Electrogenic Na⁺/HCO₃⁻ co-transporter-1 is essential for the parathyroid hormone-stimulated intestinal HCO₃⁻ secretion

Acidosis, associated with metabolic disorders, leads to the pathological changes of cognition and behavior in the clinical practices of neurology and psychology. The cellular mechanisms underlying these cerebral dysfunctions remain unclear. By using electrophysiological approach and changing extracellular pH, we have investigated the effects of acidic environment on cortical GABAergic neurons in terms of their abilities of firing spikes and responses to synaptic inputs. Artificial cerebral spinal fluid in low pH impairs the responses to excitatory synaptic inputs and the abilities of encoding sequential spikes at these GABAergic neurons. The impairments of neuronal spiking are associated with the increases of refractory periods and threshold potentials. Our studies reveal that acidosis may impair cortical GABAergic neurons and in turn deteriorate brain functions, in which their final targets are voltage-gated sodium channels and glutamate receptor-channels.     

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.     

碱中毒对小鼠皮质GABA能神经元特性和编码能力的影响

目的:研究碱中毒对小鼠皮质GABA能神经元内在特性和编码能力的影响,探讨碱中毒引起大脑功能障碍的机制。方法:选择17-22天FVB-Tg小鼠行脑片体外培养,实验对象分为碱中毒组和对照组。DIC光学显微镜下选择皮层II-III层GABA神经元,运用Axo Patch 200 B放大器全细胞模式,记录并分析神经元内在特性(包括阈电位、绝对不应期)的改变;记录与去极化脉冲相对应的峰值,分析GABA能神经元的编码能力。结果:1.阈电位峰值在对照组分别是24.58±0.68,25.44±0.82,27.02±0.78,27.55±0.74和28.66±0.79毫伏,碱中毒组分别是28.32±0.78,30.10±0.91,32.22±0.80,32.88±0.76和33.54±0.74毫伏,碱中毒组阈电位升高;绝对不应期在对照组和碱中毒组分别是4.15±0.06和5.09±0.08毫秒,碱中毒绝对不应期延长。2.两组在相同去极化刺激下诱发的连续峰值波形发生明显改变,碱中毒组产生峰值的能力下降。结论:1、碱中毒使皮质GABA能神经元动阈电位升高和绝对不应期延长;2、碱中毒降低皮质GABA能神经元编码峰值能力。     

Acidosis-Induced Dysfunction of Cortical GABAergic Neurons through Astrocyte-Related Excitotoxicity

Background

Acidosis impairs cognitions and behaviors presumably by acidification-induced changes in neuronal metabolism. Cortical GABAergic neurons are vulnerable to pathological factors and their injury leads to brain dysfunction. How acidosis induces GABAergic neuron injury remains elusive. As the glia cells and neurons interact each other, we intend to examine the role of the astrocytes in acidosis-induced GABAergic neuron injury.

Results

Experiments were done at GABAergic cells and astrocytes in mouse cortical slices. To identify astrocytic involvement in acidosis-induced impairment, we induced the acidification in single GABAergic neuron by infusing proton intracellularly or in both neurons and astrocytes by using proton extracellularly. Compared the effects of intracellular acidification and extracellular acidification on GABAergic neurons, we found that their active intrinsic properties and synaptic outputs appeared more severely impaired in extracellular acidosis than intracellular acidosis. Meanwhile, extracellular acidosis deteriorated glutamate transporter currents on the astrocytes and upregulated excitatory synaptic transmission on the GABAergic neurons. Moreover, the antagonists of glutamate NMDA-/AMPA-receptors partially reverse extracellular acidosis-induced injury in the GABAergic neurons.

Conclusion

Our studies suggest that acidosis leads to the dysfunction of cortical GABAergic neurons by astrocyte-mediated excitotoxicity, in addition to their metabolic changes as indicated previously.     

