ライフサイエンスコーパス: neuronal network

1 teady state and noisy fluctuation within the neuronal network.

2 uitry and cellular physiology that make up a neuronal network.

3 e Fbxl3(+/+) but not the Fbxl3(Afh/Afh) vSCN neuronal network.

4 ons and efficiently controls the activity of neuronal network.

5 in the respiratory network distinct from the neuronal network.

6 vesicular protein in the maturation of GnRH neuronal network.

7 atially separated areas of an interconnected neuronal network.

8 on of the adjacent, environmentally isolated neuronal network.

9 location of inputs into the same underlying neuronal network.

10 erived from the enhanced training to a wider neuronal network.

11 ent methods are demanded in investigation of neuronal network.

12 ady exists considerable understanding of the neuronal network.

13 subserved by a highly evolved cortico-motor neuronal network.

14 havior and development and their linkages to neuronal networks.

15 ent local connectivity and the modularity in neuronal networks.

16 rstand the functional logic and evolution of neuronal networks.

17 ectrical properties and neurotransmission of neuronal networks.

18 r cortical layer neurons and form functional neuronal networks.

19 ted to emerge from the dynamics of competing neuronal networks.

20 ved to be stored in the synapses of cortical neuronal networks.

21 nable noninvasive long-term interrogation of neuronal networks.

22 er the underlying structural connectivity in neuronal networks.

23 of dendritic spines and spontaneously active neuronal networks.

24 aptogenesis leading to functional defects in neuronal networks.

25 eling spiking activity in single-neurons and neuronal networks.

26 rchical connectivity patterns of oscillatory neuronal networks.

27 erstood, as is their role in the function of neuronal networks.

28 ate at the same time and depend on different neuronal networks.

29 harmacologically controlling the activity of neuronal networks.

30 its that increase the computational power of neuronal networks.

31 rated physiologically functional neurons and neuronal networks.

32 nd measure synaptic transmission in cultured neuronal networks.

33 uence subsequent development and function of neuronal networks.

34 the propagation of intracellular signals in neuronal networks.

35 uch computations requires wiring diagrams of neuronal networks.

36 e key determinants of spike synchrony within neuronal networks.

37 scillatory activity is widespread in dynamic neuronal networks.

38 finely tuned interactions within large-scale neuronal networks.

39 vity is spatially balanced across excitatory neuronal networks.

40 uid powerfully influence the excitability of neuronal networks.

41 hat can create defined topologically-complex neuronal networks.

42 ck specimens or selective photoactivation of neuronal networks.

43 microelectrode arrays and long-term cultured neuronal networks.

44 nd precisely positioned to directly (re)wire neuronal networks.

45 ability, timing, and synaptic integration in neuronal networks.

46 Learning induces plasticity in neuronal networks.

47 more focal in the specific brain regions and neuronal networks.

48 her, establishing the wiring architecture of neuronal networks.

49 f single-neuron perturbations in large-scale neuronal networks.

50 tasis or to reveal communication patterns in neuronal networks.

51 ening and other functional interrogations of neuronal networks.

52 derlying structural and temporal dynamics of neuronal networks.

53 ng response profiles obtained using cultured neuronal networks.

54 branching is crucial for proper formation of neuronal networks.

55 d inhibition is fundamental for operation of neuronal networks.

56 functional changes in individual neurons and neuronal networks?

57 ng and exercise may ameliorate developmental neuronal network abnormalities and consequent behavioral

58 synapses formed at the time of learning upon neuronal network activation depends on the stress hormon

59 The spontaneous neuronal network activities were monitored with an integ

60 E patients or hCSF were measured by in vitro neuronal network activity (ivNNA) recorded with microele

61 HCAR1 as a new player for the regulation of neuronal network activity acting in concert with other e

62 es can both sense and shape the evolution of neuronal network activity and are known to possess uniqu

63 Thus, microglia are involved in changes in neuronal network activity and SD after brain injury in v

64 f the DGC at inhibitory synapses and altered neuronal network activity and specific cognitive tasks v

65 ncephalitis (AE) patients regulates in vitro neuronal network activity differentially to healthy huma

66 a2delta1 overexpression enhances spontaneous neuronal network activity in developing and mature cultu

67 Sensory stimuli elicit a surge of neuronal network activity in the gamma range (30-50 Hz)

68 yte calcium and electrocorticogram to record neuronal network activity in the somatosensory cortex du

69 ow largely documented, their contribution to neuronal network activity is only beginning to be apprec

70 o sensory inputs and regulate sensory-evoked neuronal network activity maximizing its dynamic range.

