Stimulus-Specific Adaptation at the Synapse Level In Vitro

Stimulus-specific adaptation (SSA) is observed in many brain regions in humans and animals. SSA of cortical neurons has been proposed to accumulate through relays in ascending pathways. Here, we examined SSA at the synapse level using whole-cell patch-clamp recordings of primary cultured cortical neurons of the rat. First, we found that cultured neurons had high firing capability with 100-Hz current injection. However, neuron firing started to adapt to repeated electrically activated synaptic inputs at 10 Hz. Next, to activate different dendritic inputs, electrical stimulations were spatially separated. Cultured neurons showed similar SSA properties in the oddball stimulation paradigm compared to those reported in vivo. Single neurons responded preferentially to a deviant stimulus over repeated, standard stimuli considering both synapse-driven spikes and excitatory postsynaptic currents (EPSCs). Compared with two closely placed stimulating electrodes that activated highly overlapping dendritic fields, two separately placed electrodes that activated less overlapping dendritic fields elicited greater SSA. Finally, we used glutamate puffing to directly activate postsynaptic glutamate receptors. Neurons showed SSA to two separately placed puffs repeated at 10 Hz. Compared with EPSCs, GABAa receptor-mediated inhibitory postsynaptic currents showed weaker SSA. Heterogeneity of the synaptic inputs was critical for producing SSA, with glutamate receptor desensitization participating in the process. Our findings suggest that postsynaptic fatigue contributes largely to SSA at low frequencies.     

Dynamic modification of dendritic cable properties and synaptic transmission by voltage-gated potassium channels

Computer simulations of a dendrite possessing voltage-sensitive potassium conductances were used to determine the effects of these conductances on synaptic transmission and on the propagation of synaptic signals within the dendritic tree. Potassium conductances had two principal effects on voltage transients generated by current injections or synaptic conductances. Locally (near the source of the transient), voltage-gated potassium channels produced a potassium shunt current that reduced the amplitude of voltage transients generated by depolarizing currents. This shunt current increased as the amplitude of the depolarizing transient increased and so acted to prevent large synaptic transients from reaching levels that would saturate due to a reduction in driving force. In the presence of rapidly activating potassium currents, excitatory synapses produced larger synaptic currents that were more linearly related to synaptic conductance, but these produced smaller voltage transients. The maximum amplitudes of the voltage transients were limited by the voltage sensitivity of the K⁺ conductance and the rate at which it could activate. Sufficiently rapid synaptic currents could outrun the K⁺ conductance and thus achieve high local peak amplitudes. These effects of K⁺ conductances were unrelated to whether they were located on dendrites or not, being related only to their proximity to the source of synaptic current. The second class of effects of K⁺ conductances depended on their alteration of the electrotonic structure of the postsynaptic cell and so were observed only when they were located on postsynaptic dendrites. Voltage-gated K⁺ conductances produced voltage-dependent electrotonic expansion of depolarized dendrites, which had the effect of isolating synaptic inputs on depolarized dendrites from events on the rest of the neuron. Thus, synapses on the same dendrite interacted destructively to a degree much greater than that expected from the classical driving force nonlinearity. Synapses located proximally to a depolarized dendritic region were less effected than those located distally, and the range of the nonlinear interaction between synapses was dependent on the kinetics of activation and deactivation of the conductance. When present in conjunction with rapidly activating dendritic sodium conductance, the potassium conductance sharpened the requirement for spatial and temporal coincidence to produce synaptic boosting by inward currents, and suppressed out-of-synchrony synaptic inputs.     

