• Action Representation in the Mouse Parieto-Frontal Network 

      Tombaz, Tuce; Dunn, Benjamin Adric; Hovde, Karoline; Cubero, Ryan John Abat; Mimica, Bartul; Mamidanna, Pranav; Roudi, Yasser; Whitlock, Jonathan (Peer reviewed; Journal article, 2020)
      The posterior parietal cortex (PPC) and frontal motor areas comprise a cortical network supporting goal-directed behaviour, with functions including sensorimotor transformations and decision making. In primates, this network ...
    • Correlations and functional connections in a population of grid cells 

      Dunn, Benjamin Adric; Mørreaunet, Maria; Roudi, Yasser (Journal article; Peer reviewed, 2015)
      We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising ...
    • Decoding of neural data using cohomological feature extraction 

      Rybakken, Erik; Baas, Nils A.; Dunn, Benjamin Adric (Journal article; Peer reviewed, 2019)
      We introduce a novel data-driven approach to discover and decode features in the neural code coming from large population neural recordings with minimal assumptions, using cohomological feature extraction. We apply our ...
    • Detecting Neuronal Activity with Lasso Penalized Logistic Regression 

      Kristiansen, Dag Johnsrud (Master thesis, 2019)
      Hjernen er det mest komplekse organet i dyr, der det kontinuerlig overføres signaler mellom dens cellulære komponenter. Vi vil i denne oppgaven undersøke hvordan slik informasjon flyter, og prøve å fastslå enkelte koblinger. ...
    • Kunstige nevrale nettverk for deteksjon av aksjonspotensialer i kalsiumbildedata 

      Antonsen, Mikkel (Master thesis, 2016)
      I oppgaven blir forskjellige nettverksarkitekturer og regulariseringsteknikker for kunstige nevrale nettverk undersøkt for om de kan brukes til å finne den underliggende årsaken til kalsiumbildedata. En arkitektur som ...
    • Learning with unknowns: analyzing biological data in the presence of hidden variables 

      Battistin, Claudia; Dunn, Benjamin Adric; Roudi, Yasser (Journal article, 2017)
      Despite our improved ability to probe biological systems at a higher spatio-temporal resolution, the high dimensionality of the biological systems often prevents sufficient sampling of the state space. Even with large scale ...
    • The appropriateness of ignorance in the inverse kinetic Ising model 

      Dunn, Benjamin Adric; Battistin, Claudia (Journal article; Peer reviewed, 2017)
      We develop efficient ways to consider and correct for the effects of hidden units for the paradigmatic case of the inverse kinetic Ising model with fully asymmetric couplings. We identify two sources of error in reconstructing ...
    • Topologisk dataanalyse på konvolusjonelle nevrale nettverk 

      Larsen, Tor Erik (Master thesis, 2020)
      I denne oppgaven presenteres et forsøk på å gjenskape den såkalte primærsirkelen av pikselmatriser i vektorrommet av vekter i et konvolusjonelt nevralt nettverk (CNN) trent på et bildedatasett, ved hjelp av åpen kildekode ...
    • Using persistent homology to reveal hidden covariates in systems governed by the kinetic Ising model 

      Spreemann, Gard; Dunn, Benjamin Adric; Botnan, Magnus; Baas, Nils A. (Journal article; Peer reviewed, 2018)
      We propose a method, based on persistent homology, to uncover topological properties of a priori unknown covariates in a system governed by the kinetic Ising model with time-varying external fields. As its starting point ...