http://www.neuralsystemsandcircuits.com The latest research articles published by Neural Systems & Circuits 2012-05-02T00:00:00Z Background: Precise spike synchrony, at the millisecond or even sub-millisecond time scale, has been reported in different brain areas, but its neurobiological meaning and its underlying mechanisms remain unknown or controversial. Studying these questions is complicated by the lack of a validated, well-normalized and robust index for quantifying synchrony. Previously used measures of synchrony are often improperly normalized and thereby are not comparable between different experimental conditions, are sensitive to variations in firing rate or to the firing rate differential between the two neurons, and/or rely on untenable assumptions of firing rate stationarity and Poisson statistics. I describe here a novel measure, the Jitter-Based Synchrony Index (JBSI), that overcomes these issues.Results and discussionThe JBSI method is based on the introduction of virtual spike jitter. While previous implementations of the jitter method used it only to detect synchrony, the JBSI method also quantifies synchrony. Previous implementations of the jitter method used computationally intensive Monte Carlo simulations to generate surrogate spike trains, whereas the JBSI is computed analytically. The JBSI method does not assume any specific firing model, and does not require that the spike trains be locked to a repeating external stimulus. The JBSI can assume values from 1 (maximal possible synchrony) to -1 (minimal possible synchrony) and is therefore properly normalized. Using simulated Poisson spike trains with introduced controlled spike coincidences, I demonstrate that the JBSI is a linear measure of the spike coincidence rate, is independent of the mean firing frequency or the firing frequency differential between the two neurons, and is not sensitive to co-modulations in the firing rates of the two neurons. In contrast, several commonly used synchrony indices fail under one or more of these scenarios. I also demonstrate how the JBSI can be used to estimate the spike timing precision in the system. Conclusions: The JBSI is a conceptually simple and computationally efficient method that can be used to compute the statistical significance of firing synchrony, to quantify synchrony as a well-normalized index, and to estimate the degree of temporal precision in the system. http://www.neuralsystemsandcircuits.com/content/2/1/5 Ariel Agmon Neural Systems & Circuits 2012, null:5 2012-05-02T00:00:00Z doi:10.1186/2042-1001-2-5 /content/figures/2042-1001-2-5-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 5 2012-05-02T00:00:00Z PDF The aim of the work reviewed here is to relate the properties of individual neurons to network organization and behavior using the feeding system of the gastropod mollusk, Lymnaea. Food ingestion in this animal involves sequences of rhythmic biting movements that are initiated by the application of a chemical food stimulus to the lips and esophagus. We investigated how individual neurons contribute to various network functions that are required for the generation of feeding behavior such as rhythm generation, initiation ('decision making'), modulation and hunger and satiety. The data support the view that feeding behavior is generated by a distributed type of network organization with individual neurons often contributing to more than one network function, sharing roles with other neurons. Multitasking in a distributed type of network would be 'economically' sensible in the Lymnaea feeding system where only about 100 neurons are available to carry out a variety of complex tasks performed by millions of neurons in the vertebrate nervous system. Having complementary and potentially alternative mechanisms for network functions would also add robustness to what is a 'noisy' network where variable firing rates and synaptic strengths are commonly encountered in electrophysiological recording experiments. http://www.neuralsystemsandcircuits.com/content/2/1/4 Paul Benjamin Neural Systems & Circuits 2012, null:4 2012-04-17T00:00:00Z doi:10.1186/2042-1001-2-4 /content/figures/2042-1001-2-4-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 4 2012-04-17T00:00:00Z XML The 9th annual Computational and Systems Neuroscience meeting (Cosyne) was held 23-26 February in Salt Lake City, Utah. Cosyne meeting is the forum for exchange of experimental and theoretical/computational approaches to studying systems neuroscience. http://www.neuralsystemsandcircuits.com/content/2/1/3 Agnieszka Grabska-Barwinska Cindy Poo Neural Systems & Circuits 2012, null:3 2012-03-30T00:00:00Z doi:10.1186/2042-1001-2-3 /content/figures/2042-1001-2-3-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 3 2012-03-30T00:00:00Z PDF The development of neuroscience over the past 50 years has some similarities with the development of physics in the 17th century. Towards the beginning of that century, Bacon promoted the systematic gathering of experimental data and the induction of scientific truth; towards the end, Newton expressed his principles of gravitation and motion in a concise set of mathematical equations that made precise falsifiable predictions. This paper expresses the opinion that as neuroscience comes of age, it needs to move away from amassing large quantities of data about the brain, and adopt a popperian model in which theories are developed that can make strong falsifiable predictions and guide future experimental work. http://www.neuralsystemsandcircuits.com/content/2/1/2 David Gamez Neural Systems & Circuits 2012, null:2 2012-01-30T00:00:00Z doi:10.1186/2042-1001-2-2 /content/figures/2042-1001-2-2-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 2 2012-01-30T00:00:00Z XML No description available http://www.neuralsystemsandcircuits.com/content/2/1/1 Peter Latham Venkatesh Murthy Neural Systems & Circuits 2012, null:1 2012-01-05T00:00:00Z doi:10.1186/2042-1001-2-1 /content/figures/2042-1001-2-1-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 1 2012-01-05T00:00:00Z XML BackgroundThe primary visual cortex of many mammals contains a continuous representation of visual space, with a roughly repetitive aperiodic map of orientation preferences superimposed. It was recently found that orientation preference maps (OPMs) obey statistical laws which are apparently invariant among species widely separated in eutherian evolution. Here, we examine whether one of the most prominent models for the optimization of cortical maps, the elastic net (EN) model, can reproduce this common design. The EN model generates representations which optimally trade of stimulus space coverage and map continuity. While this model has been used in numerous studies, no analytical results about the precise layout of the predicted OPMs have been obtained so far.ResultsWe present a mathematical approach to analytically calculate the cortical representations predicted by the EN model for the joint mapping of stimulus position and orientation. We find that in all the previously studied regimes, predicted OPM layouts are perfectly periodic. An unbiased search through the EN parameter space identifies a novel regime of aperiodic OPMs with pinwheel densities lower than found in experiments. In an extreme limit, aperiodic OPMs quantitatively resembling experimental observations emerge. Stabilization of these layouts results from strong nonlocal interactions rather than from a coverage-continuity-compromise.ConclusionsOur results demonstrate that optimization models for stimulus representations dominated by nonlocal suppressive interactions are in principle capable of correctly predicting the common OPM design. They question that visual cortical feature representations can be explained by a coverage-continuity-compromise. http://www.neuralsystemsandcircuits.com/content/1/1/17 Wolfgang Keil Fred Wolf Neural Systems & Circuits 2011, null:17 2011-12-29T00:00:00Z doi:10.1186/2042-1001-1-17 /content/figures/2042-1001-1-17-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 17 2011-12-29T00:00:00Z XML Although it has been over a century since neuroscientists first conjectured that networks of neurons comprise the brain, technology has limited high-throughput investigations of neural circuitry until very recently. In the last couple of decades, several experimental paradigms have arisen that are poised to finally begin studying neuroanatomy in a high-throughput fashion. In 2005, the term connectome was coined independently by Patric Hagmann and Olaf Sporns, to describe the complete set of neural connections in a brain. Interestingly, both usages seemed to be referring to using Magnetic Resonance Imaging (MRI) to study human brain networks. Shortly thereafter, Narayanan "Bobby" Kasthuri and Jeff Lichtman published an article suggesting that "connectome" should refer to connections between neurons, which one can infer using Electron Microscopy (EM) and fluorescence microscopy (e.g., brainbow animals). "Projectome", they suggested, is more appropriate for MRI based studies. Yet, the word connectome stuck, and now refers to essentially any neuroscientific investigation of the relationship between (collections of) neurons, be they functional or structural. http://www.neuralsystemsandcircuits.com/content/1/1/16 Joshua Vogelstein Neural Systems & Circuits 2011, null:16 2011-11-18T00:00:00Z doi:10.1186/2042-1001-1-16 /content/figures/2042-1001-1-16-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 16 2011-11-18T00:00:00Z XML The 2011 EMBO Conference Series on the Assembly and Function of Neuronal Circuits was held from 25 to 30 September 2011 at Monte Verità in Ascona, Switzerland. Approximately 100 participants explored current challenges and approaches to studying neural circuit function and organization. http://www.neuralsystemsandcircuits.com/content/1/1/15 Alice Wang Jeremiah Cohen Neural Systems & Circuits 2011, null:15 2011-10-27T00:00:00Z doi:10.1186/2042-1001-1-15 /content/figures/2042-1001-1-15-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 15 2011-10-27T00:00:00Z XML - http://www.neuralsystemsandcircuits.com/content/1/1/14 Anna Webb Peter Latham Venkatesh Murthy Neural Systems & Circuits 2011, null:14 2011-10-06T00:00:00Z doi:10.1186/2042-1001-1-14 /content/figures/2042-1001-1-14-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 14 2011-10-06T00:00:00Z XML In the study of the neural circuits underlying behavior and autonomic functions, the stereotyped and accessible nervous system of medicinal leeches, Hirudo sp., has been particularly informative. These leeches express well-defined behaviors and autonomic movements which are amenable to investigation at the circuit and neuronal levels. In this review, we discuss some of the best understood of these movements and the circuits which underlie them, focusing on swimming, crawling and heartbeat. We also discuss the rudiments of decision-making: the selection between generally mutually exclusive behaviors at the neuronal level. http://www.neuralsystemsandcircuits.com/content/1/1/13 Damon Lamb Ronald Calabrese Neural Systems & Circuits 2011, null:13 2011-09-28T00:00:00Z doi:10.1186/2042-1001-1-13 /content/figures/2042-1001-1-13-toc.gif Neural Systems & Circuits 2042-1001 ${item.volume} 13 2011-09-28T00:00:00Z XML