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Published on: January 10, 2019
Quantitative assessment of the temporal stability of orientation maps using intrinsic signal optical imaging in cat
Ting Wang1, Kazuhiro Takahashi1, Jun-Ya Okamura1
1Biological Cognitive Informatics Course, Informatics Program, Department of Informatics, Graduate School of Science and Engineering, Kagoshima University, 1-21-40 Korimoto, Kagoshima 890-0065, Japan.
Background:
Intrinsic signal optical imaging (ISOI) is widely used to visualize functional organization in the visual cortex. However, intrinsic optical signals exhibit complex temporal dynamics, and the temporal stability of orientation maps during signal development remains poorly understood.
New Method:
We developed a quantitative framework for evaluating the temporal stability of orientation maps. Responsive cortical regions were extracted using combined response-magnitude and statistical-significance criteria. Temporal similarity among orientation maps was quantified using correlation analysis, and orientation distributions were examined over time.
Results:
In cat visual cortex, intrinsic optical responses gradually increased after stimulus onset and peaked at approximately 2.5 s. In contrast, orientation-selective spatial patterns emerged rapidly and became identifiable 0.5 s after stimulus onset. Their similarity to the reference map increased progressively during the early response phase, reaching a plateau at approximately 2.5 s after stimulus onset, after which the maps remained highly stable.
Comparison With Existing Methods:
Unlike conventional analyses that evaluate maps only at peak response amplitude, the proposed framework quantitatively assesses map stability throughout the temporal evolution of intrinsic optical signals. The combined extraction criterion also improves the reliability of responsive-area identification.
Conclusions:
Stable orientation-selective spatial patterns are established substantially earlier than peak intrinsic response amplitude. The proposed framework provides a practical method for evaluating the temporal reliability of functional maps obtained using ISOI.