71 rn optogenetically inputs that mimic natural neuronal network activity patterns.

72 t with neuronal elements; however, what role neuronal network activity plays in regulating microglial

73 Rapid changes in neuronal network activity trigger widespread waves of ex

74 citatory/inhibitory imbalance that scales up neuronal network activity under inflammatory conditions.

75 emonstrate polymorph-dependent alteration in neuronal network activity upon seeded aggregation of alp

76 asonable surrogate for direct measurement of neuronal network activity, but traditional imaging parad

77 bunits, resulting in a complex modulation of neuronal network activity.

78 BA receptor distribution as well as abnormal neuronal network activity.

79 nmetabolic effects of lactate for regulating neuronal network activity.

80 synaptogenesis, as well as strongly enhance neuronal network activity.

81 ay through which HCAR1 activation tunes down neuronal network activity.

82 nanodomains (~80 nm) that were controlled by neuronal network activity.

83 The mechanisms by which neuronal networks adapt to IF and how such adaptations i

84 We show that hippocampal neuronal networks adapt to IF by enhancing GABAergic ton

85 cation of conolidine/cannabidiol to cultured neuronal networks altered network firing in a highly rep

86 These neuronal network and behavioral adaptations require the

87 loped a mathematical model of the kisspeptin neuronal network and confirmed its predictions experimen

88 neuronal injury manifested by a reduction in neuronal network and connectivity.

89 ved to play a crucial mediatory role between neuronal networks and behavioral GRNs.

90 the level of the development and function of neuronal networks and circuits.

91 lly precise cross-area analyses of epileptic neuronal networks and find a feed-forward propagation pa

92 neural cells to promote the formation of new neuronal networks and functional connectivity.

93 , including information propagation units in neuronal networks and hub structure in transportation ne

94 f MeCP2 leads to precipitous collapse of the neuronal networks and incompatibility with life within d

95 tigation in the inhibitory versus excitatory neuronal networks and microcircuit connectivity is warra

96 by considering models from climate science, neuronal networks and power grids.

97 that dimensionality determines properties of neuronal networks and that several features of brain dyn

98 architecture for a profound understanding of neuronal networks and their function.

99 to identify electric phenotypes in cultured neuronal networks and to analyze additional risk genes i

100 This process depends on a distributed neuronal network, and an important current challenge is

101 t regulate brain development, maintenance of neuronal networks, and injury repair.

102 mputational methods, including convolutional neuronal networks, and other machine learning approaches

103 These cultures exhibit active neuronal networks, and subcortical projecting tracts can

104 Functionally, mPFC neuronal networks appear to be affected in a PKA-depende

105 Functionally, mPFC neuronal networks appeared to be affected in a PKA-depen

106 inability to control axon guidance, and thus neuronal network architecture, has limited investigation

107 following specific anatomical and functional neuronal network architectures.

108 Neuronal networks are dynamically modified by selective

109 the impact of the central circadian clock on neuronal networks are incompletely understood.

110 Hyperexcitable neuronal networks are mechanistically linked to the path

111 Neuronal networks are the standard heuristic model today

112 gions but become fully integrated within CA1 neuronal networks as independent, multiplexed representa

113 Human fetal colon samples have dense neuronal networks at the level of the myenteric plexus b

114 Analyzing the connectivity of neuronal networks, based on functional brain imaging dat

115 With those merits, this neuronal network-based biosensor will be promising to be

116 yed as sensing elements to build an in vitro neuronal network-based biosensor.

117 These data highlight the utility of cultured neuronal network-based workflows to efficiently identify

118 a defect in sensory adaptation within local neuronal networks, beginning at a young age and continui

119 Neuronal network behaviour first emerges at approximatel

120 t of gliotransmitters on the excitability of neuronal networks beyond synapses.

121 ference and show that cardinal behaviours of neuronal networks - both in vivo and in vitro - can be e

122 understanding of the NEUROG2/1-induced human neuronal network but also substantiate NEUROG2/1 iNs as

123 sfer effects and the recruitment of a common neuronal network by the training and the transfer tasks

124 ted AE suppressed global spiking activity of neuronal networks by a factor of 2.17 (p < 0.05) or 2.42

125 Although DM hyperexcites neuronal networks by delaying inactivation of axonal vol

126 ut these cells are also involved in creating neuronal networks by orchestrating construction of the w

127 rm plasticity and thus differentially affect neuronal network characteristics.

