Contrast summation across eyes and space is revealed along the entire dipper function by a "Swiss cheese" stimulus.

Previous contrast discrimination experiments have shown that luminance contrast is summed across ocular (T. S. Meese, M. A. Georgeson, & D. H. Baker, 2006) and spatial (T. S. Meese & R. J. Summers, 2007) dimensions at threshold and above. However, is this process sufficiently general to operate across the conjunction of eyes and space? Here we used a "Swiss cheese" stimulus where the blurred "holes" in sine-wave carriers were of equal area to the blurred target ("cheese") regions. The locations of the target regions in the monocular image pairs were interdigitated across eyes such that their binocular sum was a uniform grating. When pedestal contrasts were above threshold, the monocular neural images contained strong evidence that the high-contrast regions in the two eyes did not overlap. Nevertheless, sensitivity to dual contrast increments (i.e., to contrast increments in different locations in the two eyes) was a factor of ∼1.7 greater than to single increments (i.e., increments in a single eye), comparable with conventional binocular summation. This provides evidence for a contiguous area summation process that operates at all contrasts and is influenced little, if at all, by eye of origin. A three-stage model of contrast gain control fitted the results and possessed the properties of ocularity invariance and area invariance owing to its cascade of normalization stages. The implications for a population code for pattern size are discussed.

Surface microbial consortia from Livarot, a French smear-ripened cheese

The surface microflora (902 isolates) of Livarot cheeses from three dairies was investigated during ripening. Yeasts were mainly identified by Fourier transform infrared spectroscopy. Geotrichum candidum was the dominating yeast among 10 species. Bacteria were identified using Biotype 100 strips, dereplicated by repetitive extragenic palindromic PCR (rep-PCR); 156 representative strains were identified by either BOX-PCR or (GTG) 55-PCR, and when appropriate by 16S rDNA sequencing and SDS-PAGE analysis. Gram-positive bacteria accounted for 65% of the isolates and were mainly assigned to the genera Arthrobacter, Brevibacterium, Corynebacterium, and Staphylococcus. New taxa related to the genera Agrococcus and Leucobacter were found. Yeast and Gram-positive bacteria strains deliberately added as smearing agents were sometimes undetected during ripening. Thirty-two percent of the isolates were Gram-negative bacteria, which showed a high level of diversity and mainly included members of the genera Alcaligenes, Hafnia, Proteus, Pseudomonas, and Psychrobacter. Whatever the milk used (pasteurized or unpasteurized), similar levels of biodiversity were observed in the three dairies, all of which had efficient cleaning procedures and good manufacturing practices. It appears that some of the Gramnegative bacteria identified should now be regarded as potentially useful in some cheese technologies. The assessment of their positive versus negative role should be objectively examined.

Contrast integration over area is extensive: a three-stage model of spatial summation

Classical studies of area summation measure contrast detection thresholds as a function of grating diameter. Unfortunately, (i) this approach is compromised by retinal inhomogeneity and (ii) it potentially confounds summation of signal with summation of internal noise. The Swiss cheese stimulus of T. S. Meese and R. J. Summers (2007) and the closely related Battenberg stimulus of T. S. Meese (2010) were designed to avoid these problems by keeping target diameter constant and modulating interdigitated checks of first-order carrier contrast within the stimulus region. This approach has revealed a contrast integration process with greater potency than the classical model of spatial probability summation. Here, we used Swiss cheese stimuli to investigate the spatial limits of contrast integration over a range of carrier frequencies (1–16 c/deg) and raised plaid modulator frequencies (0.25–32 cycles/check). Subthreshold summation for interdigitated carrier pairs remained strong (~4 to 6 dB) up to 4 to 8 cycles/check. Our computational analysis of these results implied linear signal combination (following square-law transduction) over either (i) 12 carrier cycles or more or (ii) 1.27 deg or more. Our model has three stages of summation: short-range summation within linear receptive fields, medium-range integration to compute contrast energy for multiple patches of the image, and long-range pooling of the contrast integrators by probability summation. Our analysis legitimizes the inclusion of widespread integration of signal (and noise) within hierarchical image processing models. It also confirms the individual differences in the spatial extent of integration that emerge from our approach.

