Identification of neural circuits by imaging coherent electrical activity with FRET-based dyes.

We show that neurons that underlie rhythmic patterns of electrical output may be identified by optical imaging and frequency-domain analysis. Our contrast agent is a two-component dye system in which changes in membrane potential modulate the relative emission between a pair of fluorophores. We demonstrate our methods with the circuit responsible for fictive swimming in the isolated leech nerve cord. The output of a motor neuron provides a reference signal for the phase-sensitive detection of changes in fluorescence from individual neurons in a ganglion. We identify known and possibly novel neurons that participate in the swim rhythm and determine their phases within a cycle. A variant of this approach is used to identify the postsynaptic followers of intracellularly stimulated neurons.     

In vitro imaging using laser photostimulation with flavoprotein autofluorescence

Imaging of 300-500 μm mouse brain slices by laser photostimulation with flavoprotein autofluorescence (LFPA) allows the rapid and sensitive mapping of neuronal connectivity. It is accomplished using UV laser-based photo-uncaging of glutamate and imaging neuronal activation by capturing changes in green light (～520 nm) emitted under blue light (～460 nm) excitation. This fluorescence is generated by the oxidized form of flavoprotein and is a measure of metabolic activity. LPFA offers several advantages over imaging techniques that rely on dye loading. First, as flavoprotein imaging measures endogenous signals, it avoids the use of heterogeneously loaded and potentially cytotoxic dyes. Second, flavoprotein signals are large (1-20% above baseline), obviating the need for averaging. Third, the use of photostimulation ensures orthodromic neuronal activation and permits the rapid interrogation of multiple stimulation sites of the slice with a high degree of precision (～50 μm). Here we describe a step-by-step protocol for the incorporation of LPFA into virtually any slice rig, as well as how to do the experiment.     

Genetic dissection of neural circuits

Understanding the principles of information processing in neural circuits requires systematic characterization of the participating cell types and their connections, and the ability to measure and perturb their activity. Genetic approaches promise to bring experimental access to complex neural systems, including genetic stalwarts such as the fly and mouse, but also to nongenetic systems such as primates. Together with anatomical and physiological methods, cell-type-specific expression of protein markers and sensors and transducers will be critical to construct circuit diagrams and to measure the activity of genetically defined neurons. Inactivation and activation of genetically defined cell types will establish causal relationships between activity in specific groups of neurons, circuit function, and animal behavior. Genetic analysis thus promises to reveal the logic of the neural circuits in complex brains that guide behaviors. Here we review progress in the genetic analysis of neural circuits and discuss directions for future research and development.     

Development and evolution of cerebellar neural circuits

The cerebellum controls smooth and skillful movements and it is also involved in higher cognitive and emotional functions. The cerebellum is derived from the dorsal part of the anterior hindbrain and contains two groups of cerebellar neurons: glutamatergic and gamma-aminobutyric acid (GABA)ergic neurons. Purkinje cells are GABAergic and granule cells are glutamatergic. Granule and Purkinje cells receive input from outside of the cerebellum from mossy and climbing fibers. Genetic analysis of mice and zebrafish has revealed genetic cascades that control the development of the cerebellum and cerebellar neural circuits. During early neurogenesis, rostrocaudal patterning by intrinsic and extrinsic factors, such as Otx2, Gbx2 and Fgf8, plays an important role in the positioning and formation of the cerebellar primordium. The cerebellar glutamatergic neurons are derived from progenitors in the cerebellar rhombic lip, which express the proneural gene Atoh1. The GABAergic neurons are derived from progenitors in the ventricular zone, which express the proneural gene Ptf1a. The mossy and climbing fiber neurons originate from progenitors in the hindbrain rhombic lip that express Atoh1 or Ptf1a. Purkinje cells exhibit mediolateral compartmentalization determined on the birthdate of Purkinje cells, and linked to the precise neural circuitry formation. Recent studies have shown that anatomy and development of the cerebellum is conserved between mammals and bony fish (teleost species). In this review, we describe the development of cerebellar neurons and neural circuitry, and discuss their evolution by comparing developmental processes of mammalian and teleost cerebellum.     

Array tomography: a new tool for imaging the molecular architecture and ultrastructure of neural circuits

Many biological functions depend critically upon fine details of tissue molecular architecture that have resisted exploration by existing imaging techniques. This is particularly true for nervous system tissues, where information processing function depends on intricate circuit and synaptic architectures. Here, we describe a new imaging method, called array tomography, which combines and extends superlative features of modern optical fluorescence and electron microscopy methods. Based on methods for constructing and repeatedly staining and imaging ordered arrays of ultrathin (50-200 nm), resin-embedded serial sections on glass microscope slides, array tomography allows for quantitative, high-resolution, large-field volumetric imaging of large numbers of antigens, fluorescent proteins, and ultrastructure in individual tissue specimens. Compared to confocal microscopy, array tomography offers the advantage of better spatial resolution, in particular along the z axis, as well as depth-independent immunofluorescent staining. The application of array tomography can reveal important but previously unseen features of brain molecular architecture.     

