Duane Q Nykamp
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Explore the profile of Duane Q Nykamp including associated specialties, affiliations and a list of published articles.
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15
Citations
388
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Recent Articles
1.
Kim C, Nykamp D
J Comput Neurosci
. 2017 May;
43(1):65-79.
PMID: 28528529
The inhibitory restraint necessary to suppress aberrant activity can fail when inhibitory neurons cease to generate action potentials as they enter depolarization block. We investigate possible bifurcation structures that arise...
2.
Nykamp D, Friedman D, Shaker S, Shinn M, Vella M, Compte A, et al.
Phys Rev E
. 2017 May;
95(4-1):042323.
PMID: 28505854
The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies,...
3.
Bump attractor dynamics in prefrontal cortex explains behavioral precision in spatial working memory
Wimmer K, Nykamp D, Constantinidis C, Compte A
Nat Neurosci
. 2014 Feb;
17(3):431-9.
PMID: 24487232
Prefrontal persistent activity during the delay of spatial working memory tasks is thought to maintain spatial location in memory. A 'bump attractor' computational model can account for this physiology and...
4.
Day N, Terleski K, Nykamp D, Nick T
J Neurophysiol
. 2012 Nov;
109(4):913-23.
PMID: 23175804
Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no...
5.
Koelling M, Nykamp D
J Comput Neurosci
. 2012 May;
33(3):449-73.
PMID: 22580579
Many methods used to analyze neuronal response assume that neuronal activity has a fundamentally linear relationship to the stimulus. However, some neurons are strongly sensitive to multiple directions in stimulus...
6.
Zhao L, Beverlin 2nd B, Netoff T, Nykamp D
Front Comput Neurosci
. 2011 Jul;
5:28.
PMID: 21779239
We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes...
7.
Koelling M, Nykamp D
Network
. 2008 Nov;
19(4):286-313.
PMID: 18991145
We present an approach to obtain nonlinear information about neuronal response by computing multiple linear approximations. By calculating local linear approximations centered around particular stimuli, one can obtain insight into...
8.
Liu C, Nykamp D
J Comput Neurosci
. 2008 Nov;
26(3):339-68.
PMID: 18987967
We present an approach for using kinetic theory to capture first and second order statistics of neuronal activity. We coarse grain neuronal networks into populations of neurons and calculate the...
9.
Nykamp D
Phys Rev E Stat Nonlin Soft Matter Phys
. 2008 Oct;
78(2 Pt 1):021902.
PMID: 18850860
The effects of hidden nodes can lead to erroneous identification of connections among measured nodes in a network. For example, common input from a hidden node may cause correlations among...
10.
Nykamp D
J Math Biol
. 2008 Oct;
59(2):147-73.
PMID: 18830595
We present an analysis of interactions among neurons in stimulus-driven networks that is designed to control for effects from unmeasured neurons. This work builds on previous connectivity analyses that assumed...