Spatial navigation and multiscale representation by hippocampal place cells

Hippocampal lesions are known to impair success in navigation tasks. While such tasks could be solved by memorizing complete paths from a starting location to the goal, animals still perform successfully when placed in a novel starting position. We propose a navigation algorithm to solve the latter problem by exploiting two facts about hippocampal organization: (1) The size of the place fields of hippocampal place cells varies systematically along the dorsoventral axis, with dorsal place cells having smaller place fields than ventral (Kjelstrup et. al. 2008); and (2) the theta oscillation propagates as a traveling wave from dorsal to ventral hippocampus (Lubenov and Siapas, 2009). Taken together, these observations imply that the hippocampal representation of space progresses from fine- to coarse-grained within every theta cycle. 

The algorithm assumes that place cells can be activated by the animal's imagining a goal location, in addition to physically standing in the appropriate location. In the proposed algorithm, place cell activation propagates from small scale to large scale until place cells are found which respond strongly to both the physical location and the goal location. These place fields have their centers aligned roughly in the direction of the goal, providing a crude estimate of which direction the animal should step to approach the goal. Fine-grained directional information is contained in the smaller scale place fields within these large ones. Our algorithm therefore identifies a sequence of place cells, one from each scale, whose centers lie roughly along the line to the goal. 

Simulations reveal successful navigation to the goal, even around obstacles. By minimizing the number of steps the animal takes to reach the goal, we predict the organization of the optimal place field "map"; specifically the fraction of place cells which should be allocated to each spatial scale. This prediction is, in principle, experimentally testable.

The set of place fields with centers lying along a line to the goal is used to compute a step direction by maximizing the probability that those cells will be active in the next time step, given that a particular step direction is chosen.

The proposed algorithm handles navigation around obstacles by including "border cells" (Solstad et. al. 2008) which inhibit place cells in proportion to the degree of overlap between the place field and the obstacle. Furthermore, including firing rate adaptation of place cells prevents the animal from getting stuck in one spot

Nystrom Methods in the RKQ Algorithm for Initial-value Problems

We incorporate explicit Nystrom methods into the RKQ algorithm for stepwise global error control in numerical solutions of initial-value problems. The initial-value problem is transformed into an explicitly second-order problem, so as to be suitable for Nystrom integration. The Nystrom methods used are fourth-order, fifth-order and 10th-order. Two examples demonstrate the effectiveness of the algorithm.Comment: This is an extension of ideas published in J. Math. Res. (open access); see refs [1] and [2

Validation and clinical application of molecular methods for the identification of molds in tissue

Background. Invasive fungal infections due to less-common molds are an increasing problem, and accurate diagnosis is difficult.Methods. We used our previously established molecular method, which allows species identification of molds in histological tissue sections, to test sequential specimens from 56 patients with invasive fungal infections who were treated at our institution from 1982 to 2000.Results. The validity of the method was demonstrated with the establishment of a molecular diagnosis in 52 cases (93%). Confirmation of the causative organism was made in all cases in which a mold had been cultured from the tissue specimen. Less-common molds were identified in 7% of cases and appear to be an increasing problem.Conclusions. Our previously established method has proven to be of value in determining the incidence of invasive infection caused by less-common molds. Institutions should continue to pursue diagnosis of invasive fungal infections by means of tissue culture and microbiologic analysis

Breaking the color-reddening degeneracy in type Ia supernovae

A new method to study the intrinsic color and luminosity of type Ia supernovae (SNe Ia) is presented. A metric space built using principal component analysis (PCA) on spectral series SNe Ia between -12.5 and +17.5 days from B maximum is used as a set of predictors. This metric space is built to be insensitive to reddening. Hence, it does not predict the part of color excess due to dust-extinction. At the same time, the rich variability of SN Ia spectra is a good predictor of a large fraction of the intrinsic color variability. Such metric space is a good predictor of the epoch when the maximum in the B-V color curve is reached. Multivariate Partial Least Square (PLS) regression predicts the intrinsic B band light-curve and the intrinsic B-V color curve up to a month after maximum. This allows to study the relation between the light curves of SNe Ia and their spectra. The total-to-selective extinction ratio RV in the host-galaxy of SNe Ia is found, on average, to be consistent with typical Milky-Way values. This analysis shows the importance of collecting spectra to study SNe Ia, even with large sample publicly available. Future automated surveys as LSST will provide a large number of light curves. The analysis shows that observing accompaning spectra for a significative number of SNe will be important even in the case of "normal" SNe Ia.Comment: 11 pages, 11 figure

