fig rework

methods.txt

@@ -12,7 +12,7 @@
 
 **Calcium domain analysis.** The mean width in the medial-lateral and height in the rostral-caudal dimensions of the bounding box fitted to each segmented calcium domain signal was taken to be the domain diameter. The number of contiguous frames (bounding box depth) for each segmented calcium domain was taken to be the domain duration. The mean and maximum pixel intensities within each domain were taken as the mean and maximum domain amplitudes. Domains were assigned areal membership by intersection of the domain centroid with a cortical ares's pixel mask. The number of individual domains per recording within a hemisphere or cortical area was taken to be domain frequency.
 
-**Functional correlation analysis.** A binary movie array from all the segmented calcium domain masks for a recording was intersected mask representing different cortical areas. The total number of active pixels per frame expressed as a fraction of possibly active pixels per frame for each cortical area gave active pixel fraction timecourses for each cortical area in each recording. Correlation matrices were calculated for each recording by computing pairwise Pearson's product moment correlation coefficents from the matrix containing the cortical active pixel fraction timecourses. The binarized correlation matrix at *r* > 0.1 was used to form an adjacency matrix with each node representing a cortical area and each edge representing an association between a pair of nodes at weight, *r*. Community structure was detected within each functional association matrix using a fast greedy modularity optimization algorithm [#Clauset:2004] to perform hierarchial clustering using the igraph network analysis software library [#Csardi:2013]. 
+**Functional correlation analysis.** A binary movie array from all the segmented calcium domain masks for a recording was intersected mask representing different cortical areas. The total number of active pixels per frame expressed as a fraction of possibly active pixels per frame for each cortical area gave active pixel fraction timecourses for each cortical area in each recording. Correlation matrices were calculated for each recording by computing pairwise Pearson's product moment correlation coefficents from the matrix containing the cortical active pixel fraction timecourses. The binarized correlation matrix at *r* > 0.1 was used to form an adjacency matrix with each node representing a cortical area and each edge representing an association between a pair of nodes at weight, *r*. Community structure was detected within each functional association matrix using a fast greedy modularity optimization algorithm [#Clauset:2004] to perform hierarchical clustering using the igraph network analysis software library [#Csardi:2013]. 
 
 [#Ackman:2012]: Ackman, J. B., Burbridge, T. J., and Crair, M. C. (2012).  Retinal waves coordinate patterned activity throughout the developing visual system, Nature, 490(7419), 219-25
 

wholeBrain_main.md

@@ -12,19 +12,19 @@ James B. Ackman¹, Hongkui Zeng², and Michael C. Crair¹
 
 # Summary  
 
-The cerebral cortex exhibits spontaneous and sensory evoked patterns of activity during fetal and postnatal development that are crucial for the activity-dependent formation and refinement of neural circuits [#Katz:1996]. Knowing the source and flow of these activity patterns locally and globally is crucial to understanding self-organization in the developing brain. Here we show that neural population activity within newborn mice in vivo is characterized by spatially discrete domains that are coordinated in a state dependent and areal dependent fashion throughout developing neocortex. Whole brain optical recordings from neonatal mice expressing a genetic calcium reporter showed that ongoing activity in the cerebral cortex was characterized by distinct and repetitively active domains measuring hundreds of microns in diameter. Domain activity exhibited mirror-symmetric patterns between the hemispheres, with strong correlations between specific portions of frontal and parietal cortex. Ongoing activity across the cortical hemispheres showed characteristic network architectures with a frontal-motor regions functionally connected to a parietal-sensory areas through secondary motor/cingulate cortex, retrosplenial cortex, and posterior parietal cortex. Furthermore, ongoing activity was regulated by physiological state with cortical regions exhibiting areal dependent coordination of activity with motor behavior differentially during the course of development. This study provides the first comprehensive description of population activity in the developing neocortex at a scope and scale that bridges the microscopic or macroscopic spatiotemporal resolutions provided by traditional neurophysiological or neuroimaging techniques. Mesoscale maps of cortical population dynamics within animal models will be vital to future engineering of repair strategies and brain-machine interfaces for neurodevelopmental disorders.
+The cerebral cortex exhibits spontaneous and sensory evoked patterns of activity during development that are crucial for the activity-dependent formation and refinement of neural circuits. Knowing the source and flow of these activity patterns locally and globally is crucial to understanding self-organization in the developing brain. Here we show that neural population activity within newborn mice in vivo is characterized by spatially discrete domains that are coordinated in a state dependent and areal dependent fashion throughout developing neocortex. Whole brain optical recordings from neonatal mice expressing a genetic calcium reporter showed that ongoing activity in the cerebral cortex was characterized by distinct and repetitively active domains measuring hundreds of microns in diameter. Domain activity exhibited mirror-symmetric patterns between the hemispheres, with strong correlations between specific portions of frontal and parietal cortex. Ongoing activity across the cortical hemispheres showed characteristic network architectures with a frontal-motor regions functionally connected to a parietal-sensory areas through secondary motor/cingulate cortex, retrosplenial cortex, and posterior parietal cortex. Furthermore, ongoing activity was regulated by physiological state with cortical regions exhibiting areal dependent coordination of activity with motor behavior differentially during the course of development. This study provides the first comprehensive description of population activity in the developing neocortex at a scope and scale that bridges the microscopic or macroscopic spatiotemporal resolutions provided by traditional neurophysiological or neuroimaging techniques. Mesoscale maps of cortical population dynamics within animal models will be vital to future engineering of repair strategies and brain-machine interfaces for neurodevelopmental disorders.
 
