ライフサイエンスコーパス: neuroimaging

1 set (MDD n = 368, TD n = 200) also completed neuroimaging.

2 temporo-parietal lesions prior to functional neuroimaging.

3 ted rigor are growing increasingly common in neuroimaging.

4 ke mice for improved high-speed longitudinal neuroimaging.

5 PFC activation was measured using optical neuroimaging.

6 d, when available, independent review of the neuroimaging.

7 14 [standard deviation]; 138 men) underwent neuroimaging.

8 ia with typical basal ganglia involvement on neuroimaging.

9 HI produce white matter (WM) changes seen on neuroimaging.

10 et unresolved, ELSI issues posed by portable neuroimaging: (1) informed consent; (2) privacy; (3) cap

11 Evidence from neuropsychology [5], neuroimaging [6-11], transcranial magnetic stimulation [

12 hough genetic risk factors and network-level neuroimaging abnormalities have shown effects on cogniti

13 aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes,

14 Neuroimaging abnormalities were seen in 100% of PM and D

15 nalyses integrating functional and molecular neuroimaging acquired concurrently during a complex cogn

16 k will be helpful to validate other critical neuroimaging algorithms, as having a validation framewor

17 cision-making that can be adapted for use in neuroimaging, allowing investigation of the biological b

18 Machine learning (ML) brings neuroimaging analyses to individual subject level and ma

19 essed in regions that were identified in our neuroimaging analyses.

20 tive features, (2) combination of multimodal neuroimaging and (3) type of machine learning algorithms

21 dysfunction in NF1 that can be identified by neuroimaging and ameliorated by NOS inhibition.

22 on this neuroplasticity work using precision neuroimaging and arm casting to unmask previously unknow

23 Here we used neuroimaging and computational modeling to investigate h

24 fferences have been observed in post-mortem, neuroimaging and electrophysiological studies.

25 Advanced neuroimaging and electrophysiological techniques have re

26 ld be considered for gliomas with discordant neuroimaging and FISH results.

27 rements were corrected with abnormalities on neuroimaging and histopathology using mixed-effects mult

28 Advanced neuroimaging and liquid biopsy will hopefully improve re

29 dies and capitalises on cutting-edge in vivo neuroimaging and machine learning.

30 prevailing model used to guide in vivo human neuroimaging and non-human animal research assumes that

31 a multimodal experimental approach combining neuroimaging and non-invasive brain stimulation, we expl

32 findings from clinical pathology, functional neuroimaging and other approaches in humans.

33 This showcases how neuroimaging and personalized models can quantify indivi

34 ollow-up of infants included physical exams, neuroimaging, and Bayley-III developmental assessment.

35 dentification of several important clinical, neuroimaging, and cerebrospinal fluid characteristics.

36 eatly, including electrophysiological tests, neuroimaging, and chemical biomarkers.

37 cal trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS

38 ing literature on neurocognitive, structural neuroimaging, and functional neuroimaging outcomes assoc

39 the steadily increasing wealth of clinical, neuroimaging, and molecular biomarker information collec

40 lti-faceted study by combining biochemistry, neuroimaging, and neuropsychology to test how peripheral

41 y is required to determine whether clinical, neuroimaging, and/or fluid biomarker signatures can impr

42 operly tested through classic behavioral and neuroimaging approaches due to these intrinsic correlati

43 Here, we leverage computational neuroimaging approaches to map the topographic organizat

44 New analytical neuroimaging approaches will enable characterisation of

45 s.SIGNIFICANCE STATEMENT Using computational neuroimaging approaches, we mapped the topographic organ

46 ch brain white matter deficits identified by neuroimaging are common, yet of unknown cellular etiolog

47 The regions of the human brain affected on neuroimaging are similar to the affected brain areas in

48 tive, structural neuroimaging, or functional neuroimaging as an outcome measure.

