Optogenetics in neural systems

Both observational and perturbational technologies are essential for advancing the understanding of brain function and dysfunction. But while observational techniques have greatly advanced in the last century, techniques for perturbation that are matched to the speed and heterogeneity of neural systems have lagged behind. The technology of optogenetics represents a step toward addressing this disparity. Reliable and targetable single-component tools (which encompass both light sensation and effector function within a single protein) have enabled versatile new classes of investigation in the study of neural systems. Here we provide a primer on the application of optogenetics in neuroscience, focusing on the single-component tools and highlighting important problems, challenges, and technical considerations.     

Degenerate coding in neural systems

When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discuss three different neural systems that are linked by this theme. The pyloric network of the lobster, the song control system of the zebra finch, and the odor encoding system of the locust, while different in design, all contain degeneracies between their internal parameters and the outputs they encode. Indeed, although the dynamics of song generation and odor identification are quite different, computationally, odor recognition can be thought of as running the song generation circuitry backwards. In both of these systems, degeneracy plays a vital role in mapping a sparse neural representation devoid of correlations onto external stimuli (odors or song structure) that are strongly correlated. I argue that degeneracy between input and output states is an inherent feature of many neural systems, which can be exploited as a fault-tolerant method of reliably learning, generating, and discriminating closely related patterns.     

Generation and regulation of developing immortalized neural cell lines

The genetic and environmental signals that regulate progressive lineage elaboration in the mammalian brain are poorly understood. In addition, characterization of the developmental profiles of early central nervous system (CNS) stem/ progenitor cells and analysis of the mechanisms involved in their clonal expansion, lineage restriction, and cellular maturation have been fragmentary and elusive. These seminal neurodevelopmental issues have been examined using a series of clonally derived neural stem/progenitor cell lines established by retroviral transduction of embryonic (E16.5-E17.5) murine hippocampal and cerebellar cells using temperature-sensitive alleles (A58/U19) of the simian virus (SV) 40 large tumor (T) antigen. Under conditions permissive for T-antigen expression (33 degrees C), single neural stem cells exhibited self-renewal, clonal expansion, and both symmetric and asymmetric modes of cell division. By contrast, at the nonpermissive temperature for T-antigen expression (39 degrees C), specific sets of cytokines potentiated the progressive elaboration of neuronal, oligodendroglial, and astroglial lineage species. These observations demonstrate that a spectrum of genetic and epigenetic signals and distinct cellular processes are involved in orchestrating the evolution of individual neural lineages from regional CNS stem/progenitor species. Further, the availability of conditionally immortalized neural cell lines that can be transplanted back into the mammalian brain may represent an important experimental resource for the detailed characterization of cellular and molecular mechanisms involved in the developmental sculpting, plasticity, and regeneration of the mammalian CNS.     

Causal networks in simulated neural systems

Neurons engage in causal interactions with one another and with the surrounding body and environment. Neural systems can therefore be analyzed in terms of causal networks, without assumptions about information processing, neural coding, and the like. Here, we review a series of studies analyzing causal networks in simulated neural systems using a combination of Granger causality analysis and graph theory. Analysis of a simple target-fixation model shows that causal networks provide intuitive representations of neural dynamics during behavior which can be validated by lesion experiments. Extension of the approach to a neurorobotic model of the hippocampus and surrounding areas identifies shifting causal pathways during learning of a spatial navigation task. Analysis of causal interactions at the population level in the model shows that behavioral learning is accompanied by selection of specific causal pathways—“causal cores”—from among large and variable repertoires of neuronal interactions. Finally, we argue that a causal network perspective may be useful for characterizing the complex neural dynamics underlying consciousness.

Pattern computation in neural communication systems

Biological data suggests that activity patterns emerging in small- and large-scale neural systems may play an important role in performing the functions of the neural system, and in particular, neural computations. It is proposed in this paper that neural systems can be understood in terms of pattern computation and abstract communication systems theory. It is shown that analysing high-resolution surface EEG data, it is possible to determine abstract probabilistic rules that describe how emerging activity patterns follow earlier activity patterns. The results indicate the applicability of the proposed approach for understanding the working of complex neural systems.     

