<p><b>A.</b> Examples of synaptic strength evolution over time. Numbers along the top indicate the input burst duration in seconds. <b>B.</b> Mean power spectra, normalized by the peak power in each spectrum, of the final connectivity patterns in simulations using burst durations of 0.03 s (blue), 0.3 s (orange), and 3.0 s (black). <b>C.</b> Robustness of the periodic connectivity pattern to different burst durations. Reference power spectra are taken from simulations with a burst duration of 0.1 s. Black: robustness measures for each burst duration. Pink: theoretical robustness measure, based on the concentration of power at <i>k</i>* in <math><mrow>Re<mo stretchy="false">[</mo><mi>κ</mi><mo>~</mo><mo stretchy="false">(</mo><mi>k</mi><mo s...
A stochastic model of spike-timing-dependent plasticity proposes that single synapses express fixed-...
(a) Dots show trace strengths of individual trained (blue) and untrained (red) patterns. The time at...
The sustained activity in recurrent networks has been under wide computational examination in studie...
<p><b>A & B.</b> Examples of synaptic strength evolution over time for simulations in which: <b>A)</...
<p>(a,b) Firing rate time series segments based on 400 msec moving window for several randomly chose...
<p>(a) Strength of stimulus onset locked reproducible dynamics (see text) versus connectivity for ...
<p><i>(A)</i> Burst duration time as function of the network connectivity (parameter <i>J</i>) for d...
<p>(<b>A</b>) Temporal evolution of the average firing rate in the excitatory population for differe...
<p><b>A</b> Burst rate vs the trauma volume for different sizes of synaptic footprint, for local HSP...
<p>(a) Black circles: minimum observed ISI for each active cell in network simulations of different ...
<div><p>Percent change in synaptic efficacy evoked by pairings at different latencies between pre- a...
<p><i>(A)</i> Burst duration time as function of the network connectivity (parameter <i>J</i>) for d...
<p>Burst duration increases as approaches the boundary of the tonic spiking (TS) state, and decreas...
Spike timing dependent plasticity (STDP) is a synaptic learning rule where the relative timing betw...
<p>The number of information-carrying items contained in the chunks depends on the system dynamics, ...
A stochastic model of spike-timing-dependent plasticity proposes that single synapses express fixed-...
(a) Dots show trace strengths of individual trained (blue) and untrained (red) patterns. The time at...
The sustained activity in recurrent networks has been under wide computational examination in studie...
<p><b>A & B.</b> Examples of synaptic strength evolution over time for simulations in which: <b>A)</...
<p>(a,b) Firing rate time series segments based on 400 msec moving window for several randomly chose...
<p>(a) Strength of stimulus onset locked reproducible dynamics (see text) versus connectivity for ...
<p><i>(A)</i> Burst duration time as function of the network connectivity (parameter <i>J</i>) for d...
<p>(<b>A</b>) Temporal evolution of the average firing rate in the excitatory population for differe...
<p><b>A</b> Burst rate vs the trauma volume for different sizes of synaptic footprint, for local HSP...
<p>(a) Black circles: minimum observed ISI for each active cell in network simulations of different ...
<div><p>Percent change in synaptic efficacy evoked by pairings at different latencies between pre- a...
<p><i>(A)</i> Burst duration time as function of the network connectivity (parameter <i>J</i>) for d...
<p>Burst duration increases as approaches the boundary of the tonic spiking (TS) state, and decreas...
Spike timing dependent plasticity (STDP) is a synaptic learning rule where the relative timing betw...
<p>The number of information-carrying items contained in the chunks depends on the system dynamics, ...
A stochastic model of spike-timing-dependent plasticity proposes that single synapses express fixed-...
(a) Dots show trace strengths of individual trained (blue) and untrained (red) patterns. The time at...
The sustained activity in recurrent networks has been under wide computational examination in studie...