<p><b>A:</b> Amounts of LTP (green) and LTD (red) vs. reward level, with our RSTDP model (solid) and with classical RSTDP with and without unsupervised learning (dashed and dot-dashed, respectively) at the equilibrium synaptic weight. For classical RSTDP without unsupervised learning the reward signal has been shifted such that there is no LTP and LTD at the base reward level, (vertical, black, dashed line) instead of at zero reward, . <b>B:</b> An increase (decrease) in firing rate is predicted to occur in the hatched (unhatched) regions for LTP:LTD ratios at the base reward level (:) of 2:1 (red), 1:2 (green), and 1:1 (blue). On the lines that divide these regions no increase or decrease is predicted. The points marked as C and D corresp...
<p>(A) A strong low-frequency stimulus (3 pulses at 20 Hz, repeated 900 ...
The authors present their primary value learned value (PVLV) model for understanding the rewardpredi...
<p>Under the simple STDP model (red curve), weight-dependent LTP occurs only if the postsynaptic spi...
<p><b>A:</b> Change in the firing rate over time for the reinforced (blue), surround (red), and cont...
<p><b>A:</b> Qualitative summary of the observed modulation of LTP and LTD amplitudes with increasin...
<p><b>A:</b> Mean weight into the reinforced neuron () over time for LIF neurons receiving 10,000 ex...
<p><b>A:</b> Firing rates of reinforced (blue), surround (red), and control (green) neurons after le...
EPSP slope after STDP induction under different conditions. A) open red squares: model control (same...
<p>(A) Initial and final synaptic weight values across the time interval of LTP simulation (11,000–1...
A) Average EPSP slope, calculated from the 18 model synapses (red squares, using a Δt = 5 ms) and ex...
<div><p>A fundamental goal of neuroscience is to understand how cognitive processes, such as operant...
A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditi...
A. Plasticity curves of E-to-E (, blue) and I-to-E (, red) weights as a function of the postsynaptic...
<p><b>A:</b> Firing rates of reinforced (blue), surround (red), and control (green) neurons after le...
A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditi...
<p>(A) A strong low-frequency stimulus (3 pulses at 20 Hz, repeated 900 ...
The authors present their primary value learned value (PVLV) model for understanding the rewardpredi...
<p>Under the simple STDP model (red curve), weight-dependent LTP occurs only if the postsynaptic spi...
<p><b>A:</b> Change in the firing rate over time for the reinforced (blue), surround (red), and cont...
<p><b>A:</b> Qualitative summary of the observed modulation of LTP and LTD amplitudes with increasin...
<p><b>A:</b> Mean weight into the reinforced neuron () over time for LIF neurons receiving 10,000 ex...
<p><b>A:</b> Firing rates of reinforced (blue), surround (red), and control (green) neurons after le...
EPSP slope after STDP induction under different conditions. A) open red squares: model control (same...
<p>(A) Initial and final synaptic weight values across the time interval of LTP simulation (11,000–1...
A) Average EPSP slope, calculated from the 18 model synapses (red squares, using a Δt = 5 ms) and ex...
<div><p>A fundamental goal of neuroscience is to understand how cognitive processes, such as operant...
A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditi...
A. Plasticity curves of E-to-E (, blue) and I-to-E (, red) weights as a function of the postsynaptic...
<p><b>A:</b> Firing rates of reinforced (blue), surround (red), and control (green) neurons after le...
A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditi...
<p>(A) A strong low-frequency stimulus (3 pulses at 20 Hz, repeated 900 ...
The authors present their primary value learned value (PVLV) model for understanding the rewardpredi...
<p>Under the simple STDP model (red curve), weight-dependent LTP occurs only if the postsynaptic spi...