Subthreshold Oscillations Research Articles

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits.

Bundles of relatively long apical dendrites dominate the neurons that make up the thickness of the cerebral cortex. It is proposed that a major function of the apical dendrite is to produce sustained oscillations at a specific frequency that can serve as a common timing unit for the processing of information in circuits connected to that apical dendrite. Many layer 5 and 6 pyramidal neurons are connected to thalamic neurons in loop circuits. A model of the apical dendrites of these pyramidal neurons has been used to simulate the electric activity of the apical dendrite. The results of that simulation demonstrated that subthreshold electric pulses in these apical dendrites can be tuned to specific frequencies and also can be fine-tuned to narrow bandwidths of less than one Hertz (1 Hz). Synchronous pulse outputs from the circuit loops containing apical dendrites can tune subthreshold membrane oscillations of neurons they contact. When the pulse outputs are finely tuned, they function as a local “clock,” which enables the contacted neurons to synchronously communicate with each other. Thus, a shared tuning frequency can select neurons for membership in a circuit. Unlike layer 6 apical dendrites, layer 5 apical dendrites can produce burst firing in many of their neurons, which increases the amplitude of signals in the neurons they contact. This difference in amplitude of signals serves as basis of selecting a sub-circuit for specialized processing (e.g., sustained attention) within the typically larger layer 6-based circuit. After examining the sustaining of oscillations in loop circuits and the processing of spikes in network circuits, we propose that cortical functioning can be globally viewed as two systems: a loop system and a network system. The loop system oscillations influence the network system’s timing and amplitude of pulse signals, both of which can select circuits that are momentarily dominant in cortical activity.

Mixed-mode oscillations in pyramidal neurons under antiepileptic drug conditions.

Subthreshold oscillations in combination with large-amplitude oscillations generate mixed-mode oscillations (MMOs), which mediate various spatial and temporal cognition and memory processes and behavioral motor tasks. Although many studies have shown that canard theory is a reliable method to investigate the properties underlying the MMOs phenomena, the relationship between the results obtained by applying canard theory and conductance-based models of neurons and their electrophysiological mechanisms are still not well understood. The goal of this study was to apply canard theory to the conductance-based model of pyramidal neurons in layer V of the Entorhinal Cortex to investigate the properties of MMOs under antiepileptic drug conditions (i.e., when persistent sodium current is inhibited). We investigated not only the mathematical properties of MMOs in these neurons, but also the electrophysiological mechanisms that shape spike clustering. Our results show that pyramidal neurons can display two types of MMOs and the magnitude of the slow potassium current determines whether MMOs of type I or type II would emerge. Our results also indicate that slow potassium currents with large time constant have significant impact on generating the MMOs, as opposed to fast inward currents. Our results provide complete characterization of the subthreshold activities in MMOs in pyramidal neurons and provide explanation to experimental studies that showed MMOs of type I or type II in pyramidal neurons under antiepileptic drug conditions.

Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents.

Neuronal membrane potential resonance (MPR) is associated with subthreshold and network oscillations. A number of voltage-gated ionic currents can contribute to the generation or amplification of MPR, but how the interaction of these currents with linear currents contributes to MPR is not well understood. We explored this in the pacemaker PD neurons of the crab pyloric network. The PD neuron MPR is sensitive to blockers of H- (IH) and calcium-currents (ICa). We used the impedance profile of the biological PD neuron, measured in voltage clamp, to constrain parameter values of a conductance-based model using a genetic algorithm and obtained many optimal parameter combinations. Unlike most cases of MPR, in these optimal models, the values of resonant- (fres) and phasonant- (fϕ = 0) frequencies were almost identical. Taking advantage of this fact, we linked the peak phase of ionic currents to their amplitude, in order to provide a mechanistic explanation the dependence of MPR on the ICa gating variable time constants. Additionally, we found that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ). Measurements of the PD neuron MPR at more hyperpolarized voltages resulted in a reduction of fres but no change in QZ. Constraining the optimal models using these data unmasked a positive correlation between the maximal conductances of IH and ICa. Thus, although IH is not necessary for MPR in this neuron type, it contributes indirectly by constraining the parameters of ICa.

