ライフサイエンスコーパス: brain imaging

1 hysical examination, laboratory testing, and brain imaging.

2 T1-weighted diffusion tensor imaging [DTI]) brain imaging.

3 midal signs, and extensive calcifications on brain imaging.

4 bility and progressive cerebellar atrophy on brain imaging.

5 ll subcortical infarcts and lacunes) seen on brain imaging.

6 ta on cognitive performance, genotyping, and brain imaging.

7 (2.7%) patients, all with an indication for brain imaging.

8 nimal in non-time-of-flight (18)F-FDG PET/MR brain imaging.

9 nce projections, as shown using iDISCO whole-brain imaging.

10 uidelines and assess the clinical utility of brain imaging.

11 ontrol and better diagnosis from advances in brain imaging.

12 elet transfusion within 90 min of diagnostic brain imaging.

13 possibilities for functional and multimodal brain imaging.

14 ch areas in CS theory and its application to brain imaging.

15 included 503 older adults with SVD noted on brain imaging.

16 ed, 1000 youths aged 8 to 22 years underwent brain imaging.

17 the macroscopic measurements obtained during brain imaging.

18 l recruitment of prefrontolimbic activity in brain imaging.

19 ge under antiplatelet treatment diagnosis on brain imaging.

20 utions, brain homogenates, and in vivo whole brain imaging.

21 ecline associated with calcium deposition on brain imaging.

22 high-resolution positron emission tomography brain imaging.

23 was established and tested for (18)F-FDG PET brain imaging.

24 eby opening new avenues for data analysis in brain imaging.

25 s to track animal movement and perform whole-brain imaging.

26 Using high-resolution functional brain imaging (0.8 mm(3)) and multivoxel pattern informa

27 At the time of brain imaging, 1.5 years after initial phenotyping, the

28 ascular coupling is the basis for functional brain imaging(2), and impaired neurovascular coupling is

29 into all types of movements [7], functional brain imaging [8], and treatment of vestibular and highe

30 ciated with more severe disease and abnormal brain imaging (abnormal imaging 0.55cm vs 0.50cm normal

31 associated with increased disease severity, brain imaging abnormalities, and increased death by 3 mo

32 Brain imaging analyses highlighted higher dorsal anterio

33 We combined univariate and multivariate brain imaging analyses to assess whether and how the bra

34 We make our tool freely available in Brain Imaging Analysis Kit (BrainIAK).

35 Advanced brain imaging analysis methods, including multivariate p

36 Methods:(18)F-FDG PET brain imaging and a comprehensive battery of neuropsycho

37 Using functional brain imaging and a specific cognitive paradigm, modelli

38 nce imaging (MRI) has been used for baseline brain imaging and afterward as a screening tool for tril

39 Magnetic resonance brain imaging and angiography (MRI and MRA) at exit show

40 combine different levels of measures (e.g., brain imaging and behavior).

41 ata resource can be used to link genetics to brain imaging and behavior, and to study the role of pos

42 ective of the present study was to integrate brain imaging and behavioral measures to identify new br

43 In real data, including brain imaging and cancer genetics, MGC detects the prese

44 ng relationships between biological markers, brain imaging and clinical parameters may provide an imp

45 With advances in brain imaging and completion of randomized clinical tria

46 the human ventral stream using time-resolved brain imaging and deep learning.

47 ents in predictive feedback using functional brain imaging and eye-tracking whilst presenting an appa

48 Gene expression, brain imaging and fetal brain expression quantitative tr

49 Brain imaging and focal therapy should be considered bef

50 brain structures in subgroup analysis using brain imaging and full clinical data (CM: n = 24; Non-CM

51 tary tests, including polysomnography (PSG), brain imaging and genetic analysis, were used.

52 Imaging genetics combines brain imaging and genetic information to identify the re

53 nts recruited through a large-scale study of brain imaging and genetics.

54 ess ultrasound as a modality for large-scale brain imaging and modulation.

55 ion with clinical variables, cross-sectional brain imaging and neurophysiological data; their role as

56 Noninvasive human brain imaging and neurophysiology have continued develop

57 imodal biomarker combinations across fluids, brain imaging and other domains.

58 yielded a rich range of associations between brain imaging and other measures collected by UK Biobank

59 We describe UK Biobank brain imaging and present results derived from the first

60 These findings support the future use of brain imaging and SVM-based classifier in the diagnosis

61 n heterodimerization domain, four had normal brain imaging and three exhibited moderately progressive

62 Here, brain imaging and transcranial magnetic phosphene data s

63 With combined brain-imaging and cognitive-behavioral analyses, we are

64 ling with methoxy-X04, high throughput whole brain imaging, and an automated informatics pipeline.

