The basolateral amygdala and lateral hypothalamus bias learning towards motivationally significant events

Hoang, Ivy B; Sharpe, Melissa J

doi:10.1016/j.cobeha.2021.04.014

Cited by 13 publications

(11 citation statements)

References 62 publications

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“…Future research is needed to understand how the LH-VTA circuit integrates with the wider dopaminergic network. For example, we have previously hypothesized that the LH-VTA circuit forms a wider with the basolateral amygdala 109 . Here, we argue that the basolateral amygdala provides the LH with sensory-specific information about motivationally significant events relevant to the current circumstance 109 .…”

Section: Discussionmentioning

confidence: 99%

A novel hypothalamic-midbrain circuit for model-based learning

Hoang

Munier

Verghese

et al. 2023

Preprint

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Behavior is often dichotomized into model-free and model-based systems1, 2. Model-free behavior prioritizes associations that have high value, regardless of the specific consequence or circumstance. In contrast, model-based behavior involves considering all possible outcomes to produce behavior that best fits the current circumstance. We typically exhibit a mixture of these behaviors so we can trade-off efficiency and flexibility. However, substance use disorder shifts behavior more strongly towards model-free systems, which produces a difficulty abstaining from drug-seeking due to an inability to withhold making the model-free high-value response3–10. The lateral hypothalamus (LH) is implicated in substance use disorder11–17and we have demonstrated that this region is critical to Pavlovian cue-reward learning18, 19. However, it is unknown whether learning occurring in LH is model-free or model-based, where the necessary teaching signal comes from to facilitate learning in LH, and whether this is relevant for learning deficits that drive substance use disorder. Here, we reveal that learning occurring in the LH is model-based. Further, we confirm the existence of an understudied projection extending from dopamine neurons in the ventral tegmental area (VTA) to the LH and demonstrate that this input underlies model-based learning in LH. Finally, we examine the impact of methamphetamine self-administration on LH-dependent model-based processes. These experiments reveal that a history of methamphetamine administration enhances the model-based control that Pavlovian cues have over decision-making, which was accompanied by a bidirectional strengthening of the LH to VTA circuit. Together, this work reveals a novel bidirectional circuit that underlies model-based learning and is relevant to the behavioral and cognitive changes that arise with substance use disorders. This circuit represents a new addition to models of addiction, which focus on instrumental components of drug addiction and increases in model-free habits after drug exposure3–10.

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Section: Discussionmentioning

confidence: 99%

A novel hypothalamic-midbrain circuit for model-based learning

Hoang

Munier

Verghese

et al. 2023

Preprint

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“…Using monosynaptic rabies viral tracing of inputs to VGluT2+VGaT+ neurons, we found that most synaptic inputs arose from subcortical structures implicated in motor actions, outcome valuation, and threat responding, such as superior colliculus, lateral hypothalamus, lateral habenula, periaqueductal gray, dorsal raphe, substantia innominata/ventral pallidum, locally within the VTA, and parabrachial nucleus 6,19,[38][39][40][41][42][43][44][45][46][47][48][49][50][51] . These circuits likely contribute to the high sensitivity of VTA VGluT2+VGaT+ neurons toward stressful stimuli that result in social and exploratory deficits in mice 52 .…”

Section: Discussionmentioning

confidence: 99%

Monosynaptic inputs to ventral tegmental area glutamate and GABA co-transmitting neurons

Prevost

Phillips

Lauridsen

et al. 2023

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A unique population of ventral tegmental area (VTA) neurons co-transmits glutamate and GABA as well as functionally signals rewarding and aversive outcomes. However, the circuit inputs to VTA VGluT2+VGaT+ neurons are unknown, limiting our understanding of the functional capabilities of these neurons. To identify the inputs to VTA VGluT2+VGaT+ neurons, we coupled monosynaptic rabies tracing with intersectional genetic targeting of VTA VGluT2+VGaT+ neurons in mice. We found that VTA VGluT2+VGaT+ neurons received diverse brain-wide inputs. The largest numbers of monosynaptic inputs to VTA VGluT2+VGaT+ neurons were from superior colliculus, lateral hypothalamus, midbrain reticular nucleus, and periaqueductal gray, whereas the densest inputs relative to brain region volume were from dorsal raphe nucleus, lateral habenula, and ventral tegmental area. Based on these and prior data, we hypothesized that lateral hypothalamus and superior colliculus inputs were glutamatergic neurons. Optical activation of glutamatergic lateral hypothalamus neurons robustly activated VTA VGluT2+VGaT+ neurons regardless of stimulation frequency and resulted in flee-like ambulatory behavior. In contrast, optical activation of glutamatergic superior colliculus neurons activated VTA VGluT2+VGaT+ neurons for a brief period of time at high stimulation frequency and resulted in head rotation and arrested ambulatory behavior (freezing). For both pathways, behaviors induced by stimulation were uncorrelated with VTA VGluT2+VGaT+ neuron activity, suggesting that VGluT2+VGaT+ neurons are integrators of signals related to aversive outcomes but not of aversion-induced behavioral kinematics. We interpret these results such that VTA VGluT2+VGaT+ neurons may integrate diverse inputs related to the detection and processing of motivationally-salient outcomes.

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“…The BLA encodes the value of the cues during learning (Cole et al, 2013;Esber and Holland, 2014;Parkes and Balleine, 2013;Piette et al, 2012;Schoenbaum et al, 1999;Tye and Janak, 2007;Uwano et al, 1995) and is involved in appetitive cue discrimination (Ambroggi et al, 2008;Ishikawa et al, 2008) and reversal learning (Churchwell et al, 2009). However, several studies have shown the BLA may not be critical for initial acquisition of cue value learning (Balleine et al, 2003;Corbit and Balleine, 2005;Hatfield et al, 1996;Holland et al, 2002;Parkinson et al, 2000), but it is critical to encode and assess the representation of the learned associations to alter subsequent behavioral motivation and learning (Blundell et al, 2001;Corbit and Balleine, 2005;Coutureau et al, 2009;Everitt et al, 2003;Galarce et al, 2010;Hatfield et al, 1996;Holland et al, 2002;Holland and Petrovich, 2005;Johnson et al, 2009;Ostlund and Balleine, 2008;Petrovich, 2013;Setlow et al, 2002;Tye and Janak, 2007;Wassum and Izquierdo, 2015;Hoang and Sharpe, 2021;Fisher et al, 2020). This suggests a specific role for the BLA in reward value representation when appetitive learning is altered, in agreement with the current findings.…”

Section: Discussionmentioning

confidence: 99%

“…The basolateral nucleus of the amygdala (BLA) is a critical forebrain region necessary for associative conditioning and is an early processor of appetitive learning (Cole et al, 2013;Piette et al, 2012). The BLA is critically involved in appropriate behavioral responding when the values of learned appetitive cues are changed (Corbit and Balleine, 2005;Nomura et al, 2004;Schoenbaum et al, 1999;Tye et al, 2010;Fisher et al, 2020) or additional cues are incorporated to update the value of learned appetitive cues (Blundell et al, 2001;Everitt et al, 2003;Hatfield et al, 1996;Holland et al, 2002Holland et al, , 2001Holland and Petrovich, 2005;Petrovich, 2013;Setlow et al, 2002;Wassum and Izquierdo, 2015;Hoang and Sharpe, 2021). In vivo recording studies have shown that BLA neurons respond to appetitive cues, but then change their response profiles when cue outcomes are reversed (Schoenbaum et al, 1999) and when the reward is omitted (Tye et al, 2010).…”

Section: Introductionmentioning

confidence: 99%