Award Abstract # 0954797
CAREER: Bridging epileptogenic molecular level changes to neuronal network synchrony to reveal basic mechanisms of epilepsy

NSF Org: CBET
Division of Chemical, Bioengineering, Environmental, and Transport Systems
Recipient: REGENTS OF THE UNIVERSITY OF MINNESOTA
Initial Amendment Date: July 27, 2010
Latest Amendment Date: January 13, 2016
Award Number: 0954797
Award Instrument: Standard Grant
Program Manager: Michele Grimm
CBET
 Division of Chemical, Bioengineering, Environmental, and Transport Systems
ENG
 Directorate for Engineering
Start Date: August 1, 2010
End Date: September 30, 2016 (Estimated)
Total Intended Award Amount: $422,703.00
Total Awarded Amount to Date: $438,203.00
Funds Obligated to Date: FY 2010 = $422,703.00
FY 2011 = $15,500.00
History of Investigator:
  • Theoden Netoff (Principal Investigator)
    tnetoff@umn.edu
Recipient Sponsored Research Office: University of Minnesota-Twin Cities
2221 UNIVERSITY AVE SE STE 100
MINNEAPOLIS
MN  US  55414-3074
(612)624-5599
Sponsor Congressional District: 05
Primary Place of Performance: University of Minnesota-Twin Cities
2221 UNIVERSITY AVE SE STE 100
MINNEAPOLIS
MN  US  55414-3074
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): KABJZBBJ4B54
Parent UEI:
NSF Program(s): Disability & Rehab Engineering
Primary Program Source: 01001112DB NSF RESEARCH & RELATED ACTIVIT
01001011DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 1045, 9251, 010E, 1187
Program Element Code(s): 534200
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

PI: Netoff, Theoden I.
Proposal Number: 0954797

The etiologies of pathological behaviors that emerge in networks are especially difficult to diagnose. The causes are usually subtle changes in the dynamics of the nodes that lead to changes in population behavior. These multi-scale problems are very general. Epilepsy is an example of disease where molecular level changes in neurons caused by genetic mutations lead to pathological neuronal activity generating seizures. While there are many hypotheses, very little is known about how and why these mutations cause seizures, which prevents us from developing better treatments. Understanding how synchrony in networks are affected by known epileptogenic mutations and antiepileptic drugs with known molecular effects will provide a model system in which multiple scales may be bridged. A synergistic approach using numerical simulations electrophysiology experiments and computational simulations will be used. Computational models of neurons will be used to predict how epileptogenic mutations and antiepileptic drugs change the phase response curve (PRC) of a neuron. The PRC is a measure of a neuron?s sensitivity to synaptic inputs. From the PRC it is possible to infer how changes caused by epileptogenic mutations and antiepileptic drugs would alter synchrony in a network of neurons. Predictions from the modeling will be tested using dynamic clamp experiments, where a computer running a real-time interface is interfaced to a neuron through a patch clamp amplifier and electrode. Dynamic clamp experiments will be used to measure the effects of epileptogenic mutations (introduced thorough electrical knock-in) and bath applied antiepileptic drugs on the phase response curve of the neuron. Hybrid networks will then be created using the dynamic clamp to simulate synaptic connections between two patch clamped neurons in which effects of epileptogenic mutations and antiepileptic drugs on synchrony will be measured directly. Physiological experiments will be used to provide parameters to run large scale simulations where synchrony will be measured. Preliminary data is presented from simulations and electrophsiological experiments that epileptogenic mutations in voltage gated sodium channels decrease synchrony and antiepileptic drugs increase synchrony. These findings are in contrast to the popular view of epilepsy that epilepsy is caused by hypersynchrony. By developing our understanding of how these mutations and drugs actually work, we may develop new and better approaches to treating this disease.

The goal of this proposed research is to test the hypotheses that changes in the dynamics of neurons caused by epileptogenic mutations increase network synchrony, and that the modulation of neurons by drugs that prevent seizures decrease network synchrony. By proving, or disproving these hypotheses, we will understand if developing new drugs or deep brain stimulation to prevent seizures should be optimized to decrease network synchrony. To test this hypothesis we propose the following specific aims: 1) use single cell modeling to identify effects of epileptogenic mutations and antiepileptic drugs on cell dynamics, 2) network modeling to assess the effect of epileptogenic mutations and antiepileptic drugs on network synchrony, and 3) characterize changes in cell dynamics caused by mutation of SCN1A channel using hybrid experiments with real neurons and virtual ion channels.

Intellectual Merit: The research proposed here will help elucidate how changes in neuronal dynamics and topology of network connectivity result in pathological neuronal activity such as seizures. How neuron dynamics are affected by epileptogenic mutations and antiepileptic drugs will be discovered to help develop better models of seizures. Effects of known epileptogenic ion channel mutations and antiepileptic drugs on network synchrony will be used to probe the role of neuronal population synchrony in epilepsy. With this knowledge we will develop more rational approaches to treating epilepsy.

