Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony?

نویسندگان

  • Andreas Knoblauch
  • Florian Hauser
  • Marc-Oliver Gewaltig
  • Edgar Körner
  • Günther Palm
چکیده

Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, bidirectional synaptic connections as found in cortical areas could be reproduced only by assuming realistic models of STDP and rate coding. We resolve this conflict by theoretical analysis and simulation of various simple and realistic STDP models that provide a more complete characterization of conditions when STDP leads to either coupling or decoupling of neurons firing in synchrony. In particular, we show that STDP consistently couples synchronized neurons if key model parameters are matched to physiological data: First, synaptic potentiation must be significantly stronger than synaptic depression for small (positive or negative) time lags between presynaptic and postsynaptic spikes. Second, spike synchronization must be sufficiently imprecise, for example, within a time window of 5-10 ms instead of 1 ms. Third, axonal propagation delays should not be much larger than dendritic delays. Under these assumptions synchronized neurons will be strongly coupled leading to a dominance of bidirectional synaptic connections even for simple STDP models and low mean firing rates at the level of spontaneous activity.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Spike timing dependent plasticity: mechanisms, significance, and controversies

Long-term modification of synaptic strength is one of the basic mechanisms of memory formation and activity-dependent refinement of neural circuits. This idea was purposed by Hebb to provide a basis for the formation of a cell assembly. Repetitive correlated activity of pre-synaptic and post-synaptic neurons can induce long-lasting synaptic strength modification, the direction and extent of whi...

متن کامل

Spike timing dependent plasticity: mechanisms, significance, and controversies

Long-term modification of synaptic strength is one of the basic mechanisms of memory formation and activity-dependent refinement of neural circuits. This idea was purposed by Hebb to provide a basis for the formation of a cell assembly. Repetitive correlated activity of pre-synaptic and post-synaptic neurons can induce long-lasting synaptic strength modification, the direction and extent of whi...

متن کامل

Temporal characteristics of the predictive synchronous firing modeled by spike-timing-dependent plasticity.

When a sensory cue was repeatedly followed by a behavioral event with fixed delays, pairs of premotor and primary motor neurons showed significant increases of coincident spikes at times a monkey was expecting the event. These results provided evidence that neuronal firing synchrony has predictive power. To elucidate the underlying mechanism, here we argue some nontrivial characteristics of the...

متن کامل

Role of STDP in regulation of neural timing networks in human: a simulation study

Many physiological events require an accurate timing signal, usually generated by neural networks called central pattern generators (CPGs). On the other hand, properties of neurons and neural networks (e.g. time constants of neurons and weights of network connections) alter with time, resulting in gradual changes in timing of such networks. Recently, a synaptic weight adjustment mechanism has b...

متن کامل

Timing Intervals Using Population Synchrony and Spike Timing Dependent Plasticity

We present a computational model by which ensembles of regularly spiking neurons can encode different time intervals through synchronous firing. We show that a neuron responding to a large population of convergent inputs has the potential to learn to produce an appropriately-timed output via spike-time dependent plasticity. We explain why temporal variability of this population synchrony increa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2012