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512 results for “Activity pattern”
New Ideas for Brain Modelling 4-Figure 4. LHS relates to neuron binding ensemble mass, with central column activated. RHS relates to hierarchy, with a direct mapping. The two red lines show where the ensemble is missing and so it needs to be learned. The blue lines show extra neurons from the hierarchy back to the ensemble, but can be removed as error. The other paired black squares represent where the patterns match and can oscillate together.
<p>This paper continues the research that considers a new cognitive model based strongly on the human brain, last updated in Greer (2016). In particular, it considers figure 4 of that paper (Figure below) and how it might be useful in practice. The paper also describes some new methods in the areas of image processing and behaviour simulation. The image processing introduces a most classical form of pattern cross-referencing, while the behaviour equations used feedback for a memory-type of cross-referencing. The work is all based on earlier research by the author and the new additions are intended to fit in with the overall design. For image processing, a grid-like structure is used with ‘full linking’, if you like. Each cell in the classifier grid stores a list of all other cells it gets associated with and this is used as the learned image that new input is compared with. For the behaviour metric, a new prediction equation is suggested, as part of a simulation, that uses feedback and history to dynamically determine its current state and course of action. While the new methods are from widely different topics, both can be compared with the binary-analog type of interface that is the main focus of the paper. Sensory input may be static and binary, but cross- references result in variable comparisons that make the input more dynamic. It is suggested that the simplest of linking between a tree and ensemble can explain neural binding and variable signal strengths.</p>
Figure 5 in Diurnal activity pattern of age-sex groups of a small and fragmented population of Blackbuck (Antilope cervicapra L.) in Western Haryana, India
Figure 5. Behavioural activities recorded for sub adult male vs. total time spent during different season(s).
Figure 6 in Diurnal activity pattern of age-sex groups of a small and fragmented population of Blackbuck (Antilope cervicapra L.) in Western Haryana, India
Figure 6. Behavioural activities recorded for sub adult female vs. total time spent during different season(s).
Figure 3 in Diurnal activity pattern of age-sex groups of a small and fragmented population of Blackbuck (Antilope cervicapra L.) in Western Haryana, India
Figure 3. Behavioural activities recorded for adult male vs. total time spent during different season(s).
Figure 4 in Diurnal activity pattern of age-sex groups of a small and fragmented population of Blackbuck (Antilope cervicapra L.) in Western Haryana, India
Figure 4. Behavioural activities recorded for adult female vs. total time spent during different season(s).
Figure 8 in Diurnal activity pattern of age-sex groups of a small and fragmented population of Blackbuck (Antilope cervicapra L.) in Western Haryana, India
Figure 8. Average % time spent annually versus activities by different age sex group (Error bars with standard error and treatment bars with different letters differ significantly at P ≤ 0.05 based on Duncan Multiple Range Test).
Figure 7 in Diurnal activity pattern of age-sex groups of a small and fragmented population of Blackbuck (Antilope cervicapra L.) in Western Haryana, India
Figure 7. Major behavioural activities vs. total time spent on each activity by different age-sex animal.
Figure 2 in Activity patterns and habitat preference of eastern Hermann's tortoise (Testudo hermanni boettgeri) in Serbia
Figure 2. Percent of occurrence of tortoises in specific habitat types in consecutive years. For description of habitat types, see Section 2.2.
Figure 3 in Seasonal pattern of population dynamics, spawning activities, and diet composition of sardine (Sardina pilchardus Walbaum) in the eastern Adriatic Sea
Figure 3. Alternations of the mean monthly gonadosomatic index (GSI) and values of gonad masses (Wg, g) in sardines collected by commercial purse seiners during 2013 (February–November 2013) on Croatian fishing grounds.
Figure 1 in Activity patterns and habitat preference of eastern Hermann's tortoise (Testudo hermanni boettgeri) in Serbia
Figure 1. The study area. The map was constructed with Google Earth. The white line borders the area where monitoring was conducted. Triangles mark the position of open habitat or grassland. Squares mark the position of human-modified habitat. Surface without symbols represents forest.
Fig. 3 in Species richness and activity pattern of bees (Hymenoptera, Apidae) in the restinga area of Lençóis Maranhenses National Park, Barreirinhas, Maranhão, Brazil
Fig. 3. Dendrogram of Morisita similarity of the bee species collected between PNLM (Barreirinhas, MA) and other restinga and dune areas of northeastern Brazil:Paraíba (Madeira-da-Silva and Martins, 2003), Bahia (Viana and Kleinert, 2005), Salvador (Silva et al., 2015), Panaquatira (Oliveira et al., 2010), and São Luís (Albuquerque et al., 2007).
Fig. 1 in Species richness and activity pattern of bees (Hymenoptera, Apidae) in the restinga area of Lençóis Maranhenses National Park, Barreirinhas, Maranhão, Brazil
Fig. 1. Number of species netted and individuals recorded from August 2009 to 2010 of the restinga of the PNLM, Barreirinhas, MA, Brazil.
Fig. 3. Activity patterns for 14 in Camera-Trapping Survey Of Mammals In And Around Imbak Canyon Conservation Area In Sabah, Malaysian Borneo
Fig. 3. Activity patterns for 14 mammal species (with n ≥ 8) photocaptured in and around Imbak Canyon Conservation Area in central Sabah, Malaysian Borneo. Dotted bar indicates percent frequency of independent photographs taken during the day time (0600–1800 hours); Black bar indicates percent frequency of independent photographs taken during night time (1800–0600 hours). Species are listed in order of decreasing frequency of diurnal activity. Numbers in parentheses indicate sample size.
Fig. 3 in Activity patterns of frugivorous phyllostomid bats in an urban fragment in southwest Amazonia, Brazil
Fig. 3. Number of captures of the four most abundant species, according to the rainfall in the ParQue Zoobotânico, Rio Branco, state of Acre, northern Brazil.
Fig. 2 in Activity patterns of frugivorous phyllostomid bats in an urban fragment in southwest Amazonia, Brazil
Fig. 2. Number of captures of the four most abundant species throughout the night period, according to hours after sunset, in the ParQue Zoobotânico, Rio Branco, state of Acre, northern Brazil.
Fig. 1 in Activity patterns of frugivorous phyllostomid bats in an urban fragment in southwest Amazonia, Brazil
Fig. 1. Location of the forest fragment (ParQue Zoobotânico) in the urban area of Rio Branco, Acre, southwestern Amazonia, Brazil.
Map B 1 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Map B 1. number of records per UTM 10 x 10 km square in the dataset for the analysis of the phenology.
Map B 1 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Map B 1. Number of records per UTM 10 x 10 km square in the dataset for the analysis of the habitat preferences.
Fig. 43 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Fig. 43. Principal component analysis of species according to their relative abundance in the different two-month periods.
Fig. 42 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Fig. 42. Graphical representation of the species used in the PCA-ordination according to the species main habitat. Length of the coloured parts of the stacks represent the relative number of records for each species per habitat type.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
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.
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.
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.
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.