Spike suppression in a local cortical circuit induced by transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) noninvasively interferes with human cortical function, and is widely used as an effective technique for probing causal links between neural activity and cognitive function. However, the physiological mechanisms underlying TMS-induced effects on neural activity remain unclear. We examined the mechanism by which TMS disrupts neural activity in a local circuit in early visual cortex using a computational model consisting of conductance-based spiking neurons with excitatory and inhibitory synaptic connections. We found that single-pulse TMS suppressed spiking activity in a local circuit model, disrupting the population response. Spike suppression was observed when TMS was applied to the local circuit within a limited time window after the local circuit received sensory afferent input, as observed in experiments investigating suppression of visual perception with TMS targeting early visual cortex. Quantitative analyses revealed that the magnitude of suppression was significantly larger for synaptically-connected neurons than for isolated individual neurons, suggesting that intracortical inhibitory synaptic coupling also plays an important role in TMS-induced suppression. A conventional local circuit model of early visual cortex explained only the early period of visual suppression observed in experiments. However, models either involving strong recurrent excitatory synaptic connections or sustained excitatory input were able to reproduce the late period of visual suppression. These results suggest that TMS targeting early visual cortex disrupts functionally distinct neural signals, possibly corresponding to feedforward and recurrent information processing, by imposing inhibitory effects through intracortical inhibitory synaptic connections.     

TRPM channels modulate epileptic-like convulsions via systemic ion homeostasis

Neuronal networks operate over a wide range of activity levels, with both neuronal and nonneuronal cells contributing to the balance of excitation and inhibition. Activity imbalance within neuronal networks underlies many neurological diseases, such as epilepsy. The Caenorhabditis elegans locomotor circuit operates via coordinated activity of cholinergic excitatory and GABAergic inhibitory transmission. We have previously shown that a gain-of-function mutation in a neuronal acetylcholine receptor, acr-2(gf), causes an epileptic-like convulsion behavior. Here we report that the behavioral and physiological effects of acr-2(gf) require the activity of the TRPM channel GTL-2 in nonneuronal tissues. Loss of gtl-2 function does not affect baseline synaptic transmission but can compensate for the excitation-inhibition imbalance caused by acr-2(gf). The compensatory effects of removing gtl-2 are counterbalanced by another TRPM channel, GTL-1, and can be recapitulated by acute treatment with divalent cation chelators, including those specific for Zn(2+). Together, these data reveal an important role for ion homeostasis in the balance of neuronal network activity and a novel function of nonneuronal TRPM channels in the fine-tuning of this network activity.     

Ligand-gated ion channels: mechanisms underlying ion selectivity

Anion/cation selectivity is a critical property of ion channels and underpins their physiological function. Recently, there have been numerous mutagenesis studies, which have mapped sites within the ion channel-forming segments of ligand-gated ion channels that are determinants of the ion selectivity. Site-directed mutations to specific amino acids within or flanking the M2 transmembrane segments of the anion-selective glycine, GABA(A) and GABA(C) receptors and the cation-selective nicotinic acetylcholine and serotonin (type 3) receptors have revealed discrete, equivalent regions within the ion channel that form the principal selectivity filter, leading to plausible molecular mechanisms and mathematical models to describe how ions preferentially permeate these channels. In particular, the dominant factor determining anion/cation selectivity seems to be the sign and exposure of charged amino acids lining the selectivity filter region of the open channel. In addition, the minimum pore diameter, which can be influenced by the presence of a local proline residue, also makes a contribution to such ion selectivity in LGICs with smaller diameters increasing anion/cation selectivity and larger ones decreasing it.     

Monoaminergic Orchestration of Motor Programs in a Complex C. elegans Behavior

Monoamines provide chemical codes of behavioral states. However, the neural mechanisms of monoaminergic orchestration of behavior are poorly understood. Touch elicits an escape response in Caenorhabditis elegans where the animal moves backward and turns to change its direction of locomotion. We show that the tyramine receptor SER-2 acts through a Gα_o pathway to inhibit neurotransmitter release from GABAergic motor neurons that synapse onto ventral body wall muscles. Extrasynaptic activation of SER-2 facilitates ventral body wall muscle contraction, contributing to the tight ventral turn that allows the animal to navigate away from a threatening stimulus. Tyramine temporally coordinates the different phases of the escape response through the synaptic activation of the fast-acting ionotropic receptor, LGC-55, and extrasynaptic activation of the slow-acting metabotropic receptor, SER-2. Our studies show, at the level of single cells, how a sensory input recruits the action of a monoamine to change neural circuit properties and orchestrate a compound motor sequence.     

Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity

In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational studies of sensory processing in neocortical network models equipped with synaptic plasticity.     

Asymmetry and Ion Selectivity Properties of Bacterial Channel NaK Mutants Derived from Ionotropic Glutamate Receptors

Ionotropic glutamate receptors are ligand-gated cation channels that play essential roles in the excitatory synaptic transmission throughout the central nervous system. A number of open-pore structures of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic-acid (AMPA)-type glutamate receptors became available recently by cryo-electron microscopy (cryo-EM). These structures provide valuable insights into the conformation of the selectivity filter (SF), the part of the ion channel that determines the ion selectivity. Nonetheless, due to the moderate resolution of the cryo-EM structures, detailed information such as ion occupancy of monovalent and divalent cations as well as positioning of the side-chains in the SF is still missing. Here, in an attempt to obtain high-resolution information about glutamate receptor SFs, we incorporated partial SF sequences of the AMPA and kainate receptors into the bacterial tetrameric cation channel NaK, which served as a structural scaffold. We determined a series of X-ray structures of NaK-CDI, NaK-SDI and NaK-SELM mutants at 1.42–2.10 Å resolution, showing distinct ion occupation of different monovalent cations. Molecular dynamics (MD) simulations of NaK-CDI indicated the channel to be conductive to monovalent cations, which agrees well with our electrophysiology recordings. Moreover, previously unobserved structural asymmetry of the SF was revealed by the X-ray structures and MD simulations, implying its importance in ion non-selectivity of tetrameric cation channels.     

Stability and structural constraints of random brain networks with excitatory and inhibitory neural populations

The stability of brain networks with randomly connected excitatory and inhibitory neural populations is investigated using a simplified physiological model of brain electrical activity. Neural populations are randomly assigned to be excitatory or inhibitory and the stability of a brain network is determined by the spectrum of the network’s matrix of connection strengths. The probability that a network is stable is determined from its spectral density which is numerically determined and is approximated by a spectral distribution recently derived by Rajan and Abbott. The probability that a brain network is stable is maximum when the total connection strength into a population is approximately zero and is shown to depend on the arrangement of the excitatory and inhibitory connections and the parameters of the network. The maximum excitatory and inhibitory input into a structure allowed by stability occurs when the net input equals zero and, in contrast to networks with randomly distributed excitatory and inhibitory connections, substantially increases as the number of connections increases. Networks with the largest excitatory and inhibitory input allowed by stability have multiple marginally stable modes, are highly responsive and adaptable to external stimuli, have the same total input into each structure with minimal variance in the excitatory and inhibitory connection strengths, and have a wide range of flexible, adaptable, and complex behavior.     

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.     

Chimeric mutations in the M2 segment of the 5-hydroxytryptamine-gated chloride channel MOD-1 define a minimal determinant of anion/cation permeability

The ionic selectivity of ligand-gated ion channels (LGICs) determines whether receptor activation produces an excitatory or inhibitory response. The determinants of anion/cation selectivity were investigated for a new member of the LGIC superfamily, MOD-1, a serotonin-gated chloride channel cloned from the nematode Caenorhabditis elegans. In common with other anionic LGICs (glycine receptors and GABA(A) receptors), the selectivity triple mutant in the pore-forming M2 segment (proline insertion, Ala --> Glu substitution at the central ring, and Thr --> Val at the hydrophobic ring) converted the selectivity of MOD-1 from anionic to cationic. Unlike other LGICs, however, this mutant in MOD-1 was highly selective for K+ over other cations. Subsets of this selectivity triple mutant were studied to define the minimal change required for conversion from anion-permeable to cation-permeable. The double mutant at the central ring of charge (deltaPro-269/A270E) produced a non-selective cation channel. Charge reversal at the central ring alone (A270E) was sufficient to convert MOD-1 to cation-permeable. These results refine the determinants of ion-charge selectivity in LGICs and demonstrate the critical role of the central ring of charge formed by the M2 segments.     