Integration of subthreshold and suprathreshold excitatory barrages along the somatodendritic axis of pyramidal neurons

Neurons integrate inputs arriving in different cellular compartments to produce action potentials that are transmitted to other neurons. Because of the voltage- and time-dependent conductances in the dendrites and soma, summation of synaptic inputs is complex. To examine summation of membrane potentials and firing rates, we performed whole-cell recordings from layer 5 cortical pyramidal neurons in acute slices of the rat's somatosensory cortex. We delivered subthreshold and suprathreshold stimuli at the soma and several sites on the apical dendrite, and injected inputs that mimic synaptic barrages at individual or distributed sites. We found that summation of subthreshold potentials differed from that of firing rates. Subthreshold summation was linear when barrages were small but became supralinear as barrages increased. When neurons were discharging repetitively the rules were more diverse. At the soma and proximal apical dendrite summation of the evoked firing rates was predominantly sublinear whereas in the distal dendrite summation ranged from supralinear to sublinear. In addition, the integration of inputs delivered at a single location differed from that of distributed inputs only for suprathreshold responses. These results indicate that convergent inputs onto the apical dendrite and soma do not simply summate linearly, as suggested previously, and that distinct presynaptic afferents that target specific sites on the dendritic tree may perform unique sets of computations.     

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.     

Computational simulation of the input-output relationship in hippocampal pyramidal cells

The precise mapping of how complex patterns of synaptic inputs are integrated into specific patterns of spiking output is an essential step in the characterization of the cellular basis of network dynamics and function. Relative to other principal neurons of the hippocampus, the electrophysiology of CA1 pyramidal cells has been extensively investigated. Yet, the precise input-output relationship is to date unknown even for this neuronal class. CA1 pyramidal neurons receive laminated excitatory inputs from three distinct pathways: recurrent CA1 collaterals on basal dendrites, CA3 Schaffer collaterals, mostly on oblique and proximal apical dendrites, and entorhinal perforant pathway on distal apical dendrites. We implemented detailed computer simulations of pyramidal cell electrophysiology based on three-dimensional anatomical reconstructions and compartmental models of available biophysical properties from the experimental literature. To investigate the effect of synaptic input on axosomatic firing, we stochastically distributed a realistic number of excitatory synapses in each of the three dendritic layers. We then recorded the spiking response to different stimulation patterns. For all dendritic layers, synchronous stimuli resulted in trains of spiking output and a linear relationship between input and output firing frequencies. In contrast, asynchronous stimuli evoked non-bursting spike patterns and the corresponding firing frequency input-output function was logarithmic. The regular/irregular nature of the input synaptic intervals was only reflected in the regularity of output inter-burst intervals in response to synchronous stimulation, and never affected firing frequency. Synaptic stimulations in the basal and proximal apical trees across individual neuronal morphologies yielded remarkably similar input-output relationships. Results were also robust with respect to the detailed distributions of dendritic and synaptic conductances within a plausible range constrained by experimental evidence. In contrast, the input-output relationship in response to distal apical stimuli showed dramatic differences from the other dendritic locations as well as among neurons, and was more sensible to the exact channel densities. Action Editor: Alain Destexhe     

Conditions of dominant effectiveness of distal sites of active uniform dendrites with distributed tonic inputs

This simulation study aimed at assessing linkage between the membrane properties and the effectiveness of somatopetal current transfer from activated tonic excitatory inputs homogeneously distributed along uniform dendrites. It was shown that in the dendrites having anN-shaped steady current-voltage membrane characteristic due to the negative slope within a certain range of potentials, distal sites can be more effective than proximal sites in somatopetal current transfer from tonically activated excitatory synaptic inputs. Inhomogeneous dendritic depolarization produced by these inputs should be found everywhere within a range of the negative slope. In simulated dendrites receiving, as in rat abducens motoneurons, voltage-sensitive synaptic inputs of anN-methyl-D-aspartate (NMDA) type, such spatial effects occurred at low depolarization produced by subcritical excitation. At supercritical excitation, depolarization increased and left the range of the negative slope, and proximal sites became much more effective than distal ones. It is suggested that persistent inward currents (including other than of NMDA nature) can provide similar effects.     

Differences in biophysical properties of nucleus accumbens medium spiny neurons emerging from inactivation of inward rectifying potassium currents

Inward rectifying potassium (K_IR) currents in medium spiny (MS) neurons of nucleus accumbens inactivate significantly in ~40% of the neurons but not in the rest, which may lead to differences in input processing by these two groups. Using a 189-compartment computational model of the MS neuron, we investigate the influence of this property using injected current as well as spatiotemporally distributed synaptic inputs. Our study demonstrates that K_IR current inactivation facilitates depolarization, firing frequency and firing onset in these neurons. These effects may be attributed to the higher input resistance of the cell as well as a more depolarized resting/down-state potential induced by the inactivation of this current. In view of the reports that dendritic intracellular calcium levels depend closely on burst strength and spike onset time, our findings suggest that inactivation of K_IR currents may offer a means of modulating both excitability and synaptic plasticity in MS neurons.     

