Differential signaling via the same axon of neocortical pyramidal neurons.

By Henry Markram, Yun Wang, Misha Tsodyks. 1998

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Citations in the corpus

Coordinated and Compartmentalized Neuromodulation Shapes Sensory Processing in Drosophila (2015, positive): “Heterogeneous neurotransmission from the synapses along a single axon has been described in the cortex and hippocampus as a possible substrate for independent plasticity between a neuron and its myriad of postsynaptic targets (Markram et al., 1998; Pelkey and McBain, 2007).”
Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression (2008, background): “characterized by a small set of distinct phenomena such as shortterm plasticity [44] as well as early and late phases of LTP and”
Multiple Time Scales of Adaptation in Auditory Cortex Neurons (2004, background): “, 1997), ranging between a few hundreds of milliseconds and a few tens of seconds (Tsodyks and Markram, 1997; Varela et al., 1997; Markram et al., 1998), which matches the stimulus-specific time constants described here.”
Neural Networks with Dynamic Synapses (1998, background): “This assumption is valid for interpyramidal synapses studied in Markram and Tsodyks (1996) and for pyramidal interneuron synapses (Markram et al., in press).”
On the computational power of circuits of spiking neurons (2004, methodology): “Parameters of neurons and synapses were chosen to fit data from microcircuits in rat somatosensory cortex (based on [10], [27] and unpublished data from the Markram Lab).”
Reconstruction and Simulation of Neocortical Microcircuitry. (2015, methodology): “, 2002), except for connections onto Martinotti, bitufted and other interneuron types displaying spike frequency accommodation, which are facilitating (E1) (Kapfer et al., 2007; Markram et al., 1998; Reyes et al., 1998; Rozov et al., 2001; Silberberg and Markram, 2007), (3) facilitation from inhibit”
Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations (2002, methodology): “In the case of a synaptic connection from a to b , we modeled the synaptic dynamics according to the model proposed in Markram, Wang, and Tsodyks (1998), with the synaptic parameters U (use), D (time constant for depression), and F (time constant for facilitation) randomly chosen from gaussian…”
Timing in the absence of clocks: encoding time in neural network states. (2007, methodology): “Since experimental data suggests that short-term plasticity operates on the time scale of a few hundred milliseconds (Markram et al., 1998; Reyes and Sakmann, 1998), the state-dependent model predicts that the network will not have completely returned to its initial state in the ISI250 condition, th”
Emergence of Dynamic Memory Traces in Cortical Microcircuit Models through STDP (2013, background): “It is well known that biological synapses are not static, and have a complex inherent temporal dynamics (Markram et al., 1998; Gupta et al., 2000).”
Dense, Unspecific Connectivity of Neocortical Parvalbumin-Positive Interneurons: A Canonical Microcircuit for Inhibition? (2011, methodology): “Trains of eight action potentials delivered at 50 Hz followed by a single action potential 1 s after the last action potential in the train were evoked in the PV interneuron to measure the paired pulse ratio, summation, train depression, and recovery (Markram et al., 1998).”
Phenomenological models of synaptic plasticity based on spike timing (2008, background): “This is the essence of all unsupervised learning rules (ii) a mechanism for the development of input selectivity such as receptive fields (Bienenstock et al. 1982; Miller et al. 1989), in the presence of strong input features.”
Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits (2020, methodology): “There are also reports of polarization of STP along the basal dendrosomatic axis [109], and our model would predict that this polarization should extend to apical dendrites.”
Short-term synaptic plasticity. (2002, background): “The identity of postsynaptic targets can influence the magnitude or dominance of facilitation or depression (341, 342), as can developmental age (343) and the A nn u.”