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Abstract:
For many years, the idea of a ‘blanket of inhibition’ that modulates excitatory currents on average had been nearly universally accepted. However, recent experimental and theoretical findings have demonstrated evidence and benefits of excitatory/inhibitory co-tuning [1]. This, in turn, opens questions about how such co-tuning can potentially emerge. The experimental observation of STDP in inhibitory synapses [2] along with relevant theoretical studies [3] suggest that synaptic plasticity mechanisms can generate E/I co-tuning. Still, studies of the ability of inhibitory plasticity to generate detailed E/I co-tuning have been focused on feedforward networks with distinct input currents which are virtually free of noise and cross-correlations that may disrupt the tuning process. However, cortical networks rarely exhibit such architectures and are typically characterized by high levels of noise and recurrent connectivity. Our study examines the ability of a standard inhibitory plasticity rule [3], which has been shown to produce E/I co-tuning in feedforward networks, to tune inhibitory connections that match static tuned excitatory connectivity under realistic levels of noise and recurrent connections in the presynaptic neurons.
We find that noise and unstructured recurrent connectivity can significantly reduce the ability of inhibitory synaptic plasticity to produce E/I co-tuning (Fig. 1). We trace this phenomenon to the covariance structure of inputs which affects the loss function of the inhibitory learning rule. We make a theoretical investigation of a reduced rate neuron model, and then compare predictions from it with the behaviour of a large complex network of LIF neurons. We subsequently investigate which types of pre-synaptic connectivity can restore the desired input statistics for E/I tuning to emerge. We find that clustering of the pre-synaptic connections (increased connectivity within each input group) can create the appropriate input statistics for E/I tuning to emerge even in the presence of strong pre-synaptic noise.
Our findings suggest that despite the negative effects that noise and recurrent connectivity can have on the ability of inhibitory plasticity to tune inhibitory connections, these effects can be effectively mitigated by the topology of the presynaptic network. Thus, we suggest that a combined effect of connectivity and plasticity allows E/I co-tuning to emerge in networks with biologically plausible levels of noise and realistic connectivity structures.
