Predicting excitatory phase resetting curves in bursting neurons

Maran, Selva K; Sieling, Fred H.; Prinz, Astrid A.; Canavier, Carmen C.

doi:10.1186/1471-2202-9-s1-p134

Cited by 3 publications

(4 citation statements)

References 3 publications

(2 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To date these methods have been evaluated both in model networks (Achuthan and Canavier 2009;Canavier et al 1997Canavier et al , 1999Luo et al 2004;Maran et al 2008;Oh and Matveev 2008) and in hybrid networks coupled with inhibition (Oprisan et al 2004). Here we test the applicability of PRC-based firing time maps (Ermentrout and Chow 2002) to excitatory coupling of significant strength and duration, using a wide range of synaptic strengths (from 1 to 10,000 nS) and input durations (from 0.3 to 1.5 s).…”

Section: Introductionmentioning

confidence: 99%

Predictions of Phase-Locking in Excitatory Hybrid Networks: Excitation Does Not Promote Phase-Locking in Pattern-Generating Networks as Reliably as Inhibition

Sieling

Canavier²,

Prinz³

2009

Journal of Neurophysiology

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Predictions of Phase-Locking in Excitatory Hybrid Networks: Excitation Does Not Promote Phase-Locking in Pattern-Generating Networks as Reliably as Inhibition

Sieling

Canavier²,

Prinz³

2009

Journal of Neurophysiology

View full text Add to dashboard Cite

show abstract

“…Thus, prolonged inhibitory currents may serve to modulate excitatory state during either the initiation or maintenance of locomotor rhythm generation (Nadim et al, 2011). Finally, in computational models of single element oscillators, inhibitory inputs have been shown to have stronger and more reliable effects on phase resetting than do excitatory inputs (Oprisan et al, 2003; Maran et al, 2008). Therefore, these strong inhibitory currents may be important for resetting if they persist in the locomotor state.…”

Section: Discussionmentioning

confidence: 99%

Flexor and Extensor Ankle Afferents Broadly Innervate Locomotor Spinal Shox2 Neurons and Induce Similar Effects in Neonatal Mice

Garcia-Ramirez

Dougherty

2019

Front. Cell. Neurosci.

View full text Add to dashboard Cite

Central pattern generators (CPGs) in the thoracolumbar spinal cord generate the basic hindlimb locomotor pattern. The locomotor CPG integrates descending commands and sensory information from the periphery to activate, modulate and halt the rhythmic program. General CPG function and response to sensory perturbations are well described in cat and rat models. In mouse, roles for many genetically identified spinal interneurons have been inferred from locomotor alterations following population deletion or modulation. However, the organization of afferent input to specific genetically identified populations of spinal CPG interneurons in mouse remains comparatively less resolved. Here, we focused on a population of CPG neurons marked by the transcription factor Shox2. To directly test integration of afferent signaling by Shox2 neurons, sensory afferents were stimulated during patch clamp recordings of Shox2 neurons in isolated spinal cord preparations from neonatal mice. Shox2 neurons broadly displayed afferent-evoked currents at multiple segmental levels, particularly from caudal dorsal roots innervating distal hindlimb joints. As dorsal root stimulation may activate both flexor- and extensor-related afferents, preparations preserving peripheral nerves were used to provide more specific activation of ankle afferents. We found that both flexor- and extensor-related afferent stimulation were likely to evoke similar currents in a given Shox2 neuron, as assessed by response polarity, latency, duration and amplitude. It has been proposed that Shox2 neurons can be divided into neurons which contribute to rhythm generation and neurons that are premotor by the absence and presence of the V2a marker Chx10, respectively. Response to afferent stimulation did not differ based on Chx10 expression. Although currents evoked in response to flexor and extensor afferent activation did not follow expected functional antagonism, they were consistent with the observation that stimulation of flexor- and extensor-related afferents both reset the phase of ongoing fictive locomotion to flexion in neonatal mice. Together, the data suggest that Shox2 neurons are interposed in multiple sensory pathways and low threshold proprioceptive input reinforces sensory perturbation of ongoing locomotion by similarly activating or inhibiting both the rhythm and patterning layers of the CPG.

show abstract

“…As a measure of the influence of synaptic stimuli on the firing times of a neuron, we define the spike time response curves (STRC's) Φ j (t, τ R , τ D , g, E R , T 0 ) = Tj −T0 T0 [14,17,18], where T 0 is the intrinsic period of spiking, T j represents the length of the j th spiking cycle from the cycle j = 1 in which the neuron receives synaptic stimuli at time 0 < t < T 0 . The synaptic parameters are: τ R : the synapse rise time, τ D : the synaptic decay time, g: the synaptic strength and E R : the reversal potential of the synapse.…”

mentioning

confidence: 99%

“…The approximation in the form of equation 3, has been used in [19] to determine the effect of second order STRC component on stability of 1:1 synchronous state in a ring of pulse coupled oscillators; in [17] to determine phase resetting and phase locking in a hybrid circuit of one model neuron and one biological neuron and also recently in [18] to predict 1:1 and 2:2 synchrony in mutually coupled network of interneurons with synapse that is hyperpolarizing. In Figure 3a, we plot the percent error E = 100…”

mentioning

confidence: 99%

Synchrony with shunting inhibition

et al. 2009

View full text Add to dashboard Cite

Spike time response curves (STRC's) are used to study the influence of synaptic stimuli on the firing times of a neuron oscillator without the assumption of weak coupling. They allow us to approximate the dynamics of synchronous state in networks of neurons through a discrete map. Linearization about the fixed point of the discrete map can then be used to predict the stability of patterns of synchrony in the network. General theory for taking into account the contribution from higher order STRC terms, in the approximation of the discrete map for coupled neuronal oscillators in synchrony is still lacking. Here we present a general framework to account for higher order STRC corrections in the approximation of discrete map to determine the domain of 1:1 phase locking state in the network of two interacting neurons. We begin by demonstrating that the effects of synaptic stimuli through a shunting synapse to a neuron firing in the gamma frequency band (20-80 Hz) last for three consecutive firing cycles (See Figure 1). We then show that the discrete map derived by taking into account the higher order STRC contributions is successfully able predict the domain of synchronous 1:1 phase locked state in a network of two heterogeneous interneurons coupled through a shunting synapse (See Figure 2).

show abstract

Predicting excitatory phase resetting curves in bursting neurons

Cited by 3 publications

References 3 publications

Predictions of Phase-Locking in Excitatory Hybrid Networks: Excitation Does Not Promote Phase-Locking in Pattern-Generating Networks as Reliably as Inhibition

Predictions of Phase-Locking in Excitatory Hybrid Networks: Excitation Does Not Promote Phase-Locking in Pattern-Generating Networks as Reliably as Inhibition

Flexor and Extensor Ankle Afferents Broadly Innervate Locomotor Spinal Shox2 Neurons and Induce Similar Effects in Neonatal Mice

Synchrony with shunting inhibition

Contact Info

Product

Resources

About