49 Participants underwent neuroimaging at baseline, prior to starting study medica

50 ory syndrome coronavirus 2 and who underwent neuroimaging at Karolinska University Hospital between M

51 Neuroimaging-based biomarkers in ALS have been shown to

52 For neuroimaging-based machine-learning models to be interpr

53 protocol will help build more interpretable neuroimaging-based machine-learning models, contributing

54 ing an N-of-1 + i methodology, clinical- and neuroimaging-based metrics can be quantified under condi

55 Neuroimaging-based neuroanatomical studies of ASD have o

56 We have developed a new hypothesis-driven neuroimaging biomarker for schizophrenia identification,

57 Finding a clinically useful neuroimaging biomarker that can predict treatment respon

58 llowed us to explore the predictive value of neuroimaging biomarkers and determine their suitability

59 Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment tr

60 ry measured by fMRI have the potential to be neuroimaging biomarkers for future clinical trials.

61 This paper (1) assesses neuroimaging biomarkers of amyloid (A), tau (T), and neu

62 Spared ventral tissue bridges could serve as neuroimaging biomarkers of neuropathic pain and might be

63 onships and making it challenging to develop neuroimaging biomarkers to track disease severity, progr

64 's disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenoty

65 In this context, interpreting clinical neuroimaging can be complicated by the typical changes i

66 Cerebrospinal fluid analyses and neuroimaging can identify the underlying pathophysiology

67 havioral profiles, and 375 patients to study neuroimaging characteristics.

68 ent data handling strategies and studied the neuroimaging/clinical features most important for classi

69 mmatory marker patterns were associated with neuroimaging, cognition, and symptom measures.

70 Structural neuroimaging, cognitive, and learning data were collecte

71 s of youths and their environment, including neuroimaging, cognitive, biospecimen, behavioral, youth

72 ity, the authors studied a large multicenter neuroimaging cohort from the ENIGMA 22q11.2 Deletion Syn

73 EG) research, recently developed by the OHBM neuroimaging community known by the abbreviated name of

74 Recent debates in the functional neuroimaging community surrounding artifact removal proc

75 ' estimated rate of cognitive decline on the neuroimaging components and examined univariable predict

76 In this study, we used neuroimaging connectomic approaches to map the visuomoto

77 bers of 'The Tourette Association of America Neuroimaging Consortium' were not cited in PubMed.

78 osis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium.

79 An independent, blinded, neuroimaging core laboratory adjudicated favorable profi

80 Neuroimaging correlates of depression and negative affec

81 ram response is associated with clinical and neuroimaging correlates of reward processing.

82 gnition, structural neuroimaging, functional neuroimaging, CSF and genetic testing.

83 the two systems through combining multimodal neuroimaging data (diffusion magnetic resonance imaging

84 g for the instantiation of best practices in neuroimaging data acquisition, analysis, reporting and s

85 nciple using simulations based on functional neuroimaging data collected from patients with idiopathi

86 We combined neuroimaging data from 335 adult patients with high- and

87 Here, we integrated cortical neuroimaging data from patients with neurodevelopmental

88 r to achieving this is that existing primate neuroimaging data have insufficient spatial resolution t

89 ncing and cortical segmentation for advanced neuroimaging data processing and analysis.

90 Inspired by neuroimaging data showing that high value distractors ha

91 neuropathic pain, 19 pain-free patients) and neuroimaging data who had a follow-up clinical assessmen

92 d ability to predict subtype membership from neuroimaging data, this work further disentangles the he

93 tematic parameter exploration and fitting to neuroimaging data, we demonstrated that epileptic brains

94 Using a model-based analysis of functional neuroimaging data, we find that separate areas correlate

95 pact of interictal spikes and fitting to the neuroimaging data.

96 should move towards sharing of raw/voxelwise neuroimaging data.

97 molecular mechanisms from readily available neuroimaging data.

