Change search
Refine search result
1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Eriksson, Johan
    et al.
    Vogel, Edward K.
    Lansner, Anders B.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Department of Numerical Analysis and Computer Science, Stockholm University, Sweden.
    Bergstrom, Fredrik
    Nyberg, Lars
    Neurocognitive Architecture of Working Memory2015In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 88, no 1, p. 33-46Article, review/survey (Refereed)
    Abstract [en]

    A crucial role for working memory in temporary information processing and guidance of complex behavior has been recognized for many decades. There is emerging consensus that working-memory maintenance results from the interactions among long-term memory representations and basic processes, including attention, that are instantiated as reentrant loops between frontal and posterior cortical areas, as well as sub-cortical structures. The nature of such interactions can account for capacity limitations, lifespan changes, and restricted transfer after working-memory training. Recent data and models indicate that working memory may also be based on synaptic plasticity and that working memory can operate on non-consciously perceived information.

  • 2.
    Fransén, Erik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Tahvildari, B.
    Egorov, A. V.
    Hasselmo, M. E.
    Alonso, A. A.
    Mechanism of graded persistent cellular activity of entorhinal cortex layer V neurons2006In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 49, no 5, p. 735-746Article in journal (Refereed)
    Abstract [en]

    Working memory is an emergent property of neuronal networks, but its cellular basis remains elusive. Recent data show that principal neurons of the entorhinal cortex display persistent firing at graded firing rates that can be shifted up or down in response to brief excitatory or inhibitory stimuli. Here, we present a model of a potential mechanism for graded firing. Our multicompartmental model provides stable plateau firing generated by a nonspecific calcium-sensitive cationic (CAN) current. Sustained firing is insensitive to small variations in Ca2+ concentration in a neutral zone. However, both high and low Ca2+ levels alter firing rates. Specifically, increases in persistent firing rate are triggered only during high levels of calcium, while decreases in rate occur in the presence of low levels of calcium. The model is consistent with detailed experimental observations and provides a mechanism for maintenance of memory-related activity in individual neurons.

  • 3.
    Gharpure, Anant
    et al.
    Univ Texas Southwestern Med Ctr Dallas, Dept Neurosci, Dallas, TX 75390 USA..
    Teng, Jinfeng
    Univ Texas Southwestern Med Ctr Dallas, Dept Neurosci, Dallas, TX 75390 USA..
    Zhuang, Yuxuan
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, S-17121 Solna, Sweden..
    Noviello, Colleen M.
    Univ Texas Southwestern Med Ctr Dallas, Dept Neurosci, Dallas, TX 75390 USA..
    Walsh, Richard M., Jr.
    Univ Texas Southwestern Med Ctr Dallas, Dept Neurosci, Dallas, TX 75390 USA.;Harvard Med Sch, Dept Biol Chem & Mol Pharmacol, Boston, MA 02115 USA..
    Cabuco, Rico
    Univ Texas Southwestern Med Ctr Dallas, Dept Neurosci, Dallas, TX 75390 USA..
    Howard, Rebecca J.
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, S-17121 Solna, Sweden..
    Zaveri, Nurulain T.
    Astraea Therapeut, Mountain View, CA 94043 USA..
    Lindahl, Erik
    KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Engineering Sciences (SCI), Applied Physics.
    Hibbs, Ryan E.
    Univ Texas Southwestern Med Ctr Dallas, Dept Neurosci, Dallas, TX 75390 USA..
    Agonist Selectivity and Ion Permeation in the alpha 3 beta 4 Ganglionic Nicotinic Receptor2019In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 104, no 3, p. 501-+Article in journal (Refereed)
    Abstract [en]

    Nicotinic acetylcholine receptors are pentameric ion channels that mediate fast chemical neurotransmission. The alpha 3 beta 4 nicotinic receptor subtype forms the principal relay between the central and peripheral nervous systems in the autonomic ganglia. This receptor is also expressed focally in brain areas that affect reward circuits and addiction. Here, we present structures of the alpha 3 beta 4 nicotinic receptor in lipidic and detergent environments, using functional reconstitution to define lipids appropriate for structural analysis. The structures of the receptor in complex with nicotine, as well as the alpha 3 beta 4-selective ligand AT-1001, complemented by molecular dynamics, suggest principles of agonist selectivity. The structures further reveal much of the architecture of the intracellular domain, where mutagenesis experiments and simulations define residues governing ion conductance.