Plasticity of pre- and postsynaptic GABAB receptor function in the paraventricular nucleus in spontaneously hypertensive rats

GABA(B) receptor function is upregulated in the paraventricular nucleus (PVN) of the hypothalamus in spontaneously hypertensive rats (SHR), but it is unclear whether this upregulation occurs pre- or postsynaptically. We therefore determined pre- and postsynaptic GABA(B) receptor function in retrogradely labeled spinally projecting PVN neurons using whole cell patch-clamp recording in brain slices in SHR and Wistar-Kyoto (WKY) rats. Bath application of the GABA(B) receptor agonist baclofen significantly decreased the spontaneous firing activity of labeled PVN neurons in both SHR and WKY rats. However, the magnitude of reduction in the firing rate was significantly greater in SHR than in WKY rats. Furthermore, baclofen produced larger membrane hyperpolarization and outward currents in labeled PVN neurons in SHR than in WKY rats. The baclofen-induced current was abolished by either including G protein inhibitor GDPbetaS in the pipette solution or bath application of the GABA(B) receptor antagonist in both SHR and WKY rats. Blocking N-methyl-d-aspartic acid receptors had no significant effect on baclofen-elicited outward currents in SHR. In addition, baclofen caused significantly greater inhibition of glutamatergic excitatory postsynaptic currents (EPSCs) in labeled PVN neurons in brain slices from SHR than WKY rats. By contrast, baclofen produced significantly less inhibition of GABAergic inhibitory postsynaptic currents (IPSCs) in labeled PVN neurons in SHR than in WKY rats. Although microinjection of the GABA(B) antagonist into the PVN increases sympathetic vasomotor tone in SHR, the GABA(B) antagonist did not affect EPSCs and IPSCs of the PVN neurons in vitro. These findings suggest that postsynaptic GABA(B) receptor function is upregulated in PVN presympathetic neurons in SHR. Whereas presynaptic GABA(B) receptor control of glutamatergic synaptic inputs is enhanced, presynaptic GABA(B) receptor control of GABAergic inputs in the PVN is attenuated in SHR. Changes in both pre- and postsynaptic GABA(B) receptors in the PVN may contribute to the control of sympathetic outflow in hypertension.     

Activation of subfornical organ neurons in rats through pre- and postsynaptic alpha-adrenoceptors

The effects of noradrenaline (NA) and its analogs on subfornical organ (SFO) neurons in rat slice preparations were investigated by using whole cell patch-clamp recording. In the current-clamp mode, the application of NA at 10-100 microM produced membrane depolarization (63%, 17 responsive neurons/27 neurons tested) and hyperpolarization (22%, 6/27 neurons). In the voltage-clamp mode, NA application at 1-100 microM produced inward currents (69%, 42/61 neurons) and outward currents (23%, 14/61 neurons). These currents remained in the presence of TTX or both glutamate and GABA receptor antagonists. In most of the neurons (25/31 neurons) showing inward currents in the presence of NA, the membrane conductance was not changed by voltage ramps or hyperpolarizing pulse stimulation. Similar responses were obtained by the application of the alpha1-agonist phenylephrine. The phenylephrine-induced inward currents were inhibited by the alpha1-antagonist prazosin. The alpha2-agonist clonidine decreased the frequency of spontaneous GABAergic inhibitory postsynaptic currents (4/10 neurons). In addition, RT-PCR assay and immunohistochemical staining showed the existence of alpha1-adrenoceptors in the SFO. The results suggest that SFO neurons in rats are activated postsynaptically through alpha1-adrenoceptors and that the activation is enhanced by suppressing GABAergic inhibitory synaptic inputs through presynaptic alpha2-adrenoceptors.     

