Fanselow EE, Richardson KA, Connors BW. Selective, statedependent activation of somatostatin-expressing inhibitory interneurons in mouse neocortex. J Neurophysiol 100: 2640 -2652, 2008. First published September 17, 2008 doi:10.1152/jn.90691.2008. The specific functions of subtypes of cortical inhibitory neurons are not well understood. This is due in part to a dearth of information about the behaviors of interneurons under conditions when the surrounding circuit is in an active state. We investigated the firing behavior of a subset of inhibitory interneurons, identified using mice that express green fluorescent protein (GFP) in a subset of somatostatin-expressing inhibitory cells ("GFP-expressing inhibitory neuron" [GIN] cells). The somata of the GIN cells were in layer 2/3 of somatosensory cortex and had dense, layer 1-projecting axons that are characteristic of Martinotti neurons. Interestingly, GIN cells fired similarly during a variety of diverse activating conditions: when bathed in fluids with low-divalent cation concentrations, when stimulated with brief trains of local synaptic inputs, when exposed to group I metabotropic glutamate receptor agonists, or when exposed to muscarinic cholinergic receptor agonists. During these manipulations, GIN cells fired rhythmically and persistently in the theta-frequency range (3-10 Hz). Synchronous firing was often observed and its strength was directly proportional to the magnitude of electrical coupling between GIN cells. These effects were cell type specific: the four manipulations that persistently activated GIN cells rarely caused spiking of regularspiking (RS) pyramidal cells or fast-spiking (FS) inhibitory interneurons. Our results suggest that supragranular GIN interneurons form an electrically coupled network that exerts a coherent 3-to 10-Hz inhibitory influence on its targets. Because GIN cells are more readily activated than RS and FS cells, it is possible that they act as "first responders" when cortical excitatory activity increases.

We experimentally confirmed predictions that modulation of the neuronal threshold with electrical fields can speed up, slow down, and even block traveling waves in neocortical slices. The predictions are based on a Wilson-Cowan-type integro-differential equation model of propagating neocortical activity. Wave propagation could be modified quickly and reversibly within targeted regions of the network. To the best of our knowledge, this is the first example of direct modulation of the threshold to control wave propagation in a neural system.Traveling waves in excitable media are commonly observed in physical [1,2], chemical [3], and biological [4][5][6] systems. Mathematical models have been developed in conjunction with these experimental systems to provide a deeper understanding of the dynamics and infer how individual experimental parameters of the system, such as threshold, contribute to these dynamics [5,[7][8][9][10]. Rapid access to system parameters would offer the means to control pattern formation and dynamics in these systems.Successful modulation of dynamics has been accomplished in chemical, cardiac, and neural systems. In the Belousov-Zhabotinsky chemical reaction system, modulation of excitability through local changes in illumination of a light sensitive catalyst allowed control of wave propagation [11]. Electric fields modulated activity propagation in heart tissue [12]. The propagation speed of excitation waves in neocortex has been slowed by pharmacologically interfering with chemical synaptic transmission [13].It has been previously shown that electric fields can modulate neuronal thresholds by quickly and reversibly polarizing asymmetric neurons [14]. Electric fields as small as 140 μV/mm have been observed to modulate neural firing [15]. Polarization occurs on time scales of about 20 ms and can be maintained for many seconds or minutes [16]. Applied electric fields have been used to adaptively control seizure formation in vitro [17], modulate epileptiform activity in vivo, and dynamically probe activity changes associated with impending seizures [18].We show here that electric fields can quickly alter traveling wave dynamics in ways predicted by theory through direct modulation of neuronal threshold. To our knowledge, this is the first report of control of wave propagation through direct modulation of excitability threshold in any neural system. Wilson and Cowan [19] developed a set of integro-differential equations to form a continuum model of cortex which demonstrated traveling waves. This model was recently modified [20] to represent traveling pulse propagation in disinhibited neocortex [21]. The model predicts that

Gap junctions (GJs) electrically couple GABAergic neurons of the forebrain. The spatial organization of neuron clusters coupled by GJs is an important determinant of network function, yet it is poorly described for nearly all mammalian brain regions. Here we used a novel dye-coupling technique to show that GABAergic neurons in the thalamic reticular nucleus (TRN) of mice and rats form two types of GJ-coupled clusters with distinctive patterns and axonal projections. Most clusters are elongated narrowly along functional modules within the plane of the TRN, with axons that selectively inhibit local groups of relay neurons. However, some coupled clusters have neurons arrayed across the thickness of the TRN and target their axons to both first-and higher-order relay nuclei. Dye coupling was reduced, but not abolished, among cells of connexin36 knock-out mice. Our results suggest that GJs form two distinct types of inhibitory networks that correlate activity either within or across functional modules of the thalamus.

