THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images.

In recent years, the use of a large number of object concepts and naturalistic object images has been growing strongly in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science

THINGS-data: fMRI cortical surface flat maps

Cortical flat maps for three subjects derived from the anatomical MRI images. Cortical surfaces were reconstructed from T1-weighted and T2-weighted anatomical images with freesurfer's reconall procedure. Relaxation cuts were placed manually to allow for flattening of each hemisphere's surface. Results of any analysis of the fMRI data can be viewed on these flat maps with pycortex. Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151</p

THINGS-data: fMRI PRF AFNI inputs

Input files required to run a population receptive field analysis on the THINGS-fMRI localizer data with AFNI. Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151</p

THINGS-data: fMRI BIDS raw dataset

fMRI raw dataset in BIDS format. Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151</p

THINGS-data: fMRI ICA Noise Regressors

ICA-based noise regressors for the fMRI data. Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151</p

THINGS-data: fMRI Regions of Interest

Subject specific category-selective and retinotopic regions of interest for the fMRI data. Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151</p

THINGS-data: Behavioral odd-one-out data and code

4.7 million object odd-one-out judgements from human participants on Amazon Mechanical Turk. Part of THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6161151</p

Identity is an Infinite Now: Being Instead of Becoming Gallina

Archaeological research on the Gallina (AD 1100–1300) inhabitants of the region west of the Rio Chama and centered on the Llaves valley has focused on constructing a culture history and examining functional characteristics of artifacts and architecture. Limited research has attempted to understand who the residents of the Gallina heartland were. In this article, using new findings and historical contexts, we argue that the Gallina people had a complicated identity forged around resistance and a deep connection to their past. To better understand them we need to move past previous binary categories used to describe them and perceive them not as isolated or connected, aggressors or victims, traditionalists or innovators, but as an intersectional mix of these axes of identity.La investigación arqueológica sobre los habitantes Gallina (1100–1300 d. C.) de la región oeste del Río Chama, focalizada en el valle de Llaves, se orientó en la construcción de una historia cultural y el análisis de las características funcionales de los artefactos y la arquitectura. De hecho, han sido escasas las investigaciones que han intentado entender quiénes eran los residentes del Gallina. En este artículo, utilizando nuevos hallazgos y contextos históricos, argumentamos que los grupos Gallina tuvieron una identidad compleja, forjada en torno a la resistencia y a una profunda conexión con su historia. Asimismo, para entenderlas necesitamos movernos más allá de las tradicionales categorías binarias usadas para interpretarlos y percibirlos como aislados o conectados, violentos o víctimas, tradicionalistas o inventores, y en cambio, como una mezcla que abarca todos estos ejes de identidad.Archaeology of the America