 # Introduction  
 
-Brain development requires neural activity for establishing proper circuit structure and function [#Katz:1996]. The importance of perinatal neural activity can be easily recognized in children exposed to chemical agents affecting neurotransmission early in development that result in severe brain malformations, epilepsy, and mental retardation. Indeed, embryonic limb movements in species ranging from chick to human are thought to be initiated by spontaneous motor neuron activity in the spinal cord and thought to be crucial for activity-dependent development of motor synapses [#Sanes:1999][#Petersson:2003][#Marder:2005]. However it is only recently that we have begun to appreciate the underlying patterns of persistent neural activity that exist in the developing brain in vivo. For example, sensori-motor feedback associated with spontaneous movement generated by spinal motor neurons triggers synchronized 'spindle-burst' potentials among cells in somatosensory cortex [#Khazipov:2004a][#Yang:2009] before the start of locomotion and tactile behavior. Correlated bursts of activity occur in the developing rat hippocampus in vivo [#Leinekugel:2002][#Mohns:2008]. Spontaneous retinal waves drive patterned activation of circuits throughout the immature visual system before the onset of vision [#Ackman:2012] [#Hanganu:2006][#Colonnese:2010]. Furthermore, prenatal EEG recordings have demonstrated spindle burst oscillations and slow activity transients in the human infant somatosensory and occipital cortices before birth [#Vanhatalo:2005][#Tolonen:2007]. However, a comprehensive account of the dynamical patterns of persistent activity across the developing neocortex in vivo has not been undertaken, largely because a method to assess neural activity between cortical areas simultaneously and non-invasively has not been available.
+Brain development requires neural activity for establishing proper circuit structure and function [#Katz:1996]. Fetal movements, prenatal electroencephalographic oscillations [#Vanhatalo:2005][#Tolonen:2007], and sensitivity to disruptions in periphreal inputs affecting neurotransmission all underscore the presence and importance of neural activity in the developing brain. Indeed, embryonic limb movements in species ranging from chick to human are thought to be initiated by spontaneous motor neuron activity in the spinal cord and thought to be crucial for activity-dependent development of motor synapses [#Sanes:1999][#Petersson:2003][#Marder:2005]. However it is only recently that we have begun to appreciate the underlying patterns of persistent neural activity that exist in the developing brain in vivo. For example, sensori-motor feedback associated with spontaneous movement generated by spinal motor neurons triggers synchronized 'spindle-burst' potentials among cells in somatosensory cortex [#Khazipov:2004a][#Yang:2009] before the start of locomotion and tactile behavior. Correlated bursts of activity occur in the developing rat hippocampus in vivo [#Leinekugel:2002][#Mohns:2008]. Spontaneous retinal waves drive patterned activation of circuits throughout the immature visual system before the onset of vision [#Ackman:2012][#Colonnese:2010]. However, a comprehensive account of the dynamical patterns of persistent activity across the developing neocortex in vivo has not been undertaken, largely because a method to assess neural activity between cortical areas simultaneously and non-invasively has not been available.
 
