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Gotowe bibliografie tematyczne / Inhibitory Network Model

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Artykuły w czasopismach

Gotowa bibliografia na temat „Inhibitory Network Model”

Autor: Grafiati

Data publikacji: 6 września 2023

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Artykuły w czasopismach na temat "Inhibitory Network Model"

1

Skinner, F. K., J. Y. J. Chung, I. Ncube, P. A. Murray, and S. A. Campbell. "Using Heterogeneity to Predict Inhibitory Network Model Characteristics." Journal of Neurophysiology 93, no. 4 (2005): 1898–907. http://dx.doi.org/10.1152/jn.00619.2004.

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From modeling studies it has been known for >10 years that purely inhibitory networks can produce synchronous output given appropriate balances of intrinsic and synaptic parameters. Several experimental studies indicate that synchronous activity produced by inhibitory networks is critical to the production of population rhythms associated with various behavioral states. Heterogeneity of inputs to inhibitory networks strongly affect their ability to synchronize. In this paper, we explore how the amount of input heterogeneity to two-cell inhibitory networks affects their dynamics. Using numer

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Vassiliev, P. M., A. A. Spasov, A. N. Kochetkov, M. A. Perfilev, and A. R. Koroleva. "Consensus ensemble neural network multitarget model of RAGE inhibitory activity of chemical compounds." Biomeditsinskaya Khimiya 67, no. 3 (2021): 268–77. http://dx.doi.org/10.18097/pbmc20216703268.

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RAGE signal transduction via the RAGE-NF-κB signaling pathway is one of the mechanisms of inflammatory reactions that cause severe complications in diabetes mellitus. RAGE inhibitors are promising pharmacological compounds that require the development of new predictive models. Based on the methodology of artificial neural networks, consensus ensemble neural network multitarget model has been constructed. This model describes the dependence of the level of the RAGE inhibitory activity on the affinity of compounds for 34 target proteins of the RAGE-NF-κB signal pathway. For this purpose an expan

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3

Bryson, Alexander, Samuel F. Berkovic, Steven Petrou, and David B. Grayden. "State transitions through inhibitory interneurons in a cortical network model." PLOS Computational Biology 17, no. 10 (2021): e1009521. http://dx.doi.org/10.1371/journal.pcbi.1009521.

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Inhibitory interneurons shape the spiking characteristics and computational properties of cortical networks. Interneuron subtypes can precisely regulate cortical function but the roles of interneuron subtypes for promoting different regimes of cortical activity remains unclear. Therefore, we investigated the impact of fast spiking and non-fast spiking interneuron subtypes on cortical activity using a network model with connectivity and synaptic properties constrained by experimental data. We found that network properties were more sensitive to modulation of the fast spiking population, with re

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Chou, Kenny F., and Kamal Sen. "AIM: A network model of attention in auditory cortex." PLOS Computational Biology 17, no. 8 (2021): e1009356. http://dx.doi.org/10.1371/journal.pcbi.1009356.

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Attentional modulation of cortical networks is critical for the cognitive flexibility required to process complex scenes. Current theoretical frameworks for attention are based almost exclusively on studies in visual cortex, where attentional effects are typically modest and excitatory. In contrast, attentional effects in auditory cortex can be large and suppressive. A theoretical framework for explaining attentional effects in auditory cortex is lacking, preventing a broader understanding of cortical mechanisms underlying attention. Here, we present a cortical network model of attention in pr

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5

Rich, Scott, Michal Zochowski, and Victoria Booth. "Effects of Neuromodulation on Excitatory–Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure." Journal of Nonlinear Science 30, no. 5 (2018): 2171–94. http://dx.doi.org/10.1007/s00332-017-9438-6.

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Abstract Acetylcholine (ACh), one of the brain’s most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E–I networks), which are ubiquitous in the brain. Utilizing biophysical models of E–I networks, we analyze how the network conne

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6

Cao, Ying, Xiaoyan He, Yuqing Hao, and Qingyun Wang. "Transition Dynamics of Epileptic Seizures in the Coupled Thalamocortical Network Model." International Journal of Bifurcation and Chaos 28, no. 08 (2018): 1850104. http://dx.doi.org/10.1142/s0218127418501043.

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In this paper, based on the two-compartment unidirectionally coupled thalamocortical model network, we investigated the transition dynamics of epileptic seizures, by considering the inhibitory coupling strength from cortical inhibitory interneuronal (IN) population to excitatory pyramidal (PY) neuronal population as the key bifurcation parameter. The results show that in the single compartment thalamocortical model, inner-compartment inhibitory functions of IN can make the system transit from the absence seizures to the tonic oscillations. In the case of two-compartment coupled thalamocortical

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7

Tiesinga, Paul H. E. "Stimulus Competition by Inhibitory Interference." Neural Computation 17, no. 11 (2005): 2421–53. http://dx.doi.org/10.1162/0899766054796905.

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When two stimuli are present in the receptive field of a V4 neuron, the firing rate response is between the weakest and strongest response elicited by each of the stimuli when presented alone (Reynolds, Chelazzi, & Desimone, 1999). When attention is directed toward the stimulus eliciting the strongest response (the preferred stimulus), the response to the pair is increased, whereas the response decreases when attention is directed to the other stimulus (the poor stimulus). When attention is directed to either of the two stimuli presented alone, the firing rate remains the same or increases

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8

YAMAZAKI, TADASHI, and SHIGERU TANAKA. "A NEURAL NETWORK MODEL FOR TRACE CONDITIONING." International Journal of Neural Systems 15, no. 01n02 (2005): 23–30. http://dx.doi.org/10.1142/s0129065705000037.

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We studied the dynamics of a neural network that has both recurrent excitatory and random inhibitory connections. Neurons started to become active when a relatively weak transient excitatory signal was presented and the activity was sustained due to the recurrent excitatory connections. The sustained activity stopped when a strong transient signal was presented or when neurons were disinhibited. The random inhibitory connections modulated the activity patterns of neurons so that the patterns evolved without recurrence with time. Hence, a time passage between the onsets of the two transient sig

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9

Andreev, Andrey, and Vladimir Maksimenko. "Synchronization in coupled neural network with inhibitory coupling." Cybernetics and Physics, Volume 8, 2019, Number 4 (December 30, 2019): 199–204. http://dx.doi.org/10.35470/2226-4116-2019-8-4-199-204.

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A theoretical model of a network of neuron-like elements was constructed. The network included several subnetworks. The first subnetwork was used to translate a constant-amplitude signal into a spike sequence (conversion of amplitude to frequency). A similar process occurs in the brain when perceiving visual information. With an increase in the flow of information, the generation frequency of the neural ensemble participating in the processing increases. Further, the first subnetwork transmitted excitation to two large interconnected subnetworks. These subnetworks simulated the dynamics of the

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10

Blazis, Diana E. J., Thomas M. Fischer, and Thomas J. Carew. "A Neural Network Model of Inhibitory Information Processing in Aplysia." Neural Computation 5, no. 2 (1993): 213–27. http://dx.doi.org/10.1162/neco.1993.5.2.213.

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Recent cellular studies have revealed a novel form of inhibitory information processing in the siphon withdrawal reflex of the marine mollusc Aplysia: Motorneuronal output is significantly reduced by activity-dependent potentiation of recurrent inhibition within the siphon withdrawal network (Fischer and Carew 1991, 1993). This inhibitory modulation is mediated by two types of identified interneurons, L29s and L30s. In an effort to describe and analyze this and other forms of inhibitory information processing in Aplysia, and to compare it with similar processing in other nervous systems, we ha

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