Using perturbations to identify the brain circuits underlying active vision

The visual and oculomotor systems in the brain have been studied extensively in the primate. Together, they can be regarded as a single brain system that underlies active vision—the normal vision that begins with visual processing in the retina and extends through the brain to the generation of eye movement by the brainstem. The system is probably one of the most thoroughly studied brain systems in the primate, and it offers an ideal opportunity to evaluate the advantages and disadvantages of the series of perturbation techniques that have been used to study it. The perturbations have been critical in moving from correlations between neuronal activity and behaviour closer to a causal relation between neuronal activity and behaviour. The same perturbation techniques have also been used to tease out neuronal circuits that are related to active vision that in turn are driving behaviour. The evolution of perturbation techniques includes ablation of both cortical and subcortical targets, punctate chemical lesions, reversible inactivations, electrical stimulation, and finally the expanding optogenetic techniques. The evolution of perturbation techniques has supported progressively stronger conclusions about what neuronal circuits in the brain underlie active vision and how the circuits themselves might be organized.     

Evolving digital circuits using hybrid particle swarm optimization and differential evolution

This paper presents the evolution of combinational logic circuits by a new hybrid algorithm known as the Differential Evolution Particle Swarm Optimization (DEPSO), formulated from the concepts of a modified particle swarm and differential evolution. The particle swarm in the hybrid algorithm is represented by a discrete 3-integer approach. A hybrid multi-objective fitness function is coined to achieve two goals for the evolution of circuits. The first goal is to evolve combinational logic circuits with 100% functionality, called the feasible circuits. The second goal is to minimize the number of logic gates needed to realize the feasible circuits. In addition, the paper presents modifications to enhance performance and robustness of particle swarm and evolutionary techniques for discrete optimization problems. Comparison of the performance of the hybrid algorithm to the conventional Karnaugh map and evolvable hardware techniques such as genetic algorithm, modified particle swarm, and differential evolution are presented on a number of case studies. Results show that feasible circuits are always achieved by the DEPSO algorithm unlike with other algorithms and the percentage of best solutions (minimal logic gates) is higher.     

The genotypic complexity of evolved fault-tolerant and noise-robust circuits

Noise and component failure is an increasingly difficult problem in modern electronic design. Bio-inspired techniques is one approach that is applied in an effort to solve such issues, motivated by the strong robustness and adaptivity often observed in nature. Circuits investigated herein are designed to be tolerant to faults or robust to noise, using an evolutionary algorithm. A major challenge is to improve the scalability of the approach. Earlier results have indicated that the evolved circuits may be suited for the application of artificial development, an approach to indirect mapping from genotype to phenotype that may improve scalability. Those observations were based on the genotypic complexity of evolved circuits. Herein, we measure the genotypic complexity of circuits evolved for tolerance to faults or noise, in order to uncover how that tolerance affects the complexity of the circuits. The complexity is analysed and discussed with regards to how it relates to the potential benefits to the evolutionary process of introducing an indirect genotype-phenotype mapping such as artificial development.     

Neuronal basis of behavior

In addition to describing behavior in terms of neuronal properties and interconnections, some studies are using these well defined neuronal circuits to see how the circuits interact, how they develop, and how they are modified by experience, hormones and neuromodulators. The ready availability of computers and computational techniques has helped in some efforts, as have improvements in physiological and morphological techniques. The major insights, however, still come from experiments that ask clear and direct questions. This review highlights some of the promising approaches and suggests some general features of how neuronal circuits produce behavior.     

Using imaging and genetics in zebrafish to study developing spinal circuits in vivo

Imaging and molecular approaches are perfectly suited to young, transparent zebrafish (Danio rerio), where they have allowed novel functional studies of neural circuits and their links to behavior. Here, we review cutting-edge optical and genetic techniques used to dissect neural circuits in vivo and discuss their application to future studies of developing spinal circuits using living zebrafish. We anticipate that these experiments will reveal general principles governing the assembly of neural circuits that control movements.     

A high accuracy linear rate meter.

By implementing analog computer techniques using digital circuits, an instantaneous rate meter was built with approximately 100 times the accuracy of commercially available rate meters. The circuit is accurate to within +/- 0.2 events/min over a range of rates of 0.2-900 epm. Modifications can be made to provide a digital display of rate. The circuit design techniques used in developing the rate meter may be used to generate a wide variety of functions of time with very high accuracy.     

