scholarly journals Stimulus prediction in the hippocampus

2018 ◽  
Author(s):  
Peter Kok ◽  
Nicholas B. Turk-Browne
Keyword(s):  
Visual Cortex ◽  
High Resolution ◽  
Sensory Systems ◽  
Top Down ◽  
Auditory Cues ◽  
Bottom Up ◽  
Reconstruction Methods

AbstractPerception can be cast as a process of inference, in which bottom-up signals are combined with top-down predictions in sensory systems. However, the source of these top-down predictions, especially when complex and multisensory, remains largely unknown. We hypothesised that the hippocampus — which rapidly learns arbitrary associations and has bidirectional connections with sensory systems — may be involved. We exposed humans to auditory cues predicting visual shapes, while measuring high-resolution fMRI signals in visual cortex and the hippocampus. Using multivariate reconstruction methods, we discovered a dissociation between these regions: representations in visual cortex were dominated by whichever shape was presented, whereas representations in the hippocampus (CA3 and subiculum, but not CA1) reflected only which shape was predicted by the cue. The strength of hippocampal predictions correlated across participants with the amount of expectation-related facilitation in visual cortex. These findings are consistent with the possibility that the hippocampus supplies predictions to sensory systems.

Neural modulation of a realistic layered-microcircuit model of visual cortex based on bottom-up and top-down signals

2010 ◽  
Vol 68 ◽  
pp. e380
Author(s):  
Tomoki Fukai ◽  
Nobuhiko Wagatsuma ◽  
Tobias C. Potjans ◽  
Markus Diesmann
Keyword(s):  
Visual Cortex ◽  
Top Down ◽  
Bottom Up ◽  
Neural Modulation

scholarly journals Bottom-up saliency and top-down learning in the primary visual cortex of monkeys

2018 ◽  
Vol 115 (41) ◽  
pp. 10499-10504 ◽  
Author(s):  
Yin Yan ◽  
Li Zhaoping ◽  
Wu Li
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Detection Task ◽  
Late Response ◽  
Late Component ◽  
Neuronal Responses ◽  
Top Down ◽  
Bottom Up ◽  
Response Component ◽  
Orientation Contrast

Early sensory cortex is better known for representing sensory inputs but less for the effect of its responses on behavior. Here we explore the behavioral correlates of neuronal responses in primary visual cortex (V1) in a task to detect a uniquely oriented bar—the orientation singleton—in a background of uniformly oriented bars. This singleton is salient or inconspicuous when the orientation contrast between the singleton and background bars is sufficiently large or small, respectively. Using implanted microelectrodes, we measured V1 activities while monkeys were trained to quickly saccade to the singleton. A neuron’s responses to the singleton within its receptive field had an early and a late component, both increased with the orientation contrast. The early component started from the outset of neuronal responses; it remained unchanged before and after training on the singleton detection. The late component started ∼40 ms after the early one; it emerged and evolved with practicing the detection task. Training increased the behavioral accuracy and speed of singleton detection and increased the amount of information in the late response component about a singleton’s presence or absence. Furthermore, for a given singleton, faster detection performance was associated with higher V1 responses; training increased this behavioral–neural correlate in the early V1 responses but decreased it in the late V1 responses. Therefore, V1’s early responses are directly linked with behavior and represent the bottom-up saliency signals. Learning strengthens this link, likely serving as the basis for making the detection task more reflexive and less top-down driven.

scholarly journals De Novo Sequencing of Peptides from High-Resolution Bottom-Up Tandem Mass Spectra using Top-Down Intended Methods

PROTEOMICS ◽  
2017 ◽  
Vol 17 (23-24) ◽  
pp. 1600321 ◽  
Author(s):  
Kira Vyatkina ◽  
Lennard J. M. Dekker ◽  
Si Wu ◽  
Martijn M. VanDuijn ◽  
Xiaowen Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Mass Spectra ◽  
De Novo ◽  
De Novo Sequencing ◽  
Tandem Mass ◽  
Top Down ◽  
Bottom Up ◽  
Tandem Mass Spectra

