Synaptic potentiation onto habenula neurons in the learned helplessness model of depression

Abstract

The cellular basis of depressive disorders is poorly understood1. Recent studies in monkeys indicate that neurons in the lateral habenula (LHb), a nucleus that mediates communication between forebrain and midbrain structures, can increase their activity when an animal fails to receive an expected positive reward or receives a stimulus that predicts aversive conditions (i.e. disappointment or anticipation of a negative outcome)2, 3, 4. LHb neurons project to and modulate dopamine-rich regions such as the ventral-tegmental area (VTA)2, 5 that control reward-seeking behavior6 and participate in depressive disorders7. Here we show in two learned helplessness models of depression that excitatory synapses onto LHb neurons projecting to the VTA are potentiated. Synaptic potentiation correlates with an animal’s helplessness behavior and is due to an enhanced presynaptic release probability. Depleting transmitter release by repeated electrical stimulation of LHb afferents, using a protocol that can be effective on depressed patients8, 9, dramatically suppresses synaptic drive onto VTA-projecting LHb neurons in brain slices and can significantly reduce learned helplessness behavior in rats. Our results indicate that increased presynaptic action onto LHb neurons contributes to the rodent learned helplessness model of depression.

Circuits, Cells, and Synapses: Toward a New Target for Deep Brain Stimulation in Depression

“…The time course for the remission after initiating stimulation is slow, weeks for full remission, suggesting that structural changes underlie this effect. High frequency and high voltage stimulation inhibit l. habenula slice activity (Li et al, 2011) supporting the concept that inhibition occurs through DBS and this may well be the mechanism through which DBS acts (Figure 1).…”

“…It also depresses 5HT signals (Wang and Aghajanian, 1997), which feed back further increasing l. habenular activity. The l. habenula receives strong inputs from both the limbic system, through the basal nucleus of the stria terminalis, which carries information from the amygdala related to anxiety and from the mPFC, which may be related to the cognitive aspects of depression (Li et al, 2011) and sends its output to the midbrain aminergic nuclei. Because it appears the l. habenula functions as a control center that regulates the reward center, modulating cortical, and limbic areas, it might be an ideal target for deep brain stimulation in cases of intractable, treatment-resistant depression.…”

“…The l. habenula controls the midbrain monoaminergic nuclei, whose output pathways interact with each other, as well as providing strong modulatory control of limbic and cortical areas. Recently understanding of how the dopamine system is regulated by the l. habenula in normal (Matsumoto and Hikosaka, 2009) and affectively disturbed states (Li et al, 2011) has been investigated. Over activity in the l. habenula is seen in both the learned helplessness model (Li et al, 2011) and in patients who express depressive symptoms following tryptophan depletion (Roiser et al, 2009).…”

“…Recently understanding of how the dopamine system is regulated by the l. habenula in normal (Matsumoto and Hikosaka, 2009) and affectively disturbed states (Li et al, 2011) has been investigated. Over activity in the l. habenula is seen in both the learned helplessness model (Li et al, 2011) and in patients who express depressive symptoms following tryptophan depletion (Roiser et al, 2009). This over activity causes decreased dopaminergic stimuation, suppressing reward signals (Matsumoto and Hikosaka, 2009).…”

The impact of hemodynamic variability and signal mixing on the identifiability of effective connectivity structures in BOLD fMRI

“…Over the past decade, multiple generative models have been proposed in the context of the DCM (Friston, Kahan, Biswal, & Razi, 2011; Friston et al., 2003; Havlicek et al., 2015; Kiebel, Kloppel, Weiskopf, & Friston, 2007; Li et al., 2011; Marreiros, Kiebel, & Friston, 2008; Seth, Chorley, & Barnett, 2013; Smith et al., 2011; Stephan, Weiskopf, Drysdale, Robinson, & Friston, 2007; Stephan et al., 2008). In this study, we chose the original, single‐node per region DCM (Friston et al., 2003; Smith et al., 2011).…”