Spike timing precision of neuronal circuits

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.     

Specificity and randomness in the visual cortex

Research on the functional anatomy of visual cortical circuits has recently zoomed in from the macroscopic level to the microscopic. High-resolution functional imaging has revealed that the functional architecture of orientation maps in higher mammals is built with single-cell precision. By contrast, orientation selectivity in rodents is dispersed on visual cortex in a salt-and-pepper fashion, despite highly tuned visual responses. Recent studies of synaptic physiology indicate that there are disjoint subnetworks of interconnected cells in the rodent visual cortex. These intermingled subnetworks, described in vitro, may relate to the intermingled ensembles of cells tuned to different orientations, described in vivo. This hypothesis may soon be tested with new anatomic techniques that promise to reveal the detailed wiring diagram of cortical circuits.     

Development of larval motor circuits in Drosophila

How are functional neural circuits formed during development? Despite recent advances in our understanding of the development of individual neurons, little is known about how complex circuits are assembled to generate specific behaviors. Here, we describe the ways in which Drosophila motor circuits serve as an excellent model system to tackle this problem. We first summarize what has been learned during the past decades on the connectivity and development of component neurons, in particular motor neurons and sensory feedback neurons. We then review recent progress in our understanding of the development of the circuits as well as studies that apply optogenetics and other innovative techniques to dissect the circuit diagram. New approaches using Drosophila as a model system are now making it possible to search for developmental rules that regulate the construction of neural circuits.     

Beyond directed evolution: Darwinian selection as a tool for synthetic biology

Synthetic biology is an engineering approach that seeks to design and construct new biological parts, devices and systems, as well as to re-design existing components. However, rationally designed synthetic circuits may not work as expected due to the context-dependence of biological parts. Darwinian selection, the main mechanism through which evolution works, is a major force in creating biodiversity and may be a powerful tool for synthetic biology. This article reviews selection-based techniques and proposes strict Darwinian selection as an alternative approach for the identification and characterization of parts. Additionally, a strategy for fine-tuning of relatively complex circuits by coupling them to a master standard circuit is discussed.     

The zebrafish brain in research and teaching: a simple in vivo and in vitro model for the study of spontaneous neural activity

Recently, the zebrafish (Danio rerio) has been established as a key animal model in neuroscience. Behavioral, genetic, and immunohistochemical techniques have been used to describe the connectivity of diverse neural circuits. However, few studies have used zebrafish to understand the function of cerebral structures or to study neural circuits. Information about the techniques used to obtain a workable preparation is not readily available. Here, we describe a complete protocol for obtaining in vitro and in vivo zebrafish brain preparations. In addition, we performed extracellular recordings in the whole brain, brain slices, and immobilized nonanesthetized larval zebrafish to evaluate the viability of the tissue. Each type of preparation can be used to detect spontaneous activity, to determine patterns of activity in specific brain areas with unknown functions, or to assess the functional roles of different neuronal groups during brain development in zebrafish. The technique described offers a guide that will provide innovative and broad opportunities to beginner students and researchers who are interested in the functional analysis of neuronal activity, plasticity, and neural development in the zebrafish brain.     

Identifying roles for neurotransmission in circuit assembly: insights gained from multiple model systems and experimental approaches

In the adult nervous system, chemical neurotransmission between neurons is essential for information processing. However, neurotransmission is also important for patterning circuits during development, but its precise roles have yet to be identified, and some remain highly debated. Here, we highlight viewpoints that have come to be widely accepted or still challenged. We discuss how distinct techniques and model systems employed to probe the developmental role of neurotransmission may reconcile disparate ideas. We underscore how the effects of perturbing neurotransmission during development vary with model systems, the stage of development when transmission is altered, the nature of the perturbation, and how connectivity is assessed. Based on findings in circuits with connectivity arranged in layers, we raise the possibility that there exist constraints in neuronal network design that limit the role of neurotransmission. We propose that activity-dependent mechanisms are effective in refining connectivity patterns only when inputs from different cells are close enough, spatially, to influence each other's outcome.     

Advances in construction and modeling of functional neural circuits in vitro

Neurochemical Research - Over the years, techniques have been developed to culture and assemble neurons, which brought us closer to creating neuronal circuits that functionally and structurally...     

