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12 results for “hierarchical processing”

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zenodo40/100

Fig. 2 in Hierarchical establishment of information sources during foraging decision-making process involving Acromyrmex subterraneus (Forel, 1893) (Hymenoptera, Formicidae)

Fig. 2. Decision time (s) spent by the A. subterraneus target worker according to number of trips (n) made by the respective target worker and the concentration of pheromone manipulated on the branch that does not lead to the food, estimated by total flow of foragers.

opencc-by-4.0Dec 2017View details →
zenodo40/100

Fig. 1. Y in Hierarchical establishment of information sources during foraging decision-making process involving Acromyrmex subterraneus (Forel, 1893) (Hymenoptera, Formicidae)

Fig. 1. Y-trail system with branches of equal length (225 mm). Branches arranged at an angle of 60◦ connected to a bifurcation. Decision lines (LD) established at fixed points 140 mm far from the bifurcation center on the right and left branches, and 25 mm from the base branch to calculate the A. subterraneus workers' frequency of passage when half of their bodies had crossed each LD.

opencc-by-4.0Dec 2017View details →
zenodo40/100

Dataset and codes of the article "Neural correlates of hierarchical predictive processes in autistic adults"

<p>Data and code related to the article&nbsp;&quot;Neural correlates of hierarchical predictive processes in autistic adults&quot;&nbsp; by Laurie-Anne Sapey-Triomphe, Lauren Pattyn, Veith Weilnhammer, Philipp Sterzer and Johan Wagemans (Nature Communications):</p> <p>-&nbsp;Behavioral dataset&nbsp;of the 26 neurotypical participants (NT_behavioral_data.zip) and of the 26 autistic participants (ASD_behavioral_data.zip)</p> <p>- Source data of the graphics appearing in the article (Source data.xls)</p> <p>- Matlab codes used to run the experiment (Codes_to_run_experiment.zip)</p> <p>- Matlab codes to perform&nbsp;the main behavioral analyses (Codes_behavioral_analyses.zip) and to analyze the behavioral data with the HGF models (Codes_comput_model_analyses.zip)</p> <p>- Matlab codes to preprocess (Codes_fMRI_preprocessing.zip) and run the main fMRI analyses (Codes_fMRI_analyses.zip)</p>

opencc-by-4.0Apr 2023View details →
dryad36/100

Anonymized source data files for figures in: Recurrent processes support a cascade of hierarchical decisions

<p>Perception depends on a complex interplay between feedforward and recurrent processing. Yet, while the former has been extensively characterized, the computational organization of the latter remains largely unknown. Here, we use magneto-encephalography to localize, track and decode the feedforward and recurrent processes of reading, as elicited by letters and digits whose level of ambiguity was parametrically manipulated. We first confirm that a feedforward response propagates through the ventral and dorsal pathways within the first 200 ms. The subsequent activity is distributed across temporal, parietal and prefrontal cortices, which sequentially generate five levels of representations culminating in action-specific motor signals. Our decoding analyses reveal that both the content and the timing of these brain responses are best explained by a hierarchy of recurrent neural assemblies, which both maintain and broadcast increasingly rich representations. Together, these results show how recurrent processes generate, over extended time periods, a cascade of decisions that ultimately accounts for subjects' perceptual reports and reaction times.</p>

opencc-zeroSep 2020View details →
dryad36/100

Anonymized source data files for figures in: Recurrent processes support a cascade of hierarchical decisions

Open the record for dataset details and reuse information.

publicSep 2020View details →
dryad32/100

Data from: Hierarchical structure of ecological and non-ecological processes of differentiation shaped ongoing gastropod radiation in the Malawi Basin

Ecological processes, non-ecological processes or a combination of both may cause reproductive isolation and speciation, but their specific roles and potentially complex interactions in evolutionary radiations remain poorly understood, which defines a central knowledge gap at the interface of microevolution and macroevolution. Here I examine genome scans in combination with phenotypic and environmental data to disentangle how ecological and non-ecological processes contributed to population differentiation and speciation in an ongoing radiation of Lanistes gastropods from the Malawi Basin. I found a remarkable hierarchical structure of differentiation mechanisms in space and time: neutral and mutation-order processes are older and occur mainly between regions, whereas more recent adaptive processes are the main driver of genetic differentiation and reproductive isolation within regions. The strongest differentiation occurs between habitats and between regions, i.e. when ecological and non-ecological processes act synergistically. The structured occurrence of these processes based on the specific geographic setting and ecological opportunities strongly influenced the potential for evolutionary radiation. The results highlight the importance of interactions between various mechanisms of differentiation in evolutionary radiations, and suggest that non-ecological processes are important in adaptive radiations, including those of cichlids. Insight into such interactions is critical to understanding large-scale patterns of organismal diversity.

