Spatiotemporal neural network dynamics for the processing of dynamic facial expressions.

表情を処理する神経ネットワークの時空間ダイナミクスを解明. 京都大学プレスリリース. 2015-07-24.The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150-200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300-350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual-motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions

Widespread and lateralized social brain activity for processing dynamic facial expressions

Dynamic facial expressions of emotions constitute natural and powerful means of social communication in daily life. A number of previous neuroimaging studies have explored the neural mechanisms underlying the processing of dynamic facial expressions, and indicated the activation of certain social brain regions (e.g., the amygdala) during such tasks. However, the activated brain regions were inconsistent across studies, and their laterality was rarely evaluated. To investigate these issues, we measured brain activity using functional magnetic resonance imaging in a relatively large sample (n = 51) during the observation of dynamic facial expressions of anger and happiness and their corresponding dynamic mosaic images. The observation of dynamic facial expressions, compared with dynamic mosaics, elicited stronger activity in the bilateral posterior cortices, including the inferior occipital gyri, fusiform gyri, and superior temporal sulci. The dynamic facial expressions also activated bilateral limbic regions, including the amygdalae and ventromedial prefrontal cortices, more strongly versus mosaics. In the same manner, activation was found in the right inferior frontal gyrus (IFG) and left cerebellum. Laterality analyses comparing original and flipped images revealed right hemispheric dominance in the superior temporal sulcus and IFG and left hemispheric dominance in the cerebellum. These results indicated that the neural mechanisms underlying processing of dynamic facial expressions include widespread social brain regions associated with perceptual, emotional, and motor functions, and include a clearly lateralized (right cortical and left cerebellar) network like that involved in language processing

The dynamic mosaic phenotypes of flowering plants

Ecological interaction and adaptation both depend on phenotypic characteristics. In contrast with the common conception of the ‘adult’ phenotype, plant bodies develop continuously during their lives. Furthermore, the different units (metamers) that comprise plant bodies are not identical copies, but vary extensively within individuals. These characteristics foster recognition of plant phenotypes as dynamic mosaics. We elaborate this conception based largely on a wide‐ranging review of developmental, ecological and evolutionary studies of plant reproduction, and identify its utility in the analysis of plant form, function and diversification. An expanded phenotypic conception is warranted because dynamic mosaic features affect plant performance and evolve. Evidence demonstrates that dynamic mosaic phenotypes enable functional ontogeny, division of labour, resource and mating efficiency. In addition, dynamic mosaic features differ between individuals and experience phenotypic selection. Investigation of the characteristics and roles of dynamic and mosaic features of plant phenotypes benefits from considering within‐individual variation as a function‐valued trait that can be analysed with functional data methods. Phenotypic dynamics and within‐individual variation arise despite an individual's genetic uniformity, and develop largely by heterogeneous gene expression and associated hormonal control. These characteristics can be heritable, so that dynamic mosaic phenotypes can evolve and diversify by natural selection.Fil: Harder, Lawrence. University of Calgary; CanadáFil: Strelin, Marina Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional Autónoma de México. Departamento de Ecología Evolutiva. Instituto de Ecología; MéxicoFil: Clocher, Ilona C.. University of Calgary; CanadáFil: Kulbaba, Mason. University of Calgary; CanadáFil: Aizen, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentin

Wireless Software Synchronization of Multiple Distributed Cameras

We present a method for precisely time-synchronizing the capture of image sequences from a collection of smartphone cameras connected over WiFi. Our method is entirely software-based, has only modest hardware requirements, and achieves an accuracy of less than 250 microseconds on unmodified commodity hardware. It does not use image content and synchronizes cameras prior to capture. The algorithm operates in two stages. In the first stage, we designate one device as the leader and synchronize each client device's clock to it by estimating network delay. Once clocks are synchronized, the second stage initiates continuous image streaming, estimates the relative phase of image timestamps between each client and the leader, and shifts the streams into alignment. We quantitatively validate our results on a multi-camera rig imaging a high-precision LED array and qualitatively demonstrate significant improvements to multi-view stereo depth estimation and stitching of dynamic scenes. We release as open source 'libsoftwaresync', an Android implementation of our system, to inspire new types of collective capture applications.Comment: Main: 9 pages, 10 figures. Supplemental: 3 pages, 5 figure

