This paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user's preferences as a graph of textual snippets from review text, where the edges are defined by sem ...
Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the h ...
Aversively-motivated associative learning allows animals to avoid harm and thus ensures survival. Aversive learning can be studied by the fear learning paradigm, in which an innocuous sensory stimulus like a tone (conditioned stimulus, CS), acquires a nega ...
Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic netw ...
Evidence from behavioral studies suggests that the spatial origin of sounds may influence the perception of emotional valence. Using 7T fMRI we have investigated the impact of the categories of sound (vocalizations; non-vocalizations), emotional valence (p ...
Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...
Objective: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). ...