A Sub-cm3 Energy-Harvesting Stacked Wireless Sensor Node Featuring a Near-Threshold Voltage IA-32 Microcontroller in 14-nm Tri-Gate CMOS for Always-ON Always-Sensing Applications

An energy-harvesting wireless sensor node (WSN) integrates a 14-nm, 0.79-mm2, 32-b Intel Architecture core-based near-threshold voltage (NTV) microcontroller (MCU) that provides 17- $\mu \text{W}$ /MHz always-ON, always-sensing (AOAS) capability. The MCU implements four independent voltage-frequency islands, managed by an integrated power management unit and features a subthreshold voltage capable on-die oscillator and 42-nm fin-pitch, 8.3-pA leakage-per-bit SRAM. The MCU operates across a wide frequency (voltage) range from 297 MHz (1 V) to 0.5 MHz (308 mV), dissipating 23.5 mW to 21 $\mu \text{W}$ , and achieves $4.8\times $ better energy efficiency at an optimum supply voltage ( $V_{\text {OPT}}$ ) of 370 mV, 3.5 MHz, and 17 pJ/cycle. A functional AOAS WSN incorporating the NTV MCU shows promise for sustained $\mu \text{W}$ operation.

Hyperpolarization-Activated Current Induces Period-Doubling Cascades and Chaos in a Cold Thermoreceptor Model.

In this article, we describe and analyze the chaotic behavior of a conductance-based neuronal bursting model. This is a model with a reduced number of variables, yet it retains biophysical plausibility. Inspired by the activity of cold thermoreceptors, the model contains a persistent Sodium current, a Calcium-activated Potassium current and a hyperpolarization-activated current (Ih) that drive a slow subthreshold oscillation. Driven by this oscillation, a fast subsystem (fast Sodium and Potassium currents) fires action potentials in a periodic fashion. Depending on the parameters, this model can generate a variety of firing patterns that includes bursting, regular tonic and polymodal firing. Here we show that the transitions between different firing patterns are often accompanied by a range of chaotic firing, as suggested by an irregular, non-periodic firing pattern. To confirm this, we measure the maximum Lyapunov exponent of the voltage trajectories, and the Lyapunov exponent and Lempel-Ziv's complexity of the ISI time series. The four-variable slow system (without spiking) also generates chaotic behavior, and bifurcation analysis shows that this is often originated by period doubling cascades. Either with or without spikes, chaos is no longer generated when the Ih is removed from the system. As the model is biologically plausible with biophysically meaningful parameters, we propose it as a useful tool to understand chaotic dynamics in neurons.

The mixed-mode oscillations in Av-Ron-Parnas-Segel model

Mixed-mode oscillations (MMOs) as complex firing patterns with both relaxation oscillations and sub-threshold oscillations have been found in many neural models such as the stellate neuron model, HH model, and so on. Based on the work, we discuss mixed-mode oscillations in the Av-Ron-Parnas-Segel model which can govern the behavior of the neuron in the lobster cardiac ganglion. By using the geometric singular perturbation theory we first explain why the MMOs exist in the reduced Av-Ron-Parnas-Segel model. Then the mixed-mode oscillatory phenomenon and aperiodic mixed-mode behaviors in the model have been analyzed numerically. Finally, we illustrate the influence of certain parameters on the model.

Hyperbolic Modeling of Subthalamic Nucleus Cells to Investigate the Effect of Dopamine Depletion.

To investigate how different types of neurons can produce well-known spiking patterns, a new computationally efficient model is proposed in this paper. This model can help realize the neuronal interconnection issues. The model can demonstrate various neuronal behaviors observed in vivo through simple parameter modification. The behaviors include tonic and phasic spiking, tonic and phasic bursting, class 1 and class 2 excitability, rebound spike, rebound burst, subthreshold oscillation, and accommodated spiking along with inhibition neuron responses. Here, we investigate the neuronal spiking patterns in Parkinson's disease through our proposed model. Abnormal pattern of subthalamic nucleus in Parkinson's disease can be studied through variations in the shape and frequency of firing patterns. Our proposed model introduces mathematical equations, where these patterns can be derived and clearly differentiated from one another. The irregular and arrhythmic behaviors of subthalamic nucleus firing pattern under normal conditions can easily be transformed to those caused by Parkinson's disease through simple parameter modifications in the proposed model. This model can explicitly show the change of neuronal activity patterns in Parkinson's disease, which may eventually lead to effective treatment with deep brain stimulation devices.

BIOPHYSICAL PROPERTIES OF SUBTHRESHOLD RESONANCE OSCILLATIONS AND SUBTHRESHOLD MEMBRANE OSCILLATIONS IN NEURONS.