opencc-zeroDec 2016View details →
dryad32/100

Data from: Ant diversity in Neotropical savannas: hierarchical processes acting at multiple spatial scales

1. Understanding what creates and maintains macroscale biodiversity gradients is a central focus of ecological and evolutionary research. Spatial patterns in diversity are driven by a hierarchy of factors operating at multiple scales. Historical and climatic factors drive large-scale patterns of diversity by affecting the size of regional species pools, while habitat heterogeneity or microhabitat characteristics further influence species coexistence at small scales. 2. We tested the degree to which the species-energy, historical factors, habitat heterogeneity and local environment hypotheses explain observed patterns of ant diversity across hierarchical spatial scales. 3. We sampled ground-dwelling ants at 29 sites within a Neotropical savanna region, the Brazilian Cerrado. We measured species density – an abundance-dependent diversity metric – and rarefied species richness – an abundance-independent metric – at spatial scales with varying grain sizes. For each hypothesis, two correlates were used to predict ant diversity patterns: i) species-energy: rainfall and productivity; ii) historical factors: historical variation in rainfall and refugial areas; iii) habitat heterogeneity: heterogeneity in greenness and diversity of land cover; iv) local factors: contents of sand and coarse fragments in the soil. 4. Ant diversity patterns correlated to net primary productivity and to the proportion of coarse fragments in the soil, corroborating the species-energy and local environment hypotheses, respectively. Soil negatively influenced species density, but not rarefied species richness, which was positively influenced by productivity. We found scale dependencies in the effects of soil/productivity on species density; productivity best predicted species density patterns at large scales, since sampling completeness offset the abundance-driven effects of soil. 5. Considering abundance differences may help to discern the mechanisms underlying the relationship between macroscale diversity patterns and its ecological drivers. Plant productivity affected ant diversity independently of abundance, possibly by limiting the size of regional species pools. On the other hand, soil properties had an abundance-dependent effect on ant diversity, indicating a sampling mechanism. Our findings are consistent with predictions of the hierarchical theory of diversity. Large-scale patterns of productivity limit regional diversity, an effect that cascades down to finer spatial scales, where soil properties influence the number of coexisting species.

opencc-zeroDec 2019View details →
dryad32/100

Data from: Hierarchical structure of ecological and non-ecological processes of differentiation shaped ongoing gastropod radiation in the Malawi Basin

Open the record for dataset details and reuse information.

publicAug 2017View details →
dryad32/100

Data from: Ant diversity in Neotropical savannas: hierarchical processes acting at multiple spatial scales

Open the record for dataset details and reuse information.

publicDec 2019View details →
dryad28/100

Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild

The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed inference when addressing evolutionary questions. Hierarchical modelling (HM) has been proposed as a generic statistical framework to deal with complexity in ecological data and account for uncertainty. However, to date, HM has seldom been used to investigate evolutionary mechanisms possibly underlying observed patterns. Here, we contend the HM approach offers a relevant approach for the study of eco-evolutionary processes in the wild by confronting formal theories to empirical data through proper statistical inference. Studying eco-evolutionary processes requires considering the complete and often complex life histories of organisms. We show how this can be achieved by combining sequentially all life histories components and all available sources of information through HM. We demonstrate how eco-evolutionary processes may be poorly inferred or even missed without using the full potential of HM. As a case study, we use the Atlantic salmon and data on wild marked juveniles. We assess a reaction norm for migration and two potential trade-offs for survival. Overall, HM has a great potential to address evolutionary questions and investigate important processes that could not previously be assessed in laboratory or short time-scale studies.

opencc-zeroDec 2011View details →
dryad28/100

Data from: Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild

Open the record for dataset details and reuse information.

publicJul 2012View details →
geo24/100

Hierarchical RNA processing is rate limiting for mitochondrial ribosome assembly

GEO Series GSE83471. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing; Other.

openGEO-OpenAug 2016View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record