神经元放电阈值的可变性及其意义

神经元能够将不同时空模式的突触输入转化为时序精确的动作电位输出，这种灵活、可靠的信息编码方式是神经集群在动态环境或特定任务下产生所需活动模式的重要基础。动作电位的产生遵循全或无规律，只有当细胞膜电压达到放电阈值时，神经元才产生动作电位。放电阈值在细胞内和细胞间具有高度可变性，具体动态依赖于刺激输入和放电历史。特别是，放电阈值对动作电位起始前的膜电压变化十分敏感，这种状态依赖性产生的生物物理根源包括Na⁺失活和K⁺激活。在绝大多数神经元中，动作电位的触发位置是轴突起始端，这个位置处的阈值可变性是决定神经元对时空输入转化规律的关键因素。但是，电生理实验中动作电位的记录位置却通常是胞体或近端树突，此处的阈值可变性高于轴突起始端，而其产生的重要根源是轴突动作电位的反向传播。基于胞体测量的相关研究显示，放电阈值动态能够增强神经元的时间编码、特征选择、增益调控和同时侦测能力。本文首先介绍放电阈值的概念及量化方法，然后详细梳理近年来国内外关于放电阈值可变性及产生根源的研究进展，在此基础上归纳总结放电阈值可变性对神经元编码的重要性，最后对未来放电阈值的研究方向进行展望。     

A thalamo-cortical neural mass model for the simulation of brain rhythms during sleep

Cortico-thalamic interactions are known to play a pivotal role in many brain phenomena, including sleep, attention, memory consolidation and rhythm generation. Hence, simple mathematical models that can simulate the dialogue between the cortex and the thalamus, at a mesoscopic level, have a great cognitive value. In the present work we describe a neural mass model of a cortico-thalamic module, based on neurophysiological mechanisms. The model includes two thalamic populations (a thalamo-cortical relay cell population, TCR, and its related thalamic reticular nucleus, TRN), and a cortical column consisting of four connected populations (pyramidal neurons, excitatory interneurons, inhibitory interneurons with slow and fast kinetics). Moreover, thalamic neurons exhibit two firing modes: bursting and tonic. Finally, cortical synapses among pyramidal neurons incorporate a disfacilitation mechanism following prolonged activity. Simulations show that the model is able to mimic the different patterns of rhythmic activity in cortical and thalamic neurons (beta and alpha waves, spindles, delta waves, K-complexes, slow sleep waves) and their progressive changes from wakefulness to deep sleep, by just acting on modulatory inputs. Moreover, simulations performed by providing short sensory inputs to the TCR show that brain rhythms during sleep preserve the cortex from external perturbations, still allowing a high cortical activity necessary to drive synaptic plasticity and memory consolidation. In perspective, the present model may be used within larger cortico-thalamic networks, to gain a deeper understanding of mechanisms beneath synaptic changes during sleep, to investigate the specific role of brain rhythms, and to explore cortical synchronization achieved via thalamic influences.     

Prolonged modification of action potential shape by synaptic inputs in molluscan neurones

1. Somatic action potentials of Lymnaea neurons are modified by excitatory or inhibitory synaptic inputs and have been studied using phase-plane techniques and an action potential duration monitor. 2. Excitatory synaptic inputs increase the rate of neuronal discharge, cause action potential broadening, a decrease in the maximum rate of depolarization (Vd) and a decrease in the maximum rate of repolarization (Vr). 3. Inhibitory synaptic inputs decrease the discharge rate and cause narrowing of action potentials, an increase in Vd and an increase in Vr. 4. The effects reported above outlast the original synaptic inputs by many seconds and, if the somatic action potentials are similar to those in the axon terminals, they may have far-reaching effects on transmitter release.     