Spike timing-dependent plasticity of neural circuits

Recent findings of spike timing-dependent plasticity (STDP) have stimulated much interest among experimentalists and theorists. Beyond the traditional correlation-based Hebbian plasticity, STDP opens up new avenues for understanding information coding and circuit plasticity that depend on the precise timing of neuronal spikes. Here we summarize experimental characterization of STDP at various synapses, the underlying cellular mechanisms, and the associated changes in neuronal excitability and dendritic integration. We also describe STDP in the context of complex spike patterns and its dependence on the dendritic location of the synapse. Finally, we discuss timing-dependent modification of neuronal receptive fields and human visual perception and the computational significance of STDP as a synaptic learning rule.     

Balancing homeostasis and learning in neural circuits

Neural circuits are remarkably adaptable, providing animals with the ability to modify their behavior on the basis of experience. At the same time, they are extremely robust and maintain stability despite the changes associated with adaptation. This combination of adaptability and stability is difficult to achieve, and it provides a strong constraint on any models of plasticity in neural circuits. New evidence suggests that the effect of action potential timing on synaptic plasticity may be an important element in reconciling homeostasis with adaptability. In particular, spike-timing dependent plasticity can act as both an adaptive and a homeostatic mechanism, controlling overall firing rates and distributions of synaptic efficacies while making neurons selective for certain aspects of their inputs. It can also cause networks that initially represent the present state of a stimulus to predict its future state on the basis of experience, a theoretical result supported by experimental data in behaving rats.     

Evolution and development of neural circuits in invertebrates

Developmental mechanisms can shed light on how evolutionary diversity has arisen. Invertebrate nervous systems offer a wealth of diverse structures and functions from which to relate development to evolution. Individual homologous neurons have been shown to have distinct roles in species with different behaviors. In addition, specific neurons have been lost or gained in some phylogenetic lineages. The ability to address the neural basis of behavior at the cellular level in invertebrates has facilitated discoveries showing that species-specific behavior can arise from differences in synaptic strength, in neuronal structure and in neuromodulation. The mechanisms involved in the development of neural circuits lead to these differences across species.     

Development of the cerebellum and cerebellar neural circuits

The cerebellum, a structure derived from the dorsal part of the most anterior hindbrain, is important for integrating sensory perception and motor control. While the structure and development of the cerebellum have been analyzed most extensively in mammals,recent studies have shown that the anatomy and development of the cerebellum is conserved between mammals and bony fish (teleost) species, including zebrafish. In the mammalian and teleost cerebellum,Purkinje and granule cells serve, respectively, as the major GABAergic and glutamatergic neurons. Purkinje cells originate in the ventricular zone (VZ), and receive inputs from climbing fibers. Granule cells originate in the upper rhombic lip (URL) and receive inputs from mossy fibers. Thus, the teleost cerebellum shares many features with the cerebellum of other vertebrates, and isa good model system for studying cerebellar function and development. The teleost cerebellum also has features that are specific to teleosts or have not been elucidated in mammals, including eurydendroid cells and adult neurogenesis. Furthermore, the neural circuitry in part of the optic tectum and the dorsal hindbrain closely resembles the circuitry of the teleost cerebellum; hence,these are called cerebellum-like structures. Here we describe the anatomy and development of cerebellar neurons and their circuitry, and discuss the possible roles of the cerebellum and cerebellum-like structures in behavior and higher cognitive functions. We also consider the potential use of genetics and novel techniques for studying the cerebellum in zebrafish.     

Decision-making neural circuits mediating social behaviors

We propose a mathematical model of a continuous attractor network that controls social behaviors. The model is examined with bifurcation analysis and computer simulations. The results show that the model exhibits stable steady states and thresholds for steady state transitions corresponding to some experimentally observed behaviors, such as aggression control. The performance of the model and the relation with experimental evidence are discussed.     

Redundant neural circuits regulate olfactory integration

Olfactory integration is important for survival in a natural habitat. However, how the nervous system processes signals of two odorants present simultaneously to generate a coherent behavioral response is poorly understood. Here, we characterize circuit basis for a form of olfactory integration in Caenorhabditis elegans. We find that the presence of a repulsive odorant, 2-nonanone, that signals threat strongly blocks the attraction of other odorants, such as isoamyl alcohol (IAA) or benzaldehyde, that signal food. Using a forward genetic screen, we found that genes known to regulate the structure and function of sensory neurons, osm-5 and osm-1, played a critical role in the integration process. Loss of these genes mildly reduces the response to the repellent 2-nonanone and disrupts the integration effect. Restoring the function of OSM-5 in either AWB or ASH, two sensory neurons known to mediate 2-nonanone-evoked avoidance, is sufficient to rescue. Sensory neurons AWB and downstream interneurons AVA, AIB, RIM that play critical roles in olfactory sensorimotor response are able to process signals generated by 2-nonanone or IAA or the mixture of the two odorants and contribute to the integration. Thus, our results identify redundant neural circuits that regulate the robust effect of a repulsive odorant to block responses to attractive odorants and uncover the neuronal and cellular basis for this complex olfactory task.     

