Nathan W. Schultheiss

Segregation of cortical head direction cell assemblies on alternating theta cycles

High-level cortical systems for spatial navigation, including entorhinal grid cells, critically depend on input from the head direction system. We examined spiking rhythms and modes of synchrony between neurons participating in head direction networks for evidence of internal processing, independent of direct sensory drive, which may be important for grid cell function. We found that head direction networks of rats were segregated into at least two populations of neurons firing on alternate theta cycles (theta cycle skipping) with fixed synchronous or anti-synchronous relationships. Pairs of anti-synchronous theta cycle skipping neurons exhibited larger differences in head direction tuning, with a minimum difference of 40 degrees of head direction. Septal inactivation preserved the head direction signal, but eliminated theta cycle skipping of head direction cells and grid cell spatial periodicity. We propose that internal mechanisms underlying cycle skipping in head direction networks may be critical for downstream spatial computation by grid cells.

Phase response curve analysis of a full morphological globus pallidus neuron model reveals distinct perisomatic and dendritic modes of synaptic integration.

Synchronization of globus pallidus (GP) neurons and cortically entrained oscillations between GP and other basal ganglia nuclei are key features of the pathophysiology of Parkinsons disease. Phase response curves (PRCs), which tabulate the effects of phasic inputs within a neurons spike cycle on output spike timing, are efficient tools for predicting the emergence of synchronization in neuronal networks and entrainment to periodic input. In this study we apply physiologically realistic synaptic conductance inputs to a full morphological GP neuron model to determine the phase response properties of the soma and different regions of the dendritic tree. We find that perisomatic excitatory inputs delivered throughout the interspike interval advance the phase of the spontaneous spike cycle yielding a type I PRC. In contrast, we demonstrate that distal dendritic excitatory inputs can either delay or advance the next spike depending on whether they occur early or late in the spike cycle. We find this latter pattern of responses, summarized by a biphasic (type II) PRC, was a consequence of dendritic activation of the small conductance calcium-activated potassium current, SK. We also evaluate the spike-frequency dependence of somatic and dendritic PRC shapes, and we demonstrate the robustness of our results to variations of conductance densities, distributions, and kinetic parameters. We conclude that the distal dendrite of GP neurons embodies a distinct dynamical subsystem that could promote synchronization of pallidal networks to excitatory inputs. These results highlight the need to consider different effects of perisomatic and dendritic inputs in the control of network behavior.

Effects of acetylcholine on neuronal properties in entorhinal cortex.

The entorhinal cortex (EC) receives prominent cholinergic innervation from the medial septum and the vertical limb of the diagonal band of Broca (MSDB). To understand how cholinergic neurotransmission can modulate behavior, research has been directed toward identification of the specific cellular mechanisms in EC that can be modulated through cholinergic activity. This review focuses on intrinsic cellular properties of neurons in EC that may underlie functions such as working memory, spatial processing, and episodic memory. In particular, the study of stellate cells (SCs) in medial entorhinal has resulted in discovery of correlations between physiological properties of these neurons and properties of the unique spatial representation that is demonstrated through unit recordings of neurons in medial entorhinal cortex (mEC) from awake-behaving animals. A separate line of investigation has demonstrated persistent firing behavior among neurons in EC that is enhanced by cholinergic activity and could underlie working memory. There is also evidence that acetylcholine plays a role in modulation of synaptic transmission that could also enhance mnemonic function in EC. Finally, the local circuits of EC demonstrate a variety of interneuron physiology, which is also subject to cholinergic modulation. Together these effects alter the dynamics of EC to underlie the functional role of acetylcholine in memory.

In vivo cholinergic modulation of the cellular properties of medial entorhinal cortex neurons

•  Medial entorhinal cortex neurons show special intrinsic properties in vitro, which might be important for contributing to functional cell properties, such as grid cell firing. •  Both intrinsic properties in slices of medial entorhinal cortex and grid cell activity in vivo are affected by cholinergic activation, but the relationships between these effects are unknown. •  Using intracellular recording, we show that intrinsic properties including sag amplitude, sag time constant and resonance frequency are affected by cholinergic activation in vivo, and these results are consistent with in vitro studies. •  Furthermore, we show that the relationship between firing frequency and input current is also changed by cholinergic activation in our in vivo recordings. •  These results suggest the importance of cholinergic influences on the intrinsic properties of medial entorhinal neurons, and help us understand how this influence contributes to mechanisms of spatial memory and the cause of memory impairment.

