Genetic Depletion of BDNF Impairs Extinction Learning of a Spatial Appetitive Task in the Presence or Absence of the Acquisition Context
Marta Méndez-Couz, Beate Krenzek, Denise Manahan-Vaughan
Frontiers in Behavioral Neuroscience · 2021
doi:10.3389/fnbeh.2021.658686 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
Brain derived neurotropic factor (BDNF) supports neuronal survival, growth, and differentiation and is involved in forms of hippocampus-dependent and independent learning, as well as hippocampus-dependent learning. Extinction learning comprises active inhibition of no-longer relevant learned information, in conjunction with a decreased response of a previously learned behavior. It is highly dependent on context, and evidence exists that it requires hippocampal activation. The participation of BDNF in memory processing is experience-dependent. For example, BDNF has been associated with synaptic plasticity needed for spatial learning, and it is involved in acquisition and extinction learning of fear conditioning. However, little is known about its role in spatial appetitive extinction learning. In this study, we evaluated to what extent BDNF contributes to spatial appetitive extinction learning in the presence (ABA) or absence (AAA) of exposure to the acquisition context. Daily training, of BDNF+/−-mice or their wildtype (WT) littermates, to reach acquisition criterion in a T-maze, resulted in a similar performance outcome. However, extinction learning was delayed in the AAA, and impaired in the ABA-paradigm compared to performance in WT littermates. Trial-by-trial learning analysis indicated differences in the integration of the context into extinction learning by BDNF+/−-mice compared to WT littermates. Taken together, these results support an important role for BDNF in processes that relate to information updating and retrieval that in turn are crucial for effective extinction learning.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.