  • 4.
    Lindén, Henrik
    et al.
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Tetzlaff, Tom
    Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.
    Potjans, Tobias C.
    Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Research Center Jülich, Germany.
    Pettersen, Klas H.
    Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway .
    Grün, Sonja
    Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Research Center Jülich, Germany.
    Diesmann, Markus
    Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Research Center Jülich, Germany.
    Einevoll, Gaute T.
    Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway.
    Modeling the spatial reach of the LFP2011In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 72, no 5, p. 859-872Article in journal (Refereed)
    Abstract [en]

    The local field potential (LFP) reflects activity of many neurons in the vicinity of the recording electrode and is therefore useful for studying local network dynamics. Much of the nature of the LFP is, however, still unknown. There are, for instance, contradicting reports on the spatial extent of the region generating the LFP. Here, we use a detailed biophysical modeling approach to investigate the size of the contributing region by simulating the LFP from a large number of neurons around the electrode. We find that the size of the generating region depends on the neuron morphology, the synapse distribution, and the correlation in synaptic activity. For uncorrelated activity, the LFP represents cells in a small region (within a radius of a few hundred micrometers). If the LFP contributions from different cells are correlated, the size of the generating region is determined by the spatial extent of the correlated activity.

  • 5. Lundqvist, Mikael
    et al.
    Rose, Jonas
    Herman, Pawel
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Brincat, Scott L.
    Buschman, Timothy J.
    Miller, Earl K.
    Gamma and Beta Bursts Underlie Working Memory2016In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 90, no 1, p. 152-164Article in journal (Refereed)
    Abstract [en]

    Working memory is thought to result from sustained neuron spiking. However, computational models suggest complex dynamics with discrete oscillatory bursts. We analyzed local field potential (LFP) and spiking from the prefrontal cortex (PFC) of monkeys performing a working memory task. There were brief bursts of narrow-band gamma oscillations (45-100 Hz), varied in time and frequency, accompanying encoding and re-activation of sensory information. They appeared at a minority of recording sites associated with spiking reflecting the to-be-remembered items. Beta oscillations (20-35 Hz) also occurred in brief, variable bursts but reflected a default state interrupted by encoding and decoding. Only activity of neurons reflecting encoding/decoding correlated with changes in gamma burst rate. Thus, gamma bursts could gate access to, and prevent sensory interference with, working memory. This supports the hypothesis that working memory is manifested by discrete oscillatory dynamics and spiking, not sustained activity.

  • 6.
    Zhu, Fei
    et al.
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland.;UCL Inst Neurol, Queen Sq, London WC1N 3BG, England..
    Cizeron, Melissa
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland.;Univ Claude Bernard Lyon 1, Univ Lyon, Inst NeuroMyoGene, CNRS,UMR 5310,INSERM,U1217, F-69008 Lyon, France..
    Qiu, Zhen
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland..
    Benavides-Piccione, Ruth
    CSIC, Inst Cajal, E-28002 Madrid, Spain.;UPM, Ctr Tecnol Biomed, Madrid 28223, Spain.;ISCIII, CIBERNED, Madrid 28031, Spain..
    Kopanitsa, Maksym V.
    Synome Ltd, Babraham Res Campus, Cambridge CB22 3AT, England.;Imperial Coll London, UK Dementia Res Inst, London W12 0NN, England..
    Skene, Nathan G.
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland.;UCL Inst Neurol, Queen Sq, London WC1N 3BG, England.;Karolinska Inst, Dept Med Biochem & Biophys, Lab Mol Neurobiol, S-17177 Stockholm, Sweden..
    Koniaris, Babis
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland..
    DeFelipe, Javier
    CSIC, Inst Cajal, E-28002 Madrid, Spain.;UPM, Ctr Tecnol Biomed, Madrid 28223, Spain.;ISCIII, CIBERNED, Madrid 28031, Spain..
    Fransén, Erik
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Komiyama, Noboru H.
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland..
    Grant, Seth G. N.
    Univ Edinburgh, Genes Cognit Program, Ctr Clin Brain Sci, Edinburgh EH16 4SB, Midlothian, Scotland..
    Architecture of the Mouse Brain Synaptome2018In: Neuron, ISSN 0896-6273, E-ISSN 1097-4199, Vol. 99, no 4, p. 781-+Article in journal (Refereed)
    Abstract [en]

    Synapses are found in vast numbers in the brain and contain complex proteomes. We developed genetic labeling and imaging methods to examine synaptic proteins in individual excitatory synapses across all regions of the mouse brain. Synapse catalogs were generated from the molecular and morphological features of a billion synapses. Each synapse subtype showed a unique anatomical distribution, and each brain region showed a distinct signature of synapse subtypes. Whole-brain synaptome cartography revealed spatial architecture from dendritic to global systems levels and previously unknown anatomical features. Synaptome mapping of circuits showed correspondence between synapse diversity and structural and functional connectomes. Behaviorally relevant patterns of neuronal activity trigger spatio-temporal postsynaptic responses sensitive to the structure of synaptome maps. Areas controlling higher cognitive function contain the greatest synapse diversity, and mutations causing cognitive disorders reorganized synaptome maps. Synaptome technology and resources have wide-ranging application in studies of the normal and diseased brain.

1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf