Cell types, circuits, computation

How does the connectivity of a neuronal circuit, together with the individual properties of the cell types that take part in it, result in a given computation? We examine this question in the context of retinal circuits. We suggest that the retina can be viewed as a parallel assemblage of many small computational devices, highly stereotypical and task-specific circuits afferent to a given ganglion cell type, and we discuss some rules that govern computation in these devices. Multi-device processing in retina poses conceptual problems when it is contrasted with cortical processing. We lay out open questions both on processing in retinal circuits and on implications for cortical processing of retinal inputs.     

Continuous computation in engineered gene circuits

In this paper we consider the problem of representation and measurement in genetic circuits, and investigate how they can affect the reliability of engineered systems. We propose a design scheme, based on the notion of continuous computation, which addresses these issues. We illustrate the methodology by showing how a concept from computer architecture (namely, branch prediction) may be implemented in vivo, using a distributed approach. Simulation results confirm the in-principle feasibility of our method, and offer valuable insights into its future laboratory validation.     

Networks and circuits in cell regulation

Large-scale “omics” data are often represented as networks of interacting components, but such representation is inherently static and, as such, cannot provide a realistic picture of the temporal dynamics of complex cellular functions. These difficulties suggest moving to a modeling strategy that explicitly takes into account both the wiring of the components and the task they perform. From an engineering perspective, this problem resembles that of “circuit analysis”. In this paper, we focus on a limited but relevant biological circuit, the G1 to S transition in yeast cell cycle, and investigate both the network representation and the corresponding circuit described by a mathematical model, by means of a wide range of numerical simulation analysis. Reliable predictions of system-level properties are achieved and the parameters that mostly affect these properties are found out.     

Synthetic analog and digital circuits for cellular computation and memory

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Neuroendocrine-immune circuits,phenotypes, and interactions

Multidirectional interactions among the immune, endocrine, and nervous systems have been demonstrated in humans and non-human animal models for many decades by the biomedical community, but ecological and evolutionary perspectives are lacking. Neuroendocrine-immune interactions can be conceptualized using a series of feedback loops, which culminate into distinct neuroendocrine-immune phenotypes. Behavior can exert profound influences on these phenotypes, which can in turn reciprocally modulate behavior. For example, the behavioral aspects of reproduction, including courtship, aggression, mate selection and parental behaviors can impinge upon neuroendocrine-immune interactions. One classic example is the immunocompetence handicap hypothesis (ICHH), which proposes that steroid hormones act as mediators of traits important for female choice while suppressing the immune system. Reciprocally, neuroendocrine-immune pathways can promote the development of altered behavioral states, such as sickness behavior. Understanding the energetic signals that mediate neuroendocrine-immune crosstalk is an active area of research. Although the field of psychoneuroimmunology (PNI) has begun to explore this crosstalk from a biomedical standpoint, the neuroendocrine-immune-behavior nexus has been relatively underappreciated in comparative species. The field of ecoimmunology, while traditionally emphasizing the study of non-model systems from an ecological evolutionary perspective, often under natural conditions, has focused less on the physiological mechanisms underlying behavioral responses. This review summarizes neuroendocrine-immune interactions using a comparative framework to understand the ecological and evolutionary forces that shape these complex physiological interactions.     

Information processing,computation, and cognition

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects.     

Synthetic circuits,devices and modules

The aim of synthetic biology is to design artificial biological systems for novel applications. From an engineering perspective, construction of biological systems of defined functionality in a hierarchical way is fundamental to this emerging field. Here, we highlight some current advances on design of several basic building blocks in synthetic biology including the artificial gene control elements, synthetic circuits and their assemblies into devices and modules. Such engineered basic building blocks largely expand the synthetic toolbox and contribute to our understanding of the underlying design principles of living cells.     

Neural correlations, population coding and computation

How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.     

Metacognition: computation, biology and function

Many complex systems maintain a self-referential check and balance. In animals, such reflective monitoring and control processes have been grouped under the rubric of metacognition. In this introductory article to a Theme Issue on metacognition, we review recent and rapidly progressing developments from neuroscience, cognitive psychology, computer science and philosophy of mind. While each of these areas is represented in detail by individual contributions to the volume, we take this opportunity to draw links between disciplines, and highlight areas where further integration is needed. Specifically, we cover the definition, measurement, neurobiology and possible functions of metacognition, and assess the relationship between metacognition and consciousness. We propose a framework in which level of representation, order of behaviour and access consciousness are orthogonal dimensions of the conceptual landscape.     

Respiratory circuits: development, function and models

Breathing is a rhythmic motor behavior generated and controlled by hindbrain neuronal networks. Respiratory motor output arises from two distinct, but functionally interacting, rhythmogenic networks: the pre-B?tzinger complex (preB?tC) and the retrotrapezo?d nucleus/parafacial respiratory group (RTN/pFRG). This review outlines recent advances in delineating the genetic specification of the neuronal constituents of these two rhythmogenic networks, their respective roles in respiratory function and how they interact to constitute a functional respiratory circuit ensemble. The often lethal consequences of disruption to these networks found in naturally occurring developmental disorders, transgenic animals, and highly specific lesion studies are described. In addition, we discuss how recent computational models enhance our understanding of how respiratory networks generate and regulate respiratory behavior.     

Kinship, Networks, and Exchange

Kinship, Networks, and Exchange. Thomas Schweizer and Douglas R. White. eds. New York; Cambridge University Press, 1997. 338 pp.     

Pets,Networks and Well-Being

ABSTRACT

This study explores two explanations for well-being among older adults: social network analysis and human–animal relations. The data are based on a stratified probability sample of community living adults, aged 60 years and over, located in several rural communities in north-eastern Oregon. The dependent variables include three distinct measures of psychological well-being: life satisfaction, locus of control, and self-esteem. The independent variables include pet ownership and various measures of the personal network of respondents, including network structural variables (range, density, and frequency of contact) and network content variables (both instrumental and expressive). Control variables include socio-demographic characteristics and a measure of physical health. Multiple regression analysis is used to estimate the effects of the independent and control variables. Pet ownership was related to two of the well-being measures – self-esteem and locus of control – but only for men. Some methodological and theoretical implications are discussed.     

Seeing things in motion: models, circuits, and mechanisms

Motion vision provides essential cues for navigation and course control as well as for mate, prey, or predator detection. Consequently, neurons responding to visual motion in a direction-selective way are found in almost all species that see. However, directional information is not explicitly encoded at the level of a single photoreceptor. Rather, it has to be computed from the spatio-temporal excitation level of at least two photoreceptors. How this computation is done and how this computation is implemented in terms of neural circuitry and membrane biophysics have remained the focus of intense research over many decades. Here, we review recent progress made in this area with an emphasis on insects and the vertebrate retina.     

Hippocampo-cortical circuits for selective memory encoding,routing, and replay

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