Spontaneous synchronous discharges in hippocampal slices. Simulation and experiment

Chaotic oscillations of extracellular potential of field-type nerve tissues are simulated by a 2D coupled map lattice. These tissues, say, the fields of the hippocampus, are represented by neural mass sheets consisting of current sources. The relationship between the source-sink ensembles and the extracellular field potential at each discrete instant of time t = 1, 2, ... is described by a single-site map creating chaos. The 2D coupled map lattice is viewed as a network of diffusively coupled the maps creating spatiotemporal chaos. The conversion of chaotic oscillations into synchronous ones, which are typical for epileptiform discharges, is studied. The results obtained are in good agreement with those derived from hippocampal slices treated with picrotoxin.     

Dissociation of temporal and frontal components in the human auditory N1 wave: a scalp current density and dipole model analysis

This study reports a combined scalp current density (SCD) and dipole model analysis of the N1 wave of the auditory event-related potentials evoked by 1 kHz tone bursts delivered every second. The SCD distributions revealed: (i) a sink and a source of current reversing in polarity at the inferotemporal level of each hemiscalp, compatible with neural generators in and around the supratemporal plane of the auditory cortex, as previously reported; and (ii) bilateral current sinks over frontal areas. Consistently, dynamic dipole model analysis showed that generators in and outside the auditory cortex are necessary to account for the observed current fields between 65 and 140 msec post stimulus. The frontal currents could originate from the motor cortex, the supplementary motor area and/or the cingulate gyrus. The dissociation of an exogenous, obligatory frontal component from the sensory-specific response in the auditory N1 suggests that parallel processes served by distinct neural systems are activated during acoustic stimulation. Implications for recent models of auditory processing are discussed.     

Influences of membrane properties on phase response curve and synchronization stability in a model globus pallidus neuron

The activity patterns of the globus pallidus (GPe) and subthalamic nucleus (STN) are closely associated with motor function and dysfunction in the basal ganglia. In the pathological state caused by dopamine depletion, the STN–GPe network exhibits rhythmic synchronous activity accompanied by rebound bursts in the STN. Therefore, the mechanism of activity transition is a key to understand basal ganglia functions. As synchronization in GPe neurons could induce pathological STN rebound bursts, it is important to study how synchrony is generated in the GPe. To clarify this issue, we applied the phase-reduction technique to a conductance-based GPe neuronal model in order to derive the phase response curve (PRC) and interaction function between coupled GPe neurons. Using the PRC and interaction function, we studied how the steady-state activity of the GPe network depends on intrinsic membrane properties, varying ionic conductances on the membrane. We noted that a change in persistent sodium current, fast delayed rectifier Kv3 potassium current, M-type potassium current and small conductance calcium-dependent potassium current influenced the PRC shape and the steady state. The effect of those currents on the PRC shape could be attributed to extension of the firing period and reduction of the phase response immediately after an action potential. In particular, the slow potassium current arising from the M-type potassium and the SK current was responsible for the reduction of the phase response. These results suggest that the membrane property modulation controls synchronization/asynchronization in the GPe and the pathological pattern of STN–GPe activity.     

Encoding of Time-varying Stimuli in Populations of Cultured Neurons

We wondered whether random populations of dissociated cultured cortical neurons, despite of their lack of structure and/or regional specialization, are capable of modulating their neural activity as the effect of a time-varying stimulation – a simulated ‘sensory’ afference. More specifically, we used localized low-frequency, non-periodic trains of stimuli to simulate sensory afferences, and asked how much information about the original trains of stimuli could be extracted from the neural activity recorded at the different sites. Furthermore, motivated by the results of studies performed both in vivo and in vitro on different preparations, which suggested that isolated spikes and bursts may play different roles in coding time-varying signals, we explored the amount of such ‘sensory’ information that could be associated to these different firing modes. Finally, we asked whether and how such ‘sensory’ information is transferred from the sites of stimulation (i.e., the ‘sensory’ areas), to the other regions of the neural populations. To do this we applied stimulus reconstruction techniques and information theoretic concepts that are typically used to investigate neural coding in sensory systems. Our main results are that (1) slow variations of the rate of stimulation are coded into isolated spikes and in the time of occurrence of bursts (but not in the bursts’ temporal structure); (2) increasing the rate of stimulation has the effect of increasing the proportion of isolated spikes in the average evoked response and their importance in coding for the stimuli; and, (3) the ability to recover the time course of the pattern of stimulation is strongly related to the degree of functional connectivity between stimulation and recording sites. These observations parallel similar findings in intact nervous systems regarding the complementary roles of bursts and tonic spikes in encoding sensory information. Our results also have interesting implications in the field of neuro-robotic interfaces. In fact, the ability of populations of neurons to code information is a prerequisite for obtaining hybrid systems, in which neuronal populations are used to control external devices.     