98 MAGEN study with both peer victimization and neuroimaging data.

99 elated NPTX2 with corresponding clinical and neuroimaging datasets as well as with CSF neurofilament

100 ological recommendations on how longitudinal neuroimaging datasets can be used to understand heteroge

101 on large datasets, and unfortunately, large neuroimaging datasets with clinical outcome annotations

102 Functional neuroimaging demonstrated that arbitration signals were

103 We examined neuroimaging-derived hippocampal biomarkers in subjects

104 We review neuroimaging evidence across differing mental disorders

105 Converging neuroimaging evidence has shown the functional roles of

106 Recent neuroimaging evidence suggests that deterioration in sur

107 There is also increasing behavioural and neuroimaging evidence that disruption to this process ma

108 this review is to consider existing diabetes neuroimaging evidence through the lens of sensorimotor n

109 rrelate previously implicated in dyslexia by neuroimaging evidence.

110 No consensus ethical frameworks for mobile neuroimaging exist, and existing policies for traditiona

111 Here, using a set of behavioural and neuroimaging experiments with stimuli that strongly trig

112 rder with psychosis (n = 72), and identified neuroimaging features that track psychotic symptoms in a

113 steps: the selection of diagnostic samples, neuroimaging features, algorithms, and validation approa

114 Furthermore, based on neuroimaging features, the syndrome has been considered

115 We review relevant reports including neuroimaging findings (e.g., decreased functional connec

116 Purpose To describe the neuroimaging findings (excluding ischemic infarcts) in p

117 We examine neuroimaging findings associated with Fregoli and Capgra

118 mine whether neuroanatomically heterogeneous neuroimaging findings of migraine localize to a common b

119 These results extend neuroimaging findings of smaller hippocampal volume in s

120 These findings advance previous non-neuroimaging findings of zinc's associations with excita

121 Recent neuroimaging findings point to abnormalities in the thal

122 rch was conducted for whole-brain functional neuroimaging findings published through May 2018 that co

123 neonatal-onset neurodevelopmental delay with neuroimaging findings resembling mitochondrial encephalo

124 techniques offer a new approach for linking neuroimaging findings to a common neuroanatomical substr

125 cal assessment, social cognition, structural neuroimaging, functional neuroimaging, CSF and genetic t

126 Next, we review recent progress in neuroimaging genetics (correlating neuroimaging patterns

127 was designed to comprehensively incorporate neuroimaging, genetics, and environmental factors to inv

128 data analytic practices in human functional neuroimaging, given that signal and noise may be inextri

129 Neuroimaging has been widely used to characterize atypic

130 A growing body of work using functional neuroimaging has identified several regions that appear

131 ion of age-based cognitive impairment, which neuroimaging has linked to brain glucose hypometabolism.

132 Neuroimaging has radically improved our understanding of

133 Here, we applied neuroimaging in a longitudinal sample of n = 146 partici

134 mechanisms in this figure-ground modulation, neuroimaging in humans has instead largely ascribed the

135 George's Cognition and Neuroimaging in Stroke (SCANS; n=121) and Radboud Univer

136 haracterized by symmetrical lesions found on neuroimaging in the basal ganglia, thalamus, and brainst

137 allenging because of the limited accuracy of neuroimaging in the early disease stages and the absence

138 Neuroimaging in this patient revealed severe leukoenceph

139 Key features on neuroimaging include a thin corpus callosum (90%), ventr

140 tle research on co-use and associations with neuroimaging indices.

141 status) enrolled in the Alzheimer's Disease Neuroimaging Initiative (17 with AD dementia and 199 wit

142 ng 129 datasets from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and relying on the Clinic

143 normal subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (n = 417) and val

144 epression (LLD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) Depression Project study

145 mer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite)

146 , we extracted data from Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with cerebro

147 clinics and the American Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

148 000 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including cognitively un

149 om data collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI).

150 dependent samples of the Alzheimer's Disease Neuroimaging Initiative (n1 = 284; n2 = 553) with harmon

151 te matter volumes in the Alzheimer's Disease Neuroimaging Initiative [ADNI: n = 1149; 382 cognitively

152 lthy participants from the Alzheimer Disease Neuroimaging Initiative database.