 # Results
 
 ## Ongoing activity in developing neocortex is characterized by discrete domains
 
-We performed transcranial optical recordings from mice expressing the genetic calcium reporter GCaMP (GCaMP3 or GCaMP6) throughout cortical neurons to assess neural population activity patterns at macroscopic scale (millimeters) and with mesoscopic spatial and temporal resolution (10s of microns and 100s of milliseconds). We performed our recordings in three age groups during the first two postnatal weeks during which the mouse brain develops to >90% of its adult weight [#Kobayashi:1963]: P2-P5, P8-P9, and P12-13. 
+We performed transcranial optical recordings from mice expressing the genetic calcium reporter GCaMP (GCaMP3 or GCaMP6) throughout cortical neurons to assess neural population activity patterns at macroscopic scale (millimeters) and with mesoscopic spatial and temporal resolution (10s of microns and 100s of milliseconds). We performed our recordings in three age groups throughout the first two postnatal weeks during which the mouse brain attains >90% of its adult weight [#Kobayashi:1963]: P2-P5, P8-P9, and P12-13. 
 
-Functional mesoscale optical imaging (fMOI) revealed that supracellular cortical activity patterns were characterized by discrete domains of activation (Fig. 1a-c) [Supplementary Movie 1](../wholeBrain_blob/ackmanWholeBrainGcampP3.mov). These activity domains ranged from 250 - 976 µm in diameter and 0.4 - 2.6 s in duration <!--(10-90th percentiles)-->(Fig. 1e-h) (Table 1). The duration of cortical domain activations was not significantly affected by age (F = 0.933, p = 0.428, r^2 = 0.00567) or by hemisphere (F = 0.017, p = 0.900) (P2-5, N = 15653; P8-9, N = 70189; P12-13, N = 120214 domains) (Fig. 1e,f). There was a significant effect of age on the diameter of cortical domain activations (F = 25.788, p = 0.000188, r^2 = 0.1277), but not hemisphere (F = 0.192, p = 0.671808) (Fig. 1g,h). The frequency with which cortical domain activations occurred increased with age (F = 29.562, p = 8.86e-12, r^2 = 0.2535) and did not differ significantly between the hemispheres (F = 0.012, p = 0.911) (P2-5, N = 22; P8-9, N = 30; P12-13, N = 38 movies/hemi) (Fig. i,j) (Table 1).
+Functional mesoscale optical imaging (fMOI) revealed that supracellular cortical activity patterns were characterized by discrete domains of activation (Fig. 1a-c) [Supplementary Movie 1](../wholeBrain_blob/supplementaryMovie-P3gcamp3.mov). These activity domains ranged from 250 - 976 µm in diameter and 0.4 - 2.6 s in duration <!--(10-90th percentiles)-->(Fig. 1e-h) (Table 1). The duration of cortical domain activations was not significantly affected by age (F = 0.933, p = 0.428, r^2 = 0.00567) or by hemisphere (F = 0.017, p = 0.900) (P2-5, N = 15653; P8-9, N = 70189; P12-13, N = 120214 domains) (Fig. 1e,f). There was a significant effect of age on the diameter of cortical domain activations (F = 25.788, p = 0.000188, r^2 = 0.1277), but not hemisphere (F = 0.192, p = 0.671808) (Fig. 1g,h). The frequency with which cortical domain activations occurred increased with age (F = 29.562, p = 8.86e-12, r^2 = 0.2535) and did not differ significantly between the hemispheres (F = 0.012, p = 0.911) (P2-5, N = 22; P8-9, N = 30; P12-13, N = 38 movies/hemi) (Fig. i,j) (Table 1) [Supplementary Movie 2](../wholeBrain_blob/supplementaryMovie-P8gcamp3.mov).
 
