Behavioral consequences of GABAergic neuronal diversity
Section snippets
Hippocampus
The composition of inhibitory interneurons in neural networks has been most extensively studied in hippocampal area CA1 – considered to be an architecturally simplified cortical circuit. One approach to strictly define cell classes without genetic tools is to label recorded interneurons with dyes, then stain for proteins expressed by the recorded cell. This technique has been used in freely-moving rats to show the firing of soma-targeting basket cells is more sensitive to behavioral state than
The influence of disinhibition
Although these novel techniques give the experimenter unparalleled access to distinct cell types (eg. PV+ interneurons), this must not be mistaken for access to specific synapses (eg. PV-to-PC connections). Interneurons are densely interconnected, both between and within types (Figure 2a,b); such disinhibition may have important consequences for interpreting the effects of manipulating specific cell types [46].
For instance, subpopulations of PV+ soma-targeting and SOM+ dendrite-targeting
Considerations for studying dendritic inhibition
Dendrites can perform supra-linear synaptic integration under certain conditions [59], which can disproportionately influence PC output by driving burst spikes [60]. Consequently, the effects of manipulating dendritic inhibition are highly sensitive to the state of the animal. Dendritic activity in PCs is greatly reduced in anesthetized animals [61] and even in awake animals not actively engaged in a task [42•, 62], suggesting PCs will be driven by synaptic integration at the soma/axon initial
Future directions
The pioneering studies reviewed here are a first step towards understanding the functional roles of inhibitory interneurons in behaviors dependent on the hippocampus and neocortex. To move forwards, investigators must be able to read-out the activity of defined interneurons during behavior, and then selectively perturb this activity during the behaviour – ideally while recording from PCs. By performing complementary experiments in multiple interneuron types, investigators can narrowly define
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
M.L.-B. is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Postgraduate Scholarship. A.L. is supported by the Searle, McKnight and Human Frontiers Science Program Grants.
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2022, NeuroscienceCitation Excerpt :In addition, these neurons form inhibitory synapses onto the somas and axonal initial segments of PNs to powerfully modulate the excitatory network activity (Cruikshank et al., 2010; Moore and Wehr, 2013; Kubota et al., 2016; Moore et al., 2018). PV+ neurons are implicated in neuronal oscillation/synchrony, neural plasticity, learning and memory, sensory perception, and social, cognitive and emotional behaviors (Hashimoto et al., 2003; Spencer et al., 2004; Gogolla et al., 2009; Carlson et al., 2011; Wang et al., 2011; Lewis et al., 2012; Fung et al., 2014; Lovett-Barron and Losonczy, 2014; Hijazi et al., 2020). PV expression is developmentally regulated, with its expression level increasing during early development and decreasing during aging (Endo et al., 1985; Ueno et al., 2018).
Cholinergic boutons are closely associated with excitatory cells and four subtypes of inhibitory cells in the inferior colliculus
2021, Journal of Chemical NeuroanatomyPotential roles of Glucagon-like peptide-1 and its analogues in cognitive impairment associated with type 2 diabetes mellitus
2020, Mechanisms of Ageing and DevelopmentDistinct roles of parvalbumin- and somatostatin-expressing neurons in flexible representation of task variables in the prefrontal cortex
2020, Progress in NeurobiologyCitation Excerpt :Although inhibitory interneurons are a minor population, they exert powerful influences on diverse aspects of neural network operations (Buzsaki and Chrobak, 1995; Isaacson and Scanziani, 2011; Karnani et al., 2016; Letzkus et al., 2015; Lovett-Barron et al., 2012; Pouille and Scanziani, 2001; Wehr and Zador, 2003). Because numerous studies have suggested distinct roles of parvalbumin (PV)- and somatostatin (SST)-expressing neurons—two major subtypes of inhibitory interneurons in the cortex (Kepecs and Fishell, 2014; Rudy et al., 2011)—in diverse cortical processes (Hangya et al., 2014; Hu et al., 2014; Kepecs and Fishell, 2014; Lovett-Barron and Losonczy, 2014; Petersen and Crochet, 2013; Roux and Buzsaki, 2015), we focused on comparing activity patterns and inactivation effects of PV and SST neurons using an optogenetic approach. We found differences in discharge characteristics and inactivation effects related to the processing of expected and actual outcome signals between PV and SST neurons.
Learning-Related Plasticity in Dendrite-Targeting Layer 1 Interneurons
2018, NeuronCitation Excerpt :In turn, this suggests that the activity of L1 NDNF-INs may strongly be governed by internally generated signals such as those occurring during memory expression. In addition to excitation, inhibitory input from other INs can dominantly shape the activity and function of different IN types in cortical circuits (Kepecs and Fishell, 2014; Letzkus et al., 2015; Lovett-Barron and Losonczy, 2014; Overstreet-Wadiche and McBain, 2015; Wester and McBain, 2014). To determine the local inhibitory inputs to L1 NDNF-INs, we crossed Cre lines for SST, VIP, and PV (Hippenmeyer et al., 2005; Taniguchi et al., 2011) to mice expressing EGFP under the Ndnf promoter (Figures 5A, S1E, S1I, and S1J; Gong et al., 2003).