Subthreshold-level activities in neurons play a crucial role in neuronal oscillations. These small-amplitude oscillations have been suggested to be involved in synaptic plasticity and in determining the frequency of network oscillations. Subthreshold membrane oscillations (STOs) and subthreshold resonance oscillations (SROs) are the main constituents of subthreshold-level activities in neurons. In this study, a general theoretical framework for analyzing the mechanisms underlying STOs and SROs in neurons is presented. Results showed that the resting membrane potential and the hyperpolarization-activated potassium channel (h-channel) affect the subthreshold-level activities in stellate cells. The contribution of h-channel on resonance is attributed to its large time constant, which produces the time lag between Ih and the membrane potential. Conversely, the persistent sodium channels (Nap-channels) only play an amplifying role in these neurons.

The shaping of intrinsic membrane potential oscillations: positive/negative feedback, ionic resonance/amplification, nonlinearities and time scales.

The generation of intrinsic subthreshold (membrane potential) oscillations (STOs) in neuronal models requires the interaction between two processes: a relatively fast positive feedback that favors changes in voltage and a slower negative feedback that opposes these changes. These are provided by the so-called resonant and amplifying gating variables associated to the participating ionic currents. We investigate both the biophysical and dynamic mechanisms of generation of STOs and how their attributes (frequency and amplitude) depend on the model parameters for biophysical (conductance-based) models having qualitatively different types of resonant currents (activating and inactivating) and an amplifying current. Combinations of the same types of ionic currents (same models) in different parameter regimes give rise to different types of nonlinearities in the voltage equation: quasi-linear, parabolic-like and cubic-like. On the other hand, combinations of different types of ionic currents (different models) may give rise to the same type of nonlinearities. We examine how the attributes of the resulting STOs depend on the combined effect of these resonant and amplifying ionic processes, operating at different effective time scales, and the various types of nonlinearities. We find that, while some STO properties and attribute dependencies on the model parameters are determined by the specific combinations of ionic currents (biophysical properties), and are different for models with different such combinations, others are determined by the type of nonlinearities and are common for models with different types of ionic currents. Our results highlight the richness of STO behavior in single cells as the result of the various ways in which resonant and amplifying currents interact and affect the generation and termination of STOs as control parameters change. We make predictions that can be tested experimentally and are expected to contribute to the understanding of how rhythmic activity in neuronal networks emerge from the interplay of the intrinsic properties of the participating neurons and the network connectivity.

Recording Gamma Band Oscillations in Pedunculopontine Nucleus Neurons.

Synaptic efferents from the PPN are known to modulate the neuronal activity of several intralaminar thalamic regions (e.g., the centrolateral/parafascicular; Cl/Pf nucleus). The activation of either the PPN or Cl/Pf nuclei in vivo has been described to induce the arousal of the animal and an increment in gamma band activity in the cortical electroencephalogram (EEG). The cellular mechanisms for the generation of gamma band oscillations in Reticular Activating System (RAS) neurons are the same as those found to generate gamma band oscillations in other brains nuclei. During current-clamp recordings of PPN neurons (from parasagittal slices from 9 - 25 day-old rats), the use of depolarizing square steps rapidly activated voltage-dependent potassium channels that prevented PPN neurons from being depolarized beyond -25 mV. Injecting 1 - 2 sec long depolarizing current ramps gradually depolarized PPN membrane potential resting values towards 0 mV. However, injecting depolarizing square pulses generated gamma-band oscillations of membrane potential that showed to be smaller in amplitude compared to the oscillations generated by ramps. All experiments were performed in the presence of voltage-gated sodium channels and fast synaptic receptors blockers. It has been shown that the activation of high-threshold voltage-dependent calcium channels underlie gamma-band oscillatory activity in PPN neurons. Specific methodological and pharmacological interventions are described here, providing the necessary tools to induce and sustain PPN subthreshold gamma band oscillation in vitro.

Chaotic Resonance in Coupled Inferior Olive Neurons with the Llinás Approach Neuron Model.