Stochastic resonance (SR) is a phenomenon wherein the response of a nonlinear system to a weak input signal is optimized by the presence of a particular, nonzero level of noise. Our objective was to demonstrate cross-modality SR in human sensory perception. Specifically, we were interested in testing the hypothesis that the ability of an individual to detect a subthreshold mechanical cutaneous stimulus can be significantly enhanced by introducing a particular level of electrical noise. Psychophysical experiments were performed on 11 healthy subjects. The protocol consisted of the presentation of: (a) a subthreshold mechanical stimulus plus electrical noise, or (b) no mechanical stimulus plus electrical noise. The intensity of the electrical noise was varied between trials. Each subject's ability to identify correctly the presence of the mechanical stimulus was determined as a function of the noise intensity. In 9 of the 11 subjects, the introduction of a particular level of electrical noise significantly enhanced the subject's ability to detect the subthreshold mechanical cutaneous stimulus. In 2 of the 11 subjects, the introduction of electrical noise did not significantly change the subject's ability to detect the mechanical stimulus. These findings indicate that input electrical noise can serve as a negative masker for subthreshold mechanical tactile stimuli, i.e., electrical noise can increase the detectability of weak mechanical signals. Thus, for SR-type effects to be observed in human sensory perception, the noise and stimulus need not be of the same modality. From a bioengineering and clinical standpoint, this work suggests that an electrical noise-based technique could be used to improve tactile sensation in humans when the mechanical stimulus is around or below threshold. (c) 1998 American Institute of Physics.

Summary:Purpose: Electric field stimulation can interact with brain activity in a subthreshold manner. Electric fields have been previously adaptively applied to control seizures in vitro. We report the first results from establishing suitable electrode geometries and trajectories, as well as stimulation and recording electronics, to apply this technology in vivo.Methods: Electric field stimulation was performed in a rat kainic acid injection seizure model. Radial electric fields were generated unilaterally in hippocampus from an axial depth electrode. Both sinusoidal and multiphasic stimuli were applied. Hippocampal activity was recorded bilaterally from tungsten microelectrode pairs. Histologic examination was performed to establish electrode trajectory and characterize lesioning.Results: Electric field modulation of epileptiform neural activity in phase with the stimulus was observed in five of six sinusoidal and six of six multiphasic waveform experiments. Both excitatory and suppressive modulation were observed in the two experiments with stimulation electrodes most centrally placed within the hippocampus. Distinctive modulation was observed in the period preceding seizure-onset detection in two of six experiments. Short-term histologic tissue damage was observed in one of six experiments associated with high unbalanced charge delivery.Conclusions: We demonstrated in vivo electric field modulation of epileptiform hippocampal activity, suggesting that electric field control of in vivo seizures may be technically feasible. The response to stimulation before seizure could be useful for triggering control systems, and may be a novel approach to define a preseizure state. Key Words: Electric field-Neural prosthesis-Seizure-HippocampusPreseizure state-Epilepsy.Although control system technology has made extraordinary advances during the past century, our efforts to apply sophisticated control strategies to epilepsy have been limited. Such limitations arise both from the lack of a flexible control parameter that would permit us to increase or decrease activity in the brain rapidly and reversibly, and the lack of stimulation and recording amplifiers designed for simultaneous monitoring of neuronal activity during control stimulation. Uninterrupted monitoring would allow a control system to use ongoing information about the dynamics to prescribe the control perturbations as continuous feedback. The application of continuous feedback would allow a controller to modify spe- cific patterns of neuronal activity selectively while minimizing the impact on other more normal activities. This approach is in contrast to "reversible lesions" associated with high-frequency stimulation, which more indiscriminately suppresses neuronal activity in the neighborhood of stimulation. We here demonstrate in vivo some technical solutions required for future implementation of continuous feedback control of seizures by using electric field stimulation.Early strategies for controlling epileptic seizures through electrical stimulation focus...

Working memory is an essential component of higher cognitive function, and its impairment is a core symptom of multiple CNS disorders, including schizophrenia. Neuronal mechanisms supporting working memory under normal conditions have been described and include persistent, high-frequency activity of prefrontal cortical neurons. However, little is known about the molecular and cellular basis of working memory dysfunction in the context of neuropsychiatric disorders. To elucidate synaptic and neuronal mechanisms of working memory dysfunction, we have performed a comprehensive analysis of a mouse model of schizophrenia, the forebrain-specific calcineurin knock-out mouse. Biochemical analyses of cortical tissue from these mice revealed a pronounced hyperphosphorylation of synaptic vesicle cycling proteins known to be necessary for high-frequency synaptic transmission. Examination of the synaptic vesicle cycle in calcineurin-deficient neurons demonstrated an impairment of vesicle release enhancement during periods of intense stimulation. Moreover, brain slice and in vivo electrophysiological analyses showed that loss of calcineurin leads to a gene dose-dependent disruption of high-frequency synaptic transmission and network activity in the PFC, correlating with selective working memory impairment. Finally, we showed that levels of dynamin I, a key presynaptic protein and calcineurin substrate, are significantly reduced in prefrontal cortical samples from schizophrenia patients, extending the disease relevance of our findings. Our data provide support for a model in which impaired synaptic vesicle cycling represents a critical node for disease pathologies underlying the cognitive deficits in schizophrenia.

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Recently, it has been shown that interspike interval (ISI) series from driven model neurons can be used to discriminate between chaotic and stochastic inputs. Here we extend this work to in vitro experimental studies with rat cutaneous mechanoreceptors. For each of the neurons tested, we show that a chaotically driven ISI series can be distinguished from a stochastically driven ISI series on the basis of a nonlinear prediction measure. This work demonstrates that dynamical information can be preserved when an analog chaotic signal is converted into a spike train by a sensory neuron. [S0031-9007(98)05551-3]