Genetically encoded, single-component optogenetic tools have made a significant impact on neuroscience, enabling specific modulation of selected cells within complex neural tissues. As the optogenetic toolbox contents grow and diversify, the opportunities for neuroscience continue to grow. In this review, we outline the development of currently available single-component optogenetic tools and summarize the application of various optogenetic tools in diverse model organisms.

/pdf/the-development-and-application-of-optogenetics-49rsxufk6s.pdf

The Development and Application of Optogenetics

Studies in fruit flies have greatly aided our understanding of the nervous system. Bellen and colleagues take us through the key findings in the last century. They argue that thanks to the unmatched wealth of tools that can be used inDrosophila melanogaster, research in flies will continue to contribute to many aspects of vertebrate neuroscience. Discoveries in fruit flies have greatly contributed to our understanding of neuroscience. The use of an unparalleled wealth of tools, many of which originated between 1910–1960, has enabled milestone discoveries in nervous system development and function. Such findings have triggered and guided many research efforts in vertebrate neuroscience. After 100 years, fruit flies continue to be the choice model system for many neuroscientists. The combinational use of powerful research tools will ensure that this model organism will continue to lead to key discoveries that will impact vertebrate neuroscience.

/pdf/100-years-of-drosophila-research-and-its-impact-on-2hb7nfqd0q.pdf

100 years of Drosophila research and its impact on vertebrate neuroscience: a history lesson for the future

http://genetics.wustl.edu/bio5491/files/2012/02/Venken_Bellen_2011.pdf

Genetic Manipulation of Genes and Cells in the Nervous System of the Fruit Fly

This is probably the most popular design of experiments (DOE) book. It is unquestionably the leading DOE book in industry. So I am excepting it from the usual disdain I show for the  fth edition (5E) of any book, even though it follows the fourth edition (4E) by only four years. See Grice (2000) for a report on the 4E. Very likely this book bears little resemblance to the  rst edition way back in the 1970s. The author has taken particular care with this latest edition to reorganize the book to be consistent with modern DOE practice rather than classical DOE presentation. The primary change has been to move the chapters on regression modeling and response surface methods forward in the book. In the 4E these were the last two chapters in the book. In the 5E they follow the chapters on factorial and fractional factorial designs. Three chapters on “other designs” now close out the book. This certainly gives the book a better  ow for industry short courses. Perhaps these will simply be referenced as arcane methods in the sixth edition! Other production values in the book also continue to improve. There are many high-quality graphical displays. There is much use of printouts from Minitab and Design-Expert. A student version of Design-Export comes with the book. There is also an instructor’s CD-ROM with supplemental material to make the book suitable for more advanced courses. There is the now-essential Web site that has more information to help students and instructors. Perhaps if I were teaching DOE for master’s-level statisticians, the recent book by Dean and Voss (1999), reviewed by Amidan (2000), would be my choice. However, for most other audiences this is the complete DOE book. Industrial statisticians should get a copy of the new version and ensure its exposure to the relevant people in their organization.

Introduction to the Practice of Statistics

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

Visually guided collision avoidance is critical for the survival of many animals. The execution of successful collision-avoidance behaviors requires accurate processing of approaching threats by the visual system and signaling of threat characteristics to motor circuits to execute appropriate motor programs in a timely manner. Consequently, visually guided collision avoidance offers an excellent model with which to study the neural mechanisms of sensory-motor integration in the context of a natural behavior. Neurons that selectively respond to approaching threats and brain areas processing them have been characterized across many species. In locusts in particular, the underlying sensory and motor processes have been analyzed in great detail: These animals possess an identified neuron, called the LGMD, that responds selectively to approaching threats and conveys that information through a second identified neuron, the DCMD, to motor centers, generating escape jumps. A combination of behavioral and in vivo ...

Collision Detection as a Model for Sensory-Motor Integration

https://www.cell.com/neuron/pdf/S0896-6273(10)00992-X.pdf

Multiplexing of Motor Information in the Discharge of a Collision Detecting Neuron during Escape Behaviors

The firing patterns of visual neurons tracking approaching objects need to be translated into appropriate motor activation sequences to generate escape behaviors. Locusts possess an identified neuron highly sensitive to approaching objects (looming stimuli), thought to play an important role in collision avoidance through its motor projections. To study how the activity of this neuron relates to escape behaviors, we monitored jumps evoked by looming stimuli in freely behaving animals. By comparing electrophysiological and high-speed video recordings, we found that the initial preparatory phase of jumps occurs on average during the rising phase of the firing rate of the looming-sensitive neuron. The coactivation period of leg flexors and extensors, which is used to store the energy required for the jump, coincides with the timing of the peak firing rate of the neuron. The final preparatory phase occurs after the peak and takeoff happens when the firing rate of the looming-sensitive neuron has decayed to <10% of its peak. Both the initial and the final preparatory phases and takeoff are triggered when the approaching object crosses successive threshold angular sizes on the animal's retina. Our results therefore suggest that distinct phases of the firing patterns of individual sensory neurons may actively contribute to distinct phases of complex, multistage motor behaviors.

https://www.jneurosci.org/content/jneuro/27/37/10047.full.pdf

Relationship between the Phases of Sensory and Motor Activity during a Looming-Evoked Multistage Escape Behavior

Drosophila melanogaster exhibits a robust escape response to objects approaching on a collision course. Although a pair of large command interneurons called the giant fibers (GFs) have been postulated to trigger such behaviors, their role has not been directly demonstrated. Here, we show that escape from visual stimuli like those generated by approaching predators does not rely on the activation of the GFs and consists of a more complex and less stereotyped motor sequence than that evoked by the GFs. Instead, the timing of escape is tightly correlated with the activity of previously undescribed descending interneurons that signal a threshold angular size of the approaching object. The activity pattern of these interneurons shares features with those of visual escape circuits of several species, including pigeons, frogs, and locusts, and may therefore have evolved under similar constraints. These results show that visually evoked escapes in Drosophila can rely on at least two descending neuronal pathways: the GFs and the novel pathway we characterize electrophysiologically. These pathways exhibit very different patterns of sensory activity and are associated with two distinct motor programs.

https://www.physiology.org/doi/pdf/10.1152/jn.00073.2009

A Novel Neuronal Pathway for Visually Guided Escape in Drosophila melanogaster

We have developed miniature telemetry systems that capture neural, EMG, and acceleration signals from a freely moving insect or other small animal and transmit the data wirelessly to a remote digital receiver. The systems are based on custom low-power integrated circuits (ICs) that amplify, filter, and digitize four biopotential signals using low-noise circuits. One of the chips also digitizes three acceleration signals from an off-chip microelectromechanical-system accelerometer. All information is transmitted over a wireless ~ 900-MHz telemetry link. The first unit, using a custom chip fabricated in a 0.6- μm BiCMOS process, weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts as well as transdermal potentials in weakly swimming electric fish. The second unit, using a custom chip fabricated in a 0.35-μ m complementary metal-oxide semiconductor CMOS process, weighs 0.17 g and runs for five hours on a single 1.5-V battery. This system has been used to monitor neural potentials in untethered perching dragonflies.

Haleh Fotowat

Papers

Collision Detection as a Model for Sensory-Motor Integration

Multiplexing of Motor Information in the Discharge of a Collision Detecting Neuron during Escape Behaviors

Relationship between the Phases of Sensory and Motor Activity during a Looming-Evoked Multistage Escape Behavior

A Novel Neuronal Pathway for Visually Guided Escape in Drosophila melanogaster

Wireless Neural/EMG Telemetry Systems for Small Freely Moving Animals