Author

Laleh Najafizadeh

Rutgers, The State University of New JerseyORCID 0000-0002-6658-4112Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Assay:electronic health records· 1 Approach:experimental assay· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

Aastha Suvarnakar· 1 shared Ali HaddadiD· 1 shared David J. MargolisiD· 1 shared Foroogh ShamsiiD· 1 shared Janet AlderiD· 1 shared Jennifer L. FangiD· 1 shared Nicholas Fliss· 1 shared Shavonne L. TengiD· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperNeuroscience

Aastha Suvarnakar

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2 papers

Recent·Most cited

Imaging the large-scale and cellular response to focal traumatic brain injury in mouse neocortex

Yelena Bibineyshvili, Thomas J. Vajtay, Shiva Salsabilian, Nicholas Fliss, Aastha Suvarnakar, Jennifer L. Fang, Shavonne L. Teng, Janet Alder, Laleh Najafizadeh, David J. Margolis

This study uses in vivo calcium imaging to examine neural activity and behavioral changes in mice after focal traumatic brain injury, revealing spatial and temporal adaptations in the cortex.

Experimental Physiology · Nov 22, 2024Peer-reviewedNeuroscience

Early Classification of Motor Tasks Using Dynamic Functional Connectivity Graphs from EEG

Foroogh Shamsi, Ali Haddad, Laleh Najafizadeh

This paper introduces a method to classify motor tasks from EEG signals with high accuracy using short recording intervals, achieving 85.32% accuracy within 500 ms.

Journal of Neural Engineering · Nov 27, 2020Peer-reviewedNeuroscience