David J. Pinto

Initiation, Propagation, and Termination of Epileptiform Activity in Rodent Neocortex In Vitro Involve Distinct Mechanisms

Waves of epileptiform activity in neocortex have three phenomenological stages: initiation, propagation, and termination. We use a well studied model of epileptiform activity in vitro to investigate directly the hypothesis that each stage is governed by an independent mechanism within the underlying cortical circuit. Using the partially disinhibited neocortical slice preparation, activity is induced and modulated using neurotransmitter receptor antagonists and is measured using both intracellular recordings and a linear array of extracellular electrodes. We find that initiation depends on both synaptic excitation and inhibition and entails a slow process of recruitment at discrete spatial locations within cortical layer 5 but not layer 2/3. Propagation depends on synaptic excitation but not inhibition and is a fast process that involves neurons across the spatial extent of the slice and in all cortical layers. Termination is modulated by synaptic excitation and inhibition. In space, termination occurs reliably at discrete locations. In time, termination is characterized by a strong depolarizing shift (block) and recovery of neurons in all cortical layers. These results suggest that the phenomenological stages of epileptiform events correspond to distinct mechanistic stages.

Processing in layer 4 of the neocortical circuit: new insights from visual and somatosensory cortex.

Recent experimental and theoretical results in cat primary visual cortex and in the whisker-barrel fields of rodent primary somatosensory cortex suggest common organizing principles for layer 4, the primary recipient of sensory input from the thalamus. Response tuning of layer 4 cells is largely determined by a local interplay of feed-forward excitation (directly from the thalamus) and inhibition (from layer 4 inhibitory interneurons driven by the thalamus). Feed-forward inhibition dominates excitation, inherits its tuning from the thalamic input, and sharpens the tuning of excitatory cells. Recurrent excitation enhances responses to effective stimuli.

Synchronization of Electrically Coupled Pairs of Inhibitory Interneurons in Neocortex

We performed a systematic analysis of phase locking in pairs of electrically coupled neocortical fast-spiking (FS) and low-threshold-spiking (LTS) interneurons and in a conductance-based model of a pair of FS cells. Phase–response curves (PRCs) were obtained for real interneurons and the model cells. We used PRCs and the theory of weakly coupled oscillators to make predictions about phase-locking characteristics of cell pairs. Phase locking and the robustness of phase-locked states to differences in intrinsic frequencies of cells were directly examined by driving interneuron pairs through a wide range of firing frequencies. Calculations using PRCs accurately predicted that electrical coupling robustly synchronized the firing of interneurons over all frequencies studied (FS, ∼25–80 Hz; LTS, ∼10–30 Hz). The synchronizing ability of electrical coupling and the robustness of the phase-locked states were directly dependent on the strength of coupling but not on firing frequency. The FS cell model also predicted the existence of stable antiphase firing at frequencies below ∼30 Hz, but no evidence for stable antiphase firing was found using the experimentally determined PRCs or in direct measures of phase locking in pairs of interneurons. Despite significant differences in biophysical properties of FS and LTS cells, their phase-locking behavior was remarkably similar. The wide spikes and shallow action potential afterhyperpolarizations of interneurons, compared with the model, prohibited antiphase behavior. Electrical coupling between cortical interneurons of the same type maintained robust synchronous firing of cell pairs for up to ∼10% heterogeneity in their intrinsic frequencies.

Alpha-Frequency Rhythms Desynchronize over Long Cortical Distances: A Modeling Study

Neocortical networks of excitatory and inhibitory neurons can display alpha(α)-frequency rhythms when an animal is in a resting or unfocused state. Unlike some γ- and β-frequency rhythms, experimental observations in cats have shown that these α-frequency rhythms need not synchronize over long cortical distances. Here, we develop a network model of synaptically coupled excitatory and inhibitory cells to study this asynchrony. The cells of the local circuit are modeled on the neurons found in layer V of the neocortex where α-frequency rhythms are thought to originate. Cortical distance is represented by a pair of local circuits coupled with a delay in synaptic propagation. Mathematical analysis of this model reveals that the h and T currents present in layer V pyramidal (excitatory) cells not only produce and regulate the α-frequency rhythm but also lead to the occurrence of spatial asynchrony. In particular, these inward currents cause excitation and inhibition to have nonintuitive effects in the network, with excitation delaying and inhibition advancing the firing time of cells; these reversed effects create the asynchrony. Moreover, increased excitatory to excitatory connections can lead to further desynchronization. However, the local rhythms have the property that, in the absence of excitatory to excitatory connections, if the participating cells are brought close to synchrony (for example, by common input), they will remain close to synchrony for a substantial time.

Mathematical neuroscience: from neurons to circuits to systems

Applications of mathematics and computational techniques to our understanding of neuronal systems are provided. Reduction of membrane models to simplified canonical models demonstrates how neuronal spike-time statistics follow from simple properties of neurons. Averaging over space allows one to derive a simple model for the whisker barrel circuit and use this to explain and suggest several experiments. Spatio-temporal pattern formation methods are applied to explain the patterns seen in the early stages of drug-induced visual hallucinations.

Analysis of State-Dependent Transitions in Frequency and Long-Distance Coordination in a Model Oscillatory Cortical Circuit

Changes in behavioral state are typically accompanied by changes in the frequency and spatial coordination of rhythmic activity in the neocortex. In this article, we analyze the effects of neuromodulation on ionic conductances in an oscillating cortical circuit model. The model consists of synaptically-coupled excitatory and inhibitory neurons and supports rhythmic activity in the alpha, beta, and gamma ranges. We find that the effects of neuromodulation on ionic conductances are, by themselves, sufficient to induce transitions between synchronous gamma and beta rhythms and asynchronous alpha rhythms. Moreover, these changes are consistent with changes in behavioral state, with the rhythm transitioning from the slower alpha to the faster gamma and beta as arousal increases. We also observe that it is the same set of underlying intrinsic and network mechanisms that appear to be simultaneously responsible for both the observed transitions between the rhythm types and between their synchronization properties. Spike time response curves (STRCs) are used to study the relationship between the transitions in rhythm and the underlying biophysics.

Local pathways of seizure propagation in neocortex

Publisher Summary Partial seizures of the neocortex can be initiated by the relatively small and localized collections of neurons. Anticonvulsant drugs are very successful for treating most cases of partial epilepsy, but they produce unwanted side effects in the large majority of the brain that is not epileptic. For some patients, drugs simply fail to control seizures adequately. In selected cases, surgery can be a dramatically effective and selective therapy for partial seizures. Unfortunately, the inherent uncertainties of mapping both pathology and function in the cortex often lead to a removal of important, nonepileptic tissue. A better understanding of the cellular basis of epilepsy might lead to more targeted therapeutic strategies. One tactic for preventing the onset of partial seizures is to disconnect, in a literal sense, the offending neurons and so, prevent their paroxysmal collusion. Multiple subpial transection is currently being used, on a limited and usually adjunct basis, to treat some forms of partial seizure disorders. Understanding the optimal requirements for preventing and containing focal seizures by disconnection will require a detailed knowledge of the structure and function of local neocortical circuits. This chapter summarizes selected research on the neurons, axons, synaptic connections, and epileptiform activity of the neocortex to illuminate the substrates that mediate seizure propagation.