Robustness and fault tolerance make brains harder to study

Brains increase the survival value of organisms by being robust and fault tolerant. That is, brain circuits continue to operate as the organism needs, even when the circuit properties are significantly perturbed. Kispersky and colleagues, in a recent paper in Neural Systems & Circuits, have found that Granger Causality analysis, an important method used to infer circuit connections from the behavior of neurons within the circuit, is defeated by the mechanisms that give rise to this robustness and fault tolerance

Dynamic clamp with StdpC software

Dynamic clamp is a powerful method that allows the introduction of artificial electrical components into target cells to simulate ionic conductances and synaptic inputs. This method is based on a fast cycle of measuring the membrane potential of a cell, calculating the current of a desired simulated component using an appropriate model and injecting this current into the cell. Here we present a dynamic clamp protocol using free, fully integrated, open-source software (StdpC, for spike timing-dependent plasticity clamp). Use of this protocol does not require specialist hardware, costly commercial software, experience in real-time operating systems or a strong programming background. The software enables the configuration and operation of a wide range of complex and fully automated dynamic clamp experiments through an intuitive and powerful interface with a minimal initial lead time of a few hours. After initial configuration, experimental results can be generated within minutes of establishing cell recording

The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites

Conductance-based neuron models are frequently employed to study the dynamics of biological neural networks. For speed and ease of use, these models are often reduced in morphological complexity. Simplified dendritic branching structures may process inputs differently than full branching structures, however, and could thereby fail to reproduce important aspects of biological neural processing. It is not yet well understood which processing capabilities require detailed branching structures. Therefore, we analyzed the processing capabilities of full or partially branched reduced models. These models were created by collapsing the dendritic tree of a full morphological model of a globus pallidus (GP) neuron while preserving its total surface area and electrotonic length, as well as its passive and active parameters. Dendritic trees were either collapsed into single cables (unbranched models) or the full complement of branch points was preserved (branched models). Both reduction strategies allowed us to compare dynamics between all models using the same channel density settings. Full model responses to somatic inputs were generally preserved by both types of reduced model while dendritic input responses could be more closely preserved by branched than unbranched reduced models. However, features strongly influenced by local dendritic input resistance, such as active dendritic sodium spike generation and propagation, could not be accurately reproduced by any reduced model. Based on our analyses, we suggest that there are intrinsic differences in processing capabilities between unbranched and branched models. We also indicate suitable applications for different levels of reduction, including fast searches of full model parameter space

Conductance Ratios and Cellular Identity

Recent experimental evidence suggests that coordinated expression of ion channels plays a role in constraining neuronal electrical activity. In particular, each neuronal cell type of the crustacean stomatogastric ganglion exhibits a unique set of positive linear correlations between ionic membrane conductances. These data suggest a causal relationship between expressed conductance correlations and features of cellular identity, namely electrical activity type. To test this idea, we used an existing database of conductance-based model neurons. We partitioned this database based on various measures of intrinsic activity, to approximate distinctions between biological cell types. We then tested individual conductance pairs for linear dependence to identify correlations. Contrary to experimental evidence, in which all conductance correlations are positive, 32% of correlations seen in this database were negative relationships. In addition, 80% of correlations seen here involved at least one calcium conductance, which have been difficult to measure experimentally. Similar to experimental results, each activity type investigated had a unique combination of correlated conductances. Finally, we found that populations of models that conform to a specific conductance correlation have a higher likelihood of exhibiting a particular feature of electrical activity. We conclude that regulating conductance ratios can support proper electrical activity of a wide range of cell types, particularly when the identity of the cell is well-defined by one or two features of its activity. Furthermore, we predict that previously unseen negative correlations and correlations involving calcium conductances are biologically plausible

Imitation of hand and tool actions is effector-independent

Following the theoretical notion that tools often extend one’s body, in the present study, we investigated whether imitation of hand or tool actions is modulated by effector-specific information. Subjects performed grasping actions toward an object with either a handheld tool or their right hand. Actions were initiated in response to pictures representing a grip at an object that could be congruent or incongruent with the required action (grip-type congruency). Importantly, actions could be cued by means of a tool cue, a hand cue, and a symbolic cue (effector-type congruency). For both hand and tool actions, an action congruency effect was observed, reflected in faster reaction times if the observed grip type was congruent with the required movement. However, neither hand actions nor tool actions were differentially affected by the effector represented in the picture (i.e., when performing a tool action, the action congruency effect was similar for tool cues and hand cues). This finding suggests that imitation of hand and tool actions is effector-independent and thereby supports generalist rather than specialist theories of imitation

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior

Reproducibility of histopathological findings in experimental pathology of the mouse: a sorry tail

Reproducibility of $\textit{in vivo}$ research using the mouse as a model organism depends on many factors, including experimental design, strain or stock, experimental protocols, and methods of data evaluation. Gross and histopathology are often the endpoints of such research and there is increasing concern about the accuracy and reproducibility of diagnoses in the literature. To reproduce histopathological results, the pathology protocol, including necropsy methods and slide preparation, should be followed by interpretation of the slides by a pathologist familiar with reading mouse slides and familiar with the consensus medical nomenclature used in mouse pathology. Likewise, it is important that pathologists are consulted as reviewers of manuscripts where histopathology is a key part of the investigation. The absence of pathology expertise in planning, executing and reviewing $\textit{in vivo}$ research using mice leads to questionable pathology-based findings and conclusions from studies, even in high-impact journals. We discuss the various aspects of this problem, give some examples from the literature and suggest solutions.This work was supported in part by US National Institutes of Health grants R01 AR049288, CA089713 and R21 AR063781 (to J.P.S.) and by The Warden and Fellows of Robinson College, Cambridge (to P.N.S.)

Embodying the mind and representing the body

Does the existence of body representations undermine the explanatory role of the body? Or do certain types of representation depend so closely upon the body that their involvement in a cognitive task implicates the body itself? In the introduction of this special issue we explore lines of tension and complement that might hold between the notions of embodiment and body representations, which remain too often neglected or obscure. To do so, we distinguish two conceptions of embodiment that either put weight on the explanatory role of the body itself or body representations. We further analyse how and to what extent body representations can be said to be embodied. Finally, we give an overview of the full volume articulated around foundational issues (How should we define the notion of embodiment? To what extent and in what sense is embodiment compatible with representationalism? To what extent and in what sense are sensorimotor approaches similar to behaviourism?) and their applications in several cognitive domains (perception, concepts, selfhood, social cognition)

A Chemocentric Approach to the Identification of Cancer Targets

A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity screening on tumor HCT116 and normal MRC-5 cell lines to identify proteins associated with cancer emerging from a differential virtual target profiling of the most selective compounds detected in both cell lines. It is shown that this smart combination of differential in vitro and in silico screenings (DIVISS) is capable of detecting a list of proteins that are already well accepted cancer drug targets, while complementing it with additional proteins that, targeted selectively or in combination with others, could lead to synergistic benefits for cancer therapeutics. The complete list of 115 proteins identified as being hit uniquely by compounds showing selective antiproliferative effects for tumor cell lines is provided