Human Synapses Show a Wide Temporal Window for Spike-Timing-Dependent Plasticity - Silva, Guilherme T.; Verhoog, Matthijs B.; Goriounova, Natalia B.; Loebel, Alex; Hjorth, Johannes; Baayen, Johannes C.; De Kock, Christiaan P.; Mansvelder, Huibert D. (Frontiers in Synaptic Neuroscience, 2010)
Throughout our lifetime, activity-dependent changes in neuronal connection strength enable the brain to refine neural circuits and learn based on experience. Synapses can bi-directionally alter strength and the magnitude and sign depend on the millisecond timing of presynaptic and postsynaptic action potential firing. Recent findings on laboratory animals have shown that neurons can show a variety of temporal windows for spike-timing-dependent plasticity (STDP). It is unknown what synaptic learning rules exist in human synapses and whether similar temporal windows for STDP at synapses hold true for the human brain. Here, we directly tested in human slices cut from hippocampal tissue removed for surgical treatment of deeper brain structures in drug-resistant epilepsy patients, whether adult human synapses can change strength in response to millisecond timing of pre- and postsynaptic firing. We find that adult human hippocampal synapses can alter synapse strength in response to timed pre- and postsynaptic activity. In contrast to rodent hippocampal synapses, the sign of plasticity does not sharply switch around 0 millisecond timing. Instead, both positive timing intervals, in which presynaptic firing preceded the postsynaptic action potential, and negative timing intervals, in which postsynaptic firing preceded presynaptic activity down to -80 ms, increase synapse strength (tLTP). Negative timing intervals between -80 to -130 ms induce a lasting reduction of synapse strength (tLTD). Thus, similar to rodent synapses, adult human synapses can show spike-timing-dependent changes in strength. The timing rules of STDP in human hippocampus, however, seem to differ from rodent hippocampus, and suggest a less strict interpretation of Hebb’s predictions.