153 patients with MCI from the Alzheimer Disease Neuroimaging Initiative database.

154 thesis, we leveraged the Alzheimer's Disease Neuroimaging Initiative dataset.

155 mples, obtained from the Alzheimer's Disease Neuroimaging Initiative project.

156 maging outcomes from the Alzheimer's Disease Neuroimaging Initiative study, and the analyses of 64 dr

157 ctive cohort study, participants from the AD Neuroimaging Initiative were included (healthy control p

158 cluded patients from the Alzheimer's Disease Neuroimaging Initiative who underwent autopsy and for wh

159 metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers.

160 ication to the data from Alzheimer's Disease Neuroimaging Initiative, we confirmed that our approach

161 ysis using data from the Alzheimer's Disease Neuroimaging Initiative, where we assess the collective

162 ormal patients from the Alzheimer's Database Neuroimaging Initiative.

163 ging Brain Study and the Alzheimer's Disease Neuroimaging Initiative.

164 dated with data from the Alzheimer's Disease Neuroimaging Initiative.

165 In contrast, neuroimaging investigations failed to identify cerebral

166 at recent knowledge gleaned from genomic and neuroimaging investigations of eating disorders in human

167 However, neuroimaging investigations of reward processing underly

168 We review how neuroimaging is being used to identify a more focal ther

169 ood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation

170 i Mental Health Center in collaboration with neuroimaging laboratories at Harvard and MIT.

171 Our findings help unify migraine neuroimaging literature and offer a migraine-specific ta

172 was to critically examine the behavioral and neuroimaging literature on Pavlovian learning in pediatr

173 urate axon radius mapping has eluded in vivo neuroimaging, mainly due to a lack of sensitivity of the

174 spatially resolved gene expression and human neuroimaging maps.

175 ial siderosis is an established haemorrhagic neuroimaging marker of cerebral amyloid angiopathy.

176 d combined prognostic value of the different neuroimaging markers.

177 with 70.7% accuracy (p < 0.01) based on the neuroimaging measures alone, with 80.5% accuracy (p = 0.

178 used to identify relationships between these neuroimaging measures and previously assessed pain inten

179 nts of backward and forward speech alongside neuroimaging measures of voxel-based morphometry, diffus

180 % accuracy (p < 0.001) based on clinical and neuroimaging measures together.

181 l subtypes of depression based on functional neuroimaging measures, including dimensional, categorica

182 t using clinical, behavioral, and functional neuroimaging measures.

183 ltivariate pattern analysis on time-resolved neuroimaging (MEG) data to examine how object-color know

184 hrough systematic comparison with functional neuroimaging meta-analyses, we establish a statistically

185 us of neuron-glia integrity via non-invasive neuroimaging methods and demonstrated the substructures

186 Current non-invasive neuroimaging methods can assess neural activity in all a

187 ctrophysiology should be combined with other neuroimaging methods.

188 cal phenomenology, neurogenetics, multimodal neuroimaging, neurophysiology, and neuromodulation.

189 PET neuroimaging of amyloid-beta (Abeta) provides an in vivo

190 onsidered; and 4) neurocognitive, structural neuroimaging, or functional neuroimaging as an outcome m

191 ive, structural neuroimaging, and functional neuroimaging outcomes associated with cannabis and NTP c

192 (P = .005), lower platelet count at time of neuroimaging (P = .029), and higher organ bleeding score

193 We used a task-based functional neuroimaging paradigm to induce fatigue in 39 healthy in

194 nalyses using peripheral cortisol levels and neuroimaging paradigms showed that methylomic variation

195 ge on symptoms, neurocognitive deficits, and neuroimaging parameters and other biomarkers associated

196 ogress in neuroimaging genetics (correlating neuroimaging patterns of brain function with genetic dat

197 d disease subtypes characterized by distinct neuroimaging patterns of regional neurodegeneration, whi

198 ize the clinical, cognitive, behavioral, and neuroimaging phenotype of UNC13A in patients with ALS.

