• 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 ...
    • Dynamics of randomly connected neural networks and inference in the presence of hidden nodes 

      Battistin, Claudia (Doctoral theses at NTNU;2018:380, Doctoral thesis, 2018)
      Dynamikken til randomiserte nevrale nettverk og inferens med tilstedeværelse av skjulte noder Hjernen koder informasjon i populasjoner av nevroner, i motsetning til i enkeltceller. Modeller av nevrale nettverk kan hjelpe ...
    • Evaluating the quality of pairwise maximum entropy models in large neural datasets 

      Kargård Olsen, Valdemar (Master thesis, 2023)
      En intuitiv og tiltrekkende modell for å beskrive aktiviteten i en populasjon av nevroner er den parevise maksimalentropi-modellen. Denne modellen har vist seg å være god til å finne de eksperimentelt observerte sannsynlighetene ...
    • Functional reconstruction of a grid cell network 

      Dunn, Benjamin (Doctoral thesis at NTNU;2016:2016:193, Doctoral thesis, 2016)
      Norwegian summary: Gitterceller er sannsynligvis én av de enkleste representasjoner av verden i et pattedyrs hjerne i det hver eneste celle viser økt aktivitet ved knutepunkter i dyrets lokale miliø og så gir en ...
    • Grid cells and cortical representation 

      Moser, Edvard Ingjald; Roudi, Yasser; Witter, Menno; Kentros, Clifford; Bonhoeffer, Tobias; Moser, May-Britt (Journal article; Peer reviewed, 2014)
      One of the grand challenges in neuroscience is to comprehend neural computation in the association cortices, the parts of the cortex that have shown the largest expansion and differentiation during mammalian evolution and ...
    • Hippocampal spike‐time correlations and place field overlaps during open field foraging 

      Monsalve-Mercado, Mauro; Roudi, Yasser (Journal article; Peer reviewed, 2019)
      Phase precessing place cells encode spatial information on fine timescales via the timing of their spikes. This phase code has been extensively studied on linear tracks and for short runs in the open field. However, less ...
    • Investigating the Consistency and Convexity of Restricted Boltzmann Machine Learning 

      Juel, Bjørn Erik (Master thesis, 2013)
      In this thesis we asses the consistency and convexity of the parameter inference in Boltzmann machine learning algorithms based on gradient ascent on the likelihood surface. We do this by rst developing standard tools for ...
    • Learning functional connectivity in the under-sampled regime 

      Bulso, Nicola (Doctoral theses at NTNU;2020:128, Doctoral thesis, 2020)
      Læring funksjonell tilkobling i under-samplet regime Siden de første dagene har nevrovitenskap forsker merket at den elektriske aktiviteten til noen nevroner i hjernen korrelerer med spesifikke trekk i den ekstern verden. ...
    • 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 ...
    • Minimum Description Length codes are critical 

      Cubero, Ryan John Abat; Marsili, Matteo; Roudi, Yasser (Journal article; Peer reviewed, 2018)
      In the Minimum Description Length (MDL) principle, learning from the data is equivalent to an optimal coding problem. We show that the codes that achieve optimal compression in MDL are critical in a very precise sense. ...
    • Minimum Description Length Codes Are Critical 

      Cubero, Ryan John Abat; Marsili, Matteo; Roudi, Yasser (Journal article; Peer reviewed, 2018)
      In the Minimum Description Length (MDL) principle, learning from the data is equivalent to an optimal coding problem. We show that the codes that achieve optimal compression in MDL are critical in a very precise sense. ...
    • Novel Model Selection Criterion for Inference of Ising Models 

      Tarlton, Michael (Master thesis, 2021)
      In this thesis we evaluate the performance of the novel Model Selection criteria proposed in Bulso et al. 2019, for inference of network topologies. To this purpose, we consider networks of binary nodes whose probability ...
    • Path integral methods for the dynamics of stochastic and disordered systems 

      Hertz, John A.; Roudi, Yasser; Sollich, Peter (Journal article; Peer reviewed, 2017)
      We review some of the techniques used to study the dynamics of disordered systems subject to both quenched and fast (thermal) noise. Starting from the Martin–Siggia–Rose/Janssen–De Dominicis–Peliti path integral formalism ...
    • Phase transitions and asymmetry between signal comprehension and production in biological communication 

      Salahshour, Mohammad; Rouhani, Shahin; Roudi, Yasser (Journal article; Peer reviewed, 2019)
      We introduce a model for collective information acquisition from the environment, in a biological population. In this model, individuals can make noisy observations of the environment, and communicate their observation by ...
    • Reverse engineering a grid cell network 

      Mørreaunet, Maria (Master thesis, 2013)
      The neural circuitry comprising what is assumed to be the brain`s spatial navigation system has been investigated by scientists for decades. Research has revealed how the neural networks underlying this cognitive function ...
    • Sparse model selection in the highly under-sampled regime 

      Bulso, Nicola; Marsili, Matteo; Roudi, Yasser (Journal article, 2016)
      We propose a method for recovering the structure of a sparse undirected graphical model when very few samples are available. The method decides about the presence or absence of bonds between pairs of variable by considering ...
    • Task-dependent mixed selectivity in the subiculum 

      Ledergerber Wäfler, Debora; Battistin, Claudia; Blackstad, Jan Sigurd; Gardner, Richard; Witter, Menno; Moser, May-Britt; Roudi, Yasser; Moser, Edvard Ingjald (Peer reviewed; Journal article, 2021)
      CA1 and subiculum (SUB) connect the hippocampus to numerous output regions. Cells in both areas have place-specific firing fields, although they are more dispersed in SUB. Weak responses to head direction and running speed ...
    • The Distribution of Spatial Phases of Grid Cells 

      Wennberg, Daniel (Master thesis, 2015)
      Grid cells, found in the medial entorhinal cortex of mammalian brains, are among the most significant discoveries from the research into the brain's system for spatial navigation during the last decades. A lot of work has ...