The stimulus-response relationship of many sensory neurons is nonlinear, but fully quantifying this relationship by a complex nonlinear model may require too much data to be experimentally tractable. Here we present a theoretical study of a general two-stage computational method that may help to significantly reduce the number of stimuli needed to obtain an accurate mathematical description of nonlinear neural responses. Our method of active data collection first adaptively generates stimuli that are optimal for estimating the parameters of competing nonlinear models and then uses these estimates to generate stimuli online that are optimal for discriminating these models. We applied our method to simple hierarchical circuit models, including nonlinear networks built on the spatiotemporal or spectral-temporal receptive fields, and confirmed that collecting data using our two-stage adaptive algorithm was far more effective for estimating and comparing competing nonlinear sensory processing models than standard nonadaptive methods using random stimuli.

. Most studies investigating neural representations of species-specific vocalizations in nonhuman primates and other species have involved studying neural responses to vocalization tokens. One limitation of such approaches is the difficulty in determining which acoustical features of vocalizations evoke neural responses. Traditionally used filtering techniques are often inadequate in manipulating features of complex vocalizations. Furthermore, the use of vocalization tokens cannot fully account for intrinsic stochastic variations of vocalizations that are crucial in understanding the neural codes for categorizing and discriminating vocalizations differing along multiple feature dimensions. In this work, we have taken a rigorous and novel approach to the study of species-specific vocalization processing by creating parametric "virtual vocalization" models of major call types produced by the common marmoset (Callithrix jacchus). The main findings are as follows. 1) Acoustical parameters were measured from a database of the four major call types of the common marmoset. This database was obtained from eight different individuals, and for each individual, we typically obtained hundreds of samples of each major call type. 2) These feature measurements were employed to parameterize models defining representative virtual vocalizations of each call type for each of the eight animals as well as an overall species-representative virtual vocalization averaged across individuals for each call type. 3) Using the same feature-measurement that was applied to the vocalization samples, we measured acoustical features of the virtual vocalizations, including features not explicitly modeled and found the virtual vocalizations to be statistically representative of the callers and call types. 4) The accuracy of the virtual vocalizations was further confirmed by comparing neural responses to real and synthetic virtual vocalizations recorded from awake marmoset auditory cortex. We found a strong agreement between the responses to token vocalizations and their synthetic counterparts. 5) We demonstrated how these virtual vocalization stimuli could be employed to precisely and quantitatively define the notion of vocalization "selectivity" by using stimuli with parameter values both within and outside the naturally occurring ranges. We also showed the potential of the virtual vocalization stimuli in studying issues related to vocalization categorizations by morphing between different call types and individual callers.

Kotak, Vibhakar C., Christopher DiMattina, and Dan H. Sanes. GABA B and Trk receptor signaling mediates long-lasting inhibitory synaptic depression. J Neurophysiol 86: 536 -540, 2001. In many areas of the nervous system, excitatory and inhibitory synapses are reconfigured during early development. We have previously described the anatomical refinement of an inhibitory projection from the medial nucleus of the trapezoid body to the lateral superior olive in the developing gerbil auditory brain stem. Furthermore, these inhibitory synapses display an age-dependent form of long-lasting depression when activated at a low rate, suggesting that this process could support inhibitory synaptic refinement. Since the inhibitory synapses release both glycine and GABA during maturation, we tested whether GABA B receptor signaling could initiate the decrease in synaptic strength. When whole cell recordings were made from lateral superior olive neurons in a brain slice preparation, the long-lasting depression of medial nucleus of the trapezoid body-evoked inhibitory potentials was eliminated by the GABA B receptor antagonist, SCH-50911. In addition, inhibitory potentials could be depressed by repeated exposure to the GABA B receptor agonist, baclofen. Since GABA B receptor signaling may not account entirely for inhibitory synaptic depression, we examined the influence of neurotrophin signaling pathways located in the developing superior olive. Bath application of brainderived neurotrophic factor or neurotrophin-3 depressed evoked inhibitory potentials, and use-dependent depression was blocked by the tyrosine kinase antagonist, K-252a. We suggest that early expression of GABAergic and neurotrophin signaling mediates inhibitory synaptic plasticity, and this mechanism may support the anatomical refinement of inhibitory connections.