Long-term potentiation in rat hippocampal neurons is accompanied by spatially widespread changes in intrinsic oscillatory dynamics and excitability

Oscillations in neural activity are a prominent feature of many brain states. Individual hippocampal neurons exhibit intrinsic membrane potential oscillations and intrinsic resonance in the theta frequency range. We found that the subthreshold resonance frequency of CA1 pyramidal neurons was location dependent, varying more than 3-fold between the soma and the distal dendrites. Furthermore, activity- and NMDA-receptor-dependent long-term plasticity increased this resonance frequency through changes in h channel properties. The increase in resonance frequency and an associated reduction in excitability were nearly identical in the soma and the first 300 mum of the apical dendrites. These spatially widespread changes accompanying long-term synaptic potentiation also reduced the neuron's ability to elicit spikes evoked through a nonpotentiated synaptic pathway. Our results suggest that the frequency response of these neurons depends on the dendritic location of their inputs and that activity can regulate their response dynamics within an oscillating neural network.     

Intracellular Ca regulates spike encoding at cortical GABAergic neurons and cerebellar Purkinje cells differently

Spike encoding at GABAergic neurons plays an important role in maintaining the homeostasis of brain functions for well-organized behaviors. The rise of intracellular Ca²⁺ in GABAergic neurons causes synaptic plasticity. It is not clear how intracellular Ca²⁺ influences their spike encoding. We have investigated this issue at GFP-labeled GABAergic cortical neurons and cerebellar Purkinje cells by whole-cell recording in mouse brain slices. Our results show that an elevation of intracellular Ca²⁺ by infusing adenophostin-A lowers spike encoding at GABAergic cortical neurons and enhances encoding ability at cerebellar Purkinje cells. These differential effects of cytoplasmic Ca²⁺ on spike encoding are mechanistically associated with Ca²⁺-induced changes in the refractory periods and threshold potentials of sequential spikes, as well as with various expression ratios of CaM-KII to calcineurin in GABAergic cortical neurons and cerebellar Purkinje cells.     

A computational framework for cortical learning

Recent physiological findings have revealed that long-term adaptation of the synaptic strengths between cortical pyramidal neurons depends on the temporal order of presynaptic and postsynaptic spikes, which is called spike-timing-dependent plasticity (STDP) or temporally asymmetric Hebbian (TAH) learning. Here I prove by analytical means that a physiologically plausible variant of STDP adapts synaptic strengths such that the presynaptic spikes predict the postsynaptic spikes with minimal error. This prediction error model of STDP implies a mechanism for cortical memory: cortical tissue learns temporal spike patterns if these spike patterns are repeatedly elicited in a set of pyramidal neurons. The trained network finishes these patterns if their beginnings are presented, thereby recalling the memory. Implementations of the proposed algorithms may be useful for applications in voice recognition and computer vision.     

Conversion of Phase Information into a Spike-Count Code by Bursting Neurons

Single neurons in the cerebral cortex are immersed in a fluctuating electric field, the local field potential (LFP), which mainly originates from synchronous synaptic input into the local neural neighborhood. As shown by recent studies in visual and auditory cortices, the angular phase of the LFP at the time of spike generation adds significant extra information about the external world, beyond the one contained in the firing rate alone. However, no biologically plausible mechanism has yet been suggested that allows downstream neurons to infer the phase of the LFP at the soma of their pre-synaptic afferents. Therefore, so far there is no evidence that the nervous system can process phase information. Here we study a model of a bursting pyramidal neuron, driven by a time-dependent stimulus. We show that the number of spikes per burst varies systematically with the phase of the fluctuating input at the time of burst onset. The mapping between input phase and number of spikes per burst is a robust response feature for a broad range of stimulus statistics. Our results suggest that cortical bursting neurons could play a crucial role in translating LFP phase information into an easily decodable spike count code.     

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.     