Robustness, variability, phase dependence, and longevity of individual synaptic input effects on spike timing during fluctuating synaptic backgrounds: A modeling study of globus pallidus neuron phase response properties

A neurons phase response curve (PRC) shows how inputs arriving at different times during the spike cycle differentially affect the timing of subsequent spikes. Using a full morphological model of a globus pallidus (GP) neuron, we previously demonstrated that dendritic conductances shape the PRC in a spike frequency-dependent manner, suggesting different functional roles of perisomatic and distal dendritic synapses in the control of patterned network activity. In the present study we extend this analysis to examine the impact of physiologically realistic high conductance states on somatic and dendritic PRCs and the time course of spike train perturbations. First, we found that average somatic and dendritic PRCs preserved their shapes and spike frequency dependence when the model was driven by spatially-distributed, stochastic conductance inputs rather than tonic somatic current. However, responses to inputs during specific synaptic backgrounds often deviated substantially from the average PRC. Therefore, we analyzed the interactions of PRC stimuli with transient fluctuations in the synaptic background on a trial-by-trial basis. We found that the variability in responses to PRC stimuli and the incidence of stimulus-evoked added or skipped spikes were stimulus-phase-dependent and reflected the profile of the average PRC, suggesting commonality in the underlying mechanisms. Clear differences in the relation between the phase of input and variability of spike response between dendritic and somatic inputs indicate that these regions generally represent distinct dynamical subsystems of synaptic integration with respect to influencing the stability of spike time attractors generated by the overall synaptic conductance.

Phase response analysis during in vivo-like high conductance states; dendritic SK determines the mean and variance of responses to dendritic excitation

A neuron’s phase response curve (PRC) describes how synaptic inputs at different times during the spike cycle affect the timing of subsequent spikes, and PRC analysis is a powerful technique for predicting and interpreting the emergence of synchronous modes in synaptically coupled networks and neuronal populations receiving common input. However, neuronal PRCs are typically measured during intrinsic pacemaking which may not reflect neuronal excitability and dynamics during high conductance states generated by complex network activity in vivo. Using a full morphological model of a globus pallidus (GP) neuron we have recently demonstrated that during intrinsic pacemaking, somatic PRCs for GP neurons are type I, i.e. excitatory inputs at all phases of the spike cycle advance the spontaneous spiking rhythm1. We also demonstrated that synaptic excitation of the distal dendrite can paradoxically delay subsequent spiking when delivered at some phases of the spike cycle (yielding a type II PRC) as a consequence of dendritic activation of the small conductance calcium-activated potassium current, SK1. Since during high conductance states spike timing is determined by a balance between intrinsic mechanisms and synaptic input fluctuations, in this study we investigated how somatic and dendritic phase response properties of the GP model are affected by ongoing stochastic synaptic background activity. We generated high conductance states in the model by applying synaptic backgrounds composed of randomly-timed excitatory and inhibitory synaptic inputs at 1022 GABA synapses and 100 AMPA synapses distributed throughout the dendrite. By varying the synaptic gain and input frequency parameters across the physiological range for inputs to GP, we achieved a diverse set of high conductance states characterized by sub-threshold voltage fluctuations, irregular spiking, and elevated membrane conductance (Figure ​(Figure1A1A &1B) and spanning the range of spike frequencies observed in vivo (15-45 Hz). For each synaptic background parameter set, we generated 100 single-trial PRCs by delivering a single 2.5 nS AMPA-synaptic input to either the soma or distal dendrite at each of 72 time-points (in separate simulations) within the first spike cycle of each of 100 control spike trains (Figure ​(Figure1C1C &1D). We then averaged the single-trial PRCs for each synaptic background to evaluate the dependence of PRC shape on stimulus location, spike frequency, and dendritic SK conductance, in addition to the gain and input frequencies of synaptic backgrounds. Next, we analyzed on a trial-by-trial basis the interactions of PRC stimuli with transient fluctuations in the synaptic background leading to added or skipped spikes. We determined that dendritic SK underlies both the incidence of skipped spikes and the dependence of skipped spike events on stimulus phase. Interestingly, the input-phase dependence of skipped spike events mirrored the phase-dependent variance in the PRC itself (which we plotted as phase response-variance curves, PRVCs). This indicates that dendritic SK determines not only the mean response, but also the variance of responses, to excitatory dendritic inputs. Average somatic and dendritic PRCs were type I and type II, respectively, and are likely to represent the average behavior of populations of GP neurons in response to shared excitation. Furthermore, in-as-much as the GP model and simulated synaptic backgrounds are physiologically realistic, the variance in the model’s responses across trials directly reflects a major source of spike time variance across populations of GP neurons in vivo. Figure 1 A&B. Total synaptic conductance (top) and current (bottom) for synaptic backgrounds composed of 1 nS (A) or 2 nS (B) unitary inputs. C&D. Perturbations of control spike trains (black) by somatic (C) or dendritic (D2D)(D) stimuli. (Trace ...

