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The Natural Variation of a Neural Code

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The Natural Variation of a Neural Code The Natural Variation of a Neural Code Yoav Kfir1,2, Ittai Renan3, Elad Schneidman4., Ronen Segev2,5*. 1 Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel, 2 The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel, 3 Department of Zoology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel, 4 Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel, 5 Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel Abstract The way information is represented by sequences of action potentials of spiking neurons is determined by the input each neuron receives, but also by its biophysics, and the specifics of the circuit in which it is embedded. Even the ‘‘code’’ of identified neurons can vary considerably from individual to individual. Here we compared the neural codes of the identified H1 neuron in the visual systems of two families of flies, blow flies and flesh flies, and explored the effect of the sensory environment that the flies were exposed to during development on the H1 code. We found that the two families differed considerably in the temporal structure of the code, its content and energetic efficiency, as well as the temporal delay of neural response. The differences in the environmental conditions during the flies’ development had no significant effect. Our results may thus reflect an instance of a family-specific design of the neural code. They may also suggest that individual variability in information processing by this specific neuron, in terms of both form and content, is regulated genetically. Citation: Kfir Y, Renan I, Schneidman E, Segev R (2012) The Natural Variation of a Neural Code. PLoS ONE 7(3): e33149. doi:10.1371/journal.pone.0033149 Editor: Holger G. Krapp, Imperial College London, United Kingdom Received July 17, 2011; Accepted February 10, 2012; Published March 12, 2012 Copyright: ß 2012 Kfir et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the Israel Science Foundation, a fellowship from the Center for Complexity Sciences, the Human Frontiers Science Program, the Zlotowski Center for Neuroscience (RS), and the Minerva Foundation, the Horowitz Center for Complexity Science, the Clore Center for Biological Physics, and the Peter and Patricia Gruber Foundation (ES). The funders had no role in study design, data collection and analysis, decision to publish,or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: [email protected] . These authors contributed equally to this work. Introduction We used the identified H1 neuron in the fly visual system to study the individual nature of the neural code. H1 is a motion The nervous system relies on a nearly universal ‘‘alphabet’’: sensitive neuron that processes wide field visual motion, and is part most neurons, in different brain modules and in many different of a network that is responsible for stabilizing yaw optomotor species, use sequences of electrical spikes to represent and responses [10,11]. In each brain hemisphere there is one H1 transmit information [1]. However, the structure of this ‘‘neural neuron that responds to horizontal back to front motion and is code’’ – i.e. the way information is carried by spike trains and inhibited by backwards motion; each one of the neurons projects how it can be read – can differ even between brain areas in the to the contra-lateral hemisphere of the fly’s brain. This neuron has same animal. The similarity in anatomical and functional been widely used in the study of various properties of the neural organization of the nervous system in different individuals reflects code, including the reliability of its response, information content, the universal properties of brain design and function. However, it the temporal structure of its code and its adaptation properties is unclear how different the corresponding brain modules of two [7,12–22], and its sensitivity to the fly’s activity state [23,24]. animals are, or how they differ in terms of the computations they Within the same species, the H1 code can demonstrate both high perform. variability, and some universal properties [17]. It is also well Behavioral differences between individuals are often attributed known that sensory experience has an extensive effect on the to genetic variations between species or even between individuals, development of the fly’s peripheral visual system [25,26], which are likely to be reflected in the neural circuit architecture, although, as shown by [25], rearing flies in a dark environment synaptic connection patterns, etc. [2,3]. Sensory experience also did not affect the response of H1 to local visual stimuli in a small has a profound impact on the structure and performance of the region of the visual field. Here we focused on differences between nervous system [4]. Here we aimed at a detailed quantitative two fly families, and explored the effect of sensory experience on analysis of the differences between individuals at the level of their the structure of the neural code at the level of individuals. neural codes. The putative design of the neural code as regards efficiency in terms of energy [5,6], information content [7,8], or Results predictive value [9] has been explored in different neural systems. We expect that differences (or similarities) that are informative We analyzed the structure and content of the spiking patterns of about the ‘‘conserved’’ and idiosyncratic parts of the neural code the identified H1 neuron in 24 flies from two families - six blow could have a functional relation to behavioral differences between flies, and 18 flesh flies – responding to wide field motion stimuli. individuals, species, or families. To conduct such analyses, we need H1 is a directional selective spiking neuron in the lobula plate, a quantitative framework in which to explore neural code which is selective for wide field horizontal motion in front of the variability, which could then be related to behavioral variability. fly’s eye. We identified the H1 neuron according to its response PLoS ONE | www.plosone.org 1 March 2012 | Volume 7 | Issue 3 | e33149 Variations in the Neural Code of the H1 Neuron properties; namely, directional selectivity and spiking response to distributions of code words they used. The Jensen-Shannon (JS) wide field horizontal motion in front of the fly’s contra-lateral eye divergence [28] between two distributions, P and Q, is a (see methods). symmetrized, and bounded extension of the commonly used To compare the neural code of H1 in the two families we bred Kullback-Leibler (KL) divergence between probability distribu- blow flies (Fig. 1A, group B1, n = 6) under similar visual tions [29], and measures in bits how easy it is to tell the conditions as a group of flesh flies (group F1, n = 6). To estimate distributions apart (Fig. 2B). Recall that the KL divergence the effect of the environment on the neural code we further between P and Q is given by studied two other groups of flesh flies (six individuals each), X which were bred under different visual environments: one group PxðÞ was bred outdoors in a transparent cage (Fig. 1B, group F2), and D (P(X),Q(X))~ P(x)log ð1Þ KL 2 QxðÞ the other (F3) was bred outside but in an opaque cage, which x exposed the flies to similar natural light intensities, but no details The JS divergence between P and Q, ranges from ‘0’ which of the natural environment. indicates that the two distributions are identical, and ‘1’ when they After the flies matured, we recorded extracellularly the activity have no overlap. of H1 in response to wide field stimulation by a pattern of random horizontal motion of vertical bars (Fig. 1C). Figure 1D presents examples of the spiking patterns of the H1 neurons in eight flies 1 PzQ PzQ D (P,Q)~ D (P, )zD (Q, ) ð2Þ (two from each group), with respect to the same movie segment. JS 2 KL 2 KL 2 H1 responds with high firing rates when the horizontal motion is in the preferred direction of the neuron, whereas motion in the We then quantified the dissimilarity between the distributions of opposite direction results in almost complete silence [11]. words fly i used in response to the whole movie, and those that fly j Differences between the two families were already clear from used: their average firing rates: flesh flies had 5964 spikes/s (n = 6) and blowflies had 8665 spikes/s (n = 6). The families also clearly ÀÁ1 ÀÁ D fly ,fly ~ D P (W),P (W) , ð3Þ differed in their response latencies (Fig. 1E): blow flies were W i j N JS flyi flyj significantly delayed compared to flesh flies (,2 ms difference) and were also much more variable (the response of blow flies appears where N is the length of word W. We found that the code words of less repetitive, which we will later quantify as higher entropy the two families were 3:1+0:4 bits=s apart, whereas only 1 bit is values). However, importantly, the differences between families needed to tell them apart with certainty. Thus, given a neural were much more significant and intricate than firing rate or delay response segment of a fly, and knowing the total distribution of alone. words that the flies use, about 300 ms are needed to identify to which of the two families it belongs. The differences between the Different families use different neural vocabularies and different groups of flesh flies were less pronounced, at code 1:2+0:2 bits=s, which was similar to the difference between To systematically compare the neural code of the different flies individual flies within each of the flesh fly groups (1:3+0:2 bits=s).
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