Electrophysiological Properties of Ion Channels in Ascaris suum Tissue Incorporated into Planar Lipid Bilayers

Ion channels are important targets of anthelmintic agents. In this study, we identified 3 types of ion channels in Ascaris suum tissue incorporated into planar lipid bilayers using an electrophysiological technique. The most frequent channel was a large-conductance cation channel (209 pS), which accounted for 64.5% of channels incorporated (n=60). Its open-state probability (P_o) was ~0.3 in the voltage range of −60~+60 mV. A substate was observed at 55% of the main-state. The permeability ratio of Cl⁻ to K⁺ (P_Cl/P_K) was ~0.5 and P_Na/P_K was 0.81 in both states. Another type of cation channel was recorded in 7.5% of channels incorporated (n=7) and discriminated from the large-conductance cation channel by its smaller conductance (55.3 pS). Its Po was low at all voltages tested (~0.1). The third type was an anion channel recorded in 27.9% of channels incorporated (n=26). Its conductance was 39.0 pS and P_Cl/P_K was 8.6±0.8. P_o was ~1.0 at all tested potentials. In summary, we identified 2 types of cation and 1 type of anion channels in Ascaris suum. Gating of these channels did not much vary with voltage and their ionic selectivity is rather low. Their molecular nature, functions, and potentials as anthelmintic drug targets remain to be studied further.     

Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs.     

Ion coordination in the amphotericin B channel.

The antifungal polyene antibiotic amphotericin B forms channels in lipid membranes that are permeable to ions, water, and nonelectrolytes. Anion, cation, and ion pair coordination in the water-filled pore of the "barrel" unit of the channels was studied by molecular dynamics simulations. Unlike the case of the gramicidin A channel, the water molecules do not create a single-file configuration in the pore, and some cross sections of the channel contain three or four water molecules. Both the anion and cation are strongly bound to ligand groups and water molecules located in the channel. The coordination number of the ions is about six. The chloride has two binding sites in the pore. The binding with water is dominant; more than four water molecules are localized in the anion coordination sphere. Three motifs of the ion coordination were monitored. The dominant motif occurs when the anion is bound to one ligand group. The ion is bound to two or three ligand groups in the less favorable configurations. The strong affinity of cations to the channel is determined by the negatively charged ligand oxygens, whose electrostatic field dominates over the field of the hydrogens. The ligand contribution to the coordination number of the sodium ion is noticeably higher than in the case of the anion. As in the case of the anion, there are three motifs of the cation coordination. The favorable one occurs when the cation is bound to two ligand oxygens. In the less favorable cases, the cation is bound to three or four oxygens. In the contact ion pair, the cation and anion are bound to two ligand oxygens and one ligand hydrogen, respectively. There exist intermediate solvent-shared states of the ion pair. The average distances between ions in these states are twice as large as that of the contact ion pair. The stability of the solvent-shared state is defined by the water molecule oriented along the electrostatic field of both ions.     

A neural network model for the mechanism of feature-extraction

We propose a new multilayered neural network model which has the ability of rapid self-organization. This model is a modified version of the cognitron (Fukushima, 1975). It has modifiable inhibitory feedback connections, as well as conventional modifiable excitatory feedforward connections, between the cells of adjoining layers. If a feature-extracting cell in the network is excited by a stimulus which is already familiar to the network, the cell immediately feeds back inhibitory signals to its presynaptic cells in the preceding layer, which suppresses their response. On the other hand, the feature-extracting cell does not respond to an unfamiliar feature, and the responses from its presynaptic cells are therefore not suppressed because they do not receive any feedback inhibition. Modifiable synapses in the new network are reinforced in a way similar to those in the cognitron, and synaptic connections from cells yielding a large sustained output are reinforced. Since familiar stimulus features do not elicit a sustained response from the cells of the network, only circuits which detect novel stimulus features develop. The network therefore quickly acquires favorable pattern-selectivity by the mere repetitive presentation of set of learning patterns.     

Long-term plasticity at inhibitory synapses

Experience-dependent modifications of neural circuits and function are believed to heavily depend on changes in synaptic efficacy such as LTP/LTD. Hence, much effort has been devoted to elucidating the mechanisms underlying these forms of synaptic plasticity. Although most of this work has focused on excitatory synapses, it is now clear that diverse mechanisms of long-term inhibitory plasticity have evolved to provide additional flexibility to neural circuits. By changing the excitatory/inhibitory balance, GABAergic plasticity can regulate excitability, neural circuit function and ultimately, contribute to learning and memory, and neural circuit refinement. Here we discuss recent advancements in our understanding of the mechanisms and functional relevance of GABAergic inhibitory synaptic plasticity.     

Ion channels from synaptic vesicle membrane fragments reconstituted into lipid bilayers.