The inferior colliculus of the mustached bat has the frequency-vs-latency coordinates

In the mustached bat, the central auditory system contains FM–FM (delay-tuned) neurons which are specialized for processing target-distance information carried by echo delays. Mechanisms for creating the FM–FM neurons involve delay lines, coincidence detection and amplification. A neural basis for delay lines can be a map representing response latencies. The aim of the present study is to explore whether the central nucleus of the inferior colliculus has a latency axis incorporated into iso-best frequency slabs. Responses of single or multiple neurons were recorded from the inferior colliculus of unanesthetized mustached bats with tungsten-wire electrodes, and their response latencies were measured with tone bursts at their best frequencies and best amplitudes or 65 dB SPL. In the dorsoventral electrode penetrations across the inferior colliculus, response latency systematically shortens from ˜12 to ˜4␣ms. Tonotopic representation in the inferior colliculus is somewhat complex. Iso-best frequency slabs are tilted and/or curved, but they orient more or less ventrodorsally. Nevertheless, the latency axis is evident in each iso-best frequency slab, regardless of best frequency. The inferior colliculus has the frequency-vs-latency coordinates. Accepted: 2 October 1996     

Laminar distribution of current sources in the rabbit superior colliculus during optic nerve stimulation

The electric field of evoked potentials developing in the rabbit superior colliculus in response to single electrical stimulation of the optic nerve was investigated. Regions of localization of sources and sinks of synaptic current creating the evoked potential were discovered by the current source density analysis method. Sinks with the shortest latency appeared in the depth of str. griseum superficiale, after which activity created by two dipoles appeared: The sink of one dipole was located in the upper part of str. griseum superficiale, the sink of the other in the lower part. The sinks thus found corresponded in their temporal characteristics and location to the principal components of the combined evoked potential. On the basis of these data the order of activation of the various systems of fibers and synapses responsible for evoked potential formation can be traced.     

中国陆地生态系统碳源/汇整合分析

国家尺度陆地生态系统碳收支及其循环过程的研究对于提升地球系统科学与全球变化科学的科技创新能力、提高我国参与应对全球气候变化国际行动和维护国家利益的话语权、保障国家生态安全和改进生态系统管理都具有重要意义。近年来,我国已经在气候变化与陆地生态系统碳循环领域开展了大量的研究工作,主要包括国家清查、生态系统模型模拟、大气反演等手段。然而,由于大尺度陆地生态系统碳源/汇的估算存在很大的不确定性,目前尚未形成国家尺度的陆地生态系统碳源/汇的整合分析。通过搜集已发表的关于中国陆地生态系统及其组分碳源/汇的59篇文献,整合国家清查、生态系统模型模拟、大气反演3种研究手段,分析中国陆地生态系统碳源/汇大小以及时间尺度上的动态变化。结果表明,在1960s-2010s期间中国陆地生态系统碳汇整体呈上升趋势,平均为（0.213±0.030）Pg C/a,其中森林、草地、农田和灌木生态系统碳汇分别为（0.101±0.023）Pg C/a、（0.032±0.007）Pg C/a、（0.043±0.010）Pg C/a和（0.028±0.010）Pg C/a。森林生态系统中的植被碳汇远大于土壤碳汇,然而这种格局在草地和农田生态系统却相反,而且1960s-2010s期间中国主要植被类型的生态系统碳汇总体上随时间呈增加趋势。融合多源数据（地面观测、激光雷达、卫星遥感等）、多尺度数据（样地尺度、站点尺度、区域尺度）以及多手段数据（联网观测、森林清查、模型模拟）,有助于全面准确地评估中国陆地生态系统碳源/汇及其对气候变化的响应。     