Non-associative Potentiation of Perisomatic Inhibition Alters the Temporal Coding of Neocortical Layer 5 Pyramidal Neurons

In the neocortex, the coexistence of temporally locked excitation and inhibition governs complex network activity underlying cognitive functions, and is believed to be altered in several brain diseases. Here we show that this equilibrium can be unlocked by increased activity of layer 5 pyramidal neurons of the mouse neocortex. Somatic depolarization or short bursts of action potentials of layer 5 pyramidal neurons induced a selective long-term potentiation of GABAergic synapses (LTPi) without affecting glutamatergic inputs. Remarkably, LTPi was selective for perisomatic inhibition from parvalbumin basket cells, leaving dendritic inhibition intact. It relied on retrograde signaling of nitric oxide, which persistently altered presynaptic GABA release and diffused to inhibitory synapses impinging on adjacent pyramidal neurons. LTPi reduced the time window of synaptic summation and increased the temporal precision of spike generation. Thus, increases in single cortical pyramidal neuron activity can induce an interneuron-selective GABAergic plasticity effectively altering the computation of temporally coded information.     

The postnatal development of intrinsic properties and spike encoding at cortical GABAergic neurons

GABAergic neurons play a critical role in maintaining the homeostasis of brain functions for well-organized behaviors. It is not known about the dynamical change in signal encoding at these neurons during postnatal development. We investigated this issue at GFP-labeled GABAergic neurons by whole-cell recording in cortical slices of mice. Our results show that the ability of spike encoding at GABAergic neurons is improved during postnatal development. This change is associated with the reduction of refractory periods and threshold potentials of sequential spikes, as well as the improvement of linear correlations between intrinsic properties and spike capacity. Therefore, the postnatal maturation of the spike encoding capacity at GABAergic neurons will stabilize the excitatory state of cerebral cortex.     

Ca and acidosis synergistically lead to the dysfunction of cortical GABAergic neurons during ischemia

Cell death in cerebral ischemia is presumably initiated by neural excitotoxicity resulted from the dysfunction of inhibitory neurons in early stage. Molecular processes underlying the ischemic injury of inhibitory neurons remain to be elusive, which we investigated by biochemical manipulations with cellular imaging and patch clamp at GFP-labeled GABAergic cells in cortical slices. Ischemia induces Ca²⁺ elevation, acidosis and dysfunction in GABAergic cells. An elevation of cytoplasmic Ca²⁺ or H⁺ impairs the encoding of action potentials in these neurons. The effects of Ca²⁺ and H⁺ are additive in nature and occlude ischemic outcomes. Ischemia impairs spike production through prolonging spike refractory periods and raising threshold potentials. Therefore, calcium toxicity and acidosis during ischemia synergistically impair the dynamics of sodium channels and function of cortical GABAergic neurons, which lead to neural excitotoxicity. Our results also suggest that the cocktail therapeutics is needed to prevent neuronal death from ischemia.     

Maturation of GABAergic Inhibition Promotes Strengthening of Temporally Coherent Inputs among Convergent Pathways

Spike-timing-dependent plasticity (STDP), a form of Hebbian plasticity, is inherently stabilizing. Whether and how GABAergic inhibition influences STDP is not well understood. Using a model neuron driven by converging inputs modifiable by STDP, we determined that a sufficient level of inhibition was critical to ensure that temporal coherence (correlation among presynaptic spike times) of synaptic inputs, rather than initial strength or number of inputs within a pathway, controlled postsynaptic spike timing. Inhibition exerted this effect by preferentially reducing synaptic efficacy, the ability of inputs to evoke postsynaptic action potentials, of the less coherent inputs. In visual cortical slices, inhibition potently reduced synaptic efficacy at ages during but not before the critical period of ocular dominance (OD) plasticity. Whole-cell recordings revealed that the amplitude of unitary IPSCs from parvalbumin positive (Pv+) interneurons to pyramidal neurons increased during the critical period, while the synaptic decay time-constant decreased. In addition, intrinsic properties of Pv+ interneurons matured, resulting in an increase in instantaneous firing rate. Our results suggest that maturation of inhibition in visual cortex ensures that the temporally coherent inputs (e.g. those from the open eye during monocular deprivation) control postsynaptic spike times of binocular neurons, a prerequisite for Hebbian mechanisms to induce OD plasticity.     

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.     