Cholinergic synaptic vesicles were isolated from the electric organ of Torpedo californica. Vesicle membrane proteins were reconstituted into planar lipid bilayers by the nystatin/ergosterol fusion technique. After fusion, a variety of ion channels were observed. Here we identify four channels and describe two of them in detail. The two channels share a conductance of 13 pS. The first is anion selective and strongly voltage dependent, with a 50% open probability at membrane potentials of -15 mV. The second channel is slightly cation selective and voltage independent. It has a high open probability and a subconductance state. A third channel has a conductance of 4-7 pS, similar to the subconductance state of the second channel. This channel is fairly nonselective and has gating kinetics different from those of the cation channel. Finally, an approximately 10-pS, slightly cation selective channel was also observed. The data indicate that there are one or two copies of each of the above channels in every synaptic vesicle, for a total of six channels per vesicle. These observations confirm the existence of ion channels in synaptic vesicle membranes. It is hypothesized that these channels are involved in vesicle recycling and filling.     

Plasticity of GABAergic synapses in the neonatal rat hippocampus

While the development and plasticity of excitatory synaptic connections have been studied into detail, little is known about the development of inhibitory synapses. As proposed for excitatory synapses, recent studies have indicated that activity-dependent forms of synaptic plasticity, such as long-term potentiation and long-term depression, may play a role in the establishment of functional inhibitory synaptic connections. Here, I review these different forms of plasticity and focus on their possible role in the developing neuronal network.     

A neural network model for trace conditioning

We studied the dynamics of a neural network that has both recurrent excitatory and random inhibitory connections. Neurons started to become active when a relatively weak transient excitatory signal was presented and the activity was sustained due to the recurrent excitatory connections. The sustained activity stopped when a strong transient signal was presented or when neurons were disinhibited. The random inhibitory connections modulated the activity patterns of neurons so that the patterns evolved without recurrence with time. Hence, a time passage between the onsets of the two transient signals was represented by the sequence of activity patterns. We then applied this model to represent the trace eye blink conditioning, which is mediated by the hippocampus. We assumed this model as CA3 of the hippocampus and considered an output neuron corresponding to a neuron in CA1. The activity pattern of the output neuron was similar to that of CA1 neurons during trace eye blink conditioning, which was experimentally observed.     

Possible dual effect of synapses that are putatively purely excitatory or purely inhibitory: bases in stability theory and implications for neural network behavior

Depolarization of an excitable membrane has a dual effect; excitatory in that it causes rapid opening of calcium and/or sodium channels but inhibitory in that it also causes those channels to inactivate. We considered whether apparently paradoxical or dual behavior might be exhibited by excitatory and inhibitory synaptic inputs. We used the classic Hodgkin-Huxley model for voltage-gated channels plus leakage channels of appropriate selectivity for ligand-gated postsynaptic channels. We summarize a model cell's behavior by calculating elicited firing frequency as a function of reversal potential and conductance of summed synaptic inputs, using stability theory and direct simulations. Dual behavior is elicited in the model with reasonable densities of ligand-gated channels. Thus a particular synaptic input to a neuron may be either excitatory or inhibitory depending on simultaneous activity of other synaptic inputs to the cell. This input-output map may give rise to biologically realistic and rich behaviors as an element of computed neural networks, and still be computationally tractable.     

Excitatory and feed-forward inhibitory hippocampal synapses work synergistically as an adaptive filter of natural spike trains

Short-term synaptic plasticity (STP) is an important mechanism for modifying neural circuits during computation. Although STP is much studied, its role in the processing of complex natural spike patterns is unknown. Here we analyze the responses of excitatory and inhibitory hippocampal synapses to natural spike trains at near-physiological temperatures. Our results show that excitatory and inhibitory synapses express complementary sets of STP components that selectively change synaptic strength during epochs of high-frequency discharge associated with hippocampal place fields. In both types of synapses, synaptic strength rapidly alternates between a near-constant level during low activity and another near-constant, but elevated (for excitatory synapses) or reduced (for inhibitory synapses) level during high-frequency epochs. These history-dependent changes in synaptic strength are largely independent of the particular temporal pattern within the discharges, and occur concomitantly in the two types of synapses. When excitatory and feed-forward inhibitory synapses are co-activated within the hippocampal feed-forward circuit unit, the net effect of their complementary STP is an additional increase in the gain of excitatory synapses during high-frequency discharges via selective disinhibition. Thus, excitatory and feed-forward inhibitory hippocampal synapses in vitro act synergistically as an adaptive filter that operates in a switch-like manner and is selective for high-frequency epochs.