Balancing Feed-Forward Excitation and Inhibition via Hebbian Inhibitory Synaptic Plasticity

By Yotam Luz, Maoz Shamir. 2012

89 citations recorded by the source corpus.

It has been suggested that excitatory and inhibitory inputs to cortical cells are balanced, and that this balance is important for the highly irregular firing observed in the cortex. There are two hypotheses as to the origin of this balance. One assumes that it results from a stable solution of the recurrent neuronal dynamics. This model can account for a balance of steady state excitation and inhibition without fine tuning of parameters, but not for transient inputs. The second hypothesis suggests that the feed forward excitatory and inhibitory inputs to a postsynaptic cell are already balanced. This latter hypothesis thus does account for the balance of transient inputs. However, it remains unclear what mechanism underlies the fine tuning required for balancing feed forward excitatory and inhibitory inputs. Here we investigated whether inhibitory synaptic plasticity is responsible for the balance of transient feed forward excitation and inhibition. We address this issue in the framework of a model characterizing the stochastic dynamics of temporally anti-symmetric Hebbian spike timing dependent plasticity of feed forward excitatory and inhibitory synaptic inputs to a single post-synaptic cell. Our analysis shows that inhibitory Hebbian plasticity generates ‘negative feedback’ that balances excitation and inhibition, which contrasts with the ‘positive feedback’ of excitatory Hebbian synaptic plasticity. As a result, this balance may increase the sensitivity of the learning dynamics to the correlation structure of the excitatory inputs.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering

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Citations in the corpus

The temporal paradox of Hebbian learning and homeostatic plasticity (2017, background): “For instance, there are cases in which induction of ISP alone can flip the sign of subsequent plasticity at excitatory synapses [89].”
Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector (2013, background): “Recent theoretical studies [69–71] suggest that ISP could produce an intrinsically stable feed-back system.”
Inhibitory synaptic plasticity: spike timing-dependence and putative network function (2013, background): “It was recently suggested that dendrites act as independent computational units (Poirazi et al., 2003; Losonczy et al., 2008; Branco and Häusser, 2010) that locally regulate many important cellular processes, such as plasticity and protein synthesis.”
Receptive field formation by interacting excitatory and inhibitory synaptic plasticity (2016, background): “Activity-dependent Hebbian plasticity of inhibitory synapses has been suggested as a self-organization principle by which inhibitory currents can be adjusted to balance their excitatory counterparts (Vogels et al., 2011; Luz & Shamir, 2012).”
Dendritic cortical microcircuits approximate the backpropagation algorithm (2018, background): “This learning rule of apical-targeting interneuron synapses can be thought of as a dendritic variant of the homeostatic inhibitory plasticity proposed by Vogels et al. (2011); Luz and Shamir (2012).”
Plasticity of Cortical Excitatory-Inhibitory Balance (2015, background): “…not identical to that used by Vogels et al. (2011), although several different formulations of inhibitory STDP learning rules can have similar functional consequences, in terms of calibrating or balancing inhibition with excitation and controlling overall network excitability (Luz & Shamir 2012).”