Author

Cesar Santana‐Gomez

University of California, Los AngelesORCID 0000-0001-9163-5615Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 4

Signature Assays, Organisms & Methods

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Assay:electronic health records· 3 Organism:rat· 3 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

Richard J. StabaiD· 4 shared Neil G. HarrisiD· 3 shared Mohamad ShamasiD· 2 shared Aarja Pavade· 1 shared Aria FallahiD· 1 shared Atsuro DaidaiD· 1 shared Ava MousaviiD· 1 shared G. Smith· 1 shared

Activity by Year

2024-2025 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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4 shared papersNeuroscience

Richard J. StabaORCID

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4 papers

Recent·Most cited

NeuroscienceExperimental NeurologyPeer-reviewedJun 4, 2025

Unbiased Population-Based Statistics to Obtain Pathologic Burden of Injury after Experimental TBI

G. Smith, Cesar Santana‐Gomez, Richard J. Staba, Neil G. Harris

The paper introduces an unbiased whole-brain analysis method to quantify injury burden after traumatic brain injury, showing it is statistically robust and captures longitudinal changes without preselected ROIs.

1 citation

ratimaging

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NeurosciencebioRxivPreprintJun 28, 2024

The Surgical Method of Craniectomy Differentially Affects Acute Seizures, Brain Deformation and Behavior in a TBI Animal Model

Cesar Santana‐Gomez, Gregory Smith, Ava Mousavi…·Richard J. Staba

This study compares the effects of hand and electric drilling craniectomy on TBI in rats, finding that electric drilling causes more tissue damage and seizures.

DOI 10.1101/2024.06.28.601257

ratelectronic health records

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NeuroscienceJournal of Neural EngineeringPeer-reviewedMay 9, 2024

PyHFO: Lightweight Deep Learning-poweredEnd-to-End High-Frequency Oscillations AnalysisApplication

Yipeng Zhang, Lawrence Liu, Yuanyi Ding…·Vwani Roychowdhury

PyHFO is a lightweight deep learning platform for efficient HFO detection in EEG data, achieving 50x speed improvements over standard methods.

19 citationstop 4%

electronic health recordsdeep learning

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NeuroscienceNeurotrauma ReportsPeer-reviewedMay 1, 2024

Different Trajectories of Functional Connectivity Captured with Gamma-Event Coupling and Broadband Measures of EEG in the Rat Fluid Percussion Injury Model.

Rachel Fox, Cesar Santana‐Gomez, Mohamad Shamas…·Neil G. Harris

This study compares two functional connectivity measures in a rat TBI model, finding distinct temporal and spatial changes in connectivity patterns post-injury.

6 citations

ratelectronic health records

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