 
 The neocortex exhibits a characteristic modular organization across the cortical surface such that vertical arrays of cells concerned with specific sensory features are grouped together as columns in a topographic fashion [#Mountcastle:1997]. Most evidence suggests that cortical columns range from 300-600µm diameter, even between species whose brain volumes differ by a factor of 10^3 [#Mountcastle:1997]. Its intriguing that we found the size of cortical domains to be centered on this range at early ages, because this is in agreement with previous work showing that population activity in neonatal rat barrel cortex maps onto ontogenetic modules centered on each barrel column [#Yang:2012a] and barrels are an archetypical model for columnar cortical function in rodent. Indeed, we found a cortical area in primary somatosensory cortex at P2-5 where cortical domain activations group into rows and individual modules that match primary barrel cortex structure (Fig. 1c) (Supplementary Fig.). This indicates that early cortical activity in some cortical areas is matched to the size the functional cortical modules that are thought to be the fundamental processing unit of the cerebral cortex. 
@@ -45,7 +45,7 @@ The neocortex exhibits a characteristic modular organization across the cortical
 
 We examined how the spatiotemporal properties of cortical domains vary among different cortical regions by parcellating the brain into distinct anatomical boundaries using reference coordinates from a mouse line that expressed a tdtomato reporter in thalamocortical afferents at P7 (Fig. 1c,d) (Supplementary Fig.). Patterns of thalamocortical axon terminals can be used to map out areal boundaries of primary sensory cortical areas [wong riley 1979]. We aligned these parcellations to the Allen brain mouse atlas and then scaled the cortical area reference coordinates to match activity maps from each animal containing functional boundaries for barrel cortex and visual cortex where spontaneous retinal waves functionally map out developing visual areas [#Ackman:2012]  (Fig. 1c-e,g,i). 
 
-Cortical domain frequency among different regions scaled as a function of net cortical area and this association became stronger during the course of development (Fig. 2a). The most frequently active cortical regions at each age group when normalized to the amount of total amount of cortical space was the limb/trunk representations in somatosensory cortex (Fig. 1i, Supplementary Fig.). Generally, the frequency of activity was remarkably uniform across cortical areas at each age of development (Supplementary Fig) indicating a homeostatic regulation of global activity levels. The long tails in the domain duration and diameter distributions at P2-5 and P8-9 (Fig. 1f,h) were dominated by retinal wave driven cortical activity in V1 that lasted on the order of seconds to tens of seconds (Fig. 1e, Fig. 2b,c), but also by long lasting wave-like activations occurring in motor cortex (Fig. 1e, Fig. 2b,c). Indeed the cortical regions with the highest wave motion indices were V1 and M1 at P2-5, with V1 continuing to have the highest index at P8-9 and then dropping to mean motion idx level similar to other cortical regions at P12-13. The diameter of domain activation became larger among cortical regions during the second postnatal week including the S1-limb/body regions where at P13 a small subpopulation of events had mean diameters approaching that of the entire hemisphere and a higher wave motion index (Fig. 2d-f) (x% of all events, ~2/10min) [Supplementary Movie 2](../wholeBrain_blob/ackmanWholeBrainImaging-lo.mov) (Fig. 2d). These global population events synchronized activity across cortical areas and had centers of mass that were concentrated near the middle of each hemisphere in the S1-limb/body area.
+Cortical domain frequency among different regions scaled as a function of net cortical area and this association became stronger during the course of development (Fig. 2a). The most frequently active cortical regions at each age group when normalized to the amount of total amount of cortical space was the limb/trunk representations in somatosensory cortex (Fig. 1i, Supplementary Fig.). Generally, the frequency of activity was remarkably uniform across cortical areas at each age of development (Supplementary Fig) indicating a homeostatic regulation of global activity levels. The long tails in the domain duration and diameter distributions at P2-5 and P8-9 (Fig. 1f,h) were dominated by retinal wave driven cortical activity in V1 that lasted on the order of seconds to tens of seconds (Fig. 1e, Fig. 2b,c), but also by long lasting wave-like activations occurring in motor cortex (Fig. 1e, Fig. 2b,c). Indeed the cortical regions with the highest wave motion indices were V1 and M1 at P2-5, with V1 continuing to have the highest index at P8-9 and then dropping to mean motion idx level similar to other cortical regions at P12-13. The diameter of domain activation became larger among cortical regions during the second postnatal week including the S1-limb/body regions where at P13 a small subpopulation of events had mean diameters approaching that of the entire hemisphere and a higher wave motion index (Fig. 2d-f) (x% of all events, ~2/10min) [Supplementary Movie 3](../wholeBrain_blob/supplementaryMovie-P13gcamp6.mov) (Fig. 2d). These global population events synchronized activity across cortical areas and had centers of mass that were concentrated near the middle of each hemisphere in the S1-limb/body area.
 
