Katherine L Narr
Biographic Data
| ID | 7374400 |
|---|---|
| NAME | Katherine L Narr |
| GIVEN NAMES | Katherine L |
| FAMILY NAME | Narr |
| SIGNATURE | NARR K L |
| AFFILIATIONS | University of California, Los Angeles |
| ORCID | 0000-0002-9396-7936 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
White matter microstructural perturbations after total sleep deprivation in depression
Total sleep deprivation leads to rapid microstructural changes in WM pathways in patients with depression that are distinct from WM changes associated with TSD observed in HCs. WM tracts including the superior corona radiata and posterior thalamic radiation could be potential biomarkers of the rapid therapeutic effects of TSD. Changes in superior corona radiata FA, in particular, may relate to improvements in maladaptive rumination
Hippocampal subfield volumes in treatment resistant depression and serial ketamine treatment
These results provide new evidence to suggest that hippocampal subfield volumes at baseline may present a biomarker for neurocognitive improvement following ketamine treatment in TRD. In contrast, pre-treatment subfield volumes and changes in subfield volumes showed negligible relationships with ketamine-related improvements in depressive symptoms
Preliminary evidence for a lower brain age in children with attention-deficit/hyperactivity disorder
Attention-deficit hyperactivity disorder (ADHD) is a debilitating disorder with apparent roots in abnormal brain development. Here, we quantified the level of individual brain maturation in children with ADHD using structural neuroimaging and a recently developed machine learning algorithm. More specifically, we compared the BrainAGE index between three groups matched for chronological age (mean ± SD: 11.86 ± 3.25 years): 89 children diagnosed wi…
Gut Microbiome Diversity and Abundance Correlate with Gray Matter Volume (GMV) in Older Adults with Depression
Growing evidence supports the concept that bidirectional brain-gut microbiome interactions play an important mechanistic role in aging, as well as in various neuropsychiatric conditions including depression. Gray matter volume (GMV) deficits in limbic regions are widely observed in geriatric depression (GD). We therefore aimed to explore correlations between gut microbial measures and GMV within these regions in GD. Sixteen older adults (>60 year…
Machine Learning Prediction of Treatment Outcome in Late-Life Depression
Background: Recent evidence suggests that integration of multi-modal data improves performance in machine learning prediction of depression treatment outcomes. Here, we compared the predictive performance of three machine learning classifiers using differing combinations of sociodemographic characteristics, baseline clinical self-reports, cognitive tests, and structural magnetic resonance imaging (MRI) features to predict treatment outcomes in la…
Regional White Matter Integrity Predicts Treatment Response to Escitalopram and Memantine in Geriatric Depression
Background: Geriatric depression with subjective memory complaints increases the risk for Alzheimer's Disease. Memantine, a neuroprotective drug, can improve depression and help prevent cognitive decline. In our 6-months clinical trial, escitalopram/memantine (ESC/MEM) improved mood and cognition compared to escitalopram/placebo treatment (ESC/PBO; NCT01902004). In this report, we investigated whether baseline brain white matter integrity in fron…
Fronto-Temporal Connectivity Predicts ECT Outcome in Major Depression
Our data indicate that pattern classification of multimodal fMRI metrics can successfully predict ECT outcome, particularly for individuals who will not respond to treatment. Notably, connectivity with networks highly relevant to ECT and depression were consistently selected as important predictive features. These included the left DLPFC and the sgACC, which are both targets of other neurostimulation therapies for depression, as well as connectiv…
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Fronto-Temporal Connectivity Predicts ECT Outcome in Major Depression
Our data indicate that pattern classification of multimodal fMRI metrics can successfully predict ECT outcome, particularly for individuals who will not respond to treatment. Notably, connectivity with networks highly relevant to ECT and depression were consistently selected as important predictive features. These included the left DLPFC and the sgACC, which are both targets of other neurostimulation therapies for depression, as well as connectiv…
Regional White Matter Integrity Predicts Treatment Response to Escitalopram and Memantine in Geriatric Depression
Background: Geriatric depression with subjective memory complaints increases the risk for Alzheimer's Disease. Memantine, a neuroprotective drug, can improve depression and help prevent cognitive decline. In our 6-months clinical trial, escitalopram/memantine (ESC/MEM) improved mood and cognition compared to escitalopram/placebo treatment (ESC/PBO; NCT01902004). In this report, we investigated whether baseline brain white matter integrity in fron…
Machine Learning Prediction of Treatment Outcome in Late-Life Depression
Background: Recent evidence suggests that integration of multi-modal data improves performance in machine learning prediction of depression treatment outcomes. Here, we compared the predictive performance of three machine learning classifiers using differing combinations of sociodemographic characteristics, baseline clinical self-reports, cognitive tests, and structural magnetic resonance imaging (MRI) features to predict treatment outcomes in la…
Preliminary evidence for a lower brain age in children with attention-deficit/hyperactivity disorder
Attention-deficit hyperactivity disorder (ADHD) is a debilitating disorder with apparent roots in abnormal brain development. Here, we quantified the level of individual brain maturation in children with ADHD using structural neuroimaging and a recently developed machine learning algorithm. More specifically, we compared the BrainAGE index between three groups matched for chronological age (mean ± SD: 11.86 ± 3.25 years): 89 children diagnosed wi…
Gut Microbiome Diversity and Abundance Correlate with Gray Matter Volume (GMV) in Older Adults with Depression
Growing evidence supports the concept that bidirectional brain-gut microbiome interactions play an important mechanistic role in aging, as well as in various neuropsychiatric conditions including depression. Gray matter volume (GMV) deficits in limbic regions are widely observed in geriatric depression (GD). We therefore aimed to explore correlations between gut microbial measures and GMV within these regions in GD. Sixteen older adults (>60 year…
White matter microstructural perturbations after total sleep deprivation in depression
Total sleep deprivation leads to rapid microstructural changes in WM pathways in patients with depression that are distinct from WM changes associated with TSD observed in HCs. WM tracts including the superior corona radiata and posterior thalamic radiation could be potential biomarkers of the rapid therapeutic effects of TSD. Changes in superior corona radiata FA, in particular, may relate to improvements in maladaptive rumination
Hippocampal subfield volumes in treatment resistant depression and serial ketamine treatment
These results provide new evidence to suggest that hippocampal subfield volumes at baseline may present a biomarker for neurocognitive improvement following ketamine treatment in TRD. In contrast, pre-treatment subfield volumes and changes in subfield volumes showed negligible relationships with ketamine-related improvements in depressive symptoms
Medicine (7 works) · Psychology (6 works) · Functional Brain Connectivity Studies (5 works) · Cognition (4 works) · Depression (economics (4 works) · Internal Medicine (4 works) · Psychiatry (4 works) · Advanced Neuroimaging Techniques and Applications (2 works) · Antidepressant (2 works) · Artificial Intelligence (2 works)