Signal stabilization and noise suppression in neural systems

Summary Neural activity is viewed as a stochastic point process, in which information resides in the modulation of a background of spontaneous activity. Characteristic features of the spatial and temporal mapping of sensory signals are discussed. One of the puzzling aspects of neural functioning is the integrity of the signal in its passage toward higher brain centers, in view of the fundamentally noisy response of the individual neuron. It is shown, that a process, we call image stabilization, is a direct consequence of the particular mapping function exemplified by lateral inhibition and adaptation.The research reported in this paper was sponsored by the Aerospace Medical Research Laboratories, Aerospace Medical Division, Air Force Systems Command, Wright-Patterson Air Force Base, Ohio, under contract No. F 33615-67-C-1413 and the Office of Naval Research, contract No. ONR N0001467-A-0378-0001, with Syracuse University Research Institute. Further reproduction is authorized to satisfy needs of the U.S. Government.     

Basal ganglia neural mechanisms of natural movement sequences

Natural rodent grooming and other instinctive behavior serves as a natural model of complex movement sequences. Rodent grooming has syntactic (rule-driven) sequences and more random movement patterns. Both incorporate the same movements--only the serial structure differs. Recordings of neural activity in the dorsolateral striatum and the substantia nigra pars reticulata indicate preferential activation during syntactic sequences over more random sequences. Neurons that are responsive during syntactic grooming sequences are often unresponsive or have reverse activation profiles during kinematically similar movements that occur in flexible or random grooming sequences. Few neurons could be categorized as strictly movement related--instead they were activated only in the context of particular sequential patterns of movements. Particular sequential patterns included "syntactic chain" grooming sequences of paw, head, and body movements and also "warm-up" sequences, which consist of head and body/limb movements that precede locomotion after a period of quiet resting (Golani 1992). Activation during warm-up was less intense and less frequent than during grooming sequences, but both sequences activated neurons above baseline levels, and the same neurons sometimes responded to both sequences. The fact that striatal neurons code 2 natural sequences which are made up of different constituent movements suggests that the basal ganglia may have a generalized role in sequence control. The basal ganglia are modulated by the context of the sequence and may play an executive function in the complex natural patterns of sequenced behaviour.     

Self-organized neural maps of human protein sequences.

We have recently described a method based on artificial neural networks to cluster protein sequences into families. The network was trained with Kohonen''s unsupervised learning algorithm using, as inputs, the matrix patterns derived from the dipeptide composition of the proteins. We present here a large-scale application of that method to classify the 1,758 human protein sequences stored in the SwissProt database (release 19.0), whose lengths are greater than 50 amino acids. In the final 2-dimensional topologically ordered map of 15 x 15 neurons, proteins belonging to known families were associated with the same neuron or with neighboring ones. Also, as an attempt to reduce the time-consuming learning procedure, we compared 2 learning protocols: one of 500 epochs (100 SUN CPU-hours [CPU-h]), and another one of 30 epochs (6.7 CPU-h). A further reduction of learning-computing time, by a factor of about 3.3, with similar protein clustering results, was achieved using a matrix of 11 x 11 components to represent the sequences. Although network training is time consuming, the classification of a new protein in the final ordered map is very fast (14.6 CPU-seconds). We also show a comparison between the artificial neural network approach and conventional methods of biosequence analysis.     

混沌在神经系统中的作用

随着非线性动力学的发展,发现神经的不规则电活动具有确定混沌特性。混沌广泛地存在于神经系统,神经元的混沌电活动对神经元的生理功能必不可少,服电的混沌活动特性与大脑的功能状态密切相关,在大脑正常状态下脑电混沌活动的维数、李雅普指数、复杂度等指标较高;而在服功能受损的病理状态下,上述混沌指标降低。混沌在神经系统中起着重要的作用。     

A neural correlate of oculomotor sequences in supplementary eye field

Complex learned motor sequences can be composed of a combination of a small number of elementary actions. To investigate how the brain represents such sequences, we devised an oculomotor sequence task in which the monkey had to choose the target solely by the sequential context, not by the current stimulus combination. We found that many neurons in the supplementary eye field (SEF) became active with a specific target direction (D neuron) or a specific target/distractor combination (C neuron). Furthermore, such activity was often selective for one among several sequences that included the combination (S neuron). These results suggest that the SEF contributes to the generation of saccades in many learned sequences.     

