### Abstract

We study a population decoding paradigm in which the maximum likelihood inference is based on an unfaithful decoding model (UMLI). This is usually the case for neural population decoding because the encoding process of the brain is not exactly known, or because a simplified decoding model is preferred for saving computational cost. We consider an unfaithful decoding model which neglects the pair-wise correlation between neuronal activities, and prove that UMLI is asymptotically efficient when the neuronal correlation is uniform or of limited-range. The performance of UMLI is compared with that of the maximum likelihood inference based on a faithful model and that of the center of mass decoding method. It turns out that UMLI has advantages of decreasing the computational complexity remarkablely and maintaining a high-level decoding accuracy at the same time. The effect of correlation on the decoding accuracy is also discussed.

Original language | English |
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Title of host publication | Advances in Neural Information Processing Systems |

Publisher | Neural information processing systems foundation |

Pages | 192-198 |

Number of pages | 7 |

ISBN (Print) | 0262194503, 9780262194501 |

Publication status | Published - 2000 |

Externally published | Yes |

Event | 13th Annual Neural Information Processing Systems Conference, NIPS 1999 - Denver, CO Duration: 1999 Nov 29 → 1999 Dec 4 |

### Other

Other | 13th Annual Neural Information Processing Systems Conference, NIPS 1999 |
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City | Denver, CO |

Period | 99/11/29 → 99/12/4 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Networks and Communications
- Information Systems
- Signal Processing

### Cite this

*Advances in Neural Information Processing Systems*(pp. 192-198). Neural information processing systems foundation.

**Population decoding based on an unfaithful model.** / Wu, S.; Nakahara, H.; Murata, Noboru; Amari, S.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Advances in Neural Information Processing Systems.*Neural information processing systems foundation, pp. 192-198, 13th Annual Neural Information Processing Systems Conference, NIPS 1999, Denver, CO, 99/11/29.

}

TY - GEN

T1 - Population decoding based on an unfaithful model

AU - Wu, S.

AU - Nakahara, H.

AU - Murata, Noboru

AU - Amari, S.

PY - 2000

Y1 - 2000

N2 - We study a population decoding paradigm in which the maximum likelihood inference is based on an unfaithful decoding model (UMLI). This is usually the case for neural population decoding because the encoding process of the brain is not exactly known, or because a simplified decoding model is preferred for saving computational cost. We consider an unfaithful decoding model which neglects the pair-wise correlation between neuronal activities, and prove that UMLI is asymptotically efficient when the neuronal correlation is uniform or of limited-range. The performance of UMLI is compared with that of the maximum likelihood inference based on a faithful model and that of the center of mass decoding method. It turns out that UMLI has advantages of decreasing the computational complexity remarkablely and maintaining a high-level decoding accuracy at the same time. The effect of correlation on the decoding accuracy is also discussed.

AB - We study a population decoding paradigm in which the maximum likelihood inference is based on an unfaithful decoding model (UMLI). This is usually the case for neural population decoding because the encoding process of the brain is not exactly known, or because a simplified decoding model is preferred for saving computational cost. We consider an unfaithful decoding model which neglects the pair-wise correlation between neuronal activities, and prove that UMLI is asymptotically efficient when the neuronal correlation is uniform or of limited-range. The performance of UMLI is compared with that of the maximum likelihood inference based on a faithful model and that of the center of mass decoding method. It turns out that UMLI has advantages of decreasing the computational complexity remarkablely and maintaining a high-level decoding accuracy at the same time. The effect of correlation on the decoding accuracy is also discussed.

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M3 - Conference contribution

AN - SCOPUS:84898973185

SN - 0262194503

SN - 9780262194501

SP - 192

EP - 198

BT - Advances in Neural Information Processing Systems

PB - Neural information processing systems foundation

ER -