of dendritic spine plasticity

PubMed Central

Sau Wan Lai, Cora

2014-01-01

Abstract Dendritic spines are the postsynaptic part of most excitatory synapses in the mammalian brain. Recent works have suggested that the structural and functional plasticity of dendritic spines have been associated with information coding and memories. Advances in imaging and labeling techniques enable the study of dendritic spine dynamics in vivo. This perspective focuses on intravital imaging studies of dendritic spine plasticity in the neocortex. I will introduce imaging tools for studying spine dynamics and will further review current findings on spine structure and function under various physiological and pathological conditions. PMID:28243511

Wavelet analysis of head acceleration response under dirac excitation for early oedema detection.

PubMed

Kostopoulos, V; Loutas, T H; Derdas, C; Douzinas, E

2008-04-01

The present work deals with the application of an innovative in-house developed wavelet-based methodology for the analysis of the acceleration responses of a human head complex model as a simulated diffused oedema progresses. The human head complex has been modeled as a structure consisting of three confocal prolate spheroids, whereas the three defined regions by the system of spheroids, from the outside to the inside, represent the scull, the region of cerebrospinal fluid, and the brain tissue. A Dirac-like pulse has been used to excite the human head complex model and the acceleration response of the system has been calculated and analyzed via the wavelet-based methodology. For the purpose of the present analysis, a wave propagation commercial finite element code, LS-DYNA 3D, has been used. The progressive diffused oedema was modeled via consecutive increases in brain volume accompanied by a decrease in brain density. It was shown that even a small increase in brain volume (at the level of 0.5%) can be identified by the effect it has on the vibration characteristics of the human head complex. More precisely, it was found that for some of the wavelet decomposition levels, the energy content changes monotonically as the brain volume increases, thus providing a useful index of monitoring an oncoming brain oedema before any brain damage appears due to uncontrolled intracranial hypertension. For the purpose of the present work and for the levels of brain volume increase considered in the present analysis, no pressure increase was assumed into the cranial vault and, associatively, no brain compliance variation.

Spectral Variability in the Aged Brain during Fine Motor Control

PubMed Central

Quandt, Fanny; Bönstrup, Marlene; Schulz, Robert; Timmermann, Jan E.; Zimerman, Maximo; Nolte, Guido; Hummel, Friedhelm C.

2016-01-01

Physiological aging is paralleled by a decline of fine motor skills accompanied by structural and functional alterations of the underlying brain network. Here, we aim to investigate age-related changes in the spectral distribution of neuronal oscillations during fine skilled motor function. We employ the concept of spectral entropy in order to describe the flatness and peaked-ness of a frequency spectrum to quantify changes in the spectral distribution of the oscillatory motor response in the aged brain. Electroencephalogram was recorded in elderly (n = 32) and young (n = 34) participants who performed either a cued finger movement or a pinch or a whole hand grip task with their dominant right hand. Whereas young participant showed distinct, well-defined movement-related power decreases in the alpha and upper beta band, elderly participants exhibited a flat broadband, frequency-unspecific power desynchronization. This broadband response was reflected by an increase of spectral entropy over sensorimotor and frontal areas in the aged brain. Neuronal activation patterns differed between motor tasks in the young brain, while the aged brain showed a similar activation pattern in all tasks. Moreover, we found a wider recruitment of the cortical motor network in the aged brain. The present study adds to the understanding of age-related changes of neural coding during skilled motor behavior, revealing a less predictable signal with great variability across frequencies in a wide cortical motor network in the aged brain. The increase in entropy in the aged brain could be a reflection of random noise-like activity or could represent a compensatory mechanism that serves a functional role. PMID:28066231

Developmental metaplasticity in neural circuit codes of firing and structure.

PubMed

Baram, Yoram

2017-01-01

Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage. We define a neural circuit connectivity code as an indivisible set of circuit structures generated by membrane and synapse activation and silencing. Synchronous firing patterns under parameter uniformity, and asynchronous circuit firing are shown to be driven, respectively, by membrane and synapse silencing and reactivation, and maintained by the neuronal filtering property. Analytic, graphical and simulation representation of the discrete iteration maps and of the global attractor codes of neural firing rate are found to be consistent with previous empirical neurobiological findings, which have lacked, however, a specific correspondence between firing modes, time constants, circuit connectivity and cortical developmental stages. Copyright © 2016 Elsevier Ltd. All rights reserved.

LncRNA-TP53TG1 Participated in the Stress Response Under Glucose Deprivation in Glioma.

PubMed

Chen, Xin; Gao, Yang; Li, Deheng; Cao, Yiqun; Hao, Bin

2017-12-01

Gliomas are the most common brain tumors of the center nervous system. And long non-coding RNAs (lncRNAs) are non-protein coding transcripts, which have been considered as one type of gene expression regulator for cancer development. In this study, we investigated the role of lncRNA-TP53TG1 in response to glucose deprivation in human gliomas. The expression levels of TP53TG1 in glioma tissues and cells were analyzed by qRT-PCR. In addition, the influence of TP53TG1 on glucose metabolism related genes at the mRNA level during both high and low glucose treatment was detected by qRT-PCR. MTT, clonogenicity assays, and flow cytometry were performed to detect the cell proliferation and cell apoptosis. Furthermore, the migration of glioma cells was examined by Transwell assays. The expression of TP53TG1 was significantly higher in human glioma tissues or cell lines compared with normal brain tissue or NHA. Moreover, TP53TG1 and some tumor glucose metabolism related genes, such as GRP78, LDHA, and IDH1 were up-regulated significantly in U87 and LN18 cells under glucose deprivation. In addition, knockdown of TP53TG1 decreased cell proliferation and migration and down-regulated GRP78 and IDH1 expression levels and up-regulated PKM2 levels in U87 cells under glucose deprivation. However, over-expression of TP53TG1 showed the opposite tendency. Moreover, the effects of TP53TG1 were more remarkable in low glucose than that in high glucose. Our data showed that TP53TG1 under glucose deprivation may promote cell proliferation and migration by influencing the expression of glucose metabolism related genes in glioma. J. Cell. Biochem. 118: 4897-4904, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

MicroRNA-9 Mediates the Cell Apoptosis by Targeting Bcl2l11 in Ischemic Stroke.

PubMed

Wei, Na; Xiao, Lin; Xue, Rui; Zhang, Dandan; Zhou, Jun; Ren, Huayan; Guo, Si; Xu, Jingjing

2016-12-01

Ischemic strokes occur as a result of an obstruction within a blood vessel supplying blood to the brain and accounts for about 87 % of all cases. During the cerebral ischemia, most of the neurons undergo the necrosis and apoptosis upon the exposure to the dramatic blood flow reduction. Although, it is known that both the intrinsic and extrinsic pathways are involved in the neuronal apoptosis of ischemic brain injury. The complex underlying mechanisms remains less known. MicroRNAs are a class of endogenous small non-coding RNAs and the role of miRNAs in the pathophysiology of stroke has been studied. In this study, we found that miR-9 is downregulated in the mice with middle cerebral artery occlusion (MCAO) brain and oxygen-glucose deprivation (OGD) neurons. Application of miR-9 gamer could restore the neurological scores and reduces the infarct volume, brain water content, and the behavioral impairments. Moreover, upregulation of miR-9 suppresses the neuronal apoptosis in MCAO brain and OGD neurons. Furthermore, we identified that Bcl2l11 as the direct target of miR-9 and manipulation of miR-9 induces the corresponding changing of Bcl2l11 protein level. Finally, we found that the protein level of Bcl2l11 is increased in the MCAO brain and OGD neurons. Our study demonstrated the critical role of miR-9 in the neuronal apoptosis of ischemic brain injury.

Comparative analysis of human protein-coding and noncoding RNAs between brain and 10 mixed cell lines by RNA-Seq.

PubMed

Chen, Geng; Yin, Kangping; Shi, Leming; Fang, Yuanzhang; Qi, Ya; Li, Peng; Luo, Jian; He, Bing; Liu, Mingyao; Shi, Tieliu

2011-01-01

In their expression process, different genes can generate diverse functional products, including various protein-coding or noncoding RNAs. Here, we investigated the protein-coding capacities and the expression levels of their isoforms for human known genes, the conservation and disease association of long noncoding RNAs (ncRNAs) with two transcriptome sequencing datasets from human brain tissues and 10 mixed cell lines. Comparative analysis revealed that about two-thirds of the genes expressed between brain and cell lines are the same, but less than one-third of their isoforms are identical. Besides those genes specially expressed in brain and cell lines, about 66% of genes expressed in common encoded different isoforms. Moreover, most genes dominantly expressed one isoform and some genes only generated protein-coding (or noncoding) RNAs in one sample but not in another. We found 282 human genes could encode both protein-coding and noncoding RNAs through alternative splicing in the two samples. We also identified more than 1,000 long ncRNAs, and most of those long ncRNAs contain conserved elements across either 46 vertebrates or 33 placental mammals or 10 primates. Further analysis showed that some long ncRNAs differentially expressed in human breast cancer or lung cancer, several of those differentially expressed long ncRNAs were validated by RT-PCR. In addition, those validated differentially expressed long ncRNAs were found significantly correlated with certain breast cancer or lung cancer related genes, indicating the important biological relevance between long ncRNAs and human cancers. Our findings reveal that the differences of gene expression profile between samples mainly result from the expressed gene isoforms, and highlight the importance of studying genes at the isoform level for completely illustrating the intricate transcriptome.

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2012-01-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2011-12-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Reward Motivation Enhances Task Coding in Frontoparietal Cortex.

PubMed

Etzel, Joset A; Cole, Michael W; Zacks, Jeffrey M; Kay, Kendrick N; Braver, Todd S

2016-04-01

Reward motivation often enhances task performance, but the neural mechanisms underlying such cognitive enhancement remain unclear. Here, we used a multivariate pattern analysis (MVPA) approach to test the hypothesis that motivation-related enhancement of cognitive control results from improved encoding and representation of task set information. Participants underwent two fMRI sessions of cued task switching, the first under baseline conditions, and the second with randomly intermixed reward incentive and no-incentive trials. Information about the upcoming task could be successfully decoded from cue-related activation patterns in a set of frontoparietal regions typically associated with task control. More critically, MVPA classifiers trained on the baseline session had significantly higher decoding accuracy on incentive than non-incentive trials, with decoding improvement mediating reward-related enhancement of behavioral performance. These results strongly support the hypothesis that reward motivation enhances cognitive control, by improving the discriminability of task-relevant information coded and maintained in frontoparietal brain regions. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Activity-Dependent Human Brain Coding/Noncoding Gene Regulatory Networks

PubMed Central

Lipovich, Leonard; Dachet, Fabien; Cai, Juan; Bagla, Shruti; Balan, Karina; Jia, Hui; Loeb, Jeffrey A.

2012-01-01

While most gene transcription yields RNA transcripts that code for proteins, a sizable proportion of the genome generates RNA transcripts that do not code for proteins, but may have important regulatory functions. The brain-derived neurotrophic factor (BDNF) gene, a key regulator of neuronal activity, is overlapped by a primate-specific, antisense long noncoding RNA (lncRNA) called BDNFOS. We demonstrate reciprocal patterns of BDNF and BDNFOS transcription in highly active regions of human neocortex removed as a treatment for intractable seizures. A genome-wide analysis of activity-dependent coding and noncoding human transcription using a custom lncRNA microarray identified 1288 differentially expressed lncRNAs, of which 26 had expression profiles that matched activity-dependent coding genes and an additional 8 were adjacent to or overlapping with differentially expressed protein-coding genes. The functions of most of these protein-coding partner genes, such as ARC, include long-term potentiation, synaptic activity, and memory. The nuclear lncRNAs NEAT1, MALAT1, and RPPH1, composing an RNAse P-dependent lncRNA-maturation pathway, were also upregulated. As a means to replicate human neuronal activity, repeated depolarization of SY5Y cells resulted in sustained CREB activation and produced an inverse pattern of BDNF-BDNFOS co-expression that was not achieved with a single depolarization. RNAi-mediated knockdown of BDNFOS in human SY5Y cells increased BDNF expression, suggesting that BDNFOS directly downregulates BDNF. Temporal expression patterns of other lncRNA-messenger RNA pairs validated the effect of chronic neuronal activity on the transcriptome and implied various lncRNA regulatory mechanisms. lncRNAs, some of which are unique to primates, thus appear to have potentially important regulatory roles in activity-dependent human brain plasticity. PMID:22960213

Olfactory coding: giant inhibitory neuron governs sparse odor codes.

PubMed

Gupta, Nitin; Stopfer, Mark

2011-07-12

Electrophysiological investigations in locusts have revealed that the sparseness of odor representations, in the brain region expected to mediate olfactory learning, is shaped by a unique inhibitory neuron. Copyright © 2011 Elsevier Ltd. All rights reserved.

Computational modeling of temperature elevation and thermoregulatory response in the brains of anesthetized rats locally exposed at 1.5 GHz

NASA Astrophysics Data System (ADS)

Hirata, Akimasa; Masuda, Hiroshi; Kanai, Yuya; Asai, Ryuichi; Fujiwara, Osamu; Arima, Takuji; Kawai, Hiroki; Watanabe, Soichi; Lagroye, Isabelle; Veyret, Bernard

2011-12-01

The dominant effect of human exposures to microwaves is caused by temperature elevation ('thermal effect'). In the safety guidelines/standards, the specific absorption rate averaged over a specific volume is used as a metric for human protection from localized exposure. Further investigation on the use of this metric is required, especially in terms of thermophysiology. The World Health Organization (2006 RF research agenda) has given high priority to research into the extent and consequences of microwave-induced temperature elevation in children. In this study, an electromagnetic-thermal computational code was developed to model electromagnetic power absorption and resulting temperature elevation leading to changes in active blood flow in response to localized 1.457 GHz exposure in rat heads. Both juvenile (4 week old) and young adult (8 week old) rats were considered. The computational code was validated against measurements for 4 and 8 week old rats. Our computational results suggest that the blood flow rate depends on both brain and core temperature elevations. No significant difference was observed between thermophysiological responses in 4 and 8 week old rats under these exposure conditions. The computational model developed herein is thus applicable to set exposure conditions for rats in laboratory investigations, as well as in planning treatment protocols in the thermal therapy.

NIH Scientists Try to Crack the Brain's Memory Codes

MedlinePlus

... Strategy Current Research Research Funded by NINDS Basic Neuroscience Clinical Research Translational Research Research at NINDS Focus ... Diversity Resources Jobs at NINDS Director, Division of Neuroscience Director, NIH BRAIN Initiative® Health Scientist Administrator Channels ...

Concreteness effects in semantic processing: ERP evidence supporting dual-coding theory.

PubMed

Kounios, J; Holcomb, P J

1994-07-01

Dual-coding theory argues that processing advantages for concrete over abstract (verbal) stimuli result from the operation of 2 systems (i.e., imaginal and verbal) for concrete stimuli, rather than just 1 (for abstract stimuli). These verbal and imaginal systems have been linked with the left and right hemispheres of the brain, respectively. Context-availability theory argues that concreteness effects result from processing differences in a single system. The merits of these theories were investigated by examining the topographic distribution of event-related brain potentials in 2 experiments (lexical decision and concrete-abstract classification). The results were most consistent with dual-coding theory. In particular, different scalp distributions of an N400-like negativity were elicited by concrete and abstract words.

Saving Literacy: How Marks Change Minds. A Guide for Professional Caregivers

ERIC Educational Resources Information Center

Sheridan, Susan Rich

2009-01-01

An emphasis on scribbles and drawing as important brain-building behavior makes this book's Neuroconstructive theory of child development and Scribbling/Drawing/Writing practice unique. A child's brain builds itself in response to genetics, DNA codes, and the environment. One of the pre-determined ways a child's brain naturally builds itself is by…

Neonicotinoid-induced impairment of odour coding in the honeybee

PubMed Central

Andrione, Mara; Vallortigara, Giorgio; Antolini, Renzo; Haase, Albrecht

2016-01-01

Exposure to neonicotinoid pesticides is considered one of the possible causes of honeybee (Apis mellifera) population decline. At sublethal doses, these chemicals have been shown to negatively affect a number of behaviours, including performance of olfactory learning and memory, due to their interference with acetylcholine signalling in the mushroom bodies. Here we provide evidence that neonicotinoids can affect odour coding upstream of the mushroom bodies, in the first odour processing centres of the honeybee brain, i.e. the antennal lobes (ALs). In particular, we investigated the effects of imidacloprid, the most common neonicotinoid, in the AL glomeruli via in vivo two-photon calcium imaging combined with pulsed odour stimulation. Following acute imidacloprid treatment, odour-evoked calcium response amplitude in single glomeruli decreases, and at the network level the representations of different odours are no longer separated. This demonstrates that, under neonicotinoid influence, olfactory information might reach the mushroom bodies in a form that is already incorrect. Thus, some of the impairments in olfactory learning and memory caused by neonicotinoids could, in fact, arise from the disruption in odor coding and olfactory discrimination ability of the honey bees. PMID:27905515

Decoding the ubiquitous role of microRNAs in neurogenesis.

PubMed

Nampoothiri, Sreekala S; Rajanikant, G K

2017-04-01

Neurogenesis generates fledgling neurons that mature to form an intricate neuronal circuitry. The delusion on adult neurogenesis was far resolved in the past decade and became one of the largely explored domains to identify multifaceted mechanisms bridging neurodevelopment and neuropathology. Neurogenesis encompasses multiple processes including neural stem cell proliferation, neuronal differentiation, and cell fate determination. Each neurogenic process is specifically governed by manifold signaling pathways, several growth factors, coding, and non-coding RNAs. A class of small non-coding RNAs, microRNAs (miRNAs), is ubiquitously expressed in the brain and has emerged to be potent regulators of neurogenesis. It functions by fine-tuning the expression of specific neurogenic gene targets at the post-transcriptional level and modulates the development of mature neurons from neural progenitor cells. Besides the commonly discussed intrinsic factors, the neuronal morphogenesis is also under the control of several extrinsic temporal cues, which in turn are regulated by miRNAs. This review enlightens on dicer controlled switch from neurogenesis to gliogenesis, miRNA regulation of neuronal maturation and the differential expression of miRNAs in response to various extrinsic cues affecting neurogenesis.

Genome-wide chromatin and gene expression profiling during memory formation and maintenance in adult mice.

PubMed

Centeno, Tonatiuh Pena; Shomroni, Orr; Hennion, Magali; Halder, Rashi; Vidal, Ramon; Rahman, Raza-Ur; Bonn, Stefan

2016-10-11

Recent evidence suggests that the formation and maintenance of memory requires epigenetic changes. In an effort to understand the spatio-temporal extent of learning and memory-related epigenetic changes we have charted genome-wide histone and DNA methylation profiles, in two different brain regions, two cell types, and three time-points, before and after learning. In this data descriptor we provide detailed information on data generation, give insights into the rationale of experiments, highlight necessary steps to assess data quality, offer guidelines for future use of the data and supply ready-to-use code to replicate the analysis results. The data provides a blueprint of the gene regulatory network underlying short- and long-term memory formation and maintenance. This 'healthy' gene regulatory network of learning can now be compared to changes in neurological or psychiatric diseases, providing mechanistic insights into brain disorders and highlighting potential therapeutic avenues.

Objects tell us what action we can expect: dissociating brain areas for retrieval and exploitation of action knowledge during action observation in fMRI

PubMed Central

Schubotz, Ricarda I.; Wurm, Moritz F.; Wittmann, Marco K.; von Cramon, D. Yves

2014-01-01

Objects are reminiscent of actions often performed with them: knife and apple remind us on peeling the apple or cutting it. Mnemonic representations of object-related actions (action codes) evoked by the sight of an object may constrain and hence facilitate recognition of unrolling actions. The present fMRI study investigated if and how action codes influence brain activation during action observation. The average number of action codes (NAC) of 51 sets of objects was rated by a group of n = 24 participants. In an fMRI study, different volunteers were asked to recognize actions performed with the same objects presented in short videos. To disentangle areas reflecting the storage of action codes from those exploiting them, we showed object-compatible and object-incompatible (pantomime) actions. Areas storing action codes were considered to positively co-vary with NAC in both object-compatible and object-incompatible action; due to its role in tool-related tasks, we here hypothesized left anterior inferior parietal cortex (aIPL). In contrast, areas exploiting action codes were expected to show this correlation only in object-compatible but not incompatible action, as only object-compatible actions match one of the active action codes. For this interaction, we hypothesized ventrolateral premotor cortex (PMv) to join aIPL due to its role in biasing competition in IPL. We found left anterior intraparietal sulcus (IPS) and left posterior middle temporal gyrus (pMTG) to co-vary with NAC. In addition to these areas, action codes increased activity in object-compatible action in bilateral PMv, right IPS, and lateral occipital cortex (LO). Findings suggest that during action observation, the brain derives possible actions from perceived objects, and uses this information to shape action recognition. In particular, the number of expectable actions quantifies the activity level at PMv, IPL, and pMTG, but only PMv reflects their biased competition while observed action unfolds. PMID:25009519

On the Biological Plausibility of Grandmother Cells: Implications for Neural Network Theories in Psychology and Neuroscience

ERIC Educational Resources Information Center

Bowers, Jeffrey S.

2009-01-01

A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated…

On the biological plausibility of grandmother cells: implications for neural network theories in psychology and neuroscience.

PubMed

Bowers, Jeffrey S

2009-01-01

A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned in connectionist models and neural coding in brain and often dismiss localist (grandmother cell) theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes (sparse and coarse coding) and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models.

The Impact of Reading Intervention on Brain Responses Underlying Language in Children With Autism.

PubMed

Murdaugh, Donna L; Deshpande, Hrishikesh D; Kana, Rajesh K

2016-01-01

Deficits in language comprehension have been widely reported in children with autism spectrum disorders (ASD), with behavioral and neuroimaging studies finding increased reliance on visuospatial processing to aid in language comprehension. However, no study to date, has taken advantage of this strength in visuospatial processing to improve language comprehension difficulties in ASD. This study used a translational neuroimaging approach to test the role of a visual imagery-based reading intervention in improving the brain circuitry underlying language processing in children with ASD. Functional magnetic resonance imaging (MRI), in a longitudinal study design, was used to investigate intervention-related change in sentence comprehension, brain activation, and functional connectivity in three groups of participants (age 8-13 years): an experimental group of ASD children (ASD-EXP), a wait-list control group of ASD children (ASD-WLC), and a group of typically developing control children. After intervention, the ASD-EXP group showed significant increase in activity in visual and language areas and right-hemisphere language area homologues, putamen, and thalamus, suggestive of compensatory routes to increase proficiency in reading comprehension. Additionally, ASD children who had the most improvement in reading comprehension after intervention showed greater functional connectivity between left-hemisphere language areas, the middle temporal gyrus and inferior frontal gyrus while reading high imagery sentences. Thus, the findings of this study, which support the principles of dual coding theory [Paivio 2007], suggest the potential of a strength-based reading intervention in changing brain responses and facilitating better reading comprehension in ASD children. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Delineation of the Clinical, Molecular and Cellular Aspects of Novel JAM3 Mutations Underlying the Autosomal Recessive Hemorrhagic Destruction of the Brain, Subependymal Calcification and Congenital Cataracts

PubMed Central

Akawi, Nadia A.; Canpolat, Fuat E.; White, Susan M.; Quilis-Esquerra, Josep; Sanchez, Martin Morales; Gamundi, Maria José; Mochida, Ganeshwaran H.; Walsh, Christopher A.; Ali, Bassam R.; Al-Gazali, Lihadh

2014-01-01

We have recently shown that the hemorrhagic destruction of the brain, subependymal calcification and congenital cataracts is caused by biallelic mutations in the gene encoding junctional adhesion molecule 3 (JAM3) protein. Affected members from three new families underwent detailed clinical examination including imaging of the brain. Affected individuals presented with a distinctive phenotype comprising hemorrhagic destruction of the brain, subependymal calcification and congenital cataracts. All patients had a catastrophic clinical course resulting in death in 7 out of 10 affected individuals. Sequencing the coding exons of JAM3 revealed three novel homozygous mutations: c.2T>G (p.M1R), c.346G>A (p.E116K) and c.656G>A (p.C219Y). The p.M1R mutation affects the start codon and therefore is predicted to impair protein synthesis. Cellular studies showed that the p.C219Y mutation resulted in a significant retention of the mutated protein in the endoplasmic reticulum, suggesting a trafficking defect. The p.E116K mutant traffics normally to the plasma membrane as the wild type and may have lost its function due to the lack of interaction with an interacting partner. Our data further support the importance of JAM3 in the development and function of the vascular system and the brain. PMID:23255084

Brain tumor classification and segmentation using sparse coding and dictionary learning.

PubMed

Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

2016-08-01

This paper presents a novel fully automatic framework for multi-class brain tumor classification and segmentation using a sparse coding and dictionary learning method. The proposed framework consists of two steps: classification and segmentation. The classification of the brain tumors is based on brain topology and texture. The segmentation is based on voxel values of the image data. Using K-SVD, two types of dictionaries are learned from the training data and their associated ground truth segmentation: feature dictionary and voxel-wise coupled dictionaries. The feature dictionary consists of global image features (topological and texture features). The coupled dictionaries consist of coupled information: gray scale voxel values of the training image data and their associated label voxel values of the ground truth segmentation of the training data. For quantitative evaluation, the proposed framework is evaluated using different metrics. The segmentation results of the brain tumor segmentation (MICCAI-BraTS-2013) database are evaluated using five different metric scores, which are computed using the online evaluation tool provided by the BraTS-2013 challenge organizers. Experimental results demonstrate that the proposed approach achieves an accurate brain tumor classification and segmentation and outperforms the state-of-the-art methods.

Hypoxia in CNS Pathologies: Emerging Role of miRNA-Based Neurotherapeutics and Yoga Based Alternative Therapies

PubMed Central

Minhas, Gillipsie; Mathur, Deepali; Ragavendrasamy, Balakrishnan; Sharma, Neel K.; Paanu, Viraaj; Anand, Akshay

2017-01-01

Cellular respiration is a vital process for the existence of life. Any condition that results in deprivation of oxygen (also termed as hypoxia) may eventually lead to deleterious effects on the functioning of tissues. Brain being the highest consumer of oxygen is prone to increased risk of hypoxia-induced neurological insults. This in turn has been associated with many diseases of central nervous system (CNS) such as stroke, Alzheimer's, encephalopathy etc. Although several studies have investigated the pathophysiological mechanisms underlying ischemic/hypoxic CNS diseases, the knowledge about protective therapeutic strategies to ameliorate the affected neuronal cells is meager. This has augmented the need to improve our understanding of the hypoxic and ischemic events occurring in the brain and identify novel and alternate treatment modalities for such insults. MicroRNA (miRNAs), small non-coding RNA molecules, have recently emerged as potential neuroprotective agents as well as targets, under hypoxic conditions. These 18–22 nucleotide long RNA molecules are profusely present in brain and other organs and function as gene regulators by cleaving and silencing the gene expression. In brain, these are known to be involved in neuronal differentiation and plasticity. Therefore, targeting miRNA expression represents a novel therapeutic approach to intercede against hypoxic and ischemic brain injury. In the first part of this review, we will discuss the neurophysiological changes caused as a result of hypoxia, followed by the contribution of hypoxia in the neurodegenerative diseases. Secondly, we will provide recent updates and insights into the roles of miRNA in the regulation of genes in oxygen and glucose deprived brain in association with circadian rhythms and how these can be targeted as neuroprotective agents for CNS injuries. Finally, we will emphasize on alternate breathing or yogic interventions to overcome the hypoxia associated anomalies that could ultimately lead to improvement in cerebral perfusion. PMID:28744190

GeNN: a code generation framework for accelerated brain simulations

NASA Astrophysics Data System (ADS)

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-01

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

GeNN: a code generation framework for accelerated brain simulations.

PubMed

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-07

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

GeNN: a code generation framework for accelerated brain simulations

PubMed Central

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-01

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/. PMID:26740369

Regulatory consequences of neuronal ELAV-like protein binding to coding and non-coding RNAs in human brain

PubMed Central

Scheckel, Claudia; Drapeau, Elodie; Frias, Maria A; Park, Christopher Y; Fak, John; Zucker-Scharff, Ilana; Kou, Yan; Haroutunian, Vahram; Ma'ayan, Avi

2016-01-01

Neuronal ELAV-like (nELAVL) RNA binding proteins have been linked to numerous neurological disorders. We performed crosslinking-immunoprecipitation and RNAseq on human brain, and identified nELAVL binding sites on 8681 transcripts. Using knockout mice and RNAi in human neuroblastoma cells, we showed that nELAVL intronic and 3' UTR binding regulates human RNA splicing and abundance. We validated hundreds of nELAVL targets among which were important neuronal and disease-associated transcripts, including Alzheimer's disease (AD) transcripts. We therefore investigated RNA regulation in AD brain, and observed differential splicing of 150 transcripts, which in some cases correlated with differential nELAVL binding. Unexpectedly, the most significant change of nELAVL binding was evident on non-coding Y RNAs. nELAVL/Y RNA complexes were specifically remodeled in AD and after acute UV stress in neuroblastoma cells. We propose that the increased nELAVL/Y RNA association during stress may lead to nELAVL sequestration, redistribution of nELAVL target binding, and altered neuronal RNA splicing. DOI: http://dx.doi.org/10.7554/eLife.10421.001 PMID:26894958

Modulation of spike coding by subthreshold extracellular electric fields and neuronal morphology

NASA Astrophysics Data System (ADS)

Wei, Xile; Li, Bingjie; Lu, Meili; Yi, Guosheng; Wang, Jiang

2015-07-01

We use a two-compartment model, which includes soma and dendrite, to explore how extracellular subthreshold sinusoidal electric fields (EFs) influence the spike coding of an active neuron. By changing the intensity and the frequency of subthreshold EFs, we find that subthreshold EFs indeed affect neuronal coding remarkably within several stimulus frequency windows where the field effects on spike timing are stronger than that on spiking rate. The field effects are maximized at several harmonics of the intrinsic spiking frequency of an active neuron. Our findings implicate the potential resonance mechanism underlying subthreshold field effects. We also discuss how neuronal morphologic properties constrain subthreshold EF effects on spike timing. The morphologic properties are represented by two parameters, gc and p, where gc is the internal conductance between soma and dendrite and geometric factor p characterizes the proportion of area occupied by soma. We find that the contribution to field effects from the variation of p is stronger than that from gc, which suggests that neuronal geometric features play a crucial role in subthreshold field effects. Theoretically, these insights into how subthreshold sinusoidal EFs modulate ongoing neuron behaviors could contribute to uncovering the relevant mechanism of subthreshold sinusoidal EFs effects on neuronal coding. Furthermore, they are useful in rationally designing noninvasive brain stimulation strategies and developing electromagnetic stimulus techniques.

A Putative Multiple-Demand System in the Macaque Brain.

PubMed

Mitchell, Daniel J; Bell, Andrew H; Buckley, Mark J; Mitchell, Anna S; Sallet, Jerome; Duncan, John

2016-08-17

In humans, cognitively demanding tasks of many types recruit common frontoparietal brain areas. Pervasive activation of this "multiple-demand" (MD) network suggests a core function in supporting goal-oriented behavior. A similar network might therefore be predicted in nonhuman primates that readily perform similar tasks after training. However, an MD network in nonhuman primates has not been described. Single-cell recordings from macaque frontal and parietal cortex show some similar properties to human MD fMRI responses (e.g., adaptive coding of task-relevant information). Invasive recordings, however, come from limited prespecified locations, so they do not delineate a macaque homolog of the MD system and their positioning could benefit from knowledge of where MD foci lie. Challenges of scanning behaving animals mean that few macaque fMRI studies specifically contrast levels of cognitive demand, so we sought to identify a macaque counterpart to the human MD system using fMRI connectivity in 35 rhesus macaques. Putative macaque MD regions, mapped from frontoparietal MD regions defined in humans, were found to be functionally connected under anesthesia. To further refine these regions, an iterative process was used to maximize their connectivity cross-validated across animals. Finally, whole-brain connectivity analyses identified voxels that were robustly connected to MD regions, revealing seven clusters across frontoparietal and insular cortex comparable to human MD regions and one unexpected cluster in the lateral fissure. The proposed macaque MD regions can be used to guide future electrophysiological investigation of MD neural coding and in task-based fMRI to test predictions of similar functional properties to human MD cortex. In humans, a frontoparietal "multiple-demand" (MD) brain network is recruited during a wide range of cognitively demanding tasks. Because this suggests a fundamental function, one might expect a similar network to exist in nonhuman primates, but this remains controversial. Here, we sought to identify a macaque counterpart to the human MD system using fMRI connectivity. Putative macaque MD regions were functionally connected under anesthesia and were further refined by iterative optimization. The result is a network including lateral frontal, dorsomedial frontal, and insular and inferior parietal regions closely similar to the human counterpart. The proposed macaque MD regions can be useful in guiding electrophysiological recordings or in task-based fMRI to test predictions of similar functional properties to human MD cortex. Copyright © 2016 Mitchell et al.

The Long Noncoding RNA TP73-AS1 Interacted with miR-124 to Modulate Glioma Growth by Targeting Inhibitor of Apoptosis-Stimulating Protein of p53.

PubMed

Xiao, Shuai; Wang, Rensheng; Wu, Xiangwei; Liu, Wen; Ma, Shanshan

2018-02-01

P73 antisense RNA 1T (non-protein coding), known as TP73-AS1 or PDAM, is a long noncoding RNA (lncRNA), which may regulate apoptosis by regulation of p53-dependent antiapoptotic genes. An abnormal change of TP73-AS1 expression was noticed in cancers. The effects of TP73-AS1 in brain glioma growth and the underlying mechanism remain unclear so far. In this study, the effect of TP73-AS1 in human brain glioma cell lines and clinical tumor samples was detected so as to reveal its role and function. In this study, TP73-AS1 was specifically upregulated in brain glioma cell lines and promoted glioma cell growth through targeting miR-124. TP73-AS1 knocking down suppressed human brain glioma cell proliferation, invasion, and metastasis in vitro. The inhibitory effect of TP73-AS1 knocking down on glioma cell proliferation and invasion could partly be restored by miR-124 inhibition. In addition, miR-124-dependent inhibitor of apoptosis-stimulating protein of p53 (iASPP) regulation was required in TP73-AS1-induced brain glioma cell growth. Data from this study revealed that TP73-AS1 inhibited the brain glioma growth and metastasis as a competing endogenous RNA (ceRNA) through miR-124-dependent iASPP regulation. In conclusion, we regarded TP73-AS1 as an oncogenic lncRNA promoting brain glioma proliferation and metastasis and a potential target for human brain glioma treatment.

Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain

PubMed Central

Gross, Joachim; Hoogenboom, Nienke; Thut, Gregor; Schyns, Philippe; Panzeri, Stefano; Belin, Pascal; Garrod, Simon

2013-01-01

Cortical oscillations are likely candidates for segmentation and coding of continuous speech. Here, we monitored continuous speech processing with magnetoencephalography (MEG) to unravel the principles of speech segmentation and coding. We demonstrate that speech entrains the phase of low-frequency (delta, theta) and the amplitude of high-frequency (gamma) oscillations in the auditory cortex. Phase entrainment is stronger in the right and amplitude entrainment is stronger in the left auditory cortex. Furthermore, edges in the speech envelope phase reset auditory cortex oscillations thereby enhancing their entrainment to speech. This mechanism adapts to the changing physical features of the speech envelope and enables efficient, stimulus-specific speech sampling. Finally, we show that within the auditory cortex, coupling between delta, theta, and gamma oscillations increases following speech edges. Importantly, all couplings (i.e., brain-speech and also within the cortex) attenuate for backward-presented speech, suggesting top-down control. We conclude that segmentation and coding of speech relies on a nested hierarchy of entrained cortical oscillations. PMID:24391472

Preliminary Studies on Differential Expression of Auditory Functional Genes in the Brain After Repeated Blast Exposures

DTIC Science & Technology

2012-01-01

exposed mice showed significant injury (Figure). The injury level was more on the medial contra- lateral side of the brain than the ipsilateral side. The...code) JRRD Volume 49, Number 7, 2012Pages 1153–1162Preliminary studies on differential expression of auditory functional genes in the brain after...hearing- related genes in different regions of the brain 6 h after repeated blast exposures in mice. Preliminary data showed that the expres- sion of

Four out of eight genes in a mouse chromosome 7 congenic donor region are candidate obesity genes.

PubMed

Sarahan, Kari A; Fisler, Janis S; Warden, Craig H

2011-09-22

We previously identified a region of mouse chromosome 7 that influences body fat mass in F2 littermates of congenic × background intercrosses. Current analyses revealed that alleles in the donor region of the subcongenic B6.C-D7Mit318 (318) promoted a twofold increase in adiposity in homozygous lines of 318 compared with background C57BL/6ByJ (B6By) mice. Parent-of-origin effects were discounted through cross-fostering studies and an F1 reciprocal cross. Mapping of the donor region revealed that it has a maximal size of 2.8 Mb (minimum 1.8 Mb) and contains a maximum of eight protein coding genes. Quantitative PCR in whole brain, liver, and gonadal white adipose tissue (GWAT) revealed differential expression between genotypes for three genes in females and two genes in males. Alpha-2,8-sialyltransferase 8B (St8sia2) showed reduced 318 mRNA levels in brain for females and males and in GWAT for females only. Both sexes of 318 mice had reduced Repulsive guidance molecule-a (Rgma) expression in GWAT. In brain, Family with sequence similarity 174 member b (Fam174b) had increased expression in 318 females, whereas Chromodomain helicase DNA binding protein 2 (Chd2-2) had reduced expression in 318 males. No donor region genes were differentially expressed in liver. Sequence analysis of coding exons for all genes in the 318 donor region revealed only one single nucleotide polymorphism that produced a nonsynonymous missense mutation, Gln7Pro, in Fam174b. Our findings highlight the difficulty of using expression and sequence to identify quantitative trait genes underlying obesity even in small genomic regions.

Growth of malignant extracranial tumors alters microRNAome in the prefrontal cortex of TumorGraft mice

PubMed Central

Kovalchuk, Anna; Ilnytskyy, Yaroslav; Rodriguez-Juarez, Rocio; Katz, Amanda; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

2017-01-01

A wide array of central nervous system complications, neurological deficits, and cognitive impairments occur and persist as a result of systemic cancer and cancer treatments. This condition is known as chemo brain and it affects over half of cancer survivors. Recent studies reported that cognitive impairments manifest before chemotherapy and are much broader than chemo brain alone, thereby adding in tumor brain as a component. The molecular mechanisms of chemo brain are under-investigated, and the mechanisms of tumor brain have not been analyzed at all. The frequency and timing, as well as the long-term persistence, of chemo brain and tumor brain suggest they may be epigenetic in nature. MicroRNAs, small, single-stranded non-coding RNAs, constitute an important part of the cellular epigenome and are potent regulators of gene expression. miRNAs are crucial for brain development and function, and are affected by a variety of different stresses, diseases and conditions. However, nothing is known about the effects of extracranial tumor growth or chemotherapy agents on the brain microRNAome. We used the well-established TumorGraft ™ mouse models of triple negative (TNBC) and progesterone receptor positive (PR+BC) breast cancer, and profiled global microRNAome changes in tumor-bearing mice upon chemotherapy, as compared to untreated tumor-bearing mice and intact mice. Our analysis focused on the prefrontal cortex (PFC), based on its roles in memory, learning, and executive functions, and on published data showing the PFC is a target in chemo brain. This is the first study showing that tumor presence alone significantly impacted the small RNAome of PFC tissues. Both tumor growth and chemotherapy treatment affected the small RNAome and altered levels of miRNAs, piRNAs, tRNAs, tRNA fragments and other molecules involved in post-transcriptional regulation of gene expression. Amongst those, miRNA changes were the most pronounced, involving several miRNA families, such as the miR-200 family and miR-183/96/182 cluster; both were deregulated in tumor-bearing and chemotherapy-treated animals. We saw that miRNA deregulation was associated with altered levels of brain-derived neurotrophic factor (BDNF), which plays an important role in cognition and memory and is one of the known miRNA targets. BDNF downregulation has been associated with an array of neurological conditions and could be one of the mechanisms underlying tumor brain and chemo brain. In the future our study could serve as a roadmap for further analysis of cancer and chemotherapy’s neural side effects, and differentially expressed miRNAs should be explored as potential tumor brain and chemo brain biomarkers. PMID:29179434

Information theoretic analysis of proprioceptive encoding during finger flexion in the monkey sensorimotor system.

PubMed

Witham, Claire L; Baker, Stuart N

2015-01-01

There is considerable debate over whether the brain codes information using neural firing rate or the fine-grained structure of spike timing. We investigated this issue in spike discharge recorded from single units in the sensorimotor cortex, deep cerebellar nuclei, and dorsal root ganglia in macaque monkeys trained to perform a finger flexion task. The task required flexion to four different displacements against two opposing torques; the eight possible conditions were randomly interleaved. We used information theory to assess coding of task condition in spike rate, discharge irregularity, and spectral power in the 15- to 25-Hz band during the period of steady holding. All three measures coded task information in all areas tested. Information coding was most often independent between irregularity and 15-25 Hz power (60% of units), moderately redundant between spike rate and irregularity (56% of units redundant), and highly redundant between spike rate and power (93%). Most simultaneously recorded unit pairs coded using the same measure independently (86%). Knowledge of two measures often provided extra information about task, compared with knowledge of only one alone. We conclude that sensorimotor systems use both rate and temporal codes to represent information about a finger movement task. As well as offering insights into neural coding, this work suggests that incorporating spike irregularity into algorithms used for brain-machine interfaces could improve decoding accuracy. Copyright © 2015 the American Physiological Society.

Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice.

PubMed

Schmouth, Jean-François; Castellarin, Mauro; Laprise, Stéphanie; Banks, Kathleen G; Bonaguro, Russell J; McInerny, Simone C; Borretta, Lisa; Amirabbasi, Mahsa; Korecki, Andrea J; Portales-Casamar, Elodie; Wilson, Gary; Dreolini, Lisa; Jones, Steven J M; Wasserman, Wyeth W; Goldowitz, Daniel; Holt, Robert A; Simpson, Elizabeth M

2013-10-14

The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX ('high-throughput human genes on the X chromosome') strategy to expand our understanding of human gene regulation in vivo. In all, ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes, human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV, for which roles in CNS have been unclear. We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate predictions of gene expression.

An Energy Model of Place Cell Network in Three Dimensional Space.

PubMed

Wang, Yihong; Xu, Xuying; Wang, Rubin

2018-01-01

Place cells are important elements in the spatial representation system of the brain. A considerable amount of experimental data and classical models are achieved in this area. However, an important question has not been addressed, which is how the three dimensional space is represented by the place cells. This question is preliminarily surveyed by energy coding method in this research. Energy coding method argues that neural information can be expressed by neural energy and it is convenient to model and compute for neural systems due to the global and linearly addable properties of neural energy. Nevertheless, the models of functional neural networks based on energy coding method have not been established. In this work, we construct a place cell network model to represent three dimensional space on an energy level. Then we define the place field and place field center and test the locating performance in three dimensional space. The results imply that the model successfully simulates the basic properties of place cells. The individual place cell obtains unique spatial selectivity. The place fields in three dimensional space vary in size and energy consumption. Furthermore, the locating error is limited to a certain level and the simulated place field agrees to the experimental results. In conclusion, this is an effective model to represent three dimensional space by energy method. The research verifies the energy efficiency principle of the brain during the neural coding for three dimensional spatial information. It is the first step to complete the three dimensional spatial representing system of the brain, and helps us further understand how the energy efficiency principle directs the locating, navigating, and path planning function of the brain.

Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture

PubMed Central

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape. PMID:24778382

Dyadic brain modelling, mirror systems and the ontogenetic ritualization of ape gesture.

PubMed

Arbib, Michael; Ganesh, Varsha; Gasser, Brad

2014-01-01

The paper introduces dyadic brain modelling, offering both a framework for modelling the brains of interacting agents and a general framework for simulating and visualizing the interactions generated when the brains (and the two bodies) are each coded up in computational detail. It models selected neural mechanisms in ape brains supportive of social interactions, including putative mirror neuron systems inspired by macaque neurophysiology but augmented by increased access to proprioceptive state. Simulation results for a reduced version of the model show ritualized gesture emerging from interactions between a simulated child and mother ape.

A computational model of prefrontal control in free recall: strategic memory use in the California Verbal Learning Task.

PubMed

Becker, Suzanna; Lim, Jean

2003-08-15

Several decades of research into the function of the frontal lobes in brain-damaged patients, and more recently in intact individuals using function brain imaging, has delineated the complex executive functions of the frontal cortex. And yet, the mechanisms by which the brain achieves these functions remain poorly understood. Here, we present a computational model of the role of the prefrontal cortex (PFC) in controlled memory use that may help to shed light on the mechanisms underlying one aspect of frontal control: the development and deployment of recall strategies. The model accounts for interactions between the PFC and medial temporal lobe in strategic memory use. The PFC self-organizes its own mnemonic codes using internally derived performance measures. These mnemonic codes serve as retrieval cues by biasing retrieval in the medial temporal lobe memory system. We present data from three simulation experiments that demonstrate strategic encoding and retrieval in the free recall of categorized lists of words. Experiment 1 compares the performance of the model with two control networks to evaluate the contribution of various components of the model. Experiment 2 compares the performance of normal and frontally lesioned models to data from several studies using frontally intact and frontally lesioned individuals, as well as normal, healthy individuals under conditions of divided attention. Experiment 3 compares the model's performance on the recall of blocked and unblocked categorized lists of words to data from Stuss et al. (1994) for individuals with control and frontal lobe lesions. Overall, our model captures a number of aspects of human performance on free recall tasks: an increase in total words recalled and in semantic clustering scores across trials, superiority on blocked lists of related items compared to unblocked lists of related items, and similar patterns of performance across trials in the normal and frontally lesioned models, with poorer overall performance of the lesioned models on all measures. The model also has a number of shortcomings, in light of which we suggest extensions to the model that would enable more sophisticated forms of strategic control.

Semantic representations in the temporal pole predict false memories

PubMed Central

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

2016-01-01

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

Semantic representations in the temporal pole predict false memories.

PubMed

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

2016-09-06

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

Selective population rate coding: a possible computational role of gamma oscillations in selective attention.

PubMed

Masuda, Naoki

2009-12-01

Selective attention is often accompanied by gamma oscillations in local field potentials and spike field coherence in brain areas related to visual, motor, and cognitive information processing. Gamma oscillations are implicated to play an important role in, for example, visual tasks including object search, shape perception, and speed detection. However, the mechanism by which gamma oscillations enhance cognitive and behavioral performance of attentive subjects is still elusive. Using feedforward fan-in networks composed of spiking neurons, we examine a possible role for gamma oscillations in selective attention and population rate coding of external stimuli. We implement the concept proposed by Fries ( 2005 ) that under dynamic stimuli, neural populations effectively communicate with each other only when there is a good phase relationship among associated gamma oscillations. We show that the downstream neural population selects a specific dynamic stimulus received by an upstream population and represents it by population rate coding. The encoded stimulus is the one for which gamma rhythm in the corresponding upstream population is resonant with the downstream gamma rhythm. The proposed role for gamma oscillations in stimulus selection is to enable top-down control, a neural version of time division multiple access used in communication engineering.

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.

PubMed

Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol

2010-12-01

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.

Loss of Trem2 in microglia leads to widespread disruption of cell coexpression networks in mouse brain.

