diff --git a/wholeBrain_main.md b/wholeBrain_main.md index 5832a9d..fb10c59 100644 --- a/wholeBrain_main.md +++ b/wholeBrain_main.md @@ -52,6 +52,32 @@ frequency | 2.9 | | | domains/sec/hemisphere +## Cortical activity is mirrored between the hemispheres + +* Inter hemispheric functional connectivity, importance for autism, schizophrenia. Maybe an activity-dependent mechanism for commisural connectivity. +* olavarria work, evidence for inter hemispheric activity dependence +* [#Hanganu:2006], 30% of spindle bursts correlated across hemispheres +* Activity correlated in anterior-posterior and medial-lateral directions +* Mirror symmetric and non-mirror symmetric patterns +* Regional effects, more corr anticorr in certain regions? +* State dependent corr? + + + +![**Figure 2.** Cortical domain activity exhibits bilateral symmetry. **a** Examples of domains exhibiting spatially symmetric activations. Notice most timepoints contain a mixture of symmetric and asymmetric domain activations. **b** Hemispheric domain centers of mass for coactive frames in a recording along medial-lateral (ML) and anterior-posterior (AP) extents. Bottom left panels show the periods indicated by black bars at expanded view. Pearson's correlation: ML, p = 1.1591e-28; AP, p = 7.0982e-07. **d** Hemispheric autocorrelation and cross-correlation functions for cortical activity at all and short time lags. Notice the peaks above gaussian distributed noise (blue traces).](figure2.png) + + + +**Conclusions:** The two hemispheres seem to be mostly synchronized, though it’s possible the R hemispshere (which is also the slightly more ‘active’ hemisphere, see stats table below) leads the left by a bit. The asymmetric peak at –150–175frames is interesting. That would be about 30–35 sec. + +The big secondary peaks around ±30 sec is present in both autocorrs and xcorrs and is far above the random normal xcorr baseline (blue trace). In fact there is a periodicity seen in the autocorrs and the xcorrs where there is a dampening oscillation about on this interval! (See ideal dampening frequency in random sine wave example above). This corresponds to a 1/30sec == 0.033 Hz ultra-slow oscillation. + +Looking at the above plot showing lags from [–1000, 1000] frames which is ± 200 s, we can see about 5.5 cycles of this underlying dampening oscillation in both autocorr plots. This corresponds to (1000fr*0.2sec/fr)/5.5 => 36.36 sec/cycle => 0.0275 cycles/sec or ~0.03 Hz + +**Conclusions:** So the activity in both hemispheres at postnatal day 3 (P3) clearly exhibits significant spatial correlations in both in the medial-lateral and anterior-extent. This is consistent with and complementary to the fact that the active pixel fraction in each hemisphere exhibits a strong temporal correlation as I found earlier in this report [Temporal correlation of activity][]. The medial-lateral positional correlation is stronger than the anterior-posterior (higher *R* and lower *p* value). The total number of coactive frames is `numel(y1(~isnan(y1)&~isnan(y2)))` == **1114 frames**. This is accounts to **37.13%** of the movie or **222.8 s**. Cortex.L had 1635 actvFrames and cortex.R had 1677 actvFrames which means that each hemisphere was coactive with the other hemisphere 1114/1635 == **68.13%** and 1114/1677 == **66.43%** of the active time respectively. + + + @@ -65,16 +91,7 @@ frequency | 2.9 | | | domains/sec/hemisphere <120518_09_mjpeg.mov> -![**Figure 2.** Cortical domains are state dependent. **a** Experimental schematic. Red light illumination measured with a photodiode (PD) was used to monitor motor activity. **b** dF/F image sequence showing cortical domain activity before and after isoflurane anesthesia within a single recording. **c** Cortical activity (active fraction) in each hemisphere after onset of gas anesthetic. **d** Hemispheric autocorrelation and cross-correlation functions for cortical activity at all and short time lags. Notice the peaks above gaussian distributed noise (blue traces). **e** Cortical activity and coincident motor activity signals. Moving averages of cortical and motor activity at 10 s and >70 s windows. **f** Single frame domain masks for times indicated in **e**. **g** Autocorrelation and cross-correlation functions for cortical and motor activity for the whole recording or during just the active-motor-period. Notice the correlation between cortical and motor activity