Statistical independence and neural computation in the leech ganglion

 In this report, the input/output relations in an isolated ganglion of the leech Hirudo medicinalis were studied by simultaneously using six or eight suction pipettes and two intracellular electrodes. Sensory input was mimicked by eliciting action potentials in mechanosensory neurons with intracellular electrodes. The integrated neural output was measured by recording extracellular voltage signals with pipettes sucking the roots and the connectives. A single evoked action potential activated electrical activity in at least a dozen different neurons, some of which were identified. This electrical activity was characterized by a high degree of temporal and spatial variability. The action potentials of coactivated neurons, i.e. activated by the same mechanosensory neuron, did not show any significant pairwise correlation. Indeed, the analysis of evoked action potentials indicates clear statistical independence among coactivated neurons, presumably originating from the independence of synaptic transmission at distinct synapses. This statistical independence may be used to increase reliability when neuronal activity is averaged or pooled. It is suggested that statistical independence among coactivated neurons may be a usual property of distributed processing of neuronal networks and a basic feature of neural computation. Received: 20 September 1999 / Accepted in revised form: 3 March 2000     

Tuning neocortical pyramidal neurons between integrators and coincidence detectors

Do cortical neurons operate as integrators or as coincidence detectors? Despite the importance of this question, no definite answer has been given yet, because each of these two views can find its own experimental support. Here we investigated this question using models of morphologically-reconstructed neocortical pyramidal neurons under in vivo like conditions. In agreement with experiments we find that the cell is capable of operating in a continuum between coincidence detection and temporal integration, depending on the characteristics of the synaptic inputs. Moreover, the presence of synaptic background activity at a level comparable to intracellular measurements in vivo can modulate the operating mode of the cell, and act as a switch between temporal integration and coincidence detection. These results suggest that background activity can be viewed as an important determinant of the integrative mode of pyramidal neurons. Thus, background activity not only sharpens cortical responses but it can also be used to tune an entire network between integration and coincidence detection modes.     

Calcium-activated chloride channels (CaCCs) regulate action potential and synaptic response in hippocampal neurons

Central neurons respond to synaptic inputs from other neurons by generating synaptic potentials. Once the summated synaptic potentials reach threshold for action potential firing, the signal propagates leading to transmitter release at the synapse. The calcium influx accompanying such signaling opens calcium-activated ion channels for feedback regulation. Here, we report a mechanism for modulating hippocampal neuronal signaling that involves calcium-activated chloride channels (CaCCs). We present evidence that CaCCs reside in hippocampal neurons and are in close proximity of calcium channels and NMDA receptors to shorten action potential duration, dampen excitatory synaptic potentials, impede temporal summation, and raise the threshold for action potential generation by synaptic potential. Having recently identified TMEM16A and TMEM16B as CaCCs, we further show that TMEM16B but not TMEM16A is important for hippocampal CaCC, laying the groundwork for deciphering the dynamic CaCC modulation of neuronal signaling in neurons important for learning and memory.     

Characterising neural representation in terms of the dynamics of cell membrane potential activity: a control theoretic approach using differential geometry

Experimental and theoretical results seem to demand that the study of neural representations in the brain considers both the subthreshold and suprathreshold dynamic activity of the neural membrane potential, rather than be solely focussed on stimulus representation in trains of action potentials. In a dynamical systems formulation, the membrane potential can be regarded as the "state" of the neuron, evolving continuously over time and space, within an infinite dimensional space, in response to ever changing inputs. Formally, the state of the neuron, together with future inputs, is sufficient to fully determine the future behaviour of the neuron. In this paper, the characterisation of membrane potential activity is approached from a control theoretic viewpoint as a "reachability" problem, in which the effect of particular stimulus-evoked synaptic inputs is seen as driving the cell from some initial state of the neuron to a particular terminal state on a given manifold. It is shown that a fluctuating subthreshold membrane potential induced by synaptic background activity, and the cooperative interaction of excitatory and inhibitory inputs, may be important factors in allowing the cell to "reach" a maximal subset of all possible membrane potential states, through the action of its synaptic inputs.     

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.     

