Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience
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Cites methods from "Representational Similarity Analysi..."
...(5) In order to compare the IT representations between the species and to computational models, we use the method of ‘‘representational similarity analysis’’ (Kriegeskorte et al., 2008), in which RDMs are visualized and quantitatively compared....
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1,138 citations
Cites methods from "Representational Similarity Analysi..."
...Representational similarity analysis (RSA) RSA enables us to relate representations obtained from different modalities (e.g. computational models and fMRI patterns) by comparing the dissimilarity patterns of the representations....
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...1 The HMAX model which has been used in [18] was a pre-trained version of the HMAX model; however, in this study we have trained the HMAX model using a dataset that contains 442 animate and 442 inanimate objects....
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...This is the first toolbox to implement RSA....
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...Here we avoid these complications by testing the models in the framework of representational similarity analysis (RSA) [17,18,29,30], in which brain and model representations are compared at the level of the dissimilarity structure of the response patterns....
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...See [6,7,18] for further experimental details....
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900 citations
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Additional excerpts
..., 2000) and locally linear embedding (Roweis and Saul, 2000)....
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13,652 citations
"Representational Similarity Analysi..." refers background in this paper
..., Johnson, 1967; von Luxburg, 2007), as well as nonlinear manifold-learning techniques such as isomap (Tenenbaum et al., 2000) and locally linear embedding (Roweis and Saul, 2000)....
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9,614 citations
"Representational Similarity Analysi..." refers methods in this paper
...Within the classical approach of massively univariate activation-based analysis (Friston et al., 1994, 1995; Worsley and Friston, 1995; Worsley et al., 1992), one way of enriching design has been to parameterize the conditions....
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