Synthesis of empty bacterial microcompartments, directed organelle protein incorporation, and evidence of filament-associated organelle movement

Compartmentalization is an important process, since it allows the segregation of metabolic activities and, in the era of synthetic biology, represents an important tool by which defined microenvironments can be created for specific metabolic functions. Indeed, some bacteria make specialized proteinaceous metabolic compartments called bacterial microcompartments (BMCs) or metabolosomes. Here we demonstrate that the shell of the metabolosome (representing an empty BMC) can be produced within E. coil cells by the coordinated expression of genes encoding structural proteins. A plethora of diverse structures can be generated by changing the expression profile of these genes, including the formation of large axial filaments that interfere with septation. Fusing GFP to PduC, PduD, or PduV, none of which are shell proteins, allows regiospecific targeting of the reporter group to the empty BMC. Live cell imaging provides unexpected evidence of filament-associated BMC movement within the cell in the presence of Pdu

Retinal adaptation to spatial correlations

The classical center-surround retinal ganglion cell receptive field is thought to remove the strong spatial correlations in natural scenes, enabling efficient use of limited bandwidth. While early studies with drifting gratings reported robust surrounds (Enroth-Cugell and Robson, 1966), recent measurements with white noise reveal weak surrounds (Chichilnisky and Kalmar, 2002). This might be evidence for dynamical weakening of the retinal surround in response to decreased spatial correlations, which would be predicted by efficient coding theory. Such adaptation is reported in LGN (Lesica et al., 2007), but whether the retina also adapts to correlations is unknown. 

We tested for adaptation by recording simultaneously from ~40 ganglion cells on a multi-electrode array while presenting white and exponentially correlated checkerboards and strips. Measuring from ~200 cells responding to 90 minutes each of white and correlated stimuli, we were able to extract precise spatiotemporal receptive fields (STRFs). We found that a difference-of-Gaussians was not a good fit and the surround was generally displaced from the center. Thus, to assess surround strength we found the center and surround regions and the total weight on the pixels in each region. The relative surround strength was then defined as the ratio of surround weight to center weight. Surprisingly, we found that the majority of recorded cells have a stronger surround under white noise than under correlated noise (p<.05), contrary to naive expectation from theory. The conclusion was robust to different methods of extracting STRFs and persisted with checkerboard and strip stimuli.

To test, without assuming a model, whether the retina decorrelates stimuli, we also measured the pairwise correlations between spike trains of simultaneously recorded neurons under three conditions: white checkerboard, exponentially correlated noise, and scale-free noise. The typical amount of pairwise correlation increased with extent of input correlation, in line with our STRF measurements

Remote sensing in Michigan for land resource management

The Environmental Research Institute of Michigan is conducting a program whose goal is the large-scale adoption, by both public agencies and private interests in Michigan, of NASA earth-resource survey technology as an important aid in the solution of current problems in resource management and environmental protection. During the period from June 1975 to June 1976, remote sensing techniques to aid Michigan government agencies were used to achieve the following major results: (1) supply justification for public acquisition of land to establish the St. John's Marshland Recreation Area; (2) recommend economical and effective methods for performing a statewide wetlands survey; (3) assist in the enforcement of state laws relating to sand and gravel mining, soil erosion and sedimentation, and shorelands protection; (4) accomplish a variety of regional resource management actions in the East Central Michigan Planning and Development Region. Other tasks on which remote sensing technology was used include industrial and school site selection, ice detachment in the Soo Harbor, grave detection, and data presentation for wastewater management programs

Transformation of stimulus correlations by the retina

Redundancies and correlations in the responses of sensory neurons seem to waste neural resources but can carry cues about structured stimuli and may help the brain to correct for response errors. To assess how the retina negotiates this tradeoff, we measured simultaneous responses from populations of ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure. We found that pairwise correlations in the retinal output remained similar across stimuli with widely different spatio-temporal correlations including white noise and natural movies. Meanwhile, purely spatial correlations tended to increase correlations in the retinal response. Responding to more correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the similarity of pairwise correlations across stimuli where receptive field measurements were possible.Comment: author list corrected in metadat