Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 23
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
J Med Internet Res ; 23(9): e27098, 2021 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-34491204

RESUMO

BACKGROUND: Hemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device-integrated algorithm to assist medical staff in response to these adverse events a step earlier during HD. OBJECTIVE: We aimed to develop machine learning algorithms to predict intradialytic adverse events in an unbiased manner. METHODS: Three-month dialysis and physiological time-series data were collected from all patients who underwent maintenance HD therapy at a tertiary care referral center. Dialysis data were collected automatically by HD devices, and physiological data were recorded by medical staff. Intradialytic adverse events were documented by medical staff according to patient complaints. Features extracted from the time series data sets by linear and differential analyses were used for machine learning to predict adverse events during HD. RESULTS: Time series dialysis data were collected during the 4-hour HD session in 108 patients who underwent maintenance HD therapy. There were a total of 4221 HD sessions, 406 of which involved at least one intradialytic adverse event. Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) of 0.83, sensitivity of 0.53, and specificity of 0.96. The algorithm also predicted muscle cramps, with an AUC of 0.85, and blood pressure elevation, with an AUC of 0.93. In addition, the model built based on ultrafiltration-unrelated features predicted all types of adverse events, with an AUC of 0.81, indicating that ultrafiltration-unrelated factors also contribute to the onset of adverse events. CONCLUSIONS: Our results demonstrated that algorithms combining linear and differential analyses with two-class classification machine learning can predict intradialytic adverse events in quasi-real time with high AUCs. Such a methodology implemented with local cloud computation and real-time optimization by personalized HD data could warn clinicians to take timely actions in advance.

2.
eNeuro ; 8(5)2021.
Artigo em Inglês | MEDLINE | ID: mdl-34385152

RESUMO

Spatial orientation memory plays a crucial role in animal navigation. Recent studies of tethered Drosophila melanogaster (fruit fly) in a virtual reality setting showed that the head direction is encoded in the form of an activity bump, i.e., localized neural activity, in the torus-shaped ellipsoid body (EB). However, how this system is involved in orientation working memory is not well understood. We investigated this question using free moving flies (D. melanogaster) in a spatial orientation memory task by manipulating two EB subsystems, C and P circuits, which are hypothesized for stabilizing and updating the activity bump, respectively. To this end, we suppressed or activated two types of inhibitory ring neurons (EIP and P) which innervate EB, and we discovered that manipulating the two inhibitory neuron types produced distinct behavioral deficits, suggesting specific roles of the inhibitory neurons in coordinating the stabilization and updating functions of the EB circuits. We further elucidate the neural mechanisms underlying such control circuits using a connectome-constrained spiking neural network model.

3.
Neuroinformatics ; 2021 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-33666823

RESUMO

Identifying the direction of signal flows in neural networks is important for understanding the intricate information dynamics of a living brain. Using a dataset of 213 projection neurons distributed in more than 15 neuropils of a Drosophila brain, we develop a powerful machine learning algorithm: node-based polarity identifier of neurons (NPIN). The proposed model is trained only by information specific to nodes, the branch points on the skeleton, and includes both Soma Features (which contain spatial information from a given node to a soma) and Local Features (which contain morphological information of a given node). After including the spatial correlations between nodal polarities, our NPIN provided extremely high accuracy (>96.0%) for the classification of neuronal polarity, even for complex neurons with more than two dendrite/axon clusters. Finally, we further apply NPIN to classify the neuronal polarity of neurons in other species (Blowfly and Moth), which have much less neuronal data available. Our results demonstrate the potential of NPIN as a powerful tool to identify the neuronal polarity of insects and to map out the signal flows in the brain's neural networks if more training data become available in the future.