PubMed

Carbajosa, Guillermo; Malki, Karim; Lawless, Nathan; Wang, Hong; Ryder, John W; Wozniak, Eva; Wood, Kristie; Mein, Charles A; Dobson, Richard J B; Collier, David A; O'Neill, Michael J; Hodges, Angela K; Newhouse, Stephen J

2018-05-17

Rare heterozygous coding variants in the triggering receptor expressed in myeloid cells 2 (TREM2) gene, conferring increased risk of developing late-onset Alzheimer's disease, have been identified. We examined the transcriptional consequences of the loss of Trem2 in mouse brain to better understand its role in disease using differential expression and coexpression network analysis of Trem2 knockout and wild-type mice. We generated RNA-Seq data from cortex and hippocampus sampled at 4 and 8 months. Using brain cell-type markers and ontology enrichment, we found subnetworks with cell type and/or functional identity. We primarily discovered changes in an endothelial gene-enriched subnetwork at 4 months, including a shift toward a more central role for the amyloid precursor protein gene, coupled with widespread disruption of other cell-type subnetworks, including a subnetwork with neuronal identity. We reveal an unexpected potential role of Trem2 in the homeostasis of endothelial cells that goes beyond its known functions as a microglial receptor and signaling hub, suggesting an underlying link between immune response and vascular disease in dementia. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Rocky Mountain Arsenal Ecological Chemical Data (1984-1985)

DTIC Science & Technology

1986-03-01

Type Wet Areas Code Area LK Lake MT Marshy Type PD Pond C-1 APPENDIX D TISSUE CODES Code Tissue BRA Brain FIL Filet EDP Edible Portion LIV Liver MUS...ctus 472 Craton texcisis Crotoni 473 Cryptantha fcndleri Fcnder’s Cryptantha 474 Cucurbita foctidissinma Wild Gourd 475 Cytroptcrus montanus Pink Cym...adcrnocaulon Nlorthern wilIlow- herb 484 Eragrostis cilianensis Stinkgrass 485 Erfcgonum annuum Tall Erlogonum 486 Erigercn divergcns Spreading Fleabine 487

Building a neuroscience of pleasure and well-being

PubMed Central

Berridge, Kent C; Kringelbach, Morten L

2012-01-01

Background How is happiness generated via brain function in lucky individuals who have the good fortune to be happy? Conceptually, well-being or happiness has long been viewed as requiring at least two crucial ingredients: positive affect or pleasure (hedonia) and a sense of meaningfulness or engagement in life (eudaimonia). Science has recently made progress in relating hedonic pleasure to brain function, and so here we survey new insights into how brains generate the hedonic ingredient of sustained or frequent pleasure. We also briefly discuss how brains might connect hedonia states of pleasure to eudaimonia assessments of meaningfulness, and so create balanced states of positive well-being. Results Notable progress has been made in understanding brain bases of hedonic processing, producing insights into that brain systems that cause and/or code sensory pleasures. Progress has been facilitated by the recognition that hedonic brain mechanisms are largely shared between humans and other mammals, allowing application of conclusions from animal studies to a better understanding of human pleasures. In the past few years, evidence has also grown to indicate that for humans, brain mechanisms of higher abstract pleasures strongly overlap with more basic sensory pleasures. This overlap may provide a window into underlying brain circuitry that generates all pleasures, including even the hedonic quality of pervasive well-being that detaches from any particular sensation to apply to daily life in a more sustained or frequent fashion. Conclusions Hedonic insights are applied to understanding human well-being here. Our strategy combines new findings on brain mediators that generate the pleasure of sensations with evidence that human brains use many of the same hedonic circuits from sensory pleasures to create the higher pleasures. This in turn may be linked to how hedonic systems interact with other brain systems relevant to self-understanding and the meaning components of eudaimonic happiness. Finally, we speculate a bit about how brains that generate hedonia states might link to eudaimonia assessments to create properly balanced states of positive well-being that approach true happiness. PMID:22328976

Brain Immune Interactions as the Basis of Gulf War Illness: Gulf War Illness Consortium (GWIC)

DTIC Science & Technology

2016-10-01

between the immune system and the brain. The GWIC includes both clinical ( human ) and preclinical (animal and cell) studies and researchers in the 10...47 pesticides , DFP, sarin 16. Price Code (Leave Bl k) 17. Security Classification of Report Unclassified 18. Security Classification of this...stronger and longer proinflammatory signaling effects between the immune system and the brain. The GWIC includes both clinical ( human ) and

Brain-Emulating Cognition and Control Architecture (BECCA) v. 0.2 beta

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

ROHRER, BRANDON; & MORROW, JAMES

2009-06-16

BECCA is a learning and control method based on the function of the human brain. The goal behind its creation is to learn to control robots in unfamiliar environments in a way that is very robust, similar to the way that an infant learns to interact with her environment by trial and error. As of this release, this software contains an application for controlling robot hardware through a socket. The code was created so as to make it extensible to new applications. It is modular, object-oriented code in which the portions of the code that are specific to one robotmore » are easily separable from those portions that are the constant between implementations. BECCA makes very few assumptions about the robot and environment it is learning, and so is applicable to a wide range of learning and control problems.« less

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Predictive Coding Strategies for Developmental Neurorobotics

PubMed Central

Park, Jun-Cheol; Lim, Jae Hyun; Choi, Hansol; Kim, Dae-Shik

2012-01-01

In recent years, predictive coding strategies have been proposed as a possible means by which the brain might make sense of the truly overwhelming amount of sensory data available to the brain at any given moment of time. Instead of the raw data, the brain is hypothesized to guide its actions by assigning causal beliefs to the observed error between what it expects to happen and what actually happens. In this paper, we present a variety of developmental neurorobotics experiments in which minimalist prediction error-based encoding strategies are utilize to elucidate the emergence of infant-like behavior in humanoid robotic platforms. Our approaches will be first naively Piagian, then move onto more Vygotskian ideas. More specifically, we will investigate how simple forms of infant learning, such as motor sequence generation, object permanence, and imitation learning may arise if minimizing prediction errors are used as objective functions. PMID:22586416

Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: I dynamics.

PubMed

Zheng, Lei; Nikolaev, Anton; Wardill, Trevor J; O'Kane, Cahir J; de Polavieja, Gonzalo G; Juusola, Mikko

2009-01-01

Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1-R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II).

Network Adaptation Improves Temporal Representation of Naturalistic Stimuli in Drosophila Eye: I Dynamics

PubMed Central

Wardill, Trevor J.; O'Kane, Cahir J.; de Polavieja, Gonzalo G.; Juusola, Mikko

2009-01-01

Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1–R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II). PMID:19180196

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition

PubMed Central

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A.

2016-01-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. PMID:26209846

Neural Coding of Formant-Exaggerated Speech in the Infant Brain

ERIC Educational Resources Information Center

Zhang, Yang; Koerner, Tess; Miller, Sharon; Grice-Patil, Zach; Svec, Adam; Akbari, David; Tusler, Liz; Carney, Edward

2011-01-01

Speech scientists have long proposed that formant exaggeration in infant-directed speech plays an important role in language acquisition. This event-related potential (ERP) study investigated neural coding of formant-exaggerated speech in 6-12-month-old infants. Two synthetic /i/ vowels were presented in alternating blocks to test the effects of…

Neural Coding of Relational Invariance in Speech: Human Language Analogs to the Barn Owl.

ERIC Educational Resources Information Center

Sussman, Harvey M.

1989-01-01

The neuronal model shown to code sound-source azimuth in the barn owl by H. Wagner et al. in 1987 is used as the basis for a speculative brain-based human model, which can establish contrastive phonetic categories to solve the problem of perception "non-invariance." (SLD)

Objects, Numbers, Fingers, Space: Clustering of Ventral and Dorsal Functions in Young Children and Adults

ERIC Educational Resources Information Center

Chinello, Alessandro; Cattani, Veronica; Bonfiglioli, Claudia; Dehaene, Stanislas; Piazza, Manuela

2013-01-01

In the primate brain, sensory information is processed along two partially segregated cortical streams: the ventral stream, mainly coding for objects' shape and identity, and the dorsal stream, mainly coding for objects' quantitative information (including size, number, and spatial position). Neurophysiological measures indicate that such…

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks.

PubMed

Ceschin, Rafael; Zahner, Alexandria; Reynolds, William; Gaesser, Jenna; Zuccoli, Giulio; Lo, Cecilia W; Gopalakrishnan, Vanathi; Panigrahy, Ashok

2018-05-21

Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsupervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuroimaging datasets requires adequate sample size for training and well-defined signal intensity based structural differentiation. There is a lack of effective automated diagnostic tools for the reliable detection of brain dysmaturation in the neonatal period, related to small sample size and complex undifferentiated brain structures, despite both translational research and clinical importance. Volumetric information alone is insufficient for diagnosis. In this study, we developed a computational framework for the automated classification of brain dysmaturation from neonatal MRI, by combining a specific deep neural network implementation with neonatal structural brain segmentation as a method for both clinical pattern recognition and data-driven inference into the underlying structural morphology. We implemented three-dimensional convolution neural networks (3D-CNNs) to specifically classify dysplastic cerebelli, a subset of surface-based subcortical brain dysmaturation, in term infants born with congenital heart disease. We obtained a 0.985 ± 0. 0241-classification accuracy of subtle cerebellar dysplasia in CHD using 10-fold cross-validation. Furthermore, the hidden layer activations and class activation maps depicted regional vulnerability of the superior surface of the cerebellum, (composed of mostly the posterior lobe and the midline vermis), in regards to differentiating the dysplastic process from normal tissue. The posterior lobe and the midline vermis provide regional differentiation that is relevant to not only to the clinical diagnosis of cerebellar dysplasia, but also genetic mechanisms and neurodevelopmental outcome correlates. These findings not only contribute to the detection and classification of a subset of neonatal brain dysmaturation, but also provide insight to the pathogenesis of cerebellar dysplasia in CHD. In addition, this is one of the first examples of the application of deep learning to a neuroimaging dataset, in which the hidden layer activation revealed diagnostically and biologically relevant features about the clinical pathogenesis. The code developed for this project is open source, published under the BSD License, and designed to be generalizable to applications both within and beyond neonatal brain imaging. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain cDNA clone for human cholinesterase

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

McTiernan, C.; Adkins, S.; Chatonnet, A.

1987-10-01

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.more » 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.« less

Loss-of-function mutation in RUSC2 causes intellectual disability and secondary microcephaly.

PubMed

Alwadei, Ali H; Benini, Ruba; Mahmoud, Adel; Alasmari, Ali; Kamsteeg, Erik-Jan; Alfadhel, Majid

2016-12-01

Inherited aberrancies in intracellular vesicular transport are associated with a variety of neurological and non-neurological diseases. RUSC2 is a gene found on chromosome 9p13.3 that codes for iporin, a ubiquitous protein with high expression in the brain that interacts with Rab proteins (GTPases implicated in intracellular protein trafficking). Although mutations in Rab proteins have been described as causing brain abnormalities and intellectual disability, until now no disease-causing mutations in RUSC2 have ever been reported in humans. We describe, to our knowledge for the first time, three patients with inherited homozygous nonsense mutations identified in RUSC2 on whole-exome sequencing. All three patients had central hypotonia, microcephaly, and moderate to severe intellectual disability. Two patients had additional features of early-onset epilepsy and absence of the splenium. This report adds to the ever-expanding landscape of genetic causes of intellectual disability and increases our understanding of the cellular processes underlying this important neurological entity. © 2016 Mac Keith Press.

Dissociable Contributions of Imagination and Willpower to the Malleability of Human Patience.

PubMed

Jenkins, Adrianna C; Hsu, Ming

2017-07-01

The ability to exercise patience is important for human functioning. Although it is known that patience can be promoted by using top-down control, or willpower, to override impatient impulses, patience is also malleable-in particular, susceptible to framing effects-in ways that are difficult to explain using willpower alone. So far, the mechanisms underlying framing effects on patience have been elusive. We investigated the role of imagination in these effects. In a behavioral experiment (Experiment 1), a classic framing manipulation (sequence framing) increased self-reported and independently coded imagination during intertemporal choice. In an investigation of neural responses during decision making (Experiment 2), sequence framing increased the extent to which patience was related to activation in brain regions associated with imagination, relative to activation in regions associated with willpower, and increased functional connectivity of brain regions associated with imagination, but not willpower, relative to regions associated with valuation. Our results suggest that sequence framing can increase the role of imagination in decision making without increasing the exertion of willpower.

Brain Oscillations Forever--Neurophysiology in Future Research of Child Psychiatric Problems

ERIC Educational Resources Information Center

Rothenberger, Aribert

2009-01-01

For decades neurophysiology has successfully contributed to research and clinical care in child psychiatry. Recently, methodological progress has led to a revival of interest in brain oscillations (i.e., a band of periodic neuronal frequencies with a wave-duration from milliseconds to several seconds which may code and decode information). These…

Decoding the non-coding genome: elucidating genetic risk outside the coding genome.

PubMed

Barr, C L; Misener, V L

2016-01-01

Current evidence emerging from genome-wide association studies indicates that the genetic underpinnings of complex traits are likely attributable to genetic variation that changes gene expression, rather than (or in combination with) variation that changes protein-coding sequences. This is particularly compelling with respect to psychiatric disorders, as genetic changes in regulatory regions may result in differential transcriptional responses to developmental cues and environmental/psychosocial stressors. Until recently, however, the link between transcriptional regulation and psychiatric genetic risk has been understudied. Multiple obstacles have contributed to the paucity of research in this area, including challenges in identifying the positions of remote (distal from the promoter) regulatory elements (e.g. enhancers) and their target genes and the underrepresentation of neural cell types and brain tissues in epigenome projects - the availability of high-quality brain tissues for epigenetic and transcriptome profiling, particularly for the adolescent and developing brain, has been limited. Further challenges have arisen in the prediction and testing of the functional impact of DNA variation with respect to multiple aspects of transcriptional control, including regulatory-element interaction (e.g. between enhancers and promoters), transcription factor binding and DNA methylation. Further, the brain has uncommon DNA-methylation marks with unique genomic distributions not found in other tissues - current evidence suggests the involvement of non-CG methylation and 5-hydroxymethylation in neurodevelopmental processes but much remains unknown. We review here knowledge gaps as well as both technological and resource obstacles that will need to be overcome in order to elucidate the involvement of brain-relevant gene-regulatory variants in genetic risk for psychiatric disorders. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Audio-tactile integration and the influence of musical training.

PubMed

Kuchenbuch, Anja; Paraskevopoulos, Evangelos; Herholz, Sibylle C; Pantev, Christo

2014-01-01

Perception of our environment is a multisensory experience; information from different sensory systems like the auditory, visual and tactile is constantly integrated. Complex tasks that require high temporal and spatial precision of multisensory integration put strong demands on the underlying networks but it is largely unknown how task experience shapes multisensory processing. Long-term musical training is an excellent model for brain plasticity because it shapes the human brain at functional and structural levels, affecting a network of brain areas. In the present study we used magnetoencephalography (MEG) to investigate how audio-tactile perception is integrated in the human brain and if musicians show enhancement of the corresponding activation compared to non-musicians. Using a paradigm that allowed the investigation of combined and separate auditory and tactile processing, we found a multisensory incongruency response, generated in frontal, cingulate and cerebellar regions, an auditory mismatch response generated mainly in the auditory cortex and a tactile mismatch response generated in frontal and cerebellar regions. The influence of musical training was seen in the audio-tactile as well as in the auditory condition, indicating enhanced higher-order processing in musicians, while the sources of the tactile MMN were not influenced by long-term musical training. Consistent with the predictive coding model, more basic, bottom-up sensory processing was relatively stable and less affected by expertise, whereas areas for top-down models of multisensory expectancies were modulated by training.

Chirp- and random-based coded ultrasonic excitation for localized blood-brain barrier opening

PubMed Central

Kamimura, HAS; Wang, S; Wu, S-Y; Karakatsani, ME; Acosta, C; Carneiro, AAO; Konofagou, EE

2015-01-01

Chirp- and random-based coded excitation methods have been proposed to reduce standing wave formation and improve focusing of transcranial ultrasound. However, no clear evidence has been shown to support the benefits of these ultrasonic excitation sequences in vivo. This study evaluates the chirp and periodic selection of random frequency (PSRF) coded-excitation methods for opening the blood-brain barrier (BBB) in mice. Three groups of mice (n=15) were injected with polydisperse microbubbles and sonicated in the caudate putamen using the chirp/PSRF coded (bandwidth: 1.5-1.9 MHz, peak negative pressure: 0.52 MPa, duration: 30 s) or standard ultrasound (frequency: 1.5 MHz, pressure: 0.52 MPa, burst duration: 20 ms, duration: 5 min) sequences. T1-weighted contrast-enhanced MRI scans were performed to quantitatively analyze focused ultrasound induced BBB opening. The mean opening volumes evaluated from the MRI were 9.38±5.71 mm3, 8.91±3.91 mm3 and 35.47 ± 5.10 mm3 for the chirp, random and regular sonications, respectively. The mean cavitation levels were 55.40±28.43 V.s, 63.87±29.97 V.s and 356.52±257.15 V.s for the chirp, random and regular sonications, respectively. The chirp and PSRF coded pulsing sequences improved the BBB opening localization by inducing lower cavitation levels and smaller opening volumes compared to results of the regular sonication technique. Larger bandwidths were associated with more focused targeting but were limited by the frequency response of the transducer, the skull attenuation and the microbubbles optimal frequency range. The coded methods could therefore facilitate highly localized drug delivery as well as benefit other transcranial ultrasound techniques that use higher pressure levels and higher precision to induce the necessary bioeffects in a brain region while avoiding damage to the surrounding healthy tissue. PMID:26394091

miRNAs in brain development

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

Petri, Rebecca; Malmevik, Josephine; Fasching, Liana

2014-02-01

MicroRNAs (miRNAs) are small, non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. In the brain, a large number of miRNAs are expressed and there is a growing body of evidence demonstrating that miRNAs are essential for brain development and neuronal function. Conditional knockout studies of the core components in the miRNA biogenesis pathway, such as Dicer and DGCR8, have demonstrated a crucial role for miRNAs during the development of the central nervous system. Furthermore, mice deleted for specific miRNAs and miRNA-clusters demonstrate diverse functional roles for different miRNAs during the development of different brain structures. miRNAs havemore » been proposed to regulate cellular functions such as differentiation, proliferation and fate-determination of neural progenitors. In this review we summarise the findings from recent studies that highlight the importance of miRNAs in brain development with a focus on the mouse model. We also discuss the technical limitations of current miRNA studies that still limit our understanding of this family of non-coding RNAs and propose the use of novel and refined technologies that are needed in order to fully determine the impact of specific miRNAs in brain development. - Highlights: • miRNAs are essential for brain development and neuronal function. • KO of Dicer is embryonically lethal. • Conditional Dicer KO results in defective proliferation or increased apoptosis. • KO of individual miRNAs or miRNA families is necessary to determine function.« less

Listening to Brain Microcircuits for Interfacing With External World—Progress in Wireless Implantable Microelectronic Neuroengineering Devices

PubMed Central

Nurmikko, Arto V.; Donoghue, John P.; Hochberg, Leigh R.; Patterson, William R.; Song, Yoon-Kyu; Bull, Christopher W.; Borton, David A.; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2011-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature’s amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic “brain-interfaces” within the body, a point of special emphasis of this paper. PMID:21654935

Listening to Brain Microcircuits for Interfacing With External World-Progress in Wireless Implantable Microelectronic Neuroengineering Devices: Experimental systems are described for electrical recording in the brain using multiple microelectrodes and short range implantable or wearable broadcasting units.

PubMed

Nurmikko, Arto V; Donoghue, John P; Hochberg, Leigh R; Patterson, William R; Song, Yoon-Kyu; Bull, Christopher W; Borton, David A; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2010-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature's amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic "brain-interfaces" within the body, a point of special emphasis of this paper.

With or without you: predictive coding and Bayesian inference in the brain

PubMed Central

Aitchison, Laurence; Lengyel, Máté

2018-01-01

Two theoretical ideas have emerged recently with the ambition to provide a unifying functional explanation of neural population coding and dynamics: predictive coding and Bayesian inference. Here, we describe the two theories and their combination into a single framework: Bayesian predictive coding. We clarify how the two theories can be distinguished, despite sharing core computational concepts and addressing an overlapping set of empirical phenomena. We argue that predictive coding is an algorithmic / representational motif that can serve several different computational goals of which Bayesian inference is but one. Conversely, while Bayesian inference can utilize predictive coding, it can also be realized by a variety of other representations. We critically evaluate the experimental evidence supporting Bayesian predictive coding and discuss how to test it more directly. PMID:28942084

Genomics analysis of potassium channel genes in songbirds reveals molecular specializations of brain circuits for the maintenance and production of learned vocalizations

PubMed Central

2013-01-01

Background A fundamental question in molecular neurobiology is how genes that determine basic neuronal properties shape the functional organization of brain circuits underlying complex learned behaviors. Given the growing availability of complete vertebrate genomes, comparative genomics represents a promising approach to address this question. Here we used genomics and molecular approaches to study how ion channel genes influence the properties of the brain circuitry that regulates birdsong, a learned vocal behavior with important similarities to human speech acquisition. We focused on potassium (K-)Channels, which are major determinants of neuronal cell excitability. Starting with the human gene set of K-Channels, we used cross-species mRNA/protein alignments, and syntenic analysis to define the full complement of orthologs, paralogs, allelic variants, as well as novel loci not previously predicted in the genome of zebra finch (Taeniopygia guttata). We also compared protein coding domains in chicken and zebra finch orthologs to identify genes under positive selective pressure, and those that contained lineage-specific insertions/deletions in functional domains. Finally, we conducted comprehensive in situ hybridizations to determine the extent of brain expression, and identify K-Channel gene enrichments in nuclei of the avian song system. Results We identified 107 K-Channel finch genes, including 6 novel genes common to non-mammalian vertebrate lineages. Twenty human genes are absent in songbirds, birds, or sauropsids, or unique to mammals, suggesting K-Channel properties may be lineage-specific. We also identified specific family members with insertions/deletions and/or high dN/dS ratios compared to chicken, a non-vocal learner. In situ hybridization revealed that while most K-Channel genes are broadly expressed in the brain, a subset is selectively expressed in song nuclei, representing molecular specializations of the vocal circuitry. Conclusions Together, these findings shed new light on genes that may regulate biophysical and excitable properties of the song circuitry, identify potential targets for the manipulation of the song system, and reveal genomic specializations that may relate to the emergence of vocal learning and associated brain areas in birds. PMID:23845108

How Object-Specific Are Object Files? Evidence for Integration by Location

ERIC Educational Resources Information Center

van Dam, Wessel O.; Hommel, Bernhard

2010-01-01

Given the distributed representation of visual features in the human brain, binding mechanisms are necessary to integrate visual information about the same perceptual event. It has been assumed that feature codes are bound into object files--pointers to the neural codes of the features of a given event. The present study investigated the…

microRNA in Cerebral Spinal Fluid as Biomarkers of Alzheimer’s Disease Risk After Brain Injury

DTIC Science & Technology

2016-08-01

protein processing is a key feature of AD. MiRNAs are small non- coding RNA that regulate mRNA transcription, and may be a significant cause of protein...non- coding RNA that regulate mRNA transcription, and may be a significant cause of protein dysregulation. Our investigative team has generated

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

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.

Interfering with the neural activity of mirror-related frontal areas impairs mentalistic inferences.

PubMed

Herbet, Guillaume; Lafargue, Gilles; Moritz-Gasser, Sylvie; Bonnetblanc, François; Duffau, Hugues

2015-07-01

According to recently proposed interactive dual-process theories, mentalizing abilities emerge from the coherent interaction between two physically distinct neural systems: (1) the mirror network, coding for the low-level embodied representations involved in pre-reflective sociocognitive processes and (2) the mentalizing network per se, which codes for higher level representations subtending the reflective attribution of psychological states. However, although the latest studies have shown that the core areas forming these two neurocognitive systems do indeed maintain effective connectivity during mentalizing, it is unclear whether an intact mirror system (and, more specifically, its anterior node, namely the posterior inferior frontal cortex) is a prerequisite for accurate mentalistic inferences. Intraoperative brain mapping via direct electrical stimulation offers a unique opportunity to address this issue. Electrical stimulation of the brain creates a "virtual" lesion, which provides functional information on well-defined parts of the cerebral cortex. In the present study, five patients were mapped in real time while they performed a mentalizing task. We found six responsive sites: four in the lateral part of the right pars opercularis and two in the dorsal part of the right pars triangularis. On the subcortical level, two additional sites were located within the white matter connectivity of the pars opercularis. Taken as a whole, our results suggest that the right inferior frontal cortex and its underlying axonal connectivity have a key role in mentalizing. Specifically, our findings support the hypothesis whereby transient, functional disruption of the mirror network influences higher order mentalistic inferences.

Multivariate assessment of event-related potentials with the t-CWT method.

PubMed

Bostanov, Vladimir

2015-11-05

Event-related brain potentials (ERPs) are usually assessed with univariate statistical tests although they are essentially multivariate objects. Brain-computer interface applications are a notable exception to this practice, because they are based on multivariate classification of single-trial ERPs. Multivariate ERP assessment can be facilitated by feature extraction methods. One such method is t-CWT, a mathematical-statistical algorithm based on the continuous wavelet transform (CWT) and Student's t-test. This article begins with a geometric primer on some basic concepts of multivariate statistics as applied to ERP assessment in general and to the t-CWT method in particular. Further, it presents for the first time a detailed, step-by-step, formal mathematical description of the t-CWT algorithm. A new multivariate outlier rejection procedure based on principal component analysis in the frequency domain is presented as an important pre-processing step. The MATLAB and GNU Octave implementation of t-CWT is also made publicly available for the first time as free and open source code. The method is demonstrated on some example ERP data obtained in a passive oddball paradigm. Finally, some conceptually novel applications of the multivariate approach in general and of the t-CWT method in particular are suggested and discussed. Hopefully, the publication of both the t-CWT source code and its underlying mathematical algorithm along with a didactic geometric introduction to some basic concepts of multivariate statistics would make t-CWT more accessible to both users and developers in the field of neuroscience research.

Methods and Management of the Healthy Brain Study: A Large Multisite Qualitative Research Project

ERIC Educational Resources Information Center

Laditka, Sarah B.; Corwin, Sara J.; Laditka, James N.; Liu, Rui; Friedman, Daniela B.; Mathews, Anna E.; Wilcox, Sara

2009-01-01

Purpose of the study: To describe processes used in the Healthy Brain project to manage data collection, coding, and data distribution in a large qualitative project, conducted by researchers at 9 universities in 9 states. Design and Methods: Project management protocols included: (a) managing audiotapes and surveys to ensure data confidentiality,…

Differential Regulation of Brain-Derived Neurotrophic Factor Transcripts during the Consolidation of Fear Learning

ERIC Educational Resources Information Center

Ressler, Kerry J.; Rattiner, Lisa M.; Davis, Michael

2004-01-01

Brain-derived neurotrophic factor (BDNF) has been implicated as a molecular mediator of learning and memory. The BDNF gene contains four differentially regulated promoters that generate four distinct mRNA transcripts, each containing a unique noncoding 5[prime]-exon and a common 3[prime]-coding exon. This study describes novel evidence for the…

Using linked data to evaluate traumatic brain injuries in New Mexico : Crash Outcome Data Evaluation System (CODES) linked data demonstration project

DOT National Transportation Integrated Search

1998-10-01

The 1995 crude mortality rate of physician diagnosed traumatic brain injury (TBI) in the New Mexico is estimated to be 21 deaths per 100,000 population and the crude incidence of both hospitalized and fatal TBI is 110 cases per 100,000 population (1,...

Disruption of the zinc metabolism in rat fœtal brain after prenatal exposure to cadmium.

PubMed

Ben Mimouna, Safa; Boughammoura, Sana; Chemek, Marouane; Haouas, Zohra; Banni, Mohamed; Messaoudi, Imed

2018-04-25

This study was carried out to investigate the effects of maternal Cd and/or Zn exposure on some parameters of Zn metabolism in fetal brain of Wistar rats. Thus, female controls and other exposed by the oral route during the gestation period to Cd (50 mg CdCl 2 /L) and/or Zn (ZnCl 2 60 mg/L) were used. The male fetuses at age 20 days of gestation (GD20) were sacrificed and their brains were taken for histological, chemical and molecular analysis. Zn depletion was observed in the brains of fetuses issued from mothers exposed to Cd. Histological analysis showed that Cd exposure induces pyknosis in cortical region and CA1 region of the hippocampus compared to controls. Under Cd exposure, we noted an overexpression of the genes coding for membrane transporter involved in the intracellular incorporation of Zn (ZIP6) associated with inhibition of that encoding the transporters involved in the output of the Zn into the extracellular medium (ZnT1 and ZnT3). A decrease in the expression of the gene encoding the neuro-trophic factor (BDNF) associated with overexpression of the encoding the metal regulatory transcription factor 1 (MTF1), factor involved in the homeostasis of Zn, was also noted in Cd group. Interestingly, Zn supply provided a total or partial restauration of the changes induced by the Cd exposure. The depletion of brain Zn contents as well as the modification of the profile of expression of genes encoding membrane Zn transporters, suggest that the toxicity of Cd observed in fetal brain level are mediated, in part, by impairment of Zn metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

The Effect of Armed Forces Qualification Test Score on Mental Health Outcome Following Mild Traumatic Brain Injury

DTIC Science & Technology

2012-04-04

Brain reserve and dementia: a systematic review . Psychol Med 2006;36:441–54. 39. Valenzuela MJ: Brain reserve and the prevention of dementia. Curr Opin...Forces Qualification Test (AFQT) score. A retrospective review was conducted to identify those with postinjury mental health disorders (ICD-9-CM codes...studies suggest the relationship between intelligence and mental health outcome may be more robust in those with MTBI, because the injury itself may

Computations Underlying Social Hierarchy Learning: Distinct Neural Mechanisms for Updating and Representing Self-Relevant Information.

PubMed

Kumaran, Dharshan; Banino, Andrea; Blundell, Charles; Hassabis, Demis; Dayan, Peter

2016-12-07

Knowledge about social hierarchies organizes human behavior, yet we understand little about the underlying computations. Here we show that a Bayesian inference scheme, which tracks the power of individuals, better captures behavioral and neural data compared with a reinforcement learning model inspired by rating systems used in games such as chess. We provide evidence that the medial prefrontal cortex (MPFC) selectively mediates the updating of knowledge about one's own hierarchy, as opposed to that of another individual, a process that underpinned successful performance and involved functional interactions with the amygdala and hippocampus. In contrast, we observed domain-general coding of rank in the amygdala and hippocampus, even when the task did not require it. Our findings reveal the computations underlying a core aspect of social cognition and provide new evidence that self-relevant information may indeed be afforded a unique representational status in the brain. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

An experimental-finite element analysis on the kinetic energy absorption capacity of polyvinyl alcohol sponge.

PubMed

Karimi, Alireza; Navidbakhsh, Mahdi; Razaghi, Reza

2014-06-01

Polyvinyl alcohol (PVA) sponge is in widespread use for biomedical and tissue engineering applications owing to its biocompatibility, availability, relative cheapness, and excellent mechanical properties. This study reports a novel concept of design in energy absorbing materials which consist in the use of PVA sponge as an alternative reinforcement material to enhance the energy loss of impact loads. An experimental study is carried out to measure the mechanical properties of the PVA sponge under uniaxial loading. The kinetic energy absorption capacity of the PVA sponge is computed by a hexahedral finite element (FE) model of the steel ball and bullet through the LS-DYNA code under impact load at three different thicknesses (5, 10, 15mm). The results show that a higher sponge thickness invokes a higher energy loss of the steel ball and bullet. The highest energy loss of the steel ball and bullet is observed for the thickest sponge with 160 and 35J, respectively. The most common type of traumatic brain injury in which the head subject to impact load causes the brain to move within the skull and consequently brain hemorrhaging. These results suggest the application of the PVA sponge as a great kinetic energy absorber material compared to commonly used expanded polystyrene foams (EPS) to absorb most of the impact energy and reduces the transmitted load. The results might have implications not only for understanding of the mechanical properties of PVA sponge but also for use as an alternative reinforcement material in helmet and packaging material design. Copyright © 2014 Elsevier B.V. All rights reserved.

Vesicular monoamine transporter-1 (VMAT-1) mRNA and immunoreactive proteins in mouse brain.

PubMed

Ashe, Karen M; Chiu, Wan-Ling; Khalifa, Ahmed M; Nicolas, Antoine N; Brown, Bonnie L; De Martino, Randall R; Alexander, Clayton P; Waggener, Christopher T; Fischer-Stenger, Krista; Stewart, Jennifer K

2011-01-01

Vesicular monoamine transporter 1 (VMAT-1) mRNA and protein were examined (1) to determine whether adult mouse brain expresses full-length VMAT-1 mRNA that can be translated to functional transporter protein and (2) to compare immunoreactive VMAT-1 proteins in brain and adrenal. VMAT-1 mRNA was detected in mouse brain with RT-PCR. The cDNA was sequenced, cloned into an expression vector, transfected into COS-1 cells, and cell protein was assayed for VMAT-1 activity. Immunoreactive proteins were examined on western blots probed with four different antibodies to VMAT-1. Sequencing confirmed identity of the entire coding sequences of VMAT-1 cDNA from mouse medulla oblongata/pons and adrenal to a Gen-Bank reference sequence. Transfection of the brain cDNA into COS-1 cells resulted in transporter activity that was blocked by the VMAT inhibitor reserpine and a proton ionophore, but not by tetrabenazine, which has a high affinity for VMAT-2. Antibodies to either the C- or N- terminus of VMAT-1 detected two proteins (73 and 55 kD) in transfected COS-1 cells. The C-terminal antibodies detected both proteins in extracts of mouse medulla/pons, cortex, hypothalamus, and cerebellum but only the 73 kD protein and higher molecular weight immunoreactive proteins in mouse adrenal and rat PC12 cells, which are positive controls for rodent VMAT-1. These findings demonstrate that a functional VMAT-1 mRNA coding sequence is expressed in mouse brain and suggest processing of VMAT-1 protein differs in mouse adrenal and brain.

A novel long non-coding RNA linc-ZNF469-3 promotes lung metastasis through miR-574-5p-ZEB1 axis in triple negative breast cancer.

PubMed

Wang, Po-Shun; Chou, Cheng-Han; Lin, Cheng-Han; Yao, Yun-Chin; Cheng, Hui-Chuan; Li, Hao-Yi; Chuang, Yu-Chung; Yang, Chia-Ning; Ger, Luo-Ping; Chen, Yu-Chia; Lin, Forn-Chia; Shen, Tang-Long; Hsiao, Michael; Lu, Pei-Jung

2018-05-14

Triple-negative breast cancer (TNBC) patients usually lead to poor prognosis and survival because of metastasis. The major sites for TNBC metastasis include the lungs, brain, liver, and bone. Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts longer than 200 nucleotides and have been reported as important regulators in BC metastasis. However, the underlying mechanisms for lncRNAs regulating TNBC metastasis are not fully understood. Here we found that linc-ZNF469-3 was highly expressed in lung-metastatic LM2-4175 TNBC cells and overexpression of linc-ZNF469-3 enhanced invasion ability and stemness properties in vitro and lung metastasis in vivo. Furthermore, we found linc-ZNF469-3 physically interacted with miR-574-5p and overexpression of miR-574-5p attenuated ZEB1 expression. Importantly, endogenous high expressions of linc-ZNF469-3 and ZEB1 were correlated with tumor recurrence in TNBC patients with lung metastasis. Taken together, our findings suggested that linc-ZNF469-3 promotes lung metastasis of TNBC through miR-574-5p-ZEB1 signaling axis and may be used as potential prognostic marker for TNBC patients.

Conceptual Underpinnings of the Quality of Life in Neurological Disorders (Neuro-QoL): Comparisons of Core Sets for Stroke, Multiple Sclerosis, Spinal Cord Injury, and Traumatic Brain Injury.

PubMed

Wong, Alex W K; Lau, Stephen C L; Fong, Mandy W M; Cella, David; Lai, Jin-Shei; Heinemann, Allen W

2018-04-03

To determine the extent to which the content of the Quality of Life in Neurological Disorders (Neuro-QoL) covers the International Classification of Functioning, Disability and Health (ICF) Core Sets for multiple sclerosis (MS), stroke, spinal cord injury (SCI), and traumatic brain injury (TBI) using summary linkage indicators. Content analysis by linking content of the Neuro-QoL to corresponding ICF codes of each Core Set for MS, stroke, SCI, and TBI. Three academic centers. None. None. Four summary linkage indicators proposed by MacDermid et al were estimated to compare the content coverage between Neuro-QoL and the ICF codes of Core Sets for MS, stroke, MS, and TBI. Neuro-QoL represented 20% to 30% Core Set codes for different conditions in which more codes in Core Sets for MS (29%), stroke (28%), and TBI (28%) were covered than those for SCI in the long-term (20%) and early postacute (19%) contexts. Neuro-QoL represented nearly half of the unique Activity and Participation codes (43%-49%) and less than one third of the unique Body Function codes (12%-32%). It represented fewer Environmental Factors codes (2%-6%) and no Body Structures codes. Absolute linkage indicators found that at least 60% of Neuro-QoL items were linked to Core Set codes (63%-95%), but many items covered the same codes as revealed by unique linkage indicators (7%-13%), suggesting high concept redundancy among items. The Neuro-QoL links more closely to ICF Core Sets for stroke, MS, and TBI than to those for SCI, and primarily covers activity and participation ICF domains. Other instruments are needed to address concepts not measured by the Neuro-QoL when a comprehensive health assessment is needed. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Cell-assembly coding in several memory processes.

PubMed

Sakurai, Y

1998-01-01

The present paper discusses why the cell assembly, i.e., an ensemble population of neurons with flexible functional connections, is a tenable view of the basic code for information processes in the brain. The main properties indicating the reality of cell-assembly coding are neurons overlaps among different assemblies and connection dynamics within and among the assemblies. The former can be detected as multiple functions of individual neurons in processing different kinds of information. Individual neurons appear to be involved in multiple information processes. The latter can be detected as changes of functional synaptic connections in processing different kinds of information. Correlations of activity among some of the recorded neurons appear to change in multiple information processes. Recent experiments have compared several different memory processes (tasks) and detected these two main properties, indicating cell-assembly coding of memory in the working brain. The first experiment compared different types of processing of identical stimuli, i.e., working memory and reference memory of auditory stimuli. The second experiment compared identical processes of different types of stimuli, i.e., discriminations of simple auditory, simple visual, and configural auditory-visual stimuli. The third experiment compared identical processes of different types of stimuli with or without temporal processing of stimuli, i.e., discriminations of elemental auditory, configural auditory-visual, and sequential auditory-visual stimuli. Some possible features of the cell-assembly coding, especially "dual coding" by individual neurons and cell assemblies, are discussed for future experimental approaches. Copyright 1998 Academic Press.

How L2-Learners' Brains React to Code-Switches: An ERP Study with Russian Learners of German

ERIC Educational Resources Information Center

Ruigendijk, Esther; Hentschel, Gerd; Zeller, Jan Patrick

2016-01-01

This Event Related Potentials (ERP) study investigates auditory processing of sentences with so-called code-switches in Russian learners of German. It has often been argued that switching between two languages results in extra processing cost, although it is not completely clear yet what exactly causes these costs. ERP presents a good method to…

Face Coding Is Bilateral in the Female Brain

PubMed Central

Proverbio, Alice Mado; Riva, Federica; Martin, Eleonora; Zani, Alberto

2010-01-01

Background It is currently believed that face processing predominantly activates the right hemisphere in humans, but available literature is very inconsistent. Methodology/Principal Findings In this study, ERPs were recorded in 50 right-handed women and men in response to 390 faces (of different age and sex), and 130 technological objects. Results showed no sex difference in the amplitude of N170 to objects; a much larger face-specific response over the right hemisphere in men, and a bilateral response in women; a lack of face-age coding effect over the left hemisphere in men, with no differences in N170 to faces as a function of age; a significant bilateral face-age coding effect in women. Conclusions/Significance LORETA reconstruction showed a significant left and right asymmetry in the activation of the fusiform gyrus (BA19), in women and men, respectively. The present data reveal a lesser degree of lateralization of brain functions related to face coding in women than men. In this light, they may provide an explanation of the inconsistencies in the available literature concerning the asymmetric activity of left and right occipito-temporal cortices devoted to face perception during processing of face identity, structure, familiarity or affective content. PMID:20574528

Face coding is bilateral in the female brain.

PubMed

Proverbio, Alice Mado; Riva, Federica; Martin, Eleonora; Zani, Alberto

2010-06-21

It is currently believed that face processing predominantly activates the right hemisphere in humans, but available literature is very inconsistent. In this study, ERPs were recorded in 50 right-handed women and men in response to 390 faces (of different age and sex), and 130 technological objects. Results showed no sex difference in the amplitude of N170 to objects; a much larger face-specific response over the right hemisphere in men, and a bilateral response in women; a lack of face-age coding effect over the left hemisphere in men, with no differences in N170 to faces as a function of age; a significant bilateral face-age coding effect in women. LORETA reconstruction showed a significant left and right asymmetry in the activation of the fusiform gyrus (BA19), in women and men, respectively. The present data reveal a lesser degree of lateralization of brain functions related to face coding in women than men. In this light, they may provide an explanation of the inconsistencies in the available literature concerning the asymmetric activity of left and right occipito-temporal cortices devoted to face perception during processing of face identity, structure, familiarity or affective content.

Decoding the neural mechanisms of human tool use

PubMed Central

Gallivan, Jason P; McLean, D Adam; Valyear, Kenneth F; Culham, Jody C

2013-01-01

Sophisticated tool use is a defining characteristic of the primate species but how is it supported by the brain, particularly the human brain? Here we show, using functional MRI and pattern classification methods, that tool use is subserved by multiple distributed action-centred neural representations that are both shared with and distinct from those of the hand. In areas of frontoparietal cortex we found a common representation for planned hand- and tool-related actions. In contrast, in parietal and occipitotemporal regions implicated in hand actions and body perception we found that coding remained selectively linked to upcoming actions of the hand whereas in parietal and occipitotemporal regions implicated in tool-related processing the coding remained selectively linked to upcoming actions of the tool. The highly specialized and hierarchical nature of this coding suggests that hand- and tool-related actions are represented separately at earlier levels of sensorimotor processing before becoming integrated in frontoparietal cortex. DOI: http://dx.doi.org/10.7554/eLife.00425.001 PMID:23741616

75 FR 40857 - Small Business Size Standards: Waiver of the Nonmanufacturer Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-14

... Herbicides, Insecticides, and Fungicides, under Product Service Code (PSC) 6840, under North American... Rule for Herbicides, Insecticides, and Fungicides, under PSC 6840, under NAICS code 325320. The basis... Herbicides, Insecticides, and Fungicides, PSC 6840, under NAICS code 325320, Pesticides and Other...

Toward using alpha and theta brain waves to quantify programmer expertise.

PubMed

Crk, Igor; Kluthe, Timothy

2014-01-01

Empirical studies of programming language learnability and usability have thus far depended on indirect measures of human cognitive performance, attempting to capture what is at its essence a purely cognitive exercise through various indicators of comprehension, such as the correctness of coding tasks or the time spent working out the meaning of code and producing acceptable solutions. Understanding program comprehension is essential to understanding the inherent complexity of programming languages, and ultimately, having a measure of mental effort based on direct observation of the brain at work will illuminate the nature of the work of programming. We provide evidence of direct observation of the cognitive effort associated with programming tasks, through a carefully constructed empirical study using a cross-section of undergraduate computer science students and an inexpensive, off-the-shelf brain-computer interface device. This study presents a link between expertise and programming language comprehension, draws conclusions about the observed indicators of cognitive effort using recent cognitive theories, and proposes directions for future work that is now possible.

Temporal coding of brain patterns for direct limb control in humans.

PubMed

Müller-Putz, Gernot R; Scherer, Reinhold; Pfurtscheller, Gert; Neuper, Christa

2010-01-01

For individuals with a high spinal cord injury (SCI) not only the lower limbs, but also the upper extremities are paralyzed. A neuroprosthesis can be used to restore the lost hand and arm function in those tetraplegics. The main problem for this group of individuals, however, is the reduced ability to voluntarily operate device controllers. A brain-computer interface provides a non-manual alternative to conventional input devices by translating brain activity patterns into control commands. We show that the temporal coding of individual mental imagery pattern can be used to control two independent degrees of freedom - grasp and elbow function - of an artificial robotic arm by utilizing a minimum number of EEG scalp electrodes. We describe the procedure from the initial screening to the final application. From eight naïve subjects participating online feedback experiments, four were able to voluntarily control an artificial arm by inducing one motor imagery pattern derived from one EEG derivation only.

Biological and bionic hands: natural neural coding and artificial perception.

PubMed

Bensmaia, Sliman J

2015-09-19

The first decade and a half of the twenty-first century brought about two major innovations in neuroprosthetics: the development of anthropomorphic robotic limbs that replicate much of the function of a native human arm and the refinement of algorithms that decode intended movements from brain activity. However, skilled manipulation of objects requires somatosensory feedback, for which vision is a poor substitute. For upper-limb neuroprostheses to be clinically viable, they must therefore provide for the restoration of touch and proprioception. In this review, I discuss efforts to elicit meaningful tactile sensations through stimulation of neurons in somatosensory cortex. I focus on biomimetic approaches to sensory restoration, which leverage our current understanding about how information about grasped objects is encoded in the brain of intact individuals. I argue that not only can sensory neuroscience inform the development of sensory neuroprostheses, but also that the converse is true: stimulating the brain offers an exceptional opportunity to causally interrogate neural circuits and test hypotheses about natural neural coding.

Anti-differentiation non-coding RNA, ANCR, is differentially expressed in different types of brain tumors.

PubMed

Malakootian, Mahshid; Mirzadeh Azad, Fatemeh; Fouani, Youssef; Taheri Bajgan, Elham; Saberi, Hooshang; Mowla, Seyed Javad

2018-06-01

Long non-coding RNAs (lncRNAs) are important modulators of various cellular and molecular events, including cancer-associated pathways. The Anti-differentiation ncRNA (ANCR) is a key regulator of keratinocyte differentiation, where its expression is necessary to maintain epidermal progenitor's cells. Herein, we investigated the expression pattern of ANCR in the course of neural differentiation. Moreover, we used published RNAseq data and clinical samples to evaluate the alteration of ANCR expression in different cell types and brain tumors. Furthermore, we manipulated ANCR expression in glioma cell lines to clarify a potential functional role for ANCR in tumorigenesis. Our qRT-PCR results revealed a significant upregulation of ANCR in more malignant and less differentiated types of brain tumors (P = 0.03). This data was in accordance with down regulation of ANCR during neural differentiation. ANCR suppression caused an elevation in apoptosis rate, as well as a G1 cell cycle arrest in glioblastoma cell line. Altogether, our data demonstrated that ANCR may play a role in glioma genesis and that it could be considered as a potential diagnostic and therapeutic target to combat brain cancers.

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

PubMed Central

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

PubMed

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

Mother-Infant Face-to-Face Interaction: The Communicative Value of Infant-Directed Talking and Singing.

PubMed

Arias, Diana; Peña, Marcela

Across culture, healthy infants show a high interest in infant-directed (ID) talking and singing. Despite ID talking and ID singing being very similar in physical properties, infants differentially respond to each of them. The mechanisms underpinning these different responses are still under discussion. This study explored the behavioral (n = 26) and brain (n = 14) responses from 6- to 8-month-old infants to ID talking and ID singing during a face-to-face mother-infant interaction with their own mother. Behavioral response was analyzed from offline video coding, and brain response was estimated from the analysis of electrophysiological recordings. We found that during ID talking, infants displayed a significantly higher number of visual contacts, vocalizations, and body movements than during ID singing. Moreover, only during ID talking were the number of visual contacts and vocalizations positively correlated with the number of questions and pauses in the mother's speech. Our results suggest that ID talking provides infants with specific cues that allow them not only to react to mother stimulation, but also to act toward them, displaying a rudimentary version of turn-taking behavior. Brain activity partially supported that interpretation. The relevance of our results for bonding is discussed. © 2016 S. Karger AG, Basel.

Brain mechanisms underlying human communication.

PubMed

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.

Brain Mechanisms Underlying Human Communication

PubMed Central

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. PMID:19668699

Computational modeling of blast wave interaction with a human body and assessment of traumatic brain injury

NASA Astrophysics Data System (ADS)

Tan, X. G.; Przekwas, A. J.; Gupta, R. K.

2017-11-01

The modeling of human body biomechanics resulting from blast exposure poses great challenges because of the complex geometry and the substantial material heterogeneity. We developed a detailed human body finite element model representing both the geometry and the materials realistically. The model includes the detailed head (face, skull, brain and spinal cord), the neck, the skeleton, air cavities (lungs) and the tissues. Hence, it can be used to properly model the stress wave propagation in the human body subjected to blast loading. The blast loading on the human was generated from a simulated C4 explosion. We used the highly scalable solvers in the multi-physics code CoBi for both the blast simulation and the human body biomechanics. The meshes generated for these simulations are of good quality so that relatively large time-step sizes can be used without resorting to artificial time scaling treatments. The coupled gas dynamics and biomechanics solutions were validated against the shock tube test data. The human body models were used to conduct parametric simulations to find the biomechanical response and the brain injury mechanism due to blasts impacting the human body. Under the same blast loading condition, we showed the importance of inclusion of the whole body.

Neural decoding of collective wisdom with multi-brain computing.

PubMed

Eckstein, Miguel P; Das, Koel; Pham, Binh T; Peterson, Matthew F; Abbey, Craig K; Sy, Jocelyn L; Giesbrecht, Barry

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states. Copyright © 2011 Elsevier Inc. All rights reserved.

Deficits in context-dependent adaptive coding of reward in schizophrenia

PubMed Central

Kirschner, Matthias; Hager, Oliver M; Bischof, Martin; Hartmann-Riemer, Matthias N; Kluge, Agne; Seifritz, Erich; Tobler, Philippe N; Kaiser, Stefan

2016-01-01

Theoretical principles of information processing and empirical findings suggest that to efficiently represent all possible rewards in the natural environment, reward-sensitive neurons have to adapt their coding range dynamically to the current reward context. Adaptation ensures that the reward system is most sensitive for the most likely rewards, enabling the system to efficiently represent a potentially infinite range of reward information. A deficit in neural adaptation would prevent precise representation of rewards and could have detrimental effects for an organism’s ability to optimally engage with its environment. In schizophrenia, reward processing is known to be impaired and has been linked to different symptom dimensions. However, despite the fundamental significance of coding reward adaptively, no study has elucidated whether adaptive reward processing is impaired in schizophrenia. We therefore studied patients with schizophrenia (n=27) and healthy controls (n=25), using functional magnetic resonance imaging in combination with a variant of the monetary incentive delay task. Compared with healthy controls, patients with schizophrenia showed less efficient neural adaptation to the current reward context, which leads to imprecise neural representation of reward. Importantly, the deficit correlated with total symptom severity. Our results suggest that some of the deficits in reward processing in schizophrenia might be due to inefficient neural adaptation to the current reward context. Furthermore, because adaptive coding is a ubiquitous feature of the brain, we believe that our findings provide an avenue in defining a general impairment in neural information processing underlying this debilitating disorder. PMID:27430009

A New Way to Treat Brain Tumors: Targeting Proteins Coded by Microcephaly Genes?: Brain tumors and microcephaly arise from opposing derangements regulating progenitor growth. Drivers of microcephaly could be attractive brain tumor targets.

