Neuron

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Parvalbumin Interneurons: All Forest, No Trees Joshua T. Trachtenberg1,* 1Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA 90095, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.neuron.2015.06.041

There has been a surge of interest in how inhibitory neurons influence the output of local circuits in the brain. In this issue of Neuron, Scholl et al. (2015) provide a compelling argument for what one class of inhibitory neurons actually does. What is cortical inhibition good for? Recently, the answer to this question is remarkably similar to one of those questions on ‘‘Family Feud,’’ where there’s a survey of opinions and the top 10 answers are all correct. Fortunately, the results from Scholl et al. (2015) in this issue of Neuron add enough new data to tip the scales in favor of one simple answer. In the neocortex, inhibitory neurons are a fairly small minority, comprising roughly 20% of all cortical neurons. Historically, this has made it difficult to find these cells and to record from them in the intact brain. Even more maddening, this small population is subdivided, very roughly, into three groups (and more likely a dozen), based on their interaction with excitatory neurons (Kawaguchi and Kubota, 1997). Parvalbumin (PV)-expressing interneurons fire rapid barrages of action potentials, and are accordingly named ‘‘fast-spiking’’ interneurons. These innervate and inhibit the cell bodies of excitatory neurons. Somatostatin (SOM)-ex-

pressing interneurons have firing rates that are more on par with the local excitatory neurons, and are thus often referred to as ‘‘regular-spiking.’’ These innervate and inhibit the dendrites of pyramidal neurons. In the primary visual cortex, where these cells have been most extensively studied, both groups receive strong excitatory input. The final group of inhibitory neurons is characterized by their expression of vasoactive intestinal polypeptide (VIP). These cells appear to inhibit other inhibitory neurons and to receive neuromodulatory input from the brainstem, and are thought to regulate brain states during arousal (Hangya et al., 2014; Pfeffer et al., 2013). Over the past half-decade or so, a number of mouse lines have been developed in which expression of the gene encoding the bacteriophage tyrosine recombinase enzyme, Cre recombinase, is directed by PV, SOM, or VIP promoter/ enhancer elements (Pfeffer et al., 2013). These mice have given us the ability to

finally visualize and manipulate each inhibitory class. Scholl et al. (2015) provide new data supporting a view that the computational heavy lifting in the cortex is done by the excitatory neurons, whereas PV cells seem to leave a lot of potentially very useful information on the table. Rather than integrating specific cortical inputs to create complex receptive fields that extract higher-order information from the visual scene, as excitatory neurons do (Cossell et al., 2015), PV cells simply integrate inputs from the local network without specificity (Figure 1). Being uniformly connected to the local excitatory neurons makes PV cells well suited to a different role—monitoring and regulating the total activity of the local network, also known as gain control. To reach this conclusion, they imaged the activity of large numbers of excitatory and PV neurons in mouse primary visual cortex using two-photon excitation of the calcium indicator Oregon Green

Neuron 87, July 15, 2015 ª2015 Elsevier Inc. 247

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BAPTA. PV cells in these mice classes. The emergence of selectively expressed the red transgenic animals, coupled fluorescent protein tdTomato, with the ability to express prowhich was used to identify teins in specific cell types, is these cells and separate their revealing the underlying rules signals. Many earlier studies of circuit connectivity, both found that PV cells are less at the functional and anatomFigure 1. PV Cell-Mediated Gain Control and Learning interested in the particular ical levels. Instead of playing (Left) Pyramidal neurons nonlinearly integrate broad synaptic input to proorientation of a visual stimulus a game of Jeopardy, where duce sharply tuned spiking output. (Middle) PV interneurons simply sum their inputs linearly. (Right) The resulting broad inhibition acts to alter firing rates of than are excitatory neurons. answers are questions, we pyramidal neurons, which underlies learning. This response promiscuity are moving toward Wheel of could be restricted to orientaFortune, where the individual tion selectivity, or it could be a general that by simply integrating information letters, or cortical motifs, are being property of PV cells. Scholl et al. (2015) from nearby neurons, PV cells are taking uncovered. examined this by measuring ocular domi- a moment-by-moment pulse of network nance and binocular disparity in PV and activity and acting on this information to REFERENCES excitatory neurons. Because excitatory modulate cortical response gain (Atallah neurons in the binocular zone of visual et al., 2012; Wilson et al., 2012). That is, Anderson, J.S., Carandini, M., and Ferster, D. (2000). J. Neurophysiol. 84, 909–926. cortex receive inputs from both eyes, PV cells are not altering the computations they can be sensitive to binocular dispar- performed by local excitatory neurons, Atallah, B.V., Bruns, W., Carandini, M., and Scanziani, M. (2012). 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Neuron 87, this issue, For years our understanding of inhibi- 424–436. et al., 2012; Liu et al., 2011). Instead, the authors argue, as others have done tory neocortical circuitry has been limited Wilson, N.R., Runyan, C.A., Wang, F.L., and Sur, (Bock et al., 2011; Kerlin et al., 2010), by our ability to access specific cell sub- M. (2012). Nature 488, 343–348. 248 Neuron 87, July 15, 2015 ª2015 Elsevier Inc.

Parvalbumin Interneurons: All Forest, No Trees.

There has been a surge of interest in how inhibitory neurons influence the output of local circuits in the brain. In this issue of Neuron, Scholl et a...
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