We consider two types of causes leading to information loss when neural activities are passed and processed in the brain. One is responses of upstream neurons to stimuli being imperfectly observed by downstream neurons. The other is upstream neurons non-optimally decoding stimuli information contained in the activities of the downstream neurons. To investigate the importance of neural correlation in information processing in the brain, we specifically consider two situations. One is when neural responses are not simultaneously observed, i.e., neural correlation data is lost. This situation means that stimuli information is decoded without any specific assumption about neural correlations. The other is when stimuli information is decoded by a wrong statistical model where neural responses are assumed to be independent even when they are not. We provide the information geometric interpretation of these two types of information loss and clarify their relationship. We then concretely evaluate these types of information loss in some simple examples. Finally, we discuss use of these evaluations of information loss to elucidate the importance of correlation in neural information processing.
Keywords: Fisher information; coincidence detection; correlated activity; imperfect observation; information geometry; information loss; mismatched decoding.