 
 ![ **Figure 2.** Spatiotemporal characteristics of cortical domains. **a** Domain frequency as function of cortical area size. **b** Scatterplots of domain diameter and duration. **c** Time projection maps of waves in motor cortex at P3, visual cortex at P5, and occipital-parietal-frontal cortex at P13. **d** Scatterplots of wave motion index as function of domain diameter. **e** Mean wave motion index over development.](figure2.png)
@@ -77,7 +77,7 @@ To understand the patterns and how they interact we first looked at correlation
 
 ## Developing cortical activity consists of distinct subnetworks
 
-We then calculated a matrix of pearsons correlation coefficients based on the pixel active fraction timecourses for each pair of parcellations. The resulting assocaition matrix was run through a hierarchal clustering alogtithm to reveal functional modules of of activation. These functional modules typically consisted of 3 distinct subnetworks-- a frontal motor network, a posterior parietal network, a S1-body/limb network, and an auditory A1 network at P12.
+We then calculated a matrix of pearsons correlation coefficients based on the pixel active fraction timecourses for each pair of parcellations. The resulting assocaition matrix was run through a hierarchical clustering algorithm to reveal functional modules of of activation. These functional modules typically consisted of 3 distinct subnetworks-- a frontal motor network, a posterior parietal network, a S1-body/limb network, and an auditory A1 network at P12.
 
 We found many similarities but some striking differences as a function of age.
 
@@ -147,7 +147,8 @@ Anesthetized Rx-Cre:GCaMP3 or SNAP25-GCaMP6 mice between postnatal day 2 to 13 (
 * Scatterplot domain duration-diameter timeline:  140702-141423-durDiam-scatter-img.pdf
 * P3 M1 wave time projection, lomag:  140218_13-fr2564-2601-20140716-144024.tif
 * P5 V1 wave time projection, himag: 140328_10-fr2016-2153-20140710-092344.tif
-* P13 global wave time projection, lomag:  140509_07-fr1725-2004-20140717-172658.tif
+* P13 global wave time projection, lomag:  ~~140509_07-fr1725-2004-20140717-172658.tif~~
+* P13 global wave time projection, lomag:  140509_22-fr484-609-20140725-155542.tif
 * wave motion index scatter:  140702-152109-rhoDiam-scatter.png
 * Wave motion index timeline:  140702-162029-waveMotionIdx-jitterTimeline.pdf 
 -->
@@ -194,3 +195,28 @@ Anesthetized Rx-Cre:GCaMP3 or SNAP25-GCaMP6 mice between postnatal day 2 to 13 (
 * corr graph force layout: 140602-101610-P12-13_0.15.pdf
 * corr graph spatial layout: 140602-100049-P12-13_0.15.pdf
 -->
+
+
+<!-- Supplementary Movies
+
+* supplementaryMovie-P3gcamp3.mov: wholeBrain-shortAlpha-lomed.mov, (120518_07.tif) 10 s long playback, 30fps, = 300fr = 60 s real time
+* supplementaryMovie-P8gcamp3.mov: 131208_06_std_lomed-all.mov, 6 s long playback, 30fps, 6s*30fps+3fr = 184fr = 36.8 s real time
+* supplementaryMovie-P13gcamp6.mov: 140509_22_fr484-735-lo-all-trans.mov, 8 s long playback, 30fps, 8*30+11fr=. 50.2 s real time.
+ -->
+
+<!-- Supplementary Figs 
+* supplementaryFig-domain-stats.ai:
+
+* supplementaryFig-areal-stats.ai:  
+    * 140702-204319-freq_min-boxplot.pdf
+    * 140703-083800-freq_min-boxplot.pdf
+    * 140606-091326-diamnodeT-boxplot.png
+    * 140606-091332-MeanIntensitynodeT-boxplot.png
+    * 140606-091338-MaxIntensitynodeT-boxplot.png
+    * 140606-091345-Duration_snodeT-boxplot.png
+    * 140606-143236-pairwisetPvalMatrix.pdf
+
+* supplementaryFig-montage.ai:  
+    * 140509_22-fr484-735-20140729-102651-montage.png, 140509_22-fr484-735-20140729-102651-montage.tif
+
+-->