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells

Ganglion cells are the output neurons of the retina and their activity reflects the integration of multiple synaptic inputs arising from specific neural circuits. Patch clamp techniques, in voltage clamp and current clamp configurations, are commonly used to study the physiological properties of neurons and to characterize their synaptic inputs. Although the application of these techniques is highly informative, they pose various limitations. For example, it is difficult to quantify how the precise interactions of excitatory and inhibitory inputs determine response output. To address this issue, we used a modified current clamp technique, dynamic clamp, also called conductance clamp ^{1, 2, 3} and examined the impact of excitatory and inhibitory synaptic inputs on neuronal excitability. This technique requires the injection of current into the cell and is dependent on the real-time feedback of its membrane potential at that time. The injected current is calculated from predetermined excitatory and inhibitory synaptic conductances, their reversal potentials and the cell''s instantaneous membrane potential. Details on the experimental procedures, patch clamping cells to achieve a whole-cell configuration and employment of the dynamic clamp technique are illustrated in this video article. Here, we show the responses of mouse retinal ganglion cells to various conductance waveforms obtained from physiological experiments in control conditions or in the presence of drugs. Furthermore, we show the use of artificial excitatory and inhibitory conductances generated using alpha functions to investigate the responses of the cells.     

Emerging methodologies for the study of hypothalamic gonadotropin-releasing-hormone (GnRH) neurons

Gonadotropin-releasing-hormone (GnRH) neurons form part of a central neural oscillator that controls sexual reproduction through intermittent release of the GnRH peptide. Activity of GnRH neurons, and by extension release of GnRH, has been proposed to reflect intrinsic properties and synaptic input of GnRH neurons. To study GnRH neurons, we used traditional electrophysiology and computational methods. These emerging methodologies enhance the elucidation of processing in GnRH neurons. We used dynamic current-clamping to understand how living GnRH somata process input from glutamate and GABA, two key neurotransmitters in the neuroendocrine hypothalamus. In order to study the impact of synaptic integration in dendrites and neuronal morphology, we have developed full-morphology models of GnRH neurons. Using dynamic clamping, we have demonstrated that small-amplitude glutamatergic currents can drive repetitive firing in GnRH neurons. Furthermore, application of simulated GABAergic synapses with a depolarized reversal potential have revealed two functional subpopulations of GnRH neurons: one population in which GABA chronically depolarizes membrane potential (without inducing action potentials) and a second population in which GABAergic excitation results in slow spiking. Finally, when AMPA-type and GABA-type simulated inputs are applied together, action potentials occur when the AMPA-type conductance occurs during the descending phase of GABAergic excitation and at the nadir of GABAergic inhibition. Compartmental computer models have shown that excitatory synapses at >300 microns from somtata are unable to drive spiking with purely passive dendrites. In models with active dendrites, distal synapses are more efficient at driving spiking than somatic inputs. We then used our models to extend the results from dynamic current clamping at GnRH somata to distribute synaptic inputs along the dendrite. We show that propagation delays for dendritic synapses alter synaptic integration in GnRH neurons by widening the temporal window of interaction for the generation of action potentials. Finally, we have shown that changes in dendrite morphology can modulate the output of GnRH neurons by altering the efficacy of action potential generation in response to after-depolarization potentials (ADPs). Taken together, the methodologies of dynamic current clamping and multi-compartmental modeling can make major contributions to the study of synaptic integration and structure-function relationships in hypothalamic GnRH neurons. Use of these methodological approaches will continue to provide keen insights leading to conceptual advances in our understanding of reproductive hormone secretion in normal and pathological physiology and open the door to understanding whether the mechanisms of pulsatile GnRH release are conserved across species.     

锥体神经元的连接模式对突触后局部电位的依赖

脑皮层的功能连接模式与突触可塑性密切相关,受突触空间分布和刺激模式等多种因素的影响。尽管越来越多的证据表明突触可塑性不仅受突触后动作电位而且还受突触后局部树突电位的影响,但是目前尚不清楚神经元的功能连接模式是否和怎样依赖于突触后局部电位的。为此,本文建立了一个无需硬边界设置的、突触后局部膜电位依赖的可塑性模型。该模型具有突触强度的自平衡能力并且能够再现多种突触可塑性实验结果。基于该模型对两个锥体神经元的功能连接模式进行仿真的结果表明,当突触后局部电位都处于亚阈值时两个神经元无功能连接,如果一个神经元的突触后膜电位高于阈值电位则产生向该神经元的单向连接,当两个神经元的突触后膜电位都超过阈值电位时则产生双向连接,说明突触后局部膜电位分布是神经元功能连接模式形成的关键。研究结果加深了神经网络连接模式形成机制的理解,对学习和记忆的研究具有重要意义。     

