How the brain keeps the eyes still

The brain can hold the eyes still because it stores a memory of eye position. The brain’s memory of horizontal eye position appears to be represented by persistent neural activity in a network known as the neural integrator, which is localized in the brainstem and cerebellum. Existing experimental data are reinterpreted as evidence for an “attractor hypothesis” that the persistent patterns of activity observed in this network form an attractive line of fixed points in its state space. Line attractor dynamics can be produced in linear or nonlinear neural networks by learning mechanisms that precisely tune positive feedback.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Modeling the dynamics of human hair cycles by a follicular automaton

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

Catalytic mechanism of the adenylyl and guanylyl cyclases: Modeling and mutational analysis

The adenylyl and guanylyl cyclases catalyze the formation of 3′,5′-cyclic adenosine or guanosine monophosphate from the corresponding nucleoside 5′-triphosphate. The guanylyl cyclases, the mammalian adenylyl cyclases, and their microbial homologues function as pairs of homologous catalytic domains. The crystal structure of the rat type II adenylyl cyclase C2 catalytic domain was used to model by homology a mammalian adenylyl cyclase C1-C2 domain pair, a homodimeric adenylyl cyclase of Dictyostelium discoideum, a heterodimeric soluble guanylyl cyclase, and a homodimeric membrane guanylyl cyclase. Mg2+ATP or Mg2+GTP were docked into the active sites based on known stereochemical constraints on their conformation. The models are consistent with the activities of seven active-site mutants. Asp-310 and Glu-432 of type I adenylyl cyclase coordinate a Mg2+ ion. The D310S and D310A mutants have 10-fold reduced Vmax and altered [Mg2+] dependence. The NTP purine moieties bind in mostly hydrophobic pockets. Specificity is conferred by a Lys and an Asp in adenylyl cyclase, and a Glu, an Arg, and a Cys in guanylyl cyclase. The models predict that an Asp from one domain is a general base in the reaction, and that the transition state is stabilized by a conserved Asn-Arg pair on the other domain.

Data assimilation and its applications

In data assimilation, one prepares the grid data as the best possible estimate of the true initial state of a considered system by merging various measurements irregularly distributed in space and time, with a prior knowledge of the state given by a numerical model. Because it may improve forecasting or modeling and increase physical understanding of considered systems, data assimilation now plays a very important role in studies of atmospheric and oceanic problems. Here, three examples are presented to illustrate the use of new types of observations and the ability of improving forecasting or modeling.

X-ray structure determination of a metastable state of carbonmonoxy myoglobin after photodissociation.

The x-ray structure of carbon monoxide (CO)-ligated myoglobin illuminated during data collection by a laser diode at the wavelength lambda = 690 nm has been determined to a resolution of 1.7 A at T = 36 K. For comparison, we also measured data sets of deoxymyoglobin and CO-ligated myoglobin. In the photon-induced structure the electron density associated with the CO ligand can be described by a tube extending from the iron into the heme pocket over more than 4 A. This density can be interpreted by two discrete positions of the CO molecule. One is close to the heme iron and can be identified to be bound CO. In the second, the CO is dissociated from the heme iron and lies on top of pyrrole ring C. At our experimental conditions the overall structure of myoglobin in the metastable state is close to the structure of a CO-ligated molecule. However, the iron has essentially relaxed into the position of deoxymyoglobin. We compare our results with those of Schlichting el al. [Schlichting, I., Berendzen, J., Phillips, G. N., Jr., & Sweet, R. M. (1994) Nature 317, 808-812], who worked with the myoglobin mutant (D122N) that crystallizes in the space group P6 and Teng et al. [Teng, T. Y., Srajer, V. & Moffat, K. (1994) Nat. Struct. Biol. 1, 701-705], who used native myoglobin crystals of the space group P2(1). Possible reasons for the structural differences are discussed.

State of the art in continuous speech recognition.

In the past decade, tremendous advances in the state of the art of automatic speech recognition by machine have taken place. A reduction in the word error rate by more than a factor of 5 and an increase in recognition speeds by several orders of magnitude (brought about by a combination of faster recognition search algorithms and more powerful computers), have combined to make high-accuracy, speaker-independent, continuous speech recognition for large vocabularies possible in real time, on off-the-shelf workstations, without the aid of special hardware. These advances promise to make speech recognition technology readily available to the general public. This paper focuses on the speech recognition advances made through better speech modeling techniques, chiefly through more accurate mathematical modeling of speech sounds.