65 , viral-vector gene manipulation, functional brain imaging, and behavioral phenotyping to uncover AT'

66 nces in neurovascular biology, epidemiology, brain imaging, and biomarker development have started to

67 west risk] to 7 [highest risk]), findings on brain imaging, and cause of TIA or minor stroke with the

68 connections, together with neuroanatomical, brain imaging, and clinical observations, have recontext

69 y phenotyping in animal models and patients, brain imaging, and electrophysiology-based pain biomarke

70 n vitro and messenger RNA assays, functional brain imaging, and psychophysical and kinematic tests we

71 The ABCD(2) score, findings on brain imaging, and status with respect to large-artery a

72 state than VS/UWS as evidenced by functional brain imaging; and (iii) the neurophysiological and cogn

73 both structural and in-vivo functional mouse brain imaging applications.

74 , we utilized an ultra-high field multimodal brain imaging approach and demonstrated that psilocybin

75 This study used a whole--brain imaging approach known as quantitative susceptibil

76 The present study used a single-cell whole-brain imaging approach to 1) assess whether abstinence f

77 Advances in brain imaging are helping to identify the structural and

78 cal examination, electroencephalography, and brain imaging are necessary to separate patients with ac

79 e authors studied 1,394 youths who underwent brain imaging as part of the Philadelphia Neurodevelopme

80 Brain imaging at 7 T was used to segment cortical and wh

81 echnique that allows for noninvasive in vivo brain imaging at micrometer-millisecond spatiotemporal r

82 rtunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbat

83 ated from multiple sclerosis on conventional brain imaging, both in adults and children.

84 scale microscopy approaches are transforming brain imaging, but currently lack efficient multicolor c

85 Brain imaging can be used to study how individuals' brai

86 n epileptic event and laboratory studies and brain imaging can identify an acute insult contributing

87 ut eligibility, specificity varied from 25% (brain imaging; carotid imaging) to 99% (anticoagulation

88 The study was performed at the Wolfson Brain Imaging Centre of Addenbrooke's Hospital.

89 Brain imaging characteristics of MOG antibody disease ar

90 aired, and 9 PD-normal) underwent multimodal brain imaging, cognitive testing, and neurologic evaluat

91 193 patients (18.1%) with an indication for brain imaging, compared with only 2 of 356 (0.05%) with

92 Functional brain imaging comparing responsive and connected versus

93 ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigat

94 Some possible brain imaging correlates are reviewed.

95 e biological markers, such as those based on brain imaging, could aid in clinical management of BD.

96 truth subclasses, particularly on UK Biobank brain imaging data and transcriptome data from the Cance

97 56 participants had quantitative brain imaging data and were included in evaluable popula

98 Demographic, clinical, and brain imaging data as well as functional and radiologic

99 ve associations between genetic variants and brain imaging data at one time-point.

100 Network-based analyses of brain imaging data consistently reveal distinct modules

101 lthy-controls in shared data from the Autism Brain Imaging Data Exchange (ABIDE) and the Attention-De

102 Using individuals from the Autism Brain Imaging Data Exchange and ADHD-200, we apply a dat

103 bserve significant differences in the Autism Brain Imaging Data Exchange cohort, despite having achie

104 control data from the ABIDE I and II (Autism Brain Imaging Data Exchange) and PING (Pediatric Imaging

105 erature and an analysis of the ABIDE (Autism Brain Imaging Data Exchange) cohort.

106 We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state fun

107 ing in an independent sample from the Autism Brain Imaging Data Exchange.

108 We apply sample weights to structural brain imaging data from a community-based sample of chil

109 d spectroscopy (fNIRS) to collect functional brain imaging data from Costa Rican farm workers enrolle

110 tly compare these disorders using structural brain imaging data from ENIGMA consortium data.

111 hich fNIRS may be used to collect functional brain imaging data in epidemiological field surveys.

112 ariability, from 21,407 subjects' multimodal brain imaging data in UK Biobank.

113 We analysed all clinical and brain imaging data of mutation-positive individuals incl

114 Our brain imaging data reveals that the functional interplay

115 We acquire mouse whole-brain imaging data sets of multiple types of neurons and

116 ganized and described in compliance with the Brain Imaging Data Structure (BIDS).

