title: Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons.
abstract: Neurons in sensory brain regions shape our perception of the surrounding environment through two parallel operations: decomposition and integration. For example, auditory neurons decompose sounds by separately encoding their frequency, temporal modulation, intensity, and spatial location. Neurons also integrate across these various features to support a unified perceptual gestalt of an auditory object. At higher levels of a sensory pathway, neurons may select for a restricted region of feature space defined by the intersection of multiple, independent stimulus dimensions. To further characterize how auditory cortical neurons decompose and integrate multiple facets of an isolated sound, we developed an automated procedure that manipulated five fundamental acoustic properties in real time based on single-unit feedback in awake mice. Within several minutes, the online approach converged on regions of the multidimensional stimulus manifold that reliably drove neurons at significantly higher rates than predefined stimuli. Optimized stimuli were cross-validated against pure tone receptive fields and spectrotemporal receptive field estimates in the inferior colliculus and primary auditory cortex. We observed, from midbrain to cortex, increases in both level invariance and frequency selectivity, which may underlie equivalent sparseness of responses in the two areas. We found that onset and steady-state spike rates increased proportionately as the stimulus was tailored to the multidimensional receptive field. By separately evaluating the amount of leverage each sound feature exerted on the overall firing rate, these findings reveal interdependencies between stimulus features as well as hierarchical shifts in selectivity and invariance that may go unnoticed with traditional approaches.
authors.affiliation: Eaton-Peabody Laboratory, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts 02114, Program in Neuroscience, Harvard Medical School, Boston, Massachusetts 02115, chamber3@fas.harvard.edu Daniel_polley@meei.harvard.edu.
authors.forename: Anna R
authors.initials: AR
authors.lastname: Chambers
authors.affiliation: Eaton-Peabody Laboratory, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts 02114, Department of Otology and Laryngology, Harvard Medical School, Boston, Massachusetts 02115, and.
authors.forename: Kenneth E
authors.initials: KE
authors.lastname: Hancock
authors.affiliation: Hearing Research Center, Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215.
authors.forename: Kamal
authors.initials: K
authors.lastname: Sen
authors.affiliation: Eaton-Peabody Laboratory, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts 02114, Department of Otology and Laryngology, Harvard Medical School, Boston, Massachusetts 02115, and chamber3@fas.harvard.edu Daniel_polley@meei.harvard.edu.
authors.forename: Daniel B
authors.initials: DB
authors.lastname: Polley
mesh_terms: D000161:Acoustic Stimulation; D000818:Animals; D001303:Auditory Cortex / Q000166:cytology / Q000502:physiology*; D001307:Auditory Perception / Q000502:physiology*; D004567:Electrodes, Implanted; D008297:Male; D051379:Mice; D008808:Mice, Inbred CBA; D009474:Neurons / Q000502:physiology*
keywords: auditory cortex; closed-loop; genetic algorithm; online neural characterization; optimization algorithm; sparse coding