199 risk genes and associated with cognitive and neuroimaging phenotypes of SCZ, as well as with response

200 associated with SCZ risk and behavioral and neuroimaging phenotypes of the disease, as well as with

201 relation of pathogenic genetic variants with neuroimaging phenotypes.

202 Neuroimaging plays an essential role in the diagnosis of

203 OT-D trial and were assessed with functional neuroimaging pre- and post-ADM treatment (randomized to

204 invasive, interactive, adaptive and gamified neuroimaging procedure may provide important information

205 Moreover, we aimed to compare its neuroimaging profile against svPPA, which is associated

206 T and SUNA also display a similar structural neuroimaging profile, providing further support for the

207 iting impulsivity and tics using multi-modal neuroimaging protocol.

208 We included patients with neuroimaging-proven ICH, available DNA and 6-month follo

209 tes of 7547 neuroscience terms across 13 459 neuroimaging publications.

210 -1H-1,2,4-triazole ((11)C-PS13), a COX-1 PET neuroimaging radiopharmaceutical, in OvCa xenograft mous

211 Neuroimaging research has revealed that structural brain

212 Functional neuroimaging research has shown that this distinction be

213 hm will facilitate functional and structural neuroimaging research into small subcortical nuclei and

214 Future neuroimaging research of larger sample sizes, including

215 aging technologies will fundamentally change neuroimaging research.

216 Three studies examined neuroimaging results and found neurologic injury to be m

217 e a basis for the improved interpretation of neuroimaging results that are relevant to learning and a

218 vacy; (3) capacity to accurately communicate neuroimaging results to remote participants; (4) extensi

219 Exploratory neuroimaging revealed default mode network connectivity

220 Functional neuroimaging reveals that conditional alpha2-Na/K ATPase

221 The present study combined neuroimaging, salivary cortisol, and blood markers of in

222 The neuroimaging sample comprised 126 participants, mean 22.

223 Data came from 3 neuroimaging samples (N = 2423), spanning childhood or a

224 outcome was control over the SMA assessed in neuroimaging scans, in which subjects were cued to incre

225 e measures of polygenic risk, cognition, and neuroimaging show significant associations with the futu

226 ar coupling and the basis of BOLD functional neuroimaging signals.

227 g techniques such as MRI to generate nuanced neuroimaging signatures for Alzheimer's disease diagnosi

228 Neuroimaging software methods are complex, making it a n

229 ain activity, a major current focus of human neuroimaging studies aimed at developing biomarkers of d

230 Neuroimaging studies are essential in patients with epil

231 tational, and particularly recent functional neuroimaging studies converges to support the existence

232 vidual-differences approach in developmental neuroimaging studies could advance our understanding of

233 Previous neuroimaging studies examining the neuroanatomical under

234 related dementias, with a principal focus on neuroimaging studies exploring subtypes of regional neur

235 So far, however, most longitudinal neuroimaging studies focus on group-level estimates.

236 Most of the recent neuroimaging studies focusing on the brain morphometry h

237 Data-driven neuroimaging studies frequently report a negative impact

238 Neuroimaging studies have consistently reported similar

239 Neuroimaging studies have found evidence of robust alter

240 Inconsistent findings from migraine neuroimaging studies have limited attempts to localize m

241 Neuroimaging studies have observed morphologic and funct

242 Neuroimaging studies have reported unilateral OFC respon

243 Neuroimaging studies have revealed a higher prevalence o

244 Neuroimaging studies have shown neural evidence for eith

245 Neuroimaging studies have shown that major depressive di

246 Recent evidence from human lesion and neuroimaging studies implicated anterior hippocampus (aH

247 Neuroimaging studies in animals provide a unique transla

248 have turned to two complementary approaches: neuroimaging studies in human patients (and their health

249 Neuroimaging studies in humans have thus far been unable

250 dults, anatomical, electrophysiological, and neuroimaging studies in infants and children indicate LH

251 Genetic data, as well as autopsy and neuroimaging studies in patients with AD, indicate that

252 Molecular neuroimaging studies incorporating simultaneous acquisit

253 actions have not been considered in previous neuroimaging studies of excitation and inhibition imbala

254 Neuroimaging studies of humans in altered states of cons

255 ippocampal volume is a consistent finding in neuroimaging studies of individuals with schizophrenia.