117 By leveraging the Brain Imaging Data Structure to standardize both the inp

118 Worldwide cooperative analyses of brain imaging data support a profile of subcortical abno

119 We used a machine-learning technique on brain imaging data to predict, with high accuracy, which

120 e., the single nucleotide polymorphisms) and brain imaging data to reveal the associations from genot

121 s assessing median nerve sensory latency and brain imaging data were acquired at baseline and followi

122 Clinical and brain imaging data were collected over 2 years.

123 he rapidly growing amount of high-resolution brain imaging data, a great demand arises for automated

124 jectory, active versus non-active regions in brain imaging data, and firms with different financial r

125 ty of neuronal networks, based on functional brain imaging data, has yielded new insight into brain c

126 dures and recent advances in the analysis of brain imaging data, we localized purely experience-based

127 s were evaluated for their impact on the PET brain imaging data.

128 the current analytic approaches to metabolic brain imaging data.

129 hly effective at extracting information from brain imaging data.

130 neurobiologically informed subtypes based on brain imaging data.

131 edict outcomes in neurological patients from brain imaging data.

132 ge predicted from machine-learning models of brain-imaging data.

133 The aim of this study was to identify brain imaging discriminators between those three inflamm

134 Substantial advances have been made in brain imaging, especially with functional imaging and fi

135 new focal neurological deficit (FND) without brain imaging evidence of recent haemorrhage versus othe

136 Two independent brain imaging experiments using high-resolution fMRI rev

137 cal fluorescence microscopy is often used in brain imaging experiments, however conventional confocal

138 ta-analysis of a large dataset of functional brain-imaging experiments, we further found that the tha

139 r hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (

140 Herein, the authors report brain imaging features in 11 critically ill patients wit

141 rtical and/or callosal microhemorrhages were brain imaging features in critically ill patients with c

142 f the RESTART trial to explore whether these brain imaging features modify the effects of antiplatele

143 Brain imaging features of intracerebral haemorrhage and

144 ei are among the most consistent large-scale brain imaging findings in schizophrenia.

145 e found to have grossly abnormal clinical or brain imaging findings or both, including 4 infants with

146 en reported in association with a variety of brain imaging findings such as ischemic infarct, hemorrh

147 hearing loss, spasticity, and characteristic brain imaging findings.

148 ive infant with grossly abnormal clinical or brain imaging findings.

149 Brain imaging from all five affected individuals reveale

150 entally induced inflammation, and functional brain imaging (functional magnetic resonance imaging) to

151 Brain imaging genetics aims to reveal genetic effects on

152 Brain imaging genetics intends to uncover associations b

153 Brain imaging genetics studies the complex associations

154 Brain imaging genetics, which studies the linkage betwee

155 ntial and power of the non-convex methods in brain imaging genetics.

156 d, of whom 45 732 (42 073 [92%] confirmed by brain imaging) had a stroke during the study period.

157 Brain imaging has a crucial role in the presurgical asse

158 anisms such as Caenorhabditis elegans, whole brain imaging has been performed.

159 Brain imaging has revealed alterations in dopamine uptak

160 Brain imaging has revealed links between prefrontal acti

161 Recent work with noninvasive human brain imaging has started to investigate the effects of

162 ous advancement as well as widespread use of brain imaging have contributed to the increasing detecti

163 espread statistical approaches to functional brain imaging have critical blind spots in this scenario

164 asure, multitasking ability, with structural brain imaging in a sample of 100 participants.

165 ble PAT (3D-wPAT) technique is described for brain imaging in behaving rats.

166 ry assessment of internalizing disorders and brain imaging in children suggests that early adversity

167 Iterative interactions between functional brain imaging in humans and mechanistic research in othe

168 Using multimodal brain imaging in humans, this study takes initial steps

169 on and spatial selection and performed whole-brain imaging in macaque monkeys.

170 PET/CT system with suitable performance for brain imaging in NHPs.

171 Brain imaging in patients with CKD has revealed damage t

172 e emerged for cellular-resolution functional brain imaging in small organisms such as larval zebrafis

173 Brain imaging in these individuals reveals delay in myel

174 sophila circadian neural circuit using whole-brain imaging in vivo.

175 slower learning process with rapid multiband brain imaging, in-scanner kinematics and Bayesian patter

176 The brain imaging includes structural, diffusion and functio

177 temporary statistical methods for functional brain imaging-including univariate contrast, searchlight

178 Brain imaging is another potentially attractive outcome

179 Since functional brain imaging is increasingly finding practical applicat

180 tivariable analyses, multiple infarctions on brain imaging, large-artery atherosclerosis, and an ABCD

181 mental effects on neurocognitive function or brain imaging markers compared to standard antiretrovira

182 Higher burdens of these brain imaging markers were observed with both large rise

183 Recent advances in brain imaging may help to identify the optimal timing fo

184 HD), genetic tests make cognitive, motor and brain imaging measurements possible before symptom manif

185 There were no group differences in other brain imaging measures (FDR >0.16).

186 th these reciprocal CNVs in conjunction with brain imaging measures have not been reported.

