After the averaged traces were subtracted to isolate individual pharmacological components, the variances were propagated according to σa-b2 = σa2 + σb2. The propagated variance of each component was then pooled from all the cells tested to calculate the pooled variance (weighted sum of variance), which was then used for statistical analysis. Results were expressed as mean ± SEM, and the statistical significance was determined

at the level of α = 0.05 by two-tailed Student’s t test (Figure 3) or ANOVA (together with Games-Howell post hoc test if homoscedasticity was not satisfied). Additional information about patch-clamp recording, light stimulation, and data analysis can be found in Supplemental Experimental Procedures. We thank Dr. Jijian Zheng for scientific discussions. This work was supported in part by National Institutes of HealthGgrants R01EY017353 and R01EY10894 HDAC inhibitor (ZJZ), Departmental Challenge Grant from Research

to Prevent Blindness, Inc. and NIH Vision Core Grant (P30 EY000785). SP600125 “
“In principle, learning can involve alterations to different layers of an animal’s nervous system, from sensory neurons to interneurons and motor neurons. To fully understand the neural basis of experience-dependent behavioral plasticity, it is important to map the neuronal pathways that underlie behavioral responses before and after learning, understand how these neuronal pathways interact, and determine what changes occur during learning. Experience and environmental context can profoundly shape the

representations of an odor to an animal. Studies in both vertebrates and invertebrates have identified brain areas, or even specific neurons, that contribute to olfactory learning, such as a few distributed brain areas in the main olfactory system in mammals and mushroom body out neurons in flies (Sanchez-Andrade and Kendrick, 2009 and Waddell and Quinn, 2001). Specific neurotransmitters can also play regulatory roles in olfactory learning (Menzel and Muller, 1996, Schwaerzel et al., 2003 and Zhang et al., 2005). However, a systems-level analysis from sensory input to motor output, showing how both naive and learned olfactory preferences can be generated by the nervous system, has not yet been possible. The nematode Caenorhabditis elegans provides an opportunity to study the functional organization of neural networks with comprehensiveness and single-cell resolution. Its entire highly stereotyped nervous system contains just 302 neurons, and all synaptic connections between neurons have been defined by serial reconstruction of electron micrographs ( Chen et al., 2006 and White et al., 1986). The wiring diagram of the worm nervous system has facilitated the mapping of neural circuits that regulate mechanosensation ( Chalfie et al., 1985), olfactory sensation ( Bargmann et al.