Dataset Information

Detecting changes in scenes: the hippocampus is critical for strength-based perception.

ABSTRACT: Recent findings have ignited a controversy over whether the hippocampus is critical for visual perception as well as memory. Some studies have shown that hippocampal damage impairs perception of scenes, but others found no evidence for hippocampal involvement. These studies measured perception as a unitary phenomenon, but recent findings indicate that perceptual discriminations can be based on two kinds of information: states of perceiving local differences or global strength of relational match. In the current study, we separated state- and strength-based perception using a change detection paradigm with scenes. Patients with selective hippocampal damage exhibited significant reductions in strength-based perception but showed spared state-based responses. In a follow-up neuroimaging study, hippocampal activation linearly tracked confidence in strength-based perception, and was not differentially associated with state-based responses. The hippocampus therefore plays a selective role in perception, contributing high-resolution strength information possibly through its role in the representation of relational information.

SUBMITTER: Aly M

PROVIDER: S-EPMC3694276 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Detecting changes in scenes: the hippocampus is critical for strength-based perception.

Aly Mariam M Ranganath Charan C Yonelinas Andrew P AP

Neuron 20130601 6

Recent findings have ignited a controversy over whether the hippocampus is critical for visual perception as well as memory. Some studies have shown that hippocampal damage impairs perception of scenes, but others found no evidence for hippocampal involvement. These studies measured perception as a unitary phenomenon, but recent findings indicate that perceptual discriminations can be based on two kinds of information: states of perceiving local differences or global strength of relational match ...[more]

PMID: 23791201

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Project description:Humans are entertained and emotionally captivated by a good story. Artworks, such as operas, theatre plays, movies, TV series, cartoons, etc., contain implicit stories, which are conveyed visually (e.g., through scenes) and audially (e.g., via music and speech). Story theorists have explored the structure of various artworks and identified forms and paradigms that are common to most well-written stories. Further, typical story structures have been formalized in different ways and used by professional screenwriters as guidelines. Currently, computers cannot yet identify such a latent narrative structure of a movie story. Therefore, in this work, we raise the novel challenge of understanding and formulating the movie story structure and introduce the first ever story-based labeled dataset-the Flintstones Scene Dataset (FSD). The dataset consists of 1, 569 scenes taken from a manual annotation of 60 episodes of a famous cartoon series, The Flintstones, by 105 distinct annotators. The various labels assigned to each scene by different annotators are summarized by a probability vector over 10 possible story elements representing the function of each scene in the advancement of the story, such as the Climax of Act One or the Midpoint. These elements are learned from guidelines for professional script-writing. The annotated dataset is used to investigate the effectiveness of various story-related features and multi-label classification algorithms for the task of predicting the probability distribution of scene labels. We use cosine similarity and KL divergence to measure the quality of predicted distributions. The best approaches demonstrated 0.81 average similarity and 0.67 KL divergence between the predicted label vectors and the ground truth vectors based on the manual annotations. These results demonstrate the ability of machine learning approaches to detect the narrative structure in movies, which could lead to the development of story-related video analytics tools, such as automatic video summarization and recommendation systems.

Dataset Information

Detecting changes in scenes: the hippocampus is critical for strength-based perception.

Publications

Detecting changes in scenes: the hippocampus is critical for strength-based perception.

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