Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Computational subunits in thin dendrites of pyramidal cells
2004565 citationsAlon Poleg-Polsky, Bartlett W. Mel et al.profile →
Countries citing papers authored by Bartlett W. Mel
Since
Specialization
Citations
This map shows the geographic impact of Bartlett W. Mel'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 Bartlett W. Mel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bartlett W. Mel more than expected).
This network shows the impact of papers produced by Bartlett W. Mel. 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 Bartlett W. Mel. The network helps show where Bartlett W. Mel may publish in the future.
Co-authorship network of co-authors of Bartlett W. Mel
This figure shows the co-authorship network connecting the top 25 collaborators of Bartlett W. Mel.
A scholar is included among the top collaborators of Bartlett W. Mel 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 Bartlett W. Mel. Bartlett W. Mel is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Archie, Kevin A. & Bartlett W. Mel. (2000). Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual Stimuli. Neural Information Processing Systems. 13. 82–88.4 indexed citations
12.
Poirazi, Panayiota & Bartlett W. Mel. (1999). Memory Capacity of Linear vs. Nonlinear Models of Dendritic Integration. Neural Information Processing Systems. 12. 157–163.2 indexed citations
13.
Mel, Bartlett W., Daniel Ruderman, & Kevin A. Archie. (1997). Toward a Single-Cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your Dendrites. Neural Information Processing Systems. 10. 208–214.2 indexed citations
14.
Mel, Bartlett W., Daniel Ruderman, & Kevin A. Archie. (1996). Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation. Neural Information Processing Systems. 9. 83–89.3 indexed citations
Mel, Bartlett W.. (1991). The Clusteron: Toward a Simple Abstraction for a Complex Neuron. CaltechAUTHORS (California Institute of Technology). 4. 35–42.57 indexed citations
17.
Mel, Bartlett W. & Stephen M. Omohundro. (1990). How Receptive Field Parameters Affect Neural Learning. Neural Information Processing Systems. 3. 757–763.10 indexed citations
18.
Mel, Bartlett W. & Christof Koch. (1989). Sigma-Pi Learning: On Radial Basis Functions and Cortical Associative Learning. Neural Information Processing Systems. 2. 474–481.34 indexed citations
19.
Mel, Bartlett W.. (1988). Further Explorations in Visually-Guided Reaching: Making MURPHY Smarter. Neural Information Processing Systems. 1. 348–355.4 indexed citations
20.
Mel, Bartlett W.. (1987). MURPHY: A Robot that Learns by Doing. Neural Information Processing Systems. 544–553.40 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.