10.1073͞pnas.0504604102), the authors note that Eq. 1 was incorrectly given as P ϭ f ssͩ ͩ1 ϩ m ͪ ϩ Dͩ 2 ϩ m ͪͪ both in the text and in Fig. 2. The correct equation is as follows:The corrected figure and its legend appear below. The error does not affect the conclusions of the article. Fig. 2.Comprehensive characterization of the promoter library. Several orthogonal metrics were used to characterize the promoter library and ensure the consistent behavior of all its members for various genes and culturing conditions. We show here three metrics that were chosen for quantifying transcriptional of the promoters: (i) the dynamics of GFP production based on fluorescence, (ii) measurement of the relative mRNA transcript levels in the cultures, and (iii) testing of the MIC for chloramphenicol in an additional library of constructs where the promoter drove the expression of chloramphenicol acetyltransferase. The overall strong correlation between the various metrics suggests a broad-range utility of the promoter library for a variety of genes and conditions. (A) Mouse C127 cells were transduced with retrovirus expressing BPV-1 E7 with a FLAG͞HA epitope tag at either the C terminus (E7-C) or N terminus (E7-N), or with no tag (E7). Cells were lysed, and proteins were immunoprecipitated by using either an anti-FLAG antibody (Left) or an anti-BPV-1 E7 antibody (Right). Proteins were resolved by SDS͞PAGE on a 15% polyacrylamide gel and probed by immunoblotting using the anti-E7 antibody. (B) Cells were assayed for anchorage-independent growth with transduced BPV-1 oncogenes: C127 control cells, cells expressing BPV-1 E7 alone, BPV-1 E6 alone, E6 and E7, E6 and C-terminal FLAG͞HA-tagged E7 (E7-C), and E6 and N-terminal FLAG͞HA-tagged E7 (E7-N). Cells were suspended in 0.3% Noble agar, DMEM, and 10% FBS and grown for 14 days. Representative fields are shown at ϫ10 magnification. For further details, see Cortical analysis related to visual object recognition is traditionally thought to propagate serially along a bottom-up hierarchy of ventral areas. Recent proposals gradually promote the role of top-down processing in recognition, but how such facilitation is triggered remains a puzzle. We tested a specific model, proposing that low spatial frequencies facilitate visual object recognition by initiating top-down processes projected from orbitofrontal to visual cortex. The present study combined magnetoencephalography, which has superior temporal resolution, functional magnetic resonance imaging, and a behavioral task that yields successful recognition with stimulus repetitions. Object recognition elicited differential activity that developed in the left orbitofrontal cortex 50 ms earlier than it did in recognition-related areas in the temporal cortex. This early orbitofrontal activity was directly modulated by the presence of low spatial frequencies in the image. Taken together, the dynamics we revealed provide strong support for the proposal of how top-down facilitation of object recognition is initiated, and our observations a...

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The majority of the research related to visual recognition has so far focused on bottom-up analysis, where the input is processed in a cascade of cortical regions that analyze increasingly complex information. Gradually more studies emphasize the role of top-down facilitation in cortical analysis, but it remains something of a mystery how such processing would be initiated. After all, top-down facilitation implies that high-level information is activated earlier than some relevant lower-level information. Building on previous studies, I propose a specific mechanism for the activation of top-down facilitation during visual object recognition. The gist of this hypothesis is that a partially analyzed version of the input image (i.e., a blurred image) is projected rapidly from early visual areas directly to the prefrontal cortex (PFC). This coarse representation activates in the PFC expectations about the most likely interpretations of the input image, which are then back-projected as an "initial guess" to the temporal cortex to be integrated with the bottom-up analysis. The top-down process facilitates recognition by substantially limiting the number of object representations that need to be considered. Furthermore, such a rapid mechanism may provide critical information when a quick response is necessary.

Self-sustained turbulent structures have been observed in a wide range of living fluids, yet no quantitative theory exists to explain their properties. We report experiments on active turbulence in highly concentrated 3D suspensions of Bacillus subtilis and compare them with a minimal fourth-order vector-field theory for incompressible bacterial dynamics. Velocimetry of bacteria and surrounding fluid, determined by imaging cells and tracking colloidal tracers, yields consistent results for velocity statistics and correlations over 2 orders of magnitude in kinetic energy, revealing a decrease of fluid memory with increasing swimming activity and linear scaling between kinetic energy and enstrophy. The best-fit model allows for quantitative agreement with experimental data.

Objects in our environment tend to be grouped in typical contexts. How does the human brain analyze such associations between visual objects and their specific context? We addressed this question in four functional neuroimaging experiments and revealed the cortical mechanisms that are uniquely activated when people recognize highly contextual objects (e.g., a traffic light). Our findings indicate that a region in the parahippocampal cortex and a region in the retrosplenial cortex together comprise a system that mediates both spatial and nonspatial contextual processing. Interestingly, each of these regions has been identified in the past with two functions: the processing of spatial information and episodic memory. Attributing contextual analysis to these two areas, instead, provides a framework for bridging between previous reports.

People constantly make snap judgments about objects encountered in the environment. Such rapid judgments must be based on the physical properties of the targets, but the nature of these properties is yet unknown. We hypothesized that sharp transitions in contour might convey a sense of threat, and therefore trigger a negative bias. Our results were consistent with this hypothesis. The type of contour a visual object possesses--whether the contour is sharp angled or curved--has a critical influence on people's attitude toward that object.