Computation of the electroencephalogram (EEG) from network models of point neurons

The electroencephalogram (EEG) is a major tool for non-invasively studying brain function and dysfunction. Comparing experimentally recorded EEGs with neural network models is important to better interpret EEGs in terms of neural mechanisms. Most current neural network models use networks of simple point neurons. They capture important properties of cortical dynamics, and are numerically or analytically tractable. However, point neurons cannot generate an EEG, as EEG generation requires spatially separated transmembrane currents. Here, we explored how to compute an accurate approximation of a rodent’s EEG with quantities defined in point-neuron network models. We constructed different approximations (or proxies) of the EEG signal that can be computed from networks of leaky integrate-and-fire (LIF) point neurons, such as firing rates, membrane potentials, and combinations of synaptic currents. We then evaluated how well each proxy reconstructed a ground-truth EEG obtained when the synaptic currents of the LIF model network were fed into a three-dimensional network model of multicompartmental neurons with realistic morphologies. Proxies based on linear combinations of AMPA and GABA currents performed better than proxies based on firing rates or membrane potentials. A new class of proxies, based on an optimized linear combination of time-shifted AMPA and GABA currents, provided the most accurate estimate of the EEG over a wide range of network states. The new linear proxies explained 85–95% of the variance of the ground-truth EEG for a wide range of network configurations including different cell morphologies, distributions of presynaptic inputs, positions of the recording electrode, and spatial extensions of the network. Non-linear EEG proxies using a convolutional neural network (CNN) on synaptic currents increased proxy performance by a further 2–8%. Our proxies can be used to easily calculate a biologically realistic EEG signal directly from point-neuron simulations thus facilitating a quantitative comparison between computational models and experimental EEG recordings.     

Conventional measures of intrinsic excitability are poor estimators of neuronal activity under realistic synaptic inputs

Activity-dependent regulation of intrinsic excitability has been shown to greatly contribute to the overall plasticity of neuronal circuits. Such neuroadaptations are commonly investigated in patch clamp experiments using current step stimulation and the resulting input-output functions are analyzed to quantify alterations in intrinsic excitability. However, it is rarely addressed, how such changes translate to the function of neurons when they operate under natural synaptic inputs. Still, it is reasonable to expect that a strong correlation and near proportional relationship exist between static firing responses and those evoked by synaptic drive. We challenge this view by performing a high-yield electrophysiological analysis of cultured mouse hippocampal neurons using both standard protocols and simulated synaptic inputs via dynamic clamp. We find that under these conditions the neurons exhibit vastly different firing responses with surprisingly weak correlation between static and dynamic firing intensities. These contrasting responses are regulated by two intrinsic K-currents mediated by Kv1 and K_ir channels, respectively. Pharmacological manipulation of the K-currents produces differential regulation of the firing output of neurons. Static firing responses are greatly increased in stuttering type neurons under blocking their Kv1 channels, while the synaptic responses of the same neurons are less affected. Pharmacological blocking of K_ir-channels in delayed firing type neurons, on the other hand, exhibit the opposite effects. Our subsequent computational model simulations confirm the findings in the electrophysiological experiments and also show that adaptive changes in the kinetic properties of such currents can even produce paradoxical regulation of the firing output.     

Synaptic integration in motoneurons with hyper-excitable dendrites

Motoneurons have extensive dendritic trees that receive the numerous inputs required to produce movement. These dendrites are highly active, containing voltage-sensitive channels that generate persistent inward currents (PICs) that can enhance synaptic input 5-fold or more. However, this enhancement is proportional to the level of activity of monoaminergic inputs from the brainstem that release serotonin and noradrenalin. The higher this activity, the larger the dendritic PIC and the higher the firing rate evoked by a given amount of excitatory synaptic input. This brainstem control of motoneuron input-output gain translates directly into control of system gain of a motor pool and its muscle. Because large dendritic PICs are probably necessary for motoneurons to have sufficient gain to generate large forces, it is possible that descending monoaminergic inputs scale in proportion to voluntary force. Inhibition from sensory inputs has a strong suppressive effect on dendritic PICs: the stronger the inhibition, the smaller the PIC. Thus, local inhibitory inputs within the cord may oppose the descending monoaminergic control of PICs. Most motor behaviors evoke a mixture of excitation and inhibition (e.g., the reciprocal inhibition between antagonists). Therefore, normal joint movements may involve constant adjustment of PIC amplitude.     

