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Fix remaining image file paths
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akorgor committed Sep 27, 2024
1 parent e029bef commit 492e557
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infer the underlying rationale of the task. Here, the solution is to turn to the side in which more cues were
presented.
.. image:: ../../../../pynest/examples/eprop_plasticity/eprop_supervised_classification_evidence-accumulation_bsshslm_2020.png
.. image:: eprop_supervised_classification_evidence-accumulation_bsshslm_2020.png
:width: 70 %
:alt: Schematic of network architecture. Same as Figure 1 in the code.
:align: center
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binary events, which we interpret as spike trains. This conversion closely emulates biological neural
processing, making it a fitting challenge for an e-prop-equipped spiking neural network (SNN).
.. image:: ../../../../pynest/examples/eprop_plasticity/eprop_supervised_classification_evidence-accumulation.png
.. image:: eprop_supervised_classification_evidence-accumulation.png
:width: 70 %
:alt: Schematic of network architecture. Same as Figure 1 in the code.
:align: center
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network learns to reproduce with its overall spiking activity a one-dimensional, one-second-long target signal
which is a superposition of four sine waves of different amplitudes, phases, and periods.
.. image:: ../../../../pynest/examples/eprop_plasticity/eprop_supervised_regression_sine-waves_bsshslm_2020.png
.. image:: eprop_supervised_regression_sine-waves_bsshslm_2020.png
:width: 70 %
:alt: Schematic of network architecture. Same as Figure 1 in the code.
:align: center
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