PubMed

Lang, Patrick Y; Gershon, Timothy R

2018-05-01

New targets for brain tumor therapies may be identified by mutations that cause hereditary microcephaly. Brain growth depends on the repeated proliferation of stem and progenitor cells. Microcephaly syndromes result from mutations that specifically impair the ability of brain progenitor or stem cells to proliferate, by inducing either premature differentiation or apoptosis. Brain tumors that derive from brain progenitor or stem cells may share many of the specific requirements of their cells of origin. These tumors may therefore be susceptible to disruptions of the protein products of genes that are mutated in microcephaly. The potential for the products of microcephaly genes to be therapeutic targets in brain tumors are highlighted hereby reviewing research on EG5, KIF14, ASPM, CDK6, and ATR. Treatments that disrupt these proteins may open new avenues for brain tumor therapy that have increased efficacy and decreased toxicity. © 2018 WILEY Periodicals, Inc.

Neuronal and network computation in the brain

NASA Astrophysics Data System (ADS)

Babloyantz, A.

1999-03-01

The concepts and methods of non-linear dynamics have been a powerful tool for studying some gamow aspects of brain dynamics. In this paper we show how, from time series analysis of electroencepholograms in sick and healthy subjects, chaotic nature of brain activity could be unveiled. This finding gave rise to the concept of spatiotemporal cortical chaotic networks which in turn was the foundation for a simple brain-like device which is able to become attentive, perform pattern recognition and motion detection. A new method of time series analysis is also proposed which demonstrates for the first time the existence of neuronal code in interspike intervals of coclear cells.

Prefrontal activity during working memory is modulated by the interaction of variation in CB1 and COX2 coding genes and correlates with frequency of cannabis use.

PubMed

Taurisano, Paolo; Antonucci, Linda A; Fazio, Leonardo; Rampino, Antonio; Romano, Raffaella; Porcelli, Annamaria; Masellis, Rita; Colizzi, Marco; Quarto, Tiziana; Torretta, Silvia; Di Giorgio, Annabella; Pergola, Giulio; Bertolino, Alessandro; Blasi, Giuseppe

2016-08-01

The CB1 cannabinoid receptor is targeted in the brain by endocannabinoids under physiological conditions as well as by delta9-tetrahydrocannabinol under cannabis use. Furthermore, its signaling appears to affect brain cognitive processing. Recent findings highlight a crucial role of cyclooxygenase-2 (COX-2) in the mechanism of intraneuronal CB1 signaling transduction, while others indicate that two single nucleotide polymorphisms (SNPs) (rs1406977 and rs20417) modulate expression of CB1 (CNR1) and COX-2 (PTGS2) coding genes, respectively. Here, our aim was to use fMRI to investigate in healthy humans whether these SNPs interact in modulating prefrontal activity during working memory processing and if this modulation is linked with cannabis use. We recruited 242 healthy subjects genotyped for CNR1 rs1406977 and PTGS2 rs20417 that performed the N-back working memory task during fMRI and were interviewed using the Cannabis Experience Questionnaire (CEQ). We found that the interaction between CNR1 rs1406977 and PTGS2 rs20417 is associated with dorsolateral prefrontal cortex (DLPFC) activity such that specific genotype configurations (CNR1 C carriers/PTGS2 C carriers and CNR1 TT/PTGS2 GG) predict lower cortical response versus others in spite of similar behavioral accuracy. Furthermore, DLPFC activity in the cluster associated with the CNR1 by PTGS2 interaction was negatively correlated with behavioral efficiency and positively correlated with frequency of cannabis use in cannabis users. These results suggest that a genetically modulated balancing of signaling within the CB1-COX-2 pathway may reflect on more or less efficient patterns of prefrontal activity during working memory. Frequency of cannabis use may be a factor for further modulation of CNR1/PTGS2-mediated cortical processing associated with this cognitive process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Conquer Chiari

MedlinePlus

... partnered with the University of Maryland Brain and Tissue Bank to establish a procedure for interested patients to register with the tissue bank using a special code created for Conquer Chiari. ...

The potential application of a transcriptionally regulated oncolytic herpes simplex virus for human cancer therapy

PubMed Central

Miao, L; Fraefel, C; Sia, K C; Newman, J P; Mohamed-Bashir, S A; Ng, W H; Lam, P Y P

2014-01-01

Background: Emerging studies have shown the potential benefit of arming oncolytic viruses with therapeutic genes. However, most of these therapeutic genes are placed under the regulation of ubiquitous viral promoters. Our goal is to generate a safer yet potent oncolytic herpes simplex virus type-1 (HSV-1) for cancer therapy. Methods: Using bacterial artificial chromosome (BAC) recombineering, a cell cycle-regulatable luciferase transgene cassette was replaced with the infected cell protein 6 (ICP6) coding region (encoded for UL39 or large subunit of ribonucleotide reductase) of the HSV-1 genome. These recombinant viruses, YE-PC8, were further tested for its proliferation-dependent luciferase gene expression. Results: The ability of YE-PC8 to confer proliferation-dependent transgene expression was demonstrated by injecting similar amount of viruses into the tumour-bearing region of the brain and the contralateral normal brain parenchyma of the same mouse. The results showed enhanced levels of luciferase activities in the tumour region but not in the normal brain parenchyma. Similar findings were observed in YE-PC8-infected short-term human brain patient-derived glioma cells compared with normal human astrocytes. intratumoural injection of YE-PC8 viruses resulted in 77% and 80% of tumour regression in human glioma and human hepatocellular carcinoma xenografts, respectively. Conclusion: YE-PC8 viruses confer tumour selectivity in proliferating cells and may be developed further as a feasible approach to treat human cancers. PMID:24196790

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus

PubMed Central

Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2018-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications. PMID:29375311

Profiling and Co-expression Network Analysis of Learned Helplessness Regulated mRNAs and lncRNAs in the Mouse Hippocampus.

PubMed

Li, Chaoqun; Cao, Feifei; Li, Shengli; Huang, Shenglin; Li, Wei; Abumaria, Nashat

2017-01-01

Although studies provide insights into the neurobiology of stress and depression, the exact molecular mechanisms underlying their pathologies remain largely unknown. Long non-coding RNA (lncRNA) has been implicated in brain functions and behavior. A potential link between lncRNA and psychiatric disorders has been proposed. However, it remains undetermined whether IncRNA regulation, in the brain, contributes to stress or depression pathologies. In this study, we used a valid animal model of depression-like symptoms; namely learned helplessness, RNA-seq, Gene Ontology and co-expression network analyses to profile the expression pattern of lncRNA and mRNA in the hippocampus of mice. We identified 6346 differentially expressed transcripts. Among them, 340 lncRNAs and 3559 protein coding mRNAs were differentially expressed in helpless mice in comparison with control and/or non-helpless mice (inescapable stress resilient mice). Gene Ontology and pathway enrichment analyses indicated that induction of helplessness altered expression of mRNAs enriched in fundamental biological functions implicated in stress/depression neurobiology such as synaptic, metabolic, cell survival and proliferation, developmental and chromatin modification functions. To explore the possible regulatory roles of the altered lncRNAs, we constructed co-expression networks composed of the lncRNAs and mRNAs. Among our differentially expressed lncRNAs, 17% showed significant correlation with genes. Functional co-expression analysis linked the identified lncRNAs to several cellular mechanisms implicated in stress/depression neurobiology. Importantly, 57% of the identified regulatory lncRNAs significantly correlated with 18 different synapse-related functions. Thus, the current study identifies for the first time distinct groups of lncRNAs regulated by induction of learned helplessness in the mouse brain. Our results suggest that lncRNA-directed regulatory mechanisms might contribute to stress-induced pathologies; in particular, to inescapable stress-induced synaptic modifications.

A review of predictive coding algorithms.

PubMed

Spratling, M W

2017-03-01

Predictive coding is a leading theory of how the brain performs probabilistic inference. However, there are a number of distinct algorithms which are described by the term "predictive coding". This article provides a concise review of these different predictive coding algorithms, highlighting their similarities and differences. Five algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive coding that have been proposed to model cortical function. While all these algorithms aim to fit a generative model to sensory data, they differ in the type of generative model they employ, in the process used to optimise the fit between the model and sensory data, and in the way that they are related to neurobiology. Copyright © 2016 Elsevier Inc. All rights reserved.

Oscillatory networks of high-level mental alignment: A perspective-taking MEG study.

PubMed

Seymour, R A; Wang, H; Rippon, G; Kessler, K

2018-08-15

Mentally imagining another's perspective is a high-level social process, reliant on manipulating internal representations of the self in an embodied manner. Recently Wang et al. (2016) showed that theta-band (3-7 Hz) brain oscillations within the right temporo-parietal junction (rTPJ) and brain regions coding for motor/body schema contribute to the process of perspective-taking. Using a similar paradigm, we set out to unravel the extended functional brain network in detail. Increasing the angle between self and other perspective was accompanied by longer reaction times and increases in theta power within rTPJ, right lateral prefrontal cortex (PFC) and right anterior cingulate cortex (ACC). Using Granger-causality, we showed that lateral PFC and ACC exert top-down influence over rTPJ, indicative of executive control processes required for managing conflicts between self and other perspectives. Finally, we quantified patterns of whole-brain phase coupling in relation to the rTPJ. Results suggest that rTPJ increases its theta-band phase synchrony with brain regions involved in mentalizing and regions coding for motor/body schema; whilst decreasing synchrony to visual regions. Implications for neurocognitive models are discussed, and it is proposed that rTPJ acts as a 'hub' to route bottom-up visual information to internal representations of the self during perspective-taking, co-ordinated by theta-band oscillations. Copyright © 2018 Elsevier Inc. All rights reserved.

Fate of mRNA following disaggregation of brain polysomes after administration of (+)-lysergic acid diethylamide in vivo.

PubMed

Mahony, J B; Brown, I R

1979-11-22

Intravenous injection of (+)-lysergic acid diethylamide into young rabbits induced a transient brain-specific disaggregation of polysomes to monosomes. Investigation of the fate of mRNA revealed that brain poly(A+)mRNA was conserved. In particular, mRNA coding for brain-specific S100 protein was not degraded, nor was it released into free ribonucleoprotein particles. Following the (+)-lysergic acid diethylamide-induced disaggregation of polysomes, mRNA shifted from polysomes and accumulated on monosomes. Formation of a blocked monosome complex, which contained intact mRNA and 40-S plus 60-S ribosomal subunits but lacked nascent peptide chains, suggested that (+)-lysergic acid diethylamide inhibited brain protein synthesis at a specific stage of late initiation or early elongation.

The neural code of thoughts and feelings. Comment on "Topodynamics of metastable brains" by Arturo Tozzi et al.

NASA Astrophysics Data System (ADS)

Jaušovec, Norbert

2017-07-01

Recently the number of theories trying to explain the brain - cognition - behavior relation has been increased. Promoted on the one hand by the development of sophisticated brain imaging techniques, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), and on the other, by complex computational models based on chaos and graph theory. But has this really advanced our understanding of the brain-behavior relation beyond Descartes's dualistic mind body division? One could critically argue that replacing the pineal body with extracellular electric fields represented in the electroencephalogram (EEG) as rapid transitional processes (RTS), combined with algebraic topology and dubbed brain topodynamics [1] is just putting lipstick on an outmoded evergreen.

Autoimmunity as a Driving Force of Cognitive Evolution

PubMed Central

Nataf, Serge

2017-01-01

In the last decades, increasingly robust experimental approaches have formally demonstrated that autoimmunity is a physiological process involved in a large range of functions including cognition. On this basis, the recently enunciated “brain superautoantigens” theory proposes that autoimmunity has been a driving force of cognitive evolution. It is notably suggested that the immune and nervous systems have somehow co-evolved and exerted a mutual selection pressure benefiting to both systems. In this two-way process, the evolutionary-determined emergence of neurons expressing specific immunogenic antigens (brain superautoantigens) has exerted a selection pressure on immune genes shaping the T-cell repertoire. Such a selection pressure on immune genes has translated into the emergence of a finely tuned autoimmune T-cell repertoire that promotes cognition. In another hand, the evolutionary-determined emergence of brain-autoreactive T-cells has exerted a selection pressure on neural genes coding for brain superautoantigens. Such a selection pressure has translated into the emergence of a neural repertoire (defined here as the whole of neurons, synapses and non-neuronal cells involved in cognitive functions) expressing brain superautoantigens. Overall, the brain superautoantigens theory suggests that cognitive evolution might have been primarily driven by internal cues rather than external environmental conditions. Importantly, while providing a unique molecular connection between neural and T-cell repertoires under physiological conditions, brain superautoantigens may also constitute an Achilles heel responsible for the particular susceptibility of Homo sapiens to “neuroimmune co-pathologies” i.e., disorders affecting both neural and T-cell repertoires. These may notably include paraneoplastic syndromes, multiple sclerosis as well as autism, schizophrenia and neurodegenerative diseases. In the context of this theoretical frame, a specific emphasis is given here to the potential evolutionary role exerted by two families of genes, namely the MHC class II genes, involved in antigen presentation to T-cells, and the Foxp genes, which play crucial roles in language (Foxp2) and the regulation of autoimmunity (Foxp3). PMID:29123465

Affective neuroscience of pleasure: reward in humans and animals

PubMed Central

2010-01-01

Introduction Pleasure and reward are generated by brain circuits that are largely shared between humans and other animals. Discussion Here, we survey some fundamental topics regarding pleasure mechanisms and explicitly compare humans and animals. Conclusion Topics surveyed include liking, wanting, and learning components of reward; brain coding versus brain causing of reward; subjective pleasure versus objective hedonic reactions; roles of orbitofrontal cortex and related cortex regions; subcortical hedonic hotspots for pleasure generation; reappraisals of dopamine and pleasure-electrode controversies; and the relation of pleasure to happiness. PMID:18311558

A high resolution spatiotemporal atlas of gene expression of the developing mouse brain

PubMed Central

Thompson, Carol L.; Ng, Lydia; Menon, Vilas; Martinez, Salvador; Lee, Chang-Kyu; Glattfelder, Katie; Sunkin, Susan M.; Henry, Alex; Lau, Christopher; Dang, Chinh; Garcia-Lopez, Raquel; Martinez-Ferre, Almudena; Pombero, Ana; Rubenstein, John L.R.; Wakeman, Wayne B.; Hohmann, John; Dee, Nick; Sodt, Andrew J.; Young, Rob; Smith, Kimberly; Nguyen, Thuc-Nghi; Kidney, Jolene; Kuan, Leonard; Jeromin, Andreas; Kaykas, Ajamete; Miller, Jeremy; Page, Damon; Orta, Geri; Bernard, Amy; Riley, Zackery; Smith, Simon; Wohnoutka, Paul; Hawrylycz, Mike; Puelles, Luis; Jones, Allan R.

2015-01-01

SUMMARY To provide a temporal framework for the genoarchitecture of brain development, in situ hybridization data were generated for embryonic and postnatal mouse brain at 7 developmental stages for ~2100 genes, processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, 7 reference atlases, an ontogenetic ontology, and tools to explore co-expression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (developingmouse.brain-map.org). PMID:24952961

A Neural Basis of Facial Action Recognition in Humans

PubMed Central

Srinivasan, Ramprakash; Golomb, Julie D.

2016-01-01

By combining different facial muscle actions, called action units, humans can produce an extraordinarily large number of facial expressions. Computational models and studies in cognitive science and social psychology have long hypothesized that the brain needs to visually interpret these action units to understand other people's actions and intentions. Surprisingly, no studies have identified the neural basis of the visual recognition of these action units. Here, using functional magnetic resonance imaging and an innovative machine learning analysis approach, we identify a consistent and differential coding of action units in the brain. Crucially, in a brain region thought to be responsible for the processing of changeable aspects of the face, multivoxel pattern analysis could decode the presence of specific action units in an image. This coding was found to be consistent across people, facilitating the estimation of the perceived action units on participants not used to train the multivoxel decoder. Furthermore, this coding of action units was identified when participants attended to the emotion category of the facial expression, suggesting an interaction between the visual analysis of action units and emotion categorization as predicted by the computational models mentioned above. These results provide the first evidence for a representation of action units in the brain and suggest a mechanism for the analysis of large numbers of facial actions and a loss of this capacity in psychopathologies. SIGNIFICANCE STATEMENT Computational models and studies in cognitive and social psychology propound that visual recognition of facial expressions requires an intermediate step to identify visible facial changes caused by the movement of specific facial muscles. Because facial expressions are indeed created by moving one's facial muscles, it is logical to assume that our visual system solves this inverse problem. Here, using an innovative machine learning method and neuroimaging data, we identify for the first time a brain region responsible for the recognition of actions associated with specific facial muscles. Furthermore, this representation is preserved across subjects. Our machine learning analysis does not require mapping the data to a standard brain and may serve as an alternative to hyperalignment. PMID:27098688

Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses

PubMed Central

Baddeley, Michelle; Tobler, Philippe N.; Schultz, Wolfram

2016-01-01

Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment. SIGNIFICANCE STATEMENT Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result in loss of precise representation (e.g., when the avoidance of a loss in a loss-context is coded the same as receipt of a gain in a gain-context). We investigated an intermediate form of adaptation that is efficient while maintaining information about received gains and avoided losses. We found that frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Importantly, adaptation was intermediate, in line with influential models of reference dependence in behavioral economics. PMID:27683899

[Predictive quality of the injury severity score in the systematic use of cranial MRI].

PubMed

Woischneck, D; Lerch, K; Kapapa, T; Skalej, M; Firsching, R

2010-09-01

The ABBREVIATED INJURY SCORE (AIS) for the head is mostly coded on the basis of cranial computed tomography (CT). It defines, to a large extent, the predictive potency of the INJURY SEVERITY SCORE (ISS). The present study investigates whether the predictive capacity of the ISS can be improved by the systematic use of data from cranial MRI. 167 patients, who had been in a coma for at least 24 hours following trauma, underwent an MRI examination within 8 days. All had been found to have an intracranial injury on initial CT. 49 % had also suffered extracranial injuries. The GLASGOW OUTCOME SCALE (GOS) was determined 6 months post trauma. AIS, ISS and GOS values were rated as ordinal measurements. A contingency table was used as the statistical method of analysis, with a significance assumed as p < 0.05 (Chi (2) test). The median ISS based on CT was 16 and did not correlate with the GOS. 63 % of the patients revealed brain stem lesions on MRI. If these were coded with an AIS of 5, the median ISS increased significantly to 29. Thus, the correlation to the GOS was now significant. At ISS scores of 5-9, 18 % of the patients died; at scores of 50-54 the rate of favourable treatment outcomes still amounted to 50 %. Since it is now known that brain stem lesions can also have a favourable prognosis, the AIS coding was modified and adapted to the mortality of the singular types of lesion. Hence the median ISS again decreased to 16. The correlation to the GOS was significant, and the predictive potency of the ISS further improved. The prognostic potency of the REVISED INJURY SEVERITY CLASSIFICATION (RISC) score was improved by use of adapted MRI data. If visible brain stem lesions on MRI were coded according to the AIS guidelines, there was a significant increase in the ISS which correlated significantly to the GOS. If the AIS coding was adjusted to the prognostic significance of individual brain stem lesions, there was a further improvement in the prognostic potency of the ISS. The study encourages the inclusion of data obtained from MRI diagnostics in the ISS calculation. There are alternative ways. © Georg Thieme Verlag KG Stuttgart · New York.

Brain-computer interface analysis of a dynamic visuo-motor task.

PubMed

Logar, Vito; Belič, Aleš

2011-01-01

The area of brain-computer interfaces (BCIs) represents one of the more interesting fields in neurophysiological research, since it investigates the development of the machines that perform different transformations of the brain's "thoughts" to certain pre-defined actions. Experimental studies have reported some successful implementations of BCIs; however, much of the field still remains unexplored. According to some recent reports the phase coding of informational content is an important mechanism in the brain's function and cognition, and has the potential to explain various mechanisms of the brain's data transfer, but it has yet to be scrutinized in the context of brain-computer interface. Therefore, if the mechanism of phase coding is plausible, one should be able to extract the phase-coded content, carried by brain signals, using appropriate signal-processing methods. In our previous studies we have shown that by using a phase-demodulation-based signal-processing approach it is possible to decode some relevant information on the current motor action in the brain from electroencephalographic (EEG) data. In this paper the authors would like to present a continuation of their previous work on the brain-information-decoding analysis of visuo-motor (VM) tasks. The present study shows that EEG data measured during more complex, dynamic visuo-motor (dVM) tasks carries enough information about the currently performed motor action to be successfully extracted by using the appropriate signal-processing and identification methods. The aim of this paper is therefore to present a mathematical model, which by means of the EEG measurements as its inputs predicts the course of the wrist movements as applied by each subject during the task in simulated or real time (BCI analysis). However, several modifications to the existing methodology are needed to achieve optimal decoding results and a real-time, data-processing ability. The information extracted from the EEG could, therefore, be further used for the development of a closed-loop, non-invasive, brain-computer interface. For the case of this study two types of measurements were performed, i.e., the electroencephalographic (EEG) signals and the wrist movements were measured simultaneously, during the subject's performance of a dynamic visuo-motor task. Wrist-movement predictions were computed by using the EEG data-processing methodology of double brain-rhythm filtering, double phase demodulation and double principal component analyses (PCA), each with a separate set of parameters. For the movement-prediction model a fuzzy inference system was used. The results have shown that the EEG signals measured during the dVM tasks carry enough information about the subjects' wrist movements for them to be successfully decoded using the presented methodology. Reasonably high values of the correlation coefficients suggest that the validation of the proposed approach is satisfactory. Moreover, since the causality of the rhythm filtering and the PCA transformation has been achieved, we have shown that these methods can also be used in a real-time, brain-computer interface. The study revealed that using non-causal, optimized methods yields better prediction results in comparison with the causal, non-optimized methodology; however, taking into account that the causality of these methods allows real-time processing, the minor decrease in prediction quality is acceptable. The study suggests that the methodology that was proposed in our previous studies is also valid for identifying the EEG-coded content during dVM tasks, albeit with various modifications, which allow better prediction results and real-time data processing. The results have shown that wrist movements can be predicted in simulated or real time; however, the results of the non-causal, optimized methodology (simulated) are slightly better. Nevertheless, the study has revealed that these methods should be suitable for use in the development of a non-invasive, brain-computer interface. Copyright © 2010 Elsevier B.V. All rights reserved.

Connecting Neurons to a Mobile Robot: An In Vitro Bidirectional Neural Interface

PubMed Central

Novellino, A.; D'Angelo, P.; Cozzi, L.; Chiappalone, M.; Sanguineti, V.; Martinoia, S.

2007-01-01

One of the key properties of intelligent behaviors is the capability to learn and adapt to changing environmental conditions. These features are the result of the continuous and intense interaction of the brain with the external world, mediated by the body. For this reason “embodiment” represents an innovative and very suitable experimental paradigm when studying the neural processes underlying learning new behaviors and adapting to unpredicted situations. To this purpose, we developed a novel bidirectional neural interface. We interconnected in vitro neurons, extracted from rat embryos and plated on a microelectrode array (MEA), to external devices, thus allowing real-time closed-loop interaction. The novelty of this experimental approach entails the necessity to explore different computational schemes and experimental hypotheses. In this paper, we present an open, scalable architecture, which allows fast prototyping of different modules and where coding and decoding schemes and different experimental configurations can be tested. This hybrid system can be used for studying the computational properties and information coding in biological neuronal networks with far-reaching implications for the future development of advanced neuroprostheses. PMID:18350128

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

PubMed

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A

2016-08-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

How the brain assigns a neural tag to arbitrary points in a high-dimensional space

NASA Astrophysics Data System (ADS)

Stevens, Charles

Brains in almost all organisms need to deal with very complex stimuli. For example, most mammals are very good at face recognition, and faces are very complex objects indeed. For example, modern face recognition software represents a face as a point in a 10,000 dimensional space. Every human must be able to learn to recognize any of the 7 billion faces in the world, and can recognize familiar faces after a display of the face is viewed for only a few hundred milliseconds. Because we do not understand how faces are assigned locations in a high-dimensional space by the brain, attacking the problem of how face recognition is accomplished is very difficult. But a much easier problem of the same sort can be studied for odor recognition. For the mouse, each odor is assigned a point in a 1000 dimensional space, and the fruit fly assigns any odor a location in only a 50 dimensional space. A fly has about 50 distinct types of odorant receptor neurons (ORNs), each of which produce nerve impulses at a specific rate for each different odor. This pattern of firing produced across 50 ORNs is called `a combinatorial odor code', and this code assigns every odor a point in a 50 dimensional space that is used to identify the odor. In order to learn the odor, the brain must alter the strength of synapses. The combinatorial code cannot itself by used to change synaptic strength because all odors use same neurons to form the code, and so all synapses would be changed for any odor and the odors could not be distinguished. In order to learn an odor, the brain must assign a set of neurons - the odor tag - that have the property that these neurons (1) should make use of all of the information available about the odor, and (2) insure that any two tags overlap as little as possible (so one odor does not modify synapses used by other odors). In the talk, I will explain how the olfactory system of both the fruit fly and the mouse produce a tag for each odor that has these two properties. Supported by NSF.

24 CFR 578.75 - General operations.

Code of Federal Regulations, 2014 CFR

2014-04-01

... assistance under this part must meet State or local building codes, and in the absence of State or local building codes, the International Residential Code or International Building Code (as applicable to the type of structure) of the International Code Council. (2) Services provided with assistance under this...

24 CFR 578.75 - General operations.

Code of Federal Regulations, 2013 CFR

2013-04-01

... assistance under this part must meet State or local building codes, and in the absence of State or local building codes, the International Residential Code or International Building Code (as applicable to the type of structure) of the International Code Council. (2) Services provided with assistance under this...

Identification of Putative Nuclear Receptors and Steroidogenic Enzymes in Murray-Darling Rainbowfish (Melanotaenia fluviatilis) Using RNA-Seq and De Novo Transcriptome Assembly.

PubMed

Bain, Peter A; Papanicolaou, Alexie; Kumar, Anupama

2015-01-01

Murray-Darling rainbowfish (Melanotaenia fluviatilis [Castelnau, 1878]; Atheriniformes: Melanotaeniidae) is a small-bodied teleost currently under development in Australasia as a test species for aquatic toxicological studies. To date, efforts towards the development of molecular biomarkers of contaminant exposure have been hindered by the lack of available sequence data. To address this, we sequenced messenger RNA from brain, liver and gonads of mature male and female fish and generated a high-quality draft transcriptome using a de novo assembly approach. 149,742 clusters of putative transcripts were obtained, encompassing 43,841 non-redundant protein-coding regions. Deduced amino acid sequences were annotated by functional inference based on similarity with sequences from manually curated protein sequence databases. The draft assembly contained protein-coding regions homologous to 95.7% of the complete cohort of predicted proteins from the taxonomically related species, Oryzias latipes (Japanese medaka). The mean length of rainbowfish protein-coding sequences relative to their medaka homologues was 92.1%, indicating that despite the limited number of tissues sampled a large proportion of the total expected number of protein-coding genes was captured in the study. Because of our interest in the effects of environmental contaminants on endocrine pathways, we manually curated subsets of coding regions for putative nuclear receptors and steroidogenic enzymes in the rainbowfish transcriptome, revealing 61 candidate nuclear receptors encompassing all known subfamilies, and 41 putative steroidogenic enzymes representing all major steroidogenic enzymes occurring in teleosts. The transcriptome presented here will be a valuable resource for researchers interested in biomarker development, protein structure and function, and contaminant-response genomics in Murray-Darling rainbowfish.

Mapping and Deciphering Neural Codes of NMDA Receptor-Dependent Fear Memory Engrams in the Hippocampus

PubMed Central

Tsien, Joe Z.

2013-01-01

Mapping and decoding brain activity patterns underlying learning and memory represents both great interest and immense challenge. At present, very little is known regarding many of the very basic questions regarding the neural codes of memory: are fear memories retrieved during the freezing state or non-freezing state of the animals? How do individual memory traces give arise to a holistic, real-time associative memory engram? How are memory codes regulated by synaptic plasticity? Here, by applying high-density electrode arrays and dimensionality-reduction decoding algorithms, we investigate hippocampal CA1 activity patterns of trace fear conditioning memory code in inducible NMDA receptor knockout mice and their control littermates. Our analyses showed that the conditioned tone (CS) and unconditioned foot-shock (US) can evoke hippocampal ensemble responses in control and mutant mice. Yet, temporal formats and contents of CA1 fear memory engrams differ significantly between the genotypes. The mutant mice with disabled NMDA receptor plasticity failed to generate CS-to-US or US-to-CS associative memory traces. Moreover, the mutant CA1 region lacked memory traces for “what at when” information that predicts the timing relationship between the conditioned tone and the foot shock. The degraded associative fear memory engram is further manifested in its lack of intertwined and alternating temporal association between CS and US memory traces that are characteristic to the holistic memory recall in the wild-type animals. Therefore, our study has decoded real-time memory contents, timing relationship between CS and US, and temporal organizing patterns of fear memory engrams and demonstrated how hippocampal memory codes are regulated by NMDA receptor synaptic plasticity. PMID:24302990

Delirium after coronary bypass surgery evaluated by the organic brain syndrome protocol.

PubMed

Eriksson, Marléne; Samuelsson, Elsa; Gustafson, Yngve; Aberg, Torkel; Engström, Karl Gunnar

2002-08-01

The aim was to evaluate symptoms of delirium from a psychogeriatric perspective occurring postoperative to coronary bypass surgery. Patients, > or = 60 years, scheduled for coronary bypass surgery (n = 52) were enrolled in a prospective descriptive study. The patients were evaluated before and several times after surgery by the Organic Brain Syndrome scale, and delirium was diagnosed according to psychiatric codes. Of the 52 patients, 23% presented delirium. These patients were older than the control group, 73.5 +/- 4.2 and 69.3 +/- 5.9 years, respectively (mean +/- SD, p < 0.01), and had more frequently a history of previous stroke (p < 0.05). Emotional delirium was seen in 83%, hyperactive delirium in about 40%, and 25% were classified to have a psychotic delirium. A major finding was a 58% frequency of hallucinations and illusions among patients with delirium, and a similar rate among those without delirium. Delirium is common after cardiac surgery in particular in older patients, but is often under-diagnosed. Hallucinations were common in both delirious and non-delirious patients.

Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

PubMed Central

Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.

2009-01-01

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688

Localization of the mRNA for the dopamine D sub 2 receptor in the rat brain by in situ hybridization histochemistry

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

Mengod, G.; Martinez-Mir, M.I.; Vilaro, M.T.

1989-11-01

{sup 32}P-labeled oligonucleotides derived from the coding region of rat dopamine D{sub 2} receptor cDNA were used as probes to localize cells in the rat brain that contain the mRNA coding for this receptor by using in situ hybridization histochemistry. The highest level of hybridization was found in the intermediate lobe of the pituitary gland. High mRNA content was observed in the anterior lobe of the pituitary gland, the nuclei caudate-putamen and accumbens, and the olfactory tubercle. Lower levels were seen in the substantia nigra pars compacta and the ventral tegmental area, as well as in the lateral mammillary body.more » In these areas the distribution was comparable to that of the dopamine D{sub 2} receptor binding sites as visualized by autoradiography using ({sup 3}H)SDZ 205-502 as a ligand. However, in some areas such as the olfactory bulb, neocortex, hippocampus, superior colliculus, and cerebellum, D{sub 2} receptors have been visualized but no significant hybridization signal could be detected. The mRNA coding for these receptors in these areas could be contained in cells outside those brain regions, be different from the one recognized by our probes, or be present at levels below the detection limits of our procedure. The possibility of visualizing and quantifying the mRNA coding for dopamine D{sub 2} receptor at the microscopic level will yield more information about the in vivo regulation of the synthesis of these receptor and their alteration following selective lesions or drug treatments.« less

Molecular codes for neuronal individuality and cell assembly in the brain

PubMed Central

Yagi, Takeshi

2012-01-01

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain. PMID:22518100

Coding rate and duration of vocalizations of the frog, Xenopus laevis.

PubMed

Zornik, Erik; Yamaguchi, Ayako

2012-08-29

Vocalizations involve complex rhythmic motor patterns, but the underlying temporal coding mechanisms in the nervous system are poorly understood. Using a recently developed whole-brain preparation from which "fictive" vocalizations are readily elicited in vitro, we investigated the cellular basis of temporal complexity of African clawed frogs (Xenopus laevis). Male advertisement calls contain two alternating components--fast trills (∼300 ms) and slow trills (∼700 ms) that contain clicks repeated at ∼60 and ∼30 Hz, respectively. We found that males can alter the duration of fast trills without changing click rates. This finding led us to hypothesize that call rate and duration are regulated by independent mechanisms. We tested this by obtaining whole-cell patch-clamp recordings in the "fictively" calling isolated brain. We discovered a single type of premotor neuron with activity patterns correlated with both the rate and duration of fast trills. These "fast-trill neurons" (FTNs) exhibited long-lasting depolarizations (LLDs) correlated with each fast trill and action potentials that were phase-locked with motor output-neural correlates of call duration and rate, respectively. When depolarized without central pattern generator activation, FTNs produced subthreshold oscillations and action potentials at fast-trill rates, indicating FTN resonance properties are tuned to, and may dictate, the fast-trill rhythm. NMDA receptor (NMDAR) blockade eliminated LLDs in FTNs, and NMDAR activation in synaptically isolated FTNs induced repetitive LLDs. These results suggest FTNs contain an NMDAR-dependent mechanism that may regulate fast-trill duration. We conclude that a single premotor neuron population employs distinct mechanisms to regulate call rate and duration.

Neural imaging in songbirds using fiber optic fluorescence microscopy

NASA Astrophysics Data System (ADS)

Nooshabadi, Fatemeh; Hearn, Gentry; Lints, Thierry; Maitland, Kristen C.

2012-02-01

The song control system of juvenile songbirds is an important model for studying the developmental acquisition and generation of complex learned vocal motor sequences, two processes that are fundamental to human speech and language. To understand the neural mechanisms underlying song production, it is critical to characterize the activity of identified neurons in the song control system when the bird is singing. Neural imaging in unrestrained singing birds, although technically challenging, will advance our understanding of neural ensemble coding mechanisms in this system. We are exploring the use of a fiber optic microscope for functional imaging in the brain of behaving and singing birds in order to better understand the contribution of a key brain nucleus (high vocal center nucleus; HVC) to temporal aspects of song motor control. We have constructed a fluorescence microscope with LED illumination, a fiber bundle for transmission of fluorescence excitation and emission light, a ~2x GRIN lens, and a CCD for image acquisition. The system has 2 μm resolution, 375 μm field of view, 200 μm working distance, and 1 mm outer diameter. As an initial characterization of this setup, neurons in HVC were imaged using the fiber optic microscope after injection of quantum dots or fluorescent retrograde tracers into different song nuclei. A Lucid Vivascope confocal microscope was used to confirm the imaging results. Long-term imaging of the activity of these neurons in juvenile birds during singing may lead us to a better understanding of the central motor codes for song and the central mechanism by which auditory experience modifies song motor commands to enable vocal learning and imitation.

Reality = Relevance? Insights from Spontaneous Modulations of the Brain's Default Network when Telling Apart Reality from Fiction

PubMed Central

Abraham, Anna; von Cramon, D. Yves

2009-01-01

Background Although human beings regularly experience fictional worlds through activities such as reading novels and watching movies, little is known about what mechanisms underlie our implicit knowledge of the distinction between reality and fiction. The first neuroimaging study to address this issue revealed that the mere exposure to contexts involving real entities compared to fictional characters led to engagement of regions in the anterior medial prefrontal and posterior cingulate cortices (amPFC, PCC). As these core regions of the brain's default network are involved during self-referential processing and autobiographical memory retrieval, it was hypothesized that real entities may be conceptually coded as being more personally relevant to us than fictional characters. Methodology/Principal Findings In the present functional magnetic resonance imaging (fMRI) study, we directly test the hypothesis that entity-associated personal relevance is the critical factor underlying the differential engagement of these brain regions by comparing the brain's response when processing contexts involving family or friends (high relevance), famous people (medium relevance), or fictional characters (low relevance). In line with predictions, a gradient pattern of activation was observed such that higher entity-associated personal relevance was associated with stronger activation in the amPFC and the PCC. Conclusions/Significance The results of the study have several important implications. Firstly, they provide informed grounds for characterizing the dynamics of reality-fiction distinction. Secondly, they provide further insights into the functions of the amPFC and the PCC. Thirdly, in view of the current debate related to the functional relevance and specificity of brain's default network, they reveal a novel approach by which the functions of this network can be further explored. PMID:19277108

76 FR 37034 - Certain Employee Remuneration in Excess of $1,000,000 Under Internal Revenue Code Section 162(m)

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-24

... Certain Employee Remuneration in Excess of $1,000,000 Under Internal Revenue Code Section 162(m) AGENCY... remuneration in excess of $1,000,000 under the Internal Revenue Code (Code). The proposed regulations clarify... stock options, it is intended that the directors may retain discretion as to the exact number of options...

Reward skewness coding in the insula independent of probability and loss

PubMed Central

Tobler, Philippe N.

2011-01-01

Rewards in the natural environment are rarely predicted with complete certainty. Uncertainty relating to future rewards has typically been defined as the variance of the potential outcomes. However, the asymmetry of predicted reward distributions, known as skewness, constitutes a distinct but neuroscientifically underexplored risk term that may also have an impact on preference. By changing only reward magnitudes, we study skewness processing in equiprobable ternary lotteries involving only gains and constant probabilities, thus excluding probability distortion or loss aversion as mechanisms for skewness preference formation. We show that individual preferences are sensitive to not only the mean and variance but also to the skewness of predicted reward distributions. Using neuroimaging, we show that the insula, a structure previously implicated in the processing of reward-related uncertainty, responds to the skewness of predicted reward distributions. Some insula responses increased in a monotonic fashion with skewness (irrespective of individual skewness preferences), whereas others were similarly elevated to both negative and positive as opposed to no reward skew. These data support the notion that the asymmetry of reward distributions is processed in the brain and, taken together with replicated findings of mean coding in the striatum and variance coding in the cingulate, suggest that the brain codes distinct aspects of reward distributions in a distributed fashion. PMID:21849610

All-terrain vehicles (ATVs) on the road: a serious traffic safety and public health concern.

PubMed

Denning, Gerene; Jennissen, Charles; Harland, Karisa; Ellis, David; Buresh, Christopher

2013-01-01

On-road all-terrain vehicle (ATV) crashes are frequent occurrences that disproportionately impact rural communities. These crashes occur despite most states having laws restricting on-road ATV use. A number of overall risk factors for ATV-related injuries have been identified (e.g., lack of helmet, carrying passengers). However, few studies have determined the relative contribution of these and other factors to on-road crashes and injuries. The objective of our study was to determine whether there were differences between on- and off-road ATV crashes in their demographics and/or mechanisms and outcomes of injuries. Data were derived from our statewide ATV injury surveillance database (2002-2009). Crash location and crash and injury mechanisms were coded using a modification of the Department of Transportation (DOT) coding system. Descriptive analyses and statistical comparisons (chi-square test) of variables were performed. Multivariate logistic regression analysis was used to determine relative risk. 976 records were included in the final analysis, with 38 percent of the injured individuals from on-road crashes. Demographics were similar for crashes at each location, with approximately 80 percent males, 30 percent under the age of 16, and 15 percent passengers. However, females and youths under 16 were over 4 times more likely to be passengers (P ≤ 0.0001), regardless of crash location. Compared to those off-road, on-road crash victims were approximately 10 times more likely to be involved in a vehicle-vehicle collision (P < 0.001), 3 times more likely to have a severe brain injury (P < 0.001), and twice as likely to have suffered major trauma (P < 0.001). Adult operators in on-road crashes were also twice as likely to test positive for alcohol as those off-road (P < 0.05). Helmet use significantly reduced the odds of sustaining a brain injury and on-road victims were only half as likely to be helmeted (P < 0.01). More than 1 in 3 on-road crashes involved a collision with another vehicle, suggesting that ATVs on the road represent a potential traffic safety concern. Of note, helmets were associated with reduced risk for the number and severity of brain injuries, providing further support for the importance of helmet use. Finally, even controlling for helmet use, on-road crash victims suffered more major trauma and severe brain injuries than those off-road. Overall, our data reinforce the importance of laws restricting ATV road use and the need for effective enforcement, as well as the need to increase user education about ATV road-use laws and the dangers of riding on the roads.

MicroRNA's impact on neurotransmitter and neuropeptide systems: small but mighty mediators of anxiety.

PubMed

Martinetz, Stefanie

2016-06-01

Psychiatric disorders rank among the most common severe diseases worldwide, with millions of people affected worldwide every year. The symptoms are manifold, and the outcome for the patients is often unclear. As a high and yearly rising cost burden for society, anxiety disorders, depression and their related mental disorders are currently a well-researched topic in order to develop new functional pharmacological therapies as alternatives to those that are in use and bear many unpleasant side effects. Brain circuitries, such as those underlying anxiety formations, are mainly driven by the interplay of various neurotransmitter systems and the interaction of different brain loci, as well as the modulating impact of neuropeptides. Targeting those networks is a complex but promising way to regulate mood. Alterations on molecular level of the neuronal cell in response to respective receptor activation, especially at post-transcriptional level via the highly regulatory function of non-coding RNAs such as microRNAs (miRNAs) seem to hold a promising future in the development of novel therapeutic strategies and are therefore under intensified investigation. This review focusses on the impact of miRNAs on the neurotransmitter and neuropeptide systems of the central nervous system relevant for the formation of anxiety disorders and discusses the potential of miRNAs for the development of new therapeutic strategies for anxiety and mood disorders.

What the success of brain imaging implies about the neural code.

PubMed

Guest, Olivia; Love, Bradley C

2017-01-19

The success of fMRI places constraints on the nature of the neural code. The fact that researchers can infer similarities between neural representations, despite fMRI's limitations, implies that certain neural coding schemes are more likely than others. For fMRI to succeed given its low temporal and spatial resolution, the neural code must be smooth at the voxel and functional level such that similar stimuli engender similar internal representations. Through proof and simulation, we determine which coding schemes are plausible given both fMRI's successes and its limitations in measuring neural activity. Deep neural network approaches, which have been forwarded as computational accounts of the ventral stream, are consistent with the success of fMRI, though functional smoothness breaks down in the later network layers. These results have implications for the nature of the neural code and ventral stream, as well as what can be successfully investigated with fMRI.

Estimating the functional dimensionality of neural representations.

PubMed

Ahlheim, Christiane; Love, Bradley C

2018-06-07

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

Coding of visual object features and feature conjunctions in the human brain.

PubMed

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

High Brain Ammonia Tolerance and Down-Regulation of Na+:K+:2Cl- Cotransporter 1b mRNA and Protein Expression in the Brain of the Swamp Eel, Monopterus albus, Exposed to Environmental Ammonia or Terrestrial Conditions

PubMed Central

Ip, Yuen K.; Hou, Zhisheng; Chen, Xiu L.; Ong, Jasmine L. Y.; Chng, You R.; Ching, Biyun; Hiong, Kum C.; Chew, Shit F.

2013-01-01

Na+:K+:2Cl- cotransporter 1 (NKCC1) has been implicated in mediating ischemia-, trauma- or ammonia-induced astrocyte swelling/brain edema in mammals. This study aimed to determine the effects of ammonia or terrestrial exposure on ammonia concentrations in the plasma and brain, and the mRNA expression and protein abundance of nkcc/Nkcc in the brain, of the swamp eel Monopterus albus . Ammonia exposure led to a greater increase in the ammonia concentration in the brain of M. albus than terrestrial exposure. The brain ammonia concentration of M. albus reached 4.5 µmol g-1 and 2.7 µmol g-1 after 6 days of exposure to 50 mmol l-1 NH4Cl and terrestrial conditions, respectively. The full cDNA coding sequence of nkcc1b from M. albus brain comprised 3276 bp and coded for 1092 amino acids with an estimated molecular mass of 119.6 kDa. A molecular characterization indicated that it could be activated through phosphorylation and/or glycosylation by osmotic and/or oxidative stresses. Ammonia exposure for 1 day or 6 days led to significant decreases in the nkcc1b mRNA expression and Nkcc1b protein abundance in the brain of M. albus. In comparison, a significant decrease in nkcc1b mRNA expression was observed in the brain of M. albus only after 6 days of terrestrial exposure, but both 1 day and 6 days of terrestrial exposure resulted in significant decreases in the protein abundance of Nkcc1b. These results are novel because it has been established in mammals that ammonia up-regulates NKCC1 expression in astrocytes and NKCC1 plays an important role in ammonia-induced astrocyte swelling and brain edema. By contrast, our results indicate for the first time that M. albus is able to down-regulate the mRNA and protein expression of nkcc1b/Nkcc1b in the brain when confronted with ammonia toxicity, which could be one of the contributing factors to its extraordinarily high brain ammonia tolerance. PMID:24069137

De novo mutations in regulatory elements in neurodevelopmental disorders

PubMed Central

Short, Patrick J.; McRae, Jeremy F.; Gallone, Giuseppe; Sifrim, Alejandro; Won, Hyejung; Geschwind, Daniel H.; Wright, Caroline F.; Firth, Helen V; FitzPatrick, David R.; Barrett, Jeffrey C.; Hurles, Matthew E.

2018-01-01

We previously estimated that 42% of patients with severe developmental disorders carry pathogenic de novo mutations in coding sequences. The role of de novo mutations in regulatory elements affecting genes associated with developmental disorders, or other genes, has been essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 patients with developmental disorders. Here we show that de novo mutations in highly evolutionarily conserved fetal brain-active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant twofold enrichment of recurrently mutated elements. We estimate that, genome-wide, 1-3% of patients without a diagnostic coding variant carry pathogenic de novo mutations in fetal brain-active regulatory elements and that only 0.15% of all possible mutations within highly conserved fetal brain-active elements cause neurodevelopmental disorders with a dominant mechanism. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasize the importance of combining functional and evolutionary evidence to identify regulatory causes of genetic disorders. PMID:29562236

Alteration of the coenzyme A biosynthetic pathway in neurodegeneration with brain iron accumulation syndromes.

PubMed

Venco, Paola; Dusi, Sabrina; Valletta, Lorella; Tiranti, Valeria

2014-08-01

NBIA (neurodegeneration with brain iron accumulation) comprises a heterogeneous group of neurodegenerative diseases having as a common denominator, iron overload in specific brain areas, mainly basal ganglia and globus pallidus. In the past decade a bunch of disease genes have been identified, but NBIA pathomechanisms are still not completely clear. PKAN (pantothenate kinase-associated neurodegeneration), an autosomal recessive disorder with progressive impairment of movement, vision and cognition, is the most common form of NBIA. It is caused by mutations in the PANK2 (pantothenate kinase 2) gene, coding for a mitochondrial enzyme that phosphorylates vitamin B5 in the first reaction of the CoA (coenzyme A) biosynthetic pathway. A distinct form of NBIA, denominated CoPAN (CoA synthase protein-associated neurodegeneration), is caused by mutations in the CoASY (CoA synthase) gene coding for a bifunctional mitochondrial enzyme, which catalyses the final steps of CoA biosynthesis. These two inborn errors of CoA metabolism further support the concept that dysfunctions in CoA synthesis may play a crucial role in the pathogenesis of NBIA.

Coarse coding and discourse comprehension in adults with right hemisphere brain damage

PubMed Central

Tompkins, Connie A.; Scharp, Victoria L.; Meigh, Kimberly M.; Fassbinder, Wiltrud

2009-01-01

Background Various investigators suggest that some discourse-level comprehension difficulties in adults with right hemisphere brain damage (RHD) have a lexical-semantic basis. As words are processed, the intact right hemisphere arouses and sustains activation of a wide-ranging network of secondary or peripheral meanings and features—a phenomenon dubbed “coarse coding”. Coarse coding impairment has been postulated to underpin some prototypical RHD comprehension deficits, such as difficulties with nonliteral language interpretation, discourse integration, some kinds of inference generation, and recovery when a reinterpretation is needed. To date, however, no studies have addressed the hypothesised link between coarse coding deficit and discourse comprehension in RHD. Aims The current investigation examined whether coarse coding was related to performance on two measures of narrative comprehension in adults with RHD. Methods & Procedures Participants were 32 adults with unilateral RHD from cerebrovascular accident, and 38 adults without brain damage. Coarse coding was operationalised as poor activation of peripheral/weakly related semantic features of words. For the coarse coding assessment, participants listened to spoken sentences that ended in a concrete noun. Each sentence was followed by a spoken target phoneme string. Targets were subordinate semantic features of the sentence-final nouns that were incompatible with their dominant mental representations (e.g., “rotten” for apple). Targets were presented at two post-noun intervals. A lexical decision task was used to gauge both early activation and maintenance of activation of these weakly related semantic features. One of the narrative tasks assessed comprehension of implied main ideas and details, while the other indexed high-level inferencing and integration. Both comprehension tasks were presented auditorily. For all tasks, accuracy of performance was the dependent measure. Correlations were computed within the RHD group between both the early and late coarse coding measures and the two discourse measures. Additionally, ANCOVA and independent t-tests were used to compare both early and sustained coarse coding in subgroups of good and poor RHD comprehenders. Outcomes & Results The group with RHD was less accurate than the control group on all measures. The finding of coarse coding impairment (difficulty activating/sustaining activation of a word’s peripheral features) may appear to contradict prior evidence of RHD suppression deficit (prolonged activation for context-inappropriate meanings of words). However, the sentence contexts in this study were unbiased and thus did not provide an appropriate test of suppression function. Correlations between coarse coding and the discourse measures were small and nonsignificant. There were no differences in coarse coding between RHD comprehension subgroups on the high-level inferencing task. There was also no distinction in early coarse coding for subgroups based on comprehension of implied main ideas and details. But for these same subgroups, there was a difference in sustained coarse coding. Poorer RHD comprehenders of implied information from discourse were also poorer at maintaining activation for semantically distant features of concrete nouns. Conclusions This study provides evidence of a variant of the postulated link between coarse coding and discourse comprehension in RHD. Specifically, adults with RHD who were particularly poor at sustaining activation for peripheral semantic features of nouns were also relatively poor comprehenders of implied information from narratives. PMID:20037670

S-values calculated from a tomographic head/brain model for brain imaging

NASA Astrophysics Data System (ADS)

Chao, Tsi-chian; Xu, X. George

2004-11-01

A tomographic head/brain model was developed from the Visible Human images and used to calculate S-values for brain imaging procedures. This model contains 15 segmented sub-regions including caudate nucleus, cerebellum, cerebral cortex, cerebral white matter, corpus callosum, eyes, lateral ventricles, lenses, lentiform nucleus, optic chiasma, optic nerve, pons and middle cerebellar peduncle, skull CSF, thalamus and thyroid. S-values for C-11, O-15, F-18, Tc-99m and I-123 have been calculated using this model and a Monte Carlo code, EGS4. Comparison of the calculated S-values with those calculated from the MIRD (1999) stylized head/brain model shows significant differences. In many cases, the stylized head/brain model resulted in smaller S-values (as much as 88%), suggesting that the doses to a specific patient similar to the Visible Man could have been underestimated using the existing clinical dosimetry.