Area summation of first- and second-order modulations of luminance

To extend our understanding of the early visual hierarchy, we investigated the long-range integration of first- and second-order signals in spatial vision. In our first experiment we performed a conventional area summation experiment where we varied the diameter of (a) luminance-modulated (LM) noise and (b) contrastmodulated (CM) noise. Results from the LM condition replicated previous findings with sine-wave gratings in the absence of noise, consistent with long-range integration of signal contrast over space. For CM, the summation function was much shallower than for LM suggesting, at first glance, that the signal integration process was spatially less extensive than for LM. However, an alternative possibility was that the high spatial frequency noise carrier for the CM signal was attenuated by peripheral retina (or cortex), thereby impeding our ability to observe area summation of CM in the conventional way. To test this, we developed the ''Swiss cheese'' stimulus of Meese and Summers (2007) in which signal area can be varied without changing the stimulus diameter, providing some protection against inhomogeneity of the retinal field. Using this technique and a two-component subthreshold summation paradigm we found that (a) CM is spatially integrated over at least five stimulus cycles (possibly more), (b) spatial integration follows square-law signal transduction for both LM and CM and (c) the summing device integrates over spatially-interdigitated LM and CM signals when they are co-oriented, but not when crossoriented. The spatial pooling mechanism that we have identified would be a good candidate component for amodule involved in representing visual textures, including their spatial extent.

Biodiversity of the surface microbial consortia from Limburger, Reblochon, Livarot, Tilsit, and Gubbeen cheeses

Comprehensive collaborative studies from our laboratories reveal the extensive biodiversity of the microflora of the surfaces of smear-ripened cheeses. Two thousand five hundred ninety-seven strains of bacteria and 2,446 strains of yeasts from the surface of the smear-ripened cheeses Limburger, Reblochon, Livarot, Tilsit, and Gubbeen, isolated at three or four times during ripening, were identified; 55 species of bacteria and 30 species of yeast were found. The microfloras of the five cheeses showed many similarities but also many differences and interbatch variation. Very few of the commercial smear microorganisms, deliberately inoculated onto the cheese surface, were reisolated and then mainly from the initial stages of ripening, implying that smear cheese production units must have an adventitious "house" flora. Limburger cheese had the simplest microflora, containing two yeasts, Debaryomyces hansenii and Geotrichum candidum, and two bacteria, Arthrobacter arilaitensis and Brevibacterium aurantiacum. The microflora of Livarot was the most complicated, comprising 10 yeasts and 38 bacteria, including many gram-negative organisms. Reblochon also had a very diverse microflora containing 8 yeasts and 13 bacteria (excluding gram-negative organisms which were not identified), while Gubbeen had 7 yeasts and 18 bacteria and Tilsit had 5 yeasts and 9 bacteria. D. hansenii was by far the dominant yeast, followed in order by G. candidum, Candida catenulata, and Kluyveromyces lactis. B. aurantiacum was the dominant bacterium and was found in every batch of the 5 cheeses. The next most common bacteria, in order, were Staphylococcus saprophyticus, A. arilaitensis, Corynebacterium casei, Corynebacterium variabile, and Microbacterium gubbeenense. S. saprophyticus was mainly found in Gubbeen, and A. arilaitensis was found in all cheeses but not in every batch. C. casei was found in most batches of Reblochon, Livarot, Tilsit, and Gubbeen. C. variabile was found in all batches of Gubbeen and Reblochon but in only one batch of Tilsit and in no batch of Limburger or Livarot. Other bacteria were isolated in low numbers from each of the cheeses, suggesting that each of the 5 cheeses has a unique microflora. In Gubbeen cheese, several different strains of the dominant bacteria were present, as determined by pulsed-field gel electrophoresis, and many of the less common bacteria were present as single clones. The culture-independent method, denaturing gradient gel electrophoresis, resulted in identification of several bacteria which were not found by the culture-dependent (isolation and rep-PCR identification) method. It was thus a useful complementary technique to identify other bacteria in the cheeses. The gross composition, the rate of increase in pH, and the indices of proteolysis were different in most of the cheeses.