Publications
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Aasebø, Ida E. J.; Lepperød, Mikkel Elle; Stavrinou, Maria; Nøkkevangen, Sandra; Einevoll, Gaute & Hafting, Torkel
[Show all 7 contributors for this article]
(2017).
Temporal processing in the visual cortex of the awake and anesthetized rat.
eNeuro.
ISSN 2373-2822.
4:e0059-17.2017(4),
p. 1–26.
doi:
10.1523/ENEURO.0059-17.2017.
Full text in Research Archive
Show summary
The activity pattern and temporal dynamics within and between neuron ensembles are essential features of information processing and believed to be profoundly affected by anesthesia. Much of our general understanding of sensory information processing, including computational models aimed at mathematically simulating sensory information processing, rely on parameters derived from recordings conducted on animals under anesthesia. Due to the high variety of neuronal subtypes in the brain, population-based estimates of the impact of anesthesia may conceal unit- or ensemble-specific effects of the transition between states. Using chronically implanted tetrodes into primary visual cortex (V1) of rats, we conducted extracellular recordings of single units and followed the same cell ensembles in the awake and anesthetized states. We found that the transition from wakefulness to anesthesia involves unpredictable changes in temporal response characteristics. The latency of single-unit responses to visual stimulation was delayed in anesthesia, with large individual variations between units. Pair-wise correlations between units increased under anesthesia, indicating more synchronized activity. Further, the units within an ensemble show reproducible temporal activity patterns in response to visual stimuli that is changed between states, suggesting state-dependent sequences of activity. The current dataset, with recordings from the same neural ensembles across states, is well suited for validating and testing computational network models. This can lead to testable predictions, bring a deeper understanding of the experimental findings and improve models of neural information processing. Here, we exemplify such a workflow using a Brunel network model.
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Aasebø, Ida E. J.; Blankvoort, Stefan Matthias Adriaan & Tashiro, Ayumu
(2011).
Critical maturational period of new neurons in adult dentate gyrus for their involvement in memory formation.
European Journal of Neuroscience.
ISSN 0953-816X.
33(6),
p. 1094–1100.
doi:
10.1111/j.1460-9568.2011.07608.x.
View all works in Cristin
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Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida; van Swieten, Maaike M. H.; Davison, Andrew P. & Zehl, Lyuba
[Show all 11 contributors for this article]
(2022).
Share FAIR neuroscience data using the EBRAINS curation services.
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van Swieten, Maaike; Schmid, Oliver; Dénervaud, Gilles; Tsanaktsidis, Ioannis; Weyers, Benjamin & Davison, Andrew P.
[Show all 9 contributors for this article]
(2022).
A Practical Guide to Using the EBRAINS Knowledge Graph in (your) Research.
Show summary
Scientific articles are mostly published as text files containing unstructured and semi-structured information. Consequently, important information is typically deeply hidden in documents which severely limits the possibilities to automatically process and reuse scholarly knowledge. One approach to make information explicit and directly usable is to transform this into a standardised format and store it in a knowledge graph. This allows scholarly knowledge to be represented in a structured, machine-actionable, interlinked and semantically rich manner. The EBRAINS Knowledge Graph was developed to facilitate the search and information exchange in research, so that research results across different domains become directly comparable and easier to retrieve and reuse. Here, we provide a practical guide to extracting information from the EBRAINS Knowledge Graph using a user-friendly interface as well as a more advanced programmatic route via an Application Programming Interface (API). We also provide concrete examples on how the extracted information can be leveraged in order to develop new research objectives as well as validate ongoing research. The EBRAINS Knowledge Graph is integrated in the wider EBRAINS research infrastructure as a part of the EBRAINS Data and Knowledge services for sharing and finding research data and models. Data found through these services can be directly used and analysed via the various integrated tools and analysis workflows. The EBRAINS Knowledge Graph is a valuable machine-actionable and FAIR (Findable, Accessible, Interoperable and Reusable) resource for discovery-based and hypothesis-driven research as it already contains a wide variety of neuroscience data types, models and software.
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Schlegel, Ulrike; Köhnen, Stefan; Davison, Andrew P.; Najafi, Peyman; Weyers, Benjamin & Gründling, Jan
[Show all 17 contributors for this article]
(2021).
openMINDS - flexible metadata models for neuroscience.
Show summary
Enhancing transparency and findability of research data is an emerging theme across scientific disciplines. While publicly accessible databases aid in achieving this goal, their suitability is determined by attributes and constraints of the underlying metadata model. In neuroscience, the heterogeneity of data is particularly challenging. The multimodal nature of the research data as well as the wide range in spatial and temporal scales need to be adequately captured . Therefore, a suitable metadata model for neuroscience data has to balance flexibility and restrictiveness to accommodate the individuality of research products, without diminishing comparability across them. Powered by the Human Brain Project (HBP) and EBRAINS, we present the open Metadata Initiative for Neuroscience Data Structures (openMINDS). This novel initiative develops and maintains interlinked metadata models tailored to describe neuroscience research products in graph databases, such as the EBRAINS Knowledge Graph. The openMINDS research products cover data originating from human, animal or simulation studies (datasets), computational models (models), software tools (software), formal specifications for structuring metadata and/or data (metaDataModels), and reference brain atlases (brainAtlas). To illustrate the power of openMINDS, we present selected features describing these research products. We highlight how respective data and their provenance as well as studied specimens can be captured with user-defined granularity, and how the various integration of data via openMINDS can enhance its comparability and findability within and beyond the EBRAINS Knowledge Graph.
