Timothy Q. Gentner - US grants

The integration of behavioral and neurophysiological techniques in the study of birdsong has led to significant advances in our understanding of the neural bases for both complex motor systems and vocal learning. This proposal follows a similar logic by integrating the neurophysiology and behavior of song perception in European starlings (Sturnus vulgaris). This research will broaden our understanding of the neural mechanisms that underlie the perception of biologically meaningful acoustic signals. Birdsong is one such biologically meaningful signal, and European starlings, like many species of song birds, use song to recognize individual conspecifics. Starlings are an ideal animal model in which to study the neural basis of song perception because (1) recognition abilities in this species generalize to novel songs from familiar birds, and (2) the behavioral relevance that different acoustic features of song hold for individual vocal recognition is well understood. These two aspects of individual vocal recognition in starlings will allow us to differentiate between neuronal responses that are specific to single songs and those that are specific to individuals, and further, to characterize the nature of these responses with respect to the biological relevance of the specific signal properties that elicit them. This integrative approach to the study of auditory perception in starlings will provide insight into the regions of the auditory forebrain that process complex communication signals, and into the neuronal mechanisms that give rise to recognition behaviors. In so doing, the results of these experiments will contribute significantly to our understanding of the higher-order processing of complex stimuli.

[unreadable] DESCRIPTION (provided by applicant): A critical challenge in understanding the neural basis of any complex behavior, including human language, is the development of appropriate animal models. Yet, for language, longstanding theoretical positions hold that many of the underlying cognitive capabilities are uniquely human. We have recently demonstrated, however, that European starlings, a species of song bird, can acquire and use complex patterning rules extracted from sequences of conspecific songs, thereby exhibiting syntactic processing abilities previously thought unique to humans. We have also recently shown that single neurons in the auditory forebrain region CMM, an analog to mammalian auditory cortex, acquire explicit representations of acoustic features in (and only in) the songs that adult starlings have learned to recognize. The combination of these results provides a unique opportunity for significant advancement in our understanding of the neurobiological and behavioral mechanisms for the perception and cognition of temporally patterned acoustic communication signals. We propose a series of neurophysiological and behavioral studies that capitalize on this opportunity with the overall goal of establishing birdsong as a model system for the neurobiological mechanisms of syntactic processing. We will examine experience-dependent song-selective responses in the ascending auditory hierarchy, testing the hypothesis that the auditory regions adjacent to CMM show selective representations of behaviorally relevant songs. We will examine temporal pattern perception and syntactic rule learning at the behavioral level to understand how learned patterning rules (i.e. syntax) can be applied by birds independent of pattern element acoustics, perhaps a crucial distinction between birds and humans. Finally, we will explore the neural bases of temporal pattern recognition and syntactic processing directly, by testing the hypothesis that the acquisition of syntactic rules describing patterns of song motifs leads to explicit representation of the acquired syntax in CMM and/or adjacent regions. The results of these studies will establish songbirds a model system for biological study of fundamental computational processes that underlie human language. This basic research therefore advances significantly the promise of clinical treatment for a variety of language and communication disorders, in children and cognitively impaired adults. [unreadable] [unreadable] [unreadable]

DESCRIPTION: The Neurosciences Graduate Program (NGP) at the University of California, San Diego (UCSD) is committed to training the next generation of neuroscience researchers, clinician-scientists and academicians. Over the past 20 years, the UCSD NGP has become one of the top neuroscience graduate programs in the country, ranked 4th in the nation in the 2010 National Research Council ranking. This training grant supports the first- and second-year students in the program, and is endorsed by strong institutional support from the participating departments at UCSD, the Salk Institute, The Scripps Research Institute and the Sanford-Burnham Medical Research Institute. These institutions are world-class research centers on the Torrey Pines Mesa, with the UCSD campus as the home academic institution. The NGP provides the broad umbrella that unites neuroscientists from all these institutions. The NGP provides trainees with a rich curriculum covering a broad spectrum of sub-disciplines in neurosciences, mentored research in the individual laboratories of outstanding investigators, and collaborative opportunities across different programs. The NGP responds to emerging areas of interest; a new formal specialization that expands the scope of training is Computational Neuroscience, added in the past few years. The NGP's training plan is structured such that the students form close interactions with each other and with the faculty upon entry to the program. Incoming students receive intensive hands-on laboratory training through the NGP Boot Camp, which also gives the students a unique bonding experience and initial exposure to the breadth of NGP research options. Following the core courses and three research lab rotations, students choose their dissertation thesis labs at the end of the first year. Each student's progress is monitored through an integrated series of cohesive formal evaluations. All students take a required course for scientific conduct and ethics. Students are enriched through a variety of activities that facilitate and enhance the interactions between students and training faculty. Career advising and mentorship are in place at each successive year. Vertical interactions among students from different years are facilitated through journal club, research rounds, and a prestigious seminar series organized and run by the NGP students, and the annual recruitment and retreat activities. Recruitment and admission to NGP is highly competitive. The program makes dedicated efforts to improve the recruitment and retention of under-represented students; the NGP ranks the top in representation of URM population among the UCSD graduate programs for STEM (Science, Technology, Engineering and Math). This training grant is central to the success of the UCSD neurosciences graduate training. The research productivity of the trainees is outstanding, and a large fraction of former trainees continue in scientific research and higher education. Over the next five years, the UCSD School of Medicine has set a goal to increase the size of the program through enhanced institutional support, with a strong commitment to improving the program's diversity.

