Auditory neurons are characterized by their receptive field properties, which describe the organization of parameters such as frequency and amplitude of stimuli that the neurons respond to. Receptive fields are relatively better described for neurons at lower levels of the auditory system, but higher-order neurons exhibit complex non-linearities that have resisted systematic quantification. Characterization of higher-order receptive fields, however, is fundamental to understanding normal and abnormal auditory perceptual processes, and also may help optimize performance of prosthetic devices. An attractive model system has been described whereby high-order auditory neurons in starlings become highly selective for acoustic objects (""""""""motifs"""""""") embedded in natural signals (songs). Recent results implicate remarkable sequence parsing abilities of starlings that exhibit sensitivity to prototypic grammar-like structures. In the proposed research, novel statistical techniques will be combined with physiological recordings of """"""""cmHV"""""""" neurons of starlings whose song recognition behavior is under operant control. In the first experiment, the statistical methodologies will be developed for learning efficient basis sets for motif structure and for estimating feature-based receptive fields with hierarchical non-linear regression, using Markov random fields of Bayesian inference models and incorporating non-linear temporal dynamics. In the second experiment, operant procedures will be used to identify natural features of motifs and parameters of motif sequences that starlings utilize in song recognition behavior. In the third experiment, cmHV responses will be characterized, with emphasis on analysis of the features identified by behavioral testing, and using the statistical methods for characterization of non-linear properties. Successful development of this approach would give quantitative neurophysiological insight into complex acoustic object and sequence recognition behavior while developing an approach of general utility to cortical sensory physiology.
| Brawn, Timothy P; Nusbaum, Howard C; Margoliash, Daniel (2013) Sleep consolidation of interfering auditory memories in starlings. Psychol Sci 24:439-47 |
| Amador, Ana; Margoliash, Daniel (2013) A mechanism for frequency modulation in songbirds shared with humans. J Neurosci 33:11136-44 |
| Adret, Patrice; Meliza, C Daniel; Margoliash, Daniel (2012) Song tutoring in presinging zebra finch juveniles biases a small population of higher-order song-selective neurons toward the tutor song. J Neurophysiol 108:1977-87 |
| Meliza, C Daniel; Margoliash, Daniel (2012) Emergence of selectivity and tolerance in the avian auditory cortex. J Neurosci 32:15158-68 |
| Margoliash, Daniel (2010) Sleep, learning, and birdsong. ILAR J 51:378-86 |
| Meliza, C Daniel; Chi, Zhiyi; Margoliash, Daniel (2010) Representations of conspecific song by starling secondary forebrain auditory neurons: toward a hierarchical framework. J Neurophysiol 103:1195-208 |
| Brawn, Timothy P; Nusbaum, Howard C; Margoliash, Daniel (2010) Sleep-dependent consolidation of auditory discrimination learning in adult starlings. J Neurosci 30:609-13 |
| Margoliash, Daniel; van Drongelen, Wim; Kohrman, Michael (2010) Introducing songbirds as a model system for epilepsy research. J Clin Neurophysiol 27:433-7 |
| Brawn, Timothy P; Fenn, Kimberly M; Nusbaum, Howard C et al. (2010) Consolidating the effects of waking and sleep on motor-sequence learning. J Neurosci 30:13977-82 |
| Margoliash, Daniel; Nusbaum, Howard C (2009) Language: the perspective from organismal biology. Trends Cogn Sci 13:505-10 |
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