Of toasters and molecular ticker tapes

Experiments in systems neuroscience can be seen as consisting of three steps: (1) selecting the signals we are interested in, (2) probing the system with carefully chosen stimuli, and (3) getting data out of the brain. Here I discuss how emerging techniques in molecular biology are starting to improve these three steps. To estimate its future impact on experimental neuroscience, I will stress the analogy of ongoing progress with that of microprocessor production techniques. These techniques have allowed computers to simplify countless problems; because they are easier to use than mechanical timers, they are even built into toasters. Molecular biology may advance even faster than computer speeds and has made immense progress in understanding and designing molecules. These advancements may in turn produce impressive improvements to each of the three steps, ultimately shifting the bottleneck from obtaining data to interpreting it.     

Trust and Reciprocity: Are Effort and Money Equivalent?

Trust and reciprocity facilitate cooperation and are relevant to virtually all human interactions. They are typically studied using trust games: one subject gives (entrusts) money to another subject, which may return some of the proceeds (reciprocate). Currently, however, it is unclear whether trust and reciprocity in monetary transactions are similar in other settings, such as physical effort. Trust and reciprocity of physical effort are important as many everyday decisions imply an exchange of physical effort, and such exchange is central to labor relations. Here we studied a trust game based on physical effort and compared the results with those of a computationally equivalent monetary trust game. We found no significant difference between effort and money conditions in both the amount trusted and the quantity reciprocated. Moreover, there is a high positive correlation in subjects' behavior across conditions. This suggests that trust and reciprocity may be character traits: subjects that are trustful/trustworthy in monetary settings behave similarly during exchanges of physical effort. Our results validate the use of trust games to study exchanges in physical effort and to characterize inter-subject differences in trust and reciprocity, and also suggest a new behavioral paradigm to study these differences.     

Measuring cation dependent DNA polymerase fidelity landscapes by deep sequencing

High-throughput recording of signals embedded within inaccessible micro-environments is a technological challenge. The ideal recording device would be a nanoscale machine capable of quantitatively transducing a wide range of variables into a molecular recording medium suitable for long-term storage and facile readout in the form of digital data. We have recently proposed such a device, in which cation concentrations modulate the misincorporation rate of a DNA polymerase (DNAP) on a known template, allowing DNA sequences to encode information about the local cation concentration. In this work we quantify the cation sensitivity of DNAP misincorporation rates, making possible the indirect readout of cation concentration by DNA sequencing. Using multiplexed deep sequencing, we quantify the misincorporation properties of two DNA polymerases - Dpo4 and Klenow exo(-) - obtaining the probability and base selectivity of misincorporation at all positions within the template. We find that Dpo4 acts as a DNA recording device for Mn(2+) with a misincorporation rate gain of ～2%/mM. This modulation of misincorporation rate is selective to the template base: the probability of misincorporation on template T by Dpo4 increases >50-fold over the range tested, while the other template bases are affected less strongly. Furthermore, cation concentrations act as scaling factors for misincorporation: on a given template base, Mn(2+) and Mg(2+) change the overall misincorporation rate but do not alter the relative frequencies of incoming misincorporated nucleotides. Characterization of the ion dependence of DNAP misincorporation serves as the first step towards repurposing it as a molecular recording device.     

Synonymous codon usage pattern among the S,M, and L segments in Crimean-congo hemorrhagic fever virus

Crimean-Congo hemorrhagic fever (CCHF) virus is one among the major zoonosis viral diseases that use the Hyalomma ticks as their transmission vector to cause viral infection to the human and mammalian community. The fatality of infectious is high across the world especially in Africa, Asia, Middle East, and Europe. This study regarding codon usage bias of S, M, and L segments of the CCHF virus pertaining to the host Homo sapiens, reveals in-depth information about the evolutionary characteristics of CCHFV. Relative Synonymous Codon Usage (RSCU), Effective number of codons (ENC) were calculated, to determine the codon usage pattern in each segment. Correlation analysis between Codon adaptation index (CAI), GRAVY (Hydrophobicity), AROMO (Aromaticity), and nucleotide composition revealed bias in the codon usage pattern. There was no strong codon bias found among any segments of the CCHF virus, indicating both the factors i.e., natural selection and mutational pressure shapes the codon usage bias.     