4.
PLoS One ; 16(1): e0245990, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33507934

RESUMO

The Buridan's paradigm is a behavioral task designed for testing visuomotor responses or phototaxis in fruit fly Drosophila melanogaster. In the task, a wing-shortened fruit fly freely moves on a round platform surrounded by a 360° white screen with two vertical black stripes placed at 0° and 180°. A normal fly will tend to approach the stripes one at a time and move back and forth between them. A variety of tasks developed based on the Buridan's paradigm were designed to test other cognitive functions such as visual spatial memory. Although the movement patterns and the behavioral preferences of the flies in the Buridan's or similar tasks have been extensively studies a few decades ago, the protocol and experimental settings are markedly different from what are used today. We revisited the Buridan's paradigm and systematically investigated the approach behavior of fruit flies under different stimulus settings. While early studies revealed an edge-fixation behavior for a wide stripe in the initial visuomotor responses, we did not discover such tendency in the Buridan's paradigm when observing a longer-term behavior up to minutes, a memory-task relevant time scale. Instead, we observed robust negative photoaxis in which the flies approached the central part of the dark stripes of all sizes. In addition, we found that stripes of 20°-30° width yielded the best performance of approach. We further varied the luminance of the stripes and the background screen, and discovered that the performance depended on the luminance ratio between the stripes and the screen. Our study provided useful information for designing and optimizing the Buridan's paradigm and other behavioral tasks that utilize the approach behavior.


Assuntos
Comportamento Animal/fisiologia , Comportamento de Escolha/fisiologia , Drosophila melanogaster/fisiologia , Fototaxia/fisiologia , Visão Ocular/fisiologia , Animais , Memória Espacial/fisiologia
5.
Sci Rep ; 10(1): 13482, 2020 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-32778728

RESUMO

Hyperphosphorylated and truncated tau variants are enriched in neuropathological aggregates in diseases known as tauopathies. However, whether the interaction of these posttranslational modifications affects tau toxicity as a whole remains unresolved. By expressing human tau with disease-related Ser/Thr residues to simulate hyperphosphorylation, we show that despite severe neurodegeneration in full-length tau, with the truncation at Asp421, the toxicity is ameliorated. Cytological and biochemical analyses reveal that hyperphosphorylated full-length tau distributes in the soma, the axon, and the axonal terminal without evident distinction, whereas the Asp421-truncated version is mostly restricted from the axonal terminal. This discrepancy is correlated with the fact that fly expressing hyperphosphorylated full-length tau, but not Asp421-cleaved one, develops axonopathy lesions, including axonal spheroids and aberrant actin accumulations. The reduced presence of hyperphosphorylated tau in the axonal terminal is corroborated with the observation that flies expressing Asp421-truncated variants showed less motor deficit, suggesting synaptic function is preserved. The Asp421 cleavage of tau is a proteolytic product commonly found in the neurofibrillary tangles. Our finding suggests the coordination of different posttranslational modifications on tau may have an unexpected impact on the protein subcellular localization and cytotoxicity, which may be valuable when considering tau for therapeutic purposes.


Assuntos
Fosforilação/genética , Proteínas tau/genética , Proteínas tau/metabolismo , Doença de Alzheimer/metabolismo , Animais , Axônios/metabolismo , Modelos Animais de Doenças , Drosophila , Feminino , Humanos , Masculino , Emaranhados Neurofibrilares/metabolismo , Neurônios/metabolismo , Processamento de Proteína Pós-Traducional , Tauopatias/metabolismo
6.
J Comput Neurosci ; 48(2): 213-227, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-32388764

RESUMO

As the oldest, but least understood sensory system in evolution, the olfactory system represents one of the most challenging research targets in sensory neurobiology. Although a large number of computational models of the olfactory system have been proposed, they do not account for the diversity in physiology, connectivity of local neurons, and several recent discoveries in the insect antennal lobe, a major olfactory organ in insects. Recent studies revealed that the response of some projection neurons were reduced by application of a GABA antagonist, and that insects are sensitive to odor pulse frequency. To account for these observations, we propose a spiking neural circuit model of the insect antennal lobe. Based on recent anatomical and physiological studies, we included three sub-types of local neurons as well as synaptic short-term depression (STD) in the model and showed that the interaction between STD and local neurons resulted in frequency-sensitive responses. We further discovered that the unexpected response of the projection neurons to the GABA antagonist is the result of complex interactions between STD and presynaptic inhibition, which is required for enhancing sensitivity to odor stimuli. Finally, we found that odor discrimination is improved if the innervation of the local neurons in the glomeruli follows a specific pattern. Our findings suggest that STD, presynaptic inhibition and diverse physiology and connectivity of local neurons are not independent properties, but they interact to play key roles in the function of antennal lobes.