Primal-size neural circuits in meta-periodic interaction

Experimental observations of simultaneous activity in large cortical areas have seemed to justify a large network approach in early studies of neural information codes and memory capacity. This approach has overlooked, however, the segregated nature of cortical structure and functionality. Employing graph-theoretic results, we show that, given the estimated number of neurons in the human brain, there are only a few primal sizes that can be attributed to neural circuits under probabilistically sparse connectivity. The significance of this finding is that neural circuits of relatively small primal sizes in cyclic interaction, implied by inhibitory interneuron potentiation and excitatory inter-circuit potentiation, generate relatively long non-repetitious sequences of asynchronous primal-length periods. The meta-periodic nature of such circuit interaction translates into meta-periodic firing-rate dynamics, representing cortical information. It is finally shown that interacting neural circuits of primal sizes 7 or less exhaust most of the capacity of the human brain, with relatively little room to spare for circuits of larger primal sizes. This also appears to ratify experimental findings on the human working memory capacity.     

Computational aspects of feedback in neural circuits

It has previously been shown that generic cortical microcircuit models can perform complex real-time computations on continuous input streams, provided that these computations can be carried out with a rapidly fading memory. We investigate the computational capability of such circuits in the more realistic case where not only readout neurons, but in addition a few neurons within the circuit, have been trained for specific tasks. This is essentially equivalent to the case where the output of trained readout neurons is fed back into the circuit. We show that this new model overcomes the limitation of a rapidly fading memory. In fact, we prove that in the idealized case without noise it can carry out any conceivable digital or analog computation on time-varying inputs. But even with noise, the resulting computational model can perform a large class of biologically relevant real-time computations that require a nonfading memory. We demonstrate these computational implications of feedback both theoretically, and through computer simulations of detailed cortical microcircuit models that are subject to noise and have complex inherent dynamics. We show that the application of simple learning procedures (such as linear regression or perceptron learning) to a few neurons enables such circuits to represent time over behaviorally relevant long time spans, to integrate evidence from incoming spike trains over longer periods of time, and to process new information contained in such spike trains in diverse ways according to the current internal state of the circuit. In particular we show that such generic cortical microcircuits with feedback provide a new model for working memory that is consistent with a large set of biological constraints. Although this article examines primarily the computational role of feedback in circuits of neurons, the mathematical principles on which its analysis is based apply to a variety of dynamical systems. Hence they may also throw new light on the computational role of feedback in other complex biological dynamical systems, such as, for example, genetic regulatory networks.     

Optogenetic investigation of neural circuits in vivo

The recent development of light-activated optogenetic probes allows for the identification and manipulation of specific neural populations and their connections in awake animals with unprecedented spatial and temporal precision. This review describes the use of optogenetic tools to investigate neurons and neural circuits in vivo. We describe the current panel of optogenetic probes, methods of targeting these probes to specific cell types in the nervous system, and strategies of photostimulating cells in awake, behaving animals. Finally, we survey the application of optogenetic tools to studying functional neuroanatomy, behavior and the etiology and treatment of various neurological disorders.     

The dynamical stability of reverberatory neural circuits

The concept of reverberation proposed by Lorente de Nó and Hebb is key to understanding strongly recurrent cortical networks. In particular, synaptic reverberation is now viewed as a likely mechanism for the active maintenance of working memory in the prefrontal cortex. Theoretically, this has spurred a debate as to how such a potentially explosive mechanism can provide stable working-memory function given the synaptic and cellular mechanisms at play in the cerebral cortex. We present here new evidence for the participation of NMDA receptors in the stabilization of persistent delay activity in a biophysical network model of conductance-based neurons. We show that the stability of working-memory function, and the required NMDA/AMPA ratio at recurrent excitatory synapses, depend on physiological properties of neurons and synaptic interactions, such as the time constants of excitation and inhibition, mutual inhibition between interneurons, differential NMDA receptor participation at excitatory projections to pyramidal neurons and interneurons, or the presence of slow intrinsic ion currents in pyramidal neurons. We review other mechanisms proposed to enhance the dynamical stability of synaptically generated attractor states of a reverberatory circuit. This recent work represents a necessary and significant step towards testing attractor network models by cortical electrophysiology.