The consortium GLADSOILMAP

2020 ◽  
Author(s):  
Dominique Arrouays ◽  
Zamir Libohova ◽  
Budiman Minansny ◽  
Vera Leatitia Mulder ◽  
Laura Poggio ◽  
...  
Keyword(s):  
High Resolution ◽  
Soil Properties ◽  
Soil Property ◽  
Environmental Modeling ◽  
Added Value ◽  
Top Down ◽  
Ancillary Data ◽  
Bottom Up ◽  
Global Issues ◽  
The World

<p>Soils have critical relevance to global issues, such as food and water security, climate regulation, sustainable energy, desertification and biodiversity protection. All these examples require accurate national soil property information and there is a need to scientific support to develop reliable baseline soil information and pathways for measuring and monitoring soils. Soil sustainable management is a global issue, but effective actions require high-resolution data about soil properties. Two projects, GlobalSoilMap and SoilGrids, aim at delivering the first generation of high-resolution soil property grids for the globe, the first one by a bottom-up approach (from country to globe), the latter by top-down (global). The GLobAl Digital SOIL MAP (GLADSOILMAP) consortium brings together world scientific leaders involved in both projects. The consortium aims at developing and transferring methods to improve the prediction accuracy of soil properties and their associated uncertainty, by using legacy soil data and ancillary spatial information. This approach brings together new technologies and methods, existing soil databases and expert knowledge. The consortium aims at transferring methods to achieve convergence between top-down and bottom-up approaches, and to generate methods for delivering maps of soil properties. These maps are essential for communities from climate and environmental modeling to decision making and sustainable resources management at a scale that is relevant to soil management. The consortium will ensure links with the numerous actors in geosciences of the world, and will contribute to improving their skills in digital mapping and their national and international legibility. The actions include 4 main Work Packages (WP) subdivided into several tasks that are summarized below:</p><p> </p><p>WP0 Management of the project</p><p>WP1 Legacy and ancillary data for Digital Soil Mapping (DSM)</p><p>Test the potential of new ancillary data for DSM</p><p>Explore methodologies to merge and/or harmonize different products</p><p>Propose methods for harmonizing products to a common date</p><p> </p><p>WP2 Methods for sampling, modelling and mapping soils in space and time</p><p>Testing and developing new methods/models for prediction</p><p>Testing methods for estimating complete probability distribution</p><p> </p><p>WP3 Methods for estimating model and map uncertainty</p><p>Develop methods of uncertainty spatial assessment</p><p>Develop methods do deal with censored data/soft data</p><p>Solve the question of influence on the age of the rescued soil data on predictions</p><p> </p><p>WP4 Scientific outreach and capacity building</p><p>Produce an exhaustive review of GlobalSoilMap initiatives and results all over the world</p><p>Revise and update the GlobalSoilMap specifications by keeping them at the state-of-the-art level</p><p>Show relevance of gridded, Global, DSM by use cases and communication to end users</p><p> </p><p>The added value of the consortium is to allow a direct scientific exchange between members that should result in synthesis papers, in the identification of the major knowledge gaps, and in extending, deepening and disseminating knowledge of DSM, with the final aim to contribute to the achievement of global soil maps. Another added value of the consortium will certainly be to foster the creation of new ideas.</p><p> </p><p>Acknowledgements: the Consortium GLADSOILMAP is supported by LE STUDIUM Loire Valley Institute for Advanced studies.</p>

scholarly journals Layer dependent neural modulation of a realistic layered-microcircuit model in visual cortex based on bottom-up and top-down signals

2011 ◽  
Vol 12 (S1) ◽  
Author(s):  
Nobuhiko Wagatsuma ◽  
Tobias C Potjans ◽  
Markus Diesmann ◽  
Tomoki Fukai
Keyword(s):  
Visual Cortex ◽  
Top Down ◽  
Bottom Up ◽  
Neural Modulation
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