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Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida Elisabeth Jørgensen; Blixhavn, Camilla Hagen; Zehl, Lyuba & Kjelsberg, Kasper
[Show all 13 contributors for this article]
(2020).
Neuroscience community-gains from data sharing through the EBRAINS infrastructure.
Show summary
EBRAINS provides tools and services which can be used to address challenges in brain research and brain-inspired technology development. EBRAINS assists scientists to collect, analyse, share and integrate brain data, and to perform modeling and simulation of brain function. EBRAINS is delivered by the EU Flagship Human Brain Project. All tools and services in EBRAINS are available for researchers in Europe and globally through https://ebrains.eu. Here we exemplify the use of the platform in different neuroscientific projects. In particular, the ‘Data & Knowledge’ services in EBRAINS offer one of the most comprehensive services for sharing brain research data ranging in type as well as spatial and temporal scale. An extensive metadata curation process ensures a robust presentation of datasets, models and software via the EBRAINS Knowledge Graph (https://kg.ebrains.eu/search/), making the data Findable, Accessible, Interoperable and Reusable (FAIR). By describing data across modalities in a standardised way and integrating it into the same reference space, data can be compared, combined and analysed with tools and analytical workflows embedded in the platform. New data, and data derived from the analytical workflows, can be submitted to curation and added to the existing EBRAINS datasets. The interplay between datasets, models and software makes EBRAINS attractive as a platform for discovery based and hypothesis driven research.
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Schlegel, Ulrike; Reiten, Ingrid; Aasebø, Ida Elisabeth Jørgensen; Blixhavn, Camilla Hagen; Zehl, Lyuba & Kjelsberg, Kasper
[Show all 13 contributors for this article]
(2020).
EBRAINS data sharing: benefits and workflow.
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Reiten, Ingrid; Schlegel, Ulrike; Blixhavn, Camilla Hagen; Andersson, Krister Andreas; Aasebø, Ida Elisabeth Jørgensen & Yates, Sharon Christine
[Show all 12 contributors for this article]
(2020).
Data sharing through the online EBRAINS platform: a new service for brain research.
Show summary
Enhancing the reproducibility and transparency of research is an emerging theme across scientific disciplines, driven by new technological advances, and captured by the Open Science concept. The heterogeneity of research data, which often hinders direct comparisons of findings, adds a layer of complexity to this effort. To address these challenges in neuroscience, the Human Brain Project has developed a new research infrastructure, EBRAINS, providing tools and services to the neuroscientific community. The EBRAINS data curation service offers comprehensive stewardship for sharing experimental and computational data. New workflows and standards for neuroscience data and metadata management have been developed to make the research results discoverable, comparable across modalities, and possible to reanalyse and reuse in new combinations. Here we present our workflows and curation services tailored for sharing heterogeneous neuroscience data. We demonstrate the integration of such data in the infrastructure, and highlight some practicalities for researchers who want to share their neuroscience data through EBRAINS.
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Andersson, Krister Andreas; Blixhavn, Camilla Hagen; Kleven, Heidi; Zehl, Lyuba; Bjerke, Ingvild Elise & Schmid, Oliver
[Show all 17 contributors for this article]
(2019).
Neuroinformatics platform for making neuroscience data Findable, Accessible, Interoperable, and Reuseable.
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Røe, Malin Benum; Aasebø, Ida Elisabeth Jørgensen; Mobarhan, Milad; Lensjø, Kristian Kinden; Einevoll, Gaute & Hafting, Torkel
[Show all 7 contributors for this article]
(2019).
Stable orientation tuning in the freely moving rat: Movement-robust orientation-selective neurons in the deep layers of the primary visual cortex.
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Røe, Malin Benum; Aasebø, Ida Elisabeth Jørgensen; Mobarhan, Milad; Lensjø, Kristian Kinden; Einevoll, Gaute & Hafting, Torkel
[Show all 7 contributors for this article]
(2019).
Stable orientation tuning in the freely moving rat: Movement-robust orientation-selective neurons in the deep layers of the primary visual cortex.
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Røe, Malin Benum; Aasebø, Ida Elisabeth Jørgensen; Mobarhan, Milad; Lensjø, Kristian Kinden; Stöber, Tristan Manfred & Einevoll, Gaute
[Show all 8 contributors for this article]
(2018).
Stable orientation tuning in the freely moving rat: Movement-robust orientation-selective neurons in the deep layers of the primary visual cortex.