Sparse coded image super-resolution using K-SVD trained dictionary based on regularized orthogonal matching pursuit.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2015-01-01

Image super-resolution (SR) plays a vital role in medical imaging that allows a more efficient and effective diagnosis process. Usually, diagnosing is difficult and inaccurate from low-resolution (LR) and noisy images. Resolution enhancement through conventional interpolation methods strongly affects the precision of consequent processing steps, such as segmentation and registration. Therefore, we propose an efficient sparse coded image SR reconstruction technique using a trained dictionary. We apply a simple and efficient regularized version of orthogonal matching pursuit (ROMP) to seek the coefficients of sparse representation. ROMP has the transparency and greediness of OMP and the robustness of the L1-minization that enhance the dictionary learning process to capture feature descriptors such as oriented edges and contours from complex images like brain MRIs. The sparse coding part of the K-SVD dictionary training procedure is modified by substituting OMP with ROMP. The dictionary update stage allows simultaneously updating an arbitrary number of atoms and vectors of sparse coefficients. In SR reconstruction, ROMP is used to determine the vector of sparse coefficients for the underlying patch. The recovered representations are then applied to the trained dictionary, and finally, an optimization leads to high-resolution output of high-quality. Experimental results demonstrate that the super-resolution reconstruction quality of the proposed scheme is comparatively better than other state-of-the-art schemes.

A stimulus-dependent spike threshold is an optimal neural coder

PubMed Central

Jones, Douglas L.; Johnson, Erik C.; Ratnam, Rama

2015-01-01

A neural code based on sequences of spikes can consume a significant portion of the brain's energy budget. Thus, energy considerations would dictate that spiking activity be kept as low as possible. However, a high spike-rate improves the coding and representation of signals in spike trains, particularly in sensory systems. These are competing demands, and selective pressure has presumably worked to optimize coding by apportioning a minimum number of spikes so as to maximize coding fidelity. The mechanisms by which a neuron generates spikes while maintaining a fidelity criterion are not known. Here, we show that a signal-dependent neural threshold, similar to a dynamic or adapting threshold, optimizes the trade-off between spike generation (encoding) and fidelity (decoding). The threshold mimics a post-synaptic membrane (a low-pass filter) and serves as an internal decoder. Further, it sets the average firing rate (the energy constraint). The decoding process provides an internal copy of the coding error to the spike-generator which emits a spike when the error equals or exceeds a spike threshold. When optimized, the trade-off leads to a deterministic spike firing-rule that generates optimally timed spikes so as to maximize fidelity. The optimal coder is derived in closed-form in the limit of high spike-rates, when the signal can be approximated as a piece-wise constant signal. The predicted spike-times are close to those obtained experimentally in the primary electrosensory afferent neurons of weakly electric fish (Apteronotus leptorhynchus) and pyramidal neurons from the somatosensory cortex of the rat. We suggest that KCNQ/Kv7 channels (underlying the M-current) are good candidates for the decoder. They are widely coupled to metabolic processes and do not inactivate. We conclude that the neural threshold is optimized to generate an energy-efficient and high-fidelity neural code. PMID:26082710

75 FR 33992 - Interest and Penalty Suspension Provisions Under Section 6404(g) of the Internal Revenue Code

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-16

... Interest and Penalty Suspension Provisions Under Section 6404(g) of the Internal Revenue Code AGENCY.... SUMMARY: This document contains final regulations under section 6404(g)(2)(E) of the Internal Revenue Code... Procedure and Administration Regulations (26 CFR part 301) by adding rules under section 6404(g) relating to...

Distinct Correlation Structure Supporting a Rate-Code for Sound Localization in the Owl’s Auditory Forebrain

PubMed Central

2017-01-01

Abstract While a topographic map of auditory space exists in the vertebrate midbrain, it is absent in the forebrain. Yet, both brain regions are implicated in sound localization. The heterogeneous spatial tuning of adjacent sites in the forebrain compared to the midbrain reflects different underlying circuitries, which is expected to affect the correlation structure, i.e., signal (similarity of tuning) and noise (trial-by-trial variability) correlations. Recent studies have drawn attention to the impact of response correlations on the information readout from a neural population. We thus analyzed the correlation structure in midbrain and forebrain regions of the barn owl’s auditory system. Tetrodes were used to record in the midbrain and two forebrain regions, Field L and the downstream auditory arcopallium (AAr), in anesthetized owls. Nearby neurons in the midbrain showed high signal and noise correlations (RNCs), consistent with shared inputs. As previously reported, Field L was arranged in random clusters of similarly tuned neurons. Interestingly, AAr neurons displayed homogeneous monotonic azimuth tuning, while response variability of nearby neurons was significantly less correlated than the midbrain. Using a decoding approach, we demonstrate that low RNC in AAr restricts the potentially detrimental effect it can have on information, assuming a rate code proposed for mammalian sound localization. This study harnesses the power of correlation structure analysis to investigate the coding of auditory space. Our findings demonstrate distinct correlation structures in the auditory midbrain and forebrain, which would be beneficial for a rate-code framework for sound localization in the nontopographic forebrain representation of auditory space. PMID:28674698

75 FR 32519 - Small Business Size Standards: Waiver of the Nonmanufacturer Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-08

... (Compressed and Liquefied Gases), under NAICS code 325120 (Industrial Gases Manufacturing). On March 23, 2010...), under NAICS code 325120 (Industrial Gases Manufacturing). Dated: June 1, 2010. Karen Hontz, Director... Propane Gas (LPG), North American Industry Classification System (NAICS) code 325120, Product Service Code...

The problem with value

PubMed Central

O’Doherty, John P.

2015-01-01

Neural correlates of value have been extensively reported in a diverse set of brain regions. However, in many cases it is difficult to determine whether a particular neural response pattern corresponds to a value-signal per se as opposed to an array of alternative non-value related processes, such as outcome-identity coding, informational coding, encoding of autonomic and skeletomotor consequences, alongside previously described “salience” or “attentional” effects. Here, I review a number of experimental manipulations that can be used to test for value, and I identify the challenges in ascertaining whether a particular neural response is or is not a value signal. Finally, I emphasize that some non-value related signals may be especially informative as a means of providing insight into the nature of the decision-making related computations that are being implemented in a particular brain region. PMID:24726573

The Sociobiological Foundations of Stability and Support Operations

DTIC Science & Technology

1999-01-01

of fatherhood. Parental responsibility is not a factor for the warrior rapist as future proof of paternity is unlikely. In raping the wives and...allows a single parent to replicate his genetic code for as long as the reproductive resources last. If there is a change in the environment or the...aggression. The mammalian brain controls, among other emotions, social behavior and the nurturing of children . The surrounding primate brain gives man

Autoradiographic Distribution and Applied Pharmacological Characteristics of Dextromethorphan and Related Antitissue/Anticonvulsant Drugs and Novel Analogs.

DTIC Science & Technology

1994-10-01

Human Brain PRINCIPAL INVESTIGATOR: Professor Norman G. Bowery CONTRACTING ORGANIZATION: University of London Department of Pharmacology The School...Rat and Human Brain 12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for public release; distribution unlimited 13. ABSTRACT...DM ’bindinj was clearly not a marker for the degree of neuronal damage. At autoradiographic technique is als( being developed for examining the binding

BrainLiner: A Neuroinformatics Platform for Sharing Time-Aligned Brain-Behavior Data

PubMed Central

Takemiya, Makoto; Majima, Kei; Tsukamoto, Mitsuaki; Kamitani, Yukiyasu

2016-01-01

Data-driven neuroscience aims to find statistical relationships between brain activity and task behavior from large-scale datasets. To facilitate high-throughput data processing and modeling, we created BrainLiner as a web platform for sharing time-aligned, brain-behavior data. Using an HDF5-based data format, BrainLiner treats brain activity and data related to behavior with the same salience, aligning both behavioral and brain activity data on a common time axis. This facilitates learning the relationship between behavior and brain activity. Using a common data file format also simplifies data processing and analyses. Properties describing data are unambiguously defined using a schema, allowing machine-readable definition of data. The BrainLiner platform allows users to upload and download data, as well as to explore and search for data from the web platform. A WebGL-based data explorer can visualize highly detailed neurophysiological data from within the web browser, and a data-driven search feature allows users to search for similar time windows of data. This increases transparency, and allows for visual inspection of neural coding. BrainLiner thus provides an essential set of tools for data sharing and data-driven modeling. PMID:26858636

An electrocorticographic BCI using code-based VEP for control in video applications: a single-subject study

PubMed Central

Kapeller, Christoph; Kamada, Kyousuke; Ogawa, Hiroshi; Prueckl, Robert; Scharinger, Josef; Guger, Christoph

2014-01-01

A brain-computer-interface (BCI) allows the user to control a device or software with brain activity. Many BCIs rely on visual stimuli with constant stimulation cycles that elicit steady-state visual evoked potentials (SSVEP) in the electroencephalogram (EEG). This EEG response can be generated with a LED or a computer screen flashing at a constant frequency, and similar EEG activity can be elicited with pseudo-random stimulation sequences on a screen (code-based BCI). Using electrocorticography (ECoG) instead of EEG promises higher spatial and temporal resolution and leads to more dominant evoked potentials due to visual stimulation. This work is focused on BCIs based on visual evoked potentials (VEP) and its capability as a continuous control interface for augmentation of video applications. One 35 year old female subject with implanted subdural grids participated in the study. The task was to select one out of four visual targets, while each was flickering with a code sequence. After a calibration run including 200 code sequences, a linear classifier was used during an evaluation run to identify the selected visual target based on the generated code-based VEPs over 20 trials. Multiple ECoG buffer lengths were tested and the subject reached a mean online classification accuracy of 99.21% for a window length of 3.15 s. Finally, the subject performed an unsupervised free run in combination with visual feedback of the current selection. Additionally, an algorithm was implemented that allowed to suppress false positive selections and this allowed the subject to start and stop the BCI at any time. The code-based BCI system attained very high online accuracy, which makes this approach very promising for control applications where a continuous control signal is needed. PMID:25147509

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.

PubMed

Bakhurin, Konstantin I; Goudar, Vishwa; Shobe, Justin L; Claar, Leslie D; Buonomano, Dean V; Masmanidis, Sotiris C

2017-01-25

Telling time is fundamental to many forms of learning and behavior, including the anticipation of rewarding events. Although the neural mechanisms underlying timing remain unknown, computational models have proposed that the brain represents time in the dynamics of neural networks. Consistent with this hypothesis, changing patterns of neural activity dynamically in a number of brain areas-including the striatum and cortex-has been shown to encode elapsed time. To date, however, no studies have explicitly quantified and contrasted how well different areas encode time by recording large numbers of units simultaneously from more than one area. Here, we performed large-scale extracellular recordings in the striatum and orbitofrontal cortex of mice that learned the temporal relationship between a stimulus and a reward and reported their response with anticipatory licking. We used a machine-learning algorithm to quantify how well populations of neurons encoded elapsed time from stimulus onset. Both the striatal and cortical networks encoded time, but the striatal network outperformed the orbitofrontal cortex, a finding replicated both in simultaneously and nonsimultaneously recorded corticostriatal datasets. The striatal network was also more reliable in predicting when the animals would lick up to ∼1 s before the actual lick occurred. Our results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate "clock" as it integrates information across multiple cortical areas. The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs. Copyright © 2017 the authors 0270-6474/17/370854-17$15.00/0.

Hyperforin changes the zinc-storage capacities of brain cells.

PubMed

Gibon, Julien; Richaud, Pierre; Bouron, Alexandre

2011-12-01

In vitro and in vivo experiments were carried out to investigate the consequences on brain cells of a chronic treatment with hyperforin, a plant extract known to dissipate the mitochondrial membrane potential and to release Zn(2+) and Ca(2+) from these organelles. Dissociated cortical neurons were grown in a culture medium supplemented with 1 μM hyperforin. Live-cell imaging experiments with the fluorescent probes FluoZin-3 and Fluo-4 show that a 3 day-hyperforin treatment diminishes the size of the hyperforin-sensitive pools of Ca(2+) and Zn(2+) whereas it increases the size of the DTDP-sensitive pool of Zn(2+) without affecting the ionomycin-sensitive pool of Ca(2+). When assayed by quantitative PCR the levels of mRNA coding for metallothioneins (MTs) I, II and III were increased in cortical neurons after a 3 day-hyperforin treatment. This was prevented by the zinc chelator TPEN, indicating that the plant extract controls the expression of MTs in a zinc-dependent manner. Brains of adult mice who received a daily injection (i.p.) of hyperforin (4 mg/kg/day) for 4 weeks had a higher sulphur content than control animals. They also exhibited an enhanced expression of the genes coding for MTs. However, the long-term treatment did not affect the brain levels of calcium and zinc. Based on these results showing that hyperforin influences the size of the internal pools of Zn(2+), the expression of MTs and the brain cellular sulphur content, it is proposed that hyperforin changes the Zn-storage capacity of brain cells and interferes with their thiol status. Copyright © 2011 Elsevier Ltd. All rights reserved.

Detecting and interpreting conscious experiences in behaviorally non-responsive patients.

PubMed

Naci, Lorina; Sinai, Leah; Owen, Adrian M

2017-01-15

Decoding the contents of consciousness from brain activity is one of the most challenging frontiers of cognitive neuroscience. The ability to interpret mental content without recourse to behavior is most relevant for understanding patients who may be demonstrably conscious, but entirely unable to speak or move willfully in any way, precluding any systematic investigation of their conscious experience. The lack of consistent behavioral responsivity engenders unique challenges to decoding any conscious experiences these patients may have solely based on their brain activity. For this reason, paradigms that have been successful in healthy individuals cannot serve to interpret conscious mental states in this patient group. Until recently, patient studies have used structured instructions to elicit willful modulation of brain activity according to command, in order to decode the presence of willful brain-based responses in this patient group. In recent work, we have used naturalistic paradigms, such as watching a movie or listening to an audio-story, to demonstrate that a common neural code supports conscious experiences in different individuals. Moreover, we have demonstrated that this code can be used to interpret the conscious experiences of a patient who had remained non-responsive for several years. This approach is easy to administer, brief, and does not require compliance with task instructions. Rather, it engages attention naturally through meaningful stimuli that are similar to the real-world sensory information in a patient's environment. Therefore, it may be particularly suited to probing consciousness and revealing residual brain function in highly impaired, acute, patients in a comatose state, thus helping to improve diagnostication and prognostication for this vulnerable patient group from the critical early stages of severe brain-injury. Copyright © 2015 Elsevier Inc. All rights reserved.

Genetics of Cerebellar and Neocortical Expansion in Anthropoid Primates: A Comparative Approach

PubMed Central

Harrison, Peter W.; Montgomery, Stephen H.

2017-01-01

What adaptive changes in brain structure and function underpin the evolution of increased cognitive performance in humans and our close relatives? Identifying the genetic basis of brain evolution has become a major tool in answering this question. Numerous cases of positive selection, altered gene expression or gene duplication have been identified that may contribute to the evolution of the neocortex, which is widely assumed to play a predominant role in cognitive evolution. However, the components of the neocortex co-evolve with other functionally interdependent regions of the brain, most notably in the cerebellum. The cerebellum is linked to a range of cognitive tasks and expanded rapidly during hominoid evolution. Here we present data that suggest that, across anthropoid primates, protein-coding genes with known roles in cerebellum development were just as likely to be targeted by selection as genes linked to cortical development. Indeed, based on currently available gene ontology data, protein-coding genes with known roles in cerebellum development are more likely to have evolved adaptively during hominoid evolution. This is consistent with phenotypic data suggesting an accelerated rate of cerebellar expansion in apes that is beyond that predicted from scaling with the neocortex in other primates. Finally, we present evidence that the strength of selection on specific genes is associated with variation in the volume of either the neocortex or the cerebellum, but not both. This result provides preliminary evidence that co-variation between these brain components during anthropoid evolution may be at least partly regulated by selection on independent loci, a conclusion that is consistent with recent intraspecific genetic analyses and a mosaic model of brain evolution that predicts adaptive evolution of brain structure. PMID:28683440

Embodying Others in Immersive Virtual Reality: Electro-Cortical Signatures of Monitoring the Errors in the Actions of an Avatar Seen from a First-Person Perspective.

PubMed

Pavone, Enea Francesco; Tieri, Gaetano; Rizza, Giulia; Tidoni, Emmanuele; Grisoni, Luigi; Aglioti, Salvatore Maria

2016-01-13

Brain monitoring of errors in one's own and other's actions is crucial for a variety of processes, ranging from the fine-tuning of motor skill learning to important social functions, such as reading out and anticipating the intentions of others. Here, we combined immersive virtual reality and EEG recording to explore whether embodying the errors of an avatar by seeing it from a first-person perspective may activate the error monitoring system in the brain of an onlooker. We asked healthy participants to observe, from a first- or third-person perspective, an avatar performing a correct or an incorrect reach-to-grasp movement toward one of two virtual mugs placed on a table. At the end of each trial, participants reported verbally how much they embodied the avatar's arm. Ratings were maximal in first-person perspective, indicating that immersive virtual reality can be a powerful tool to induce embodiment of an artificial agent, even through mere visual perception and in the absence of any cross-modal boosting. Observation of erroneous grasping from a first-person perspective enhanced error-related negativity and medial-frontal theta power in the trials where human onlookers embodied the virtual character, hinting at the tight link between early, automatic coding of error detection and sense of embodiment. Error positivity was similar in 1PP and 3PP, suggesting that conscious coding of errors is similar for self and other. Thus, embodiment plays an important role in activating specific components of the action monitoring system when others' errors are coded as if they are one's own errors. Detecting errors in other's actions is crucial for social functions, such as reading out and anticipating the intentions of others. Using immersive virtual reality and EEG recording, we explored how the brain of an onlooker reacted to the errors of an avatar seen from a first-person perspective. We found that mere observation of erroneous actions enhances electrocortical markers of error detection in the trials where human onlookers embodied the virtual character. Thus, the cerebral system for action monitoring is maximally activated when others' errors are coded as if they are one's own errors. The results have important implications for understanding how the brain can control the external world and thus creating new brain-computer interfaces. Copyright © 2016 the authors 0270-6474/16/360268-12$15.00/0.

26 CFR 1.466-2 - Special protective election for certain taxpayers.

Code of Federal Regulations, 2014 CFR

2014-04-01

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26 CFR 1.466-2 - Special protective election for certain taxpayers.

Code of Federal Regulations, 2013 CFR

2013-04-01

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26 CFR 1.466-2 - Special protective election for certain taxpayers.

Code of Federal Regulations, 2011 CFR

2011-04-01

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26 CFR 1.466-2 - Special protective election for certain taxpayers.

Code of Federal Regulations, 2012 CFR

2012-04-01

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75 FR 28077 - Small Business Size Standards: Waiver of the Nonmanufacturer Rule

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-19

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Medical Surveillance Monthly Report (MSMR). Volume 22, Number 12, December 2015

DTIC Science & Technology

2015-12-01

veterans in whom chronic pain may be comorbid with, and exacerbated by, post-traumatic stress disorder (PTSD), depression, or traumatic brain...unspecifi ed 51 780.52 Insomnia , unspecifi ed 46 723.1 Cervicalgia Other chronic pain Chronic pain syndrome No. ICD-9code Description No. ICD-9 code...without myelopathy 982 719.45 Pain in joint involving pelvic region and thigh 205 309.81 Post-traumatic stress disorder 961 722.52 Degeneration of

Decision-making in schizophrenia: A predictive-coding perspective.

PubMed

Sterzer, Philipp; Voss, Martin; Schlagenhauf, Florian; Heinz, Andreas

2018-05-31

Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences. Copyright © 2018 Elsevier Inc. All rights reserved.

Voxel-Based Lesion Symptom Mapping of Coarse Coding and Suppression Deficits in Patients With Right Hemisphere Damage

PubMed Central

Tompkins, Connie A.; Meigh, Kimberly M.; Prat, Chantel S.

2015-01-01

Purpose This study examined right hemisphere (RH) neuroanatomical correlates of lexical–semantic deficits that predict narrative comprehension in adults with RH brain damage. Coarse semantic coding and suppression deficits were related to lesions by voxel-based lesion symptom mapping. Method Participants were 20 adults with RH cerebrovascular accidents. Measures of coarse coding and suppression deficits were computed from lexical decision reaction times at short (175 ms) and long (1000 ms) prime-target intervals. Lesions were drawn on magnetic resonance imaging images and through normalization were registered on an age-matched brain template. Voxel-based lesion symptom mapping analysis was applied to build a general linear model at each voxel. Z score maps were generated for each deficit, and results were interpreted using automated anatomical labeling procedures. Results A deficit in coarse semantic activation was associated with lesions to the RH posterior middle temporal gyrus, dorsolateral prefrontal cortex, and lenticular nuclei. A maintenance deficit for coarsely coded representations involved the RH temporal pole and dorsolateral prefrontal cortex more medially. Ineffective suppression implicated lesions to the RH inferior frontal gyrus and subcortical regions, as hypothesized, along with the rostral temporal pole. Conclusion Beyond their scientific implications, these lesion–deficit correspondences may help inform the clinical diagnosis and enhance decisions about candidacy for deficit-focused treatment to improve narrative comprehension in individuals with RH damage. PMID:26425785

Voxel-Based Lesion Symptom Mapping of Coarse Coding and Suppression Deficits in Patients With Right Hemisphere Damage.

PubMed

Yang, Ying; Tompkins, Connie A; Meigh, Kimberly M; Prat, Chantel S

2015-11-01

This study examined right hemisphere (RH) neuroanatomical correlates of lexical-semantic deficits that predict narrative comprehension in adults with RH brain damage. Coarse semantic coding and suppression deficits were related to lesions by voxel-based lesion symptom mapping. Participants were 20 adults with RH cerebrovascular accidents. Measures of coarse coding and suppression deficits were computed from lexical decision reaction times at short (175 ms) and long (1000 ms) prime-target intervals. Lesions were drawn on magnetic resonance imaging images and through normalization were registered on an age-matched brain template. Voxel-based lesion symptom mapping analysis was applied to build a general linear model at each voxel. Z score maps were generated for each deficit, and results were interpreted using automated anatomical labeling procedures. A deficit in coarse semantic activation was associated with lesions to the RH posterior middle temporal gyrus, dorsolateral prefrontal cortex, and lenticular nuclei. A maintenance deficit for coarsely coded representations involved the RH temporal pole and dorsolateral prefrontal cortex more medially. Ineffective suppression implicated lesions to the RH inferior frontal gyrus and subcortical regions, as hypothesized, along with the rostral temporal pole. Beyond their scientific implications, these lesion-deficit correspondences may help inform the clinical diagnosis and enhance decisions about candidacy for deficit-focused treatment to improve narrative comprehension in individuals with RH damage.

Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes.

PubMed

Kumar, Manoj; Federmeier, Kara D; Fei-Fei, Li; Beck, Diane M

2017-07-15

A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. "sandy beach") describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and frontal cortices. This similarity of neural activity patterns across the two input types, for categories that co-activate local brain regions, provides strong evidence of a common semantic code for pictures and words in the brain. Copyright © 2017 Elsevier Inc. All rights reserved.

Computer codes developed and under development at Lewis

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1992-01-01

The objective of this summary is to provide a brief description of: (1) codes developed or under development at LeRC; and (2) the development status of IPACS with some typical early results. The computer codes that have been developed and/or are under development at LeRC are listed in the accompanying charts. This list includes: (1) the code acronym; (2) select physics descriptors; (3) current enhancements; and (4) present (9/91) code status with respect to its availability and documentation. The computer codes list is grouped by related functions such as: (1) composite mechanics; (2) composite structures; (3) integrated and 3-D analysis; (4) structural tailoring; and (5) probabilistic structural analysis. These codes provide a broad computational simulation infrastructure (technology base-readiness) for assessing the structural integrity/durability/reliability of propulsion systems. These codes serve two other very important functions: they provide an effective means of technology transfer; and they constitute a depository of corporate memory.

Brain Region-Specific Expression of Genes Mapped within Quantitative Trait Loci for Behavioral Responsiveness to Acute Stress in Fisher 344 and Wistar Kyoto Male Rats (Postprint)

DTIC Science & Technology

2018-03-12

Integrative Genomics Viewer (Broad Institute, Cambridge, Massachusetts), we iden- tified the coding sequence variations between the F344 and WKY... abnormalities and disturbances in brain metabolism resem- bling those in depressive states [74]. Ifna2 is also known to induce memory, concentration, and...Variant and Chronic Interpersonal Stress Prospectively Predicts Social Anxiety and Depression Symptoms Over Six Years. Clinical psychological science

The Association between Psychiatric Comorbidities and Outcomes for Inpatients with Traumatic Brain Injury.

PubMed

Brandel, Michael G; Hirshman, Brian R; McCutcheon, Brandon A; Tringale, Kathryn; Carroll, Kate; Richtand, Neil M; Perry, William; Chen, Clark C; Carter, Bob S

2017-03-01

It is well established that traumatic brain injury (TBI) is associated with the development of psychiatric disorders. However, the impact of psychiatric disorders on TBI outcome is less well understood. We examined the outcomes of patients who experienced a traumatic subdural hemorrhage and whether a comorbid psychiatric disorder was associated with a change in outcome. A retrospective observational study was performed in the California Office of Statewide Health Planning and Development (OSHPD) and the Nationwide Inpatient Sample (NIS). Patients hospitalized for acute subdural hemorrhage were identified using International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes. Patients with coexisting psychiatric diagnoses were identified. Outcomes studied included mortality and adverse discharge disposition. In OSPHD, diagnoses of depression (OR = 0.64, p < 0.001), bipolar disorder (OR = 0.45, p < 0.05), and anxiety (OR = 0.37, p < 0.001) were associated with reduced mortality during hospitalization for TBI, with a trend toward psychosis (OR = 0.56, p = 0.08). Schizophrenia had no effect. Diagnoses of psychosis (OR = 2.12, p < 0.001) and schizophrenia (OR = 2.60, p < 0.001) were associated with increased adverse discharge. Depression and bipolar disorder had no effect, and anxiety was associated with reduced adverse discharge (OR = 0.73, p = 0.01). Results were confirmed using the NIS. Analysis revealed novel associations between coexisting psychiatric diagnoses and TBI outcomes, with some subgroups having decreased mortality and increased adverse discharge. Potential mechanisms include pharmacological effects of frequently prescribed psychiatric medications, the pathophysiology of individual psychiatric disorders, or under-coding of psychiatric illness in the most severely injured patients. Because pharmacological mechanisms, if validated, might lead to improved outcome in TBI patients, further studies may provide significant public health benefit.

Integrative analyses of RNA editing, alternative splicing, and expression of young genes in human brain transcriptome by deep RNA sequencing.

PubMed

Wu, Dong-Dong; Ye, Ling-Qun; Li, Yan; Sun, Yan-Bo; Shao, Yi; Chen, Chunyan; Zhu, Zhu; Zhong, Li; Wang, Lu; Irwin, David M; Zhang, Yong E; Zhang, Ya-Ping

2015-08-01

Next-generation RNA sequencing has been successfully used for identification of transcript assembly, evaluation of gene expression levels, and detection of post-transcriptional modifications. Despite these large-scale studies, additional comprehensive RNA-seq data from different subregions of the human brain are required to fully evaluate the evolutionary patterns experienced by the human brain transcriptome. Here, we provide a total of 6.5 billion RNA-seq reads from different subregions of the human brain. A significant correlation was observed between the levels of alternative splicing and RNA editing, which might be explained by a competition between the molecular machineries responsible for the splicing and editing of RNA. Young human protein-coding genes demonstrate biased expression to the neocortical and non-neocortical regions during evolution on the lineage leading to humans. We also found that a significantly greater number of young human protein-coding genes are expressed in the putamen, a tissue that was also observed to have the highest level of RNA-editing activity. The putamen, which previously received little attention, plays an important role in cognitive ability, and our data suggest a potential contribution of the putamen to human evolution. © The Author (2015). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.

Blood oxygen-level dependent functional assessment of cerebrovascular reactivity: Feasibility for intraoperative 3 Tesla MRI.

PubMed

Fierstra, Jorn; Burkhardt, Jan-Karl; van Niftrik, Christiaan Hendrik Bas; Piccirelli, Marco; Pangalu, Athina; Kocian, Roman; Neidert, Marian Christoph; Valavanis, Antonios; Regli, Luca; Bozinov, Oliver

2017-02-01

To assess the feasibility of functional blood oxygen-level dependent (BOLD) MRI to evaluate intraoperative cerebrovascular reactivity (CVR) at 3 Tesla field strength. Ten consecutive neurosurgical subjects scheduled for a clinical intraoperative MRI examination were enrolled in this study. In addition to the clinical protocol a BOLD sequence was implemented with three cycles of 44 s apnea to calculate CVR values on a voxel-by-voxel basis throughout the brain. The CVR range was then color-coded and superimposed on an anatomical volume to create high spatial resolution CVR maps. Ten subjects (mean age 34.8 ± 13.4; 2 females) uneventfully underwent the intraoperative BOLD protocol, with no complications occurring. Whole-brain CVR for all subjects was (mean ± SD) 0.69 ± 0.42, whereas CVR was markedly higher for tumor subjects as compared to vascular subjects, 0.81 ± 0.44 versus 0.33 ± 0.10, respectively. Furthermore, color-coded functional maps could be robustly interpreted for a whole-brain assessment of CVR. We demonstrate that intraoperative BOLD MRI is feasible in creating functional maps to assess cerebrovascular reactivity throughout the brain in subjects undergoing a neurosurgical procedure. Magn Reson Med 77:806-813, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Polarized skylight navigation in insects: model and electrophysiology of e-vector coding by neurons in the central complex.

PubMed

Sakura, Midori; Lambrinos, Dimitrios; Labhart, Thomas

2008-02-01

Many insects exploit skylight polarization for visual compass orientation or course control. As found in crickets, the peripheral visual system (optic lobe) contains three types of polarization-sensitive neurons (POL neurons), which are tuned to different ( approximately 60 degrees diverging) e-vector orientations. Thus each e-vector orientation elicits a specific combination of activities among the POL neurons coding any e-vector orientation by just three neural signals. In this study, we hypothesize that in the presumed orientation center of the brain (central complex) e-vector orientation is population-coded by a set of "compass neurons." Using computer modeling, we present a neural network model transforming the signal triplet provided by the POL neurons to compass neuron activities coding e-vector orientation by a population code. Using intracellular electrophysiology and cell marking, we present evidence that neurons with the response profile of the presumed compass neurons do indeed exist in the insect brain: each of these compass neuron-like (CNL) cells is activated by a specific e-vector orientation only and otherwise remains silent. Morphologically, CNL cells are tangential neurons extending from the lateral accessory lobe to the lower division of the central body. Surpassing the modeled compass neurons in performance, CNL cells are insensitive to the degree of polarization of the stimulus between 99% and at least down to 18% polarization and thus largely disregard variations of skylight polarization due to changing solar elevations or atmospheric conditions. This suggests that the polarization vision system includes a gain control circuit keeping the output activity at a constant level.

Spatial information outflow from the hippocampal circuit: distributed spatial coding and phase precession in the subiculum.

PubMed

Kim, Steve M; Ganguli, Surya; Frank, Loren M

2012-08-22

Hippocampal place cells convey spatial information through a combination of spatially selective firing and theta phase precession. The way in which this information influences regions like the subiculum that receive input from the hippocampus remains unclear. The subiculum receives direct inputs from area CA1 of the hippocampus and sends divergent output projections to many other parts of the brain, so we examined the firing patterns of rat subicular neurons. We found a substantial transformation in the subicular code for space from sparse to dense firing rate representations along a proximal-distal anatomical gradient: neurons in the proximal subiculum are more similar to canonical, sparsely firing hippocampal place cells, whereas neurons in the distal subiculum have higher firing rates and more distributed spatial firing patterns. Using information theory, we found that the more distributed spatial representation in the subiculum carries, on average, more information about spatial location and context than the sparse spatial representation in CA1. Remarkably, despite the disparate firing rate properties of subicular neurons, we found that neurons at all proximal-distal locations exhibit robust theta phase precession, with similar spiking oscillation frequencies as neurons in area CA1. Our findings suggest that the subiculum is specialized to compress sparse hippocampal spatial codes into highly informative distributed codes suitable for efficient communication to other brain regions. Moreover, despite this substantial compression, the subiculum maintains finer scale temporal properties that may allow it to participate in oscillatory phase coding and spike timing-dependent plasticity in coordination with other regions of the hippocampal circuit.

Dissociation between awareness and spatial coding: evidence from unilateral neglect.

PubMed

Treccani, Barbara; Cubelli, Roberto; Sellaro, Roberta; Umiltà, Carlo; Della Sala, Sergio

2012-04-01

Prevalent theories about consciousness propose a causal relation between lack of spatial coding and absence of conscious experience: The failure to code the position of an object is assumed to prevent this object from entering consciousness. This is consistent with influential theories of unilateral neglect following brain damage, according to which spatial coding of neglected stimuli is defective, and this would keep their processing at the nonconscious level. Contrary to this view, we report evidence showing that spatial coding and consciousness can dissociate. A patient with left neglect, who was not aware of contralesional stimuli, was able to process their color and position. However, in contrast to (ipsilesional) consciously perceived stimuli, color and position of neglected stimuli were processed separately. We propose that individual object features, including position, can be processed without attention and consciousness and that conscious perception of an object depends on the binding of its features into an integrated percept.

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

PubMed

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M; Grinberg, Lea T

2017-04-15

Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional organization for musical consonance and tonal pitch hierarchy in human auditory cortex.

PubMed

Bidelman, Gavin M; Grall, Jeremy

2014-11-01

Pitch relationships in music are characterized by their degree of consonance, a hierarchical perceptual quality that distinguishes how pleasant musical chords/intervals sound to the ear. The origins of consonance have been debated since the ancient Greeks. To elucidate the neurobiological mechanisms underlying these musical fundamentals, we recorded neuroelectric brain activity while participants listened passively to various chromatic musical intervals (simultaneously sounding pitches) varying in their perceptual pleasantness (i.e., consonance/dissonance). Dichotic presentation eliminated acoustic and peripheral contributions that often confound explanations of consonance. We found that neural representations for pitch in early human auditory cortex code perceptual features of musical consonance and follow a hierarchical organization according to music-theoretic principles. These neural correlates emerge pre-attentively within ~ 150 ms after the onset of pitch, are segregated topographically in superior temporal gyrus with a rightward hemispheric bias, and closely mirror listeners' behavioral valence preferences for the chromatic tone combinations inherent to music. A perceptual-based organization implies that parallel to the phonetic code for speech, elements of music are mapped within early cerebral structures according to higher-order, perceptual principles and the rules of Western harmony rather than simple acoustic attributes. Copyright © 2014 Elsevier Inc. All rights reserved.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Learning pattern recognition and decision making in the insect brain

NASA Astrophysics Data System (ADS)

Huerta, R.

2013-01-01

We revise the current model of learning pattern recognition in the Mushroom Bodies of the insects using current experimental knowledge about the location of learning, olfactory coding and connectivity. We show that it is possible to have an efficient pattern recognition device based on the architecture of the Mushroom Bodies, sparse code, mutual inhibition and Hebbian leaning only in the connections from the Kenyon cells to the output neurons. We also show that despite the conventional wisdom that believes that artificial neural networks are the bioinspired model of the brain, the Mushroom Bodies actually resemble very closely Support Vector Machines (SVMs). The derived SVM learning rules are situated in the Mushroom Bodies, are nearly identical to standard Hebbian rules, and require inhibition in the output. A very particular prediction of the model is that random elimination of the Kenyon cells in the Mushroom Bodies do not impair the ability to recognize odorants previously learned.

What the success of brain imaging implies about the neural code

PubMed Central

Guest, Olivia; Love, Bradley C

2017-01-01

The success of fMRI places constraints on the nature of the neural code. The fact that researchers can infer similarities between neural representations, despite fMRI’s limitations, implies that certain neural coding schemes are more likely than others. For fMRI to succeed given its low temporal and spatial resolution, the neural code must be smooth at the voxel and functional level such that similar stimuli engender similar internal representations. Through proof and simulation, we determine which coding schemes are plausible given both fMRI’s successes and its limitations in measuring neural activity. Deep neural network approaches, which have been forwarded as computational accounts of the ventral stream, are consistent with the success of fMRI, though functional smoothness breaks down in the later network layers. These results have implications for the nature of the neural code and ventral stream, as well as what can be successfully investigated with fMRI. DOI: http://dx.doi.org/10.7554/eLife.21397.001 PMID:28103186

Simultaneous perception of a spoken and a signed language: The brain basis of ASL-English code-blends

PubMed Central

Weisberg, Jill; McCullough, Stephen; Emmorey, Karen

2018-01-01

Code-blends (simultaneous words and signs) are a unique characteristic of bimodal bilingual communication. Using fMRI, we investigated code-blend comprehension in hearing native ASL-English bilinguals who made a semantic decision (edible?) about signs, audiovisual words, and semantically equivalent code-blends. English and ASL recruited a similar fronto-temporal network with expected modality differences: stronger activation for English in auditory regions of bilateral superior temporal cortex, and stronger activation for ASL in bilateral occipitotemporal visual regions and left parietal cortex. Code-blend comprehension elicited activity in a combination of these regions, and no cognitive control regions were additionally recruited. Furthermore, code-blends elicited reduced activation relative to ASL presented alone in bilateral prefrontal and visual extrastriate cortices, and relative to English alone in auditory association cortex. Consistent with behavioral facilitation observed during semantic decisions, the findings suggest that redundant semantic content induces more efficient neural processing in language and sensory regions during bimodal language integration. PMID:26177161

Phenotypic Graphs and Evolution Unfold the Standard Genetic Code as the Optimal

NASA Astrophysics Data System (ADS)

Zamudio, Gabriel S.; José, Marco V.

2018-03-01

In this work, we explicitly consider the evolution of the Standard Genetic Code (SGC) by assuming two evolutionary stages, to wit, the primeval RNY code and two intermediate codes in between. We used network theory and graph theory to measure the connectivity of each phenotypic graph. The connectivity values are compared to the values of the codes under different randomization scenarios. An error-correcting optimal code is one in which the algebraic connectivity is minimized. We show that the SGC is optimal in regard to its robustness and error-tolerance when compared to all random codes under different assumptions.

Binocular depth processing in the ventral visual pathway

PubMed Central

Vogels, Rufin

2016-01-01

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269602

Stress and visceral pain: from animal models to clinical therapies

PubMed Central

Larauche, Muriel; Mulak, Agata; Taché, Yvette

2011-01-01

Epidemiological studies have implicated stress (psychosocial and physical) as a trigger of first onset or exacerbation of irritable bowel syndrome (IBS) symptoms of which visceral pain is an integrant landmark. A number of experimental acute or chronic exteroceptive or interoceptive stressors induce visceral hyperalgesia in rodents although recent evidence also points to stress-related visceral analgesia as established in the somatic pain field. Underlying mechanisms of stress-related visceral hypersensitivity may involve a combination of sensitization of primary afferents, central sensitization in response to input from the viscera and dysregulation of descending pathways that modulate spinal nociceptive transmission or analgesic response. Biochemical coding of stress involves the recruitment of corticotropin releasing factor (CRF) signaling pathways. Experimental studies established that activation of brain and peripheral CRF receptor subtype 1 plays a primary role in the development of stress-related delayed visceral hyperalgesia while subtype 2 activation induces analgesic response. In line with stress pathways playing a role in IBS, non-pharmacologic and pharmacologic treatment modalities aimed at reducing stress perception using a broad range of evidence-based mind-body interventions and centrally-targeted medications to reduce anxiety impact on brain patterns activated by visceral stimuli and dampen visceral pain. PMID:21575632

Epigenetic stability in the adult mouse cortex under conditions of pharmacologically induced histone acetylation.

PubMed

Benoit, Jamie; Ayoub, Albert; Rakic, Pasko

2016-11-01

Histone acetylation is considered a major epigenetic process that affects brain development and synaptic plasticity, as well as learning and memory. The transcriptional effectors and morphological changes responsible for plasticity as a result of long-term modifications to histone acetylation are not fully understood. To this end, we pharmacologically inhibited histone deacetylation using Trichostatin A in adult (6-month-old) mice and found significant increases in the levels of the acetylated histone marks H3Lys9, H3Lys14 and H4Lys12. High-resolution transcriptome analysis of diverse brain regions uncovered few differences in gene expression between treated and control animals, none of which were plasticity related. Instead, after increased histone acetylation, we detected a large number of novel transcriptionally active regions, which correspond to long non-coding RNAs (lncRNAs). We also surprisingly found no significant changes in dendritic spine plasticity in layers 1 and 2/3 of the visual cortex using long-term in vivo two-photon imaging. Our results indicate that chronic pharmacologically induced histone acetylation can be decoupled from gene expression and instead, may potentially exert a post-transcriptional effect through the differential production of lncRNAs.

Binocular depth processing in the ventral visual pathway.

PubMed

Verhoef, Bram-Ernst; Vogels, Rufin; Janssen, Peter

2016-06-19

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

PubMed

Dai, Shengfa; Wei, Qingguo

2017-01-01

Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.

Disruption of hierarchical predictive coding during sleep

PubMed Central

Strauss, Melanie; Sitt, Jacobo D.; King, Jean-Remi; Elbaz, Maxime; Azizi, Leila; Buiatti, Marco; Naccache, Lionel; van Wassenhove, Virginie; Dehaene, Stanislas

2015-01-01

When presented with an auditory sequence, the brain acts as a predictive-coding device that extracts regularities in the transition probabilities between sounds and detects unexpected deviations from these regularities. Does such prediction require conscious vigilance, or does it continue to unfold automatically in the sleeping brain? The mismatch negativity and P300 components of the auditory event-related potential, reflecting two steps of auditory novelty detection, have been inconsistently observed in the various sleep stages. To clarify whether these steps remain during sleep, we recorded simultaneous electroencephalographic and magnetoencephalographic signals during wakefulness and during sleep in normal subjects listening to a hierarchical auditory paradigm including short-term (local) and long-term (global) regularities. The global response, reflected in the P300, vanished during sleep, in line with the hypothesis that it is a correlate of high-level conscious error detection. The local mismatch response remained across all sleep stages (N1, N2, and REM sleep), but with an incomplete structure; compared with wakefulness, a specific peak reflecting prediction error vanished during sleep. Those results indicate that sleep leaves initial auditory processing and passive sensory response adaptation intact, but specifically disrupts both short-term and long-term auditory predictive coding. PMID:25737555

Upregulation of Haploinsufficient Gene Expression in the Brain by Targeting a Long Non-coding RNA Improves Seizure Phenotype in a Model of Dravet Syndrome.

PubMed

Hsiao, J; Yuan, T Y; Tsai, M S; Lu, C Y; Lin, Y C; Lee, M L; Lin, S W; Chang, F C; Liu Pimentel, H; Olive, C; Coito, C; Shen, G; Young, M; Thorne, T; Lawrence, M; Magistri, M; Faghihi, M A; Khorkova, O; Wahlestedt, C

2016-07-01

Dravet syndrome is a devastating genetic brain disorder caused by heterozygous loss-of-function mutation in the voltage-gated sodium channel gene SCN1A. There are currently no treatments, but the upregulation of SCN1A healthy allele represents an appealing therapeutic strategy. In this study we identified a novel, evolutionary conserved mechanism controlling the expression of SCN1A that is mediated by an antisense non-coding RNA (SCN1ANAT). Using oligonucleotide-based compounds (AntagoNATs) targeting SCN1ANAT we were able to induce specific upregulation of SCN1A both in vitro and in vivo, in the brain of Dravet knock-in mouse model and a non-human primate. AntagoNAT-mediated upregulation of Scn1a in postnatal Dravet mice led to significant improvements in seizure phenotype and excitability of hippocampal interneurons. These results further elucidate the pathophysiology of Dravet syndrome and outline a possible new approach for the treatment of this and other genetic disorders with similar etiology. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease

NASA Astrophysics Data System (ADS)

2014-01-01

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD). These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case-control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer's disease in seven independent case-control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer's disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer's disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer's disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease.

PubMed

Cruchaga, Carlos; Karch, Celeste M; Jin, Sheng Chih; Benitez, Bruno A; Cai, Yefei; Guerreiro, Rita; Harari, Oscar; Norton, Joanne; Budde, John; Bertelsen, Sarah; Jeng, Amanda T; Cooper, Breanna; Skorupa, Tara; Carrell, David; Levitch, Denise; Hsu, Simon; Choi, Jiyoon; Ryten, Mina; Sassi, Celeste; Bras, Jose; Gibbs, Raphael J; Hernandez, Dena G; Lupton, Michelle K; Powell, John; Forabosco, Paola; Ridge, Perry G; Corcoran, Christopher D; Tschanz, JoAnn T; Norton, Maria C; Munger, Ronald G; Schmutz, Cameron; Leary, Maegan; Demirci, F Yesim; Bamne, Mikhil N; Wang, Xingbin; Lopez, Oscar L; Ganguli, Mary; Medway, Christopher; Turton, James; Lord, Jenny; Braae, Anne; Barber, Imelda; Brown, Kristelle; Pastor, Pau; Lorenzo-Betancor, Oswaldo; Brkanac, Zoran; Scott, Erick; Topol, Eric; Morgan, Kevin; Rogaeva, Ekaterina; Singleton, Andy; Hardy, John; Kamboh, M Ilyas; George-Hyslop, Peter St; Cairns, Nigel; Morris, John C; Kauwe, John S K; Goate, Alison M

2014-01-23

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD). These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case-control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer's disease in seven independent case-control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer's disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer's disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer's disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

Neural Mechanisms Underlying Risk and Ambiguity Attitudes.

PubMed

Blankenstein, Neeltje E; Peper, Jiska S; Crone, Eveline A; van Duijvenvoorde, Anna C K

2017-11-01

Individual differences in attitudes to risk (a taste for risk, known probabilities) and ambiguity (a tolerance for uncertainty, unknown probabilities) differentially influence risky decision-making. However, it is not well understood whether risk and ambiguity are coded differently within individuals. Here, we tested whether individual differences in risk and ambiguity attitudes were reflected in distinct neural correlates during choice and outcome processing of risky and ambiguous gambles. To these ends, we developed a neuroimaging task in which participants ( n = 50) chose between a sure gain and a gamble, which was either risky or ambiguous, and presented decision outcomes (gains, no gains). From a separate task in which the amount, probability, and ambiguity level were varied, we estimated individuals' risk and ambiguity attitudes. Although there was pronounced neural overlap between risky and ambiguous gambling in a network typically related to decision-making under uncertainty, relatively more risk-seeking attitudes were associated with increased activation in valuation regions of the brain (medial and lateral OFC), whereas relatively more ambiguity-seeking attitudes were related to temporal cortex activation. In addition, although striatum activation was observed during reward processing irrespective of a prior risky or ambiguous gamble, reward processing after an ambiguous gamble resulted in enhanced dorsomedial PFC activation, possibly functioning as a general signal of uncertainty coding. These findings suggest that different neural mechanisms reflect individual differences in risk and ambiguity attitudes and that risk and ambiguity may impact overt risk-taking behavior in different ways.

Neural Substrates of Visual Spatial Coding and Visual Feedback Control for Hand Movements in Allocentric and Target-Directed Tasks

PubMed Central

Thaler, Lore; Goodale, Melvyn A.

2011-01-01

Neuropsychological evidence suggests that different brain areas may be involved in movements that are directed at visual targets (e.g., pointing or reaching), and movements that are based on allocentric visual information (e.g., drawing or copying). Here we used fMRI to investigate the neural correlates of these two types of movements in healthy volunteers. Subjects (n = 14) performed right hand movements in either a target-directed task (moving a cursor to a target dot) or an allocentric task (moving a cursor to reproduce the distance and direction between two distal target dots) with or without visual feedback about their hand movement. Movements were monitored with an MR compatible touch panel. A whole brain analysis revealed that movements in allocentric conditions led to an increase in activity in the fundus of the left intra-parietal sulcus (IPS), in posterior IPS, in bilateral dorsal premotor cortex (PMd), and in the lateral occipital complex (LOC). Visual feedback in both target-directed and allocentric conditions led to an increase in activity in area MT+, superior parietal–occipital cortex (SPOC), and posterior IPS (all bilateral). In addition, we found that visual feedback affected brain activity differently in target-directed as compared to allocentric conditions, particularly in the pre-supplementary motor area, PMd, IPS, and parieto-occipital cortex. Our results, in combination with previous findings, suggest that the LOC is essential for allocentric visual coding and that SPOC is involved in visual feedback control. The differences in brain activity between target-directed and allocentric visual feedback conditions may be related to behavioral differences in visual feedback control. Our results advance the understanding of the visual coordinate frame used by the LOC. In addition, because of the nature of the allocentric task, our results have relevance for the understanding of neural substrates of magnitude estimation and vector coding of movements. PMID:21941474

Visualizing the pressure and time burden of intracranial hypertension in adult and paediatric traumatic brain injury.

