Auditory cortex plays an important role in the processing of complex sounds e.g., vocal communication sounds and human speech. Cortical organization is altered by deafness and cortical plasticity is thought to play a critical role in recovery of speech perception e.g., in children with cochlear implants. Our long-term goal is to understand the neural basis for cortical processing of complex sounds and associated plasticity. A fundamental problem faced by animals and humans is to discriminate between complex sounds e.g., species-specific sound. However, cortical neural mechanisms underlying such discrimination are poorly understood. How reliably do cortical neurons discriminate between communication sounds? How does neural discrimination change during development, depend on early acoustic experience, and recover from early auditory deprivation. In this proposal we begin to investigate these questions in songbirds, a model system that offers unique advantages, with particular relevance to human speech. We will probe neural discrimination in field L, the avian analogue of primary auditory cortex, which is thought to play an important role in the perception of vocal communication sounds. This proposal will focus on adult male zebra finches. We will take an integrative approach combining experiments, theoretical analysis and computational modeling.
In Aim 1, we will record neural responses to conspecific songs. We will then use theoretical methods to quantify how reliably these different sounds can be discriminated, based on single neuron responses, analyzing how discrimination evolves over time, and how it depends on the temporal precision of neural responses, We will test if spike timing improves discrimination accuracy.
In Aim 2, we will characterize the receptive field (RF), i.e., the features of sound to which a neuron responds, identify critical RF parameters that may improve discrimination and assess thecontribution of non-linear response ; components to neural discrimination. We will test whether the RF is predictive of discrimination. In the long term, we will examine processing of vocal communication sounds in young birds, the effects of rearing birds under abnormal acoustic conditions e.g., isolation, and the recovery from auditory deprivation. Ultimately, understanding the capacity, as well as limits, of cortical plasticity in processing vocal communication sounds, may help guide recovery in humans with deficits in speech perception.
| Larson, Eric; Maddox, Ross K; Perrone, Ben P et al. (2012) Neuron-specific stimulus masking reveals interference in spike timing at the cortical level. J Assoc Res Otolaryngol 13:81-9 |
| Maddox, Ross K; Billimoria, Cyrus P; Perrone, Ben P et al. (2012) Competing sound sources reveal spatial effects in cortical processing. PLoS Biol 10:e1001319 |
| Larson, Eric; Perrone, Ben P; Sen, Kamal et al. (2010) A robust and biologically plausible spike pattern recognition network. J Neurosci 30:15566-72 |
| Grana, Gilberto David; Billimoria, Cyrus P; Sen, Kamal (2009) Analyzing variability in neural responses to complex natural sounds in the awake songbird. J Neurophysiol 101:3147-57 |
| Lee, Shane; Sen, Kamal; Kopell, Nancy (2009) Cortical gamma rhythms modulate NMDAR-mediated spike timing dependent plasticity in a biophysical model. PLoS Comput Biol 5:e1000602 |
| Greene, Garrett; Barrett, David G T; Sen, Kamal et al. (2009) Sparse coding of birdsong and receptive field structure in songbirds. Network 20:162-77 |
| Larson, Eric; Billimoria, Cyrus P; Sen, Kamal (2009) A biologically plausible computational model for auditory object recognition. J Neurophysiol 101:323-31 |
| Dent, Micheal L; McClaine, Elizabeth M; Best, Virginia et al. (2009) Spatial unmasking of birdsong in zebra finches (Taeniopygia guttata) and budgerigars (Melopsittacus undulatus). J Comp Psychol 123:357-67 |
| Billimoria, Cyrus P; Kraus, Benjamin J; Narayan, Rajiv et al. (2008) Invariance and sensitivity to intensity in neural discrimination of natural sounds. J Neurosci 28:6304-8 |
| Houghton, Conor; Sen, Kamal (2008) A new multineuron spike train metric. Neural Comput 20:1495-511 |
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