Frontal Cortex Activation Causes Rapid Plasticity of Auditory Cortical Processing

Winkowski, Daniel E.; Bandyopadhyay, Sambaran; Shamma, Shihab A.; Kanold, Patrick O.

doi:10.1523/jneurosci.0180-13.2013

Cited by 71 publications

(78 citation statements)

References 53 publications

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“…A commonly used procedure to assess the magnitude of top-down mechanisms is to compare neural responsiveness during two different states of behavioral engagement (37,(44)(45)(46)(47)(48)(49). Specifically, top-down inputs are thought to actively modulate ACx responses during task performance (or "engagement") but not during nontask ("disengaged") listening sessions (50,51). Thus, the difference between engaged and disengaged sensitivity is a proxy for the strength of a top-down mechanism.…”

Section: Significancementioning

confidence: 99%

“…For our purposes, top-down refers to the functional influence of a higher-order brain region on neural activity in ACx, brought about by task engagement. Several plausible candidate regions may mediate this top-down effect, either in isolation or in concert with one another, including frontal cortex (50,51), nucleus basalis (73)(74)(75), locus coeruleus (76), ventral tegmental area (77,78), and multisensory cortex (17).…”

Section: Significancementioning

confidence: 99%

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Top-down modulation of sensory cortex gates perceptual learning

Caras

Sanes

2017

Proc. Natl. Acad. Sci. U.S.A.

104

108

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Practice sharpens our perceptual judgments, a process known as perceptual learning. Although several brain regions and neural mechanisms have been proposed to support perceptual learning, formal tests of causality are lacking. Furthermore, the temporal relationship between neural and behavioral plasticity remains uncertain. To address these issues, we recorded the activity of auditory cortical neurons as gerbils trained on a sound detection task. Training led to improvements in cortical and behavioral sensitivity that were closely matched in terms of magnitude and time course. Surprisingly, the degree of neural improvement was behaviorally gated. During task performance, cortical improvements were large and predicted behavioral outcomes. In contrast, during nontask listening sessions, cortical improvements were weak and uncorrelated with perceptual performance. Targeted reduction of auditory cortical activity during training diminished perceptual learning while leaving psychometric performance largely unaffected. Collectively, our findings suggest that training facilitates perceptual learning by strengthening both bottom-up sensory encoding and top-down modulation of auditory cortex.broad range of sensory skills improve with practice during perceptual learning (PL), including language acquisition (1-3), musical abilities (4), and recognition of emotions (5). The neural bases for such perceptual improvement may vary widely. For example, training-based changes in neural activity have been identified in a number of brain regions, including early (6-13) and late (14, 15) sensory cortices, multisensory regions (16, 17), and downstream decision-making areas (18). Similarly, several neural mechanisms have been proposed, such as enhanced signal representation (19), reduction of external (20, 21) or internal (22, 23) noise, and improvement in sensory readout or decision making (13,18,24,25).The apparent divergence of loci and mechanisms associated with PL could be due, in part, to limitations of experimental design. For example, some neural changes associated with PL are transient (26-29), making it necessary to monitor neural activity throughout the duration of perceptual training, rather than making comparisons only after PL is complete (6-12, 14-16, 30). For similar reasons, it is critical to block the function of a specific candidate brain region during training to determine whether it plays a causal role in PL. Although some reports show that manipulating brain activity can influence PL (28,(31)(32)(33)(34), there are no loss-of-function experiments to determine whether a particular region is required for behavioral improvement.To address these unresolved issues, we recorded from auditory cortex (ACx) as animals improved on an auditory detection task and, in separate experiments, blocked ACx activity during the period of perceptual training. We found that neural and behavioral sensitivity improved in a nearly identical manner over the course of training, in terms of both absolute magnitude and kinetics. Furthermore,...

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Section: Significancementioning

confidence: 99%

Section: Significancementioning

confidence: 99%

Top-down modulation of sensory cortex gates perceptual learning

Caras

Sanes

2017

Proc. Natl. Acad. Sci. U.S.A.

104

108

View full text Add to dashboard Cite

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“…(a ) Tonotopic best frequency (BF) map reconstructed from ~50 extracellular multiunit recording sites from the middle layers of mouse AI, each spaced ~100 μm apart (data from [18]) In addition to receiving heavy feedforward sensory input from the medial geniculate body, AI tonotopic organization is influenced by long-range neuromodulatory inputs such as dopaminergic (DA) inputs from the ventral tegmental area [141], noradrenergic (NA) inputs from locus coeruleus [142], serotinergic inputs from the dorsal raphe (5-HT) [143], glutamatergic inputs from the frontal cortex [144], and cholinergic (ACh) input from nucleus basalis [49]. Of these systems, retuning of auditory response properties by cholingeric modulation is by far the best understood.…”

Section: Figurementioning

confidence: 99%

Auditory map plasticity: diversity in causes and consequences

Schreiner

Polley

2014

Current Opinion in Neurobiology

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Auditory cortical maps have been a long-standing focus of studies that assess the expression, mechanisms, and consequences of sensory plasticity. Here we discuss recent progress in understanding how auditory experience transforms spatially organized sound representations at higher levels of the central auditory pathways. New insights into the mechanisms underlying map changes have been achieved and more refined interpretations of various map plasticity effects and their consequences in terms of behavioral corollaries and learning as well as other cognitive aspects have been offered. The systematic organizational principles of cortical sound processing remains a key-aspect in studying and interpreting the role of plasticity in hearing.

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“…First, this result provides insight into the functional role of structural connections between the OFC and superior temporal gyrus previously reported in monkeys (Barbas et al, 1999; Petrides & Pandya, 2007). Another study in mice also showed OFC stimulation modulates sensory-evoked activity in the primary auditory cortex (Winkowski, Bandyopadhyay, Shamma, & Kanold, 2013). These studies converge on the OFC’s capacity for top-down sensory modulation of the auditory cortex across species.…”

mentioning

confidence: 96%