Towards an understanding of the costs of fire.

The ability to produce fire at will and to maintain it for a long duration is considered one of the major advances in human evolution. The exact process by which hominins first learned to use and to create fire is still hotly debated, with some arguing for a sudden transformative event that was quickly followed by a biological and cultural dependence on fire, such as a reliance on the extra calories saved through cooking food and an external source of heat. Others suggest that the 'domestication' of fire was a long and drawn-out process, with hominins using fire when it was available on the landscape but perhaps not having the ability to produce fire until much later in human history. In this paper we propose a third option, that fire should be considered like other technologies - that is, it certainly comes with benefits but also with costs, and that hominins functioned as optimal foragers who chose to use this tool only when the costs were less than the benefits. The potential benefits of fire have been well-described in other publications. Here we discuss in detail the various kinds of costs associated with fire and how these costs could, and do, structure human fire-use behavior. We then describe a small experiment to 'put some numbers on' the potential costs of fire, by quantifying one of the most expensive costs (fuel collection) and comparing it to one of the most-praised benefits (cooking of food). The results suggest that the costs of fuel collection are very high in less-forested environments, and that excessively large amounts of cooked foods are needed to match the total costs of fuel collection and the act of cooking. Overall, the costs of fire can be quite high and must be considered when proposing models for pre-modern human adoption and regular use of fire technologies

Cortical and subcortical contributions to interference resolution and inhibition – An fMRI ALE meta-analysis

Interacting with our environment requires the selection of appropriate responses and the inhibition of others. Such effortful inhibition is achieved by a number of interference resolution and global inhibition processes. This meta-analysis including 57 studies and 73 contrasts revisits the overlap and differences in brain areas supporting interference resolution and global inhibition in cortical and subcortical brain areas. Activation likelihood estimation was used to discern the brain regions subserving each type of cognitive control. Individual contrast analysis revealed a common activation of the bilateral insula and supplementary motor areas. Subtraction analyses demonstrated the voxel-wise differences in recruitment in a number of areas including the precuneus in the interference tasks and the frontal pole and dorsal striatum in the inhibition tasks. Our results display a surprising lack of subcortical involvement within these types of cognitive control, a finding that is likely to reflect a systematic gap in the field of functional neuroimaging

A probabilistic atlas of the human ventral tegmental area (VTA) based on 7 Tesla MRI data

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Laminar signal extraction over extended cortical areas by means of a spatial GLM

Contains fulltext : 202552.pdf (publisher's version ) (Open Access)20 p

Fast and robust 3-D MRI brain structure segmentation

We present a novel method for the automatic detection and segmentation of (sub-)cortical gray matter structures in 3-D magnetic resonance images of the human brain. Essentially, the method is a topdown segmentation approach based on the recently introduced concept of Marginal Space Learning (MSL). We show that MSL naturally decomposes the parameter space of anatomy shapes along decreasing levels of geometrical abstraction into subspaces of increasing dimensionality by exploiting parameter invariance. At each level of abstraction, i.e., in each subspace, we build strong discriminative models from annotated training data, and use these models to narrow the range of possible solutions until a final shape can be inferred. Contextual information is introduced into the system by representing candidate shape parameters with high-dimensional vectors of 3-D generalized Haar features and steerable features derived from the observed volume intensities. Our system allows us to detect and segment 8 (sub-)cortical gray matter structures in T1-weighted 3-D MR brain scans from a variety of different scanners in on average 13.9 sec., which is faster than most of the approaches in the literature. In order to ensure comparability of the achieved results and to validate robustness, we evaluate our method on two publicly available gold standard databases consisting of several T1-weighted 3-D brain MR scans from different scanners and sites. The proposed method achieves an accuracy better than most state-of-the-art approaches using standardized distance and overlap metrics.Michael Wels, Yefeng Zheng, Gustavo Carneiro, Martin Huber, Joachim Hornegger and Dorin Comanici

High rate capability pure Sn-based nano-architectured electrode assembly for rechargeable lithium batteries

New high surface area nano-architectured copper current collectors have been designed based on simple electrodeposition method. The nano-architectured electrode design not only increases the effective surface area of the electrode but it is also very suitable for sustaining the mechanical and structural strain during electrochemical reaction. In this work, a nano-architectured Sn anode for Li-ion battery, based on Li-Sn alloying reaction, delivers very high cycle life and good power performance compared to planar tin films. This electrode could be successfully used in the field of 3D microbatteries. © 2008 Elsevier B.V. All rights reserved