Knowing a nascent synapse when you see it

To understand brain development, we must learn how synapse formation shapes functional neural circuits. At the heart of this process lies the nascent synapse--an enigmatic structure spanning the developmental gap between initial cell-cell contact and the mature synapse. New experimental techniques are beginning to illuminate the processes involved in synaptogenesis, but much remains to be learned, including simply how to recognize the synapse in its nascent form.     

A novel fluorescent tracer for visualizing coupled cells in neural circuits of living tissue.

Gap junctions have diverse roles in a wide variety of tissues and have recently become a subject of intense investigation in neural circuits where synchrony and oscillations may play an important part. In circuits where gap junctions are present, the possibility arises of identifying intercommunicating cells via introduction of tracer into one cell and observing its spread into its coupled neighbors. Staining the coupled cells by this means opens the door to many vital techniques including paired-cell electrophysiology, RT-PCR, and morphological characterization of previously unknown coupled cells. Tracers commonly used at the present time are not generally suitable for these purposes in many tissues, including neurons. This paper describes how a fluorescent nuclear tracer, Po-pro-1, can be used to visualize coupled cells in several types of retinal neurons thought to be comprised of different connexin proteins including Cx36, Cx45, Cx50, and Cx57.     

Computer-assisted measurement of biomechanical values exemplified by the renovascular system

The high innovation in electronics and measuring techniques has influenced the development of medical equipment. The progressive miniaturization of integrated circuits yields in an increased possibility of functions with the respective technical equipments. Therewith also in medical technology more universal equipments are available. Unfortunately the development of sensors did not match the development rate in microelectronics. Hence computer-aided measuring (indirect measuring) becomes more and more important, to pick up normally non-measurable biomechanical quantities, which will be shown for the case study of the renovascular system.     

Inhibiting the Activity of CA1 Hippocampal Neurons Prevents the Recall of Contextual Fear Memory in Inducible ArchT Transgenic Mice

The optogenetic manipulation of light-activated ion-channels/pumps (i.e., opsins) can reversibly activate or suppress neuronal activity with precise temporal control. Therefore, optogenetic techniques hold great potential to establish causal relationships between specific neuronal circuits and their function in freely moving animals. Due to the critical role of the hippocampal CA1 region in memory function, we explored the possibility of targeting an inhibitory opsin, ArchT, to CA1 pyramidal neurons in mice. We established a transgenic mouse line in which tetracycline trans-activator induces ArchT expression. By crossing this line with a CaMKIIα-tTA transgenic line, the delivery of light via an implanted optrode inhibits the activity of excitatory CA1 neurons. We found that light delivery to the hippocampus inhibited the recall of a contextual fear memory. Our results demonstrate that this optogenetic mouse line can be used to investigate the neuronal circuits underlying behavior.     

Microfabrication using focused ion beams part II

Soon all semiconductor devices could be made this way is a claim often made for focused ion beam technology. As the Osaka University team relates in this overview, numerous labs around the world have used FIB to dope, deposit, etch and define semiconductor and other films to microfabricate circuits and devices. FIB has yet to become a routine method but the techniques under this banner hold much promise for the production of next generation devices.     

Illuminating neural circuits and behaviour in Caenorhabditis elegans with optogenetics

The development of optogenetics, a family of methods for using light to control neural activity via light-sensitive proteins, has provided a powerful new set of tools for neurobiology. These techniques have been particularly fruitful for dissecting neural circuits and behaviour in the compact and transparent roundworm Caenorhabditis elegans. Researchers have used optogenetic reagents to manipulate numerous excitable cell types in the worm, from sensory neurons, to interneurons, to motor neurons and muscles. Here, we show how optogenetics applied to this transparent roundworm has contributed to our understanding of neural circuits.     

Optogenetic approaches in neuroscience

The recently introduced term 'optogenetics' describes a variety of techniques for expressing genes in nerve cells that render them responsive to light. This approach makes use of light-sensitive channel proteins that can be used to manipulate neuronal function. Using genetic strategies, these channel proteins can be expressed in neurons defined by a common genetic identity, which can then be selectively activated or silenced through illumination. In?this minireview, we shall describe the basic principles of such manipulative optogenetic approaches in neuroscience and summarize how these tools are being exploited to investigate neuronal circuits and behavior.