above random noise and that motor activity generally follows cortical activity (shift towards right).](figure2.png) - - -Conclusions: The two hemispheres seem to be mostly synchronized, though it’s possible the R hemispshere (which is also the slightly more ‘active’ hemisphere, see stats table below) leads the left by a bit. The asymmetric peak at –150–175frames is interesting. That would be about 30–35 sec. - -The big secondary peaks around ±30 sec is present in both autocorrs and xcorrs and is far above the random normal xcorr baseline (blue trace). In fact there is a periodicity seen in the autocorrs and the xcorrs where there is a dampening oscillation about on this interval! (See ideal dampening frequency in random sine wave example above). This corresponds to a 1/30sec == 0.033 Hz ultra-slow oscillation. - -Looking at the above plot showing lags from [–1000, 1000] frames which is ± 200 s, we can see about 5.5 cycles of this underlying dampening oscillation in both autocorr plots. This corresponds to (1000fr*0.2sec/fr)/5.5 => 36.36 sec/cycle => 0.0275 cycles/sec or ~0.03 Hz - - +![**Figure 3.** Cortical domains are state dependent. **a** Experimental schematic. Red light illumination measured with a photodiode (PD) was used to monitor motor activity. **b** dF/F image sequence showing cortical domain activity before and after isoflurane anesthesia within a single recording. **c** Cortical activity (active fraction) in each hemisphere after onset of gas anesthetic. **e** Cortical activity and coincident motor activity signals. Moving averages of cortical and motor activity at 10 s and >70 s windows. **f** Single frame domain masks for times indicated in **e**. **g** Autocorrelation and cross-correlation functions for cortical and motor activity for the whole recording or during just the active-motor-period. Notice the correlation between cortical and motor activity above random noise and that motor activity generally follows cortical activity (shift towards right).](figure3.png) @@ -90,24 +107,10 @@ lenActvFraction>0 | fracCorr | timeCorr_s | fracCorrPos | timeCorrPos_s | fracCo +## Developing cortical networks consist of distinct modules. -## Cortical activity is mirrored between the hemispheres +![**Figure 4.** Subnetworks in developing isocortex. **a** Areal trace examples. **b** Correlation matrix of domain activity among cortical areas. **c** Graph.](figure4.png) -* Inter hemispheric functional connectivity, importance for autism, schizophrenia. Maybe an activity-dependent mechanism for commisural connectivity. -* olavarria work, evidence for inter hemispheric activity dependence -* [#Hanganu:2006], 30% of spindle bursts correlated across hemispheres -* Activity correlated in anterior-posterior and medial-lateral directions -* Mirror symmetric and non-mirror symmetric patterns -* Regional effects, more corr anticorr in certain regions? -* State dependent corr? - - - -![**Figure 3.** Cortical domain activity exhibits bilateral symmetry. **a** Examples of domains exhibiting spatially symmetric activations. Notice most timepoints contain a mixture of symmetric and asymmetric domain activations. **b** Hemispheric domain centers of mass for coactive frames in a recording along medial-lateral (ML) and anterior-posterior (AP) extents. Bottom left panels show the periods indicated by black bars at expanded view. Pearson's correlation: ML, p = 1.1591e-28; AP, p = 7.0982e-07. **c** Correlation matrix of domain activity among cortical areas.](figure3.png) - - - -**Conclusions:** So the activity in both hemispheres at postnatal day 3 (P3) clearly exhibits significant spatial correlations in both in the medial-lateral and anterior-extent. This is consistent with and complementary to the fact that the active pixel fraction in each hemisphere exhibits a strong temporal correlation as I found earlier in this report [Temporal correlation of activity][]. The medial-lateral positional correlation is stronger than the anterior-posterior (higher *R* and lower *p* value). The total number of coactive frames is `numel(y1(~isnan(y1)&~isnan(y2)))` == **1114 frames**. This is accounts to **37.13%** of the movie or **222.8 s**. Cortex.L had 1635 actvFrames and cortex.R had 1677 actvFrames which means that each hemisphere was coactive with the other hemisphere 1114/1635 == **68.13%** and 1114/1677 == **66.43%** of the active time respectively. # Conclusions