PMC

Two examples of experiments demonstrating the cumulative effect of two opposing stimulation protocols: (A) −1,100-ms latency (lat.) pairing followed by zero-latency pairing; and (B) −300-ms latency pairing followed by −2,100-ms latency pairing. Horizontal blue lines represent the mean EPSC size, and vertical green and red boxes demonstrate the duration of the stimulation protocol.

Percent change in synaptic efficacy evoked by pairings at different latencies between pre- and postsynaptic bursts. The average change for non-overlapping bursts (E) is shown as a dashed line. The best symmetric (solid) or asymmetric (dotted) burst-based rules are also shown. The three numbered examples are considered in detail in .
t _post, time of the postsynaptic burst; t _pre, time of the presynaptic burst.

(A) The maximum current during EPSCs evoked every 30 s throughout the course of a zero-latency pairing experiment (with simultaneous pre- and postsynaptic bursts). Inset: average EPSCs before (dashed) and after (solid) stimulation. As with (B–D), horizontal blue lines represent the mean EPSC size, and vertical green and red boxes demonstrate the duration of the stimulation protocol.
dep., depolarization; stim, stimulation.
(B) Summary of all zero-latency experiments, showing an average increase in synaptic efficacy of 21.3% (n = 7 neurons).
(C) A single experiment showing EPSC size for a −1,100-ms latency pairing experiment.
(D) Summary over all non-overlapping experiments shows an average −5.9% change in EPSC size (n = 13 neurons).
(E) The zero-latency and non-overlapping burst protocols evoke significant changes in synaptic efficacy: summary plot with standard error is shown.

(A) Schematic demonstrating natural activity resulting from retinal waves in the retina (top) and LGN (bottom): a retinal wave involves activity over a population of RGCs (#1) that evokes a large synaptic input in target LGN neurons (#2). Dashed boxes correspond to the two components of natural retinal wave activity reproduced in our experiments. Retinal wave multi-electrode recording data were adapted from Wong et al. []; LGN synaptic recording adapted from Mooney et al. []
(B) Retinal wave activity at the retinogeniculate synapse is reproduced by minimal 10-Hz stimulation to the OT (vertical blue lines) paired at a given latency with direct current injection into the recorded LGN neuron to evoke 10–20 Hz bursting (top). Participation of the selected synapse has negligible effect on LGN firing, as shown by comparing the depolarization paired with +100 ms latency OT stimulation (stim) (top) with depolarization alone (bottom).
(C) This situation is in marked contrast to a tetanus protocol, which involves higher current stimulation (100 Hz for 1 s), resulting in a long-lasting depolarization largely absent of postsynaptic spiking.
Scale bars for (B) and (C) are shown between these panels.

(A) Histograms of spike-time latencies (right) measured from the timing between EPSPs and spikes evoked during the three different burst-based stimulation protocols shown (left). Nearest-neighbor times are shown in black, with additional non–nearest-neighbor times in green.
(B) CCs demonstrating the degree to which different learning rules predict the observed data of . Spike-based rules from the Xenopus retinotectal system [] (hashed cyan) and mammalian somatosensory cortex [] (green)—are compared with the burst-latency–based rules (left columns). Removing consideration of spike pairs that result in weakening produces better predictions: from the naively applied STDP (#1), to only considering nearest-neighbor spikes (#2), to the modified STDP that takes multi-spike interactions into account as suggested by Sjöstrom et al. [] (#3). Removing the temporal window for depression entirely—leaving a simple spike-based coincidence rule—yields the best predictions (right column).
(C) The ability of spike-based rules to predict the data in () is related to the degree to which depressing latencies are ignored. Left: the average Xenopus (top) and cortex (bottom) learning rule as more spike latencies are selectively ignored. Right: the resulting balance between strengthening (blue +) and weakening (red −) changes with successive modifications to STDP: the best predictions correspond to rules with the least amount of weakening.
(D) The predictions of the spike-based learning rule derived from the total number of spike coincidences, compared with the burst-based rule that is just a function of burst latency (dashed line). t _post, time of the postsynaptic burst; t _pre, time of the presynaptic burst.

(A) Model schematic of localized areas in two retinas providing input to a single LGN neuron. Below: the LGN neuron activity is the sum of RGC activity over its inputs; a RGC from each eye and the LGN activity is shown for 5 min during a simulation with normal retinal waves (left) and a simulation in which the left eye has activity simulating raised cAMP levels, which results in increased wave size and frequency (right) [].
(B) The amount of coincident activity between RGCs and the LGN neuron as a function of two-dimensional RGC position in the retina (top, contour plot) and a one-dimensional slice through the middle of each retina (bottom). The dashed horizontal line in each figure illustrates that for a given cutoff between strengthening and weakening, a larger number of RGCs in the left eye (compared with the right eye) will be strengthened in retinotopically appropriate positions. As a result, no matter where this cutoff is, more connections will be weakened (shaded areas) that originate from the right eye.
(C) The results of simulations over a range of initial bias in connection strength between the eyes, demonstrating that the initial strength of connection biases competition in favor of the more strongly connected eye. Simulations were run using normal waves (solid line), as well as a condition simulating elevated cAMP levels in one eye (dashed line) or both eyes (dotted line).
(D) The amount of activity overlap for simulations of elevated cAMP levels in both eyes (same format as in [B], bottom), showing that increasing wave size and frequency results in normal eye segregation as shown in (C), but less retinotopic refinement.