Dopaminergic Contributions to Vocal Learning

Hoffmann, Lukas A.; Saravanan, Varun; Wood, Alynda N.; He, Li; Sober, Samuel J.

doi:10.1523/jneurosci.3883-15.2016

Cited by 83 publications

(137 citation statements)

References 62 publications

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“…For the predictor variables, we included our two behavioral measures (number of songs and bouts of non-vocal behaviors), and expression in Area X for each neural marker (CB 1 , FABP7, FABP5, FAAH, DAGLα). While, Area X may play a role in reinforcement related to vocal learning (e.g., Hoffman et al, 2016), it does not have a definitive role in reward processes comparable to other brain regions (e.g., PAG, POM, VTA; thus we would not predict a relationship between CPP and Area X mRNA expression, a prediction we confirmed below). However, Area X is critical for song learning (Sohrabji et al, 1990; Scharff and Nottebohm, 1991) and variability in song production (Leblois et al, 2010; Leblois and Perkel, 2012); therefore, we also conducted separate correlation analyses for each neural marker to examine the relationship between the number of songs produced and mRNA expression in Area X.…”

Section: Methodsmentioning

confidence: 69%

Song-associated reward correlates with endocannabinoid-related gene expression in male European starlings ( Sturnus vulgaris )

et al. 2017

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Vocal communication is required for successful social interactions in numerous species. During the breeding season, songbirds produce songs that are reinforced by behavioral consequences (e.g., copulation). However, some songbirds also produce songs not obviously directed at other individuals. The consequences maintaining or reinforcing these songs are less obvious and the neural mechanisms associated with undirected communication are not well-understood. Previous studies indicate that undirected singing is intrinsically rewarding and mediated by opioid or dopaminergic systems; however, endocannabinoids are also involved in regulating reward and singing behavior. We used a conditioned place preference paradigm to examine song-associated reward in European starlings and quantitative real-time PCR to measure expression of endocannabinoid-related neural markers (CB1, FABP7, FABP5, FAAH, DAGLα), in brain regions involved in social behavior, reward and motivation (ventral tegmental area [VTA], periaqueductal gray [PAG], and medial preoptic nucleus [POM]), and a song control region (Area X). Our results indicate that starlings producing high rates of song developed a conditioned place preference, suggesting that undirected song is associated with a positive affective state. We found a significant positive relationship between song-associated reward and CB1 receptors in VTA and a significant negative relationship between song-associated reward and CB1 in PAG. There was a significant positive relationship between reward and the cannabinoid transporter FABP7 in POM and a significant negative relationship between reward and FABP7 in PAG. In Area X, FABP5 and DAGLα correlated positively with singing. These results suggest a role for endocannabinoid signaling in vocal production and reward associated with undirected communication.

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Section: Methodsmentioning

confidence: 69%

Song-associated reward correlates with endocannabinoid-related gene expression in male European starlings ( Sturnus vulgaris )

et al. 2017

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“…As such, the tutor circuit must learn the mapping. Indeed, it is known that LMAN in the bird receives an indirect evaluation signal via Area X, which might be used to effect this learning (Andalman and Fee, 2009; Gadagkar et al, 2016; Hoffmann et al, 2016; Kubikova et al, 2010). One way in which this can be achieved is through a reinforcement paradigm.…”

Section: Resultsmentioning

confidence: 99%

Rules and mechanisms for efficient two-stage learning in neural circuits

Teşileanu

Ölveczky

Balasubramanian

2017

eLife

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Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ‘tutor’ circuits (e.g., LMAN) should match plasticity mechanisms in ‘student’ circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.DOI: http://dx.doi.org/10.7554/eLife.20944.001

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“…Signals encoding rendition-by-rendition variation in the FF of targeted syllables are potentially generated within Area X (Woolley et al, 2014) or relayed to Area X by inputs from the motor pathway (Charlesworth et al, 2012) or LMAN (Fee and Goldberg, 2011; Kao et al, 2005). Signals encoding outcomes – whether or not a given rendition escapes WN – plausibly derive from rich neuromodulatory inputs to the AFP, including from midbrain dopaminergic neurons (Gadagkar et al, 2016; Hoffmann et al, 2016). The association between contextual signals (HVC X activity) and appropriate motor-biasing AFP activity could then be mediated by plasticity at cortical-striatal (HVC X -X) synapses (Fee and Goldberg, 2011), as has been implicated for decision-making tasks in mammals (Xiong et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird

Tian

Brainard

2017

Neuron

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SUMMARY Motor skills depend on the reuse of individual gestures in multiple sequential contexts (e.g., a single phoneme in different words). Yet optimal performance requires that a given gesture be modified appropriately depending on the sequence in which it occurs. To investigate the neural architecture underlying such context-dependent modifications, we studied Bengalese finch song, a skill that, like speech, consists of variable sequences of “syllables.” We found that when birds are instructed to modify a syllable in one sequential context, learning generalizes across contexts; however, if unique instruction is provided in different contexts, learning is specific for each context. Using localized inactivation of a cortical-basal ganglia circuit specialized for song, we show this balance between generalization and specificity reflects a hierarchical organization of neural substrates. Primary motor circuitry encodes a “core” syllable representation that contributes to generalization, while top-down input from cortical-basal ganglia circuitry biases this representation to enable context-specific learning.

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Dopaminergic Contributions to Vocal Learning

Cited by 83 publications

References 62 publications

Song-associated reward correlates with endocannabinoid-related gene expression in male European starlings ( Sturnus vulgaris )

Song-associated reward correlates with endocannabinoid-related gene expression in male European starlings ( Sturnus vulgaris )

Rules and mechanisms for efficient two-stage learning in neural circuits

Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird

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