Applications of neural networks to colour recognition

Colour specification and matching are important tasks used in a number of different industries. However, current methods can employ very complicated, elaborate pieces of laboratory equipment which are not portable, such as spectrophotometers with combinations of calibrated light sources and a large number of narrow band filters. Simpler, portable devices are typically not sophisticated enough to give a high degree of quality control due to the less sophisticated light sources and the necessarily smaller number of filters employed. Lastly, techniques such as the `match by eye' method can lead to deceptive metameric matches. This paper outlines the beginning of the development of a colour measurement system which is portable, easy to use, and more accurate than other portable devices by virtue of an artificial neural network used to analyze the data. With specialized training of the neural network, it could even be used in applications such as teeth and skin colour measurements. Received: 6 November 1996 / Accepted in revised form: 13 July 1998     

An isomorphic mapping hypothesis of the grid representation

We introduce a grid cell microcircuit hypothesis. We propose the ‘grid in the world’ (evident in grid cell discharges) is generated by a ‘grid in the cortex’. This cortical grid is formed by patches of calbindin-positive pyramidal neurons in layer 2 of medial entorhinal cortex (MEC). Our isomorphic mapping hypothesis assumes three types of isomorphism: (i) metric correspondence of neural space (the two-dimensional cortical sheet) and the external two-dimensional space within patches; (ii) isomorphism between cellular connectivity matrix and firing field; (iii) isomorphism between single cell and population activity. Each patch is a grid cell lattice arranged in a two-dimensional map of space with a neural : external scale of approximately 1 : 2000 in the dorsal part of rat MEC. The lattice behaves like an excitable medium with neighbouring grid cells exciting each other. Spatial scale is implemented as an intrinsic scaling factor for neural propagation speed. This factor varies along the dorsoventral cortical axis. A connectivity scheme of the grid system is described. Head direction input specifies the direction of activity propagation. We extend the theory to neurons between grid patches and predict a rare discharge pattern (inverted grid cells) and the relative location and proportion of grid cells and spatial band cells.     

A neural network study of precollicular saccadic averaging

Saccadic averaging is the phenomenon that two simultaneously presented retinal inputs result in a saccade with an endpoint located on an intermediate position between the two stimuli. Recordings from neurons in the deeper layers of the superior colliculus have revealed neural correlates of saccade averaging, indicating that it takes place at this level or upstream. Recently, we proposed a neural network for internal feedback in saccades. This neural network model is different from other models in that it suggests the possibility that averaging takes place in a stage upstream of the colliculus. The network consists of output units representing the neural map of the deeper layers of the superior colliculus and hidden layers imitating areas in the posterior parietal cortex. The deeper layers of the superior colliculus represent the motor error of a desired saccade, e.g. an eye movement to a visual target. In this article we show that averaging is an emergent property of the proposed network. When two retinal targets with different intensities are simultaneously presented to the network, the activity in the output layer represents a single motor error with a weighted average value. Our goal is to understand the mechanism of weighted averaging in this neural network. It appears that averaging in the model is caused by the linear dependence of the net input, received by the hidden units, on retinal error, independent of its retinal coding format. For nonnormalized retinal error inputs, also the nonlinearity between the net input and the activity of the hidden units plays a role in the averaging process. The averaging properties of the model are in agreement with physiological experiments if the hypothetical retinal error input map is normalized. The neural network predicts that if this normalization is overruled by electrical stimulation, averaging still takes place. However, in this case – as a consequence of the feedback task – the location of the resulting saccade depends on the initial eye position and the total intensity/current applied at the two locations. This could be a way to verify the neural network model. If the assumptions for the model are valid, a physiological implication of this paper is that averaging of saccades takes place upstream of the superior colliculus. Received: 22 June 1997 / Accepted in revised form: 19 February 1998     

Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity

 A computational model of hippocampal activity during spatial cognition and navigation tasks is presented. The spatial representation in our model of the rat hippocampus is built on-line during exploration via two processing streams. An allothetic vision-based representation is built by unsupervised Hebbian learning extracting spatio-temporal properties of the environment from visual input. An idiothetic representation is learned based on internal movement-related information provided by path integration. On the level of the hippocampus, allothetic and idiothetic representations are integrated to yield a stable representation of the environment by a population of localized overlapping CA3-CA1 place fields. The hippocampal spatial representation is used as a basis for goal-oriented spatial behavior. We focus on the neural pathway connecting the hippocampus to the nucleus accumbens. Place cells drive a population of locomotor action neurons in the nucleus accumbens. Reward-based learning is applied to map place cell activity into action cell activity. The ensemble action cell activity provides navigational maps to support spatial behavior. We present experimental results obtained with a mobile Khepera robot. Received: 02 July 1999 / Accepted in revised form: 20 March 2000     

Decoding of a motor command vector from distributed activity in superior colliculus

 Several alternative methods for decoding the desired motor command vector from neural networks containing distributed, place-coded information have been suggested. The two most widely discussed candidate mechanisms are vector summation (VS) and a center-of-mass (CM) computation. The latter mechanism has also been called vector averaging. The present paper compares the operation of these two methods in a model of an experimentally well-studied neural structure, the superior colliculus (SC). The SC is one structure that has been shown to be responsible for generating saccadic command vectors in the form of distributed neural activity that is topologically arranged across its surface. It has been suggested that the pattern of eye-movement errors obtained following the placement of a collicular lesion can distinguish between these two mechanisms. As a result of this suggestion, the pattern of saccadic errors produced by lesions in the SC have been widely cited to support the CM hypothesis. In the present paper the placement of a discrete lesion is simulated in a recurrent (dynamic) neural network model of the SC. These dynamic connections in the model SC network produce a systematic shift of the locus of distributed activity away from the site of the lesion. The spatiotemporal shift in the location of SC activity then produces a pattern of saccadic errors that appear to support the CM hypothesis, even though ensemble activity in our model colliculus is decoded by VS. This result demonstrates that, when ensemble activity on the SC motor map is dynamically modulated over space and time by intrinsic collicular circuitry, an explicit CM computation is not needed to reproduce the pattern of physiological results that follow focal SC lesions. Received: 19 December 2000 / Accepted in revised form: 27 September 2001     

The Carbon Economy of Clonal Plants of Trifolium repens L.

Fluxes of carbon between sources and sinks were quantified forclonal plants of Trifolium repens L. (cv. Blanca) in two glasshouseexperiments. Carbon sources were (a) leaves on the parent (=main)stolon apex, or (b) leaves on either young or old branches,and the major sinks of interest were the parent stolon apex,branches, and the adventitious root arising at the same parentstolon node as a young source branch. Defoliation treatmentswere applied to the parent stolon and/or branches (excludingsource branches). Carbon moved freely from the parent stolon to branches and vice-versa;these bidirectional exchanges of C provided important supplementarysources of carbohydrate for the sinks and buffered them againstthe effects of defoliation. Young branches exported more C tothe parent plant (mean=6.3µmol d^–1) than they importedfrom leaves on the parent stolon (5·2µmol d^–1)which, in turn, exceeded the amount fixed by leaves on the branchand utilized within the branch itself (2·7µmold^–1). In contrast, the C economy of old branches was largelyself-contained with, on average, 25·4µmol d^–1exported to the parent plant, 1·8µmol d^–1imported from the parent, and 63·0µmol d^–1fixed and utilized by the branch itself. Thus the growth ofyoung branches was immediately reduced by removal of parentstolon leaves, but old branches were unaffected. An estimated 42% of the C utilized by the main stolon apex originatedfrom branches, while by far the largest proportion (84%) ofthe C used for growth of young nodal roots originated from theassociated branch and not from leaves on the parent stolon towhich the root was directly attached. Key words: Trifolium repens, clonal growth, carbon economy, physiological integration, defoliation     

