Core Metrics
Total Citations
5,594
H-Index
27
Publications
128
i10-Index
43
2-Year Citedness
2.3
avg citations per work
Ability Dimensions
5,594 citations, h=27
2yr mean: 2.3
128 papers (8.0/year)
44 cites/paper
1 unique research topics
4 topic areas
Top 3 papers: 38% of citations
* Percentile scores are calculated relative to all scholars in the computational neuroscience dataset. Tags are assigned based on dimension combinations. Hover over the radar chart for details.
Scholar Profile Analysis
Anna C. Schapiro is a rising scholar with 5k+ citations in computational neuroscience, currently affiliated with California University of Pennsylvania.
Over a 16-year academic career, published 128 papers (averaging 8.0 per year), with 5,594 citations.
Primary research areas include Recall, Recall, Recall.
Key Findings
Signature Work
"A deep learning framework for neuroscience" is the most influential work, with 1,018 citations, published in 2019.
Early Career Analysis (First 5 Years)
Career Start
2009 - 2013
Early Citations
1,448
Early Works
11
Early Impact %
25.9%
Top Early Career Paper
Neural representations of events arise from temporal community structure
Publication Timeline
Research Topics
Top Publications
A deep learning framework for neuroscience
1,018
Citations
Neural representations of events arise from temporal community structure
602
Citations
Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning
512
Citations
Shaping of Object Representations in the Human Medial Temporal Lobe Based on Temporal Regularities
477
Citations
The Necessity of the Medial Temporal Lobe for Statistical Learning
342
Citations
Statistical learning of temporal community structure in the hippocampus
328
Citations
Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance
270
Citations
Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles
197
Citations
Hippocampal Structure Predicts Statistical Learning and Associative Inference Abilities during Development
169
Citations
Switching between internal and external modes: A multiscale learning principle
135
Citations