Assuntos
Antenas de Artrópodes/fisiologia , Insetos/fisiologia , Plasticidade Neuronal/fisiologia , Neurônios/fisiologia , Terminações Pré-Sinápticas/fisiologia , Algoritmos , Animais , Antenas de Artrópodes/efeitos dos fármacos , Discriminação Psicológica , Antagonistas GABAérgicos/farmacologia , Modelos Neurológicos , Plasticidade Neuronal/efeitos dos fármacos , Neurônios/efeitos dos fármacos , Odorantes , Terminações Pré-Sinápticas/efeitos dos fármacos , Olfato/efeitos dos fármacos , Olfato/fisiologia , Transmissão Sináptica
7.
Front Behav Neurosci ; 13: 215, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31572145

RESUMO

Drosophila Melanogaster has been shown to exhibit short-term orientation memory by fixating on orientations toward previously displayed visual landmarks. However, the fixation behavior varies and is often mixed with other types of movement. Therefore, carefully designed statistical measures are required in order to properly describe the characteristics of the fixation behavior and to quantify the orientation memory exhibited by the fruit flies. To this end, we propose a set of analytical methods. First, we defined the deviation angle which is used to quantify the deviation of the fruit fly's heading from the landmark positions. The deviation angle is defined based on the fruit fly's perspective and is able to reveal more task-relevant movement patterns than the commonly used definition which is based on the "observer's perspective." We further introduce a temporal deviation angle plot which visually presents the complex movement pattern as a function of time. Next, we define the fixation index which tolerates fluctuation in the movement and performs better in quantifying the level of fixation behavior, or the orientation memory, than the conventional method.

8.
Front Neuroinform ; 12: 99, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30687056

RESUMO

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which (1) identifies the polarity of each neuron arbor, (2) predicts connections between neurons, (3) translates morphology data from the database into physiology parameters for computational modeling, (4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and (5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.

9.
Nat Commun ; 8(1): 139, 2017 07 26.
Artigo em Inglês | MEDLINE | ID: mdl-28747622

RESUMO

Maintaining spatial orientation when carrying out goal-directed movements requires an animal to perform angular path integration. Such functionality has been recently demonstrated in the ellipsoid body (EB) of fruit flies, though the precise circuitry and underlying mechanisms remain unclear. We analyze recently published cellular-level connectomic data and identify the unique characteristics of the EB circuitry, which features coupled symmetric and asymmetric rings. By constructing a spiking neural circuit model based on the connectome, we reveal that the symmetric ring initiates a feedback circuit that sustains persistent neural activity to encode information regarding spatial orientation, while the asymmetric rings are capable of integrating the angular path when the body rotates in the dark. The present model reproduces several key features of EB activity and makes experimentally testable predictions, providing new insight into how spatial orientation is maintained and tracked at the cellular level.Ellipsoid body (EB) neurons in the fruit fly represent the animal heading through a bump-like activity dynamics. Here the authors report a connectome-driven spiking neural circuit model of the EB and the protocerebral bridge (PB) that can maintain and update an activity bump related to the spatial orientation.


Assuntos
Algoritmos , Drosophila/fisiologia , Modelos Neurológicos , Neurônios/fisiologia , Orientação Espacial/fisiologia , Potenciais de Ação/fisiologia , Animais , Encéfalo/citologia , Encéfalo/fisiologia , Conectoma
10.
Front Neuroinform ; 11: 26, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28443014

RESUMO

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of "atypical" neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the "typical" neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex.

11.
J Neurosci ; 36(45): 11375-11383, 2016 11 09.
Artigo em Inglês | MEDLINE | ID: mdl-27911739

RESUMO

Recent advances in neuro-technologies have revolutionized knowledge of brain structure and functions. Governments and private organizations worldwide have initiated several large-scale brain connectome projects, to further understand how the brain works at the systems levels. Most recent projects focus on only brain neurons, with the exception of an early effort to reconstruct the 302 neurons that comprise the whole body of the small worm, Caenorhabditis elegans However, to fully elucidate the neural circuitry of complex behavior, it is crucial to understand brain interactions with the whole body, which can be achieved only by mapping the whole-body connectome. In this article, we discuss the current state of connectomics study, focusing on novel optical approaches and related imaging technologies. We also discuss the challenges encountered by scientists who endeavor to map these whole-body connectomes in large animals.