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Hazen, Jennifer; Wigestrand, Mattis B; Aasebø, Ida Elisabeth Jørgensen; Tully, Annabelle; Dinh, Tovy & Lepperød, Mikkel
[Show all 8 contributors for this article]
(2018).
Lateral hypothalamic area projection neurons contribute to an innate freezing response.
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Røe, Malin Benum; Aasebø, Ida Elisabeth Jørgensen; Mobarhan, Milad; Lensjø, Kristian Kinden; Einevoll, Gaute & Hafting, Torkel
[Show all 7 contributors for this article]
(2018).
Stable orientation tuning in the freely moving rat: Movement-robust orientation selective neurons in the deep layers of the primary visual cortex.
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Aasebø, Ida Elisabeth Jørgensen; Røe, Malin Benum; Mobarhan, Milad; Lensjø, Kristian Kinden; Stöber, Tristan Manfred & Einevoll, Gaute
[Show all 8 contributors for this article]
(2018).
Orientation selectivity in the freely moving rat: Movement-robust orientation-selectivity (MROS) of units in the deep layers of the rat visual cortex
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Røe, Malin Benum; Aasebø, Ida Elisabeth Jørgensen; Mobarhan, Milad; Lensjø, Kristian Kinden; Einevoll, Gaute & Hafting, Torkel
[Show all 7 contributors for this article]
(2018).
Movement-resistant orientation selectivity of cells in the deep layers of the rat visual cortex.
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Aasebø, Ida E. J.; Mobarhan, Milad; Røe, Malin Benum; Lensjø, Kristian Kinden; Einevoll, Gaute & Hafting, Torkel
[Show all 7 contributors for this article]
(2017).
Movement-resistant orientation-selective units in the deep layers of the visual cortex.
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Wigestrand, Mattis B; Aasebø, Ida E. J.; Tully, Annabelle; Lepperød, Mikkel Elle; Hafting, Torkel & Fyhn, Marianne
(2016).
Lateral hypothalamic outputs control innate defensive responses.
Show summary
When facing a threat, animals display defensive behaviors that are critical for survival. The hypothalamus is believed to mediate such defensive responses, but the prevailing view includes a medial/lateral separation, where medial hypothalamus is thought to influence defensive responses, while the lateral hypothalamic area (LHA) regulates feeding and arousal. Here we identify two distinct neural populations in the LHA with surprising survival functions in rats. The two neural populations, defined by their output projections to either the periaqueductal gray (PAG) or the lateral habenula (LHb) have distinct anatomical placements along the anterior-posterior axis of the LHA and express distinct biochemical markers. Optogenetic stimulation of the two LHA populations robustly induced opposite active- or passive defensive responses. Further, chemogenetic silencing of LHA and optogenetic silencing of the LHA-PAG projection disrupted innate defensive responses to a predator-like looming shadow. Using single-unit recordings in the downstream LHb and PAG, we show that the LHA-LHb projection is largely excitatory, while the LHA-PAG projection is mainly inhibitory. We are currently using a miniaturized microscope to image the calcium activity of the two LHA populations during threat processing in behaving rats. Overall, our findings identify a novel LHA circuit that is critical for appropriate defensive responses to innate visual threats. The location of the LHA defense circuits, intermingled within circuitry that governs feeding, suggests that this circuit may provide rapid cross-talk between circuits that govern foraging- and anti-predator behaviors.
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Røe, Malin Benum; Aasebø, Ida E. J.; Lensjø, Kristian Kinden; Hafting, Torkel & Fyhn, Marianne
(2016).
Orientation selective cells in layer six of the primary visual cortex are resistant to the animal's movement.
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Bjerke, Line; Wigestrand, Mattis B; Aasebø, Ida E. J.; Fyhn, Marianne & Hafting, Torkel
(2016).
Inhibitory outputs from lateral hypothalamus to paraqueductal grey control innate defensive behavior.
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Wigestrand, Mattis B; Aasebø, Ida E. J.; Tully, Annabelle; Dinh, Vy To; Lepperød, Mikkel Elle & Hafting, Torkel
[Show all 7 contributors for this article]
(2016).
Lateral hypothalamic outputs control innate defensive responses.
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Aasebø, Ida E. J.; Hafting, Torkel; Stavrinou, Maria; Sandra, Nøkkevangen; Lepperød, Bjørn Mikkel Elle & Fyhn, Marianne
(2015).
Temporal processing in the visual cortex in the awake and anesthetized rat.
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Aasebø, Ida E. J.; Norheim, Eivind Skjønsberg; Lensjø, Kristian Kinden; Fyhn, Marianne & Fyhn, Torkel Hafting
(2013).
The effect of anesthesia on activity and modulation of visually responsive neurons in cortical and subcortical areas.
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Aasebø, Ida Elisabeth Jørgensen; Fyhn, Marianne; Hafting, Torkel & Einevoll, Gaute
(2018).
Behavioural state and neuronal activity: how the freely moving paradigm can uncover novel response characteristics.
Universitetet i Oslo.
View all works in Cristin
Published
Jan. 31, 2012 5:06 PM
- Last modified
Dec. 17, 2020 1:31 PM