Daniel F. Liu

1.5k total citations
13 papers, 762 citations indexed

About

Daniel F. Liu is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Daniel F. Liu has authored 13 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 11 papers in Cellular and Molecular Neuroscience and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Daniel F. Liu's work include Memory and Neural Mechanisms (9 papers), Neural dynamics and brain function (8 papers) and Neuroscience and Neuropharmacology Research (8 papers). Daniel F. Liu is often cited by papers focused on Memory and Neural Mechanisms (9 papers), Neural dynamics and brain function (8 papers) and Neuroscience and Neuropharmacology Research (8 papers). Daniel F. Liu collaborates with scholars based in United States, Germany and China. Daniel F. Liu's co-authors include Loren M. Frank, Jason E. Chung, Mattias Karlsson, Kenneth Kay, Marielena Sosa, Uri T. Eden, Jonathan S. Schor, Hexin Liang, Na Ji and Charlotte Geaghan-Breiner and has published in prestigious journals such as Cell, Nature Communications and Neuron.

In The Last Decade

Daniel F. Liu

13 papers receiving 755 citations

Peers

Daniel F. Liu

CN

CMN

EEE

BE

PP

Hannah R. Joo United States

Alexey Pimashkin Russia

Richárd Fiáth Hungary

Ruiqing Hou China

Shabnam Kadir United Kingdom

Marius Bauža United Kingdom

Vanessa Tolosa United States

Cyrille Rossant United Kingdom

Jakob Voigts United States

Irina Erchova United Kingdom

Hannah R. Joo United States

Daniel F. Liu

510 ×0.9

CN

535 ×0.9

CMN

94 ×0.7

EEE

58 ×0.7

BE

29 ×0.7

PP

Citations per year, relative to Daniel F. Liu Daniel F. Liu (= 1×) peers Hannah R. Joo

Countries citing papers authored by Daniel F. Liu

Since Specialization

Citations

This map shows the geographic impact of Daniel F. Liu'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 Daniel F. Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel F. Liu more than expected).

Fields of papers citing papers by Daniel F. Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel F. Liu. 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 Daniel F. Liu. The network helps show where Daniel F. Liu may publish in the future.

Co-authorship network of co-authors of Daniel F. Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel F. Liu. A scholar is included among the top collaborators of Daniel F. Liu 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 Daniel F. Liu. Daniel F. Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

1.

Coulter, Michael E., Anna K. Gillespie, Eric L. Denovellis, et al.. (2025). Closed-loop modulation of remote hippocampal representations with neurofeedback. Neuron. 113(6). 949–961.e3. 1 indexed citations

2.

Kastner, David B., et al.. (2022). Spatial preferences account for inter-animal variability during the continual learning of a dynamic cognitive task. Cell Reports. 39(3). 110708–110708. 3 indexed citations

3.

Zhao, Zhengtuo, Hanlin Zhu, Xue Li, et al.. (2022). Ultraflexible electrode arrays for months-long high-density electrophysiological mapping of thousands of neurons in rodents. Nature Biomedical Engineering. 7(4). 520–532. 106 indexed citations

4.

Gillespie, Anna K., Eric L. Denovellis, Daniel F. Liu, et al.. (2021). Hippocampal replay reflects specific past experiences rather than a plan for subsequent choice. Neuron. 109(19). 3149–3163.e6. 89 indexed citations

5.

Kay, Kenneth, Jason E. Chung, Marielena Sosa, et al.. (2020). Constant Sub-second Cycling between Representations of Possible Futures in the Hippocampus. Cell. 180(3). 552–567.e25. 159 indexed citations

6.

Joo, Hannah R., Na Ji, Supin Chen, et al.. (2019). A microfabricated, 3D-sharpened silicon shuttle for insertion of flexible electrode arrays through dura mater into brain. Journal of Neural Engineering. 16(6). 66021–66021. 43 indexed citations

7.

Yu, Jai Y., et al.. (2018). Specific hippocampal representations are linked to generalized cortical representations in memory. Nature Communications. 9(1). 2209–2209. 39 indexed citations

8.

Chung, Jason E., Hannah R. Joo, Na Ji, et al.. (2018). High-Density, Long-Lasting, and Multi-region Electrophysiological Recordings Using Polymer Electrode Arrays. Neuron. 101(1). 21–31.e5. 218 indexed citations

9.

Yu, Jai Y., Kenneth Kay, Daniel F. Liu, et al.. (2017). Distinct hippocampal-cortical memory representations for experiences associated with movement versus immobility. eLife. 6. 29 indexed citations

10.

Liu, Daniel F., et al.. (2016). Rapid classification of hippocampal replay content for real-time applications. Journal of Neurophysiology. 116(5). 2221–2235. 15 indexed citations

11.

Liu, Daniel F., et al.. (2015). Decoding position from multiunit activity using a marked point process filter. BMC Neuroscience. 16(S1). 2 indexed citations

12.

Liu, Daniel F., et al.. (2015). Clusterless Decoding of Position from Multiunit Activity Using a Marked Point Process Filter. Neural Computation. 27(7). 1438–1460. 42 indexed citations

13.

Du, Haitao, et al.. (2010). Toward Ensemble Characterization and Projection of Multistage Cyber Attacks. 1–8. 16 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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