---
res:
  bibo_abstract:
  - "The hippocampus is central to memory formation, storage and retrieval over many\r\ntimescales.
    Neurons in this brain area are highly selective to spatial position as well as
    to many\r\nother variables of the environment. It is believed that the selectivity
    patterns of hippocampal\r\nneurons reflect the structure of tasks an animal performs.
    However, especially at timescales\r\nlonger than a few minutes or hours it is
    not fully known how these representations evolve, nor\r\nhow they map to behaviour
    in the process. In this thesis, I monitored the evolution of\r\nhippocampal representations
    in a novel spatial-associative memory task for rats. Reward\r\nlocations were
    associated with global sensory cues (i.e. context); animals had to remember the\r\nassociations
    and dig for food in those locations only. I used in vivo electrophysiology to
    record\r\nthe activity of the hippocampus dorsal CA1 neurons during the learning
    period of a few days.\r\nI report here a novel and simple method to classify behaviour
    performance to account\r\nfor individual variability in learning speed and spurious
    performance unrelated to true task rule\r\nlearning. Using this classification
    I was then able to investigate neural responses on different\r\nstages of learning
    matched across animals. On the first day of learning, I observed a fast\r\nformation
    of single-cell selectivity to task variables which remained stable over days.
    I also\r\nobserved that reward tuning was not a single process but dependent on
    task-related cognitive\r\nload. At the population level, a linear decoding approach
    revealed a hierarchy in the\r\nrepresentation of task variables that changed with
    learning. In the high-dimensional space of\r\npopulation activity, the representation
    of contexts was specific to each position in the maze, and\r\ncould thus be better
    decoded if the position was known. The decoding of position did not improve\r\nwith
    knowledge of other variables. As learning progressed, the hippocampal code underwent
    a\r\nreorganisation of high-variance directions in population activity, identified
    by principal\r\ncomponent analysis. I found that dominant dimensions started carrying
    increasing amounts of\r\ninformation about task context specifically at those
    positions where it mattered for task\r\nperformance. When I contrasted this with
    variables less relevant to task performance (e.g.\r\nmovement direction), I did
    not observe differences in decoding quality over positions nor a\r\nreduction
    of dimensionality with learning.\r\nOverall, the largest changes in CA1 neural
    response with task learning happened in a\r\nmatter of a few trials; over days,
    changes undetectable in single-cell statistics were responsible\r\nfor re-structuring
    the hierarchy of neural representations at the population level; these changes\r\nwere
    task-specific and reflected different stages of learning. This indicates that
    complex task\r\nlearning may involve different magnitudes of response modulation
    in CA1, which happen at\r\nspecific time scales linked to behaviour.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Heloisa
      foaf_name: Chiossi, Heloisa
      foaf_surname: Chiossi
      foaf_workInfoHomepage: http://www.librecat.org/personId=2BBA502C-F248-11E8-B48F-1D18A9856A87
    orcid: 0009-0004-2973-278X
  bibo_doi: 10.15479/at:ista:14821
  dct_date: 2024^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/2663-337X
  dct_language: eng
  dct_publisher: Institute of Science and Technology Austria@
  dct_title: Adaptive hierarchical representations in the hippocampus@
...