The activity phase of postsynaptic neurons (Bose et al 2004)

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Accession:45513
We show, in a simplified network consisting of an oscillator inhibiting a follower neuron, how the interaction between synaptic depression and a transient potassium current in the follower neuron determines the activity phase of this neuron. We derive a mathematical expression to determine at what phase of the oscillation the follower neuron becomes active. This expression can be used to understand which parameters determine the phase of activity of the follower as the frequency of the oscillator is changed. See paper for more.
Reference:
1 . Bose A, Manor Y, Nadim F (2004) The activity phase of postsynaptic neurons in a simplified rhythmic network. J Comput Neurosci 17:245-61 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Stomatogastric ganglion;
Cell Type(s): Abstract Morris-Lecar neuron;
Channel(s): I A;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: XPP; MATLAB;
Model Concept(s): Activity Patterns; Bursting; Temporal Pattern Generation; Oscillations; Simplified Models;
Implementer(s): Nadim, Farzan [Farzan at andromeda.Rutgers.edu]; Bose, Amitabha [bose at njit.edu]; Lewis, Timothy [tlewis at cns.nyu.edu];
Search NeuronDB for information about:  I A;
  
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activityphase
readme.txt
DBdep+A.ode
DBdep+A.ode.set
DBjcns1.m
DBjcns2.m
DBjcns3.m
                            
This is the readme.txt for the models associated with the paper

Bose A, Manor Y, Nadim F. The activity phase of postsynaptic neurons in a 
simplified rhythmic network. J Comput Neurosci. 2004

Abstract:

Many inhibitory rhythmic networks produce activity in a range of frequencies.
The relative phase of activity between neurons in these networks is often a 
determinant of the network output. This relative phase is determined by the 
interaction between synaptic inputs to the neurons and their intrinsic 
properties. We show, in a simplified network consisting of an oscillator 
inhibiting a follower neuron, how the interaction between synaptic depression
and a transient potassium current in the follower neuron determines the 
activity phase of this neuron. We derive a mathematical expression to 
determine at what phase of the oscillation the follower neuron becomes 
active. This expression can be used to understand which parameters determine
the phase of activity of the follower as the frequency of the oscillator is 
changed. We show that in the presence of synaptic depression, there can be 
three distinct frequency intervals, in which the phase of the follower neuron
is determined by different sets of parameters. Alternatively, when the 
synapse is not depressing, only one set of parameters determines the phase of
activity at all frequencies.

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This model is a a Morris-Lecar system with IA and depression.
The interesting phase plane for the "middle" branch is the v vs. ha. 
Note also that the v vs w phase plane can have a quintic v nullcline.

To run the models:
Matlab: after you add the path of the activityphase directory start the 
DBjcns1.m file.  It will compute and display fig 9D.

XPP: start with the command
xpp DBdep+A.ode

Click File, Read Set and then DBdep+A.ode.set
Type i g for Initial Conditions Go. 
You should see the voltage trace shown in Figure 10 corresponding to the 
unscaled version of Period = 800 (lower left).  You can change the period
by changing the parameter per.

Bard Ermentrout's website http://www.pitt.edu/~phase/
describes how to get and use xpp (Bard wrote xpp).

Bose A, Manor Y, Nadim F (2004) The activity phase of postsynaptic neurons in a simplified rhythmic network. J Comput Neurosci 17:245-61[PubMed]

References and models cited by this paper

References and models that cite this paper

Ahissar E, Sosnik R, Haidarliu S (2000) Transformation from temporal to rate coding in a somatosensory thalamocortical pathway. Nature 406:302-6 [PubMed]

Bartos M, Manor Y, Nadim F, Marder E, Nusbaum MP (1999) Coordination of fast and slow rhythmic neuronal circuits. J Neurosci 19:6650-60 [PubMed]

Bose A, Manor Y, Nadim F (2001) Bistable oscillations arising from synaptic depression. Siam J Appl Math 62:706-727