PubMed

Güiza, Fabian; Depreitere, Bart; Piper, Ian; Citerio, Giuseppe; Chambers, Iain; Jones, Patricia A; Lo, Tsz-Yan Milly; Enblad, Per; Nillson, Pelle; Feyen, Bart; Jorens, Philippe; Maas, Andrew; Schuhmann, Martin U; Donald, Rob; Moss, Laura; Van den Berghe, Greet; Meyfroidt, Geert

2015-06-01

To assess the impact of the duration and intensity of episodes of increased intracranial pressure on 6-month neurological outcome in adult and paediatric traumatic brain injury. Analysis of prospectively collected minute-by-minute intracranial pressure and mean arterial blood pressure data of 261 adult and 99 paediatric traumatic brain injury patients from multiple European centres. The relationship of episodes of elevated intracranial pressure (defined as a pressure above a certain threshold during a certain time) with 6-month Glasgow Outcome Scale was visualized in a colour-coded plot. The colour-coded plot illustrates the intuitive concept that episodes of higher intracranial pressure can only be tolerated for shorter durations: the curve that delineates the duration and intensity of those intracranial pressure episodes associated with worse outcome is an approximately exponential decay curve. In children, the curve resembles that of adults, but the delineation between episodes associated with worse outcome occurs at lower intracranial pressure thresholds. Intracranial pressures above 20 mmHg lasting longer than 37 min in adults, and longer than 8 min in children, are associated with worse outcomes. In a multivariate model, together with known baseline risk factors for outcome in severe traumatic brain injury, the cumulative intracranial pressure-time burden is independently associated with mortality. When cerebrovascular autoregulation, assessed with the low-frequency autoregulation index, is impaired, the ability to tolerate elevated intracranial pressures is reduced. When the cerebral perfusion pressure is below 50 mmHg, all intracranial pressure insults, regardless of duration, are associated with worse outcome. The intracranial pressure-time burden associated with worse outcome is visualised in a colour-coded plot. In children, secondary injury occurs at lower intracranial pressure thresholds as compared to adults. Impaired cerebrovascular autoregulation reduces the ability to tolerate intracranial pressure insults. Thus, 50 mmHg might be the lower acceptable threshold for cerebral perfusion pressure.

Deficient brain RNA polymerase and altered nucleolar structure persists until day 8 after perinatal asphyxia of the rat.

PubMed

Kastner, Philomena; Mosgoeller, Wilhelm; Fang-Kircher, Susanne; Kitzmueller, Erwin; Kirchner, Liselotte; Hoeger, Harald; Seither, Peter; Lubec, Gert; Lubec, Barbara

2003-01-01

RNA polymerases (POL) are integral constituents of the protein synthesis machinery, with POL I and POL III coding for ribosomal RNA and POL II coding for protein. POL I is located in the nucleolus and transcribes class I genes, those that code for large ribosomal RNA. It has been reported that the POL system is seriously affected in perinatal asphyxia (PA) immediately after birth. Because POL I is necessary for protein synthesis and brain protein synthesis was shown to be deranged after hypoxic-ischemic conditions, we aimed to study whether POL derangement persists in a simple, well-documented animal model of graded global PA at the activity, mRNA, protein, and morphologic level until 8 d after the asphyctic insult. Nuclear POL I activity was determined according to a radiochemical method; mRNA steady state and protein levels of RPA4O-an essential subunit of POL I and III-were evaluated by blotting methods; and the POL I subunit polymerase activating factor-53 was evaluated using immunohistochemistry. Silver staining and transmission electron microscopy were used to examine the nucleolus. At the eighth day after PA, nuclear POL I decreased with the length of the asphyctic period, whereas mRNA and protein levels for RPA4O were unchanged. The subunit polymerase activating factor-53, however, was unambiguously reduced in several brain regions. Dramatic changes of nucleolar morphology were observed, the main finding being nucleolar disintegration at the electron microscopy level. We suggest that severe acidosis and/or deficient protein kinase C in the brain during the asphyctic period may be responsible for disintegration of the nucleolus as well as for decreased POL activity persisting until the eighth day after PA. The biologic effect may be that PA causes impaired RNA and protein synthesis, which has been already observed in hypoxic-ischemic states.

MicroRNAs in brain metastases: potential role as diagnostics and therapeutics.

PubMed

Alsidawi, Samer; Malek, Ehsan; Driscoll, James J

2014-06-11

Brain metastases remain a daunting adversary that negatively impact patient survival. Metastatic brain tumors affect up to 45% of all cancer patients with systemic cancer and account for ~20% of all cancer-related deaths. A complex network of non-coding RNA molecules, microRNAs (miRNAs), regulate tumor metastasis. The brain micro-environment modulates metastatic tumor growth; however, defining the precise genetic events that promote metastasis in the brain niche represents an important, unresolved problem. Understanding these events will reveal disease-based targets and offer effective strategies to treat brain metastases. Effective therapeutic strategies based upon the biology of brain metastases represent an urgent, unmet need with immediate potential for clinical impact. Studies have demonstrated the ability of miRNAs to distinguish normal from cancerous cells, primary from secondary brain tumors, and correctly categorize metastatic brain tumor tissue of origin based solely on miRNA profiles. Interestingly, manipulation of miRNAs has proven effective in cancer treatment. With the promise of reduced toxicity, increased efficacy and individually directed personalized anti-cancer therapy, using miRNA in the treatment of metastatic brain tumors may prove very useful and improve patient outcome. In this review, we focus on the potential of miRNAs as diagnostic and therapeutic targets for the treatment of metastatic brain lesions.

Two Δ6-desaturase-like genes in common carp (Cyprinus carpio var. Jian): structure characterization, mRNA expression, temperature and nutritional regulation.

PubMed

Ren, Hong-tao; Zhang, Guang-qin; Li, Jian-lin; Tang, Yong-kai; Li, Hong-xia; Yu, Ju-hua; Xu, Pao

2013-08-01

Δ6-Desaturase is the rate-limiting enzyme involved in highly unsaturated fatty acid (HUFA) biosynthesis. There is very little information on the evolution and functional characterization of Δ6Fad-a and Δ6Fad-b in common carp (Cyprinus carpio var. Jian). In the present study, the genomic sequences and structures of two putative Δ6-desaturase-like genes in common carp genome were obtained. We investigated the mRNA expression patterns of Δ6Fad-a and Δ6Fad-b in tissue, hatching carp embryos, larvae by temperature shock and juveniles under nutritional regulation. Our results showed that the two Δ6Fad genes had identical coding exon structures, being comprised of 12 coding exons, and with introns of distinct size and sequence composition. They were not allelic variants of a single gene. Both Δ6Fad genes were highly expressed in liver, intestine (pyloric caeca) and brain. The Δ6Fad-a and Δ6Fad-b mRNAs showed an increase in expression from newly hatched to 25 days after hatching. The expression levels of Δ6Fad-a were obviously regulated by temperature, whereas Δ6Fad-b was not affected by temperature. The regulation of Δ6Fad-a and Δ6Fad-b in response to dietary fatty acid composition was determined in liver, brain and intestine (pyloric caeca) of common carp fed with diets: diet1with fish oil (FO) rich in n-3 HUFA, diet2 with corn oil (CO, 18:2n-6) and diet3 with linseed oil (LO, 18:3n-3). The differential expression of Δ6Fad-a and Δ6Fad-b genes in liver, brain and intestine in common carps was fed with different oil sources, respectively. Further work is in progress to determine the mechanism of differential expression of the Δ6Fad-a and Δ6Fad-b genes in different tissues and the roles of transcription factors in regulating HUFA synthesis. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-12-15

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

Visual Dysfunction Following Blast-Related Traumatic Brain Injury from the Battlefield

DTIC Science & Technology

2011-01-01

and visual disorders is varied, depending on the diagnostic criteria, condition and patient popu- lation, but has primarily been studied in civilian... diagnostic codes for ‘disorders of the eye and adnexa’ (360.0– 379.9) obtained from electronic outpatient medical records (Standard Ambulatory Data Record) and...disorder diagnostic category by TBI status. ICD-9-CM code and categorya TBI (n¼ 837) Other injury (n¼1417) 360 Disorders of the globe 0 1 ɘ.1% 361

Visual Dysfunction Following Blast-Related Traumatic Brain Injury from the Battlefield

DTIC Science & Technology

2010-10-27

sequelae follow- ing a TBI [12, 13]. The occurrence of TBI-related ocular and visual disorders is varied, depending on the diagnostic criteria...measure, ocular/visual disor- der, was indicated by the ICD-9-CM diagnostic codes for ‘disorders of the eye and adnexa’ (360.0– 379.9) obtained from...II. Number and percentage of US service members in each ocular/visual disorder diagnostic category by TBI status. ICD-9-CM code and categorya TBI (n

Predictive coding accelerates word recognition and learning in the early stages of language development.

PubMed

Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

2017-11-01

The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard syllables are faster and more robust when the preceding word context predicts the ending of a familiar word. For unfamiliar, novel word forms, however, word-expectancy violation generates a prediction error response, the strength of which significantly correlates with children's vocabulary scores at 12 months. These results suggest that predictive coding may accelerate word recognition and support early learning of novel words, including not only the learning of heard word forms but also their mapping to meanings. Prediction error may mediate learning via attention, since infants' attention allocation to the entire learning situation in natural environments could account for the link between prediction error and the understanding of word meanings. On the whole, the present results on predictive coding support the view that principles of brain function reported across domains in humans and non-human animals apply to language and its development in the infant brain. A video abstract of this article can be viewed at: http://hy.fi/unitube/video/e1cbb495-41d8-462e-8660-0864a1abd02c. [Correction added on 27 January 2017, after first online publication: The video abstract link was added.]. © 2016 John Wiley & Sons Ltd.

Learning to Estimate Dynamical State with Probabilistic Population Codes.

PubMed

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

2015-11-01

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

Learning to Estimate Dynamical State with Probabilistic Population Codes

PubMed Central

Sabes, Philip N.

2015-01-01

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

The 'selfish brain' is regulated by aquaporins and autophagy under nutrient deprivation.

PubMed

Ye, Qiao; Wu, Yonghong; Gao, Yan; Li, Zhihui; Li, Weiguang; Zhang, Chenggang

2016-05-01

The brain maintains its mass and physiological functional capacity compared with other organs under harsh conditions such as starvation, a mechanism termed the 'selfish brain' theory. To further investigate this phenomenon, mice were examined following water and/or food deprivation. Although the body weights of the mice, the weight of the organs except the brain and blood glucose levels were significantly reduced in the absence of water and/or food, the brain weight maintained its original state. Furthermore, no significant differences in the water content of the brain or its energy balance were observed when the mice were subjected to water and/or food deprivation. To further investigate the mechanism underlying the brain maintenance of water and substance homeostasis, the expression levels of aquaporins (AQPs) and autophagy‑specific protein long‑chain protein 3 (LC3) were examined. During the process of water and food deprivation, no significant differences in the transcriptional levels of AQPs were observed. However, autophagy activity levels were initially stimulated, then suppressed in a time‑dependent manner. LC3 and AQPs have important roles for the survival of the brain under conditions of food and water deprivation, which provided further understanding of the mechanism underlying the 'selfish brain' phenomenon. Although not involved in the energy regulation of the 'selfish brain', AQPs were observed to have important roles in water and food deprivation, specifically with regards to the control of water content. Additionally, the brain exhibits an 'unselfish strategy' using autophagy during water and/or food deprivation. The present study furthered current understanding of the 'selfish brain' theory, and identified additional regulating target genes of AQPs and autophagy, with the aim of providing a basis for the prevention of nutrient shortage in humans and animals.

The 'selfish brain' is regulated by aquaporins and autophagy under nutrient deprivation

PubMed Central

YE, QIAO; WU, YONGHONG; GAO, YAN; LI, ZHIHUI; LI, WEIGUANG; ZHANG, CHENGGANG

2016-01-01

The brain maintains its mass and physiological functional capacity compared with other organs under harsh conditions such as starvation, a mechanism termed the 'selfish brain' theory. To further investigate this phenomenon, mice were examined following water and/or food deprivation. Although the body weights of the mice, the weight of the organs except the brain and blood glucose levels were significantly reduced in the absence of water and/or food, the brain weight maintained its original state. Furthermore, no significant differences in the water content of the brain or its energy balance were observed when the mice were subjected to water and/or food deprivation. To further investigate the mechanism underlying the brain maintenance of water and substance homeostasis, the expression levels of aquaporins (AQPs) and autophagy-specific protein long-chain protein 3 (LC3) were examined. During the process of water and food deprivation, no significant differences in the transcriptional levels of AQPs were observed. However, autophagy activity levels were initially stimulated, then suppressed in a time-dependent manner. LC3 and AQPs have important roles for the survival of the brain under conditions of food and water deprivation, which provided further understanding of the mechanism underlying the 'selfish brain' phenomenon. Although not involved in the energy regulation of the 'selfish brain', AQPs were observed to have important roles in water and food deprivation, specifically with regards to the control of water content. Additionally, the brain exhibits an 'unselfish strategy' using autophagy during water and/or food deprivation. The present study furthered current understanding of the 'selfish brain' theory, and identified additional regulating target genes of AQPs and autophagy, with the aim of providing a basis for the prevention of nutrient shortage in humans and animals. PMID:26986971

Exploring Symmetry to Assist Alzheimer's Disease Diagnosis

NASA Astrophysics Data System (ADS)

Illán, I. A.; Górriz, J. M.; Ramírez, J.; Salas-Gonzalez, D.; López, M.; Padilla, P.; Chaves, R.; Segovia, F.; Puntonet, C. G.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder first affecting memory functions and then gradually affecting all cognitive functions with behavioral impairments and eventually causing death. Functional brain imaging as Single-Photon Emission Computed Tomography (SPECT) is commonly used to guide the clinician's diagnosis. The essential left-right symmetry of human brains is shown to play a key role in coding and recognition. In the present work we explore the implications of this symmetry in AD diagnosis, showing that recognition may be enhanced when considering this latent symmetry.

Neural representation of objects in space: a dual coding account.

PubMed Central

Humphreys, G W

1998-01-01

I present evidence on the nature of object coding in the brain and discuss the implications of this coding for models of visual selective attention. Neuropsychological studies of task-based constraints on: (i) visual neglect; and (ii) reading and counting, reveal the existence of parallel forms of spatial representation for objects: within-object representations, where elements are coded as parts of objects, and between-object representations, where elements are coded as independent objects. Aside from these spatial codes for objects, however, the coding of visual space is limited. We are extremely poor at remembering small spatial displacements across eye movements, indicating (at best) impoverished coding of spatial position per se. Also, effects of element separation on spatial extinction can be eliminated by filling the space with an occluding object, indicating that spatial effects on visual selection are moderated by object coding. Overall, there are separate limits on visual processing reflecting: (i) the competition to code parts within objects; (ii) the small number of independent objects that can be coded in parallel; and (iii) task-based selection of whether within- or between-object codes determine behaviour. Between-object coding may be linked to the dorsal visual system while parallel coding of parts within objects takes place in the ventral system, although there may additionally be some dorsal involvement either when attention must be shifted within objects or when explicit spatial coding of parts is necessary for object identification. PMID:9770227

42 CFR Appendix A to Part 81 - Glossary of ICD-9 Codes and Their Cancer Descriptions 1

Code of Federal Regulations, 2013 CFR

2013-10-01

... Malignant neoplasm of brain. 192 Malignant neoplasm of other and unspecified parts of nervous system. 193... and ill-defined sites within the respiratory system and intrathoracic organs. 170 Malignant neoplasm...

42 CFR Appendix A to Part 81 - Glossary of ICD-9 Codes and Their Cancer Descriptions 1

Code of Federal Regulations, 2014 CFR

2014-10-01

... Malignant neoplasm of brain. 192 Malignant neoplasm of other and unspecified parts of nervous system. 193... and ill-defined sites within the respiratory system and intrathoracic organs. 170 Malignant neoplasm...

42 CFR Appendix A to Part 81 - Glossary of ICD-9 Codes and Their Cancer Descriptions 1

Code of Federal Regulations, 2012 CFR

2012-10-01

... Malignant neoplasm of brain. 192 Malignant neoplasm of other and unspecified parts of nervous system. 193... and ill-defined sites within the respiratory system and intrathoracic organs. 170 Malignant neoplasm...

42 CFR Appendix A to Part 81 - Glossary of ICD-9 Codes and Their Cancer Descriptions 1

Code of Federal Regulations, 2011 CFR

2011-10-01

... Malignant neoplasm of brain. 192 Malignant neoplasm of other and unspecified parts of nervous system. 193... and ill-defined sites within the respiratory system and intrathoracic organs. 170 Malignant neoplasm...

EEGgui: a program used to detect electroencephalogram anomalies after traumatic brain injury.

PubMed

Sick, Justin; Bray, Eric; Bregy, Amade; Dietrich, W Dalton; Bramlett, Helen M; Sick, Thomas

2013-05-21

Identifying and quantifying pathological changes in brain electrical activity is important for investigations of brain injury and neurological disease. An example is the development of epilepsy, a secondary consequence of traumatic brain injury. While certain epileptiform events can be identified visually from electroencephalographic (EEG) or electrocorticographic (ECoG) records, quantification of these pathological events has proved to be more difficult. In this study we developed MATLAB-based software that would assist detection of pathological brain electrical activity following traumatic brain injury (TBI) and present our MATLAB code used for the analysis of the ECoG. Software was developed using MATLAB(™) and features of the open access EEGLAB. EEGgui is a graphical user interface in the MATLAB programming platform that allows scientists who are not proficient in computer programming to perform a number of elaborate analyses on ECoG signals. The different analyses include Power Spectral Density (PSD), Short Time Fourier analysis and Spectral Entropy (SE). ECoG records used for demonstration of this software were derived from rats that had undergone traumatic brain injury one year earlier. The software provided in this report provides a graphical user interface for displaying ECoG activity and calculating normalized power density using fast fourier transform of the major brain wave frequencies (Delta, Theta, Alpha, Beta1, Beta2 and Gamma). The software further detects events in which power density for these frequency bands exceeds normal ECoG by more than 4 standard deviations. We found that epileptic events could be identified and distinguished from a variety of ECoG phenomena associated with normal changes in behavior. We further found that analysis of spectral entropy was less effective in distinguishing epileptic from normal changes in ECoG activity. The software presented here was a successful modification of EEGLAB in the Matlab environment that allows detection of epileptiform ECoG signals in animals after TBI. The code allows import of large EEG or ECoG data records as standard text files and uses fast fourier transform as a basis for detection of abnormal events. The software can also be used to monitor injury-induced changes in spectral entropy if required. We hope that the software will be useful for other investigators in the field of traumatic brain injury and will stimulate future advances of quantitative analysis of brain electrical activity after neurological injury or disease.

Simulation of blast-induced early-time intracranial wave physics leading to traumatic brain injury.

PubMed

Taylor, Paul A; Ford, Corey C

2009-06-01

The objective of this modeling and simulation study was to establish the role of stress wave interactions in the genesis of traumatic brain injury (TBI) from exposure to explosive blast. A high resolution (1 mm3 voxels) five material model of the human head was created by segmentation of color cryosections from the Visible Human Female data set. Tissue material properties were assigned from literature values. The model was inserted into the shock physics wave code, CTH, and subjected to a simulated blast wave of 1.3 MPa (13 bars) peak pressure from anterior, posterior, and lateral directions. Three-dimensional plots of maximum pressure, volumetric tension, and deviatoric (shear) stress demonstrated significant differences related to the incident blast geometry. In particular, the calculations revealed focal brain regions of elevated pressure and deviatoric stress within the first 2 ms of blast exposure. Calculated maximum levels of 15 KPa deviatoric, 3.3 MPa pressure, and 0.8 MPa volumetric tension were observed before the onset of significant head accelerations. Over a 2 ms time course, the head model moved only 1 mm in response to the blast loading. Doubling the blast strength changed the resulting intracranial stress magnitudes but not their distribution. We conclude that stress localization, due to early-time wave interactions, may contribute to the development of multifocal axonal injury underlying TBI. We propose that a contribution to traumatic brain injury from blast exposure, and most likely blunt impact, can occur on a time scale shorter than previous model predictions and before the onset of linear or rotational accelerations traditionally associated with the development of TBI.

Encoding and Decoding Models in Cognitive Electrophysiology

PubMed Central

Holdgraf, Christopher R.; Rieger, Jochem W.; Micheli, Cristiano; Martin, Stephanie; Knight, Robert T.; Theunissen, Frederic E.

2017-01-01

Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model-based methods for asking neuroscience questions, allowing scientists to investigate multiple hypotheses with a single dataset, to use complex, time-varying stimuli, and to study the human brain under more naturalistic conditions. These tools come in the form of “Encoding” models, in which stimulus features are used to model brain activity, and “Decoding” models, in which neural features are used to generated a stimulus output. Here we review the current state of encoding and decoding models in cognitive electrophysiology and provide a practical guide toward conducting experiments and analyses in this emerging field. Our examples focus on using linear models in the study of human language and audition. We show how to calculate auditory receptive fields from natural sounds as well as how to decode neural recordings to predict speech. The paper aims to be a useful tutorial to these approaches, and a practical introduction to using machine learning and applied statistics to build models of neural activity. The data analytic approaches we discuss may also be applied to other sensory modalities, motor systems, and cognitive systems, and we cover some examples in these areas. In addition, a collection of Jupyter notebooks is publicly available as a complement to the material covered in this paper, providing code examples and tutorials for predictive modeling in python. The aim is to provide a practical understanding of predictive modeling of human brain data and to propose best-practices in conducting these analyses. PMID:29018336

Modeling and simulation of blast-induced, early-time intracranial wave physics leading to traumatic brain injury.

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

Ford, Corey C.; Taylor, Paul Allen

The objective of this modeling and simulation study was to establish the role of stress wave interactions in the genesis of traumatic brain injury (TBI) from exposure to explosive blast. A high resolution (1 mm{sup 3} voxels), 5 material model of the human head was created by segmentation of color cryosections from the Visible Human Female dataset. Tissue material properties were assigned from literature values. The model was inserted into the shock physics wave code, CTH, and subjected to a simulated blast wave of 1.3 MPa (13 bars) peak pressure from anterior, posterior and lateral directions. Three dimensional plots ofmore » maximum pressure, volumetric tension, and deviatoric (shear) stress demonstrated significant differences related to the incident blast geometry. In particular, the calculations revealed focal brain regions of elevated pressure and deviatoric (shear) stress within the first 2 milliseconds of blast exposure. Calculated maximum levels of 15 KPa deviatoric, 3.3 MPa pressure, and 0.8 MPa volumetric tension were observed before the onset of significant head accelerations. Over a 2 msec time course, the head model moved only 1 mm in response to the blast loading. Doubling the blast strength changed the resulting intracranial stress magnitudes but not their distribution. We conclude that stress localization, due to early time wave interactions, may contribute to the development of multifocal axonal injury underlying TBI. We propose that a contribution to traumatic brain injury from blast exposure, and most likely blunt impact, can occur on a time scale shorter than previous model predictions and before the onset of linear or rotational accelerations traditionally associated with the development of TBI.« less

Structure and variation of three canine genes involved in serotonin binding and transport: the serotonin receptor 1A gene (htr1A), serotonin receptor 2A gene (htr2A), and serotonin transporter gene (slc6A4).

PubMed

van den Berg, L; Kwant, L; Hestand, M S; van Oost, B A; Leegwater, P A J

2005-01-01

Aggressive behavior is the most frequently encountered behavioral problem in dogs. Abnormalities in brain serotonin metabolism have been described in aggressive dogs. We studied canine serotonergic genes to investigate genetic factors underlying canine aggression. Here, we describe the characterization of three genes of the canine serotonergic system: the serotonin receptor 1A and 2A gene (htr1A and htr2A) and the serotonin transporter gene (slc6A4). We isolated canine bacterial artificial chromosome clones containing these genes and designed oligonucleotides for genomic sequencing of coding regions and intron-exon boundaries. Golden retrievers were analyzed for DNA sequence variations. We found two nonsynonymous single nucleotide polymorphisms (SNPs) in the coding sequence of htr1A; one SNP close to a splice site in htr2A; and two SNPs in slc6A4, one in the coding sequence and one close to a splice site. In addition, we identified a polymorphic microsatellite marker for each gene. Htr1A is a strong candidate for involvement in the domestication of the dog. We genotyped the htr1A SNPs in 41 dogs of seven breeds with diverse behavioral characteristics. At least three SNP haplotypes were found. Our results do not support involvement of the gene in domestication.

Retronasal odor representations in the dorsal olfactory bulb of rats

PubMed Central

Gautam, Shree Hari; Verhagen, Justus V.

2012-01-01

Animals perceive their olfactory environment not only from odors originating in the external world (orthonasal route) but also from odors released in the oral cavity while eating food (retronasal route). Retronasal olfaction is crucial for the perception of food flavor in humans. However, little is known about the retronasal stimulus coding in the brain. The most basic question is if and how route affects the odor representations at the level of the olfactory bulb (OB), where odor quality codes originate. We used optical calcium imaging of presynaptic dorsal OB responses to odorants in anesthetized rats to ask whether the rat OB could be activated retronasally, and how these responses compare to orthonasal responses under similar conditions. We further investigated the effects of specific odorant properties on orthoversus retronasal response patterns. We found that at a physiologically relevant flow rate retronasal odorants can effectively reach the olfactory receptor neurons, eliciting glomerular response patterns that grossly overlap with those of orthonasal responses, but differ from the orthonasal patterns in the response amplitude and temporal dynamics. Interestingly, such differences correlated well with specific odorant properties. Less volatile odorants yielded relatively smaller responses retronasally, but volatility did not affect relative temporal profiles. More polar odorants responded with relatively longer onset latency and time to peak retronasally, but polarity did not affect relative response magnitudes. These data provide insight into the early stages of retronasal stimulus coding and establish relationships between ortho- and retronasal odor representations in the rat OB. PMID:22674270

Unaware Processing of Tools in the Neural System for Object-Directed Action Representation.

PubMed

Tettamanti, Marco; Conca, Francesca; Falini, Andrea; Perani, Daniela

2017-11-01

The hypothesis that the brain constitutively encodes observed manipulable objects for the actions they afford is still debated. Yet, crucial evidence demonstrating that, even in the absence of perceptual awareness, the mere visual appearance of a manipulable object triggers a visuomotor coding in the action representation system including the premotor cortex, has hitherto not been provided. In this fMRI study, we instantiated reliable unaware visual perception conditions by means of continuous flash suppression, and we tested in 24 healthy human participants (13 females) whether the visuomotor object-directed action representation system that includes left-hemispheric premotor, parietal, and posterior temporal cortices is activated even under subliminal perceptual conditions. We found consistent activation in the target visuomotor cortices, both with and without perceptual awareness, specifically for pictures of manipulable versus non-manipulable objects. By means of a multivariate searchlight analysis, we also found that the brain activation patterns in this visuomotor network enabled the decoding of manipulable versus non-manipulable object picture processing, both with and without awareness. These findings demonstrate the intimate neural coupling between visual perception and motor representation that underlies manipulable object processing: manipulable object stimuli specifically engage the visuomotor object-directed action representation system, in a constitutive manner that is independent from perceptual awareness. This perceptuo-motor coupling endows the brain with an efficient mechanism for monitoring and planning reactions to external stimuli in the absence of awareness. SIGNIFICANCE STATEMENT Our brain constantly encodes the visual information that hits the retina, leading to a stimulus-specific activation of sensory and semantic representations, even for objects that we do not consciously perceive. Do these unconscious representations encompass the motor programming of actions that could be accomplished congruently with the objects' functions? In this fMRI study, we instantiated unaware visual perception conditions, by dynamically suppressing the visibility of manipulable object pictures with mondrian masks. Despite escaping conscious perception, manipulable objects activated an object-directed action representation system that includes left-hemispheric premotor, parietal, and posterior temporal cortices. This demonstrates that visuomotor encoding occurs independently of conscious object perception. Copyright © 2017 the authors 0270-6474/17/3710712-13$15.00/0.

The HYPE Open Source Community

NASA Astrophysics Data System (ADS)

Strömbäck, L.; Pers, C.; Isberg, K.; Nyström, K.; Arheimer, B.

2013-12-01

The Hydrological Predictions for the Environment (HYPE) model is a dynamic, semi-distributed, process-based, integrated catchment model. It uses well-known hydrological and nutrient transport concepts and can be applied for both small and large scale assessments of water resources and status. In the model, the landscape is divided into classes according to soil type, vegetation and altitude. The soil representation is stratified and can be divided in up to three layers. Water and substances are routed through the same flow paths and storages (snow, soil, groundwater, streams, rivers, lakes) considering turn-over and transformation on the way towards the sea. HYPE has been successfully used in many hydrological applications at SMHI. For Europe, we currently have three different models; The S-HYPE model for Sweden; The BALT-HYPE model for the Baltic Sea; and the E-HYPE model for the whole Europe. These models simulate hydrological conditions and nutrients for their respective areas and are used for characterization, forecasts, and scenario analyses. Model data can be downloaded from hypeweb.smhi.se. In addition, we provide models for the Arctic region, the Arab (Middle East and Northern Africa) region, India, the Niger River basin, the La Plata Basin. This demonstrates the applicability of the HYPE model for large scale modeling in different regions of the world. An important goal with our work is to make our data and tools available as open data and services. For this aim we created the HYPE Open Source Community (OSC) that makes the source code of HYPE available for anyone interested in further development of HYPE. The HYPE OSC (hype.sourceforge.net) is an open source initiative under the Lesser GNU Public License taken by SMHI to strengthen international collaboration in hydrological modeling and hydrological data production. The hypothesis is that more brains and more testing will result in better models and better code. The code is transparent and can be changed and learnt from. New versions of the main code are delivered frequently. HYPE OSC is open to everyone interested in hydrology, hydrological modeling and code development - e.g. scientists, authorities, and consultancies. By joining the HYPE OSC you get access a state-of-the-art operational hydrological model. The HYPE source code is designed to efficiently handle large scale modeling for forecast, hindcast and climate applications. The code is under constant development to improve the hydrological processes, efficiency and readability. In the beginning of 2013 we released a version with new and better modularization based on hydrological processes. This will make the code easier to understand and further develop for a new user. An important challenge in this process is to produce code that is easy for anyone to understand and work with, but still maintain the properties that make the code efficient enough for large scale applications. Input from the HYPE Open Source Community is an important source for future improvements of the HYPE model. Therefore, by joining the community you become an active part of the development, get access to the latest features and can influence future versions of the model.

Numerical Models of Human Circulatory System under Altered Gravity: Brain Circulation

NASA Technical Reports Server (NTRS)

Kim, Chang Sung; Kiris, Cetin; Kwak, Dochan; David, Tim

2003-01-01

A computational fluid dynamics (CFD) approach is presented to model the blood flow through the human circulatory system under altered gravity conditions. Models required for CFD simulation relevant to major hemodynamic issues are introduced such as non-Newtonian flow models governed by red blood cells, a model for arterial wall motion due to fluid-wall interactions, a vascular bed model for outflow boundary conditions, and a model for auto-regulation mechanism. The three-dimensional unsteady incompressible Navier-Stokes equations coupled with these models are solved iteratively using the pseudocompressibility method and dual time stepping. Moving wall boundary conditions from the first-order fluid-wall interaction model are used to study the influence of arterial wall distensibility on flow patterns and wall shear stresses during the heart pulse. A vascular bed modeling utilizing the analogy with electric circuits is coupled with an auto-regulation algorithm for multiple outflow boundaries. For the treatment of complex geometry, a chimera overset grid technique is adopted to obtain connectivity between arterial branches. For code validation, computed results are compared with experimental data for steady and unsteady non-Newtonian flows. Good agreement is obtained for both cases. In sin-type Gravity Benchmark Problems, gravity source terms are added to the Navier-Stokes equations to study the effect of gravitational variation on the human circulatory system. This computational approach is then applied to localized blood flows through a realistic carotid bifurcation and two Circle of Willis models, one using an idealized geometry and the other model using an anatomical data set. A three- dimensional anatomical Circle of Willis configuration is reconstructed from human-specific magnetic resonance images using an image segmentation method. The blood flow through these Circle of Willis models is simulated to provide means for studying gravitational effects on the brain circulation under auto-regulation.

EEG functional connectivity is partially predicted by underlying white matter connectivity

PubMed Central

Chu, CJ; Tanaka, N; Diaz, J; Edlow, BL; Wu, O; Hämäläinen, M; Stufflebeam, S; Cash, SS; Kramer, MA.

2015-01-01

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales. PMID:25534110

Synergism and Combinatorial Coding for Binary Odor Mixture Perception in Drosophila

PubMed Central

Chakraborty, Tuhin Subhra; Siddiqi, Obaid

2016-01-01

Most odors in the natural environment are mixtures of several compounds. Olfactory receptors housed in the olfactory sensory neurons detect these odors and transmit the information to the brain, leading to decision-making. But whether the olfactory system detects the ingredients of a mixture separately or treats mixtures as different entities is not well understood. Using Drosophila melanogaster as a model system, we have demonstrated that fruit flies perceive binary odor mixtures in a manner that is heavily dependent on both the proportion and the degree of dilution of the components, suggesting a combinatorial coding at the peripheral level. This coding strategy appears to be receptor specific and is independent of interneuronal interactions. PMID:27588303

A denoising algorithm for CT image using low-rank sparse coding

NASA Astrophysics Data System (ADS)

Lei, Yang; Xu, Dong; Zhou, Zhengyang; Wang, Tonghe; Dong, Xue; Liu, Tian; Dhabaan, Anees; Curran, Walter J.; Yang, Xiaofeng

2018-03-01

We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously construct the dictionary and achieve sparse representation through clustering similar image patches. A variable-splitting scheme and a quadratic optimization are used to reconstruct CT image based on achieved sparse coefficients. We tested this denoising technology using phantom, brain and abdominal CT images. The experimental results showed that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

26 CFR 1.614-4 - Treatment under the Internal Revenue Code of 1939 with respect to separate operating mineral...

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 7 2010-04-01 2010-04-01 true Treatment under the Internal Revenue Code of 1939..., in the case of oil and gas wells. 1.614-4 Section 1.614-4 Internal Revenue INTERNAL REVENUE SERVICE....614-4 Treatment under the Internal Revenue Code of 1939 with respect to separate operating mineral...

3 CFR - Delegation of Functions and Authority Under Sections 315 and 325 of Title 32, United States Code

Code of Federal Regulations, 2012 CFR

2012-01-01

... 3 The President 1 2012-01-01 2012-01-01 false Delegation of Functions and Authority Under Sections 315 and 325 of Title 32, United States Code Presidential Documents Other Presidential Documents Memorandum of April 14, 2011 Delegation of Functions and Authority Under Sections 315 and 325 of Title 32, United States Code Memorandum for the...

Extending Gurwitsch's field theory of consciousness.

PubMed

Yoshimi, Jeff; Vinson, David W

2015-07-01

Aron Gurwitsch's theory of the structure and dynamics of consciousness has much to offer contemporary theorizing about consciousness and its basis in the embodied brain. On Gurwitsch's account, as we develop it, the field of consciousness has a variable sized focus or "theme" of attention surrounded by a structured periphery of inattentional contents. As the field evolves, its contents change their status, sometimes smoothly, sometimes abruptly. Inner thoughts, a sense of one's body, and the physical environment are dominant field contents. These ideas can be linked with (and help unify) contemporary theories about the neural correlates of consciousness, inattention, the small world structure of the brain, meta-stable dynamics, embodied cognition, and predictive coding in the brain. Published by Elsevier Inc.

Assessing Occupational Exposure to Chemicals in an International Epidemiological Study of Brain Tumours

PubMed Central

van Tongeren, Martie

2013-01-01

The INTEROCC project is a multi-centre case–control study investigating the risk of developing brain cancer due to occupational chemical and electromagnetic field exposures. To estimate chemical exposures, the Finnish Job Exposure Matrix (FINJEM) was modified to improve its performance in the INTEROCC study and to address some of its limitations, resulting in the development of the INTEROCC JEM. An international team of occupational hygienists developed a crosswalk between the Finnish occupational codes used in FINJEM and the International Standard Classification of Occupations 1968 (ISCO68). For ISCO68 codes linked to multiple Finnish codes, weighted means of the exposure estimates were calculated. Similarly, multiple ISCO68 codes linked to a single Finnish code with evidence of heterogeneous exposure were refined. One of the key time periods in FINJEM (1960–1984) was split into two periods (1960–1974 and 1975–1984). Benzene exposure estimates in early periods were modified upwards. The internal consistency of hydrocarbon exposures and exposures to engine exhaust fumes was improved. Finally, exposure to polycyclic aromatic hydrocarbon and benzo(a)pyrene was modified to include the contribution from second-hand smoke. The crosswalk ensured that the FINJEM exposure estimates could be applied to the INTEROCC study subjects. The modifications generally resulted in an increased prevalence of exposure to chemical agents. This increased prevalence of exposure was not restricted to the lowest categories of cumulative exposure, but was seen across all levels for some agents. Although this work has produced a JEM with important improvements compared to FINJEM, further improvements are possible with the expansion of agents and additional external data. PMID:23467593

Cracking Taste Codes by Tapping into Sensory Neuron Impulse Traffic

PubMed Central

Frank, Marion E.; Lundy, Robert F.; Contreras, Robert J.

2008-01-01

Insights into the biological basis for mammalian taste quality coding began with electrophysiological recordings from “taste” nerves and this technique continues to produce essential information today. Chorda tympani (geniculate ganglion) neurons, which are particularly involved in taste quality discrimination, are specialists or generalists. Specialists respond to stimuli characterized by a single taste quality as defined by behavioral cross-generalization in conditioned taste tests. Generalists respond to electrolytes that elicit multiple aversive qualities. Na+-salt (N) specialists in rodents and sweet-stimulus (S) specialists in multiple orders of mammals are well-characterized. Specialists are associated with species’ nutritional needs and their activation is known to be malleable by internal physiological conditions and contaminated external caloric sources. S specialists, associated with the heterodimeric G-protein coupled receptor: T1R, and N specialists, associated with the epithelial sodium channel: ENaC, are consistent with labeled line coding from taste bud to afferent neuron. Yet, S-specialist neurons and behavior are less specific thanT1R2-3 in encompassing glutamate and E generalist neurons are much less specific than a candidate, PDK TRP channel, sour receptor in encompassing salts and bitter stimuli. Specialist labeled lines for nutrients and generalist patterns for aversive electrolytes may be transmitting taste information to the brain side by side. However, specific roles of generalists in taste quality coding may be resolved by selecting stimuli and stimulus levels found in natural situations. T2Rs, participating in reflexes via the glossopharynygeal nerve, became highly diversified in mammalian phylogenesis as they evolved to deal with dangerous substances within specific environmental niches. Establishing the information afferent neurons traffic to the brain about natural taste stimuli imbedded in dynamic complex mixtures will ultimately “crack taste codes.” PMID:18824076

The storage capacity of Potts models for semantic memory retrieval

NASA Astrophysics Data System (ADS)

Kropff, Emilio; Treves, Alessandro

2005-08-01

We introduce and analyse a minimal network model of semantic memory in the human brain. The model is a global associative memory structured as a collection of N local modules, each coding a feature, which can take S possible values, with a global sparseness a (the average fraction of features describing a concept). We show that, under optimal conditions, the number cM of modules connected on average to a module can range widely between very sparse connectivity (high dilution, c_{M}/N\\to 0 ) and full connectivity (c_{M}\\to N ), maintaining a global network storage capacity (the maximum number pc of stored and retrievable concepts) that scales like pc~cMS2/a, with logarithmic corrections consistent with the constraint that each synapse may store up to a fraction of a bit.

Toward an Integration of Deep Learning and Neuroscience

PubMed Central

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P.

2016-01-01

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses. PMID:27683554

Investigating common coding of observed and executed actions in the monkey brain using cross-modal multi-variate fMRI classification.

PubMed

Fiave, Prosper Agbesi; Sharma, Saloni; Jastorff, Jan; Nelissen, Koen

2018-05-19

Mirror neurons are generally described as a neural substrate hosting shared representations of actions, by simulating or 'mirroring' the actions of others onto the observer's own motor system. Since single neuron recordings are rarely feasible in humans, it has been argued that cross-modal multi-variate pattern analysis (MVPA) of non-invasive fMRI data is a suitable technique to investigate common coding of observed and executed actions, allowing researchers to infer the presence of mirror neurons in the human brain. In an effort to close the gap between monkey electrophysiology and human fMRI data with respect to the mirror neuron system, here we tested this proposal for the first time in the monkey. Rhesus monkeys either performed reach-and-grasp or reach-and-touch motor acts with their right hand in the dark or observed videos of human actors performing similar motor acts. Unimodal decoding showed that both executed or observed motor acts could be decoded from numerous brain regions. Specific portions of rostral parietal, premotor and motor cortices, previously shown to house mirror neurons, in addition to somatosensory regions, yielded significant asymmetric action-specific cross-modal decoding. These results validate the use of cross-modal multi-variate fMRI analyses to probe the representations of own and others' actions in the primate brain and support the proposed mapping of others' actions onto the observer's own motor cortices. Copyright © 2018 Elsevier Inc. All rights reserved.

The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.

Automating Cell Detection and Classification in Human Brain Fluorescent Microscopy Images Using Dictionary Learning and Sparse Coding

PubMed Central

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A.; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M.

2017-01-01

Background Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. New method Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Results Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. Comparison with existing methods We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. Conclusion The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. PMID:28267565

Body language in the brain: constructing meaning from expressive movement.

PubMed

Tipper, Christine M; Signorini, Giulia; Grafton, Scott T

2015-01-01

This fMRI study investigated neural systems that interpret body language-the meaningful emotive expressions conveyed by body movement. Participants watched videos of performers engaged in modern dance or pantomime that conveyed specific themes such as hope, agony, lust, or exhaustion. We tested whether the meaning of an affectively laden performance was decoded in localized brain substrates as a distinct property of action separable from other superficial features, such as choreography, kinematics, performer, and low-level visual stimuli. A repetition suppression (RS) procedure was used to identify brain regions that decoded the meaningful affective state of a performer, as evidenced by decreased activity when emotive themes were repeated in successive performances. Because the theme was the only feature repeated across video clips that were otherwise entirely different, the occurrence of RS identified brain substrates that differentially coded the specific meaning of expressive performances. RS was observed bilaterally, extending anteriorly along middle and superior temporal gyri into temporal pole, medially into insula, rostrally into inferior orbitofrontal cortex, and caudally into hippocampus and amygdala. Behavioral data on a separate task indicated that interpreting themes from modern dance was more difficult than interpreting pantomime; a result that was also reflected in the fMRI data. There was greater RS in left hemisphere, suggesting that the more abstract metaphors used to express themes in dance compared to pantomime posed a greater challenge to brain substrates directly involved in decoding those themes. We propose that the meaning-sensitive temporal-orbitofrontal regions observed here comprise a superordinate functional module of a known hierarchical action observation network (AON), which is critical to the construction of meaning from expressive movement. The findings are discussed with respect to a predictive coding model of action understanding.

Progesterone Sharpens Temporal Response Profiles of Sensory Cortical Neurons in Animals Exposed to Traumatic Brain Injury

PubMed Central

Allitt, Benjamin J.; Johnstone, Victoria P. A.; Richards, Katrina L.; Yan, Edwin B.

2017-01-01

Traumatic brain injury (TBI) initiates a cascade of pathophysiological changes that are both complex and difficult to treat. Progesterone (P4) is a neuroprotective treatment option that has shown excellent preclinical benefits in the treatment of TBI, but these benefits have not translated well in the clinic. We have previously shown that P4 exacerbates the already hypoactive upper cortical responses in the short-term post-TBI and does not reduce upper cortical hyperactivity in the long term, and we concluded that there is no tangible benefit to sensory cortex firing strength. Here we examined the effects of P4 treatment on temporal coding resolution in the rodent sensory cortex in both the short term (4 d) and long term (8 wk) following impact-acceleration–induced TBI. We show that in the short-term postinjury, TBI has no effect on sensory cortex temporal resolution and that P4 also sharpens the response profile in all cortical layers in the uninjured brain and all layers other than layer 2 (L2) in the injured brain. In the long term, TBI broadens the response profile in all cortical layers despite firing rate hyperactivity being localized to upper cortical layers and P4 sharpens the response profile in TBI animals in all layers other than L2 and has no long-term effect in the sham brain. These results indicate that P4 has long-term effects on sensory coding that may translate to beneficial perceptual outcomes. The effects seen here, combined with previous beneficial preclinical data, emphasize that P4 is still a potential treatment option in ameliorating TBI-induced disorders. PMID:28933224

An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

NASA Astrophysics Data System (ADS)

Prabhu Verleker, Akshay; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M.

2015-03-01

The purpose of this study is to develop an alternate empirical approach to estimate near-infra-red (NIR) photon propagation and quantify optically induced drug release in brain metastasis, without relying on computationally expensive Monte Carlo techniques (gold standard). Targeted drug delivery with optically induced drug release is a noninvasive means to treat cancers and metastasis. This study is part of a larger project to treat brain metastasis by delivering lapatinib-drug-nanocomplexes and activating NIR-induced drug release. The empirical model was developed using a weighted approach to estimate photon scattering in tissues and calibrated using a GPU based 3D Monte Carlo. The empirical model was developed and tested against Monte Carlo in optical brain phantoms for pencil beams (width 1mm) and broad beams (width 10mm). The empirical algorithm was tested against the Monte Carlo for different albedos along with diffusion equation and in simulated brain phantoms resembling white-matter (μs'=8.25mm-1, μa=0.005mm-1) and gray-matter (μs'=2.45mm-1, μa=0.035mm-1) at wavelength 800nm. The goodness of fit between the two models was determined using coefficient of determination (R-squared analysis). Preliminary results show the Empirical algorithm matches Monte Carlo simulated fluence over a wide range of albedo (0.7 to 0.99), while the diffusion equation fails for lower albedo. The photon fluence generated by empirical code matched the Monte Carlo in homogeneous phantoms (R2=0.99). While GPU based Monte Carlo achieved 300X acceleration compared to earlier CPU based models, the empirical code is 700X faster than the Monte Carlo for a typical super-Gaussian laser beam.

Three-dimensional brain reconstruction of in vivo electrode tracks for neuroscience and neural prosthetic applications

PubMed Central

Markovitz, Craig D.; Tang, Tien T.; Edge, David P.; Lim, Hubert H.

2012-01-01

The brain is a densely interconnected network that relies on populations of neurons within and across multiple nuclei to code for features leading to perception and action. However, the neurophysiology field is still dominated by the characterization of individual neurons, rather than simultaneous recordings across multiple regions, without consistent spatial reconstruction of their locations for comparisons across studies. There are sophisticated histological and imaging techniques for performing brain reconstructions. However, what is needed is a method that is relatively easy and inexpensive to implement in a typical neurophysiology lab and provides consistent identification of electrode locations to make it widely used for pooling data across studies and research groups. This paper presents our initial development of such an approach for reconstructing electrode tracks and site locations within the guinea pig inferior colliculus (IC) to identify its functional organization for frequency coding relevant for a new auditory midbrain implant (AMI). Encouragingly, the spatial error associated with different individuals reconstructing electrode tracks for the same midbrain was less than 65 μm, corresponding to an error of ~1.5% relative to the entire IC structure (~4–5 mm diameter sphere). Furthermore, the reconstructed frequency laminae of the IC were consistently aligned across three sampled midbrains, demonstrating the ability to use our method to combine location data across animals. Hopefully, through further improvements in our reconstruction method, it can be used as a standard protocol across neurophysiology labs to characterize neural data not only within the IC but also within other brain regions to help bridge the gap between cellular activity and network function. Clinically, correlating function with location within and across multiple brain regions can guide optimal placement of electrodes for the growing field of neural prosthetics. PMID:22754502

Stephen Baylin, M.D., Explains Genetics and Epigenetics - TCGA

Cancer.gov

Stephen Baylin, M.D., at the Johns Hopkins Kimmel Cancer Center discusses the how alterations in the DNA code are deciphered in a combined effort with The Cancer Genome Atlas at the National Cancer Institute to decode the brain cancer genome.

Human brain factor 1, a new member of the fork head gene family

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

Murphy, D.B.; Wiese, S.; Burfeind, P.

1994-06-01

Analysis of cDNA clones that cross-hybridized with the fork head domain of the rat HNF-3 gene family revealed 10 cDNAs from human fetal brain and human testis cDNA libraries containing this highly conserved DNA-binding domain. Three of these cDNAs (HFK1, HFK2, and HFK3) were further analyzed. The cDNA HFK1 has a length of 2557 nucleotides and shows strong homology at the nucleotide level (91.2%) to brain factor 1 (BF-1) from rat. The HFK1 cDNA codes for a putative 476 amino acid protein. The homology to BF-1 from rat in the coding region at the amino acid level is 87.5%. Themore » fork head homologous region includes 111 amino acids starting at amino acid 160 and has a 97.5% homology to BF-1. Southern hybridization revealed that HFK1 is highly conserved among mammalian species and possibly birds. Northern analysis with total RNA from human tissues and poly(A)-rich RNA from mouse revealed a 3.2-kb transcript that is present in human and mouse fetal brain and in adult mouse brain. In situ hybridization with sections of mouse embryo and human fetal brain reveals that HFK1 expression is restricted to the neuronal cells in the telencepthalon, with strong expression being observed in the developing dentate gyrus and hippocampus. HFK1 was chromosomally localized by in situ hybridization to 14q12. The cDNA clones HFK2 and HFK3 were analyzed by restriction analysis and sequencing. HFK2 and HFK3 were found to be closely related but different from HFK1. Therefore, it would appear that HFK1, HFK2, HFK3, and BF-1 form a new fork head related subfamily. 33 refs., 6 figs.« less

Hospitalizations for critically ill children with traumatic brain injuries: a longitudinal analysis.