It is well known that cerebellar motor control is fine-tuned by the learning process adjusted according to rich error signals from inferior olive (IO) neurons. Schweighofer and colleagues proposed that these signals can be produced by chaotic irregular firing in the IO neuron assembly; such chaotic resonance (CR) was replicated in their computer demonstration of a Hodgkin-Huxley (HH)-type compartment model. In this study, we examined the response of CR to a periodic signal in the IO neuron assembly comprising the Llinás approach IO neuron model. This system involves empirically observed dynamics of the IO membrane potential and is simpler than the HH-type compartment model. We then clarified its dependence on electrical coupling strength, input signal strength, and frequency. Furthermore, we compared the physiological validity for IO neurons such as low firing rate and sustaining subthreshold oscillation between CR and conventional stochastic resonance (SR) and examined the consistency with asynchronous firings indicated by the previous model-based studies in the cerebellar learning process. In addition, the signal response of CR and SR was investigated in a large neuron assembly. As the result, we confirmed that CR was consistent with the above IO neuron's characteristics, but it was not as easy for SR.

Subthreshold and suprathreshold vibrational resonance in the FitzHugh-Nagumo neuron model.

We study the subthreshold and suprathreshold vibrational resonance in the FitzHugh-Nagumo neuron model. For the subthreshold situation, two cases where the stationary states are equilibrium point and limit cycle are considered, where different natures of vibrational resonance are observed via theoretical and numerical methods. Especially when the frequency of the high-frequency driving force is near the so-called canard-resonance frequency, the firing rate can be significantly enhanced at the presence of noise. For the suprathreshold situation, we show that the local maxima of the response amplitude are located at the transition boundaries of different phase-locking patterns. The minimal required forcing amplitudes of high-frequency signal of the firing onset are just multiples of the spiking frequency. Furthermore, phase portraits and time series show that the presence of the global maxima of the response results from not only the suprathreshold but also the subthreshold phase-locking modes. In spite of the distinct characteristics for two stationary states on subthreshold oscillation, the suprathreshold vibrational resonance showed no qualitative difference between the two cases.

Distinct current modules shape cellular dynamics in model neurons

Numerous intrinsic currents are known to collectively shape neuronal membrane potential dynamics, or neuronal signatures. Although how sets of currents shape specific signatures such as spiking characteristics or oscillations has been studied individually, it is less clear how a neuron’s suite of currents jointly shape its entire set of signatures. Biophysical conductance-based models of neurons represent a viable tool to address this important question. We hypothesized that currents are grouped into distinct modules that shape specific neuronal characteristics or signatures, such as resting potential, sub-threshold oscillations, and spiking waveforms, for several classes of neurons. For such a grouping to occur, the currents within one module should have minimal functional interference with currents belonging to other modules. This condition is satisfied if the gating functions of currents in the same module are grouped together on the voltage axis; in contrast, such functions are segregated along the voltage axis for currents belonging to different modules. We tested this hypothesis using four published example case models and found it to be valid for these classes of neurons. This insight into the neurobiological organization of currents also suggests an intuitive, systematic, and robust methodology to develop biophysical single-cell models with multiple biological characteristics applicable for both hand- and automated-tuning approaches. We illustrate the methodology using two example case rodent pyramidal neurons, from the lateral amygdala and the hippocampus. The methodology also helped reveal that a single-core compartment model could capture multiple neuronal properties. Such biophysical single-compartment models have potential to improve the fidelity of large network models.

Heterogeneous Expression of T-type Ca(2+) Channels Defines Different Neuronal Populations in the Inferior Olive of the Mouse.

The neurons in the inferior olive express subthreshold oscillations in their membrane potential. This oscillatory activity is known to drive synchronous activity in the cerebellar cortex and plays a role in motor learning and motor timing. In the past years, it was commonly thought that olivary neurons belonged to a unique population of oscillating units and that oscillation properties were exclusively dependent on network settings and/or synaptic inputs. The origin of olivary oscillations is now known to be a local phenomenon and is generated by a combination of conductances. In the present work, we show the existence of at least two neuronal populations that can be distinguished on the basis of the presence or absence of low-voltage activated Ca2+ channels. The expression of this channel determines the oscillatory behavior of olivary neurons. Furthermore, the number of cells that express this channel is different between sub nuclei of the inferior olive. These findings clearly indicate the functional variability within and between olivary sub nuclei.