Prediction of signal peptides in protein sequences by neural networks

We present here a neural network-based method for detection of signal peptides (abbreviation used: SP) in proteins. The method is trained on sequences of known signal peptides extracted from the Swiss-Prot protein database and is able to work separately on prokaryotic and eukaryotic proteins. A query protein is dissected into overlapping short sequence fragments, and then each fragment is analyzed with respect to the probability of it being a signal peptide and containing a cleavage site. While the accuracy of the method is comparable to that of other existing prediction tools, it provides a significantly higher speed and portability. The accuracy of cleavage site prediction reaches 73% on heterogeneous source data that contains both prokaryotic and eukaryotic sequences while the accuracy of discrimination between signal peptides and non-signal peptides is above 93% for any source dataset. As a consequence, the method can be easily applied to genome-wide datasets. The software can be downloaded freely from http://rpsp.bioinfo.pl/RPSP.tar.gz.     

Generation of oligodendroglial progenitors from neural stem cells

To understand how the differentiation of stem cells to oligodendroglial progenitors is regulated, we established cultures of neural stem cells from neonatal rat striatum in the presence of epidermal growth factor (EGF) as free-floating neurospheres that were then exposed to an increasing amount of B104 cell-conditioned medium (B104CM). The resultant cells proliferated in response to B104CM but no longer to EGF. In vitro analysis and transplantation studies indicated that these cells were committed to the oligodendroglial lineage, and they were thus referred to as oligospheres. Further characterization of their expression of early markers, cell cycle, migration, and self-renewal suggests that they were pre-O2A progenitors. RT-PCR analysis indicated that the oligosphere cells expressed mRNAs of platelet-derived growth factor α receptor in addition to fibroblast growth factor receptor but not EGF receptor; the latter two receptor mRNAs were expressed by neurosphere cells. Thus, the progression of stem cells to oligodendroglial progenitors is likely induced by factors in B104CM.     

Generation of neural progenitor cells by chemical cocktails and hypoxia

Neural progenitor cells (NPCs) can be induced from somatic cells by defined factors. Here we report that NPCs can be generated from mouse embryonic fibroblasts by a chemical cocktail, namely VCR (V, VPA, an inhibitor of HDACs; C, CHIR99021, an inhibitor of GSK-3 kinases and R, Repsox, an inhibitor of TGF-β pathways), under a physiological hypoxic condition. These chemical-induced NPCs (ciNPCs) resemble mouse brain-derived NPCs regarding their proliferative and self-renewing abilities, gene expression profiles, and multipotency for different neuroectodermal lineages in vitro and in vivo. Further experiments reveal that alternative cocktails with inhibitors of histone deacetylation, glycogen synthase kinase, and TGF-β pathways show similar efficacies for ciNPC induction. Moreover, ciNPCs can also be induced from mouse tail-tip fibroblasts and human urinary cells with the same chemical cocktail VCR. Thus our study demonstrates that lineage-specific conversion of somatic cells to NPCs could be achieved by chemical cocktails without introducing exogenous factors.     

Generation of nonidentical compartments in vesicular transport systems

How can organelles communicate by bidirectional vesicle transport and yet maintain different protein compositions? We show by mathematical modeling that a minimal system, in which the basic variables are cytosolic coats for vesicle budding and membrane-bound soluble N-ethyl-maleimide–sensitive factor attachment protein receptors (SNAREs) for vesicle fusion, is sufficient to generate stable, nonidentical compartments. A requirement for establishing and maintaining distinct compartments is that each coat preferentially packages certain SNAREs during vesicle budding. Vesicles fuse preferentially with the compartment that contains the highest concentration of cognate SNAREs, thus further increasing these SNAREs. The stable steady state is the result of a balance between this autocatalytic SNARE accumulation in a compartment and the distribution of SNAREs between compartments by vesicle budding. The resulting nonhomogeneous SNARE distribution generates coat-specific vesicle fluxes that determine the size of compartments. With nonidentical compartments established in this way, the localization and cellular transport of cargo proteins can be explained simply by their affinity for coats.