128 ences likely relevant for mediating abnormal neuronal network connectivity in vitro.

129 as early progression mechanisms of decreased neuronal network connectivity, hypoxia, altered blood-br

130 ism, neurotransmitter imbalance and impaired neuronal network connectivity.

131 must be closely linked to adaptations of the neuronal network controlling the underlying singing moto

132 hite matter integrity and disorganization of neuronal networks could be important determinants of chr

133 Interestingly, defects in neuronal networks could be rescued by insulin growth fac

134 ntly increased neuronal activity in cultured neuronal networks derived from primary mouse cortical ne

135 tudies demonstrate essential roles of p39 in neuronal network development and function.

136 biological processes like cancer metastasis, neuronal network development and wound healing.

137 Neuronal network development requires tightly regulated

138 With the trained neuronal networks different biologically active molecule

139 The generated neuronal network differentiated PVOD from PAH samples wi

140 Neuronal network disintegration is fundamental to neurod

141 Since TLE is a neuronal network disorder, DKI may be well suited to ful

142 Developing neuronal networks display spontaneous bursts of action p

143 or counteracting synaptic impairments in the neuronal networks during the early progression of AD.

144 rge is pivotal for understanding large-scale neuronal network dynamics and computation.

145 utational model of seizures to elucidate the neuronal network dynamics underlying seizure termination

146 int measurements of cholinergic activity and neuronal network dynamics with high spatio-temporal reso

147 Epileptic seizures represent altered neuronal network dynamics, but the temporal evolution an

148 y complex processes, from protein folding to neuronal network dynamics, can be described as stochasti

149 us large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating n

150 CHF is at least partly the result of central neuronal network dysfunction.

151 M10 substrates provide a molecular basis for neuronal network dysfunctions in conditional ADAM10-/- m

152 In neuronal networks, electrical synapses may function as a

153 Studies of neuronal network emergence during sensory processing and

154 cognized as important regulators of cell and neuronal network excitability.

155 ane depolarization and contribute greatly to neuronal network excitability.

156 portant functions in synaptic maturation and neuronal network excitability.

157 though current studies indicate an increased neuronal network excitability.

158 linear integrators, it was demonstrated that neuronal networks exhibit mixing in response to imposed

159 properly balanced in individual neurons and neuronal networks for proper brain function.

160 t activators direct Cdk5 signaling to govern neuronal network formation and function still remains el

161 n FMR1, presenting with early alterations in neuronal network formation and function that precede neu

162 w genetic deficits in TRIO can lead to early neuronal network formation by directly affecting both ne

163 t mediator of early cortical development and neuronal network formation in the brain.

164 l spike activity (ESA) functions critical to neuronal network formation.

165 al-receiving arbor of neurons that underlies neuronal network formation.

166 cular mechanisms that set in motion aberrant neuronal network formations during the course of limbic

167 In this study, we show that the neuronal networks formed a functional circuitry that was

168 mal development, maturation, and function of neuronal networks formed between the brainstem and cereb

169 his paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate t

170 er, generating electrophysiologically mature neuronal networks from hPSCs has been challenging.

171 m cells offers the capability to study human neuronal networks from patient or engineered human cell

172 CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to lin

173 by which nuclear calcium signaling controls neuronal network function is by regulating the expressio

174 Therefore, this antibody likely restores neuronal network function that possibly underlies cognit

175 ADAM10 is also required for neuronal network functions in murine brain, but neuronal

176 ecades of investigation, the identity of the neuronal network generating pulsatile reproductive hormo

177 ological small-world network, the C. elegans neuronal network, has strikingly low SWP.

178 ibute to the development of a hyperexcitable neuronal network have been elucidated.

179 Biophysical modeling of neuronal networks helps to integrate and interpret rapid

180 In this study, hippocampal neuronal networks (HNNs) endogenously expressing 5-HT re

181 he App(NL-G-F) mouse model of AD, IF reduces neuronal network hyperexcitability and ameliorates defic

182 ting in a deficit in GABAergic signaling and neuronal network hyperexcitability.

183 t G(i)-dependent microglial dynamics prevent neuronal network hyperexcitability.

184 e brain while accelerating the maturation of neuronal networks, important features underdeveloped in

185 We describe remodeling of the cholinergic neuronal network in asthmatic airways driven by brain-de

186 n vivo we investigated the cutaneous sensory neuronal network in wild-type, Il31-transgenic, and IL-3

187 often studied using computational models of neuronal networks in a dynamically balanced state.