Project Summary/Abstract: Processing acoustic communication signals is among the most difficult, yet vital capabilities that the auditory system must achieve. These abilities lie at the heart of language and speech processing, and their success or failure can have profound impacts on quality of life across the lifespan. Understanding the neurobiological mechanisms that support these basic abilities holds promise for advancing assistive listening devices, as well as improving diagnoses and treatments for learning disabilities and communication disorders such as auditory processing disorder, dyslexia, and specific language impairment. While much has been learned about the loci of language-related processing using non-invasive neuroscience techniques in humans, these techniques cannot answer how individual neurons and neural circuits implement language-relevant computations. As a result, the explicit cellular circuit-level and neuro-computational mechanisms that support acoustic communication signal processing are poorly understood. Multiple lines of research suggest that songbirds can provide an excellent model for investigating shared auditory processing abilities relevant to language, in particular the processing of temporal patterns within communication signals. The experiments outlined in this proposal investigate the neural mechanisms of auditory temporal pattern processing. In humans, the transition statistics between adjacent speech sounds (phonemes) can aid or alter phoneme categorization, providing cues for language learners and listeners to disambiguate perceptually similar sounds. Sensitivity to transition statistics is not exclusive to speech signals however, but reflects general auditory processes shared by many animals. In Aim 1 we investigate the categorical perception of complex auditory objects in populations of cortical neurons in an animal model, and ask how these neural representations are effected by temporal context. In addition to which elements occur in a sequence, speech processing also requires knowing where those elements occur. Sensitivities to the statistical regularities of speech sequences are established long before infants learn to speak, and continue to affect both recognition and comprehension throughout adulthood. Studies in Aim 2 focus on how sequence-specific information is encoded by single neurons and neural populations in auditory cortex. In Aim 3, we propose a basic circuit in which population level representations of auditory objects could be differentially modulated by patterning rules, and test this proposed pattern processing circuit using direct, casual manipulations. The proposed approach permits progress in the near term towards establishing the basic neurobiological substrates of foundational language-relevant abilities and a general framework within which more complex, uniquely human processes, can be proposed and eventually tested.

Understanding the physical, computational, and theoretical bases of human vocal communication, speech, is crucial to improved comprehension of voice, speech and language diseases and disorders, and improving their diagnosis, treatment and prevention. Meeting this challenge requires knowledge of the neural and sensorimotor mechanisms of vocal motor control. Our project will directly investigate the neural and sensorimotor mechanisms involved in the production of complex, natural, vocal communication signals. Our results will directly enhance brain-computer interface technology for communication and will accelerate the development of prostheses and other assistive/augmentative technologies for individuals with communications deficits due to injury or disease. We will develop a vocal prosthetic that directly translates neural signals in cortical sensorimotor and vocal-motor control regions into vocal communication signals output in real-time. Building on success using non-human primates for brain computer interfaces for general motor control, the prosthetic will be developed in songbirds, whose acoustically rich, learned vocalizations share many features with human speech. Because the songbird vocal apparatus is functionally and anatomically similar to the human larynx, and the cortical regions that control it are closely analogous to speech motor-control areas of the human brain, songbirds offer an ideal model for the proposed studies. Beyond the application of our work to human voice and speech, development of the vocal prosthetic will enable novel speech-relevant studies in the songbird model that can reveal fundamental mechanisms of vocal learning and production. In the first stage of the project, we collect a large data set of simultaneously recorded neural activity and vocalizations. In stage two, we will apply machine learning and artificial intelligence techniques to develop algorithms that map neural recordings to vocal output and enable us to estimate intended vocalizations directly from neural data. In stage three, we will develop computing infrastructure to run these algorithms in real-time, predicting intended vocalizations from neural activity as the animal is actively producing these vocalizations. In stage four, we will test the effectiveness of the prosthetic by substituting the bird?s own vocalization with the output from our prosthetic system. Success will set the stage for testing of these technologies in humans and translation to multiple assistive devices. In addition to our research goals, the project will engage graduate, undergraduate, and high school students through the development of novel educational modules that introduce students to brain machine interface and multidisciplinary studies that span engineering and the basic sciences.

