Common Principles in Functional Organization of VIP/Calretinin Cell-Driven Disinhibitory Circuits Across Cortical Areas.

In the brain, there is a vast diversity of different structures, circuitries, cell types, and cellular genetic expression profiles. While this large diversity can often occlude a clear understanding of how the brain works, careful analyses of analogous studies performed across different brain areas can hint at commonalities in neuronal organization. This in turn can yield a fundamental understanding of necessary circuitry components that are crucial for how information is processed across the brain. In this review, we outline recent in vivo and in vitro studies that have been performed in different cortical areas to characterize the vasoactive intestinal polypeptide (VIP)- and/or calretinin (CR)-expressing cells that specialize in inhibiting GABAergic interneurons. In doing so, we make the case that, across cortical structures, interneuron-specific cells commonly specialize in the synaptic disinhibition of excitatory neurons, which can ungate the integration and plasticity of external inputs onto excitatory neurons. In line with this, activation of interneuron- specific cells enhances animal performance across a variety of behavioral tasks that involve learning, memory formation, and sensory discrimination, and may represent a key target for therapeutic interventions under different pathological conditions. As such, interneuron-specific cells across different cortical structures are an essential network component for information processing and normal brain function.

Synaptic Mechanisms Underlying the Network State-Dependent Recruitment of VIP-Expressing Interneurons in the CA1 Hippocampus.

Disinhibition is a widespread circuit mechanism for information selection and transfer. In the hippocampus, disinhibition of principal cells is provided by the interneuron-specific interneurons that express the vasoactive intestinal polypeptide (VIP-IS) and innervate selectively inhibitory interneurons. By combining optophysiological experiments with computational models, we determined the impact of synaptic inputs onto the network state-dependent recruitment of VIP-IS cells. We found that VIP-IS cells fire spikes in response to both the Schaffer collateral and the temporoammonic pathway activation. Moreover, by integrating their intrinsic and synaptic properties into computational models, we predicted recruitment of these cells between the rising phase and peak of theta oscillation and during ripples. Two-photon Ca2+-imaging in awake mice supported in part the theoretical predictions, revealing a significant speed modulation of VIP-IS cells and their preferential albeit delayed recruitment during theta-run epochs, with estimated firing at the rising phase and peak of the theta cycle. However, it also uncovered that VIP-IS cells are not activated during ripples. Thus, given the preferential theta-modulated firing of VIP-IS cells in awake hippocampus, we postulate that these cells may be important for information gating during spatial navigation and memory encoding.

Moving beyond Type I and Type II neuron types.

In 1948, Hodgkin delineated different classes of axonal firing.  This has been mathematically translated allowing insight and understanding to emerge.  As such, the terminology of 'Type I' and 'Type II' neurons is commonplace in the Neuroscience literature today.  Theoretical insights have helped us realize that, for example, network synchronization depends on whether neurons are Type I or Type II.  Mathematical models are precise with analyses (considering Type I/II aspects), but experimentally, the distinction can be less clear.  On the other hand, experiments are becoming more sophisticated in terms of distinguishing and manipulating particular cell types but are limited in terms of being able to consider network aspects simultaneously.   Although there is much work going on mathematically and experimentally, in my opinion it is becoming common that models are either superficially linked with experiment or not described in enough detail to appreciate the biological context.  Overall, we all suffer in terms of impeding our understanding of brain networks and applying our understanding to neurological disease.  I suggest that more modelers become familiar with experimental details and that more experimentalists appreciate modeling assumptions. In other words, we need to move beyond our comfort zones.