PubMed

Tilford, John M; Aitken, Mary E; Anand, K J S; Green, Jerril W; Goodman, Allen C; Parker, James G; Killingsworth, Jeffrey B; Fiser, Debra H; Adelson, P David

2005-09-01

This study examines the incidence, utilization of procedures, and outcomes for critically ill children hospitalized with traumatic brain injury over the period 1988-1999 to describe the benefits of improved treatment. Retrospective analysis of hospital discharges was conducted using data from the Health Care Cost and Utilization Project Nationwide Inpatient Sample that approximates a 20% sample of U.S. acute care hospitals. Hospital inpatient stays from all types of U.S. community hospitals. The study sample included all children aged 0-21 with a primary or secondary ICD-9-CM diagnosis code for traumatic brain injury and a procedure code for either endotracheal intubation or mechanical ventilation. None. Deaths occurring during hospitalization were used to calculate mortality rates. Use of intracranial pressure monitoring and surgical openings of the skull were investigated as markers for the aggressiveness of treatment. Patients were further classified by insurance status, household income, and hospital characteristics. Over the 12-yr study period, mortality rates decreased 8 percentage points whereas utilization of intracranial pressure monitoring increased by 11 percentage points. The trend toward more aggressive management of traumatic brain injury corresponded with improved hospital outcomes over time. Lack of insurance was associated with vastly worse outcomes. An estimated 6,437 children survived their traumatic brain injury hospitalization because of improved treatment, and 1,418 children died because of increased mortality risk associated with being uninsured. Improved treatment was valued at approximately dollar 17 billion, whereas acute care hospitalization costs increased by dollar 1.5 billion (in constant 2000 dollars). Increased mortality in uninsured children was associated with a dollar 3.76 billion loss in economic benefits. More aggressive management of pediatric traumatic brain injury appears to have contributed to reduced mortality rates over time and saved thousands of lives. Additional lives could be saved if mortality rates could be equalized between insured and uninsured children.

Evolution and genomics of the human brain.

PubMed

Rosales-Reynoso, M A; Juárez-Vázquez, C I; Barros-Núñez, P

2018-05-01

Most living beings are able to perform actions that can be considered intelligent or, at the very least, the result of an appropriate reaction to changing circumstances in their environment. However, the intelligence or intellectual processes of humans are vastly superior to those achieved by all other species. The adult human brain is a highly complex organ weighing approximately 1500g, which accounts for only 2% of the total body weight but consumes an amount of energy equal to that required by all skeletal muscle at rest. Although the human brain displays a typical primate structure, it can be identified by its specific distinguishing features. The process of evolution and humanisation of the Homo sapiens brain resulted in a unique and distinct organ with the largest relative volume of any animal species. It also permitted structural reorganization of tissues and circuits in specific segments and regions. These steps explain the remarkable cognitive abilities of modern humans compared not only with other species in our genus, but also with older members of our own species. Brain evolution required the coexistence of two adaptation mechanisms. The first involves genetic changes that occur at the species level, and the second occurs at the individual level and involves changes in chromatin organisation or epigenetic changes. The genetic mechanisms include: a) genetic changes in coding regions that lead to changes in the sequence and activity of existing proteins; b) duplication and deletion of previously existing genes; c) changes in gene expression through changes in the regulatory sequences of different genes; and d) synthesis of non-coding RNAs. Lastly, this review describes some of the main documented chromosomal differences between humans and great apes. These differences have also contributed to the evolution and humanisation process of the H. sapiens brain. Copyright © 2014 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Learning and coding in biological neural networks

NASA Astrophysics Data System (ADS)

Fiete, Ila Rani

How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and theoretical results on the scalability of this rule show that learning with stochastic gradient ascent may be adequately fast to explain learning in the bird. Finally, we address the more general issue of the scalability of stochastic gradient learning on quadratic cost surfaces in linear systems, as a function of system size and task characteristics, by deriving analytical expressions for the learning curves.

[Some implications of the "consciousness and brain" problem].

PubMed

Ivanitskiĭ, A M; Ivanitskiĭ, G A

2009-10-01

Three issues are discussed: the possible mechanism of subjective events, the rhythmic coding of thinking operations and the possible brain basis of understanding. 1. Several approaches have been developed to explain how subjective experience emerges from brain activity. One of them is the return of the nervous impulses to the sites of their primary projections, providing a synthesis of sensory information with memory and motivation. Support for the existence of such a mechanism stems from studies upon the brain activity that underlies perception (visual and somatosensory) and thought (verbal and imaginative). The cortical centers for information synthesis have been found. For perception, these are located in projection areas: for thinking,--in frontal and temporal-parietal associative cortex. Closely related ideas were also developed by G. Edelman in his re-entry theory of consciousness. Both theories emphasize the key role of memory and motivation in the origin of conscious function. 2. Rearrangements of EEC rhythms underlie mental functions. Certain rhythmical patterns are related with definite types of mental activity. The dependence of one upon the other is rather pronounced and expressive, so it becomes possible to recognize the type of mental operation being performed in mind with few seconds of the ongoing EEG, provided that the analysis of rhythms is accomplished using an artificial neural network. 3. It is commonly recognized that the computer, in contrast to the living brain, can calculate, yet cannot understand. Comprehension implies the comparison of new and old information that requires the ability to search for associations, group similar objects together, and distinguish different objects one from another. However, these functions may also be implemented on a computer. Still, it is believed that computers perform these complicated operations without genuine understanding. Evidently, comprehension additionally has to be based upon some biologically significant ground. It is hypothesized that the subjective feeling of understanding appears when current information is attributed to a definite need, which is scaled in sigh (+/-) coordinated. This coordinate system ceases the brain calculations, when "comprehension" is reached, i. e., the acceptable level of need satisfaction is attained.

Decoding Crucial LncRNAs Implicated in Neurogenesis and Neurological Disorders.

PubMed

Ayana, R; Singh, Shailja; Pati, Soumya

2017-04-15

Unraveling transcriptional heterogeneity and the labyrinthine nature of neurodevelopment can probe insights into neuropsychiatric disorders. It is noteworthy that adult neurogenesis is restricted to the subventricular and subgranular zones of the brain. Recent studies suggest long non-coding RNAs (lncRNAs) as an avant-garde class of regulators implicated in neurodevelopment. But, paucity exists in the knowledge regarding lncRNAs in neurogenesis and their associations with neurodevelopmental defects. To address this, we extensively reviewed the existing literature databases as well as performed relevant in-silico analysis. We utilized Allen Brain Atlas (ABA) differential search module and generated a catalogue of ∼30,000 transcripts specific to the neurogenic zones, including coding and non-coding transcripts. To explore the existing lncRNAs reported in neurogenesis, we performed extensive literature mining and identified 392 lncRNAs. These degenerate lncRNAs were mapped onto the ABA transcript list leading to detection of 20 lncRNAs specific to neurogenic zones (Dentate gyrus/Lateral ventricle), among which 10 showed associations to several neurodevelopmental disorders following in-silico mapping onto brain disease databases like Simons Foundation Autism Research Initiative, AutDB, and lncRNADisease. Notably, using ABA correlation module, we could establish lncRNA-to-mRNA coexpression networks for the above 10 candidate lncRNAs. Finally, pathway prediction revealed physical, biochemical, or regulatory interactions for nine lncRNAs. In addition, ABA differential search also revealed 54 novel significant lncRNAs from the null set (∼30,000). Conclusively, this review represents an updated catalogue of lncRNAs in neurogenesis and neurological diseases, and overviews the field of OMICs-based data analysis for understanding lncRNome-based regulation in neurodevelopment.

Surveillance of paediatric traumatic brain injuries using the NEISS: choosing an appropriate case definition.

PubMed

Thompson, Meghan C; Wheeler, Krista K; Shi, Junxin; Smith, Gary A; Groner, Jonathan I; Haley, Kathryn J; Xiang, Huiyun

2014-01-01

To evaluate the definition of traumatic brain injury (TBI) in the National Electronic Injury Surveillance System (NEISS) and compare TBI case ascertainment using NEISS vs. ICD-9-CM diagnosis coding. Two data samples from a NEISS participating emergency department (ED) in 2008 were compared: (1) NEISS records meeting the recommended NEISS TBI definition and (2) Hospital ED records meeting the ICD-9-CM CDC recommended TBI definition. The sensitivity and positive predictive value were calculated for the NEISS definition using the ICD-9-CM definition as the gold standard. Further analyses were performed to describe cases characterized as TBIs in both datasets and to determine why some cases were not classified as TBIs in both datasets. There were 1834 TBI cases captured by the NEISS and 1836 TBI cases captured by the ICD-9-CM coded ED record, but only 1542 were eligible for inclusion in NEISS. There were 1403 cases classified as TBIs by both the NEISS and ICD-9-CM diagnosis codes. The NEISS TBI definition had a sensitivity of 91.0% (95% CI = 89.6-92.4%) and positive predictive value of 76.5% (95% CI = 74.6-78.4%). Using the NEISS TBI definition presented in this paper would standardize and improve the accuracy of TBI research using the NEISS.

Transcriptional role of androgen receptor in the expression of long non-coding RNA Sox2OT in neurogenesis

PubMed Central

Tosetti, Valentina; Sassone, Jenny; Ferri, Anna L. M.; Taiana, Michela; Bedini, Gloria; Nava, Sara; Brenna, Greta; Di Resta, Chiara; Pareyson, Davide; Di Giulio, Anna Maria; Carelli, Stephana

2017-01-01

The complex architecture of adult brain derives from tightly regulated migration and differentiation of precursor cells generated during embryonic neurogenesis. Changes at transcriptional level of genes that regulate migration and differentiation may lead to neurodevelopmental disorders. Androgen receptor (AR) is a transcription factor that is already expressed during early embryonic days. However, AR role in the regulation of gene expression at early embryonic stage is yet to be determinate. Long non-coding RNA (lncRNA) Sox2 overlapping transcript (Sox2OT) plays a crucial role in gene expression control during development but its transcriptional regulation is still to be clearly defined. Here, using Bicalutamide in order to pharmacologically inactivated AR, we investigated whether AR participates in the regulation of the transcription of the lncRNASox2OTat early embryonic stage. We identified a new DNA binding region upstream of Sox2 locus containing three androgen response elements (ARE), and found that AR binds such a sequence in embryonic neural stem cells and in mouse embryonic brain. Our data suggest that through this binding, AR can promote the RNA polymerase II dependent transcription of Sox2OT. Our findings also suggest that AR participates in embryonic neurogenesis through transcriptional control of the long non-coding RNA Sox2OT. PMID:28704421

Transcriptional role of androgen receptor in the expression of long non-coding RNA Sox2OT in neurogenesis.

PubMed

Tosetti, Valentina; Sassone, Jenny; Ferri, Anna L M; Taiana, Michela; Bedini, Gloria; Nava, Sara; Brenna, Greta; Di Resta, Chiara; Pareyson, Davide; Di Giulio, Anna Maria; Carelli, Stephana; Parati, Eugenio A; Gorio, Alfredo

2017-01-01

The complex architecture of adult brain derives from tightly regulated migration and differentiation of precursor cells generated during embryonic neurogenesis. Changes at transcriptional level of genes that regulate migration and differentiation may lead to neurodevelopmental disorders. Androgen receptor (AR) is a transcription factor that is already expressed during early embryonic days. However, AR role in the regulation of gene expression at early embryonic stage is yet to be determinate. Long non-coding RNA (lncRNA) Sox2 overlapping transcript (Sox2OT) plays a crucial role in gene expression control during development but its transcriptional regulation is still to be clearly defined. Here, using Bicalutamide in order to pharmacologically inactivated AR, we investigated whether AR participates in the regulation of the transcription of the lncRNASox2OTat early embryonic stage. We identified a new DNA binding region upstream of Sox2 locus containing three androgen response elements (ARE), and found that AR binds such a sequence in embryonic neural stem cells and in mouse embryonic brain. Our data suggest that through this binding, AR can promote the RNA polymerase II dependent transcription of Sox2OT. Our findings also suggest that AR participates in embryonic neurogenesis through transcriptional control of the long non-coding RNA Sox2OT.

Predictive information processing is a fundamental learning mechanism present in early development: evidence from infants.

PubMed

Trainor, Laurel J

2012-02-01

Evidence is presented that predictive coding is fundamental to brain function and present in early infancy. Indeed, mismatch responses to unexpected auditory stimuli are among the earliest robust cortical event-related potential responses, and have been measured in young infants in response to many types of deviation, including in pitch, timing, and melodic pattern. Furthermore, mismatch responses change quickly with specific experience, suggesting that predictive coding reflects a powerful, early-developing learning mechanism. Copyright © 2011 Elsevier B.V. All rights reserved.

A Non-Critical String (Liouville) Approach to Brain Microtubules:. State Vector Reduction, Memory Coding and Capacity

NASA Astrophysics Data System (ADS)

Mavromatos, N. E.; Nanopoulos, D. V.

Microtubule (MT) networks, subneural paracrystalline cytoskeletal structures, seem to play a fundamental role in the neurons. We cast here the complicated MT dynamics in the form of a (1+1)-dimensional noncritical string theory, thus enabling us to provide a consistent quantum treatment of MTs, including enviromental friction effects. We suggest, thus, that the MTs are the microsites, in the brain, for the emergence of stable, macroscopic quantum coherent states, identifiable with the preconscious states. Quantum space-time effects, as described by noncritical string theory, trigger then an organized collapse of the coherent states down to a specific or conscious state. The whole process we estimate to take { O}(1 sec), in excellent agreement with a plethora of experimental/observational findings. The microscopic arrow of time, endemic in noncritical string theory, and apparent here in the self-collapse process, provides a satisfactory and simple resolution to the age-old problem of how the, central to our feelings of awareness, sensation of the progression of time is generated. In addition, the complete integrability of the stringy model for MT we advocate in this work proves sufficient in providing a satisfactory solution to memory coding and capacity. Such features might turn out to be important for a model of the brain as a quantum computer.

The PRP Effect Following Callosotomy: Residual Interference Despite Uncoupling of Lateralized Response Codes

NASA Technical Reports Server (NTRS)

Ivry, Richard B.; Franz, Elizabeth A.; Kingstone, Alan; Johnston, James C.; Null, Cynthia H. (Technical Monitor)

1995-01-01

A callosotomy patient was tested in two dual-task experiments requiring successive speeded responses to lateralized stimuli. In accord with the recent findings of Pashler, O'Brien, Luck, Hillyard, Mangun, and Gazzaniga (in press), the patient showed a robust psychological refractory period effect (PRP) responses on Task 2 were inversely related to the stimulus-onset asynchrony (SOA). However, three aspects of our data indicated that the processing limitations for the patient were different than those observed with control subjects. First, the split-brain patient did not show an increase in reaction time when the two tasks required responses from a common output system (i.e., both manual responses) in comparison to when different output systems were used (i.e., manual-vocal). Second, inconsistent stimulus-response mappings for the two tasks greatly inflated response latencies for the control subjects, but had minimal effect on the performance of the split-brain patient. Third, the consistency manipulation was underadditive with SOA for only the patient, suggesting a later bottleneck in processing following callosotomy than was observed for the control subjects. It is proposed that sectioning the corpus callosum eliminates interference resulting from competing stimulus response codes. Nonetheless, dual-task interference persists for the split-brain subject because a subcortical gate constrains when selected responses can be implemented.

A Novel Method of Building Functional Brain Network Using Deep Learning Algorithm with Application in Proficiency Detection.

PubMed

Hua, Chengcheng; Wang, Hong; Wang, Hong; Lu, Shaowen; Liu, Chong; Khalid, Syed Madiha

2018-04-11

Functional brain network (FBN) has become very popular to analyze the interaction between cortical regions in the last decade. But researchers always spend a long time to search the best way to compute FBN for their specific studies. The purpose of this study is to detect the proficiency of operators during their mineral grinding process controlling based on FBN. To save the search time, a novel semi-data-driven method of computing functional brain connection based on stacked autoencoder (BCSAE) is proposed in this paper. This method uses stacked autoencoder (SAE) to encode the multi-channel EEG data into codes and then computes the dissimilarity between the codes from every pair of electrodes to build FBN. The highlight of this method is that the SAE has a multi-layered structure and is semi-supervised, which means it can dig deeper information and generate better features. Then an experiment was performed, the EEG of the operators were collected while they were operating and analyzed to detect their proficiency. The results show that the BCSAE method generated more number of separable features with less redundancy, and the average accuracy of classification (96.18%) is higher than that of the control methods: PLV (92.19%) and PLI (78.39%).

Genome wide identification of Staufen2-bound mRNAs in embryonic rat brains.

PubMed

Maher-Laporte, Marjolaine; DesGroseillers, Luc

2010-05-01

Messenger ribonucleoprotein particles (mRNPs) are used to transport mRNAs along neuronal dendrites to their site of translation. Staufen2 is an mRNA-binding protein expressed in the cell bodies and cellular processes of different brain cells. It is notably involved in the transport of dendritic mRNAs along microtubules. Its knockdown expression was shown to change spine morphology and impair synaptic functions. However, the identity of Staufen2-bound mRNAs in brain cells is still completely unknown. As a mean to identify these mRNAs, we immunoprecipitated Staufen2-containing mRNPs from embryonic rat brains and used a genome wide approach to identify Staufen2-associated mRNAs. The genome wide approach identified 1780 mRNAs in Staufen2-containing mRNPs that code for proteins involved in cellular processes such as post-translational protein modifications, RNA metabolism, intracellular transport and translation. These results represent an additional and important step in the characterization of Staufen2- mediated neuronal functions in rat brains.

Clinical applications of modern imaging technology: stereo image formation and location of brain cancer

NASA Astrophysics Data System (ADS)

Wang, Dezong; Wang, Jinxiang

1994-05-01

It is very important to locate the tumor for a patient, who has cancer in his brain. If he only gets X-CT or MRI pictures, the doctor does not know the size, shape location of the tumor and the relation between the tumor and other organs. This paper presents the formation of stereo images of cancer. On the basis of color code and color 3D reconstruction. The stereo images of tumor, brain and encephalic truncus are formed. The stereo image of cancer can be round on X, Y, Z-coordinates to show the shape from different directions. In order to show the location of tumor, stereo image of tumor and encephalic truncus are provided on different angles. The cross section pictures are also offered to indicate the relation of brain, tumor and encephalic truncus on cross sections. In this paper the calculating of areas, volume and the space between cancer and the side of the brain are also described.

Brain Tumor Database, a free relational database for collection and analysis of brain tumor patient information.

PubMed

Bergamino, Maurizio; Hamilton, David J; Castelletti, Lara; Barletta, Laura; Castellan, Lucio

2015-03-01

In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org. © The Author(s) 2013.

Brain Region-Specific Expression of Genes Mapped within Quantitative Trait Loci for Behavioral Responsiveness to Acute Stress in Fisher 344 and Wistar Kyoto Male Rats (Open Access Postprint)

DTIC Science & Technology

2018-03-12

RGSC_3.4. Using the Integrative Genomics Viewer (Broad Institute, Cambridge, Massachusetts), we iden- tified the coding sequence variations between the...adrenal axis abnormalities and disturbances in brain metabolism resem- bling those in depressive states [74]. Ifna2 is also known to induce memory... psychological science a journal of the Association for Psychological Science. 2016; 4(1):17–27. https://doi.org/10.1177/2167702615577470 PMID: 26958455

A practical VEP-based brain-computer interface.

PubMed

Wang, Yijun; Wang, Ruiping; Gao, Xiaorong; Hong, Bo; Gao, Shangkai

2006-06-01

This paper introduces the development of a practical brain-computer interface at Tsinghua University. The system uses frequency-coded steady-state visual evoked potentials to determine the gaze direction of the user. To ensure more universal applicability of the system, approaches for reducing user variation on system performance have been proposed. The information transfer rate (ITR) has been evaluated both in the laboratory and at the Rehabilitation Center of China, respectively. The system has been proved to be applicable to > 90% of people with a high ITR in living environments.

Critical Role of Peripheral Vasoconstriction in Fatal Brain Hyperthermia Induced by MDMA (Ecstasy) under Conditions That Mimic Human Drug Use

PubMed Central

Kim, Albert H.; Wakabayashi, Ken T.; Baumann, Michael H.; Shaham, Yavin

2014-01-01

MDMA (Ecstasy) is an illicit drug used by young adults at hot, crowed “rave” parties, yet the data on potential health hazards of its abuse remain controversial. Here, we examined the effect of MDMA on temperature homeostasis in male rats under standard laboratory conditions and under conditions that simulate drug use in humans. We chronically implanted thermocouple microsensors in the nucleus accumbens (a brain reward area), temporal muscle, and facial skin to measure temperature continuously from freely moving rats. While focusing on brain hyperthermia, temperature monitoring from the two peripheral locations allowed us to evaluate the physiological mechanisms (i.e., intracerebral heat production and heat loss via skin surfaces) that underlie MDMA-induced brain temperature responses. Our data confirm previous reports on high individual variability and relatively weak brain hyperthermic effects of MDMA under standard control conditions (quiet rest, 22−23°C), but demonstrate dramatic enhancements of drug-induced brain hyperthermia during social interaction (exposure to male conspecific) and in warm environments (29°C). Importantly, we identified peripheral vasoconstriction as a critical mechanism underlying the activity- and state-dependent potentiation of MDMA-induced brain hyperthermia. Through this mechanism, which prevents proper heat dissipation to the external environment, MDMA at a moderate nontoxic dose (9 mg/kg or ∼1/5 of LD50 in rats) can cause fatal hyperthermia under environmental conditions commonly encountered by humans. Our results demonstrate that doses of MDMA that are nontoxic under cool, quiet conditions can become highly dangerous under conditions that mimic recreational use of MDMA at rave parties or other hot, crowded venues. PMID:24899699

Adaptive neural coding: from biological to behavioral decision-making

PubMed Central

Louie, Kenway; Glimcher, Paul W.; Webb, Ryan

2015-01-01

Empirical decision-making in diverse species deviates from the predictions of normative choice theory, but why such suboptimal behavior occurs is unknown. Here, we propose that deviations from optimality arise from biological decision mechanisms that have evolved to maximize choice performance within intrinsic biophysical constraints. Sensory processing utilizes specific computations such as divisive normalization to maximize information coding in constrained neural circuits, and recent evidence suggests that analogous computations operate in decision-related brain areas. These adaptive computations implement a relative value code that may explain the characteristic context-dependent nature of behavioral violations of classical normative theory. Examining decision-making at the computational level thus provides a crucial link between the architecture of biological decision circuits and the form of empirical choice behavior. PMID:26722666

Independent rate and temporal coding in hippocampal pyramidal cells.

PubMed

Huxter, John; Burgess, Neil; O'Keefe, John

2003-10-23

In the brain, hippocampal pyramidal cells use temporal as well as rate coding to signal spatial aspects of the animal's environment or behaviour. The temporal code takes the form of a phase relationship to the concurrent cycle of the hippocampal electroencephalogram theta rhythm. These two codes could each represent a different variable. However, this requires the rate and phase to vary independently, in contrast to recent suggestions that they are tightly coupled, both reflecting the amplitude of the cell's input. Here we show that the time of firing and firing rate are dissociable, and can represent two independent variables: respectively the animal's location within the place field, and its speed of movement through the field. Independent encoding of location together with actions and stimuli occurring there may help to explain the dual roles of the hippocampus in spatial and episodic memory, or may indicate a more general role of the hippocampus in relational/declarative memory.

A comparison of the COG and MCNP codes in computational neutron capture therapy modeling, Part II: gadolinium neutron capture therapy models and therapeutic effects.

PubMed

Wangerin, K; Culbertson, C N; Jevremovic, T

2005-08-01

The goal of this study was to evaluate the COG Monte Carlo radiation transport code, developed and tested by Lawrence Livermore National Laboratory, for gadolinium neutron capture therapy (GdNCT) related modeling. The validity of COG NCT model has been established for this model, and here the calculation was extended to analyze the effect of various gadolinium concentrations on dose distribution and cell-kill effect of the GdNCT modality and to determine the optimum therapeutic conditions for treating brain cancers. The computational results were compared with the widely used MCNP code. The differences between the COG and MCNP predictions were generally small and suggest that the COG code can be applied to similar research problems in NCT. Results for this study also showed that a concentration of 100 ppm gadolinium in the tumor was most beneficial when using an epithermal neutron beam.

Temporal Processing in the Olfactory System: Can We See a Smell?

PubMed Central

Gire, David H.; Restrepo, Diego; Sejnowski, Terrence J.; Greer, Charles; De Carlos, Juan A.; Lopez-Mascaraque, Laura

2013-01-01

Sensory processing circuits in the visual and olfactory systems receive input from complex, rapidly changing environments. Although patterns of light and plumes of odor create different distributions of activity in the retina and olfactory bulb, both structures use what appears on the surface similar temporal coding strategies to convey information to higher areas in the brain. We compare temporal coding in the early stages of the olfactory and visual systems, highlighting recent progress in understanding the role of time in olfactory coding during active sensing by behaving animals. We also examine studies that address the divergent circuit mechanisms that generate temporal codes in the two systems, and find that they provide physiological information directly related to functional questions raised by neuroanatomical studies of Ramon y Cajal over a century ago. Consideration of differences in neural activity in sensory systems contributes to generating new approaches to understand signal processing. PMID:23664611

Computational Hemodynamic Simulation of Human Circulatory System under Altered Gravity

NASA Technical Reports Server (NTRS)

Kim. Chang Sung; Kiris, Cetin; Kwak, Dochan

2003-01-01

A computational hemodynamics approach is presented to simulate the blood flow through the human circulatory system under altered gravity conditions. Numerical techniques relevant to hemodynamics issues are introduced to non-Newtonian modeling for flow characteristics governed by red blood cells, distensible wall motion due to the heart pulse, and capillary bed modeling for outflow boundary conditions. Gravitational body force terms are added to the Navier-Stokes equations to study the effects of gravity on internal flows. Six-type gravity benchmark problems are originally presented to provide the fundamental understanding of gravitational effects on the human circulatory system. For code validation, computed results are compared with steady and unsteady experimental data for non-Newtonian flows in a carotid bifurcation model and a curved circular tube, respectively. This computational approach is then applied to the blood circulation in the human brain as a target problem. A three-dimensional, idealized Circle of Willis configuration is developed with minor arteries truncated based on anatomical data. Demonstrated is not only the mechanism of the collateral circulation but also the effects of gravity on the distensible wall motion and resultant flow patterns.

Impaired fast-spiking interneuron function in a genetic mouse model of depression

PubMed Central

Sauer, Jonas-Frederic; Strüber, Michael; Bartos, Marlene

2015-01-01

Rhythmic neuronal activity provides a frame for information coding by co-active cell assemblies. Abnormal brain rhythms are considered as potential pathophysiological mechanisms causing mental disease, but the underlying network defects are largely unknown. We find that mice expressing truncated Disrupted-in-Schizophrenia 1 (Disc1), which mirror a high-prevalence genotype for human psychiatric illness, show depression-related behavior. Theta and low-gamma synchrony in the prelimbic cortex (PrlC) is impaired in Disc1 mice and inversely correlated with the extent of behavioural despair. While weak theta activity is driven by the hippocampus, disturbance of low-gamma oscillations is caused by local defects of parvalbumin (PV)-expressing fast-spiking interneurons (FS-INs). The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets. Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations. Our data link network defects with a gene mutation underlying depression in humans. DOI: http://dx.doi.org/10.7554/eLife.04979.001 PMID:25735038

Reptiles: a new model for brain evo-devo research.

PubMed

Nomura, Tadashi; Kawaguchi, Masahumi; Ono, Katsuhiko; Murakami, Yasunori

2013-03-01

Vertebrate brains exhibit vast amounts of anatomical diversity. In particular, the elaborate and complex nervous system of amniotes is correlated with the size of their behavioral repertoire. However, the evolutionary mechanisms underlying species-specific brain morphogenesis remain elusive. In this review we introduce reptiles as a new model organism for understanding brain evolution. These animal groups inherited ancestral traits of brain architectures. We will describe several unique aspects of the reptilian nervous system with a special focus on the telencephalon, and discuss the genetic mechanisms underlying reptile-specific brain morphology. The establishment of experimental evo-devo approaches to studying reptiles will help to shed light on the origin of the amniote brains. Copyright © 2013 Wiley Periodicals, Inc.

Photoperiodic responses of depression-like behavior, the brain serotonergic system, and peripheral metabolism in laboratory mice.

PubMed

Otsuka, Tsuyoshi; Kawai, Misato; Togo, Yuki; Goda, Ryosei; Kawase, Takahiro; Matsuo, Haruka; Iwamoto, Ayaka; Nagasawa, Mao; Furuse, Mitsuhiro; Yasuo, Shinobu

2014-02-01

Seasonal affective disorder (SAD) is characterized by depression during specific seasons, generally winter. The pathophysiological mechanisms underlying SAD remain elusive due to a limited number of animal models with high availability and validity. Here we show that laboratory C57BL/6J mice display photoperiodic changes in depression-like behavior and brain serotonin content. C57BL/6J mice maintained under short-day conditions, as compared to those under long-day conditions, demonstrated prolonged immobility times in the forced swimming test with lower brain levels of serotonin and its precursor l-tryptophan. Furthermore, photoperiod altered multiple parameters reflective of peripheral metabolism, including the ratio of plasma l-tryptophan to the sum of other large neutral amino acids that compete for transport across the blood-brain barrier, responses of circulating glucose and insulin to glucose load, sucrose intake under restricted feeding condition, and sensitivity of the brain serotonergic system to peripherally administered glucose. These data suggest that the mechanisms underlying SAD involve the brain-peripheral tissue network, and C57BL/6J mice can serve as a powerful tool for investigating the link between seasons and mood. Copyright © 2013 Elsevier Ltd. All rights reserved.

Body and brain temperature coupling: the critical role of cerebral blood flow

PubMed Central

Ackerman, Joseph J. H.; Yablonskiy, Dmitriy A.

2010-01-01

Direct measurements of deep-brain and body-core temperature were performed on rats to determine the influence of cerebral blood flow (CBF) on brain temperature regulation under static and dynamic conditions. Static changes of CBF were achieved using different anesthetics (chloral hydrate, CH; α-chloralose, αCS; and isoflurane, IF) with αCS causing larger decreases in CBF than CH and IF; dynamic changes were achieved by inducing transient hypercapnia (5% CO2 in 40% O2 and 55% N2). Initial deep-brain/body-core temperature differentials were anesthetic-type dependent with the largest differential observed with rats under αCS anesthesia (ca. 2°C). Hypercapnia induction raised rat brain temperature under all three anesthesia regimes, but by different anesthetic-dependent amounts correlated with the initial differentials—αCS anesthesia resulted in the largest brain temperature increase (0.32 ± 0.08°C), while CH and IF anesthesia lead to smaller increases (0.12 ± 0.03 and 0.16 ± 0.05°C, respectively). The characteristic temperature transition time for the hypercapnia-induced temperature increase was 2–3 min under CH and IF anesthesia and ~4 min under αCS anesthesia. We conclude that both, the deep-brain/body-core temperature differential and the characteristic temperature transition time correlate with CBF: a lower CBF promotes higher deep-brain/body-core temperature differentials and, upon hypercapnia challenge, longer characteristic transition times to increased temperatures. PMID:19277681

Body and brain temperature coupling: the critical role of cerebral blood flow.

PubMed

Zhu, Mingming; Ackerman, Joseph J H; Yablonskiy, Dmitriy A

2009-08-01

Direct measurements of deep-brain and body-core temperature were performed on rats to determine the influence of cerebral blood flow (CBF) on brain temperature regulation under static and dynamic conditions. Static changes of CBF were achieved using different anesthetics (chloral hydrate, CH; alpha-chloralose, alphaCS; and isoflurane, IF) with alphaCS causing larger decreases in CBF than CH and IF; dynamic changes were achieved by inducing transient hypercapnia (5% CO(2) in 40% O(2) and 55% N(2)). Initial deep-brain/body-core temperature differentials were anesthetic-type dependent with the largest differential observed with rats under alphaCS anesthesia (ca. 2 degrees C). Hypercapnia induction raised rat brain temperature under all three anesthesia regimes, but by different anesthetic-dependent amounts correlated with the initial differentials--alphaCS anesthesia resulted in the largest brain temperature increase (0.32 +/- 0.08 degrees C), while CH and IF anesthesia lead to smaller increases (0.12 +/- 0.03 and 0.16 +/- 0.05 degrees C, respectively). The characteristic temperature transition time for the hypercapnia-induced temperature increase was 2-3 min under CH and IF anesthesia and approximately 4 min under alphaCS anesthesia. We conclude that both, the deep-brain/body-core temperature differential and the characteristic temperature transition time correlate with CBF: a lower CBF promotes higher deep-brain/body-core temperature differentials and, upon hypercapnia challenge, longer characteristic transition times to increased temperatures.

A power-efficient communication system between brain-implantable devices and external computers.

PubMed

Yao, Ning; Lee, Heung-No; Chang, Cheng-Chun; Sclabassi, Robert J; Sun, Mingui

2007-01-01

In this paper, we propose a power efficient communication system for linking a brain-implantable device to an external system. For battery powered implantable devices, the processor and the transmitter power should be reduced in order to both conserve battery power and reduce the health risks associated with transmission. To accomplish this, a joint source-channel coding/decoding system is devised. Low-density generator matrix (LDGM) codes are used in our system due to their low encoding complexity. The power cost for signal processing within the implantable device is greatly reduced by avoiding explicit source encoding. Raw data which is highly correlated is transmitted. At the receiver, a Markov chain source correlation model is utilized to approximate and capture the correlation of raw data. A turbo iterative receiver algorithm is designed which connects the Markov chain source model to the LDGM decoder in a turbo-iterative way. Simulation results show that the proposed system can save up to 1 to 2.5 dB on transmission power.

Distinct cortical codes and temporal dynamics for conscious and unconscious percepts

PubMed Central

Salti, Moti; Monto, Simo; Charles, Lucie; King, Jean-Remi; Parkkonen, Lauri; Dehaene, Stanislas

2015-01-01

The neural correlates of consciousness are typically sought by comparing the overall brain responses to perceived and unperceived stimuli. However, this comparison may be contaminated by non-specific attention, alerting, performance, and reporting confounds. Here, we pursue a novel approach, tracking the neuronal coding of consciously and unconsciously perceived contents while keeping behavior identical (blindsight). EEG and MEG were recorded while participants reported the spatial location and visibility of a briefly presented target. Multivariate pattern analysis demonstrated that considerable information about spatial location traverses the cortex on blindsight trials, but that starting ≈270 ms post-onset, information unique to consciously perceived stimuli, emerges in superior parietal and superior frontal regions. Conscious access appears characterized by the entry of the perceived stimulus into a series of additional brain processes, each restricted in time, while the failure of conscious access results in the breaking of this chain and a subsequent slow decay of the lingering unconscious activity. DOI: http://dx.doi.org/10.7554/eLife.05652.001 PMID:25997100

Interoceptive inference: From computational neuroscience to clinic.

PubMed

Owens, Andrew P; Allen, Micah; Ondobaka, Sasha; Friston, Karl J

2018-04-22

The central and autonomic nervous systems can be defined by their anatomical, functional and neurochemical characteristics, but neither functions in isolation. For example, fundamental components of autonomically mediated homeostatic processes are afferent interoceptive signals reporting the internal state of the body and efferent signals acting on interoceptive feedback assimilated by the brain. Recent predictive coding (interoceptive inference) models formulate interoception in terms of embodied predictive processes that support emotion and selfhood. We propose interoception may serve as a way to investigate holistic nervous system function and dysfunction in disorders of brain, body and behaviour. We appeal to predictive coding and (active) interoceptive inference, to describe the homeostatic functions of the central and autonomic nervous systems. We do so by (i) reviewing the active inference formulation of interoceptive and autonomic function, (ii) survey clinical applications of this formulation and (iii) describe how it offers an integrative approach to human physiology; particularly, interactions between the central and peripheral nervous systems in health and disease. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.

Losing the rose tinted glasses: neural substrates of unbiased belief updating in depression

PubMed Central

Garrett, Neil; Sharot, Tali; Faulkner, Paul; Korn, Christoph W.; Roiser, Jonathan P.; Dolan, Raymond J.

2014-01-01

Recent evidence suggests that a state of good mental health is associated with biased processing of information that supports a positively skewed view of the future. Depression, on the other hand, is associated with unbiased processing of such information. Here, we use brain imaging in conjunction with a belief update task administered to clinically depressed patients and healthy controls to characterize brain activity that supports unbiased belief updating in clinically depressed individuals. Our results reveal that unbiased belief updating in depression is mediated by strong neural coding of estimation errors in response to both good news (in left inferior frontal gyrus and bilateral superior frontal gyrus) and bad news (in right inferior parietal lobule and right inferior frontal gyrus) regarding the future. In contrast, intact mental health was linked to a relatively attenuated neural coding of bad news about the future. These findings identify a neural substrate mediating the breakdown of biased updating in major depression disorder, which may be essential for mental health. PMID:25221492

Integrating Hebbian and homeostatic plasticity: introduction.

PubMed

Fox, Kevin; Stryker, Michael

2017-03-05

Hebbian plasticity is widely considered to be the mechanism by which information can be coded and retained in neurons in the brain. Homeostatic plasticity moves the neuron back towards its original state following a perturbation, including perturbations produced by Hebbian plasticity. How then does homeostatic plasticity avoid erasing the Hebbian coded information? To understand how plasticity works in the brain, and therefore to understand learning, memory, sensory adaptation, development and recovery from injury, requires development of a theory of plasticity that integrates both forms of plasticity into a whole. In April 2016, a group of computational and experimental neuroscientists met in London at a discussion meeting hosted by the Royal Society to identify the critical questions in the field and to frame the research agenda for the next steps. Here, we provide a brief introduction to the papers arising from the meeting and highlight some of the themes to have emerged from the discussions.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'. © 2017 The Author(s).

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

PubMed

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Alterations in autobiographical memory for a blast event in Operation Enduring Freedom and Operation Iraqi Freedom veterans with mild traumatic brain injury.

PubMed

Palombo, Daniela J; Kapson, Heather S; Lafleche, Ginette; Vasterling, Jennifer J; Marx, Brian P; Franz, Molly; Verfaellie, Mieke

2015-07-01

Although loss of consciousness associated with moderate or severe traumatic brain injury (TBI) is thought to interfere with encoding of the TBI event, little is known about the effects of mild TBI (mTBI), which typically involves only transient disruption in consciousness. Blast-exposed Afghanistan and Iraq War veterans were asked to recall the blast event. Participants were stratified based on whether the blast was associated with probable mTBI (n = 50) or not (n = 25). Narratives were scored for organizational structure (i.e., coherence) using the Narrative Coherence Coding Scheme (Reese et al., 2011) and episodic recollection using the Autobiographical Interview Coding Procedures (Levine et al., 2002). The mTBI group produced narratives that were less coherent but contained more episodic details than those of the no-TBI group. These results suggest that mTBI interferes with the organizational quality of memory in a manner that is independent of episodic detail generation. (c) 2015 APA, all rights reserved).

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

PubMed Central

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. PMID:29503613

Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease.

PubMed Central

Buzsáki, György; Watson, Brendon O.

2012-01-01

The perpetual activity of the cerebral cortex is largely supported by the variety of oscillations the brain generates, spanning a number of frequencies and anatomical locations, as well as behavioral correlates. First, we review findings from animal studies showing that most forms of brain rhythms are inhibition-based, producing rhythmic volleys of inhibitory inputs to principal cell populations, thereby providing alternating temporal windows of relatively reduced and enhanced excitability in neuronal networks. These inhibition-based mechanisms offer natural temporal frames to group or “chunk” neuronal activity into cell assemblies and sequences of assemblies, with more complex multi-oscillation interactions creating syntactical rules for the effective exchange of information among cortical networks. We then review recent studies in human psychiatric patients demonstrating a variety alterations in neural oscillations across all major psychiatric diseases, and suggest possible future research directions and treatment approaches based on the fundamental properties of brain rhythms. PMID:23393413

I'm Still Me: Inspiration and Instruction from Individuals with Brain Cancer.

PubMed

Piderman, Katherine M; Egginton, Jason S; Ingram, Cory; Dose, Ann Marie; Yoder, Timothy J; Lovejoy, Laura A; Swanson, Spence W; Hogg, James T; Lapid, Maria I; Jatoi, Aminah; Remtema, Megan S; Tata, Beba S; Breitkopf, Carmen Radecki

2017-01-01

Individuals with brain cancer face many challenges, including threats to cognition, personality, and sensory and motor functioning. These can alter one's sense of identity and result in despair. Chaplain-led spiritual interviews were conducted with 19 patients with brain cancer as part of a larger spiritual legacy intervention called "Hear My Voice." The majority was female (58%), married (68%) and had aggressive/advanced tumors (63%). Participants were 22-68 years of age and expressed the following religious affiliations: Protestant (42%), Catholic (21%), Muslim (5%), and none (32%). Framework analysis was applied to reduce and understand the interview data. Primary codes were relationships with: God or the spiritual, others, and self. Brain cancer was reported to deepen and enrich patients' commitment to these relationships. Struggle and grief were also revealed. Results suggest the continued vitality, growth and generativity of these participants and provide insight for chaplains and others on the medical team.

The brain's dress code: How The Dress allows to decode the neuronal pathway of an optical illusion.

PubMed

Schlaffke, Lara; Golisch, Anne; Haag, Lauren M; Lenz, Melanie; Heba, Stefanie; Lissek, Silke; Schmidt-Wilcke, Tobias; Eysel, Ulf T; Tegenthoff, Martin

2015-12-01

Optical illusions have broadened our understanding of the brain's role in visual perception. A modern day optical illusion emerged from a posted photo of a striped dress, which some perceived as white and gold and others as blue and black. Here we show, using functional magnetic resonance imaging (fMRI), that those who perceive The Dress as white/gold have higher activation in response to the image of The Dress in brain regions critically involved in higher cognition (frontal and parietal brain areas). These results are consistent with theories of top-down modulation and present a neural signature associated with the differences in perceiving The Dress as white/gold or blue/black. Furthermore the results support recent psychophysiological data on this phenomenon and provide a fundamental building block to study interindividual differences in visual processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Examination of the accuracy of coding hospital-acquired pressure ulcer stages.

PubMed

Coomer, Nicole M; McCall, Nancy T

2013-01-01

Pressure ulcers (PU) are considered harmful conditions that are reasonably prevented if accepted standards of care are followed. They became subject to the payment adjustment for hospitalacquired conditions (HACs) beginning October 1, 2008. We examined several aspects of the accuracy of coding for pressure ulcers under the Medicare Hospital-Acquired Condition Present on Admission (HAC-POA) Program. We used the "4010" claim format as a basis of reference to show some of the issues of the old format, such as the underreporting of pressure ulcer stages on pressure ulcer claims and how the underreporting varied by hospital characteristics. We then used the rate of Stage III and IV pressure ulcer HACs reported in the Hospital Cost and Utilization Project State Inpatient Databases data to look at the sensitivity of PU HAC-POA coding to the number of diagnosis fields. We examined Medicare claims data for FYs 2009 and 2010 to examine the degree that the presence of stage codes were underreported on pressure ulcer claims. We selected all claims with a secondary diagnosis code of pressure ulcer site (ICD-9 diagnosis codes 707.00-707.09) that were not reported as POA (POA of "N" or "U"). We then created a binary indicator for the presence of any pressure ulcer stage diagnosis code. We examine the percentage of claims with a diagnosis of a pressure ulcer site code with no accompanying pressure ulcer stage code. Our results point to underreporting of PU stages under the "4010" format and that the reporting of stage codes varied across hospital type and location. Further, our results indicate that under the "5010" format, a higher number of pressure ulcer HACs can be expected to be reported and we should expect to encounter a larger percentage of pressure ulcers incorrectly coded as POA under the new format. The combination of the capture of 25 diagnosis codes under the new "5010" format and the change from ICD-9 to ICD-10 will likely alleviate the observed underreporting of pressure ulcer HACs. However, as long as coding guidelines direct that Stage III and IV pressure ulcers be coded as POA, if a lower stage pressure ulcer was POA and progressed to a higher stage pressure ulcer during the admission, the acquisition of Stage III and IV pressure ulcers in the hospital will be underreported.

Hierarchical neurocomputations underlying concurrent sound segregation: connecting periphery to percept.

PubMed

Bidelman, Gavin M; Alain, Claude

2015-02-01

Natural soundscapes often contain multiple sound sources at any given time. Numerous studies have reported that in human observers, the perception and identification of concurrent sounds is paralleled by specific changes in cortical event-related potentials (ERPs). Although these studies provide a window into the cerebral mechanisms governing sound segregation, little is known about the subcortical neural architecture and hierarchy of neurocomputations that lead to this robust perceptual process. Using computational modeling, scalp-recorded brainstem/cortical ERPs, and human psychophysics, we demonstrate that a primary cue for sound segregation, i.e., harmonicity, is encoded at the auditory nerve level within tens of milliseconds after the onset of sound and is maintained, largely untransformed, in phase-locked activity of the rostral brainstem. As then indexed by auditory cortical responses, (in)harmonicity is coded in the signature and magnitude of the cortical object-related negativity (ORN) response (150-200 ms). The salience of the resulting percept is then captured in a discrete, categorical-like coding scheme by a late negativity response (N5; ~500 ms latency), just prior to the elicitation of a behavioral judgment. Subcortical activity correlated with cortical evoked responses such that weaker phase-locked brainstem responses (lower neural harmonicity) generated larger ORN amplitude, reflecting the cortical registration of multiple sound objects. Studying multiple brain indices simultaneously helps illuminate the mechanisms and time-course of neural processing underlying concurrent sound segregation and may lead to further development and refinement of physiologically driven models of auditory scene analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Error suppression via complementary gauge choices in Reed-Muller codes

NASA Astrophysics Data System (ADS)

Chamberland, Christopher; Jochym-O'Connor, Tomas

2017-09-01

Concatenation of two quantum error-correcting codes with complementary sets of transversal gates can provide a means toward universal fault-tolerant quantum computation. We first show that it is generally preferable to choose the inner code with the higher pseudo-threshold to achieve lower logical failure rates. We then explore the threshold properties of a wide range of concatenation schemes. Notably, we demonstrate that the concatenation of complementary sets of Reed-Muller codes can increase the code capacity threshold under depolarizing noise when compared to extensions of previously proposed concatenation models. We also analyze the properties of logical errors under circuit-level noise, showing that smaller codes perform better for all sampled physical error rates. Our work provides new insights into the performance of universal concatenated quantum codes for both code capacity and circuit-level noise.

Regulation of the Adrenal Cortex Function During Stress

NASA Technical Reports Server (NTRS)

Soliman, K. F. A.

1978-01-01

A proposal to study the function of the adrenal gland in the rat during stress is presented. In the proposed project, three different phases of experimentation will be undertaken. The first phase includes establishment of the circadian rhythm of both brain amines and glucocoticoids, under normal conditions and under chronic and acute stressful conditions. The second phase includes the study of the pharmacokinetics of glucocorticoid binding under normal and stress conditions. The third phase includes brain uptake and binding under different experimental conditions. In the outlined experiments brain biogenic amines will be evaluated, adrenal functions will be measured and stress effect on those parameters will be studied. It is hoped that this investigation can explain some of the complex relationships between the brain neurotransmitter and adrenal function.

Fatal anaphylaxis registries data support changes in the who anaphylaxis mortality coding rules.

PubMed

Tanno, Luciana Kase; Simons, F Estelle R; Annesi-Maesano, Isabella; Calderon, Moises A; Aymé, Ségolène; Demoly, Pascal

2017-01-13

Anaphylaxis is defined as a severe life-threatening generalized or systemic hypersensitivity reaction. The difficulty of coding anaphylaxis fatalities under the World Health Organization (WHO) International Classification of Diseases (ICD) system is recognized as an important reason for under-notification of anaphylaxis deaths. On current death certificates, a limited number of ICD codes are valid as underlying causes of death, and death certificates do not include the word anaphylaxis per se. In this review, we provide evidences supporting the need for changes in WHO mortality coding rules and call for addition of anaphylaxis as an underlying cause of death on international death certificates. This publication will be included in support of a formal request to the WHO as a formal request for this move taking the 11 th ICD revision.

Neuronal foundations of human numerical representations.

PubMed

Eger, E

2016-01-01

The human species has developed complex mathematical skills which likely emerge from a combination of multiple foundational abilities. One of them seems to be a preverbal capacity to extract and manipulate the numerosity of sets of objects which is shared with other species and in humans is thought to be integrated with symbolic knowledge to result in a more abstract representation of numerical concepts. For what concerns the functional neuroanatomy of this capacity, neuropsychology and functional imaging have localized key substrates of numerical processing in parietal and frontal cortex. However, traditional fMRI mapping relying on a simple subtraction approach to compare numerical and nonnumerical conditions is limited to tackle with sufficient precision and detail the issue of the underlying code for number, a question which more easily lends itself to investigation by methods with higher spatial resolution, such as neurophysiology. In recent years, progress has been made through the introduction of approaches sensitive to within-category discrimination in combination with fMRI (adaptation and multivariate pattern recognition), and the present review summarizes what these have revealed so far about the neural coding of individual numbers in the human brain, the format of these representations and parallels between human and monkey neurophysiology findings. © 2016 Elsevier B.V. All rights reserved.

