Abigail Morrison

4.0k total citations
87 papers, 1.7k citations indexed

About

Abigail Morrison is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Abigail Morrison has authored 87 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Cognitive Neuroscience, 54 papers in Electrical and Electronic Engineering and 22 papers in Cellular and Molecular Neuroscience. Recurrent topics in Abigail Morrison's work include Neural dynamics and brain function (65 papers), Advanced Memory and Neural Computing (53 papers) and Neuroscience and Neural Engineering (17 papers). Abigail Morrison is often cited by papers focused on Neural dynamics and brain function (65 papers), Advanced Memory and Neural Computing (53 papers) and Neuroscience and Neural Engineering (17 papers). Abigail Morrison collaborates with scholars based in Germany, Japan and Norway. Abigail Morrison's co-authors include Markus Diesmann, Wulfram Gerstner, Ad Aertsen, Renato Duarte, Susanne Kunkel, Hans Ekkehard Pleßer, T. Geisel, Carsten Mehring, Moritz Helias and Alexander Hanuschkin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Abigail Morrison

81 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Abigail Morrison Germany 20 1.4k 1.1k 784 301 135 87 1.7k
Sylvain Saïghi France 15 1.0k 0.7× 1.9k 1.7× 995 1.3× 446 1.5× 96 0.7× 31 2.4k
Paolo Del Giudice Italy 20 1.2k 0.9× 683 0.6× 616 0.8× 249 0.8× 272 2.0× 51 1.6k
Jayawan Wijekoon United Kingdom 11 859 0.6× 1.3k 1.2× 758 1.0× 364 1.2× 64 0.5× 19 1.8k
Fopefolu Folowosele United States 8 722 0.5× 1.1k 1.0× 620 0.8× 306 1.0× 46 0.3× 16 1.5k
Moritz Helias Germany 22 1.1k 0.8× 451 0.4× 500 0.6× 185 0.6× 341 2.5× 74 1.3k
Alfonso Renart Spain 15 1.6k 1.2× 349 0.3× 796 1.0× 174 0.6× 382 2.8× 25 1.8k
Paweł Hottowy Poland 21 1.1k 0.8× 901 0.8× 1.6k 2.1× 91 0.3× 119 0.9× 49 2.0k
Jaime de la Rocha Spain 14 1.9k 1.4× 333 0.3× 1.1k 1.4× 132 0.4× 527 3.9× 24 2.0k
Rubén Moreno‐Bote Spain 26 2.3k 1.6× 234 0.2× 668 0.9× 219 0.7× 462 3.4× 62 2.6k
Srdjan Ostojic France 21 1.4k 1.0× 372 0.3× 562 0.7× 293 1.0× 455 3.4× 48 1.7k

Countries citing papers authored by Abigail Morrison

Since Specialization
Citations

This map shows the geographic impact of Abigail Morrison's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Abigail Morrison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abigail Morrison more than expected).

Fields of papers citing papers by Abigail Morrison

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Abigail Morrison. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Abigail Morrison. The network helps show where Abigail Morrison may publish in the future.

Co-authorship network of co-authors of Abigail Morrison

This figure shows the co-authorship network connecting the top 25 collaborators of Abigail Morrison. A scholar is included among the top collaborators of Abigail Morrison based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Abigail Morrison. Abigail Morrison is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Diaz-Pier, Sandra, et al.. (2024). Multiscale co-simulation design pattern for neuroscience applications. Frontiers in Neuroinformatics. 18. 1156683–1156683.
3.
Dahmen, David, et al.. (2023). Signal denoising through topographic modularity of neural circuits. eLife. 12.
4.
Golosio, Bruno, et al.. (2023). Runtime Construction of Large-Scale Spiking Neuronal Network Models on GPU Devices. Applied Sciences. 13(17). 9598–9598. 4 indexed citations
5.
Illing, Bernd, et al.. (2023). NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways. Proceedings of the National Academy of Sciences. 120(32). e2300558120–e2300558120. 10 indexed citations
6.
Diaz-Pier, Sandra, et al.. (2023). Emergent communication enhances foraging behavior in evolved swarms controlled by spiking neural networks. Swarm Intelligence. 18(1). 1–29. 5 indexed citations
7.
Duarte, Renato, et al.. (2022). Source code for "Towards reproducible models of sequence learning: replication and analysis of a modular spiking network with reward-based learning". Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
8.
Terhorst, D., et al.. (2021). NEST 3.1. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
9.
Tetzlaff, Tom, et al.. (2020). Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer’s disease. PLoS Computational Biology. 16(8). e1007790–e1007790. 11 indexed citations
10.
11.
Duarte, Renato & Abigail Morrison. (2019). Leveraging heterogeneity for neural computation with fading memory in layer 2/3 cortical microcircuits. PLoS Computational Biology. 15(4). e1006781–e1006781. 19 indexed citations
12.
Eppler, Jochen Martin, et al.. (2018). Automatically Selecting a Suitable Integration Scheme for Systems of Differential Equations in Neuron Models. Frontiers in Neuroinformatics. 12. 50–50. 6 indexed citations
13.
Duarte, Renato, et al.. (2017). Synaptic patterning and the timescales of cortical dynamics. Current Opinion in Neurobiology. 43. 156–165. 25 indexed citations
14.
Eppler, Jochen Martin, Alexander Peyser, Abigail Morrison, et al.. (2015). NEST 2.8.0. Zenodo (CERN European Organization for Nuclear Research). 17 indexed citations
15.
Kunkel, Susanne, Maximilian Schmidt, Jochen Martin Eppler, et al.. (2014). Spiking network simulation code for petascale computers. Frontiers in Neuroinformatics. 8. 78–78. 64 indexed citations
16.
Morrison, Abigail, et al.. (2013). Increasing quality and managing complexity in neuroinformatics software development with continuous integration. Frontiers in Neuroinformatics. 6. 31–31. 8 indexed citations
17.
Schrader, Sven, Markus Diesmann, & Abigail Morrison. (2011). A Compositionality Machine Realized by a Hierarchic Architecture of Synfire Chains. Frontiers in Computational Neuroscience. 4. 154–154. 12 indexed citations
18.
Hanuschkin, Alexander, Markus Diesmann, & Abigail Morrison. (2011). A reafferent and feed-forward model of song syntax generation in the Bengalese finch. Journal of Computational Neuroscience. 31(3). 509–532. 23 indexed citations
19.
Hanuschkin, Alexander, Susanne Kunkel, Moritz Helias, Abigail Morrison, & Markus Diesmann. (2010). A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations. Frontiers in Neuroinformatics. 4. 113–113. 43 indexed citations
20.
Morrison, Abigail, et al.. (2010). Enabling Functional Neural Circuit Simulations with Distributed Computing of Neuromodulated Plasticity. Frontiers in Computational Neuroscience. 4. 141–141. 28 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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