A simple computer model of excitable synaptically connected neurons

 The space-lumped two-variable neuron model is studied. Extension of the neural model by adding a simple synaptic current allows the demonstration of neural interactions. The production of synchronous burst activity in this simple two-neuron excitatory loop is modeled, including the influence of random background excitatory input. The ability of the neuron model to integrate inputs spatially and temporally is shown. Two refractory periods after stimuli were identified and their role in burst cessation is demonstrated. Our findings show that simple neural units without long-lasting membrane processes are capable of generating long lasting patterns of activity. The results of simulation of simple background activity suggest that an increase in background activity tends to cause decreased activity of the network. This phenomenon, as well as the existence of two refractory periods, allows for burst cessation without inhibition in this simple model. Received: 6 December 1996/Accepted in revised form: 7 April 1997     

Are Swedish forest soils sinks or sources for CO<Subscript>2</Subscript>—model analyses based on forest inventory data

Forests soils should be neither sinks nor sources of carbon in a long-term perspective. From a Swedish perspective the time since the last glaciation has probably not been long enough to reach a steady state, although changes are currently very slow. In a shorter perspective, climatic and management changes over the past 100 years have probably created imbalances between litter input to soils and organic carbon mineralisation. Using extant data on forest inventories, we applied models to analyse possible changes in the carbon stocks of Swedish forest soils. The models use tree stocks to provide estimates of tree litter production, which are fed to models of litter decomposition and from which carbon stocks are calculated. National soil carbon stocks were estimated to have increased by 3 Tg yr⁻¹ or 12–13 g m⁻² yr⁻¹ in the period 1926–2000 and this increase will continue because soil stocks are far from equilibrium with current litter inputs. The figure obtained is likely to be an underestimation because wet sites store more carbon than predicted here and the inhibitory effect of nitrogen deposition on soil carbon mineralisation was neglected. Knowledge about site history prior to the calculation period determines the accuracy of current soil carbon stocks estimates, although changes can be more accurately estimated.     

Effects of Land-Use Change on Carbon Stocks in Switzerland

We assessed how consequences of future land-use change may affect size and spatial shifts of C stocks under three potential trends in policy—(a) business-as-usual: continuation of land-use trends observed during the past 15 years; (b) extensification: full extensification of open-land; and (c) liberalization: full reforestation potential. The build-up times for the three scenarios are estimated at 30, 80 and 100 years, respectively. Potential C-stock change rates are derived from the literature. Whereas the business-as-usual scenario would cause marginal changes of 0.5%, liberalization would provoke a 13% increase in C stocks (+62 MtC). Gains of 24% would be expected for forests (+95 MtC), whereas open-land C stock would decrease 27% (−33 MtC). Extensification would lead to a C stock decrease of 3% (−12 MtC). Whereas forest C is expected to increase 12% (+36.5 MtC) at high elevations, stocks of open-land C would decline 38.5% (−48.5 MtC). Most affected are unfavorable grasslands, which increase in area (+59%) but contribute only 14.5% to the C stocks. C sinks would amount to 0.6 MtC y⁻¹ assuming a build-up time of 100 years for the liberalization scenario. C stocks on the current forest area are increasing by 1 MtC y⁻¹. The maximal total C sink of 1.6 MtC might thus suffice to compensate for agricultural greenhouse gases (2004: 1.4 Mt CO₂–C equivalents), but corresponds only to 11–13% of the anthropogenic greenhouse gas emission in Switzerland. Thus, even the largest of the expected terrestrial C stocks under liberalization will be small in comparison with current emissions of anthropogenic greenhouse gases.     

