Dependency of amplitude and phase characteristics of vasomotor oscillations on visual stimulation conditions and experiment duration

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Abstract

The intrinsic-signal optical imaging is widely used in experimental, theoretical and applied research of the mammal’s brain neocortex functional anatomy. However, a neural activity signal is hidden by the background activity, the amplitude of which is an order of magnitude larger than the mapping signal amplitude. Most of such background activity represents spontaneous oscillations in 0.01–0.15 Hz frequency range related to vasomotor oscillations. In this paper, we point out that such oscillations change their power and phase during the response time course. The most dramatic influence is intrinsic for 0.05–0.15 Hz oscillations. The power of vasomotor oscillations declines more quickly than the stability features of their phase characteristics. Departing from these data, we suggested approaches for minimization of role of vasomotor oscillations in functional maps resulting from intrinsic-signal optical imaging.

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About the authors

S. A. Kozhukhov

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Author for correspondence.
Email: sergei.kozhukhov@ihna.ru
Russian Federation, Moscow

K. A. Saltykov

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Email: sergei.kozhukhov@ihna.ru
Russian Federation, Moscow

I. V. Bondar

Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences

Email: sergei.kozhukhov@ihna.ru
Russian Federation, Moscow

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2. Fig. 1. An example of data processing for the first block of experiments. (a) – image of a visible part of the cortex recorded by means of intrinsic-signal optical imaging where 1 and 2 corresponds to selected Regions of Interests (ROI): 1 – ROI within the neural tissue, 2 – ROI within the blood vessel; (б) – an example of vasomotor oscillations recorded from the neural tissue (left graph) and blood vessel (right graph). Depicted on ordinate is relative change of intrinsic optical signal, in % from its mean value; (в) – spectrogram for vasomotor oscillations recorded from the neural tissue (left graph) and from the blood vessel (right graph). A vertical dashed line separated very-low frequency (VLF) and low-frequency (LF) oscillation ranges; (г) – dynamics of spectrum power for the very-low-frequency (left graph) and the low-frequency (right graph) oscillations recorded from the neural tissue. The dynamics itself is depicted by the dots where each point corresponds to a particular recording session. Thick line is a trend line obtained by means of linear regression. Dashed lines are displaced from the thick line by the squared mean value of real data vs trend differences. The session start time is depicted on abscissa. (д) – change in stimulus contrast during the whole experiment. (е) – non-monotonic changes in the power of low-frequency (LF) oscillations during the whole experiment

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3. Fig. 2. An example of data processing for the second block of experiments: (а) – an image of the visible part of the cortex recorded by means of intrinsic-signal optical imaging. Designations are the same as in Fig. 1 (a); (б) – examples of vasomotor oscillations recorded at different time sessions. The session start time is at the top of the graphs. The other designations are the same as in Fig. 1 (б); (в) – absolute value of cross-spectral density for pairs of vasomotor oscillations depicted in Fig. (б). A vertical dashed line separated very-low-frequency (at the left) and low-frequency (at-the-right) oscillation ranges; (г) – cross-spectral matrices plotted for very-low-frequency (on the left) and low-frequency (on the right) oscillation ranges. The session start time is depicted on abscissa, another session start time is depicted on ordinate, a color of each point reflects cross-spectrum power for a pair of oscillations related to abcissa and ordinate of that point. Corresponding color code is at the right of both graphs; (д) – dependency of cross-spectral power for two oscillations pairs shown in Fig. (в) and (г) from time lag. A bar height corresponds to the average cross-spectrum power estimated within the 10 minutes interval. Temporary lag value in on the abscissa, cross-spectrum power is on the ordinate; (е) – temporal coherence between records shown above. Time lag is on the abscissa, temporal coherence value is on the ordinate

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4. Fig. 3. Dependency of the power of vasomotor oscillations on time. (а), (б), (в), (г) – an example of such dependency for an animal shown in Fig. 1. Depicted on (а), (б) are oscillations recorded from the neural tissue, shown on (в), (г) are oscillations revealed from the blood vessel. Very-low-frequency oscillations are shown on Fig. (а), (в) and low-frequency oscillations are shown in Fig. (б), (г). Each black point relates to stand-alone recording session. A thick line is a trend line revealed by means of linear regression. Dashed lines are separated from the thick line by the distance equal to standard deviation of real graph from the linear trend. Session start time is depicted on abscissa; (д) – regression slope statistics for very-low-frequency oscillations in the tissue (1), very-low-frequency oscillations from the vessel (2), low-frequency oscillations from the tissue (3) and low-frequency oscillations from the vessel (4). A box plot diagram is plotted for each of these cases which meaning is the following: box borders relate to 25-th and 75-th percentile, a line at the middle of the box is for median value. Black circles relate to single data points. If there is no data lying outside the whiskers, whisker borders relate to maximum and minimum values. Otherwise, the whisker length is 1.5 times higher that interquantile interval

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5. Fig. 4. Temporal coherence of vasomotor oscillations revealed under difference time lags. (а) – temporal coherence for the very-low-frequency oscillations in the tissue, (б) – temporal coherence for the very-low-frequency oscillations in the vessel; (в) – temporal coherence for the low-frequency oscillations in the tissue; (г) – temporal coherence for the low-frequency oscillations in the vessel; (д) – comparison of coherence between very-low-frequency and low-frequency oscillations recorded in neural tissue; (е) – comparison of temporal coherence between very-low-frequency and low-frequency oscillations in the blood vessel. On Fig. (а), (б), (в), (г): box plot description is the same as for Fig. 3. Stars are reliability value for temporal coherence for a given time lag vs temporal coherence for 0.42 hours time lag: * – p < 0.004 (corresponds to reliability threshold of 0.05 after Bonferroni correction), ** – p < 0.0004; *** – p < 0.00004. On Fig. (д), (е): each point represents the mean value, whiskers relate to the standard error of mean

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6. Fig. 5. Change in temporal coherence for vasomotor oscillations related to the change of the time lag: (а) relates to the very-low-frequency oscillations in the tissue; (б) is for very-low-frequency oscillations in the vessel; (в) is for low-frequency oscillations in the tissue; (г) is for low-frequency oscillations in the vessel. Denoted on all figures: a thick line is for regression plotted using medians, other designations are the same as in Fig. 3

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