The primary goal of this project is to determine how acoustic information is represented in the auditory cortex. Though there have been numerous electrophysiological studies that characterize the responses of cortical neurons to sound, the underlying cellular and network mechanisms are still unclear. Here, we will use a combination of experiments and computer simulations to elucidate how neural networks in cortex process and transmit information. In the experiments of Aim 1, simultaneous whole-cell recordings will be performed from excitatory and inhibitory cells in cortical layers 2/3, 4, and 5 to determine the network architecture and characterize the synaptic connections between the neurons. In the experiments of Aim 2, the patterns of connections between neurons between neurons in layer 4 &layer 2/3 and between layer 2/3 &layer L5 will be characterized. This will provide information as to how signals are transformed from network to network. Finally, in Aim 3, the data obtained from the experiments will be used to construct a realistic model of auditory cortex. These experiments and simulations will provide basic information about cortical circuitry as well as provide insights as to how auditory signals are processed in cortex. The data and simulations will shed light on how hearing disorders are manifested at the cellular and network levels and conversely, how dysfunction at the cellular and network levels translate to hearing deficits.
These experiments and simulations will provide basic information about cortical circuitry as well as provide insights as to how auditory signals are processed in cortex. The data and simulations will shed light on how hearing disorders are manifested at the cellular and network levels and conversely, how dysfunction at the cellular and network levels translate to hearing deficits.
|Barral, Jérémie; Reyes, Alex D (2017) Optogenetic Stimulation and Recording of Primary Cultured Neurons with Spatiotemporal Control. Bio Protoc 7:|
|Graupner, Michael; Wallisch, Pascal; Ostojic, Srdjan (2016) Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate. J Neurosci 36:11238-11258|
|Higgins, David; Graupner, Michael; Brunel, Nicolas (2014) Memory maintenance in synapses with calcium-based plasticity in the presence of background activity. PLoS Comput Biol 10:e1003834|
|Graupner, Michael; Reyes, Alex D (2013) Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex. J Neurosci 33:15075-85|
|Oviedo, Hysell V; Reyes, Alex D (2012) Integration of subthreshold and suprathreshold excitatory barrages along the somatodendritic axis of pyramidal neurons. PLoS One 7:e33831|
|Graupner, Michael; Brunel, Nicolas (2012) Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location. Proc Natl Acad Sci U S A 109:3991-6|
|Schiff, Max L; Reyes, Alex D (2012) Characterization of thalamocortical responses of regular-spiking and fast-spiking neurons of the mouse auditory cortex in vitro and in silico. J Neurophysiol 107:1476-88|
|Levy, Robert B; Reyes, Alex D (2012) Spatial profile of excitatory and inhibitory synaptic connectivity in mouse primary auditory cortex. J Neurosci 32:5609-19|
|Levy, Robert B; Reyes, Alex D (2011) Coexistence of lateral and co-tuned inhibitory configurations in cortical networks. PLoS Comput Biol 7:e1002161|
|Reyes, Alex D (2011) Synaptic short-term plasticity in auditory cortical circuits. Hear Res 279:60-6|
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