Assuntos
Conectoma/métodos , Rede Nervosa/citologia , Rede Nervosa/fisiologia , Neurônios/citologia , Neurônios/fisiologia , Imagem Corporal Total/métodos , Animais , Humanos , Aumento da Imagem/métodos
12.
PLoS Comput Biol ; 12(8): e1005081, 2016 08.
Artigo em Inglês | MEDLINE | ID: mdl-27551824

RESUMO

Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a "Stop" process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception.


Assuntos
Tomada de Decisões/fisiologia , Modelos Neurológicos , Movimentos Sacádicos/fisiologia , Biologia Computacional , Humanos , Rede Nervosa/fisiologia , Neurônios/fisiologia , Tempo de Reação/fisiologia
13.
IEEE Trans Neural Netw Learn Syst ; 27(11): 2229-2241, 2016 11.
Artigo em Inglês | MEDLINE | ID: mdl-26415185

RESUMO

One of the ultimate goals of computational neuroscience is to quantitatively connect between complex neural circuits and behaviors. In the past decades, the touch response circuit in Caenorhabditis elegans (C. elegans) has extensively been investigated in studies using genetically modified or laser-ablated worms. Synaptic connections, including chemical and electrical synapses, have been identified for most neurons in the C. elegans. However, we still do not know whether the empirically observed touch responses can be derived from connectome reconstructed from databases. To address this issue, we defined the transmission abilities (or levels) of neurons in a rate model in order to infer the behaviors of wild-type and ablated worms in response to posterior/nose/anterior touch stimuli. Our analysis showed that transmission abilities can be used to identify sensorimotor mapping from stimuli to movements and then to infer the C. elegans behaviors under simulations based on the perspective of decision-making, and provide useful information about how chemical and electronic synapses should be combined in the neural network movement analysis. This paper reveals an efficient tool that provided insights into the functions of complex neural circuits.


Assuntos
Caenorhabditis elegans/fisiologia , Conectoma , Locomoção , Transmissão Sináptica , Animais , Bases de Dados Factuais , Rede Nervosa , Redes Neurais de Computação , Sinapses
14.
J Neurophysiol ; 114(1): 650-61, 2015 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-25995354

RESUMO

A hallmark of flexible behavior is the brain's ability to dynamically adjust speed and accuracy in decision-making. Recent studies suggested that such adjustments modulate not only the decision threshold, but also the rate of evidence accumulation. However, the underlying neuronal-level mechanism of the rate change remains unclear. In this work, using a spiking neural network model of perceptual decision, we demonstrate that speed and accuracy of a decision process can be effectively adjusted by manipulating a top-down control signal with balanced excitation and inhibition [balanced synaptic input (BSI)]. Our model predicts that emphasizing accuracy over speed leads to reduced rate of ramping activity and reduced baseline activity of decision neurons, which have been observed recently at the level of single neurons recorded from behaving monkeys in speed-accuracy tradeoff tasks. Moreover, we found that an increased inhibitory component of BSI skews the decision time distribution and produces a pronounced exponential tail, which is commonly observed in human studies. Our findings suggest that BSI can serve as a top-down control mechanism to rapidly and parametrically trade between speed and accuracy, and such a cognitive control signal presents both when the subjects emphasize accuracy or speed in perceptual decisions.