Structure of peripheral synapses: autonomic ganglia

Final motor neurons in sympathetic and parasympathetic ganglia receive synaptic inputs from preganglionic neurons. Quantitative ultrastructural analyses have shown that the spatial distribution of these synapses is mostly sparse and random. Typically, only about 1%-2% of the neuronal surface is covered with synapses, with the rest of the neuronal surface being closely enclosed by Schwann cell processes. The number of synaptic inputs is correlated with the dendritic complexity of the target neuron, and the total number of synaptic contacts is related to the surface area of the post-synaptic neuron. Overall, most neurons receive fewer than 150 synaptic contacts, with individual preganglionic inputs providing between 10 and 50 synaptic contacts. This variation is probably one determinant of synaptic strength in autonomic ganglia. Many neurons in prevertebral sympathetic ganglia receive additional convergent synaptic inputs from intestinofugal neurons located in the enteric plexuses. The neurons support these additional inputs via larger dendritic arborisations together with a higher overall synaptic density. There is considerable neurochemical heterogeneity in presynaptic boutons. Some synapses apparently lack most of the proteins normally required for fast transmitter release and probably do not take part in conventional ganglionic transmission. Furthermore, most preganglionic boutons in the ganglionic neuropil do not form direct synaptic contacts with any neurons. Nevertheless, these boutons may well contribute to slow transmission processes that need not require conventional synaptic structures.     

Identifying and Tracking Simulated Synaptic Inputs from Neuronal Firing: Insights from In Vitro Experiments

Accurately describing synaptic interactions between neurons and how interactions change over time are key challenges for systems neuroscience. Although intracellular electrophysiology is a powerful tool for studying synaptic integration and plasticity, it is limited by the small number of neurons that can be recorded simultaneously in vitro and by the technical difficulty of intracellular recording in vivo. One way around these difficulties may be to use large-scale extracellular recording of spike trains and apply statistical methods to model and infer functional connections between neurons. These techniques have the potential to reveal large-scale connectivity structure based on the spike timing alone. However, the interpretation of functional connectivity is often approximate, since only a small fraction of presynaptic inputs are typically observed. Here we use in vitro current injection in layer 2/3 pyramidal neurons to validate methods for inferring functional connectivity in a setting where input to the neuron is controlled. In experiments with partially-defined input, we inject a single simulated input with known amplitude on a background of fluctuating noise. In a fully-defined input paradigm, we then control the synaptic weights and timing of many simulated presynaptic neurons. By analyzing the firing of neurons in response to these artificial inputs, we ask 1) How does functional connectivity inferred from spikes relate to simulated synaptic input? and 2) What are the limitations of connectivity inference? We find that individual current-based synaptic inputs are detectable over a broad range of amplitudes and conditions. Detectability depends on input amplitude and output firing rate, and excitatory inputs are detected more readily than inhibitory. Moreover, as we model increasing numbers of presynaptic inputs, we are able to estimate connection strengths more accurately and detect the presence of connections more quickly. These results illustrate the possibilities and outline the limits of inferring synaptic input from spikes.     

Muscarinic Receptor Modulation of the Cerebellar Interpositus Nucleus In Vitro

How the cerebellum carries out its functions is not clear, even for its established roles in motor control. In particular, little is known about how the cerebellar nuclei (CN) integrate their synaptic and neuromodulatory inputs to generate cerebellar output. CN neurons receive inhibitory inputs from Purkinje cells, excitatory inputs from mossy fibre and climbing fibre collaterals, as well as a variety of neuromodulatory inputs, including cholinergic inputs. In this study we tested how activation of acetylcholine receptors modulated firing rate, intrinsic properties and synaptic transmission in the CN. Using in vitro whole-cell patch clamp recordings from neurons in the interpositus nucleus, the acetylcholine receptor agonist carbachol was shown to induce a short-term increase in firing rate, increase holding current and decrease input resistance of interpositus CN neurons. Carbachol also induced long-term depression of evoked inhibitory postsynaptic currents and a short-term depression of evoked excitatory postsynaptic currents. All effects were shown to be dependent upon muscarinic acetylcholine receptor activation. Overall, the present study has identified muscarinic receptor activation as a modulator of CN activity.

