Statistical learning of transition patterns in the songbird auditory forebrain

Dong, Mingwen; Vicario, David S.

doi:10.1038/s41598-020-64671-4

Cited by 4 publications

(2 citation statements)

References 48 publications

(82 reference statements)

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“…We did not test whether statistical learning for pain is automatic but, based on previous work, we expect it to happen spontaneously, without requiring the need to explicitly report stimulus probabilities. Indeed, statistical learning of visual or auditory inputs has been reported in songbirds, primates and newborns [28][29][30][31][32] . Furthermore, previous studies have shown implicit expectation effects from sequences of stimuli in humans [33][34][35] .…”

Section: Discussionmentioning

confidence: 99%

Computational and neural mechanisms of statistical pain learning

2022

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Pain invariably changes over time. These fluctuations contain statistical regularities which, in theory, could be learned by the brain to generate expectations and control responses. We demonstrate that humans learn to extract these regularities and explicitly predict the likelihood of forthcoming pain intensities in a manner consistent with optimal Bayesian inference with dynamic update of beliefs. Healthy participants received probabilistic, volatile sequences of low and high-intensity electrical stimuli to the hand during brain fMRI. The inferred frequency of pain correlated with activity in sensorimotor cortical regions and dorsal striatum, whereas the uncertainty of these inferences was encoded in the right superior parietal cortex. Unexpected changes in stimulus frequencies drove the update of internal models by engaging premotor, prefrontal and posterior parietal regions. This study extends our understanding of sensory processing of pain to include the generation of Bayesian internal models of the temporal statistics of pain.

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Section: Discussionmentioning

confidence: 99%

Computational and neural mechanisms of statistical pain learning

2022

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“…Numerous studies have highlighted the importance of the caudomedial nidopallium (NCM), a higher order auditory processing area, in sensory learning in songbirds (12,13,(24)(25)(26)(27)(28)(29)(30)(31)(32)(33). For example, song learning leads to a subset of NCM neurons becoming selectively tuned to the tutor song (34), and manipulations of signaling cascades in NCM during developmental song learning affect tutor song imitation (35,36).…”

Section: Introductionmentioning

confidence: 99%

Norepinephrine in the avian auditory cortex enhances developmental song learning

Sakata

2021

Journal of Neurophysiology

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Sensory learning during critical periods in development has lasting effects on behavior. Neuromodulators like dopamine and norepinephrine (NE) have been implicated in various forms of sensory learning, but little is known about their contribution to sensory learning during critical periods. Songbirds like the zebra finch communicate with each other using vocal signals (e.g., songs) that are learned during a critical period in development, and the first crucial step in song learning is memorizing the sound of an adult conspecific's (tutor's) song. Here we analyzed the extent to which NE modulates the auditory learning of a tutor's song and the fidelity of song imitation. Specifically, we paired infusions of NE or vehicle into the caudomedial nidopallium (NCM) with brief epochs of song tutoring. We analyzed the effect of NE in juvenile zebra finches that had or had not previously been exposed to song. Regardless of previous exposure to song, juveniles that received NE infusions into NCM during song tutoring produced songs that were more acoustically similar to the tutor song and that incorporated more elements of the tutor song than juveniles with control infusions. These data support the notion that NE can regulate the formation of sensory memories that shape the development of vocal behaviors that are used throughout an organism's life.

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Estrogens rapidly shape synaptic and intrinsic properties to regulate the temporal precision of songbird auditory neurons

Scarpa

Starrett

et al. 2022

Cerebral Cortex

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Sensory neurons parse millisecond-variant sound streams like birdsong and speech with exquisite precision. The auditory pallial cortex of vocal learners like humans and songbirds contains an unconventional neuromodulatory system: neuronal expression of the estrogen synthesis enzyme aromatase. Local forebrain neuroestrogens fluctuate when songbirds hear a song, and subsequently modulate bursting, gain, and temporal coding properties of auditory neurons. However, the way neuroestrogens shape intrinsic and synaptic properties of sensory neurons remains unknown. Here, using a combination of whole-cell patch clamp electrophysiology and calcium imaging, we investigate estrogenic neuromodulation of auditory neurons in a region resembling mammalian auditory association cortex. We found that estradiol rapidly enhances the temporal precision of neuronal firing via a membrane-bound G-protein coupled receptor and that estradiol rapidly suppresses inhibitory synaptic currents while sparing excitation. Notably, the rapid suppression of intrinsic excitability by estradiol was predicted by membrane input resistance and was observed in both males and females. These findings were corroborated by analysis of in vivo electrophysiology recordings, in which local estrogen synthesis blockade caused acute disruption of the temporal correlation of song-evoked firing patterns. Therefore, on a modulatory timescale, neuroestrogens alter intrinsic cellular properties and inhibitory neurotransmitter release to regulate the temporal precision of higher-order sensory neurons.

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Statistical learning of transition patterns in the songbird auditory forebrain

Cited by 4 publications

References 48 publications

Computational and neural mechanisms of statistical pain learning

Computational and neural mechanisms of statistical pain learning

Norepinephrine in the avian auditory cortex enhances developmental song learning

Estrogens rapidly shape synaptic and intrinsic properties to regulate the temporal precision of songbird auditory neurons

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