PhD, Biophysics, Harvard University
AB, Molecular Biology, Princeton University
For more information, please visit http://www.med.upenn.edu/hearing.
Auditory perception is shaped by the interactions of sensory inputs, experience, emotion and attention. The long-term goal of our research is to identify the neuronal circuits and codes that support auditory perception in real-life acoustic environments. Decades of research have identified how neuronal response properties to basic sounds, such as tones or whistles, are transformed in the auditory pathway in the passive brain. Recent advances in imaging, electrophysiological, optogenetic and behavioral techniques, have led to tremendous experimental progress in our understanding of the structure of sensory circuits. However, we are still missing an understanding of how the brain creates a percept of a complex auditory scene, and how this representation is shaped by learning and experience. My laboratory seeks to develop a quantitative understanding of the neuronal circuits supporting dynamic auditory perception, through a multi-faceted approach, combining behavioral, electrophysiological, optogenetic, imaging, mathematical and computational approaches, in mice and, through collaboration, in humans.
Neuronal circuits facilitating hearing in complex acoustic environments.
Adaptation to stimulus context is a ubiquitous property of cortical neurons, thought to enhance efficiency of sensory coding. Yet the specific neuronal circuits that facilitate cortical adaptation remain unknown. In the primary auditory cortex, the vast majority of neurons exhibit stimulus-specific adaptation, responding weakly to frequently repeated tones and strongly to rare tones. We are investigating the hypothesis that a complex circuit composed of several subtypes of cortical interneurons facilitates stimulus-specific adaptation. We use optogenetic methods to up-or down-activate the activity of parvalbumin-positive or somatostatin-positive interneurons and test the effect of their manipulation on responses of principal cortical neurons. By reducing responses to frequent sounds, complex inhibitory networks may enhance cortical sensitivity to rare sounds that may represent unexpected events.
Cortical mechanisms driving changes in auditory perception following emotional learning
Traumatic events lead to changes in the emotional response to the environment, and to changes in the way the environment is perceives. Identifying the brain circuits that link emotional responses and sensory perception is of crucial importance to learning the causes and developing treatments for anxiety and post-traumatic stress disorder (PTSD). We recently discovered a new link between emotional learning, a model of anxiety acquisition, and changes in perceptual acuity, and found that the auditory cortex plays a crucial in facilitating this plasticity. We are presently investigating the neuronal mechanisms that support dynamic changes in sensory perception driven by emotional learning, as well as identifying the source for individual variability in specificity of emotional learning. In order to achieve that, we combine behavioral, electrophysiological, computational and optogenetic tools. Our results will shed light on the circuits that are likely disrupted in PTSD and anxiety disorders and will eventually lead to development of novel tools for prevention and treatment of these devastating mental conditions.
Specialization of the auditory cortex for processing of natural sounds
Sensory systems are thought to have evolved to efficiently encode and represent the full range of sensory stimuli encountered in the natural world. The statistics of natural environmental sounds have an intricate spectro-temporal structure, yet how populations of neurons encode and process information about such complex statistics is only beginning to be elucidated. We recently identified a new form of statistical dependence in environmental sounds: In sounds of running water, a subset of environmental sounds, the temporal modulation spectrum across spectral bands scales with the center frequency of the band. In a psychophysical study, we found that sounds that obeyed the invariant scaling relation, but which varied in cyclo-temporal coefficients and spectro-temporal sound density evoked different percepts, ranging from pattering of rain to sound of a waterfall to artificial ringing. We are presently exploring changing spectro-temporal statistical properties of water-like sounds affects responses of neurons in the primary auditory cortex.
An essential task of the auditory system is to tell apart different communication signals, such as vocalizations. We recently found that neuronal populations in the auditory cortex are specialized for encoding con-specific vocalizations. We are presently investigating the neuronal mechanisms for creating an invariant representation of vocalizations in the auditory pathways, which would allow the brain to preserve the ability to tell apart vocalizations produced by different speakers or in the presence of noise. We are testing the hypothesis that invariant representations are created gradually through hierarchical transformation within the auditory pathway.
Computation in the auditory system
Throughout our studies we combine electrophysiological investigation of the neuronal pathways with computational approaches. Our goal is to understand the principles of encoding of information by populations of neurons, the function of specific cortical circuits comprised of inhibitory and excitatory neurons in learning and perception, and the mechanisms driving development of auditory perception and speech comprehension.