188 neurotransmission, and the critical roles of neuronal networks in anesthetic effects on memory and co

189 read technologies to monitor the activity of neuronal networks in awake, behaving animals over long p

190 and paves the road to map the perturbome of neuronal networks in future studies.

191 MEA recordings from neuronal networks in miniaturized hyperbaric measuring c

192 egenerative brain niches in cellular repair, neuronal networks in synaptic plasticity, and the distin

193 ng and regulating the proper function of the neuronal networks in the adult CNS, but these cells are

194 imilar to reservoir computing enables random neuronal networks in the granule cell layer to provide t

195 vity is spatially balanced across excitatory neuronal networks in V1.

196 truct enables the formation of 3D functional neuronal networks in vitro, allowing novel strategies fo

197 ng waves of activity, is a robust feature of neuronal networks in vivo and in vitro The neurophysiolo

198 report a detailed characterization of human neuronal networks induced by the expression of human NEU

199 activities of neuroendocrine and sympathetic neuronal networks, influencing in turn sympatho-humoral

200 We investigated astrocyte-neuronal network interactions in vivo by combining two-p

201 Transplantation of scaffold-supported neuronal networks into mouse brain striatum improved sur

202 define structural E/I ratio in an in silico neuronal network, investigate how it relates to power an

203 d VGLUT3 is key for the function of specific neuronal networks involved in motor coordination, emotio

204 he FEF, demonstrating that its effect on the neuronal network is consistent across the cortical hiera

205 l glucagon-like peptide-1 receptor-dependent neuronal network is necessary for ileal propionate and l

206 We propose that formation of connectivity in neuronal networks is associated with a concerted interpl

207 Optimal functioning of neuronal networks is critical to the complex cognitive p

208 ANCE STATEMENT The computational capacity of neuronal networks is determined by their connectivity.

209 Therefore, modelling focal seizures in human neuronal networks is now possible with the developed chi

210 re we show that synchronization in 2D and 3D neuronal networks is significantly different.

211 Yet, the neuronal network linking to pancreatic islets has never

212 Optogenetic neuronal network manipulation promises to unravel a long

213 Small-scale neuronal networks may impose widespread effects on large

214 these mediators with developing neurons and neuronal networks may lead to long-lasting structural an

215 Here, we develop the first neuronal network model for the nerve nets of jellyfish.

216 te the dynamics of how a biophysically-based neuronal network model synchronizes its period and phase

217 der which synaesthesia evolves, we studied a neuronal network model that represents two recurrently c

218 e 3D Vicsek flocking model and a small-world neuronal network model.

219 Neuronal network modeling revealed that these gradients

220 Cultured neuronal networks monitored with microelectrode arrays (

221 rons may allow considerable flexibility when neuronal networks must adapt to perturbations in their o

222 functional and structural reorganization of neuronal networks occurs resulting in the onset of focal

223 We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dy

224 for generating realistic computer models of neuronal networks of striatal and midbrain dopaminergic

225 Inhibition in neuronal networks of the neocortex serves a multitude of

226 APP, we used a microfluidic corticocortical neuronal network-on-a-chip to examine APP transport and

227 of the interneuron-astrocyte signaling into neuronal network operation remains unknown.

228 such, they do not model groups of connected neuronal networks or focal seizures.

229 n the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attentio

230 Thus, the hypothalamic leptin-NTS-HCRT neuronal network orchestrates key homeostatic output, in

231 E) and inhibition (I) is a key principle for neuronal network organization and information processing

232 The brain is a massive neuronal network, organized into anatomically distribute

233 ise temporal recruitment relative to ongoing neuronal network oscillations.

234 educe detrimental leak-current influences on neuronal networks over a broad conductance range and ind

235 key features, including gene expression and neuronal network patterns, are shared across several phy

236 Changes in synaptic physiology underlie neuronal network plasticity and behavioral phenomena, wh

237 onal simulation studies in understanding how neuronal networks process biological signals, and how th

238 nformation is acquired and thus the way that neuronal networks process the information.