Color categories are not universal: new evidence from traditional and western cultures

NASA Astrophysics Data System (ADS)

Roberson, Debi D.; Davidoff, Jules; Davies, Ian R. L.

2002-06-01

Evidence presented supports the linguistic relativity of color categories in three different paradigms. Firstly, a series of cross-cultural investigations, which had set out to replicate the seminal work of Rosch Heider with the Dani of New Guinea, failed to find evidence of a set of universal color categories. Instead, we found evidence of linguistic relativity in both populations tested. Neither participants from a Melanesian hunter-gatherer culture, nor those from an African pastoral tribe, whose languages both contain five color terms, showed a cognitive organization of color resembling that of English speakers. Further, Melanesian participants showed evidence of Categorical Perception, but only at their linguistic category boundaries. Secondly, in native English speakers verbal interference was found to selectively remove the defining features of Categorical Perception. Under verbal interference, the greater accuracy normally observed for cross-category judgements compared to within-category judgements disappeared. While both visual and verbal codes may be employed in the recognition memory of colors, participants only make use of verbal coding when demonstrating Categorical Perception. Thirdly, in a brain- damaged patient suffering from a naming disorder, the loss of labels radically impaired his ability to categorize colors. We conclude that language affects both the perception of and memory for colors.

Researcher Perceptions of Ethical Guidelines and Codes of Conduct

PubMed Central

Giorgini, Vincent; Mecca, Jensen T.; Gibson, Carter; Medeiros, Kelsey; Mumford, Michael D.; Connelly, Shane; Devenport, Lynn D.

2014-01-01

Ethical codes of conduct exist in almost every profession. Field-specific codes of conduct have been around for decades, each articulating specific ethical and professional guidelines. However, there has been little empirical research on researchers’ perceptions of these codes of conduct. In the present study, we interviewed faculty members in six research disciplines and identified five themes bearing on the circumstances under which they use ethical guidelines and the underlying reasons for not adhering to such guidelines. We then identify problems with the manner in which codes of conduct in academia are constructed and offer solutions for overcoming these problems. PMID:25635845

Silencing Effect of Hominoid Highly Conserved Noncoding Sequences on Embryonic Brain Development

PubMed Central

Mahmoudi Saber, Morteza

2017-01-01

Abstract Superfamily Hominoidea, which consists of Hominidae (humans and great apes) and Hylobatidae (gibbons), is well-known for sharing human-like characteristics, however, the genomic origins of these shared unique phenotypes have mainly remained elusive. To decipher the underlying genomic basis of Hominoidea-restricted phenotypes, we identified and characterized Hominoidea-restricted highly conserved noncoding sequences (HCNSs) that are a class of potential regulatory elements which may be involved in evolution of lineage-specific phenotypes. We discovered 679 such HCNSs from human, chimpanzee, gorilla, orangutan and gibbon genomes. These HCNSs were demonstrated to be under purifying selection but with lineage-restricted characteristics different from old CNSs. A significant proportion of their ancestral sequences had accelerated rates of nucleotide substitutions, insertions and deletions during the evolution of common ancestor of Hominoidea, suggesting the intervention of positive Darwinian selection for creating those HCNSs. In contrary to enhancer elements and similar to silencer sequences, these Hominoidea-restricted HCNSs are located in close proximity of transcription start sites. Their target genes are enriched in the nervous system, development and transcription, and they tend to be remotely located from the nearest coding gene. Chip-seq signals and gene expression patterns suggest that Hominoidea-restricted HCNSs are likely to be functional regulatory elements by imposing silencing effects on their target genes in a tissue-restricted manner during fetal brain development. These HCNSs, emerged through adaptive evolution and conserved through purifying selection, represent a set of promising targets for future functional studies of the evolution of Hominoidea-restricted phenotypes. PMID:28633494

Separate valuation subsystems for delay and effort decision costs.

PubMed

Prévost, Charlotte; Pessiglione, Mathias; Météreau, Elise; Cléry-Melin, Marie-Laure; Dreher, Jean-Claude

2010-10-20

Decision making consists of choosing among available options on the basis of a valuation of their potential costs and benefits. Most theoretical models of decision making in behavioral economics, psychology, and computer science propose that the desirability of outcomes expected from alternative options can be quantified by utility functions. These utility functions allow a decision maker to assign subjective values to each option under consideration by weighting the likely benefits and costs resulting from an action and to select the one with the highest subjective value. Here, we used model-based neuroimaging to test whether the human brain uses separate valuation systems for rewards (erotic stimuli) associated with different types of costs, namely, delay and effort. We show that humans devalue rewards associated with physical effort in a strikingly similar fashion to those they devalue that are associated with delays, and that a single computational model derived from economics theory can account for the behavior observed in both delay discounting and effort discounting. However, our neuroimaging data reveal that the human brain uses distinct valuation subsystems for different types of costs, reflecting in opposite fashion delayed reward and future energetic expenses. The ventral striatum and the ventromedial prefrontal cortex represent the increasing subjective value of delayed rewards, whereas a distinct network, composed of the anterior cingulate cortex and the anterior insula, represent the decreasing value of the effortful option, coding the expected expense of energy. Together, these data demonstrate that the valuation processes underlying different types of costs can be fractionated at the cerebral level.

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

PubMed Central

Mehler, Mark F.

2009-01-01

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

Peering at Brain Polysomes with Atomic Force Microscopy

PubMed Central

Lunelli, Lorenzo; Bernabò, Paola; Bolner, Alice; Vaghi, Valentina; Marchioretto, Marta; Viero, Gabriella

2016-01-01

The translational machinery, i.e., the polysome or polyribosome, is one of the biggest and most complex cytoplasmic machineries in cells. Polysomes, formed by ribosomes, mRNAs, several proteins and non-coding RNAs, represent integrated platforms where translational controls take place. However, while the ribosome has been widely studied, the organization of polysomes is still lacking comprehensive understanding. Thus much effort is required in order to elucidate polysome organization and any novel mechanism of translational control that may be embedded. Atomic force microscopy (AFM) is a type of scanning probe microscopy that allows the acquisition of 3D images at nanoscale resolution. Compared to electron microscopy (EM) techniques, one of the main advantages of AFM is that it can acquire thousands of images both in air and in solution, enabling the sample to be maintained under near physiological conditions without any need for staining and fixing procedures. Here, a detailed protocol for the accurate purification of polysomes from mouse brain and their deposition on mica substrates is described. This protocol enables polysome imaging in air and liquid with AFM and their reconstruction as three-dimensional objects. Complementary to cryo-electron microscopy (cryo-EM), the proposed method can be conveniently used for systematically analyzing polysomes and studying their organization. PMID:27023752

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex.

PubMed

Mejias, Jorge F; Murray, John D; Kennedy, Henry; Wang, Xiao-Jing

2016-11-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

PubMed Central

Mejias, Jorge F.; Murray, John D.; Kennedy, Henry; Wang, Xiao-Jing

2016-01-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions. PMID:28138530

The neural coding of creative idea generation across adolescence and early adulthood

PubMed Central

Kleibeuker, Sietske W.; Koolschijn, P. Cédric M. P.; Jolles, Dietsje D.; De Dreu, Carsten K. W.; Crone, Eveline A.

2013-01-01

Creativity is considered key to human prosperity, yet the neurocognitive principles underlying creative performance, and their development, are still poorly understood. To fill this void, we examined the neural correlates of divergent thinking in adults (25–30 years) and adolescents (15–17 years). Participants generated alternative uses (AU) or ordinary characteristics (OC) for common objects while brain activity was assessed using fMRI. Adults outperformed adolescents on the number of solutions for AU and OC trials. Contrasting neural activity for AU with OC trials revealed increased recruitment of left angular gyrus, left supramarginal gyrus, and bilateral middle temporal gyrus in both adults and adolescents. When only trials with multiple AU were included in the analysis, participants showed additional left inferior frontal gyrus (IFG)/middle frontal gyrus (MFG) activation for AU compared to OC trials. Correspondingly, individual difference analyses showed a positive correlation between activations for AU relative to OC trials in left IFG/MFG and divergent thinking performance and activations were more pronounced in adults than in adolescents. Taken together, the results of this study demonstrated that creative idea generation involves recruitment of mainly left lateralized parietal and temporal brain regions. Generating multiple creative ideas, a hallmark of divergent thinking, shows additional lateral PFC activation that is not yet optimized in adolescence. PMID:24416008

Design of Intelligent Cross-Layer Routing Protocols for Airborne Wireless Networks Under Dynamic Spectrum Access Paradigm

DTIC Science & Technology

2011-05-01

rate convolutional codes or the prioritized Rate - Compatible Punctured ...Quality of service RCPC Rate - compatible and punctured convolutional codes SNR Signal to noise ratio SSIM... Convolutional (RCPC) codes . The RCPC codes achieve UEP by puncturing off different amounts of coded bits of the parent code . The

Assessment of the impact of the change from manual to automated coding on mortality statistics in Australia.

PubMed

McKenzie, Kirsten; Walker, Sue; Tong, Shilu

It remains unclear whether the change from a manual to an automated coding system (ACS) for deaths has significantly affected the consistency of Australian mortality data. The underlying causes of 34,000 deaths registered in 1997 in Australia were dual coded, in ICD-9 manually, and by using an automated computer coding program. The diseases most affected by the change from manual to ACS were senile/presenile dementia, and pneumonia. The most common disease to which a manually assigned underlying cause of senile dementia was coded with ACS was unspecified psychoses (37.2%). Only 12.5% of codes assigned by ACS as senile dementia were coded the same by manual coders. This study indicates some important differences in mortality rates when comparing mortality data that have been coded manually with those coded using an automated computer coding program. These differences may be related to both the different interpretation of ICD coding rules between manual and automated coding, and different co-morbidities or co-existing conditions among demographic groups.

Visuospatial memory computations during whole-body rotations in roll.

PubMed

Van Pelt, S; Van Gisbergen, J A M; Medendorp, W P

2005-08-01

We used a memory-saccade task to test whether the location of a target, briefly presented before a whole-body rotation in roll, is stored in egocentric or in allocentric coordinates. To make this distinction, we exploited the fact that subjects, when tilted sideways in darkness, make systematic errors when indicating the direction of gravity (an allocentric task) even though they have a veridical percept of their self-orientation in space. We hypothesized that if spatial memory is coded allocentrically, these distortions affect the coding of remembered targets and their readout after a body rotation. Alternatively, if coding is egocentric, updating for body rotation becomes essential and errors in performance should be related to the amount of intervening rotation. Subjects (n = 6) were tested making saccades to remembered world-fixed targets after passive body tilts. Initial and final tilt angle ranged between -120 degrees CCW and 120 degrees CW. The results showed that subjects made large systematic directional errors in their saccades (up to 90 degrees ). These errors did not occur in the absence of intervening body rotation, ruling out a memory degradation effect. Regression analysis showed that the errors were closely related to the amount of subjective allocentric distortion at both the initial and final tilt angle, rather than to the amount of intervening rotation. We conclude that the brain uses an allocentric reference frame, possibly gravity-based, to code visuospatial memories during whole-body tilts. This supports the notion that the brain can define information in multiple frames of reference, depending on sensory inputs and task demands.

A new brain-computer interface design using fuzzy ARTMAP.

PubMed

Palaniappan, Ramaswamy; Paramesran, Raveendran; Nishida, Shogo; Saiwaki, Naoki

2002-09-01

This paper proposes a new brain-computer interface (BCI) design using fuzzy ARTMAP (FA) neural network, as well as an application of the design. The objective of this BCI-FA design is to classify the best three of the five available mental tasks for each subject using power spectral density (PSD) values of electroencephalogram (EEG) signals. These PSD values are extracted using the Wiener-Khinchine and autoregressive methods. Ten experiments employing different triplets of mental tasks are studied for each subject. The findings show that the average BCI-FA outputs for four subjects gave less than 6% of error using the best triplets of mental tasks identified from the classification performances of FA. This implies that the BCI-FA can be successfully used with a tri-state switching device. As an application, a proposed tri-state Morse code scheme could be utilized to translate the outputs of this BCI-FA design into English letters. In this scheme, the three BCI-FA outputs correspond to a dot and a dash, which are the two basic Morse code alphabets and a space to denote the end (or beginning) of a dot or a dash. The construction of English letters using this tri-state Morse code scheme is determined only by the sequence of mental tasks and is independent of the time duration of each mental task. This is especially useful for constructing letters that are represented as multiple dots or dashes. This combination of BCI-FA design and the tri-state Morse code scheme could be developed as a communication system for paralyzed patients.

An Investigation of the Dual Task Performance Relationship to Hemispheric Specialization.

DTIC Science & Technology

1980-06-01

described in Appendix A, were conducted to ensure descriminability of the stimuli from each other, and to ensure that none would be readily verbally coded...cerebral hemipsheres in descriminative reaction time to physiognomical and alphabetical material. Brain, 1971, 94, 431-442. Rollins, H. & Hendricks

Rare coding variants in Phospholipase D3 (PLD3) confer risk for Alzheimer's disease

PubMed Central

Cruchaga, Carlos; Benitez, Bruno A.; Cai, Yefei; Guerreiro, Rita; Harari, Oscar; Norton, Joanne; Budde, John; Bertelsen, Sarah; Jeng, Amanda T.; Cooper, Breanna; Skorupa, Tara; Carrell, David; Levitch, Denise; Hsu, Simon; Choi, Jiyoon; Ryten, Mina; Sassi, Celeste; Bras, Jose; Gibbs, Raphael J.; Hernandez, Dena G.; Lupton, Michelle K.; Powell, John; Forabosco, Paola; Ridge, Perry G.; Corcoran, Christopher D.; Tschanz, JoAnn T.; Norton, Maria C.; Munger, Ronald G.; Schmutz, Cameron; Leary, Maegan; Demirci, F. Yesim; Bamne, Mikhil N.; Wang, Xingbin; Lopez, Oscar L.; Ganguli, Mary; Medway, Christopher; Turton, James; Lord, Jenny; Braae, Anne; Barber, Imelda; Brown, Kristelle; Pastor, Pau; Lorenzo-Betancor, Oswaldo; Brkanac, Zoran; Scott, Erick; Topol, Eric; Morgan, Kevin; Rogaeva, Ekaterina; Singleton, Andy; Hardy, John; Kamboh, M. Ilyas; George-Hyslop, Peter St; Cairns, Nigel; Morris, John C.; Kauwe, John S.K.; Goate, Alison M.

2014-01-01

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1,2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low frequency coding variants with large effects on LOAD risk, we performed whole exome-sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large case-control datasets. A rare variant in PLD3 (phospholipase-D family, member 3, rs145999145; V232M) segregated with disease status in two independent families and doubled risk for AD in seven independent case-control series (V232M meta-analysis; OR= 2.10, CI=1.47-2.99; p= 2.93×10-5, 11,354 cases and controls of European-descent). Gene-based burden analyses in 4,387 cases and controls of European-descent and 302 African American cases and controls, with complete sequence data for PLD3, indicate that several variants in this gene increase risk for AD in both populations (EA: OR= 2.75, CI=2.05-3.68; p=1.44×10-11, AA: OR= 5.48, CI=1.77-16.92; p=1.40×10-3). PLD3 is highly expressed in brain regions vulnerable to AD pathology, including hippocampus and cortex, and is expressed at lower levels in neurons from AD brains compared to control brains (p=8.10×10-10). Over-expression of PLD3 leads to a significant decrease in intracellular APP and extracellular Aβ42 and Aβ40, while knock-down of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a two-fold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may be used to identify rare variants with large effects on risk for disease or other complex traits. PMID:24336208

Regulation of brain temperature in winter-acclimatized reindeer under heat stress.

PubMed

Blix, Arnoldus Schytte; Walløe, Lars; Folkow, Lars P

2011-11-15

Reindeer (Rangifer tarandus) are protected against the Arctic winter cold by thick fur of prime insulating capacity and hence have few avenues of heat loss during work. We have investigated how these animals regulate brain temperature under heavy heat loads. Animals were instrumented for measurements of blood flow, tissue temperatures and respiratory frequency (f) under full anaesthesia, whereas measurements were also made in fully conscious animals while in a climatic chamber or running on a treadmill. At rest, brain temperature (T(brain)) rose from 38.5±0.1°C at 10°C to 39.5±0.2°C at 50°C, while f increased from ×7 to ×250 breaths min(-1), with a change to open-mouth panting (OMP) at T(brain) 39.0±0.1°C, and carotid and sublingual arterial flows increased by 160% and 500%, respectively. OMP caused jugular venous and carotid arterial temperatures to drop, presumably owing to a much increased respiratory evaporative heat loss. Angular oculi vein (AOV) flow was negligible until T(brain) reached 38.9±0.1°C, but it increased to 0.81 ml min(-1) kg(-1) at T(brain) 39.2±0.2°C. Bilateral occlusion of both AOVs induced OMP and a rise in T(brain) and f at T(brain) >38.8°C. We propose that reindeer regulate body and, particularly, brain temperature under heavy heat loads by a combination of panting, at first through the nose, but later, when the heat load and the minute volume requirements increase due to exercise, primarily through the mouth and that they eventually resort to selective brain cooling.

Blood-brain barrier dysfunction in brain diseases: clinical experience.

PubMed

Schoknecht, Karl; Shalev, Hadar

2012-11-01

The blood-brain barrier, a unique feature of the cerebral vasculature, is gaining attention as a feature in common neurologic disorders including stroke, traumatic brain injury, epilepsy, and schizophrenia. Although acute blood-brain barrier dysfunction can induce cerebral edema, seizures, or neuropsychiatric symptoms, epileptogenesis and cognitive decline are among the chronic effects. The mechanisms underlying blood-brain barrier dysfunction are diverse and may range from physical endothelial damage in traumatic brain injury to degradation of extracellular matrix proteins via matrix metalloproteinases as part of an inflammatory response. Clinically, blood-brain barrier dysfunction is often detected using contrast-enhanced imaging. However, these techniques do not give any insights into the underlying mechanism. Elucidating the specific pathways of blood-brain barrier dysfunction at different time points and in different brain diseases using novel imaging techniques promises a more accurate blood-brain barrier terminology as well as new treatment options and personalized treatment. Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.

Brain Imaging and Behavioral Outcome in Traumatic Brain Injury.

ERIC Educational Resources Information Center

Bigler, Erin D.

1996-01-01

This review explores the cellular pathology associated with traumatic brain injury (TBI) and its relation to neurobehavioral outcomes, the relationship of brain imaging findings to underlying pathology, brain imaging techniques, various image analysis procedures and how they relate to neuropsychological testing, and the importance of brain imaging…

Fluorescein sodium-guided surgery of a brain abscess: A case report

PubMed Central

Höhne, Julius; Brawanski, Alexander; Schebesch, Karl-Michael

2016-01-01

Background: Up to now, the feasibility and benefit of using fluorescein sodium under a dedicated surgical microscope filter (YE560, YELLOW 560 nm filter, Carl Zeiss Meditec, Germany) has never been clinically evaluated in infectious disorders of the brain. Case Description: Here, we report the case of a male patient with a brain abscess in the right parietal lobe that was removed under fluorescence-guidance (intravenous administration of fluorescein sodium 10%, 5 mg/kg bodyweight). The abscess capsule showed intensive yellow fluorescent staining, while − under white light − the cortex appeared normal. Conclusion: This technique may improve the identification and surgical removal of brain abscesses. PMID:28031990

A family of hyperelastic models for human brain tissue

NASA Astrophysics Data System (ADS)

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.

Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.

2016-04-01

The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.

Are Registration of Disease Codes for Adult Anaphylaxis Accurate in the Emergency Department?

PubMed Central

Choi, Byungho; Lee, Hyeji

2018-01-01

Purpose There has been active research on anaphylaxis, but many study subjects are limited to patients registered with anaphylaxis codes. However, anaphylaxis codes tend to be underused. The aim of this study was to investigate the accuracy of anaphylaxis code registration and the clinical characteristics of accurate and inaccurate anaphylaxis registration in anaphylactic patients. Methods This retrospective study evaluated the medical records of adult patients who visited the university hospital emergency department between 2012 and 2016. The study subjects were divided into the groups with accurate and inaccurate anaphylaxis codes registered under anaphylaxis and other allergy-related codes and symptom-related codes, respectively. Results Among 211,486 patients, 618 (0.29%) had anaphylaxis. Of these, 161 and 457 were assigned to the accurate and inaccurate coding groups, respectively. The average age, transportation to the emergency department, past anaphylaxis history, cancer history, and the cause of anaphylaxis differed between the 2 groups. Cutaneous symptom manifested more frequently in the inaccurate coding group, while cardiovascular and neurologic symptoms were more frequently observed in the accurate group. Severe symptoms and non-alert consciousness were more common in the accurate group. Oxygen supply, intubation, and epinephrine were more commonly used as treatments for anaphylaxis in the accurate group. Anaphylactic patients with cardiovascular symptoms, severe symptoms, and epinephrine use were more likely to be accurately registered with anaphylaxis disease codes. Conclusions In case of anaphylaxis, more patients were registered inaccurately under other allergy-related codes and symptom-related codes rather than accurately under anaphylaxis disease codes. Cardiovascular symptoms, severe symptoms, and epinephrine treatment were factors associated with accurate registration with anaphylaxis disease codes in patients with anaphylaxis. PMID:29411554

CFD Code Development for Combustor Flows

NASA Technical Reports Server (NTRS)

Norris, Andrew

2003-01-01

During the lifetime of this grant, work has been performed in the areas of model development, code development, code validation and code application. For model development, this has included the PDF combustion module, chemical kinetics based on thermodynamics, neural network storage of chemical kinetics, ILDM chemical kinetics and assumed PDF work. Many of these models were then implemented in the code, and in addition many improvements were made to the code, including the addition of new chemistry integrators, property evaluation schemes, new chemistry models and turbulence-chemistry interaction methodology. Validation of all new models and code improvements were also performed, while application of the code to the ZCET program and also the NPSS GEW combustor program were also performed. Several important items remain under development, including the NOx post processing, assumed PDF model development and chemical kinetic development. It is expected that this work will continue under the new grant.

76 FR 22003 - Delegation of Functions and Authority Under Sections 315 and 325 of Title 32, United States Code

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-20

... Functions and Authority Under Sections 315 and 325 of Title 32, United States Code Memorandum for the... United States of America, including section 301 of title 3, United States Code, I hereby delegate to you: (a) the functions and authority of the President contained in section 315 of title 32, United States...

31 CFR 29.302 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

.... Code (1997) (under the Police and Firefighters Plan) or section 31-1231(a) of the D.C. Code (1997... accrue, that is, age 55 under the Police and Firefighters Plan and age 62 under the Teachers Plan... and Firefighters Plan or Teachers Plan. Department service or departmental service may include certain...

31 CFR 29.302 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

.... Code (1997) (under the Police and Firefighters Plan) or section 31-1231(a) of the D.C. Code (1997... accrue, that is, age 55 under the Police and Firefighters Plan and age 62 under the Teachers Plan... and Firefighters Plan or Teachers Plan. Department service or departmental service may include certain...

31 CFR 29.302 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

.... Code (1997) (under the Police and Firefighters Plan) or section 31-1231(a) of the D.C. Code (1997... accrue, that is, age 55 under the Police and Firefighters Plan and age 62 under the Teachers Plan... and Firefighters Plan or Teachers Plan. Department service or departmental service may include certain...

31 CFR 29.302 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

.... Code (1997) (under the Police and Firefighters Plan) or section 31-1231(a) of the D.C. Code (1997... accrue, that is, age 55 under the Police and Firefighters Plan and age 62 under the Teachers Plan... and Firefighters Plan or Teachers Plan. Department service or departmental service may include certain...

31 CFR 29.302 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... Code (1997) (under the Police and Firefighters Plan) or section 31-1231(a) of the D.C. Code (1997... accrue, that is, age 55 under the Police and Firefighters Plan and age 62 under the Teachers Plan. Department service or departmental service means any period of employment in a position covered by the Police...

Measuring Sparseness in the Brain: Comment on Bowers (2009)

ERIC Educational Resources Information Center

Quian Quiroga, Rodrigo; Kreiman, Gabriel

2010-01-01

Bowers challenged the common view in favor of distributed representations in psychological modeling and the main arguments given against localist and grandmother cell coding schemes. He revisited the results of several single-cell studies, arguing that they do not support distributed representations. We praise the contribution of Bowers (2009) for…

Visual Neuroscience: Unique Neural System for Flight Stabilization in Hummingbirds.

PubMed

Ibbotson, M R

2017-01-23

The pretectal visual motion processing area in the hummingbird brain is unlike that in other birds: instead of emphasizing detection of horizontal movements, it codes for motion in all directions through 360°, possibly offering precise visual stability control during hovering. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Technology Review 10: Emerging Technologies that Will Change the World.

ERIC Educational Resources Information Center

Technology Review, 2001

2001-01-01

Identifies 10 emerging areas of technology that will soon have a profound impact on the economy and on how people live and work: brain-machine interfaces; flexible transistors; data mining; digital rights management; biometrics; natural language processing; microphotonics; untangling code; robot design; and microfluidics. In each area, one…

Brain Systems for Assessing Facial Attractiveness

ERIC Educational Resources Information Center

Winston, Joel S.; O'Doherty, John; Kilner, James M.; Perrett, David I.; Dolan, Raymond J.

2007-01-01

Attractiveness is a facial attribute that shapes human affiliative behaviours. In a previous study we reported a linear response to facial attractiveness in orbitofrontal cortex (OFC), a region involved in reward processing. There are strong theoretical grounds for the hypothesis that coding stimulus reward value also involves the amygdala. The…

The Relationship between Simultaneous-Successive Processing and Academic Achievement.

ERIC Educational Resources Information Center

Merritt, Frank M.; McCallum, Steve

The Luria-Das Information Processing Model of human learning holds that information is analysed and coded within the brain in either a simultaneous or a successive fashion. Simultaneous integration refers to the synthesis of separate elements into groups, often with spatial characteristics; successive integration means that information is…

A new code for Galileo

NASA Technical Reports Server (NTRS)

Dolinar, S.

1988-01-01

Over the past six to eight years, an extensive research effort was conducted to investigate advanced coding techniques which promised to yield more coding gain than is available with current NASA standard codes. The delay in Galileo's launch due to the temporary suspension of the shuttle program provided the Galileo project with an opportunity to evaluate the possibility of including some version of the advanced codes as a mission enhancement option. A study was initiated last summer to determine if substantial coding gain was feasible for Galileo and, is so, to recommend a suitable experimental code for use as a switchable alternative to the current NASA-standard code. The Galileo experimental code study resulted in the selection of a code with constant length 15 and rate 1/4. The code parameters were chosen to optimize performance within cost and risk constraints consistent with retrofitting the new code into the existing Galileo system design and launch schedule. The particular code was recommended after a very limited search among good codes with the chosen parameters. It will theoretically yield about 1.5 dB enhancement under idealizing assumptions relative to the current NASA-standard code at Galileo's desired bit error rates. This ideal predicted gain includes enough cushion to meet the project's target of at least 1 dB enhancement under real, non-ideal conditions.

China Brain Project: Basic Neuroscience, Brain Diseases, and Brain-Inspired Computing.

PubMed

Poo, Mu-Ming; Du, Jiu-Lin; Ip, Nancy Y; Xiong, Zhi-Qi; Xu, Bo; Tan, Tieniu

2016-11-02

The China Brain Project covers both basic research on neural mechanisms underlying cognition and translational research for the diagnosis and intervention of brain diseases as well as for brain-inspired intelligence technology. We discuss some emerging themes, with emphasis on unique aspects. Copyright © 2016. Published by Elsevier Inc.

A Right Brain/Left Brain Model of Acting.

ERIC Educational Resources Information Center

Bowlen, Clark

Using current right brain/left brain research, this paper develops a model that explains acting's underlying quality--the actor is both himself and the character. Part 1 presents (1) the background of the right brain/left brain theory, (2) studies showing that propositional communication is a left hemisphere function while affective communication…

Effects of diabetes on brain metabolism--is brain glycogen a significant player?

PubMed

Sickmann, Helle M; Waagepetersen, Helle S

2015-02-01

Brain glycogen, being an intracellular glucose reservoir, contributes to maintain energy and neurotransmitter homeostasis under physiological as well as pathological conditions. Under conditions with a disturbance in systemic glucose metabolism such as in diabetes, the supply of glucose to the brain may be affected and have important impacts on brain metabolism and neurotransmission. This also implies that brain glycogen may serve an essential role in the diabetic state to sustain appropriate brain function. There are two main types of diabetes; type 1 and type 2 diabetes and both types may be associated with brain impairments e.g. cognitive decline and dementia. It is however, not clear how these impairments on brain function are linked to alterations in brain energy and neurotransmitter metabolism. In this review, we will illuminate how rodent diabetes models have contributed to a better understanding of how brain energy and neurotransmitter metabolism is affected in diabetes. There will be a particular focus on the role of brain glycogen to support glycolytic and TCA cycle activity as well as glutamate-glutamine cycle in type 1 and type 2 diabetes.

Pretest aerosol code comparisons for LWR aerosol containment tests LA1 and LA2

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

Wright, A.L.; Wilson, J.H.; Arwood, P.C.

The Light-Water-Reactor (LWR) Aerosol Containment Experiments (LACE) are being performed in Richland, Washington, at the Hanford Engineering Development Laboratory (HEDL) under the leadership of an international project board and the Electric Power Research Institute. These tests have two objectives: (1) to investigate, at large scale, the inherent aerosol retention behavior in LWR containments under simulated severe accident conditions, and (2) to provide an experimental data base for validating aerosol behavior and thermal-hydraulic computer codes. Aerosol computer-code comparison activities are being coordinated at the Oak Ridge National Laboratory. For each of the six LACE tests, ''pretest'' calculations (for code-to-code comparisons) andmore » ''posttest'' calculations (for code-to-test data comparisons) are being performed. The overall goals of the comparison effort are (1) to provide code users with experience in applying their codes to LWR accident-sequence conditions and (2) to evaluate and improve the code models.« less

The impact of medical tourism and the code of medical ethics on advertisement in Nigeria

PubMed Central

Makinde, Olusesan Ayodeji; Brown, Brandon; Olaleye, Olalekan

2014-01-01

Advances in management of clinical conditions are being made in several resource poor countries including Nigeria. Yet, the code of medical ethics which bars physician and health practices from advertising the kind of services they render deters these practices. This is worsened by the incursion of medical tourism facilitators (MTF) who continue to market healthcare services across countries over the internet and social media thereby raising ethical questions. A significant review of the advertisement ban in the code of ethics is long overdue. Limited knowledge about advances in medical practice among physicians and the populace, the growing medical tourism industry and its attendant effects, and the possibility of driving brain gain provide evidence to repeal the code. Ethical issues, resistance to change and elitist ideas are mitigating factors working in the opposite direction. The repeal of the code of medical ethics against advertising will undoubtedly favor health facilities in the country that currently cannot advertise the kind of services they render. A repeal or review of this code of medical ethics is necessary with properly laid down guidelines on how advertisements can be and cannot be done. PMID:25722776

The impact of medical tourism and the code of medical ethics on advertisement in Nigeria.

PubMed

Makinde, Olusesan Ayodeji; Brown, Brandon; Olaleye, Olalekan

2014-01-01

Advances in management of clinical conditions are being made in several resource poor countries including Nigeria. Yet, the code of medical ethics which bars physician and health practices from advertising the kind of services they render deters these practices. This is worsened by the incursion of medical tourism facilitators (MTF) who continue to market healthcare services across countries over the internet and social media thereby raising ethical questions. A significant review of the advertisement ban in the code of ethics is long overdue. Limited knowledge about advances in medical practice among physicians and the populace, the growing medical tourism industry and its attendant effects, and the possibility of driving brain gain provide evidence to repeal the code. Ethical issues, resistance to change and elitist ideas are mitigating factors working in the opposite direction. The repeal of the code of medical ethics against advertising will undoubtedly favor health facilities in the country that currently cannot advertise the kind of services they render. A repeal or review of this code of medical ethics is necessary with properly laid down guidelines on how advertisements can be and cannot be done.

Structure and expression of canary myc family genes.

PubMed Central

Collum, R G; Clayton, D F; Alt, F W

1991-01-01

We found that the canary N-myc gene is highly related to mammalian N-myc genes in both the protein-coding region and the long 3' untranslated region. Examined coding regions of the canary c-myc gene were also highly related to their mammalian counterparts, but in contrast to N-myc, the canary and mammalian c-myc genes were quite divergent in their 3' untranslated regions. We readily detected N-myc and c-myc expression in the adult canary brain and found N-myc expression both at sites of proliferating neuronal precursors and in mature neurons. Images PMID:1996121

Spatiotemporal Dissociation of Brain Activity Underlying Subjective Awareness, Objective Performance and Confidence

PubMed Central

Li, Qi; Hill, Zachary

2014-01-01

Despite intense recent research, the neural correlates of conscious visual perception remain elusive. The most established paradigm for studying brain mechanisms underlying conscious perception is to keep the physical sensory inputs constant and identify brain activities that correlate with the changing content of conscious awareness. However, such a contrast based on conscious content alone would not only reveal brain activities directly contributing to conscious perception, but also include brain activities that precede or follow it. To address this issue, we devised a paradigm whereby we collected, trial-by-trial, measures of objective performance, subjective awareness, and the confidence level of subjective awareness. Using magnetoencephalography recordings in healthy human volunteers, we dissociated brain activities underlying these different cognitive phenomena. Our results provide strong evidence that widely distributed slow cortical potentials (SCPs) correlate with subjective awareness, even after the effects of objective performance and confidence were both removed. The SCP correlate of conscious perception manifests strongly in its waveform, phase, and power. In contrast, objective performance and confidence were both contributed by relatively transient brain activity. These results shed new light on the brain mechanisms of conscious, unconscious, and metacognitive processing. PMID:24647958

Striking differences in glucose and lactate levels between brain extracellular fluid and plasma in conscious human subjects: effects of hyperglycemia and hypoglycemia.

PubMed

Abi-Saab, Walid M; Maggs, David G; Jones, Tim; Jacob, Ralph; Srihari, Vinod; Thompson, James; Kerr, David; Leone, Paola; Krystal, John H; Spencer, Dennis D; During, Matthew J; Sherwin, Robert S

2002-03-01

Brain levels of glucose and lactate in the extracellular fluid (ECF), which reflects the environment to which neurons are exposed, have never been studied in humans under conditions of varying glycemia. The authors used intracerebral microdialysis in conscious human subjects undergoing electrophysiologic evaluation for medically intractable epilepsy and measured ECF levels of glucose and lactate under basal conditions and during a hyperglycemia-hypoglycemia clamp study. Only measurements from nonepileptogenic areas were included. Under basal conditions, the authors found the metabolic milieu in the brain to be strikingly different from that in the circulation. In contrast to plasma, lactate levels in brain ECF were threefold higher than glucose. Results from complementary studies in rats were consistent with the human data. During the hyperglycemia-hypoglycemia clamp study the relationship between plasma and brain ECF levels of glucose remained similar, but changes in brain ECF glucose lagged approximately 30 minutes behind changes in plasma. The data demonstrate that the brain is exposed to substantially lower levels of glucose and higher levels of lactate than those in plasma; moreover, the brain appears to be a site of significant anaerobic glycolysis, raising the possibility that glucose-derived lactate is an important fuel for the brain.

Aging in the Brain: New Roles of Epigenetics in Cognitive Decline.

PubMed

Barter, Jolie D; Foster, Thomas C

2018-06-01

Gene expression in the aging brain depends on transcription signals generated by senescent physiology, interacting with genetic and epigenetic programs. In turn, environmental factors influence epigenetic mechanisms, such that an epigenetic-environmental link may contribute to the accumulation of cellular damage, susceptibility or resilience to stressors, and variability in the trajectory of age-related cognitive decline. Epigenetic mechanisms, DNA methylation and histone modifications, alter chromatin structure and the accessibility of DNA. Furthermore, small non-coding RNA, termed microRNA (miRNA) bind to messenger RNA (mRNA) to regulate translation. In this review, we examine key questions concerning epigenetic mechanisms in regulating the expression of genes associated with brain aging and age-related cognitive decline. In addition, we highlight the interaction of epigenetics with senescent physiology and environmental factors in regulating transcription.

Prototype of Kepler Processing Workflows For Microscopy And Neuroinformatics

PubMed Central

Astakhov, V.; Bandrowski, A.; Gupta, A.; Kulungowski, A.W.; Grethe, J.S.; Bouwer, J.; Molina, T.; Rowley, V.; Penticoff, S.; Terada, M.; Wong, W.; Hakozaki, H.; Kwon, O.; Martone, M.E.; Ellisman, M.

2016-01-01

We report on progress of employing the Kepler workflow engine to prototype “end-to-end” application integration workflows that concern data coming from microscopes deployed at the National Center for Microscopy Imaging Research (NCMIR). This system is built upon the mature code base of the Cell Centered Database (CCDB) and integrated rule-oriented data system (IRODS) for distributed storage. It provides integration with external projects such as the Whole Brain Catalog (WBC) and Neuroscience Information Framework (NIF), which benefit from NCMIR data. We also report on specific workflows which spawn from main workflows and perform data fusion and orchestration of Web services specific for the NIF project. This “Brain data flow” presents a user with categorized information about sources that have information on various brain regions. PMID:28479932

An In vitro evaluation of the reliability of QR code denture labeling technique.

PubMed

Poovannan, Sindhu; Jain, Ashish R; Krishnan, Cakku Jalliah Venkata; Chandran, Chitraa R

2016-01-01

Positive identification of the dead after accidents and disasters through labeled dentures plays a key role in forensic scenario. A number of denture labeling methods are available, and studies evaluating their reliability under drastic conditions are vital. This study was conducted to evaluate the reliability of QR (Quick Response) Code labeled at various depths in heat-cured acrylic blocks after acid treatment, heat treatment (burns), and fracture in forensics. It was an in vitro study. This study included 160 specimens of heat-cured acrylic blocks (1.8 cm × 1.8 cm) and these were divided into 4 groups (40 samples per group). QR Codes were incorporated in the samples using clear acrylic sheet and they were assessed for reliability under various depths, acid, heat, and fracture. Data were analyzed using Chi-square test, test of proportion. The QR Code inclusion technique was reliable under various depths of acrylic sheet, acid (sulfuric acid 99%, hydrochloric acid 40%) and heat (up to 370°C). Results were variable with fracture of QR Code labeled acrylic blocks. Within the limitations of the study, by analyzing the results, it was clearly indicated that the QR Code technique was reliable under various depths of acrylic sheet, acid, and heat (370°C). Effectiveness varied in fracture and depended on the level of distortion. This study thus suggests that QR Code is an effective and simpler denture labeling method.

On ways to overcome the magical capacity limit of working memory.

PubMed

Turi, Zsolt; Alekseichuk, Ivan; Paulus, Walter

2018-04-01

The ability to simultaneously process and maintain multiple pieces of information is limited. Over the past 50 years, observational methods have provided a large amount of insight regarding the neural mechanisms that underpin the mental capacity that we refer to as "working memory." More than 20 years ago, a neural coding scheme was proposed for working memory. As a result of technological developments, we can now not only observe but can also influence brain rhythms in humans. Building on these novel developments, we have begun to externally control brain oscillations in order to extend the limits of working memory.

Circular RNA: a new star in neurological diseases.

PubMed

Li, Tao-Ran; Jia, Yan-Jie; Wang, Qun; Shao, Xiao-Qiu; Lv, Rui-Juan

2017-08-01

Circular RNAs (circRNAs) are novel endogenous non-coding RNAs characterized by the presence of a covalent bond linking the 3' and 5' ends generated by backsplicing. In this review, we summarize a number of the latest theories regarding the biogenesis, properties and functions of circRNAs. Specifically, we focus on the advancing characteristics and functions of circRNAs in the brain and neurological diseases. CircRNAs exhibit the characteristics of species conservation, abundance and tissue/developmental-stage-specific expression in the brain. We also describe the relationship between circRNAs and several neurological diseases and highlight their functions in neurological diseases.

Finding numbers in the brain.

PubMed

Gallistel, C R

2017-02-19

After listing functional constraints on what numbers in the brain must do, I sketch the two's complement fixed-point representation of numbers because it has stood the test of time and because it illustrates the non-obvious ways in which an effective coding scheme may operate. I briefly consider its neurobiological implementation. It is easier to imagine its implementation at the cell-intrinsic molecular level, with thermodynamically stable, volumetrically minimal polynucleotides encoding the remembered numbers, than at the circuit level, with plastic synapses encoding them.This article is part of a discussion meeting issue 'The origins of numerical abilities'. © 2017 The Author(s).

Natural and Artificial Intelligence, Language, Consciousness, Emotion, and Anticipation

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2010-11-01

The classical paradigm of the neural brain as the seat of human natural intelligence is too restrictive. This paper defends the idea that the neural ectoderm is the actual brain, based on the development of the human embryo. Indeed, the neural ectoderm includes the neural crest, given by pigment cells in the skin and ganglia of the autonomic nervous system, and the neural tube, given by the brain, the spinal cord, and motor neurons. So the brain is completely integrated in the ectoderm, and cannot work alone. The paper presents fundamental properties of the brain as follows. Firstly, Paul D. MacLean proposed the triune human brain, which consists to three brains in one, following the species evolution, given by the reptilian complex, the limbic system, and the neo-cortex. Secondly, the consciousness and conscious awareness are analysed. Thirdly, the anticipatory unconscious free will and conscious free veto are described in agreement with the experiments of Benjamin Libet. Fourthly, the main section explains the development of the human embryo and shows that the neural ectoderm is the whole neural brain. Fifthly, a conjecture is proposed that the neural brain is completely programmed with scripts written in biological low-level and high-level languages, in a manner similar to the programmed cells by the genetic code. Finally, it is concluded that the proposition of the neural ectoderm as the whole neural brain is a breakthrough in the understanding of the natural intelligence, and also in the future design of robots with artificial intelligence.

Expression of the ADHD candidate gene Diras2 in the brain.

PubMed

Grünewald, Lena; Becker, Nils; Camphausen, Annika; O'Leary, Aet; Lesch, Klaus-Peter; Freudenberg, Florian; Reif, Andreas

2018-06-01

The distinct subgroup of the Ras family member 2 (DIRAS2) gene has been found to be associated with attention-deficit/hyperactivity disorder (ADHD) in one of our previous studies. This gene is coding for a small Ras GTPase with unknown function. DIRAS2 is highly expressed in the brain. However, the exact neural expression pattern of this gene was unknown so far. Therefore, we investigated the expressional profile of DIRAS2 in the human and murine brain. In the present study, qPCR analyses in the human and in the developing mouse brain, immunocytological double staining on murine hippocampal primary cells and RNA in situ hybridization (ISH) on brain sections of C57BL/6J wild-type mice, have been used to reveal the expression pattern of DIRAS2 in the brain. We could show that DIRAS2 expression in the human brain is the highest in the hippocampus and the cerebral cortex, which is in line with the ISH results in the mouse brain. During mouse brain development, Diras2 levels strongly increase from prenatal to late postnatal stages. Co-expression studies indicate Diras2 expression in glutamatergic and catecholaminergic neurons. Our findings support the idea of DIRAS2 as a candidate gene for ADHD as the timeline of its expression as well as the brain regions and cell types that show Diras2 expression correspond to those assumed to underlie the pathomechanisms of the disease.

Auto-Regulatory RNA Editing Fine-Tunes mRNA Re-Coding and Complex Behaviour in Drosophila

PubMed Central

Savva, Yiannis A.; Jepson, James E.C; Sahin, Asli; Sugden, Arthur U.; Dorsky, Jacquelyn S.; Alpert, Lauren; Lawrence, Charles; Reenan, Robert A.

2014-01-01

Auto-regulatory feedback loops are a common molecular strategy used to optimize protein function. In Drosophila many mRNAs involved in neuro-transmission are re-coded at the RNA level by the RNA editing enzyme dADAR, leading to the incorporation of amino acids that are not directly encoded by the genome. dADAR also re-codes its own transcript, but the consequences of this auto-regulation in vivo are unclear. Here we show that hard-wiring or abolishing endogenous dADAR auto-regulation dramatically remodels the landscape of re-coding events in a site-specific manner. These molecular phenotypes correlate with altered localization of dADAR within the nuclear compartment. Furthermore, auto-editing exhibits sexually dimorphic patterns of spatial regulation and can be modified by abiotic environmental factors. Finally, we demonstrate that modifying dAdar auto-editing affects adaptive complex behaviors. Our results reveal the in vivo relevance of auto-regulatory control over post-transcriptional mRNA re-coding events in fine-tuning brain function and organismal behavior. PMID:22531175

High compression image and image sequence coding

NASA Technical Reports Server (NTRS)

Kunt, Murat

1989-01-01

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Neural Tuning to Numerosity Relates to Perceptual Tuning in 3-6-Year-Old Children.

PubMed

Kersey, Alyssa J; Cantlon, Jessica F

2017-01-18

Neural representations of approximate numerical value, or numerosity, have been observed in the intraparietal sulcus (IPS) in monkeys and humans, including children. Using functional magnetic resonance imaging, we show that children as young as 3-4 years old exhibit neural tuning to cardinal numerosities in the IPS and that their neural responses are accounted for by a model of numerosity coding that has been used to explain neural responses in the adult IPS. We also found that the sensitivity of children's neural tuning to number in the right IPS was comparable to their numerical discrimination sensitivity observed behaviorally, outside of the scanner. Children's neural tuning curves in the right IPS were significantly sharper than in the left IPS, indicating that numerical representations are more precise and mature more rapidly in the right hemisphere than in the left. Further, we show that children's perceptual sensitivity to numerosity can be predicted by the development of their neural sensitivity to numerosity. This research provides novel evidence of developmental continuity in the neural code underlying numerical representation and demonstrates that children's neural sensitivity to numerosity is related to their cognitive development. Here we test for the existence of neural tuning to numerosity in the developing brain in the youngest sample of children tested with fMRI to date. Although previous research shows evidence of numerical distance effects in the intraparietal sulcus of the developing brain, those effects could be explained by patterns of neural activity that do not represent neural tuning to numerosity. These data provide the first robust evidence that from as early as 3-4 years of age there is developmental continuity in how the intraparietal sulcus represents the values of numerosities. Moreover, the study goes beyond previous research by examining the relation between neural tuning and perceptual tuning in children. Copyright © 2017 the authors 0270-6474/17/370512-11$15.00/0.

Probing the reaching-grasping network in humans through multivoxel pattern decoding.

PubMed

Di Bono, Maria Grazia; Begliomini, Chiara; Castiello, Umberto; Zorzi, Marco

2015-11-01

The quest for a putative human homolog of the reaching-grasping network identified in monkeys has been the focus of many neuropsychological and neuroimaging studies in recent years. These studies have shown that the network underlying reaching-only and reach-to-grasp movements includes the superior parieto-occipital cortex (SPOC), the anterior part of the human intraparietal sulcus (hAIP), the ventral and the dorsal portion of the premotor cortex, and the primary motor cortex (M1). Recent evidence for a wider frontoparietal network coding for different aspects of reaching-only and reach-to-grasp actions calls for a more fine-grained assessment of the reaching-grasping network in humans by exploiting pattern decoding methods (multivoxel pattern analysis--MVPA). Here, we used MPVA on functional magnetic resonance imaging (fMRI) data to assess whether regions of the frontoparietal network discriminate between reaching-only and reach-to-grasp actions, natural and constrained grasping, different grasp types, and object sizes. Participants were required to perform either reaching-only movements or two reach-to-grasp types (precision or whole hand grasp) upon spherical objects of different sizes. Multivoxel pattern analysis highlighted that, independently from the object size, all the selected regions of both hemispheres contribute in coding for grasp type, with the exception of SPOC and the right hAIP. Consistent with recent neurophysiological findings on monkeys, there was no evidence for a clear-cut distinction between a dorsomedial and a dorsolateral pathway that would be specialized for reaching-only and reach-to-grasp actions, respectively. Nevertheless, the comparison of decoding accuracy across brain areas highlighted their different contributions to reaching-only and grasping actions. Altogether, our findings enrich the current knowledge regarding the functional role of key brain areas involved in the cortical control of reaching-only and reach-to-grasp actions in humans, by revealing novel fine-grained distinctions among action types within a wide frontoparietal network.

Quantum error-correcting codes from algebraic geometry codes of Castle type

NASA Astrophysics Data System (ADS)

Munuera, Carlos; Tenório, Wanderson; Torres, Fernando

2016-10-01

We study algebraic geometry codes producing quantum error-correcting codes by the CSS construction. We pay particular attention to the family of Castle codes. We show that many of the examples known in the literature in fact belong to this family of codes. We systematize these constructions by showing the common theory that underlies all of them.

Synaptic E-I Balance Underlies Efficient Neural Coding.

PubMed

Zhou, Shanglin; Yu, Yuguo

2018-01-01

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.

Synaptic E-I Balance Underlies Efficient Neural Coding

PubMed Central

Zhou, Shanglin; Yu, Yuguo

2018-01-01

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding. PMID:29456491

Mapping of the serotonin 5-HT{sub 1D{alpha}} autoreceptor gene (HTR1D) on chromosome 1 using a silent polymorphism in the coding region

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

Ozaki, N.; Lappalainen, J.; Linnoila, M.