187 The UK Biobank provides cognition and brain imaging measures in the largest population cohort

188 t conditioned inhibition paradigms alongside brain imaging methodologies, we investigated neural acti

189 ctrophysiology and optical imaging, or whole-brain imaging methods, such as fMRI.

190 rge scale in comparison to other traditional brain imaging methods.

191 (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and conne

192 y reported biological changes in patients by brain imaging, neurochemical and pharmacological approac

193 In summary, we show how whole brain imaging of amyloid pathology in mice reveals the e

194 Thus, brain imaging of cholinesterase activity associated with

195 r of deriving hypotheses directly from human brain imaging of clinical conditions that can be invasiv

196 nical trials of dopamine-targeting drugs and brain imaging of dopamine receptors in patients with men

197 tively, we have provided the first molecular brain imaging of gamma-secretase, which may not only acc

198 Here we have undertaken brain imaging of patients carrying microduplications in

199 sed cerebral ischemic lesions and atrophy in brain imaging of patients on hemodialysis.

200 Whole-brain imaging of stable transgenic id2b:gal4 larvae reve

201 In vivo functional and structural brain imaging of synucleinopathies in humans have provid

202 [(11)C]PBR28 Positron Emission Tomography brain imaging of the 18-kDa translocator protein (TSPO),

203 chers are increasingly turning to functional brain imaging, often applying machine-learning algorithm

204 and functional recovery were behavioural and brain imaging open-label trials and case reports, but se

205 entangle the shared variance among different brain-imaging or behavioral variables has become a prior

206 n between MS polygenic risk scores (PRS) and brain imaging outcomes from a large, population-based pe

207 analyzed the association between AD PRSs and brain imaging parameters using T1-weighted structural (n

208 in 7,577 children aged 9 to 11 y across 585 brain imaging phenotypes and 617 cognitive, behavioral,

209 r psychiatric disorders, personality traits, brain imaging phenotypes and externalizing behaviours wi

210 Here, we correlated brain imaging phenotypes from ~9000 UK Biobank participa

211 ions are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide dat

212 SNPs)) and quantitative traits (QTs) such as brain imaging phenotypes.

213 prehensive neuropsychological assessment and brain imaging, PI monotherapy does not increase the risk

214 story of seizures, and four had anomalies on brain imaging ranging from agenesis of the corpus callos

215 ) correlates with the specific parameters of brain imaging related to cognitive impairment and 2) dis

216 Field-based brain imaging research, including populations underrepre

217 ng and its interaction with other aspects of brain imaging research.

218 gy poses a fundamental challenge to relating brain imaging results across the scientific literature.

219 sults of laboratory tests for Zika virus and brain imaging results were available for 79 (87%) cases;

220 A preliminary investigation using structural brain imaging revealed a region of anterior cingulate co

221 Brain imaging revealed an almost agyric brain with diffu

222 Brain imaging revealed that the hippocampus was responsi

223 Brain imaging revealed that viewing a string activates t

224 tive interaction between neuroanatomists and brain-imaging scientists.

225 In vivo brain imaging shows that the chemiluminescence signal of

226 Non-expert-defined brain imaging signs of brain frailty and acute ischaemia

227 imited by inconsistent methods for assessing brain imaging, small sample sizes, and racially/ethnical

228 Functional brain imaging studies and non-invasive brain stimulation

229 rse of BD is often progressive, longitudinal brain imaging studies are scarce.

230 network (DMN) has been defined in functional brain imaging studies as a set of highly connected brain

231 Large-scale brain imaging studies by the ENIGMA Consortium identifie

232 brain regions implicated in depression, and brain imaging studies demonstrate altered connectivity a

233 Brain imaging studies demonstrate extensive posterior pr

234 Only a few electromagnetic brain imaging studies have examined neural correlates of

235 Brain imaging studies have provided a firmer understandi

236 Brain imaging studies in children with prenatal methamph

237 Brain imaging studies in patients with a heterozygous mu

238 We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ,

239 Limited in vivo brain imaging studies months to years after individuals

240 Evidence from brain imaging studies of patients with psychotic disorde

241 Brain imaging studies performed in humans have associate

242 Moreover, brain imaging studies show alterations in corticolimbic

243 However, whole-brain imaging studies so far have delivered highly heter

244 Recent brain imaging studies suggest abnormal brain activity un

245 ine clinic visits and with serial functional brain imaging studies, including structural brain MRI, m

246 traindications are invited to participate in brain imaging studies.