Broader impact: Electrophysiolgy data acquired will be cataloged in a database available to any scientist interested in analyzing the data. To complete the electrophysiolgical experiment, we will generate many modules for the dynamicclamp which will be made available to the community using the RTXI dynamic clamp. Code developed to run network simulations using CUDA enabled machines for supercomputer performance on a desktop will be made available to the public. Outreach plan includes collaborations with the Bakken museum, the Epilepsy Foundation, the University of Minnesota?s ?Brain U?, its summer high school program ?Exploring Careers in Engineering and Physical Science?, and it?s North Star Alliance Program.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 38)
Park Y, Luo L, Parhi KK, Netoff T. "Seizure prediction with spectral power of EEG using cost-sensitive support vector machines." Epilepsia , v.52 , 2011 , p.1761 10.1111/j.1528-1167.2011.03138.x
Bandarabadi M, Rasekhi J, Teixeira CA, Netoff TI, Parhi KK, Dourado A "Early Seizure Detection Using Neuronal Potential Similarity: A Generalized Low-Complexity and Robust Measure." Int J Neural Syst , v.25 , 2015 , p.1550019 10.1142/S0129065715500197
Bandarabadi M, Rasekhi J, Teixeira CA, Netoff TI, Parhi KK, Dourado A. "Early Seizure Detection Using Neuronal Potential Similarity: A Generalized Low-Complexity and Robust Measure." Int J Neural Syst , v.25 , 2015 , p.1550019 10.1142/S0129065715500197
Beverlin B 2nd, Kakalios J, Nykamp D, Netoff TI. "Dynamical changes in neurons during seizures determine tonic to clonic shift." J Comput Neurosci , v.33 , 2012 , p.41 10.1007/s10827-011-0373-5
Beverlin, Bryce, II; Kakalios, James; Nykamp, Duane; Netoff, Theoden Ivan "Dynamical changes in neurons during seizures determine tonic to clonic shift" JOURNAL OF COMPUTATIONAL NEUROSCIENCE , v.33 , 2012 , p.41-51
Beverlin, Bryce, II; Netoff, Theoden I. "Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation" FRONTIERS IN NEURAL CIRCUITS , v.7 , 2013 , p.1
Beverlin Ii B, Netoff TI. "Dynamic control of modeled tonic-clonic seizure states with closed-loop stimulation." Front Neural Circuits , v.6 , 2013 , p.6 10.3389/fncir.2012.00126
Connolly AT, Jensen AL, Bello EM, Netoff TI, Baker KB, Johnson MD, Vitek JL. "Modulations in oscillatory frequency and coupling in globus pallidus with increasing parkinsonian severity." J. Neurosci , v.35 , 2015 10.1523/JNEUROSCI.4137-14.2015
Ermentrout GB, Beverlin B 2nd, Troyer T, Netoff TI. "The variance of phase-resetting curves" J Comput Neurosci. , v.epub , 2011 21207126
Ferguson JE, Boldt C, Puhl JG, Stigen TW, Jackson JC, Crisp KM, Mesce KA, Netoff TI, Redish AD "Nanowires precisely grown on the ends of microwire electrodes permit the recording of intracellular action potentials within deeper neural structures." Nanomedicine (Lond) , v.7 , 2012 , p.847 10.2217/nnm.11.157
Han Xie, Yuehua Zhang, Pingping Zhang, Jingmin Wang, Ye Wu, Xiru Wu, Theoden Netoff , Yuwu Jiang "Functional study of NIPA2 mutations identified from the patients with childhood absence epilepsy" PLOS One , v.9 , 2014 10.1371/journal.pone.0109749
(Showing: 1 - 10 of 38)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The goal of the research supported by this CAREER grant is to understand how epileptogenic mutations and antiepileptic therapies affect neuronal dynamics to generate or stop seizures.  The central hypothesis proposed is that antiepileptic drugs decrease the ability of neurons to synchronize while epileptogenic mutations increase the ability to synchronize.  This hypothesis is being tested both in computational modeling and in in vitro experiments.  From the analysis of the effects of many anti-epileptic drugs and mutations on neuronal dynamics, we have come to the conclusion that anti-epileptic drugs may reduce excitability of neurons while preserving how they interact.  This simple principle could be a guiding principle in new drug design.

Over the life of the grant, the scope of the research has expanded to understanding antiepileptic therapies in general, and in particular how deep brain stimulation may desynchronize neurons to suppress seizures.  This work has resulted in several analytical and experimental tools to help us better understand how neurons synchronize.  We have measured how an input, such as a synaptic input from another cell or a stimulus pulse from a deep brain stimulation, advances or delays the next spike of a neuron, called a phase response curves (PRCs).  From a neuron’s PRC, we can predict how it will synchronize with other neurons and design inputs that desynchronize neuronal populations.  This research has spawned several collaborative grants supporting research designing optimal electrical stimulation waveforms to desynchronize neuronal populations with applications to Parkinson’s disease.

A major emphasis of a CAREER award is outreach and education.  This research helped support the education of 5 graduate students, 7 undergraduates, 3 high school students, and two international visiting scholars.  The Netoff lab has hosted visits from over 100 high school and middle school children during this time.  Members of the lab have also regularly participated in a summer camp for children with epilepsy.  Our outreach effort continues by running an REU program at University of Minnesota that provides summer research opportunities for underrepresented minorities and disadvantaged students spawned to study Neural Systems Engineering.

 


Last Modified: 01/02/2017
Modified by: Theoden I Netoff

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