Capacity Building and Community Empowerment: Connecting Noto and Ifugao

地域環境知プロジェクト第1回国際シンポジウム，総合地球環境学研究所 講演室，2014-09-13，総合地球環境学研究所 地域環境知プロジェクト

Pre-European fire regimes in Australian ecosystems

We use multiple lines of evidence, including palaeo-environmental, ecological, historical, anthropological and archaeological, to investigate pre-European fire regimes in Australia, with particular focus on the extent to which the use of fire by Aboriginal peoples since their colonisation of the continent at least 45,000 years ago has impacted on the Australian biota. The relative roles of people and climate (including past climate change) as agents driving fire regime are assessed for the major climate–vegetation regions of the continent. Both historical accounts and evidence from current land-use practices in some areas support the argument that Aboriginal peoples used fire as a land management tool. Evidence for pre-European fire regimes suggests that while large areas of savanna woodlands in northern Australia, and dry forests and woodlands in temperate southern Australia, were subjected to increased fire under Aboriginal land management; others were not. Areas where fire regime was controlled primarily by ‘natural’ climate-fuel relationships probably included those that were difficult to burn because they were too wet (e.g. rainforests), fuel levels were usually too low (e.g. desert and semi-arid rangelands), or resource availability was low and did not support other than transient human occupation (e.g. some shrublands). Scientific studies suggest that many fire-sensitive woody species would decline under more frequent burning, so that the use of a small patch size, frequent fire regime – such as may have existed over large parts of Australia in the pre-European (Aboriginal occupation) period – may have harmful biodiversity conservation outcomes if instituted without careful consideration of individual ecosystem and species requirements

What does ‘traditional’ management really mean?

In spite of the increases in our knowledge achieved over the past half century, not least through the contributions of Oliver Rackham, we still know relatively little about historic land use practices or their ecological outcomes. By the time the characteristics of particular habitat types were first recorded in the mid-late nineteenth century, by Richard Jefferies for example, they were already changing fast, as a consequence of agricultural modernisation, industrialisation, and unprecedented population growth. Yet even before all of these far-reaching developments, land management systems had changed radically over time, and had varied from place to place, producing a constellation of landscape types that were considerably more unstable and variable than those produced by modern conservation methods (Fuller et al. 2017). Population fluctuated both locally and nationally, and farming varied in response to markets in meat and grain or the requirements of local and national industries. Throughout western Europe, semi-natural habitats are often classified according to their past exploitation (e.g. Tansley 1939; Ratcliffe 1977; EC 1992), and within our surviving fragments of semi-natural vegetation, conservation management generally aims to continue the ‘traditional’ practices (those of pre-industrial [c. 1200-1750] land management systems) which originally contributed to their character. While these traditional practices have created a number of the habitats that we value today, our ancestors were, of course, not carrying them out with any aim of increasing biodiversity. The wildlife value of traditional landscapes came as a fortuitous by-product of intensive land stripping, vegetation clearance and exploitation by man; characterised by dynamic nested heterogeneity, compatible to a sizeable subset of potential Biodiversity. However, while current management of wildlife habitats may attempt to mimic aspects of ‘traditional’ practices, it arguably simplifies their character and thus, as the ‘State of Nature Report’ (Hayhow et al. 2016) has shown, is failing to sustain the species with which they are particularly associated. Indeed, it is likely that, to a significant extent, the conviction that ‘traditional’ management systems are insufficient for conservation is based on a poor understanding of what these actually involved, and of what they achieved. The management of individual land parcels, including those that we think of today as ‘semi-natural’, was far from static, and this raises important questions about how we can restore them to a meaningful ‘baseline’. More importantly, in failing to understand the real processes which made particular suites of species characteristic of particular places, we may be unable to sustain these into the future. In this article we elucidate the real character of past management systems, and suggest how the principles they embody can be used to develop innovative new conservation techniques

Análise das Mudanças da Cobertura do Solo de uma Área de Cerrado (Savana Tropical) no Centro-Oeste do Brasil

The objective of the present work was to carry out an analysis of the land cover of an area in the centre-west of Brazil, at two different times, in 1966 and 2001, using a satellite image and a topographic map, in the Geographic Information System (GIS) environment. The 1966 land cover map was obtained by vectorizing the SE-22-Y-A-V topographic map (IBGE), while the 2001 land cover map was obtained from supervised automatic classification of the Landsat image ETM+ satellite orbit/point 224/073 of August 2001. The analysis showed alterations from natural cover to anthropogenic. In 1966, natural cover was 90% or more (principally true cerrado and forest), while in 2001, natural cover had decreased to 24%, being replaced by arable land and primarily grassland.O objetivo do presente trabalho foi produzir uma análise multitemporal da cobertura do solo em uma área no centro-oeste do Brasil, em duas diferentes épocas, em 1966 e 2001, utilizando uma imagem de satélite e uma carta topográfica em ambiente SIG (Sistema de Informações Geográficas). A carta de cobertura do solo de 1966 foi obtida pela vetorialização da carta topográfica SE-22-Y-A-V (IBGE), enquanto que a carta de cobertura do solo de 2001 foi obtida através de uma classificação automática supervisionada da imagem do satélite Landsat 7 ETM+ órbita/ponto 224/073 de agosto de 2001. A análise mostrou as alterações da cobertura natural para antrópica. Em 1966, a cobertura natural representava 90% ou mais da área estudada (principalmente por cerrado sentido restrito e formações florestais), enquanto que em 2001, a cobertura natural havia diminuído para 24%, sendo substituída principalmente por áreas de agricultura e pasto