Natan, R.G., Isaac M. Carruthers, Laetitia Mwilambwe-Tshilobo, Geffen, M.N. (2016) Gain Control in the Auditory Cortex Evoked by Changing Temporal Correlation of Sounds. Cerebral Cortex, pii: bhw083. Pubmed. Article.
Gervain, J., Werker, J.F., Black, A., Geffen, M.N. (2016) The neural correlates of processing scale-invariant environmental sounds at birth. NeuroImage, 133:144-150. Pubmed. Article.
Blackwell, J.M., Taillefumier, T.O., Natan, R.G., Carruthers, I.M., Magnasco, M.O., Geffen, M.N. (2016) Stable encoding of sounds over a broad range of statistical parameters in the auditory cortex. European Journal of Neuroscience, 43(6), 751-764. Pubmed. Article.
Aizenberg, M., Mwilambwe-Tshilobo, L., Briguglio, J.J., Natan, R.G., Geffen, M.N. (2015) Bi-directional regulation of innate and learned behaviors that rely on frequency discrimination by cortical inhibitory interneurons. PLoS Biology, 13(12): e1002308.
Natan, R.G., Briguglio, J.J., Mwilambwe-Tshilobo, L., Jones, S., Aizenberg, M., Goldberg, E.M., Geffen, M.N. (2015) Complementary control of sensory adaptation by two types of cortical interneurons. eLife 2015; 4: e09868. doi: 10.7554/eLife.09868.
Blackwell, J.M., Taillefumier, T.O., Natan, R.G., Carruthers, I.M., Magnasco, M.O., Geffen, M.N. (2016) Stable encoding of sounds over a broad range of statistical parameters in the auditory cortex. European Journal of Neuroscience, 10.1111/ejn.13144.
Carruthers, I.M., Laplagne, D.A., Jaegle, A., Briguglio, J.J., Mwilambwe-Tshilobo, L., Natan, R.G., Geffen, M.N. (2015) Emergence of invariant representation of vocalizations in the auditory cortex. Journal of Neurophysiology, 114(5):2726-40. doi: 10.1152/jn.00095.2015.
Mwilambwe-Tshilobo, L., Davis, A.J.O., Aizenberg, M., Geffen, M.N. (2015) Selective impairment in frequency discrimination in a mouse model of tinnitus. PLoS ONE, 10(9): e0137749. doi: 10.1371/journal.pone.0137749.
Gervain, J., Werker, J.F., Geffen, M.N. (2014) Category-specific processing of scale-invariant sounds in infancy. PLoS ONE, 9(5): e96278.
Zaidi, Q., Victor, J.D., McDermott, J., Geffen, M.N., Bensmaia, S., Cleland, T.A. (2013) Perceptual Spaces: Mathematical structures to neural mechanisms. Journal of Neuroscience, 33(45), 17597-17602.
Aizenberg, M., Geffen, M.N. (2013) Bidirectional effects of auditory aversive learning on sensory acuity are mediated by the auditory cortex. Nature Neuroscience, 16, 994–996.
Carruthers, I.M., Natan, R.G., Geffen, M.N. (2013) Encoding of ultra-sonic vocalizations in the rat auditory cortex. Journal of Neurophysiology, 109(7), 1912-1927.
Geffen, M.N., Gervain, J., Werker, J.F., Magnasco, M.O. (2011) Auditory perception of self-similarity in water sounds. Frontiers in Integrative Neuroscience, 5:15.
Geffen, M.N., Broome, B.M., Laurent, G., Meister, M. (2009) Neural encoding of rapidly fluctuating odors. Neuron, 61(4), 570-586.
Geffen, M.N., de Vries, S.E.J., and Meister, M. (2007) Retinal ganglion cells can rapidly change polarity from Off to On. PLoS Biology, 5(3), e65.
Andermann, M.L., Ritt, J., Neimark, M.A., Moore, C.I. (2004) Neural correlates of vibrissa resonance: band-pass and somatotopic representation of high-frequency stimuli. Neuron, 42, 451-463.
Neimark, M.A., Andermann, M.L., Hopfield, J.J. and Moore, C.I. (2003) Vibrissa resonance as a transduction mechanism for tactile encoding. Journal of Neuroscience, 23(16), 6499-6509.