Assuntos
Tomada de Decisões , Redes Neurais de Computação , Potenciais de Ação , Animais , Haplorrinos , Inibição Neural/fisiologia , Neurônios/fisiologia , Lobo Parietal/fisiologia , Desempenho Psicomotor/fisiologia , Sinapses/fisiologia , Fatores de Tempo
15.
Neuroinformatics ; 12(3): 487-507, 2014 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-24692020

RESUMO

Directional signal transmission is essential for neural circuit function and thus for connectomic analysis. The directions of signal flow can be obtained by experimentally identifying neuronal polarity (axons or dendrites). However, the experimental techniques are not applicable to existing neuronal databases in which polarity information is not available. To address the issue, we proposed SPIN: a method of Skeleton-based Polarity Identification for Neurons. SPIN was designed to work with large-scale neuronal databases in which tracing-line data are available. In SPIN, a classifier is first trained by neurons with known polarity in two steps: 1) identifying morphological features that most correlate with the polarity and 2) constructing a linear classifier by determining a discriminant axis (a specific combination of the features) and decision boundaries. Each polarity-undefined neuron is then divided into several morphological substructures (domains) and the corresponding polarities are determined using the classifier. Finally, the result is evaluated and warnings for potential errors are returned. We tested this method on fruitfly (Drosophila melanogaster) and blowfly (Calliphora vicina and Calliphora erythrocephala) unipolar neurons using data obtained from the Flycircuit and Neuromorpho databases, respectively. On average, the polarity of 84-92 % of the terminal points in each neuron could be correctly identified. An ideal performance with an accuracy between 93 and 98 % can be achieved if we fed SPIN with relatively "clean" data without artificial branches. Our result demonstrates that SPIN, as a computer-based semi-automatic method, provides quick and accurate polarity identification and is particularly suitable for analyzing large-scale data. We implemented SPIN in Matlab and released the codes under the GPLv3 license.


Assuntos
Algoritmos , Axônios/ultraestrutura , Dendritos/ultraestrutura , Software , Animais , Polaridade Celular , Drosophila melanogaster/citologia , Neurônios/citologia , Reconhecimento Automatizado de Padrão
16.
Front Neuroinform ; 8: 27, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-24672472

RESUMO

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

17.
Front Comput Neurosci ; 7: 178, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-24339814

RESUMO

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

18.
PLoS One ; 8(4): e62379, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-23626812

RESUMO

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.


Assuntos
Retroalimentação , Modelos Neurológicos , Inibição Neural/fisiologia , Neurônios/fisiologia , Percepção/fisiologia , Transmissão Sináptica/fisiologia , Algoritmos , Sistema Nervoso Central/fisiologia , Humanos , Estimulação Luminosa , Tempo de Reação
19.
Europhys Lett ; 102(1): 10008, 2013 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-24653582

RESUMO

We study dynamical aspects of sleep micro-architecture. We find that sleep dynamics exhibits a high degree of asymmetry, and that the entire class of sleep-stage transition pathways underlying the complexity of sleep dynamics throughout the night can be characterized by two independent asymmetric transition paths. These basic pathways remain stable under sleep disorders, even though the degree of asymmetry is significantly reduced. Our findings indicate an intriguing temporal organization in sleep dynamics at short time scales that is typical for physical systems exhibiting self-organized criticality (SOC).

20.
PLoS One ; 7(10): e47574, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-23071824

RESUMO

Daily sessions of therapeutic transcranial brain stimulation are thought to prolong or amplify the effect of a single intervention. Here we show in patients with focal hand dystonia that additional, new effects build up progressively over time, making it difficult to predict the effect of long term interventions from shorter treatment sessions. In a sham-controlled study, real or sham continuous theta burst stimulation (cTBS) was given once daily for five consecutive days to dorsolateral premotor cortex (PMd). Five days of real, but not sham, premotor cTBS improved intracortical inhibition in primary motor cortex (M1) to a similar extent on day 1 and day 5. However 5 days of cTBS were required to restore the abnormal PMd-M1 interactions observed on day 1. Similarly, excessive M1 plasticity seen at baseline was also significantly reduced by five days of real premotor cTBS. There was only a marginal benefit on writing. The results show that additional, new effects, at sites distant from the point of stimulation, build up progressively over time, making it difficult to predict the effect of long term interventions from shorter treatment sessions. The results indicate that it may take many days of therapeutic intervention to rebalance activity in a complex network.


Assuntos
Estimulação Encefálica Profunda/métodos , Distúrbios Distônicos/terapia , Córtex Motor/fisiologia , Inibição Neural/fisiologia , Adulto , Análise de Variância , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Plasticidade Neuronal/fisiologia , Fatores de Tempo , Resultado do Tratamento
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...