239 nization of alpha oscillations across a wide neuronal network promotes the maintenance and stabilizat

240 Imaging neuronal networks provides a foundation for understandin

241 thod to accelerate the development of mature neuronal networks, providing a means to enhance throughp

242 ed in the temporal patterns of activity in a neuronal network rather than just synaptic weights betwe

243 of whether or not addictive drugs usurp the neuronal networks recruited by natural rewards by evalua

244 Information processing in cortical neuronal networks relies on properly balanced excitatory

245 Information processing in neuronal networks relies on the precise synchronization

246 eins used by neurons to develop and maintain neuronal networks, relying on trans homophilic interacti

247 uence of its modulatory control over diverse neuronal networks required for memory, motor coordinatio

248 GNIFICANCE STATEMENT The proper formation of neuronal networks requires accurate guidance of axons an

249 Comprehensive analysis of neuronal networks requires brain-wide measurement of con

250 Neuronal networks responded to DM ([Formula: see text])

251 into grafts elicited distinct and segregated neuronal network responses throughout the graft.

252 rvated spinal cord also triggered local host neuronal network responses.

253 d can prevent the appropriate integration of neuronal networks, resulting in neurodegenerative disord

254 Multielectrode recordings of neuronal networks revealed hyperexcitability and altered

255 model for synchronous infra-slow bursting in neuronal networks.SIGNIFICANCE STATEMENT Infra-slow rhyt

256 by neuronal activity and, in turn, modulates neuronal network slow oscillations.

257 cells that probably started to connect into neuronal networks soon afterward.

258 that the intermediate level organization of neuronal networks strongly influences the dynamics of th

259 hich are known to be the results of aberrant neuronal network structure and/or function in the brain.

260 In stereotyped neuronal networks, synaptic connectivity is dictated by

261 using multi-electrodes arrays, we show that neuronal network synchronization was altered in MECP2dup

262 tor (MC) cortices are key links in the brain neuronal network that allows rodents to explore the envi

263 dult-onset dysfunction and degeneration of a neuronal network that are seen in patients, including de

264 indicate species-specific adaptations of the neuronal network that might be closely linked to the evo

265 ional approach to model a randomly connected neuronal network that relies on short-term synaptic faci

266 ain is thus a prerequisite to understand the neuronal network that underlies celestial compass orient

267 Do behaviors and neuronal networks that control them evolve together in l

268 thmic movements of animals are controlled by neuronal networks that have been conceived as hierarchic

269 Brain structures and neuronal networks that mediate spatial navigation, decis

270 Furthermore, neuronal networks that were either modulated or not by a

271 y identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac gangli

272 ectivity metrics in the microscopic scale of neuronal networks through a wide set of network conditio

273 Disintegration of neuronal networks through different pathological process

274 bal disturbances in dynamic intra- and inter-neuronal networks through pathologic rewiring of the cha

275 sy cellular oscillators communicate within a neuronal network to generate precise system-wide circadi

276 For a neuronal network to perform inference, it must integrate

277 tors for computational models of large-scale neuronal networks to address this challenge.

278 properly balanced in individual neurons and neuronal networks to allow proper brain function.

279 Brain function requires connecting neuronal networks to empower movement, sensation, behavi

280 tamate receptor content that are required by neuronal networks to generate cellular correlates of lea

281 gation in Cataglyphis requires sophisticated neuronal networks to process the broad repertoire of vis

282 utilizes the innate capacity of surrounding neuronal networks to provide protection against both for

283 The ability of neuronal networks to reconfigure is a key property under

284 that Bri2 BRICHOS monomers potently prevent neuronal network toxicity of Abeta, while dimers strongl

285 Our results suggest that separate neuronal networks underlie error sensitivity and retriev

286 vely, these studies suggest that spinal cord neuronal networks underlying flexion reflex, multiple fo

287 ose the best-suited genetic tools to dissect neuronal networks underlying the behavior of larval frui

288 tly as we increase the basal activity of the neuronal network using continuous low-frequency optogene

289 We focused on fast neuronal network waves in the gamma-band (30-70 Hz).

290 tory and inhibitory GABA actions in cortical neuronal networks, we present a novel optogenetic approa

291 Scaffold-supported, reprogrammed neuronal networks were successfully grafted into organot

292 lications of neuronal dynamics by simulating neuronal networks, where each neuron minimises its free

293 ges in action potential (AP) patterns within neuronal networks, which could result from subtle subcel

294 Understanding the detailed dynamics of neuronal networks will require the simultaneous measurem

295 a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve

296 temporal patterns of spontaneous activity in neuronal networks with neuron clustering.

297 Neuronal networks with strong recurrent connectivity pro

298 d patterns of light for photo-stimulation of neuronal networks, with future implications ranging from

299 ever, the cellular identity of the activated neuronal network within the responsive barrel was unchan

300 Neuronal networks within the spinal cord, collectively k