Multi-Connection Pattern Analysis: Decoding the representational content of neural communication
نویسندگان
چکیده
The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions.
منابع مشابه
Title: Multi-Connection Pattern Analysis: Decoding the Representational Content of Neural Communication
What information is represented in the interactions between neural populations is unknown due to the lack of multivariate methods for decoding the representational content of neural communication. Here we present Multi-Connection Pattern Analysis (MCPA), which probes the involvement of distributed computational processing and probe the representational structure of neural interactions. MCPA lea...
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ورودعنوان ژورنال:
- NeuroImage
دوره 162 شماره
صفحات -
تاریخ انتشار 2017