     

An efficient coding hypothesis links sparsity and selectivity of neural responses

To what extent are sensory responses in the brain compatible with first-order principles? The efficient coding hypothesis projects that neurons use as few spikes as possible to faithfully represent natural stimuli. However, many sparsely firing neurons in higher brain areas seem to violate this hypothesis in that they respond more to familiar stimuli than to nonfamiliar stimuli. We reconcile this discrepancy by showing that efficient sensory responses give rise to stimulus selectivity that depends on the stimulus-independent firing threshold and the balance between excitatory and inhibitory inputs. We construct a cost function that enforces minimal firing rates in model neurons by linearly punishing suprathreshold synaptic currents. By contrast, subthreshold currents are punished quadratically, which allows us to optimally reconstruct sensory inputs from elicited responses. We train synaptic currents on many renditions of a particular bird''s own song (BOS) and few renditions of conspecific birds'' songs (CONs). During training, model neurons develop a response selectivity with complex dependence on the firing threshold. At low thresholds, they fire densely and prefer CON and the reverse BOS (REV) over BOS. However, at high thresholds or when hyperpolarized, they fire sparsely and prefer BOS over REV and over CON. Based on this selectivity reversal, our model suggests that preference for a highly familiar stimulus corresponds to a high-threshold or strong-inhibition regime of an efficient coding strategy. Our findings apply to songbird mirror neurons, and in general, they suggest that the brain may be endowed with simple mechanisms to rapidly change selectivity of neural responses to focus sensory processing on either familiar or nonfamiliar stimuli. In summary, we find support for the efficient coding hypothesis and provide new insights into the interplay between the sparsity and selectivity of neural responses.     

Solutions for transients in arbitrarily branching cables: III. Voltage clamp problems.

Branched cable voltage recording and voltage clamp analytical solutions derived in two previous papers are used to explore practical issues concerning voltage clamp. Single exponentials can be fitted reasonably well to the decay phase of clamped synaptic currents, although they contain many underlying components. The effective time constant depends on the fit interval. The smoothing effects on synaptic clamp currents of dendritic cables and series resistance are explored with a single cylinder + soma model, for inputs with different time courses. "Soma" and "cable" charging currents cannot be separated easily when the soma is much smaller than the dendrites. Subtractive soma capacitance compensation and series resistance compensation are discussed. In a hippocampal CA1 pyramidal neurone model, voltage control at most dendritic sites is extremely poor. Parameter dependencies are illustrated. The effects of series resistance compound those of dendritic cables and depend on the "effective capacitance" of the cell. Plausible combinations of parameters can cause order-of-magnitude distortions to clamp current waveform measures of simulated Schaeffer collateral inputs. These voltage clamp problems are unlikely to be solved by the use of switch clamp methods.     

Synaptic integration in dendritic trees

Most neurons have elaborate dendritic trees that receive tens of thousands of synaptic inputs. Because postsynaptic responses to individual synaptic events are usually small and transient, the integration of many synaptic responses is needed to depolarize most neurons to action potential threshold. Over the past decade, advances in electrical and optical recording techniques have led to new insights into how synaptic responses propagate and interact within dendritic trees. In addition to their passive electrical and morphological properties, dendrites express active conductances that shape individual synaptic responses and influence synaptic integration locally within dendrites. Dendritic voltage-gated Na(+) and Ca(2+) channels support action potential backpropagation into the dendritic tree and local initiation of dendritic spikes, whereas K(+) conductances act to dampen dendritic excitability. While all dendrites investigated to date express active conductances, different neuronal types show specific patterns of dendritic channel expression leading to cell-specific differences in the way synaptic responses are integrated within dendritic trees. This review explores the way active and passive dendritic properties shape synaptic responses in the dendrites of central neurons, and emphasizes their role in synaptic integration.