Electrical Coupling and Synchronized Subthreshold Oscillations in the Inferior Olive of the Rhesus Macaque

Inferior olive (IO) neurons are critical for motor coordination and exhibit oscillations in membrane potential that are subthreshold for spiking. The prevalence, coherence, and continuity of those subthreshold oscillations (STOs) depend upon resonant interactions between neighboring neurons supported by electrical coupling. Many studies of the olivocerebellar system in rodents, in which STOs were related to tremor, whisking, and licking, fueled a debate over whether IO STOs were relevant for primates whose repertoire of movement is generally less periodic. The debate was never well informed due to the lack of a direct examination of the physiological properties of primate IO neurons. Here, we obtained dual patch-clamp recordings of neighboring IO neurons from young adult macaques in brainstem slices and compared them to identical recordings from rats. Macaque IO neurons exhibited an equivalent prevalence of continuous STOs as rats (45 vs 54%, respectively). However, macaque STOs were slower (1-4 Hz) and did not overlap with the dominant 4-9 Hz frequency of rats. The slower STO frequency of macaques was at least partially due to a prolonged membrane time constant and increased membrane capacitance that could be attributed to stronger electrical coupling and greater total dendritic length. The presence of synchronized STOs in the IO of adult macaques, coincident with strong and prevalent electrical coupling, answers a fundamental outstanding question in cerebellar neuroscience and is consistent with a prominent role for synchronized oscillation in primate sensory-motor control. It was debated whether inferior olive (IO) neurons of primates behave as synchronized oscillators as was found for rodents using intracellular, optical, and multielectrode recordings. An inability to resolve this issue using single-Purkinje cell extracellular recordings in monkeys limited our understanding of timing mechanisms in the primate brain. Using dual whole-cell recordings from the IO of young adult rhesus macaques in acutely prepared brainstem slices, our work demonstrates that pairs of primate IO neurons show synchronized oscillations in membrane potential. The findings have strong mechanistic and translational relevance, as IO activation has been implicated in humans' perceptual timing of sensory events and motricity.

Squeezed-light spin noise spectroscopy

We report quantum enhancement of Faraday rotation spin noise spectroscopy by polarization squeezing of the probe beam. Using natural abundance Rb in 100 Torr of N_2 buffer gas, and squeezed light from a sub-threshold optical parametric oscillator stabilized 20 GHz to the blue of the D_1 resonance, we observe that an input squeezing of 3.0 dB improves the signal-to-noise ratio by 1.5 dB to 2.6 dB over the combined (power)$\otimes$(number density) ranges (0.5 mW to 4.0 mW )$\otimes$(1.5 x 10^{12} cm^{-3} to 1.3 x 10^{13} cm^{-3}), covering the ranges used in optimized spin noise spectroscopy experiments. We also show that squeezing improves the trade-off between statistical sensitivity and broadening effects, a previously unobserved quantum advantage.

Biophysical constraints on lateral inhibition in the olfactory bulb.

The mitral cells (MCs) of the mammalian olfactory bulb (OB) constitute one of two populations of principal neurons (along with middle/deep tufted cells) that integrate afferent olfactory information with top-down inputs and intrinsic learning and deliver output to downstream olfactory areas. MC activity is regulated in part by inhibition from granule cells, which form reciprocal synapses with MCs along the extents of their lateral dendrites. However, with MC lateral dendrites reaching over 1.5 mm in length in rats, the roles of distal inhibitory synapses pose a quandary. Here, we systematically vary the properties of a MC model to assess the capacity of inhibitory synaptic inputs on lateral dendrites to influence afferent information flow through MCs. Simulations using passivized models with varying dendritic morphologies and synaptic properties demonstrated that, even with unrealistically favorable parameters, passive propagation fails to convey effective inhibitory signals to the soma from distal sources. Additional simulations using an active model exhibiting action potentials, subthreshold oscillations, and a dendritic morphology closely matched to experimental values further confirmed that distal synaptic inputs along the lateral dendrite could not exert physiologically relevant effects on MC spike timing at the soma. Larger synaptic conductances representative of multiple simultaneous inputs were not sufficient to compensate for the decline in signal with distance. Reciprocal synapses on distal MC lateral dendrites may instead serve to maintain a common fast oscillatory clock across the OB by delaying spike propagation within the lateral dendrites themselves.

Interplay between Subthreshold Oscillations and Depressing Synapses in Single Neurons.

In this paper we analyze the interplay between the subthreshold oscillations of a single neuron conductance-based model and the short-term plasticity of a dynamic synapse with a depressing mechanism. In previous research, the computational properties of subthreshold oscillations and dynamic synapses have been studied separately. Our results show that dynamic synapses can influence different aspects of the dynamics of neuronal subthreshold oscillations. Factors such as maximum hyperpolarization level, oscillation amplitude and frequency or the resulting firing threshold are modulated by synaptic depression, which can even make subthreshold oscillations disappear. This influence reshapes the postsynaptic neuron’s resonant properties arising from subthreshold oscillations and leads to specific input/output relations. We also study the neuron’s response to another simultaneous input in the context of this modulation, and show a distinct contextual processing as a function of the depression, in particular for detection of signals through weak synapses. Intrinsic oscillations dynamics can be combined with the characteristic time scale of the modulatory input received by a dynamic synapse to build cost-effective cell/channel-specific information discrimination mechanisms, beyond simple resonances. In this regard, we discuss the functional implications of synaptic depression modulation on intrinsic subthreshold dynamics.

Nav Channels in Damaged Membranes.

Sick excitable cells (ie, Nav channel-expressing cells injured by trauma, ischemia, inflammatory, and other conditions) typically exhibit "acquired sodium channelopathies" which, we argue, reflect bleb-damaged membranes rendering their Nav channels "leaky."The situation is excitotoxic because untreated Nav leak exacerbates bleb damage. Fast Nav inactivation (a voltage-independent process) is so tightly coupled, kinetically speaking, to the inherently voltage-dependent process of fast activation that when bleb damage accelerates and thus left-shifts macroscopic fast activation, fast inactivation accelerates to the same extent. The coupled g(V) and availability(V) processes and their window conductance regions consequently left-shift by the same number of millivolts. These damage-induced hyperpolarizing shifts, whose magnitude increases with damage intensity, are called coupled left shift (CLS). Based on past work and modeling, we discuss how to test for Nav-CLS, emphasizing the virtue of sawtooth ramp clamp. We explain that it is the inherent mechanosensitivity of Nav activation that underlies Nav-CLS. Using modeling of excitability, we show the known process of Nav-CLS is sufficient to predict a wide variety of "sick excitable cell" phenomena, from hyperexcitability through to depolarizing block. When living cells are mimicked by inclusion of pumps, mild Nav-CLS produces a wide array of burst phenomena and subthreshold oscillations. Dynamical analysis of mild damage scenarios shows how these phenomena reflect changes in spike thresholds as the pumps try to counteract the leaky Nav channels. Smart Nav inhibitors designed for sick excitable cells would target bleb-damaged membrane, buying time for cell-mediated removal or repair of Nav-bearing membrane that has become bleb-damaged (ie, detached from the cytoskeleton).

Channel-specific input/output transformations arising from the interaction between dynamic synapses and subthreshold oscillations

Subthreshold oscillations are observed in a wide variety of neurons in the nervous system (e.g. see [1,2]). They typically appear associated to resonance phenomena that allow, for instance, the implementation of intrinsic memory mechanisms for the detection of specific spike sequences in single neurons and neural networks [3-5]. On the other hand, synaptic transmission and, therefore, the corresponding input/output transformation in the postsynaptic cell are affected by recent presynaptic activity. Dynamic synapses modulate incoming information increasing (facilitation) or decreasing (depression) the postsynaptic response. This modulation provides additional characteristic time scales to the single neuron and network processing [6,7]. In the context of a neuron displaying subthreshold oscillations, the interplay between these additional time scales and the characteristic intrinsic fast and slow dynamics underlying the neuron's oscillatory activity can significantly affect its input/output transformation. Neuronal intrinsic subthreshold oscillations and dynamic synapses underlie several computational properties both at the single neuron and the network levels. Traditionally, intrinsic oscillations and dynamic synapses have been studied separately and their interaction has attracted almost no attention. In this work, we use a conductance-based neuron model and a dynamic synapse to investigate how intrinsic subthreshold oscillations and the short-term plasticity of a depressing synapse act together to shape its resonant properties and the corresponding input/output transformation. Our results suggest that factors such as the maximum hyperpolarization level, the oscillation amplitude and frequency or the resulting firing threshold can be modulated by synaptic depression. This shapes the postsynaptic neuron's resonant properties arising from the subthreshold oscillation and leads to complex channel-specific input/output relations. Thus, a low-cost modification in synaptic parameters can produce a significant different response. This complex synaptic-dependent input/output transformation allows the implementation of cost-effective information discrimination mechanisms in single neurons by just tuning the depression level of the synaptic channel without modifying the intrinsic neural dynamics.