Abstract
Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. The generation of novelty responses does not depend on the periodicity but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make experimentally testable predictions.
Highlights
In an ever-changing environment, animals must rapidly extract behaviorally useful information from sensory stimuli
To understand if and how plastic inhibitory circuits could explain the emergence of novelty responses, we built a biologically-plausible spiking neuronal network model of recurrently connected excitatory and inhibitory neurons based on recent experimental findings on tuning, connectivity, and inhibitory and excitatory spike-timing-dependent synaptic plasticity (STDP) in the cortex (Methods) (Pfister and Gerstner, 2006; Vogels et al, 2011; Fiete et al, 2010; Sjöström et al, 2001; D’amour and Froemke, 2015)
Inhibitory plasticity and tuned inhibitory neurons support stimulus-specific adaptation we investigated whether inhibitory plasticity of tuned inhibitory neurons support additional computational capabilities beyond the generation of novelty responses and adaptation of responses to repeated stimuli on multiple timescales
Summary
In an ever-changing environment, animals must rapidly extract behaviorally useful information from sensory stimuli. Appropriate behavioral adjustments to unexpected changes in stimulus statistics are fundamental for the survival of an animal. Repeated or predictable stimuli do not provide new meaningful information. One should expect that responses to repeated stimuli are suppressed – a phenomenon postulated by the framework of predictive coding (Clark, 2013; Spratling, 2017). Recent experiments have demonstrated that sensory circuits across different modalities can encode a sequence or expectation violation and can detect novelty (Keller et al, 2012; Natan et al, 2015; Zmarz and Keller, 2016; Hamm and Yuste, 2016; Homann et al, 2017). The underlying neuronal and circuit mechanisms behind expectation violation and novelty detection, remain elusive
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