The abrupt transition from theta to hyper- excitable spiking activity in stellate cells from layer II of the medial entorhinal cortex Horacio G. Rotstein Department of Mathematical Sciences New Jersey Institute of Technology Network Synchronization: From dynamical systems to neuroscience Leiden (NL) - May 27, 2008

Collaborators  Tilman Kispersky Program in Neuroscience - Boston University  Nancy Kopell Math & Center for BioDynamics – Boston University  Martin Wechselberger Math – University of Sidney  John White Biomedical Engineering – University of Utah

Entorhinal Cortex & Hippocampus Photomicrograph of a section through the rat hippocampal region (Gluck & Myers). Adapted from Amaral & Witter (1989). Photomicrograph of a section through the rat hippocampal region (Gluck & Myers). Adapted from Amaral & Witter (1989)

Stellate cells (SCs)  Entorhinal cortex (EC) is the interface between the neocortex and the hippocampus.  Information flows from the neocortex to the hippocampus through the superficial layers (II and III) of the EC.  SCs are the most abundant cell type in layer II of the EC.  SCs are putative grid cells.

Subthreshold oscillations (STOs)  SCs develop rhythmic STOs at theta frequencies (8 – 12 Hz).  Spikes occur at the peaks of STOs but not at every cycle.  Interaction between two currents: h- and persistent sodium.  Single cell phenomenon Depolarization increases from 1 to 3 (Adapted from Dickson et al., J. Neurophysiol., 2000)

SCs: Theta regime (background)  SCs have intrinsic biophysical properties that endow them with the ability to display rhythmic activity in the theta frequency regime (8 – 12 Hz)  Subthreshold oscillations (STOs): interaction between a persistent sodium and a hyperpolarization-activated (h-) current.  Spikes  Mixed-mode oscillations (MMOs): STOs interspersed with spikes R., Oppermann, White, Kopell (JCNS – 2005) R., Wechselberger, Kopell (Submitted) Focus issue on MMOs (Chaos 2008)

SCs – Hyperexcitable regime (this project)  SCs have intrinsic biophysical properties that endow them with the ability to display spiking activity in the “gamma” frequency regime (~60 Hz).  This time scale can be uncovered by phasic excitation.  The frequency regime depends on a combination of intrinsic and network properties. Kispersky, White & R., Work in Progress.

SC dynamic structure Nonlinearities and multiple time-scales in the subthreshold regime:  How are they created?  How do they depend on the intrinsic SC biophysical properties?  How do they interact with synaptic (excitatory and inhibitory) inputs?

SC biophysical model

Subthreshold oscillations (STOs) and spikes in the SC model

STOs generated by persistent sodium channel noise in the SC model

Subthreshold Regime: Reduction of Dimensions Multiscale analysis:  Identification of the active and inactive currents  Identification of the appropriate time scales

Subthreshold Regime: Reduction of Dimensions Multiscale analysis:  Identification of the active and inactive currents  Identification of the appropriate time scales

Subthreshold regime: reduced SC model SC biophysical model Subthreshold regime

Subthreshold regime: reduced SC model

SC biophysical model Subthreshold regime

Subthreshold regime: reduced SC model

Nonlinear Artificially Spiking (NAS) SC model

Inhibitory inputs can advance the next spike by “killing” an STO.

Transition from theta to hyper-excitable (gamma) rhythmic activity Experimental (in vitro) results:  There exist recurrent connections among SCs.  These connections are “similar” in normal (control) and epileptic cells.  Recurrent inhibitory circuits are reduced in epileptic cells as compared to normal (control) ones. Recurrent circuits in layer II of MEC in a model of temporal lobe epilepsy. Kumar, Buckmaster, Huguenard, J. Neurosci. (2007)

Minimal S-I network model

 A minimal S-S network reproduces the experimentally found transition form normal activity to hyper- excitability in SCs due to lack of inhibition

Minimal S-I network model  A minimal SIS network reproduces the experimentally found transition form normal activity to hyper- excitability in SCs due to lack of inhibition

Minimal SC network model (no inhibition)  A small increase in the SC recurrent synaptic conductance causes an explosion of the SC firing frequency

Minimal SC network model (no inhibition)  A small increase in the SC recurrent synaptic conductance causes an explosion of the SC firing frequency

Minimal S-I network model  A small increase in the inhibitory input to the SCs brings their frequency back to the theta regime

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation Single SC model representing a population of synchronized (in phase) SCs.

Single SC + autapse (no inhibition)  Effects of changes in the maximal conductances

Single SC + autapse (no inhibition)  Effects of changes in the maximal conductances

Single SC (no autapse - no inhibition)

 The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC (no autapse - no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition)  The abrupt changes in the SC firing frequency are the result of phasic (synaptic) and not tonic excitation

Single SC + autapse (no inhibition) Tilman Kispersky & John White Dynamic clamp experiments

Voltage record of a stellate cell coupled to itself. Inset: close up view of a single burst Under control conditions

Dynamic clamp experiments Voltage record of a stellate cell coupled to itself. Inset: close up view of a single burst Under linopiridine application (M-channel blocker)

Dynamic clamp experiments Freq. vs. current under control conditions

Dynamic clamp experiments

Minimal S-I network model

Summary  SCs have intrinsic biophysical properties that endow them with the ability to display rhythmic activity in the theta and “gamma” frequency regimes (nonlinearities and time scale separation)  In “normal” conditions SCs display theta rhythmic activity (STOs and MMOs.  Abrupt transitions resulting from recurrent excitation.  Theoretical predictions confirmed by dynamic clamp experiments (Tilman Kispersky)