Synaptic integration gradients in single cortical pyramidal cell dendrites

Cortical pyramidal neurons receive thousands of synaptic inputs arriving at different dendritic locations with varying degrees of temporal synchrony. It is not known if different locations along single cortical dendrites integrate excitatory inputs in different ways. Here we have used two-photon glutamate uncaging and compartmental modeling to reveal a gradient of nonlinear synaptic integration in basal and apical oblique dendrites of cortical pyramidal neurons. Excitatory inputs to the proximal dendrite sum linearly and require precise temporal coincidence for effective summation, whereas distal inputs are amplified with high gain and integrated over broader time windows. This allows distal inputs to overcome their electrotonic disadvantage, and become surprisingly more effective than proximal inputs at influencing action potential output. Thus, single dendritic branches can already exhibit nonuniform synaptic integration, with the computational strategy shifting from temporal coding to rate coding along the dendrite.     

Altered Neuronal Intrinsic Properties and Reduced Synaptic Transmission of the Rat's Medial Geniculate Body in Salicylate-Induced Tinnitus

Sodium salicylate (NaSal), an aspirin metabolite, can cause tinnitus in animals and human subjects. To explore neural mechanisms underlying salicylate-induced tinnitus, we examined effects of NaSal on neural activities of the medial geniculate body (MGB), an auditory thalamic nucleus that provides the primary and immediate inputs to the auditory cortex, by using the whole-cell patch-clamp recording technique in MGB slices. Rats treated with NaSal (350 mg/kg) showed tinnitus-like behavior as revealed by the gap prepulse inhibition of acoustic startle (GPIAS) paradigm. NaSal (1.4 mM) decreased the membrane input resistance, hyperpolarized the resting membrane potential, suppressed current-evoked firing, changed the action potential, and depressed rebound depolarization in MGB neurons. NaSal also reduced the excitatory and inhibitory postsynaptic response in the MGB evoked by stimulating the brachium of the inferior colliculus. Our results demonstrate that NaSal alters neuronal intrinsic properties and reduces the synaptic transmission of the MGB, which may cause abnormal thalamic outputs to the auditory cortex and contribute to NaSal-induced tinnitus.     

GABA-mediated synaptic inhibition of projection neurons in the antennal lobes of the sphinx moth,Manduca sexta

Responses of neurons in the antennal lobe (AL) of the moth Manduca sexta to stimulation of the ipsilateral antenna by odors consist of excitatory and inhibitory synaptic potentials. Stimulation of primary afferent fibers by electrical shock of the antennal nerve causes a characteristic IPSP-EPSP synaptic response in AL projection neurons. The IPSP in projection neurons reverses below the resting potential, is sensitive to changes in external and internal chloride concentration, and thus is apparently mediated by an increase in chloride conductance. The IPSP is reversibly blocked by 100 microM picrotoxin or bicuculline. Many AL neurons respond to application of GABA with a strong hyperpolarization and an inhibition of spontaneous spiking activity. GABA responses are associated with an increase in neuronal input conductance and a reversal potential below the resting potential. Application of GABA blocks inhibitory synaptic inputs and reduces or blocks excitatory inputs. EPSPs can be protected from depression by application of GABA. Muscimol, a GABA analog that mimics GABA responses at GABAA receptors but not at GABAB receptors in the vertebrate CNS, inhibits many AL neurons in the moth.     

p53 Mutation suppresses adult neurogenesis in medaka fish (Oryzias latipes)

Acid-base imbalance leads to pathological cognition and behaviors in the clinical practices. In the comparison with acidosis, the cellular mechanisms underlying alkalosis-induced brain dysfunction remain unclear. By using electrophysiological approach, we investigated the influences of high extracellular pH environment on cortical GABAergic neurons in terms of their responsiveness to synaptic inputs and their ability to produce action potentials. Artificial cerebral spinal fluid in high pH impairs excitatory synaptic transmission and spike initiation in cortical GABAergic neurons. The alkalosis-induced dysfunction of GABAergic neurons is associated with the decrease of receptor responsiveness and the increases of spike refractory periods and threshold potentials. Our studies reveal that alkalosis impairs cortical GABAergic neurons and subsequently deteriorate brain functions. The molecular targets for alkalosis action include glutamate receptor-channels and voltage-gated sodium channels on GABAergic neurons.     

