Calvin J Schneider

Toward a full-scale computational model of the rat dentate gyrus

Recent advances in parallel computing, including the creation of the parallel version of the NEURON simulation environment, have allowed for a previously unattainable level of complexity and detail in neural network models. Previously, we published a functional NEURON model of the rat dentate gyrus with over 50,000 biophysically realistic, multicompartmental neurons, but network simulations could only utilize a single processor. By converting the model to take advantage of parallel NEURON, we are now able to utilize greater computational resources and are able to simulate the full-scale dentate gyrus, containing over a million neurons. This has eliminated the previous necessity for scaling adjustments and allowed for a more direct comparison to experimental techniques and results. The translation to parallel computing has provided a superlinear speedup of computation time and dramatically increased the overall computer memory available to the model. The incorporation of additional computational resources has allowed for more detail and elements to be included in the model, bringing the model closer to a more complete and accurate representation of the biological dentate gyrus. As an example of a major step toward an increasingly accurate representation of the biological dentate gyrus, we discuss the incorporation of realistic granule cell dendrites into the model. Our previous model contained simplified, two-dimensional dendritic morphologies that were identical for neurons of the same class. Using the software tools L-Neuron and L-Measure, we are able to introduce cell-to-cell variability by generating detailed, three-dimensional granule cell morphologies that are based on biological reconstructions. Through these and other improvements, we aim to construct a more complete full-scale model of the rat dentate gyrus, to provide a better tool to delineate the functional role of cell types within the dentate gyrus and their pathological changes observed in epilepsy.

Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations

Dendritic morphology has been shown to have a dramatic impact on neuronal function. However, population features such as the inherent variability in dendritic morphology between cells belonging to the same neuronal type are often overlooked when studying computation in neural networks. While detailed models for morphology and electrophysiology exist for many types of single neurons, the role of detailed single cell morphology in the population has not been studied quantitatively or computationally. Here we use the structural context of the neural tissue in which dendritic trees exist to drive their generation in silico. We synthesize the entire population of dentate gyrus granule cells, the most numerous cell type in the hippocampus, by growing their dendritic trees within their characteristic dendritic fields bounded by the realistic structural context of (1) the granule cell layer that contains all somata and (2) the molecular layer that contains the dendritic forest. This process enables branching statistics to be linked to larger scale neuroanatomical features. We find large differences in dendritic total length and individual path length measures as a function of location in the dentate gyrus and of somatic depth in the granule cell layer. We also predict the number of unique granule cell dendrites invading a given volume in the molecular layer. This work enables the complete population-level study of morphological properties and provides a framework to develop complex and realistic neural network models.

Proton Radiation Alters Intrinsic and Synaptic Properties of CA1 Pyramidal Neurons of the Mouse Hippocampus

High-energy protons constitute at least 85% of the fluence of energetic ions in interplanetary space. Although protons are only sparsely ionizing compared to higher atomic mass ions, they nevertheless significantly contribute to the delivered dose received by astronauts that can potentially affect central nervous system function at high fluence, especially during prolonged deep space missions such as to Mars. Here we report on the long-term effects of 1 Gy proton irradiation on electrophysiological properties of CA1 pyramidal neurons in the mouse hippocampus. The hippocampus is a key structure for the formation of long-term episodic memory, for spatial orientation and for information processing in a number of other cognitive tasks. CA1 pyramidal neurons form the last and critical relay point in the trisynaptic circuit of the hippocampal principal neurons through which information is processed before being transferred to other brain areas. Proper functioning of CA1 pyramidal neurons is crucial for hippocampus-dependent tasks. Using the patch-clamp technique to evaluate chronic effects of 1 Gy proton irradiation on CA1 pyramidal neurons, we found that the intrinsic membrane properties of CA1 pyramidal neurons were chronically altered at 3 months postirradiation, resulting in a hyperpolarization of the resting membrane potential (VRMP) and a decrease in input resistance (Rin). These small but significant alterations in intrinsic properties decreased the excitability of CA1 pyramidal neurons, and had a dramatic impact on network function in a computational model of the CA1 microcircuit. We also found that proton-radiation exposure upregulated the persistent Na+ current (INaP) and increased the rate of miniature excitatory postsynaptic currents (mEPSCs). Both the INaP and the heightened rate of mEPSCs contribute to neuronal depolarization and excitation, and at least in part, could compensate for the reduced excitability resulting from the radiation effects on the VRMP and the Rin. These results show long-term alterations in the intrinsic properties of CA1 pyramidal cells after realistic, low-dose proton irradiation.