Are Swedish forest soils sinks or sources for CO<Subscript>2</Subscript>—model analyses based on forest inventory data

Forests soils should be neither sinks nor sources of carbon in a long-term perspective. From a Swedish perspective the time since the last glaciation has probably not been long enough to reach a steady state, although changes are currently very slow. In a shorter perspective, climatic and management changes over the past 100 years have probably created imbalances between litter input to soils and organic carbon mineralisation. Using extant data on forest inventories, we applied models to analyse possible changes in the carbon stocks of Swedish forest soils. The models use tree stocks to provide estimates of tree litter production, which are fed to models of litter decomposition and from which carbon stocks are calculated. National soil carbon stocks were estimated to have increased by 3 Tg yr⁻¹ or 12–13 g m⁻² yr⁻¹ in the period 1926–2000 and this increase will continue because soil stocks are far from equilibrium with current litter inputs. The figure obtained is likely to be an underestimation because wet sites store more carbon than predicted here and the inhibitory effect of nitrogen deposition on soil carbon mineralisation was neglected. Knowledge about site history prior to the calculation period determines the accuracy of current soil carbon stocks estimates, although changes can be more accurately estimated. This article has previously been published in issue 82/3, under DOI .     

Neural mechanisms potentially contributing to the intersegmental phase lag in lamprey

Most previous models of the spinal central pattern generator (CPG) underlying locomotion in the lamprey have relied on reciprocal inhibition between the left and right side for oscillations to be produced. Here, we have explored the consequences of using self-oscillatory hemisegments. Within a single hemisegment, the oscillations are produced by a network of recurrently coupled excitatory neurons (E neurons) that by themselves are not oscillatory but when coupled together through N-methyl-d-aspartate (NMDA) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionicacid (AMPA)/kainate transmission can produce oscillations. The bursting mechanism relies on intracellular accumulation of calcium that activates Ca²⁺-dependent K⁺. The intracellular calcium is modeled by two different intracellular calcium pools, one of which represents the calcium entry following the action potential, Ca_AP pool, and the other represents the calcium inflow through the NMDA channels, Ca_NMDA pool. The Ca²⁺-dependent K⁺ activated by these two calcium pools are referred to as K_CaAP and K_CaNMDA, respectively, and their relative conductances are modulated and increase with the background activation of the network. When changing the background stimulation, the bursting activity in this network can be made to cover a frequency range of 0.5–5.5 Hz with reasonable burst proportions if the adaptation is modulated with the activity. When a chain of such hemisegments are coupled together, a phase lag along the chain can be produced. The local oscillations as well as the phase lag is dependent on the axonal conduction delay as well as the types of excitatory coupling that are assumed, i.e. AMPA/kainate and/or NMDA. When the caudal excitatory projections are extended further than the rostral ones, and assumed to be of approximately equal strength, this kind of network is capable of reproducing several experimental observations such as those occurring during strychnine blockade of the left-right reciprocal inhibition. Addition of reciprocally coupled inhibitory neurons in such a network gives rise to antiphasic activity between the left and right side, but not necessarily to any change of the frequency if the burst proportion of the hemisegmental bursts is well below 50%. Prolongation of the C neuron projection in the rostrocaudal direction restricts the phase lag produced by only the excitatory hemisegmental network by locking together the interburst intervals at different levels of the spinal cord. Received: 29 September 1998 Accepted in Revised Form: 26 March 1999     

Synchronization regulation in a model of coupled neural masses

A model of coupled neural masses can generate seizure-like events and dynamics similar to those observed during interictal to ictal transitions and thus can be used for theoretical study of the control of epileptic seizures. In an effort to understand the mechanisms underlying epileptic seizures and how to avoid them, we added a control input to this model. Epileptic seizures are always accompanied by hypersynchronous firing of neurons, so research on synchronization among cortical areas is significant for seizure control. In this study, principal component analysis (PCA) was used to identify synchronization clusters composed of several neural masses. A method for calculating the synchronization cluster strength and participation rate is presented. The synchronization cluster strength can be used to identify synchronization clusters and the participation rate can be employed to identify neural masses that participate in the clusters. Each synchronization cluster is controlled as a whole using a proportional-integral-derivative (PID) controller. We illustrate these points using coupled neural mass models of synchronization to show their responses to increased (between node) coupling with and without control. Experiment results indicated that PID control can effectively regulate synchronization between neural masses and has the potential for seizure prevention.     

Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.