Variability and coding efficiency of noisy neural spike encoders

Encoding synaptic inputs as a train of action potentials is a fundamental function of nerve cells. Although spike trains recorded in vivo have been shown to be highly variable, it is unclear whether variability in spike timing represents faithful encoding of temporally varying synaptic inputs or noise inherent in the spike encoding mechanism. It has been reported that spike timing variability is more pronounced for constant, unvarying inputs than for inputs with rich temporal structure. This could have significant implications for the nature of neural coding, particularly if precise timing of spikes and temporal synchrony between neurons is used to represent information in the nervous system. To study the potential functional role of spike timing variability, we estimate the fraction of spike timing variability which conveys information about the input for two types of noisy spike encoders--an integrate and fire model with randomly chosen thresholds and a model of a patch of neuronal membrane containing stochastic Na(+) and K(+) channels obeying Hodgkin-Huxley kinetics. The quality of signal encoding is assessed by reconstructing the input stimuli from the output spike trains using optimal linear mean square estimation. A comparison of the estimation performance of noisy neuronal models of spike generation enables us to assess the impact of neuronal noise on the efficacy of neural coding. The results for both models suggest that spike timing variability reduces the ability of spike trains to encode rapid time-varying stimuli. Moreover, contrary to expectations based on earlier studies, we find that the noisy spike encoding models encode slowly varying stimuli more effectively than rapidly varying ones.     

Mechanism of activation of human c-KIT kinase by internal tandem duplications of the juxtamembrane domain and point mutations at aspartic acid 816

The patients suffering from acidosis usually sign psychological deficits. The cerebral dysfunction is reportedly caused by an acid-induced functional impairment of GABAergic neurons; however, the role of pyramidal neurons in this process remains unclear. By using electrophysiological method and changing extracellular pH, we investigated the influence of acidic environment on pyramidal neurons in the cortical slices, such as their ability of firing spikes and response to synaptic inputs. A low pH of artificial cerebral spinal fluid elevates the responses of pyramidal neurons to excitatory synaptic inputs and their ability of encoding digital spikes, as well as reduces the signal transmission at GABAergic synapses. The elevated ability of neuronal spiking is associated with the decreases of refractory periods and threshold potentials. Therefore, acidosis deteriorates brain functions through making the activities between cortical pyramidal neurons and GABAergic neurons imbalanced toward the overexcitation of neural networks, a process similar to neural excitotoxicity.     

Role of active dendritic conductances in subthreshold input integration

Dendrites of many types of neurons contain voltage-dependent conductances that are active at subthreshold membrane potentials. To understand the computations neurons perform it is key to understand the role of active dendrites in the subthreshold processing of synaptic inputs. We examine systematically how active dendritic conductances affect the time course of postsynaptic potentials propagating along dendrites, and how they affect the interaction between such signals. Voltage-dependent currents can be classified into two types that have qualitatively different effects on subthreshold input responses: regenerative dendritic currents boost and broaden EPSPs, while restorative currents attenuate and narrow EPSPs. Importantly, the effects of active dendritic currents on EPSP shape increase as the EPSP travels along the dendrite. The effectiveness of active currents in modulating the EPSP shape is determined by their activation time constant: the faster it is, the stronger the effect on EPSP amplitude, while the largest effects on EPSP width occur when it is comparable to the membrane time constant. We finally demonstrate that the two current types can differentially improve precision and robustness of neural computations: restorative currents enhance coincidence detection of dendritic inputs, whereas direction selectivity to sequences of dendritic inputs is enhanced by regenerative dendritic currents.