Daniel Margoliash, PhD

Neuroethology investigates nervous system function by relating it to innate and learned natural behaviors. It is distinguished from traditional neurobiology and psychology by being fundamentally centered in evolutionary biology, and by examining behavioral specialization across the breadth of the animal kingdom. We study multiple facets of birdsong learning, from cellular to behavioral levels of analysis, taking the neuroethological perspective.

Washington University
St. Louis
Postdoc - Bat auditory cortex
1986

California Institute of Technology
Pasadena
Ph.D. - Engineerg Science and Neurobiology; Birdsong electrophysiology
1983

California Institute of Technology
Pasadena
M.Sc. - BioInformation Systems
1981

California Institute of Technology
Pasadena
B.Sc. - Biology
1975

Intrinsic plasticity and birdsong learning.
Daou A, Margoliash D. Intrinsic plasticity and birdsong learning. Neurobiol Learn Mem. 2021 04; 180:107407.
PMID: 33631346

Budgerigars have complex sleep structure similar to that of mammals.
Canavan SV, Margoliash D. Budgerigars have complex sleep structure similar to that of mammals. PLoS Biol. 2020 11; 18(11):e3000929.
PMID: 33201883

Rhythm: Similar Structure in Birdsong and Music Gives Neuroethological Insight.
Margoliash D. Rhythm: Similar Structure in Birdsong and Music Gives Neuroethological Insight. Curr Biol. 2020 09 21; 30(18):R1056-R1058.
PMID: 32961164

Intrinsic neuronal properties represent song and error in zebra finch vocal learning.
Daou A, Margoliash D. Intrinsic neuronal properties represent song and error in zebra finch vocal learning. Nat Commun. 2020 02 19; 11(1):952.
PMID: 32075972

Sleep-dependent reconsolidation after memory destabilization in starlings.
Brawn TP, Nusbaum HC, Margoliash D. Sleep-dependent reconsolidation after memory destabilization in starlings. Nat Commun. 2018 08 06; 9(1):3093.
PMID: 30082791

Differential development of retroactive and proactive interference during post-learning wakefulness.
Brawn TP, Nusbaum HC, Margoliash D. Differential development of retroactive and proactive interference during post-learning wakefulness. Learn Mem. 2018 07; 25(7):325-329.
PMID: 29907640

Response to "Comment on 'A unifying view of synchronization for data assimilation in complex nonlinear networks'" [Chaos 28, 028101 (2018)].
Abarbanel HDI, Shirman S, Breen D, Kadakia N, Rey D, Armstrong E, Margoliash D. Response to "Comment on 'A unifying view of synchronization for data assimilation in complex nonlinear networks'" [Chaos 28, 028101 (2018)]. Chaos. 2018 02; 28(2):028102.
PMID: 29495669

A unifying view of synchronization for data assimilation in complex nonlinear networks.
Abarbanel HDI, Shirman S, Breen D, Kadakia N, Rey D, Armstrong E, Margoliash D. A unifying view of synchronization for data assimilation in complex nonlinear networks. Chaos. 2017 Dec; 27(12):126802.
PMID: 29289057

Nonlinear statistical data assimilation for HVC[Formula: see text] neurons in the avian song system.
Kadakia N, Armstrong E, Breen D, Morone U, Daou A, Margoliash D, Abarbanel HD. Nonlinear statistical data assimilation for HVC[Formula: see text] neurons in the avian song system. Biol Cybern. 2016 12; 110(6):417-434.
PMID: 27688218

Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data.
Nogaret A, Meliza CD, Margoliash D, Abarbanel HD. Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data. Sci Rep. 2016 09 08; 6:32749.
PMID: 27605157

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