247 Brain-imaging studies implicate aberrant prefrontal cort

248 These observations suggest that prospective brain-imaging studies of infants at high familial risk o

249 Most brain-imaging studies of language comprehension focus on

250 ogy, and economics, and recent findings from brain-imaging studies of value-guided decision-making.

251 Cross-sectional brain-imaging studies reveal that obese versus lean huma

252 Brain-imaging studies show a relationship between neuroa

253 Phylogenetic, developmental, and brain-imaging studies suggest that human personality is

254 ps through a psychophysiology and structural brain imaging study in a large sample of patients across

255 h: last year saw reports on the first modern brain imaging study with LSD and three separate clinical

256 t Susceptibility (AGES)-Reykjavik Study in a brain imaging study.

257 This novel, repeated-measures brain-imaging study suggests that adolescents who gained

258 x of tPA ahead of time, initiation of tPA in brain imaging suite, and prompt data feedback to emergen

259 ective marker-based tracking and ratiometric brain imaging system, permitting brain activity imaging

260 limited by the unnatural environment typical brain imaging systems impose.

261 Brain imaging techniques that use vascular signals to ma

262 ngths and limitations in comparison to other brain imaging techniques, showcases interesting applicat

263 Using brain imaging techniques, we sought to determine whether

264 that underlies hemodynamic-based functional brain imaging techniques.

265 Advances in brain imaging, technology, and understanding of the path

266 e first successful PET radioligand for BACE1 brain imaging that demonstrates favorable in vivo bindin

267 rd task during functional magnetic resonance brain imaging, the authors tested how brain reward learn

268 cipated in three waves of magnetic resonance brain imaging through school age and early adolescence.

269 this study, we used magnetoencephalographic brain imaging to begin addressing this knowledge gap by

270 Diagnosis depends on clinical features and brain imaging to differentiate between ischaemic stroke

271 Here we use deep-brain imaging to identify changes in fluorescence of the

272 Here we use fMRI brain imaging to investigate the neural basis of one com

273 nalgesia, we used brainstem optimized, whole-brain imaging to record responses to concurrent thermal

274 of electrophysiology, blood biomarkers, and brain imaging, to optimise prognostic accuracy.

275 in the long term, as demonstrated by in vivo brain imaging using (18)F-fluorodopa and (11)C-racloprid

276 ique eye-tracking tests, in combination with brain imaging via MRI, we found a series of physiologica

277 Median time between metal measurement and brain imaging was 21 y (range: 18-25 y).

278 Five of 18 individuals for whom brain imaging was available had lesions reminiscent of t

279 Methods:(18)F-AV-1451 PET brain imaging was completed in 16 4 young healthy volunt

280 Methods:(18)F-AV-1451 PET brain imaging was completed in 16 subjects: 4 young heal

281 Here, using functional brain imaging, we asked humans to perform a planning tas

282 Next, using structural and functional brain imaging, we found that in comparison to controls,

283 However, to apply it to in vivo brain imaging, we must address the challenges of 3D imag

284 Using functional brain imaging, we show that, when subjects make the risk

285 lure center that routinely employs admission brain imaging, we sought 1) the prevalence of intracrani

286 Data on mother-reported callous traits and brain imaging were collected at age 10 years from partic

287 Paired baseline ONSD and brain imaging were performed in 63 participants.

288 lts of subsequent electroencephalography and brain imaging were unchanged, and a fluorodeoxyglucose F

289 s (n = 137, 83 females) completed structural brain imaging with 3 Tesla MRI at two timepoints (mean a

290 trols underwent positron emission tomography brain imaging with [(18)F]AV-1451.

291 (18)F-FDG PET brain imaging with advanced statistical analysis may pro

292 This instrument provides whole-brain imaging with cellular resolution in an unrestraine

293 In worms, this reporter enables whole-brain imaging with faster kinetics and brighter fluoresc

294 speech/arithmetic stressors and simultaneous brain imaging with high-resolution positron emission tom

295 lity of (18)F-FDG PET/CT versus conventional brain imaging with MRI.

296 while the long length (>2 mm) allow for deep-brain imaging with no additional complexity in the optic

297 Although presynaptic dopaminergic brain imaging with PET and SPECT is clinically widely us

298 on the brain basis of parenting is combining brain imaging with social, cognitive, and behavioral ana

299 We compared their brain imaging with those in published findings from Powa

300 ereby facilitating superresolution and whole-brain imaging without immunohistochemistry.