Abstract
Unilateral medial forebrain bundle (MFB) stimulation is an extremely effective promoter of reinforcement learning irrespective of the conditioned cue's laterality. The effectiveness of unilateral MFB stimulation, which activates the mesolimbic pathway connecting the ventral tegmental area to the ventral striatum (vStr), is surprising considering that these fibers rarely cross to the contralateral hemisphere. Specifically, this type of biased fiber distribution entails the activation of brain structures that are primarily ipsilateral to the stimulated MFB, along with weak to negligible activation of the contralateral structures, thus impeding the formation of a cue-outcome association. To better understand the spread of activation of MFB stimulation across hemispheres, we studied whether unilateral MFB stimulation primarily activates the ipsilateral vStr or the vStr of both hemispheres. We simultaneously recorded neuronal activity in the vStr of both hemispheres in response to several sets of unilateral MFB stimulation in anesthetized and freely moving rats. Unilateral MFB stimulation evoked strong stimulus-dependent activation of vStr tonically active neurons (TANs), presumably the cholinergic interneurons, in both hemispheres. However, the TANs’ activation patterns and responsiveness depended on whether the stimulus was delivered ipsilaterally or contralaterally to the recorded neuron. These findings indicate that unilateral MFB stimulation effectively activates the vStr in both hemispheres in a stimulus-dependent manner which may serve as neuronal substrate for the formation of cue-outcome associations during reinforcement learning.
Original language | English |
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Pages (from-to) | 4499-4516 |
Number of pages | 18 |
Journal | European Journal of Neuroscience |
Volume | 52 |
Issue number | 11 |
DOIs | |
State | Published - Dec 2020 |
Bibliographical note
Publisher Copyright:© 2020 Federation of European Neuroscience Societies and John Wiley & Sons Ltd
Keywords
- chronic recording
- electrophysiology
- extracellular activity
- reinforcement learning
- reward system