Serotonin (5-HT){sub ID} receptors are 5-HT release-regulating autoreceptors in the human brain. Abnormalities in brain 5-HT function have been hypothesized in the pathophysiology of various psychiatric disorders, including obsessive-compulsive disorder, autism, mood disorders, eating disorders, impulsive violent behavior, and alcoholism. Thus, mutations occurring in 5-HT autoreceptors may cause or increase the vulnerability to any of these conditions. 5-HT{sub 1D{alpha}} and 5-HT{sub 1D{Beta}} subtypes have been previously localized to chromosomes 1p36.3-p34.3 and 6q13, respectively, using rodent-human hybrids and in situ localization. In this communication, we report the detection of a 5-HT{sub 1D{alpha}} receptor gene polymorphism by single strand conformation polymorphism (SSCP)more » analysis of the coding sequence. The polymorphism was used for fine scale linkage mapping of 5-HT{sub 1D{alpha}} on chromosome 1. This polymorphism should also be useful for linkage studies in populations and in families. Our analysis also demonstrates that functionally significant coding sequence variants of the 5-HT{sub 1D{alpha}} are probably not abundant either among alcoholics or in the general population. 14 refs., 1 fig., 1 tab.« less

Isolation and characterization of full-length cDNA clones coding for cholinesterase from fetal human tissues

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

Prody, C.A.; Zevin-Sonkin, D.; Gnatt, A.

1987-06-01

To study the primary structure and regulation of human cholinesterases, oligodeoxynucleotide probes were prepared according to a consensus peptide sequence present in the active site of both human serum pseudocholinesterase and Torpedo electric organ true acetylcholinesterase. Using these probes, the authors isolated several cDNA clones from lambdagt10 libraries of fetal brain and liver origins. These include 2.4-kilobase cDNA clones that code for a polypeptide containing a putative signal peptide and the N-terminal, active site, and C-terminal peptides of human BtChoEase, suggesting that they code either for BtChoEase itself or for a very similar but distinct fetal form of cholinesterase. Inmore » RNA blots of poly(A)/sup +/ RNA from the cholinesterase-producing fetal brain and liver, these cDNAs hybridized with a single 2.5-kilobase band. Blot hybridization to human genomic DNA revealed that these fetal BtChoEase cDNA clones hybridize with DNA fragments of the total length of 17.5 kilobases, and signal intensities indicated that these sequences are not present in many copies. Both the cDNA-encoded protein and its nucleotide sequence display striking homology to parallel sequences published for Torpedo AcChoEase. These finding demonstrate extensive homologies between the fetal BtChoEase encoded by these clones and other cholinesterases of various forms and species.« less

Maternal transcription of non-protein coding RNAs from the PWS-critical region rescues growth retardation in mice.

PubMed

Rozhdestvensky, Timofey S; Robeck, Thomas; Galiveti, Chenna R; Raabe, Carsten A; Seeger, Birte; Wolters, Anna; Gubar, Leonid V; Brosius, Jürgen; Skryabin, Boris V

2016-02-05

Prader-Willi syndrome (PWS) is a neurogenetic disorder caused by loss of paternally expressed genes on chromosome 15q11-q13. The PWS-critical region (PWScr) contains an array of non-protein coding IPW-A exons hosting intronic SNORD116 snoRNA genes. Deletion of PWScr is associated with PWS in humans and growth retardation in mice exhibiting ~15% postnatal lethality in C57BL/6 background. Here we analysed a knock-in mouse containing a 5'HPRT-LoxP-Neo(R) cassette (5'LoxP) inserted upstream of the PWScr. When the insertion was inherited maternally in a paternal PWScr-deletion mouse model (PWScr(p-/m5'LoxP)), we observed compensation of growth retardation and postnatal lethality. Genomic methylation pattern and expression of protein-coding genes remained unaltered at the PWS-locus of PWScr(p-/m5'LoxP) mice. Interestingly, ubiquitous Snord116 and IPW-A exon transcription from the originally silent maternal chromosome was detected. In situ hybridization indicated that PWScr(p-/m5'LoxP) mice expressed Snord116 in brain areas similar to wild type animals. Our results suggest that the lack of PWScr RNA expression in certain brain areas could be a primary cause of the growth retardation phenotype in mice. We propose that activation of disease-associated genes on imprinted regions could lead to general therapeutic strategies in associated diseases.

Holding a manual response sequence in memory can disrupt vocal responses that share semantic features with the manual response.

PubMed

Fournier, Lisa Renee; Wiediger, Matthew D; McMeans, Ryan; Mattson, Paul S; Kirkwood, Joy; Herzog, Theibot

2010-07-01

Holding an action plan in memory for later execution can delay execution of another action if the actions share a similar (compatible) feature. This compatibility interference (CI) occurs for actions that share the same response modality (e.g., manual response). We investigated whether CI can generalize to actions that utilize different response modalities (manual and vocal). In three experiments, participants planned and withheld a sequence of key-presses with the left- or right-hand based on the visual identity of the first stimulus, and then immediately executed a speeded, vocal response ('left' or 'right') to a second visual stimulus. The vocal response was based on discriminating stimulus color (Experiment 1), reading a written word (Experiment 2), or reporting the antonym of a written word (Experiment 3). Results showed that CI occurred when the manual response hand (e.g., left) was compatible with the identity of the vocal response (e.g., 'left') in Experiment 1 and 3, but not in Experiment 2. This suggests that partial overlap of semantic codes is sufficient to obtain CI unless the intervening action can be accessed automatically (Experiment 2). These findings are consistent with the code occupation hypothesis and the general framework of the theory of event coding (Behav Brain Sci 24:849-878, 2001a; Behav Brain Sci 24:910-937, 2001b).

Source space analysis of event-related dynamic reorganization of brain networks.

PubMed

Ioannides, Andreas A; Dimitriadis, Stavros I; Saridis, George A; Voultsidou, Marotesa; Poghosyan, Vahe; Liu, Lichan; Laskaris, Nikolaos A

2012-01-01

How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

Brain regions that retain the spatial layout of tactile stimuli during working memory - A 'tactospatial sketchpad'?

PubMed

Schmidt, Timo Torsten; Blankenburg, Felix

2018-05-31

Working memory (WM) studies have been essential for ascertaining how the brain flexibly handles mentally represented information in the absence of sensory stimulation. Most studies on the memory of sensory stimulus features have focused, however, on the visual domain. Here, we report a human WM study in the tactile modality where participants had to memorize the spatial layout of patterned Braille-like stimuli presented to the index finger. We used a whole-brain searchlight approach in combination with multi-voxel pattern analysis (MVPA) to investigate tactile WM representations without a priori assumptions about which brain regions code tactospatial information. Our analysis revealed that posterior and parietal cortices, as well as premotor regions, retained information across the twelve-second delay phase. Interestingly, parts of this brain network were previously shown to also contain information of visuospatial WM. Also, by specifically testing somatosensory regions for WM representations, we observed content-specific activation patterns in primary somatosensory cortex (SI). Our findings demonstrate that tactile WM depends on a distributed network of brain regions in analogy to the representation of visuospatial information. Copyright © 2018. Published by Elsevier Inc.

Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering.

PubMed

Yang, Guang; Raschke, Felix; Barrick, Thomas R; Howe, Franklyn A

2015-09-01

To investigate whether nonlinear dimensionality reduction improves unsupervised classification of (1) H MRS brain tumor data compared with a linear method. In vivo single-voxel (1) H magnetic resonance spectroscopy (55 patients) and (1) H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With (1) H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of (1) H MRSI data after cluster analysis. © 2014 Wiley Periodicals, Inc.

17A, a novel non-coding RNA, regulates GABA B alternative splicing and signaling in response to inflammatory stimuli and in Alzheimer disease.

PubMed

Massone, Sara; Vassallo, Irene; Fiorino, Gloria; Castelnuovo, Manuele; Barbieri, Federica; Borghi, Roberta; Tabaton, Massimo; Robello, Mauro; Gatta, Elena; Russo, Claudio; Florio, Tullio; Dieci, Giorgio; Cancedda, Ranieri; Pagano, Aldo

2011-02-01

Alternative splicing is a central component of human brain complexity; nonetheless, its regulatory mechanisms are still largely unclear. In this work, we describe a novel non-coding (nc) RNA (named 17A) RNA polymerase (pol) III-dependent embedded in the human G-protein-coupled receptor 51 gene (GPR51, GABA B2 receptor). The stable expression of 17A in SHSY5Y neuroblastoma cells induces the synthesis of an alternative splicing isoform that abolish GABA B2 intracellular signaling (i.e., inhibition of cAMP accumulation and activation of K(+) channels). Indeed, 17A is expressed in human brain, and we report that it is upregulated in cerebral tissues derived from Alzheimer disease patients. We demonstrate that 17A expression in neuroblastoma cells enhances the secretion of amyloid β peptide (Aβ) and the Aβ x-42/Αβ x-40 peptide ratio and that its synthesis is induced in response to inflammatory stimuli. These data correlate, for the first time, the activity of a novel pol III-dependent ncRNA to alternative splicing events and, possibly, to neurodegeneration induced by abnormal GABA B function. We anticipate that further analysis of pol III-dependent regulation of alternative splicing will disclose novel regulatory pathways associated to brain physiology and/or pathology. Copyright © 2010 Elsevier Inc. All rights reserved.

Olfactory modulation by dopamine in the context of aversive learning

PubMed Central

Riffell, Jeffrey A.; Martin, Joshua P.; Gage, Stephanie L.; Nighorn, Alan J.

2012-01-01

The need to detect and process sensory cues varies in different behavioral contexts. Plasticity in sensory coding can be achieved by the context-specific release of neuromodulators in restricted brain areas. The context of aversion triggers the release of dopamine in the insect brain, yet the effects of dopamine on sensory coding are unknown. In this study, we characterize the morphology of dopaminergic neurons that innervate each of the antennal lobes (ALs; the first synaptic neuropils of the olfactory system) of the moth Manduca sexta and demonstrate with electrophysiology that dopamine enhances odor-evoked responses of the majority of AL neurons while reducing the responses of a small minority. Because dopamine release in higher brain areas mediates aversive learning we developed a naturalistic, ecologically inspired aversive learning paradigm in which an innately appetitive host plant floral odor is paired with a mimic of the aversive nectar of herbivorized host plants. This pairing resulted in a decrease in feeding behavior that was blocked when dopamine receptor antagonists were injected directly into the ALs. These results suggest that a transient dopaminergic enhancement of sensory output from the AL contributes to the formation of aversive memories. We propose a model of olfactory modulation in which specific contexts trigger the release of different neuromodulators in the AL to increase olfactory output to downstream areas of processing. PMID:22552185

Semantic graphs and associative memories

NASA Astrophysics Data System (ADS)

Pomi, Andrés; Mizraji, Eduardo

2004-12-01

Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.

Brain Injury Association of America

MedlinePlus

... Only) 1-800-444-6443 Welcome to the Brain Injury Association of America (BIAA) Brain injury is not an event or an outcome. ... misunderstood, under-funded neurological disease. People who sustain brain injuries must have timely access to expert trauma ...

Leadership Class Configuration Interaction Code - Status and Opportunities

NASA Astrophysics Data System (ADS)

Vary, James

2011-10-01

With support from SciDAC-UNEDF (www.unedf.org) nuclear theorists have developed and are continuously improving a Leadership Class Configuration Interaction Code (LCCI) for forefront nuclear structure calculations. The aim of this project is to make state-of-the-art nuclear structure tools available to the entire community of researchers including graduate students. The project includes codes such as NuShellX, MFDn and BIGSTICK that run a range of computers from laptops to leadership class supercomputers. Codes, scripts, test cases and documentation have been assembled, are under continuous development and are scheduled for release to the entire research community in November 2011. A covering script that accesses the appropriate code and supporting files is under development. In addition, a Data Base Management System (DBMS) that records key information from large production runs and archived results of those runs has been developed (http://nuclear.physics.iastate.edu/info/) and will be released. Following an outline of the project, the code structure, capabilities, the DBMS and current efforts, I will suggest a path forward that would benefit greatly from a significant partnership between researchers who use the codes, code developers and the National Nuclear Data efforts. This research is supported in part by DOE under grant DE-FG02-87ER40371 and grant DE-FC02-09ER41582 (SciDAC-UNEDF).

75 FR 17854 - Travel Expenses of State Legislators

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-08

... election under section 162(h) of the Internal Revenue Code (Code). The regulations clarify the amount of... a taxpayer may make or revoke an election under section 162(h). The collection of information is... during the taxable year may make an election under section 162(h) to treat the taxpayer's place of...

Representations of Pitch and Timbre Variation in Human Auditory Cortex

PubMed Central

2017-01-01

Pitch and timbre are two primary dimensions of auditory perception, but how they are represented in the human brain remains a matter of contention. Some animal studies of auditory cortical processing have suggested modular processing, with different brain regions preferentially coding for pitch or timbre, whereas other studies have suggested a distributed code for different attributes across the same population of neurons. This study tested whether variations in pitch and timbre elicit activity in distinct regions of the human temporal lobes. Listeners were presented with sequences of sounds that varied in either fundamental frequency (eliciting changes in pitch) or spectral centroid (eliciting changes in brightness, an important attribute of timbre), with the degree of pitch or timbre variation in each sequence parametrically manipulated. The BOLD responses from auditory cortex increased with increasing sequence variance along each perceptual dimension. The spatial extent, region, and laterality of the cortical regions most responsive to variations in pitch or timbre at the univariate level of analysis were largely overlapping. However, patterns of activation in response to pitch or timbre variations were discriminable in most subjects at an individual level using multivoxel pattern analysis, suggesting a distributed coding of the two dimensions bilaterally in human auditory cortex. SIGNIFICANCE STATEMENT Pitch and timbre are two crucial aspects of auditory perception. Pitch governs our perception of musical melodies and harmonies, and conveys both prosodic and (in tone languages) lexical information in speech. Brightness—an aspect of timbre or sound quality—allows us to distinguish different musical instruments and speech sounds. Frequency-mapping studies have revealed tonotopic organization in primary auditory cortex, but the use of pure tones or noise bands has precluded the possibility of dissociating pitch from brightness. Our results suggest a distributed code, with no clear anatomical distinctions between auditory cortical regions responsive to changes in either pitch or timbre, but also reveal a population code that can differentiate between changes in either dimension within the same cortical regions. PMID:28025255

Quantitative analysis of brain magnetic resonance imaging for hepatic encephalopathy

NASA Astrophysics Data System (ADS)

Syh, Hon-Wei; Chu, Wei-Kom; Ong, Chin-Sing

1992-06-01

High intensity lesions around ventricles have recently been observed in T1-weighted brain magnetic resonance images for patients suffering hepatic encephalopathy. The exact etiology that causes magnetic resonance imaging (MRI) gray scale changes has not been totally understood. The objective of our study was to investigate, through quantitative means, (1) the amount of changes to brain white matter due to the disease process, and (2) the extent and distribution of these high intensity lesions, since it is believed that the abnormality may not be entirely limited to the white matter only. Eleven patients with proven haptic encephalopathy and three normal persons without any evidence of liver abnormality constituted our current data base. Trans-axial, sagittal, and coronal brain MRI were obtained on a 1.5 Tesla scanner. All processing was carried out on a microcomputer-based image analysis system in an off-line manner. Histograms were decomposed into regular brain tissues and lesions. Gray scale ranges coded as lesion were then brought back to original images to identify distribution of abnormality. Our results indicated the disease process involved pallidus, mesencephalon, and subthalamic regions.

Linking Brain Arteriovenous Malformations With Anorectal Hemorrhoids: A Clinical and Anatomical Review

PubMed Central

Cuoco, Joshua A.; Hoehmann, Christopher L.; Hitscherich, Kyle; Zakhary, Sherry M.; Leheste, Joerg R.

2017-01-01

ABSTRACT Patients who harbor brain arteriovenous malformations are at risk for intracranial hemorrhage. These malformations are often seen in inherited vascular diseases such as hereditary hemorrhagic telangiectasia. However, malformations within the brain also sporadically occur without a hereditary‐coding component. Here, we review recent insights into the pathophysiology of arteriovenous malformations, in particular, certain signaling pathways that might underlie endothelial cell pathology. To better interpret the origins, determinants and consequences of brain arteriovenous malformations, we present a clinical case to illustrate the phenotypic landscape of the disease. We also propose that brain arteriovenous malformations might share certain signaling dimensions with those of anorectal hemorrhoids. This working hypothesis provides casual anchors from which to understand vascular diseases characterized by arteriovenous lesions with a hemorrhagic‐ or bleeding‐risk component. Anat Rec, 2017. © The Authors. The Anatomical Record published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists. Anat Rec, 300:1973–1980, 2017. © 2017 The Authors. The Anatomical Record published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists. PMID:28696502

What is special about the adolescent (JME) brain?

PubMed

Craiu, Dana

2013-07-01

Juvenile myoclonic epilepsy (JME) involves cortico-thalamo-cortical networks. Thalamic, frontal gray matter, connectivity, and neurotransmitter disturbances have been demonstrated by structural/functional imaging studies. Few patients with JME show mutations in genes coding ion channels or GABAA (gamma-aminobutyric acid) receptor subunits. Recent research points to EFHC1 gene mutations leading to microdysgenesis and possible aberrant circuitry. Imaging studies have shown massive structural/functional changes of normally developing adolescent brain structures maturing at strikingly different rates and times. Gray matter (GM) volume diminishes in cortical areas (frontal and parietal) and deep structures (anterior thalamus, putamen, and caudate). Diffusion tensor imaging (DTI) findings support continued microstructural change in WM (white matter) during late adolescence with robust developmental changes in thalamocortical connectivity. The GABAA receptor distribution and specific receptor subunits' expression patterns change with age from neonate to adolescent/adult, contributing to age-related changes in brain excitability. Hormonal influence on brain structure development during adolescence is presented. Possible implications of brain changes during adolescence on the course of JME are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Mindboggling morphometry of human brains

PubMed Central

Bao, Forrest S.; Giard, Joachim; Stavsky, Eliezer; Lee, Noah; Rossa, Brian; Reuter, Martin; Chaibub Neto, Elias

2017-01-01

Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle’s algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available. PMID:28231282

Evidence-Based Practice for the Use of Internal Strategies as a Memory Compensation Technique After Brain Injury: A Systematic Review.

PubMed

OʼNeil-Pirozzi, Therese M; Kennedy, Mary R T; Sohlberg, McKay M

2016-01-01

To complete a systematic review of internal memory strategy use with people who have brain injury and provide practitioners with information that will impact their clinical work. A systematic literature search to identify published intervention studies that evaluated an internal memory strategy or technique to improve memory function of individuals with brain injury. Relevant data from reviewed articles were coded using 4 clinical questions targeting participants, interventions, research methods, and outcomes. A comprehensive search identified 130 study citations and abstracts. Forty-six met inclusion/exclusion criteria and were systematically reviewed. Visual imagery was most frequently studied, in isolation or in combination with other internal strategies. Despite significant variability in research methods and outcomes across studies, the evidence provides impetus for use of internal memory strategies with individuals following brain injury. Individuals with traumatic brain injury may benefit from internal memory strategy use, and clinicians should consider internal memory strategy instruction as part of intervention plans. Further research needs to better delineate influences on intervention candidacy and outcomes.

Reliability of cause of death coding: an international comparison.

PubMed

Antini, Carmen; Rajs, Danuta; Muñoz-Quezada, María Teresa; Mondaca, Boris Andrés Lucero; Heiss, Gerardo

2015-07-01

This study evaluates the agreement of nosologic coding of cardiovascular causes of death between a Chilean coder and one in the United States, in a stratified random sample of death certificates of persons aged ≥ 60, issued in 2008 in the Valparaíso and Metropolitan regions, Chile. All causes of death were converted to ICD-10 codes in parallel by both coders. Concordance was analyzed with inter-coder agreement and Cohen's kappa coefficient by level of specification ICD-10 code for the underlying cause and the total causes of death coding. Inter-coder agreement was 76.4% for all causes of death and 80.6% for the underlying cause (agreement at the four-digit level), with differences by the level of specification of the ICD-10 code, by line of the death certificate, and by number of causes of death per certificate. Cohen's kappa coefficient was 0.76 (95%CI: 0.68-0.84) for the underlying cause and 0.75 (95%CI: 0.74-0.77) for the total causes of death. In conclusion, causes of death coding and inter-coder agreement for cardiovascular diseases in two regions of Chile are comparable to an external benchmark and with reports from other countries.

Exome sequencing and arrayCGH detection of gene sequence and copy number variation between ILS and ISS mouse strains.

PubMed

Dumas, Laura; Dickens, C Michael; Anderson, Nathan; Davis, Jonathan; Bennett, Beth; Radcliffe, Richard A; Sikela, James M

2014-06-01

It has been well documented that genetic factors can influence predisposition to develop alcoholism. While the underlying genomic changes may be of several types, two of the most common and disease associated are copy number variations (CNVs) and sequence alterations of protein coding regions. The goal of this study was to identify CNVs and single-nucleotide polymorphisms that occur in gene coding regions that may play a role in influencing the risk of an individual developing alcoholism. Toward this end, two mouse strains were used that have been selectively bred based on their differential sensitivity to alcohol: the Inbred long sleep (ILS) and Inbred short sleep (ISS) mouse strains. Differences in initial response to alcohol have been linked to risk for alcoholism, and the ILS/ISS strains are used to investigate the genetics of initial sensitivity to alcohol. Array comparative genomic hybridization (arrayCGH) and exome sequencing were conducted to identify CNVs and gene coding sequence differences, respectively, between ILS and ISS mice. Mouse arrayCGH was performed using catalog Agilent 1 × 244 k mouse arrays. Subsequently, exome sequencing was carried out using an Illumina HiSeq 2000 instrument. ArrayCGH detected 74 CNVs that were strain-specific (38 ILS/36 ISS), including several ISS-specific deletions that contained genes implicated in brain function and neurotransmitter release. Among several interesting coding variations detected by exome sequencing was the gain of a premature stop codon in the alpha-amylase 2B (AMY2B) gene specifically in the ILS strain. In total, exome sequencing detected 2,597 and 1,768 strain-specific exonic gene variants in the ILS and ISS mice, respectively. This study represents the most comprehensive and detailed genomic comparison of ILS and ISS mouse strains to date. The two complementary genome-wide approaches identified strain-specific CNVs and gene coding sequence variations that should provide strong candidates to contribute to the alcohol-related phenotypic differences associated with these strains.

The hidden side of drug action: Brain temperature changes induced by neuroactive drugs

PubMed Central

Kiyatkin, Eugene A.

2013-01-01

Rationale Most neuroactive drugs affect brain metabolism as well as systemic and cerebral blood flow, thus altering brain temperature. Although this aspect of drug action usually remains in the shadows, drug-induced alterations in brain temperature reflect their metabolic neural effects and affect neural activity and neural functions. Objectives Here, I review brain temperature changes induced by neuroactive drugs, which are used therapeutically (general anesthetics), as a research tool (dopamine agonists and antagonists), and self-administered to induce desired psychic effects (cocaine, methamphetamine, ecstasy). I consider the mechanisms underlying these temperature fluctuations and their influence on neural, physiological, and behavioral effects of these drugs. Results By interacting with neural mechanisms regulating metabolic activity and heat exchange between the brain and the rest of the body, neuroactive drugs either increase or decrease brain temperatures both within (35-39°C) and exceeding the range of physiological fluctuations. These temperature effects differ drastically depending upon the environmental conditions and activity state during drug administration. This state-dependence is especially important for drugs of abuse that are usually taken by humans during psycho-physiological activation and in environments that prevent proper heat dissipation from the brain. Under these conditions, amphetamine-like stimulants induce pathological brain hyperthermia (>40°C) associated with leakage of the blood-brain barrier and structural abnormalities of brain cells. Conclusions The knowledge on brain temperature fluctuations induced by neuroactive drugs provides new information to understand how they influence metabolic neural activity, why their effects depend upon the behavioral context of administration, and the mechanisms underlying adverse drug effects including neurotoxicity PMID:23274506

Multichannel activity propagation across an engineered axon network

NASA Astrophysics Data System (ADS)

Chen, H. Isaac; Wolf, John A.; Smith, Douglas H.

2017-04-01

Objective. Although substantial progress has been made in mapping the connections of the brain, less is known about how this organization translates into brain function. In particular, the massive interconnectivity of the brain has made it difficult to specifically examine data transmission between two nodes of the connectome, a central component of the ‘neural code.’ Here, we investigated the propagation of multiple streams of asynchronous neuronal activity across an isolated in vitro ‘connectome unit.’ Approach. We used the novel technique of axon stretch growth to create a model of a long-range cortico-cortical network, a modular system consisting of paired nodes of cortical neurons connected by axon tracts. Using optical stimulation and multi-electrode array recording techniques, we explored how input patterns are represented by cortical networks, how these representations shift as they are transmitted between cortical nodes and perturbed by external conditions, and how well the downstream node distinguishes different patterns. Main results. Stimulus representations included direct, synaptic, and multiplexed responses that grew in complexity as the distance between the stimulation source and recorded neuron increased. These representations collapsed into patterns with lower information content at higher stimulation frequencies. With internodal activity propagation, a hierarchy of network pathways, including latent circuits, was revealed using glutamatergic blockade. As stimulus channels were added, divergent, non-linear effects were observed in local versus distant network layers. Pairwise difference analysis of neuronal responses suggested that neuronal ensembles generally outperformed individual cells in discriminating input patterns. Significance. Our data illuminate the complexity of spiking activity propagation in cortical networks in vitro, which is characterized by the transformation of an input into myriad outputs over several network layers. These results provide insight into how the brain potentially processes information and generates the neural code and could guide the development of clinical therapies based on multichannel brain stimulation.

Self-government of complex reading and writing brains informed by cingulo-opercular network for adaptive control and working memory components for language learning.

PubMed

Richards, Todd L; Abbott, Robert D; Yagle, Kevin; Peterson, Dan; Raskind, Wendy; Berninger, Virginia W

2017-01-01

To understand mental self-government of the developing reading and writing brain, correlations of clustering coefficients on fMRI reading or writing tasks with BASC 2 Adaptivity ratings (time 1 only) or working memory components (time 1 before and time 2 after instruction previously shown to improve achievement and change magnitude of fMRI connectivity) were investigated in 39 students in grades 4 to 9 who varied along a continuum of reading and writing skills. A Philips 3T scanner measured connectivity during six leveled fMRI reading tasks (subword-letters and sounds, word-word-specific spellings or affixed words, syntax comprehension-with and without homonym foils or with and without affix foils, and text comprehension) and three fMRI writing tasks-writing next letter in alphabet, adding missing letter in word spelling, and planning for composing. The Brain Connectivity Toolbox generated clustering coefficients based on the cingulo-opercular (CO) network; after controlling for multiple comparisons and movement, significant fMRI connectivity clustering coefficients for CO were identified in 8 brain regions bilaterally (cingulate gyrus, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, superior temporal gyrus, insula, cingulum-cingulate gyrus, and cingulum-hippocampus). BASC2 Parent Ratings for Adaptivity were correlated with CO clustering coefficients on three reading tasks (letter-sound, word affix judgments and sentence comprehension) and one writing task (writing next letter in alphabet). Before instruction, each behavioral working memory measure (phonology, orthography, morphology, and syntax coding, phonological and orthographic loops for integrating internal language and output codes, and supervisory focused and switching attention) correlated significantly with at least one CO clustering coefficient. After instruction, the patterning of correlations changed with new correlations emerging. Results show that the reading and writing brain's mental government, supported by both CO Adaptive Control and multiple working memory components, had changed in response to instruction during middle childhood/early adolescence.

Evidence of a Conserved Molecular Response to Selection for Increased Brain Size in Primates

PubMed Central

Harrison, Peter W.; Caravas, Jason A.; Raghanti, Mary Ann; Phillips, Kimberley A.; Mundy, Nicholas I.

2017-01-01

The adaptive significance of human brain evolution has been frequently studied through comparisons with other primates. However, the evolution of increased brain size is not restricted to the human lineage but is a general characteristic of primate evolution. Whether or not these independent episodes of increased brain size share a common genetic basis is unclear. We sequenced and de novo assembled the transcriptome from the neocortical tissue of the most highly encephalized nonhuman primate, the tufted capuchin monkey (Cebus apella). Using this novel data set, we conducted a genome-wide analysis of orthologous brain-expressed protein coding genes to identify evidence of conserved gene–phenotype associations and species-specific adaptations during three independent episodes of brain size increase. We identify a greater number of genes associated with either total brain mass or relative brain size across these six species than show species-specific accelerated rates of evolution in individual large-brained lineages. We test the robustness of these associations in an expanded data set of 13 species, through permutation tests and by analyzing how genome-wide patterns of substitution co-vary with brain size. Many of the genes targeted by selection during brain expansion have glutamatergic functions or roles in cell cycle dynamics. We also identify accelerated evolution in a number of individual capuchin genes whose human orthologs are associated with human neuropsychiatric disorders. These findings demonstrate the value of phenotypically informed genome analyses, and suggest at least some aspects of human brain evolution have occurred through conserved gene–phenotype associations. Understanding these commonalities is essential for distinguishing human-specific selection events from general trends in brain evolution. PMID:28391320

Mechanical characterization of human brain tissue.

PubMed

Budday, S; Sommer, G; Birkl, C; Langkammer, C; Haybaeck, J; Kohnert, J; Bauer, M; Paulsen, F; Steinmann, P; Kuhl, E; Holzapfel, G A

2017-01-15

Mechanics are increasingly recognized to play an important role in modulating brain form and function. Computational simulations are a powerful tool to predict the mechanical behavior of the human brain in health and disease. The success of these simulations depends critically on the underlying constitutive model and on the reliable identification of its material parameters. Thus, there is an urgent need to thoroughly characterize the mechanical behavior of brain tissue and to identify mathematical models that capture the tissue response under arbitrary loading conditions. However, most constitutive models have only been calibrated for a single loading mode. Here, we perform a sequence of multiple loading modes on the same human brain specimen - simple shear in two orthogonal directions, compression, and tension - and characterize the loading-mode specific regional and directional behavior. We complement these three individual tests by combined multiaxial compression/tension-shear tests and discuss effects of conditioning and hysteresis. To explore to which extent the macrostructural response is a result of the underlying microstructural architecture, we supplement our biomechanical tests with diffusion tensor imaging and histology. We show that the heterogeneous microstructure leads to a regional but not directional dependence of the mechanical properties. Our experiments confirm that human brain tissue is nonlinear and viscoelastic, with a pronounced compression-tension asymmetry. Using our measurements, we compare the performance of five common constitutive models, neo-Hookean, Mooney-Rivlin, Demiray, Gent, and Ogden, and show that only the isotropic modified one-term Ogden model is capable of representing the hyperelastic behavior under combined shear, compression, and tension loadings: with a shear modulus of 0.4-1.4kPa and a negative nonlinearity parameter it captures the compression-tension asymmetry and the increase in shear stress under superimposed compression but not tension. Our results demonstrate that material parameters identified for a single loading mode fail to predict the response under arbitrary loading conditions. Our systematic characterization of human brain tissue will lead to more accurate computational simulations, which will allow us to determine criteria for injury, to develop smart protection systems, and to predict brain development and disease progression. There is a pressing need to characterize the mechanical behavior of human brain tissue under multiple loading conditions, and to identify constitutive models that are able to capture the tissue response under these conditions. We perform a sequence of experimental tests on the same brain specimen to characterize the regional and directional behavior, and we supplement our tests with DTI and histology to explore to which extent the macrostructural response is a result of the underlying microstructure. Results demonstrate that human brain tissue is nonlinear and viscoelastic, with a pronounced compression-tension asymmetry, and we show that the multiaxial data can best be captured by a modified version of the one-term Ogden model. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Goddard Visiting Scientist Program

NASA Technical Reports Server (NTRS)

2000-01-01

Under this Indefinite Delivery Indefinite Quantity (IDIQ) contract, USRA was expected to provide short term (from I day up to I year) personnel as required to provide a Visiting Scientists Program to support the Earth Sciences Directorate (Code 900) at the Goddard Space Flight Center. The Contractor was to have a pool, or have access to a pool, of scientific talent, both domestic and international, at all levels (graduate student to senior scientist), that would support the technical requirements of the following laboratories and divisions within Code 900: 1) Global Change Data Center (902); 2) Laboratory for Atmospheres (Code 910); 3) Laboratory for Terrestrial Physics (Code 920); 4) Space Data and Computing Division (Code 930); 5) Laboratory for Hydrospheric Processes (Code 970). The research activities described below for each organization within Code 900 were intended to comprise the general scope of effort covered under the Visiting Scientist Program.

Is a Genome a Codeword of an Error-Correcting Code?

PubMed Central

Kleinschmidt, João H.; Silva-Filho, Márcio C.; Bim, Edson; Herai, Roberto H.; Yamagishi, Michel E. B.; Palazzo, Reginaldo

2012-01-01

Since a genome is a discrete sequence, the elements of which belong to a set of four letters, the question as to whether or not there is an error-correcting code underlying DNA sequences is unavoidable. The most common approach to answering this question is to propose a methodology to verify the existence of such a code. However, none of the methodologies proposed so far, although quite clever, has achieved that goal. In a recent work, we showed that DNA sequences can be identified as codewords in a class of cyclic error-correcting codes known as Hamming codes. In this paper, we show that a complete intron-exon gene, and even a plasmid genome, can be identified as a Hamming code codeword as well. Although this does not constitute a definitive proof that there is an error-correcting code underlying DNA sequences, it is the first evidence in this direction. PMID:22649495

Targeting caspase-3 as dual therapeutic benefits by RNAi facilitating brain-targeted nanoparticles in a rat model of Parkinson's disease.

PubMed

Liu, Yang; Guo, Yubo; An, Sai; Kuang, Yuyang; He, Xi; Ma, Haojun; Li, Jianfeng; Lu, Jing; Lv, Jing; Zhang, Ning; Jiang, Chen

2013-01-01

The activation of caspase-3 is an important hallmark in Parkinson's disease. It could induce neuron death by apoptosis and microglia activation by inflammation. As a result, inhibition the activation of caspase-3 would exert synergistic dual effect in brain in order to prevent the progress of Parkinson's disease. Silencing caspase-3 genes by RNA interference could inhibit the activation of caspase-3. We developed a brain-targeted gene delivery system based on non-viral gene vector, dendrigraft poly-L-lysines. A rabies virus glycoprotein peptide with 29 amino-acid linked to dendrigraft poly-L-lysines could render gene vectors the ability to get across the blood brain barrier by specific receptor mediated transcytosis. The resultant brain-targeted vector was complexed with caspase-3 short hairpin RNA coding plasmid DNA, yielding nanoparticles. In vivo imaging analysis indicated the targeted nanoparticles could accumulate in brain more efficiently than non-targeted ones. A multiple dosing regimen by weekly intravenous administration of the nanoparticles could reduce activated casapse-3 levels, significantly improve locomotor activity and rescue dopaminergic neuronal loss and in Parkinson's disease rats' brain. These results indicated the rabies virus glycoprotein peptide modified brain-targeted nanoparticles were promising gene delivery system for RNA interference to achieve anti-apoptotic and anti-inflammation synergistic therapeutic effects by down-regulation the expression and activation of caspase-3.

The Deceptively Simple N170 Reflects Network Information Processing Mechanisms Involving Visual Feature Coding and Transfer Across Hemispheres

PubMed Central

Ince, Robin A. A.; Jaworska, Katarzyna; Gross, Joachim; Panzeri, Stefano; van Rijsbergen, Nicola J.; Rousselet, Guillaume A.; Schyns, Philippe G.

2016-01-01

A key to understanding visual cognition is to determine “where”, “when”, and “how” brain responses reflect the processing of the specific visual features that modulate categorization behavior—the “what”. The N170 is the earliest Event-Related Potential (ERP) that preferentially responds to faces. Here, we demonstrate that a paradigmatic shift is necessary to interpret the N170 as the product of an information processing network that dynamically codes and transfers face features across hemispheres, rather than as a local stimulus-driven event. Reverse-correlation methods coupled with information-theoretic analyses revealed that visibility of the eyes influences face detection behavior. The N170 initially reflects coding of the behaviorally relevant eye contralateral to the sensor, followed by a causal communication of the other eye from the other hemisphere. These findings demonstrate that the deceptively simple N170 ERP hides a complex network information processing mechanism involving initial coding and subsequent cross-hemispheric transfer of visual features. PMID:27550865

An Eye-Tracking Study of How Color Coding Affects Multimedia Learning

ERIC Educational Resources Information Center

Ozcelik, Erol; Karakus, Turkan; Kursun, Engin; Cagiltay, Kursat

2009-01-01

Color coding has been proposed to promote more effective learning. However, insufficient evidence currently exists to show how color coding leads to better learning. The goal of this study was to investigate the underlying cause of the color coding effect by utilizing eye movement data. Fifty-two participants studied either a color-coded or…

DUF1220 copy number is linearly associated with increased cognitive function as measured by total IQ and mathematical aptitude scores

PubMed Central

Davis, Jonathon M.; Searles, Veronica B.; Anderson, Nathan; Keeney, Jonathon; Raznahan, Armin; Horwood, L. John; Fergusson, David M.; Kennedy, Martin A.; Giedd, Jay

2014-01-01

DUF1220 protein domains exhibit the greatest human lineage-specific copy number expansion of any protein-coding sequence in the genome, and variation in DUF1220 copy number has been linked to both brain size in humans and brain evolution among primates. Given these findings, we examined associations between DUF1220 subtypes CON1 and CON2 and cognitive aptitude. We identified a linear association between CON2 copy number and cognitive function in two independent populations of European descent. In North American males, an increase in CON2 copy number corresponded with an increase in WISC IQ (R2 = 0.13, p = 0.02), which may be driven by males aged 6–11 (R2 = 0.42, p = 0.003). We utilized ddPCR in a subset as a confirmatory measurement. This group had 26–33 copies of CON2 with a mean of 29, and each copy increase of CON2 was associated with a 3.3-point increase in WISC IQ (R2 = 0.22, p = 0.045). In individuals from New Zealand, an increase in CON2 copy number was associated with an increase in math aptitude ability (R2 = 0.10 p = 0.018). These were not confounded by brain size. To our knowledge, this is the first study to report a replicated association between copy number of a gene coding sequence and cognitive aptitude. Remarkably, dosage variations involving DUF1220 sequences have now been linked to human brain expansion, autism severity and cognitive aptitude, suggesting that such processes may be genetically and mechanistically inter-related. The findings presented here warrant expanded investigations in larger, well-characterized cohorts. PMID:25287832

From perceptual to lexico‐semantic analysis—cortical plasticity enabling new levels of processing

PubMed Central

Schlaffke, Lara; Rüther, Naima N.; Heba, Stefanie; Haag, Lauren M.; Schultz, Thomas; Rosengarth, Katharina; Tegenthoff, Martin; Bellebaum, Christian

2015-01-01

Abstract Certain kinds of stimuli can be processed on multiple levels. While the neural correlates of different levels of processing (LOPs) have been investigated to some extent, most of the studies involve skills and/or knowledge already present when performing the task. In this study we specifically sought to identify neural correlates of an evolving skill that allows the transition from perceptual to a lexico‐semantic stimulus analysis. Eighteen participants were trained to decode 12 letters of Morse code that were presented acoustically inside and outside of the scanner environment. Morse code was presented in trains of three letters while brain activity was assessed with fMRI. Participants either attended to the stimulus length (perceptual analysis), or evaluated its meaning distinguishing words from nonwords (lexico‐semantic analysis). Perceptual and lexico‐semantic analyses shared a mutual network comprising the left premotor cortex, the supplementary motor area (SMA) and the inferior parietal lobule (IPL). Perceptual analysis was associated with a strong brain activation in the SMA and the superior temporal gyrus bilaterally (STG), which remained unaltered from pre and post training. In the lexico‐semantic analysis post learning, study participants showed additional activation in the left inferior frontal cortex (IFC) and in the left occipitotemporal cortex (OTC), regions known to be critically involved in lexical processing. Our data provide evidence for cortical plasticity evolving with a learning process enabling the transition from perceptual to lexico‐semantic stimulus analysis. Importantly, the activation pattern remains task‐related LOP and is thus the result of a decision process as to which LOP to engage in. Hum Brain Mapp 36:4512–4528, 2015. © 2015 The Authors. Human Brain Mapping Published byWiley Periodicals, Inc. PMID:26304153

Overcoming Dyslexia in Children, Adolescents, and Adults. Third Edition.

ERIC Educational Resources Information Center

Jordan, Dale R.

This book aims to interpret recent research on dyslexia into practical information for those who work with individuals with dyslexia. Chapter 1 summarizes new information about how genetic codes determine brian development and how differences in brain structure cause dyslexia. Chapter 2 explains the perceptual and emotional nature of dyslexia.…

Predictive Coding Explains Binocular Rivalry: An Epistemological Review

ERIC Educational Resources Information Center

Hohwy, Jakob; Roepstorff, Andreas; Friston, Karl

2008-01-01

Binocular rivalry occurs when the eyes are presented with different stimuli and subjective perception alternates between them. Though recent years have seen a number of models of this phenomenon, the mechanisms behind binocular rivalry are still debated and we still lack a principled understanding of why a cognitive system such as the brain should…

Brain-to-brain coupling during handholding is associated with pain reduction.

PubMed

Goldstein, Pavel; Weissman-Fogel, Irit; Dumas, Guillaume; Shamay-Tsoory, Simone G

2018-03-13

The mechanisms underlying analgesia related to social touch are not clear. While recent research highlights the role of the empathy of the observer to pain relief in the target, the contribution of social interaction to analgesia is unknown. The current study examines brain-to-brain coupling during pain with interpersonal touch and tests the involvement of interbrain synchrony in pain alleviation. Romantic partners were assigned the roles of target (pain receiver) and observer (pain observer) under pain-no-pain and touch-no-touch conditions concurrent with EEG recording. Brain-to-brain coupling in alpha-mu band (8-12 Hz) was estimated by a three-step multilevel analysis procedure based on running window circular correlation coefficient and post hoc power of the findings was calculated using simulations. Our findings indicate that hand-holding during pain administration increases brain-to-brain coupling in a network that mainly involves the central regions of the pain target and the right hemisphere of the pain observer. Moreover, brain-to-brain coupling in this network was found to correlate with analgesia magnitude and observer's empathic accuracy. These findings indicate that brain-to-brain coupling may be involved in touch-related analgesia.

Coding “What” and “When” in the Archer Fish Retina

PubMed Central

Vasserman, Genadiy; Shamir, Maoz; Ben Simon, Avi; Segev, Ronen

2010-01-01

Traditionally, the information content of the neural response is quantified using statistics of the responses relative to stimulus onset time with the assumption that the brain uses onset time to infer stimulus identity. However, stimulus onset time must also be estimated by the brain, making the utility of such an approach questionable. How can stimulus onset be estimated from the neural responses with sufficient accuracy to ensure reliable stimulus identification? We address this question using the framework of colour coding by the archer fish retinal ganglion cell. We found that stimulus identity, “what”, can be estimated from the responses of best single cells with an accuracy comparable to that of the animal's psychophysical estimation. However, to extract this information, an accurate estimation of stimulus onset is essential. We show that stimulus onset time, “when”, can be estimated using a linear-nonlinear readout mechanism that requires the response of a population of 100 cells. Thus, stimulus onset time can be estimated using a relatively simple readout. However, large nerve cell populations are required to achieve sufficient accuracy. PMID:21079682

High OCT4A levels drive tumorigenicity and metastatic potential of medulloblastoma cells

PubMed Central

Gonçalves da Silva, Patrícia Benites; Teixeira dos Santos, Márcia Cristina; Rodini, Carolina Oliveira; Kaid, Carolini; Leite Pereira, Márcia Cristina; Furukawa, Gabriela; Gimenes da Cruz, Daniel Sanzio; Goldfeder, Mauricio Barbugiani; Reily Rocha, Clarissa Ribeiro; Rosenberg, Carla; Okamoto, Oswaldo Keith

2017-01-01

Medulloblastoma is a highly aggressive pediatric brain tumor, in which sporadic expression of the pluripotency factor OCT4 has been recently correlated with poor patient survival. However the contribution of specific OCT4 isoforms to tumor aggressiveness is still poorly understood. Here, we report that medulloblastoma cells stably overexpressing the OCT4A isoform displayed enhanced clonogenic, tumorsphere generation, and invasion capabilities. Moreover, in an orthotopic metastatic model of medulloblastoma, OCT4A overexpressing cells generated more developed, aggressive and infiltrative tumors, with tumor-bearing mice attaining advanced metastatic disease and shorter survival rates. Pro-oncogenic OCT4A effects were expression-level dependent and accompanied by distinct chromosomal aberrations. OCT4A overexpression in medulloblastoma cells also induced a marked differential expression of non-coding RNAs, including poorly characterized long non-coding RNAs and small nucleolar RNAs. Altogether, our findings support the relevance of pluripotency-related factors in the aggravation of medulloblastoma traits classically associated with poor clinical outcome, and underscore the prognostic and therapeutic value of OCT4A in this challenging type of pediatric brain cancer. PMID:28186969

High OCT4A levels drive tumorigenicity and metastatic potential of medulloblastoma cells.

PubMed

da Silva, Patrícia Benites Gonçalves; Teixeira Dos Santos, Márcia Cristina; Rodini, Carolina Oliveira; Kaid, Carolini; Pereira, Márcia Cristina Leite; Furukawa, Gabriela; da Cruz, Daniel Sanzio Gimenes; Goldfeder, Mauricio Barbugiani; Rocha, Clarissa Ribeiro Reily; Rosenberg, Carla; Okamoto, Oswaldo Keith

2017-03-21

Medulloblastoma is a highly aggressive pediatric brain tumor, in which sporadic expression of the pluripotency factor OCT4 has been recently correlated with poor patient survival. However the contribution of specific OCT4 isoforms to tumor aggressiveness is still poorly understood. Here, we report that medulloblastoma cells stably overexpressing the OCT4A isoform displayed enhanced clonogenic, tumorsphere generation, and invasion capabilities. Moreover, in an orthotopic metastatic model of medulloblastoma, OCT4A overexpressing cells generated more developed, aggressive and infiltrative tumors, with tumor-bearing mice attaining advanced metastatic disease and shorter survival rates. Pro-oncogenic OCT4A effects were expression-level dependent and accompanied by distinct chromosomal aberrations. OCT4A overexpression in medulloblastoma cells also induced a marked differential expression of non-coding RNAs, including poorly characterized long non-coding RNAs and small nucleolar RNAs. Altogether, our findings support the relevance of pluripotency-related factors in the aggravation of medulloblastoma traits classically associated with poor clinical outcome, and underscore the prognostic and therapeutic value of OCT4A in this challenging type of pediatric brain cancer.

Monte Carlo calculation for the development of a BNCT neutron source (1eV-10KeV) using MCNP code.

PubMed

El Moussaoui, F; El Bardouni, T; Azahra, M; Kamili, A; Boukhal, H

2008-09-01

Different materials have been studied in order to produce the epithermal neutron beam between 1eV and 10KeV, which are extensively used to irradiate patients with brain tumors such as GBM. For this purpose, we have studied three different neutrons moderators (H(2)O, D(2)O and BeO) and their combinations, four reflectors (Al(2)O(3), C, Bi, and Pb) and two filters (Cd and Bi). Results of calculation showed that the best obtained assembly configuration corresponds to the combination of the three moderators H(2)O, BeO and D(2)O jointly to Al(2)O(3) reflector and two filter Cd+Bi optimize the spectrum of the epithermal neutron at 72%, and minimize the thermal neutron to 4% and thus it can be used to treat the deep tumor brain. The calculations have been performed by means of the Monte Carlo N (particle code MCNP 5C). Our results strongly encourage further studying of irradiation of the head with epithermal neutron fields.

Satb2 determines miRNA expression and long-term memory in the adult central nervous system.

PubMed

Jaitner, Clemens; Reddy, Chethan; Abentung, Andreas; Whittle, Nigel; Rieder, Dietmar; Delekate, Andrea; Korte, Martin; Jain, Gaurav; Fischer, Andre; Sananbenesi, Farahnaz; Cera, Isabella; Singewald, Nicolas; Dechant, Georg; Apostolova, Galina

2016-11-29

SATB2 is a risk locus for schizophrenia and encodes a DNA-binding protein that regulates higher-order chromatin configuration. In the adult brain Satb2 is almost exclusively expressed in pyramidal neurons of two brain regions important for memory formation, the cerebral cortex and the CA1-hippocampal field. Here we show that Satb2 is required for key hippocampal functions since deletion of Satb2 from the adult mouse forebrain prevents the stabilization of synaptic long-term potentiation and markedly impairs long-term fear and object discrimination memory. At the molecular level, we find that synaptic activity and BDNF up-regulate Satb2, which itself binds to the promoters of coding and non-coding genes. Satb2 controls the hippocampal levels of a large cohort of miRNAs, many of which are implicated in synaptic plasticity and memory formation. Together, our findings demonstrate that Satb2 is critically involved in long-term plasticity processes in the adult forebrain that underlie the consolidation and stabilization of context-linked memory.

Effect of a thymol application on olfactory memory and gene expression levels in the brain of the honeybee Apis mellifera.

PubMed

Bonnafé, Elsa; Drouard, Florian; Hotier, Lucie; Carayon, Jean-Luc; Marty, Pierre; Treilhou, Michel; Armengaud, Catherine

2015-06-01

Essential oils are used by beekeepers to control the Varroa mites that infest honeybee colonies. So, bees can be exposed to thymol formulations in the hive. The effects of the monoterpenoid thymol were explored on olfactory memory and gene expression in the brain of the honeybee. In bees previously exposed to thymol (10 or 100 ng/bee), the specificity of the response to the conditioned stimulus (CS) was lost 24 h after learning. Besides, the octopamine receptor OA1 gene Amoa1 showed a significant decrease of expression 3 h after exposure with 10 or 100 ng/bee of thymol. With the same doses, expression of Rdl gene, coding for a GABA receptor subunit, was not significantly modified but the trpl gene was upregulated 1 and 24 h after exposure to thymol. These data indicated that the genes coding for the cellular targets of thymol could be rapidly regulated after exposure to this molecule. Memory and sensory processes should be investigated in bees after chronic exposure in the hive to thymol-based preparations.