Resolution revolution: epilepsy dynamics at the microscale

Our understanding of the neuronal mechanisms behind epilepsy dynamics has recently advanced due to the application of novel technologies, monitoring hundreds of neurons with single cell resolution. These developments have provided new theories on the relationship between physiological and pathological states, as well as common motifs for the propagation of paroxysmal activity. Although traditional electroencephalogram (EEG) recordings continue to describe normal network oscillations and abnormal epileptic events within and outside of the seizure focus, analysis of epilepsy dynamics at the microscale has found variability in the composition of macroscopically repetitive epileptiform events. These novel results point to heterogeneity in the underlying dynamics of the disorder, highlighting both the need and potential for more specific and targeted therapies.

Computer modeling of epilepsy

This chapter reviews current computational models and proposes future directions for computational modeling in the field of epilepsy. The models include single cells with mutated ion channels; small‐ and large‐scale networks of detailed cells; and macroscopic, mean‐field models of network dynamics. In addition, we consider the potential therapeutic applications of modeling. For an expanded treatment of this topic see Jasper’s Basic Mechanisms of the Epilepsies, Fourth Edition (Noebels JL, Avoli M, Rogawski MA, Olsen RW, Delgado‐Escueta AC, eds) published by Oxford University Press (available on the National Library of Medicine Bookshelf [NCBI] at http://www.ncbi.nlm.nih.gov/books).

Net Worth of Networks: Specificity in Anticonvulsant Action

Commentary The effectiveness of sodium channel-targeting anticonvulsants in epilepsy treatment has been well-known for decades, which has inspired numerous insightful investigations into their mechanism of action from both molecular and cellular perspectives. This class of drugs—including carbamazepine, phenytoin, and lamotrigine—preferentially binds to the inactivated conformation of sodium channels and acts in a usedependent manner, increasing channel block with prolonged or repetitive activation (1, 2). This dependence on high levels of neuronal activity has led to the hypothesis that these drugs inhibit the hallmark pathological high-frequency oscillations prevalent in epilepsy, while leaving normal physiological function relatively (albeit certainly not completely) intact (3). However, there has been a need to bridge the divide between the specific molecular–cellular mechanisms and broad clinical effectiveness by considering the intermediate network context and taking into account the existence of distinct neuronal subpopulations and the different aspects of network function. In particular, while the effects of anticonvulsants have been examined primarily in excitatory cell types (4, 5), their effects on interneurons and inhibition have been largely understudied. It therefore remains an intriguing open question as to whether inhibitory function is also compromised by sodium channeltargeting anticonvulsants. In a complex series of elegant, carefully conducted experiments, Pothmann and colleagues addressed the question of whether there are cell type-specific effects of carbamazepine arising from the impressive diversity of inhibitory interneurons (6, 7). The authors used a variety of techniques, including slice electrophysiology, voltage-sensitive dye imaging, morphological identification and in vivo juxtacellular recordings from freely moving animals to not only extend the well-established use-dependent blocking action of carbamazepine to the interneuronal population but also to discover striking cell-type specificity in its efficacy. Starting with pyramidal cells in acute hippocampal slices, the authors first showed that, as expected from use-dependent block, reduction in the maximal firing rate of pyramidal cells in response to carbamazepine applied at a clinically relevant dose increased with longer somatic current injections. The drug-induced firing rate changes in response to intracellular current pulses were then quantified again, but this time in three classes of interneurons that innervate different regions of CA1 pyramidal cells: basket cells that target the perisomatic region (BCs), oriens lacunosum-moleculare cells that target the distal dendrites (OLM), and interneurons that target the proximal dendrites (PD). While the BCs and OLM cells showed a similar reduction to that of the pyramidal cells, carbamazepine caused a larger reduction in PD cells. This Function of Inhibitory Micronetworks Is Spared by Na+ Channel-Acting Anticonvulsant Drugs.