Buchholtz F, Golowasch J, Epstein IR, Marder E (1992) Mathematical model of an identified stomatogastric ganglion neuron. J Neurophysiol 67:332-40 [Journal] [PubMed]

Connor JA, Stevens CF (1971) Voltage clamp studies of a transient outward membrane current in gastropod neural somata. J Physiol 213:21-30 [PubMed]

Connor JA, Walter D, McKown R (1977) Neural repetitive firing: modifications of the Hodgkin-Huxley axon suggested by experimental results from crustacean axons. Biophys J 18:81-102 [PubMed]

Dicaprio R, Jordan G, Hampton T (1997) Maintenance of motor pattern phase relationships in the ventilatory system of the crab J Exp Biol 200:963-74 [PubMed]

Ermentrout GB (2002) Simulating, Analyzing, and Animating Dynamical System: A Guide to XPPAUT for Researchers and Students Society for Industrial and Applied Mathematics (SIAM)

Harris-Warrick RM, Coniglio LM, Barazangi N, Guckenheimer J, Gueron S (1995) Dopamine modulation of transient potassium current evokes phase shifts in a central pattern generator network. J Neurosci 15:342-58 [PubMed]

Hess D, El Manira A (2001) Characterization of a high-voltage-activated IA current with a role in spike timing and locomotor pattern generation. Proc Natl Acad Sci U S A 98:5276-81 [PubMed]

Hooper SL (1997) Phase maintenance in the pyloric pattern of the lobster (Panulirus interruptus) stomatogastric ganglion. J Comput Neurosci 4:191-205 [Journal] [PubMed]

Hooper SL (1997) The pyloric pattern of the lobster (Panulirus interruptus) stomatogastric ganglion comprises two phase-maintaining subsets. J Comput Neurosci 4:207-19 [Journal] [PubMed]

Hsiao CF, Chandler SH (1995) Characteristics of a fast transient outward current in guinea pig trigeminal motoneurons. Brain Res 695:217-26 [PubMed]

Laurent G, Wehr M, Davidowitz H (1996) Temporal representations of odors in an olfactory network. J Neurosci 16:3837-47 [PubMed]

Manor Y, Bose A, Booth V, Nadim F (2003) The contribution of synaptic depression to phase maintenance in a model rhythmic network. J Neurophysiol : [Journal] [PubMed]

Marder E, Calabrese RL (1996) Principles of rhythmic motor pattern generation. Physiol Rev 76:687-717 [PubMed]

Mishchenko EF, Rozov NK (1980) Differential Equations with Small Parameters and Relaxation Oscillators

Morris C, Lecar H (1981) Voltage oscillations in the barnacle giant muscle fiber. Biophys J 35:193-213 [Journal] [PubMed]

   Morris-Lecar model of the barnacle giant muscle fiber (Morris, Lecar 1981) [Model]

O'Keefe J, Recce ML (1993) Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus 3:317-30 [PubMed]

Pearson KG, Iles JF (1970) Discharge patterns of coxal levator and depressor motoneurones of the cockroach, Periplaneta americana. J Exp Biol 52:139-65

Rinzel J, Ermentrout G (1997) Methods in Neuronal Modeling: From Synapses to Networks, Koch C:Segev I, ed. pp.135

Rush ME, Rinzel J (1995) The potassium A-current, low firing rates and rebound excitation in Hodgkin-Huxley models. Bull Math Biol 57:899-929 [PubMed]

Skinner FK, Mulloney B (1998) Intersegmental coordination of limb movements during locomotion: mathematical models predict circuits that drive swimmeret beating. J Neurosci 18:3831-42 [PubMed]

Storm JF (1990) Potassium currents in hippocampal pyramidal cells. Prog Brain Res 83:161-87 [PubMed]

Thompson SH (1977) Three pharmacologically distinct potassium channels in molluscan neurones. J Physiol 265:465-88 [PubMed]

(25 refs)