256 erefore compared meta-analyses of functional neuroimaging studies of induced and pathological anxiety

257 egenerative disorder, both mouse studies and neuroimaging studies of presymptomatic mutation carriers

258 Neuroimaging studies of psychotic disorders have demonst

259 Neuroimaging studies of task switching and set-shifting

260 has been exponential growth in the number of neuroimaging studies reporting structural and functional

261 Results from neuroimaging studies suggest that disruptions in flexibl

262 Neuroimaging studies suggest that increased brain connec

263 Human neuroimaging studies suggest that such experiences drive

264 In this review, we highlight longitudinal neuroimaging studies that have moved beyond group-level

265 ated in language comprehension, including in neuroimaging studies that have reported activation in do

266 Notably, no structural neuroimaging studies were found to examine the combined

267 Case histories and neuroimaging studies were reviewed.

268 ntive and therapeutic considerations and for neuroimaging studies, as they suggest to take informatio

269 Despite extensive genetic and neuroimaging studies, detailed cellular mechanisms under

270 This is due to the limited number of neuroimaging studies, the presence of conflicting result

271 In neuroimaging studies, there is preliminary evidence for

272 thesizing results from electrophysiology and neuroimaging studies.

273 sed primarily on evidence from correlational neuroimaging studies.

274 In the largest neuroimaging study of 22q11DS to date, the authors found

275 the first comparative and noninvasive visual neuroimaging study of a non-primate and a primate specie

276 In a longitudinal neuroimaging study of infants at familial high or low ri

277 In the present functional neuroimaging study of the human brain, a multidomain pro

278 To address this question, we conducted a neuroimaging study with people born without upper limbs-

279 In this longitudinal case-control neuroimaging study, we included subjects with unilateral

280 We used multimodal neuroimaging [T1-weighted magnetic resonance imaging (MR

281 Diffusion-weighted imaging (DWI) is a neuroimaging technique that has allowed us an unpreceden

282 Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood fl

283 -infrared spectroscopy (NIRS), a noninvasive neuroimaging technique, to determine whether patients wi

284 However, noninvasive neuroimaging techniques such as magnetic resonance spect

285 The neuroimaging techniques used in our patient were vital f

286 However, this is challenging using standard neuroimaging techniques.

287 Highly portable, cloud-enabled neuroimaging technologies will fundamentally change neur

288 Genomics Superstruct Project, and Enhancing NeuroImaging through Meta Analysis (ENIGMA; combined n >

289 te human neuroscience tools including mobile neuroimaging to explore long-term, embodied human-robot

290 l hypoxia-ischemia is nonspecific and merits neuroimaging to identify antecedent brain malformations

291 nsory preconditioning task and pattern-based neuroimaging to study this question.

292 incentive delay (MID) task during functional neuroimaging was completed at baseline and after 2 weeks

293 identified and the usefulness of aggressive neuroimaging was examined.

294 With recent advances in high-resolution neuroimaging we can then test these predictions in human

295 ng ex vivo gene down-regulation with in vivo neuroimaging, we find that transcriptional correlates of

296 Using functional neuroimaging, we measured brain responses while particip

297 les discussing deep learning applications in neuroimaging were identified, divided by imaging modalit

298 Functional neuroimaging, which has prognostic significance, has yet

299 to rely on myoclonic status epilepticus and neuroimaging, which were favored over median nerve somat

300 Our previous mechanistic and neuroimaging work in young rhesus monkeys linked the cen