An Examination of the Generalizability of Motor Costs

Most approaches to understanding human motor control assume that people maximize their rewards while minimizing their motor efforts. This tradeoff between potential rewards and a sense of effort is quantified with a cost function. While the rewards can change across tasks, our sense of effort is assumed to remain constant and characterize how the nervous system organizes motor control. As such, when a proposed cost function compares well with data it is argued to be the underlying cause of a motor behavior, and not simply a fit to the data. Implicit in this proposition is the assumption that this cost function can then predict new motor behaviors. Here we examined this idea and asked whether an inferred cost function in one setting could explain subject’s behavior in settings that differed dynamically but had identical rewards. We found that the pattern of behavior observed across settings was similar to our predictions of optimal behavior. However, we could not conclude that this behavior was consistent with a conserved sense of effort. These results suggest that the standard forms for quantifying cost may not be sufficient to accurately examine whether or not human motor behavior abides by optimality principles.     

Speed Constancy or Only Slowness: What Drives the Kappa Effect

In the Kappa effect, two visual stimuli are given, and their spatial distance affects their perceived temporal interval. The classical model assumes constant speed while a competing Bayesian model assumes a slow speed prior. The two models are based on different assumptions about the statistical structure of the environment. Here we introduce a new visual experiment to distinguish between these models. When fit to the data, both the two models replicated human response, but the slowness model makes better behavioral predictions than the speed constancy model, and the estimated constant speed is close to the absolute threshold of speed. Our findings suggest that the Kappa effect appears to be due to slow speeds, and also modulated by spatial variance.     

The Database for Reaching Experiments and Models

Reaching is one of the central experimental paradigms in the field of motor control, and many computational models of reaching have been published. While most of these models try to explain subject data (such as movement kinematics, reaching performance, forces, etc.) from only a single experiment, distinct experiments often share experimental conditions and record similar kinematics. This suggests that reaching models could be applied to (and falsified by) multiple experiments. However, using multiple datasets is difficult because experimental data formats vary widely. Standardizing data formats promises to enable scientists to test model predictions against many experiments and to compare experimental results across labs. Here we report on the development of a new resource available to scientists: a database of reaching called the Database for Reaching Experiments And Models (DREAM). DREAM collects both experimental datasets and models and facilitates their comparison by standardizing formats. The DREAM project promises to be useful for experimentalists who want to understand how their data relates to models, for modelers who want to test their theories, and for educators who want to help students better understand reaching experiments, models, and data analysis.     

The approximate entropy of the electromyographic signals of tremor correlates with the osmotic fragility of human erythrocytes

Background  

The main problem of tremor is the damage caused to the quality of the life of patients, especially those at more advanced ages. There is not a consensus yet about the origins of this disorder, but it can be examined in the correlations between the biological signs of aging and the tremor characteristics.     

Self versus Environment Motion in Postural Control

To stabilize our position in space we use visual information as well as non-visual physical motion cues. However, visual cues can be ambiguous: visually perceived motion may be caused by self-movement, movement of the environment, or both. The nervous system must combine the ambiguous visual cues with noisy physical motion cues to resolve this ambiguity and control our body posture. Here we have developed a Bayesian model that formalizes how the nervous system could solve this problem. In this model, the nervous system combines the sensory cues to estimate the movement of the body. We analytically demonstrate that, as long as visual stimulation is fast in comparison to the uncertainty in our perception of body movement, the optimal strategy is to weight visually perceived movement velocities proportional to a power law. We find that this model accounts for the nonlinear influence of experimentally induced visual motion on human postural behavior both in our data and in previously published results.