Models and Theoretical Frameworks for Hippocampal and Entorhinal Cortex Function in Memory and Navigation

The hippocampus and related medial temporal lobe structures subserve both navigation and memory. These seemingly disparate functions have been characterized extensively at the cellular, network, and systems levels, leading to models of the hippocampus at different levels of abstraction. Mechanistic models relating neural activity to spatial and/or mnemonic function often rely on representations of individual neurons, synapses, or network structure, while theoretical models of the hippocampus incorporate and attempt to reconcile aspects of the hippocampal codes for space and/or past experience. In this chapter we first provide a brief introduction to the research history and concepts relating the hippocampus to memory and navigation, incorporating an overview of some of the influential models and theories that have been proposed to capture aspects of the hippocampus’s role in mnemonic or spatial processing. We then describe the anatomy of the hippocampal-entorhinal circuit, emphasizing the rough division of labor across hippocampal subregions and entorhinal cortex related to the computational demands of navigation and episodic memory. Next, we discuss the role of oscillations and cross-frequency coupling in coordinating neural activity to encode spatially and temporally sequenced information about ongoing or remembered experience. Finally, we discuss an important conceptual framework that links numerous experimental observations of hippocampal spatial and mnemonic function based on commonalities between map-based and self-motion-based navigation strategies on the one hand and semantic and episodic memory on the other.

The compass within

Head direction cells have been hypothesized to form representations of an animals spatial orientation through internal network interactions. New data from mice show the predicted signatures of these internal dynamics.

Continuum of Type I Somatic to Type II Dendritic PRCs; Phase Response Properties of a Morphologically Reconstructed Globus Pallidus Neuron Model

A neuron’s phase response curve (PRC) describes how inputs at different times during the spike cycle affect the timing of subsequent spikes, and PRC analysis is a powerful technique for predicting and interpreting the emergence of synchronous modes in coupled networks and neuronal populations. However, neuron models whose PRCs are used to study network dynamics typically consist of a minimal set of dynamic variables and often lack a realistic dendritic structure. In this chapter I describe the phase response properties of a fully reconstructed morphological model of a globus pallidus (GP) neuron during intrinsic pacemaking and during faster spiking driven by somatic current injection. This approach allows investigation of how intrinsic conductances contribute to neuronal responses in a model that preserves the complex staptiotemporal interactions between active properties of the model. I demonstrate that a single neuron can possess both type I and type II PRCs for inputs delivered to different places within the neuronal morphology. Whereas the somatic PRC for the GP model is type I, the distal dendritic PRC is type II as a consequence of the high voltage activated calcium current (CaHVA) and the small conductance calcium-activated potassium current (SK) in distal dendritic segments. The precise shapes of these somatic and dendritic PRCs are highly sensitive to the spike frequency of the model such that during faster spiking the skewness of the primary somatic PRC is reduced, the second-order somatic PRC contains a significant negative lobe, and the negative lobe in the primary dendritic PRC is shifted to the second-order PRC. These results illustrate the complex spatiotemporal interactions of synaptic inputs with intrinsic neuronal mechanisms and highlight the need to consider network connectivity on a scale that distinguishes inputs to different regions of the neuronal morphology.

Phase response curve analysis of a morphologically realistic globus pallidus neuron model reveals a distal dendritic mechanism for synchronization

Background Phase-locked bursting and oscillations in low frequency bands between the subthalamic nucleus (STN) and the globus pallidus (GP) are key features of the pathophysiology of Parkinsons disease (PD). These dynamics may reflect susceptibility of the basal ganglia (BG) to entrainment with cortical oscillations or could also be a consequence of enhanced reciprocal STN-GP coupling under conditions of dopamine depletion. Phase response analysis is an efficient method of characterizing the tendency of single neurons to entrain to periodic input, and to predict the tendency of connected networks to synchronize. A phase response curve (PRC) describes the dependency of shifts in spike timing that result from weak inputs on the timing of inputs within the ongoing inter-spike interval (ISI). If, independent of stimulus phase, a depolarizing input causes an advance of the next spike, the PRC will be composed purely of positive values (a Type I PRC). A Type II PRC contains both positive and negative regions, indicating that a depolarizing from Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 Toronto, Canada. 7–12 July 2007