Project Summary/Abstract: Processing acoustic communication signals is among the most difficult yet vital abilities of the auditory system. These abilities lie at the heart of language and speech processing, and their success or failure has profound impacts on quality of life across the lifespan. Understanding the neurobiological mechanisms that support these basic abilities holds promise for advancing assistive listening devices, and for improving diagnoses and treatments for learning disabilities and communication disorders, such as auditory processing disorder, dyslexia, and specific language impairment. Non-invasive neuroscience techniques in humans reveal the loci of language-related processing but do not answer how individual neurons and neural circuits implement language-relevant computations. Thus, circuit-level neuro-computational mechanisms that support acoustic communication signal processing remain poorly understood. Multiple lines of research suggest that songbirds can provide an excellent model for investigating shared auditory processing abilities relevant to language. This proposal investigates neural mechanisms of auditory temporal pattern processing abilities shared between songbirds and humans. In Aim 1, we test the cellular-level predictions of a powerful modelling framework, called predictive coding, proposed as a general computational mechanism to support the learned recognition of complex temporally patterned signals at multiple timescales. We combine state-of-the-art machine learning methods with multi-electrode electrophysiology, to test explicit models for natural stimulus representation, prediction, and error coding in single cortical neurons and neural populations. One aspect of auditory perception integral to speech is the discretization of the signal into learned categorically perceived sounds (phonemes). In Aim 2, we use the predictive coding framework to investigate the learned categorical perception of natural auditory categories in populations of cortical neurons. In humans, the transition statistics between adjacent phonemes can aid or alter phoneme categorization, providing cues for language learners and listeners to disambiguate perceptually similar sounds. Aim2 also examines how categorical neural representations are affected by temporal context. In addition to which phonemes occur in a sequence, speech processing also requires knowing where those elements occur. Sensitivities to the statistical regularities of speech sequences are established long before infants learn to speak, and continue to affect both recognition and comprehension throughout adulthood. Songbirds also attend to the statistical regularities in their vocal communication signals. In Aim 3, we focus on how sequence-specific information is encoded by single neurons and neural populations in auditory cortex. The proposed approach permits progress in the near term towards establishing the basic neurobiological substrates of foundational language-relevant abilities and a general framework within which more complex, uniquely human processes, can be proposed and eventually tested.

Project Summary/Abstract The Neurosciences Graduate Program (NGP) at UC San Diego (UCSD) is committed to training the next generation of neuroscience leaders. The NGP brings together world-class research institutions and laboratories at UCSD, The Salk Institute, The Scripps Research Institute, and the Sanford Burnham Institute, to create one of the largest and most diverse neuroscience environments in the world. The proposed training program combines this environment with a progressive, quantitatively rigorous curriculum covering multiple neuroscience disciplines, mentored research with world-leading investigators, collaborative opportunities across clinical and academic settings, and mentored professional development. Research productivity and placement of prior NGP trainees is outstanding, with most trainees continuing in scientific research and higher education. The NGP consistently ranks among the top graduate programs in US. The proposed training program supports 1st and 2nd-year NGP students and is endorsed by strong institutional support. The program reinforces close, productive interactions between students and faculty. Incoming students receive intensive hands-on laboratory training in a two-week Boot Camp that provides a unique bonding experience. Students choose thesis labs after completing the core courses and research lab rotations in the first year. Student progress is closely monitored through formal evaluations, with individually tailored career advising and mentorship. Scientific interactions among students and faculty are facilitated through student-run journal clubs, discussion courses, student talks, colloquia, outreach programs, recruitment activities, and an annual retreat. The NGP has met prior goals to increase program size by enhancing institutional support, and to strengthen recruitment and retention of underrepresented students. Representation of URM students in the NGP is now the highest among all UCSD STEM graduate programs, and the overall size of the program has increased by nearly 40%, to 102 PhD students, since 2012, while recruitment and admission have remained highly competitive (applications have doubled since 2007). Our guiding mission to develop tomorrow's leading neuroscientists is founded on rigorous skills in experimental design, statistical methodology and quantitative reasoning. Over the next five years, the NGP has set a goal to strengthen and comprehensively integrate the tenets of quantitative rigor, reproducibility, and research transparency into all aspects of the training program. This includes broadening the quantitative scope of the NGP by expanding the successful Computational Neuroscience specialization, modifying curricula, and altering mentoring practices to anticipate future challenges for data collection, access, and analysis. Our goal is a broad interdisciplinary neuroscience training environment that emphasizes strong quantitative skills coupled to rigorous experimental design and statistical methodology.