Excitatory actions of GABA in the cortex

Little is known about how GABAergic inputs interact with excitatory inputs under conditions that maintain physiological concentrations of intracellular anions. Using extracellular and gramicidin perforated-patch recording, we show that somatic and dendritic GABA responses in mature cortical pyramidal neurons are depolarizing from rest and can facilitate action potential generation when combined with proximal excitatory input. Dendritic GABA responses were excitatory regardless of timing, whereas somatic GABA responses were inhibitory when coincident with excitatory input but excitatory at earlier times. These excitatory actions of GABA occur even though the GABA reversal potential is below action potential threshold and largely uniform across the somato-dendritic axis, and arise when GABAergic inputs are temporally or spatially isolated from concurrent excitation. Our findings demonstrate that under certain circumstances GABA will have an excitatory role in synaptic integration in the cortex.     

Afterhyperpolarization improves spike programming through lowering threshold potentials and refractory periods mediated by voltage-gated sodium channels

Neurons program various patterns of sequential spikes as neural codes to guide animal behavior. Studies show that spike programming (capacity and timing precision) is influenced by inhibitory synaptic inputs and membrane afterhyperpolarization (AHP). Less is clear about how these inhibitory components regulate spike programming, which we investigated at the cortical neurons. Whole-cell current-clamp recording for action potentials and single channel recording for voltage-gated sodium channels (VGSC) were conducted at regular-spiking and fast-spiking neurons in the cortical slices. With quantifying the threshold potentials and refractory periods of sequential spikes, we found that fast-spiking neurons expressing AHP possess lower threshold potentials and shorter refractory periods, and the hyperpolarization pulse immediately after each of spikes lowers threshold potentials and shortens refractory periods at regular-spiking neurons. Moreover, the hyperpolarization pulses shorten the refractory periods for VGSC reactivation and threshold potentials for its sequential activation. Our data indicate that inhibitory components immediately after spikes, such as AHP and recurrent inhibition, improve spike capacity and timing precision via lowering the refractory periods and threshold potentials mediated by voltage-gated sodium channels.     

Enhancement of spike-timing precision by autaptic transmission in neocortical inhibitory interneurons

In vivo studies suggest that precise firing of neurons is important for correct sensory representation. Principal neocortical neurons fire imprecisely when repeatedly activated by fixed sensory stimuli or current depolarizations. Here we show that in contrast to pyramidal neurons, firing in neocortical GABAergic fast-spiking (FS) interneurons is quite precise. FS interneurons are self-innervated by powerful GABAergic autaptic connections reliably activated after each spike, suggesting that autapses strongly regulate FS-cell spike timing. Indeed, blockade of autaptic transmission degraded temporal precision in multiple ways. Under these conditions, realistic dynamic-clamp hyperpolarizing autapses restored precision of spike timing, even in the presence of synaptic noise. Furthermore, firing precision was increased in pyramidal neurons by artificial GABAergic autaptic conductances, suggesting that tightly coupled synaptic feedback inhibition regulates spike timing in principal cells. Thus, well-timed inhibition, whether autaptic or synaptic, facilitates precise spike timing and promotes synchronized cortical network oscillations relevant to several behaviors.     

Quantal glutamate release is essential for reliable neuronal encodings in cerebral networks

Background

The neurons and synapses work coordinately to program the brain codes of controlling cognition and behaviors. Spike patterns at the presynaptic neurons regulate synaptic transmission. The quantitative regulations of synapse dynamics in spike encoding at the postsynaptic neurons remain unclear.

Methodology/Principal Findings

With dual whole-cell recordings at synapse-paired cells in mouse cortical slices, we have investigated the regulation of synapse dynamics to neuronal spike encoding at cerebral circuits assembled by pyramidal neurons and GABAergic ones. Our studies at unitary synapses show that postsynaptic responses are constant over time, such as glutamate receptor-channel currents at GABAergic neurons and glutamate transport currents at astrocytes, indicating quantal glutamate release. In terms of its physiological impact, our results demonstrate that the signals integrated from quantal glutamatergic synapses drive spike encoding at GABAergic neurons reliably, which in turn precisely set spike encoding at pyramidal neurons through feedback inhibition.

Conclusion/Significance

Our studies provide the evidences for the quantal glutamate release to drive the spike encodings precisely in cortical circuits, which may be essential for programming the reliable codes in the brain to manage well-organized behaviors.     

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.     

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex.