Depressing synapse as a detector of frequency change.
نویسندگان
چکیده
In this article we discuss the short-term synaptic depression using a mathematical model. We derive the model of synaptic depression caused by the depletion of synaptic vesicles for the case of infinitely short stimulation time and show that the analytical formulas for the postsynaptic potential (PSP) and kinetic functions take simple closed form. A solution in this form allows an analysis of the characteristics of depression as a function of the models parameters and the derivation of analytic formulas for measures of short time synaptic depression commonly used in experimental studies. Those formulas are used to validate the model by fitting it to two types of synapses described in the literature. Given the fitted parameters we discuss the behavior of the synapse in situations involving frequency change. We also indicate a possible role of depressing synapses in information processing as not only a filter of high frequency input but as a detector of the return from high frequency stimulation to the stimulation within frequency band specific for a given synapse.
منابع مشابه
Synaptic depression creates a switch that controls the frequency of an oscillatory circuit.
Synaptic depression is a form of short-term plasticity exhibited by many synapses. Nonetheless, the functional significance of synaptic depression in oscillatory networks is not well understood. We show that, in a recurrent inhibitory network that includes an intrinsic oscillator, synaptic depression can give rise to two distinct modes of network operation. When the maximal conductance of the d...
متن کاملNeuronal synchrony detection on single-electron neural networks
Synchrony detection between burst and non-burst spikes is known to be one functional example of depressing synapses. Kanazawa et al. demonstrated synchrony detection with MOS depressing synapse circuits. They found that the performance of a network with depressing synapses that discriminates between burst and random input spikes increases non-monotonically as the static device mismatch is incre...
متن کاملContribution of synaptic depression to phase maintenance in a model rhythmic network.
In many rhythmic neuronal networks that operate in a wide range of frequencies, the time of neuronal firing relative to the cycle period (the phase) is invariant. This invariance suggests that when frequency changes, firing time is precisely adjusted either by intrinsic or synaptic mechanisms. We study the maintenance of phase in a computational model in which an oscillator neuron (O) inhibits ...
متن کاملHigh-frequency, depressing inhibition facilitates synchronization in globally inhibitory networks.
Motivated by the study of sharp wave-associated ripples, high-frequency (approximately 200 Hz) extracellular field oscillations observed in the CA1 region of the rat hippocampus during slow-wave sleep and periods of behavioural immobility, we consider a single inhibitory neuron synapsing onto a network of uncoupled, excitatory neurons. The inhibitory synapse is depressing and has a small synapt...
متن کاملA hardware depressing synapse and its application to contrast-invariant pattern recognition
Analog circuits for depressing synapses are proposed for emulating the dynamic properties of neural networks using dynamic neurons. Although the circuits have few MOS transistors, they mimic well the dynamic properties of depressing synapses. A simple neural network using depressing synapses is introduced for evaluating the performance of hardware depressing synapses. We show that a device usin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Journal of theoretical biology
دوره 266 3 شماره
صفحات -
تاریخ انتشار 2010