Lateral habenula projections to dopamine and GABA neurons in the rat ventral tegmental area.

Abstract

Ventral tegmental area (VTA) dopamine (DA) neurons and their forebrain projections are critically involved in reward processing and cognitive functions. Descending projections from the lateral habenula (LHb) play a central role in inhibiting DA cell activity in response to the absence of expected rewards. As LHb efferents are reportedly glutamatergic, their ability to inhibit DA cells would theoretically require a disynaptic connection involving VTA GABA neurons and their local collateral inputs to DA cells. We therefore used anterograde tract-tracing from the LHb to investigate the relative selectivity of LHb synapses onto GABA versus DA VTA neurons. LHb axons were visualized using immunoperoxidase, and DA and GABA cells were marked by immunogold-silver labeling for tyrosine hydroxylase (TH) or GABA, respectively. By ultrastructural analysis, 16% of LHb axons were observed to form synaptic contacts in the VTA, and most of these were of an intermediate morphological type that did not exhibit definitive asymmetric or symmetric character. LHb axons synaptically targeted TH- and GABA-labeled dendrites to a comparable extent (45 and 52% observed incidence, respectively). Pre-embedding immunogold labeling for the vesicular glutamate transporter type 2 and post-embedding immunogold staining for GABA confirmed that approximately 85% of LHb terminals were glutamatergic and not GABAergic. These results suggest that the robust inhibition of DA cells evoked by the LHb is unlikely to arise from a selective innervation of VTA GABA neurons. Moreover, the LHb may mediate a direct excitation of DA cells that is over-ridden by indirect inhibition originating from an extrinsic source.

DOI: 10.1111/j.1460-9568.2009.06924.x

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@article{Omelchenko2009LateralHP, title={Lateral habenula projections to dopamine and GABA neurons in the rat ventral tegmental area.}, author={Natalia Omelchenko and Roland Bell and Susan R . Sesack}, journal={The European journal of neuroscience}, year={2009}, volume={30 7}, pages={1239-50} }