Transcranial Electric Stimulation Entrains Cortical Neuronal Populations in Rats

Low intensity electric fields have been suggested to affect the ongoing neuronal activity in vitro and in human studies. However, the physiological mechanism of how weak electrical fields affect and interact with intact brain activity is not well understood. We performed in vivo extracellular and intracellular recordings from the neocortex and hippocampus of anesthetized rats and extracellular recordings in behaving rats. Electric fields were generated by sinusoid patterns at slow frequency (0.8, 1.25 or 1.7 Hz) via electrodes placed on the surface of the skull or the dura. Transcranial electric stimulation (TES) reliably entrained neurons in widespread cortical areas, including the hippocampus. The percentage of TES phase-locked neurons increased with stimulus intensity and depended on the behavioral state of the animal. TES-induced voltage gradient, as low as 1 mV/mm at the recording sites, was sufficient to phase-bias neuronal spiking. Intracellular recordings showed that both spiking and subthreshold activity were under the combined influence of TES forced fields and network activity. We suggest that TES in chronic preparations may be used for experimental and therapeutic control of brain activity

Involvement of fast-spiking cells in ictal sequences during spontaneous seizures in rats with chronic temporal lobe epilepsy

Epileptic seizures represent altered neuronal network dynamics, but the temporal evolution and cellular substrates of the neuronal activity patterns associated with spontaneous seizures are not fully understood. We used simultaneous recordings from multiple neurons in the hippocampus and neocortex of rats with chronic temporal lobe epilepsy to demonstrate that subsets of cells discharge in a highly stereotypical sequential pattern during ictal events, and that these stereotypical patterns were reproducible across consecutive seizures. In contrast to the canonical view that principal cell discharges dominate ictal events, the ictal sequences were predominantly composed of fast-spiking, putative inhibitory neurons, which displayed unusually strong coupling to local field potential even before seizures. The temporal evolution of activity was characterized by unique dynamics where the most correlated neuronal pairs before seizure onset displayed the largest increases in correlation strength during the seizures. These results demonstrate the selective involvement of fast spiking interneurons in structured temporal sequences during spontaneous ictal events in hippocampal and neocortical circuits in experimental models of chronic temporal lobe epilepsy

Neuronal synchrony: peculiarity and generality

Synchronization in neuronal systems is a new and intriguing application of dynamical systems theory. Why are neuronal systems different as a subject for synchronization? (1) Neurons in themselves are multidimensional nonlinear systems that are able to exhibit a wide variety of different activity patterns. Their “dynamical repertoire” includes regular or chaotic spiking, regular or chaotic bursting, multistability, and complex transient regimes. (2) Usually, neuronal oscillations are the result of the cooperative activity of many synaptically connected neurons (a neuronal circuit). Thus, it is necessary to consider synchronization between different neuronal circuits as well. (3) The synapses that implement the coupling between neurons are also dynamical elements and their intrinsic dynamics influences the process of synchronization or entrainment significantly. In this review we will focus on four new problems: (i) the synchronization in minimal neuronal networks with plastic synapses (synchronization with activity dependent coupling), (ii) synchronization of bursts that are generated by a group of nonsymmetrically coupled inhibitory neurons (heteroclinic synchronization), (iii) the coordination of activities of two coupled neuronal networks (partial synchronization of small composite structures), and (iv) coarse grained synchronization in larger systems (synchronization on a mesoscopic scale

Desynchronizing effect of high-frequency stimulation in a generic cortical network model

Transcranial Electrical Stimulation (TCES) and Deep Brain Stimulation (DBS) are two different applications of electrical current to the brain used in different areas of medicine. Both have a similar frequency dependence of their efficiency, with the most pronounced effects around 100Hz. We apply superthreshold electrical stimulation, specifically depolarizing DC current, interrupted at different frequencies, to a simple model of a population of cortical neurons which uses phenomenological descriptions of neurons by Izhikevich and synaptic connections on a similar level of sophistication. With this model, we are able to reproduce the optimal desynchronization around 100Hz, as well as to predict the full frequency dependence of the efficiency of desynchronization, and thereby to give a possible explanation for the action mechanism of TCES.Comment: 9 pages, figs included. Accepted for publication in Cognitive Neurodynamic

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.We kindly thank S. Gillet, J. Hinman, E. Newman and L. Ewell for their invaluable consultations and comments on previous versions of this manuscript, as well as M. Connerney, S. Eriksson, C. Libby and T. Ware for technical assistance and behavioral training. This work was supported by grants from the National Institute of Mental Health (R01 MH60013 and MH61492) and the Office of Naval Research Multidisciplinary University Research Initiative (N00014-10-1-0936). (R01 MH60013 - National Institute of Mental Health; MH61492 - National Institute of Mental Health; N00014-10-1-0936 - Office of Naval Research Multidisciplinary University Research Initiative)Accepted manuscrip

Oscillator-based neuronal modeling for seizure progression investigation and seizure control strategy

The coupled oscillator model has previously been used for the simulation of neuronal activities in in vitro rat hippocampal slice seizure data and the evaluation of seizure suppression algorithms. Each model unit can be described as either an oscillator which can generate action potential spike trains without inputs, or a threshold-based unit. With the change of only one parameter, each unit can either be an oscillator or a threshold-based spiking unit. This would eliminate the need for a new set of equations for each type of unit. Previous analysis has suggested that long kernel duration and imbalance of inhibitory feedback can cause the system to intermittently transition into and out of ictal activities. The state transitions of seizure-like events were investigated here; specifically, how the system excitability may change when the system undergoes transitions in the preictal and postictal processes. Analysis showed that the area of the excitation kernel is positively correlated with the mean firing rate of the ictal activity. The kernel duration is also correlated to the amount of ictal activity. The transition into ictal activity involved the escape from the saddle point foci in the state space trajectory identified by using Newton\u27s method. The ability to accurately anticipate and suppress seizures is an important endeavor that has tremendous impact on improving the quality of lives for epileptic patients. The stimulation studies have suggested that an electrical stimulation strategy that uses the intrinsic high complexity dynamics of the biological system may be more effective in reducing the duration of seizure-like activities in the computer model. In this research, we evaluate this strategy on an in vitro rat hippocampal slice magnesium-free model. Simulated postictal field potential data generated by an oscillator-based hippocampal network model was applied to the CA1 region of the rat hippocampal slices through a multi-electrode array (MEA) system. It was found to suppress and delay the onset of future seizures temporarily. The average inter-seizure time was found to be significantly prolonged after postictal stimulation when compared to the negative control trials and bipolar square wave signals. The result suggests that neural signal-based stimulation related to resetting may be suitable for seizure control in the clinical environment

Neural synchrony in cortical networks : history, concept and current status

Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies