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@@ -12,17 +12,17 @@ James B. Ackman¹, Hongkui Zeng², and Michael C. Crair¹
# Summary # 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 isocortex. 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 cortex, retrosplenial cortex, and posterior parietal cortex. Furthermore, ongoing cortical activity was regulated by physiological state with frontal cortex activity shifting from negative to positive correlations with motor behavior during the course of development. This study provides the first comprehensive description of population activity in the developing isocortex 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 engineering future repair strategies and brain-machine interfaces for neurodevelopmental disorders. 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.
# Introduction # Introduction
Brain development requires neural activity and calcium dynamics for establishing proper circuit structure and function. The importance of neural activity in the prenatal and postnatal period can be easily recognized in children exposed to chemical agents affecting neurotransmission during the fetal period 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 [Schoenberg:2003] [Marder,Lichtmann]. 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 [Yang:2009][Khazipov:2004a] before the start of locomotion and tactile behavior. Correlated bursts of activity occur in the developing rat hippocampus in vivo [#Leinekugel:2002] [Mohns&Blumberg]. Spontaneous retinal waves drive patterned activation of circuits throughout the immature visual system before the onset of vision [#Ackman:2012] [Hanganu,Colonnese?]. 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 isocortex in vivo has not been undertaken, largely because a method to assess neural activity between most cortical areas simultaneously and non-invasively has not been available. Brain development requires neural activity and calcium dynamics for establishing proper circuit structure and function. The importance of neural activity in the prenatal and postnatal period can be easily recognized in children exposed to chemical agents affecting neurotransmission during the fetal period 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 [Schoenberg:2003] [Marder,Lichtmann]. 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 [Yang:2009][Khazipov:2004a] before the start of locomotion and tactile behavior. Correlated bursts of activity occur in the developing rat hippocampus in vivo [#Leinekugel:2002] [Mohns&Blumberg]. Spontaneous retinal waves drive patterned activation of circuits throughout the immature visual system before the onset of vision [#Ackman:2012] [Hanganu,Colonnese?]. 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 most cortical areas simultaneously and non-invasively has not been available.
# Results # Results
## Ongoing activity in developing neocortex is characterized by discrete domains ## 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 with mesoscopic spatial and temporal resolutions (10s of microns and 100s of milliseconds) at macroscopic scale (millimeters). 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. 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 147 - 735 µm in diameter <!--(median ± 2MAD)--> (Table 1.) (*Ns*, *fig*) and , with larger sized domains of activation in the visual cortex and motor cortex (*Ns*, *fig*). In the second postnatal week the size of cortical activity domains became larger in the frontal-motor and S1-limb/body regions [Supplementary Movie 2](../wholeBrain_blob/ackmanWholeBrainImaging-lo.mov). 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 with mesoscopic spatial and temporal resolutions (10s of microns and 100s of milliseconds) at macroscopic scale (millimeters). 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. 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)-->(Table 1.) (*Ns*, Fig. 1e-h).
The duration of 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). The duration of 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).
@@ -33,10 +33,13 @@ Cortical calcium domain frequency significantly increased with age (F = 29.562,
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 to date suggests that cortical columns range from 300-600µm diameter, even between species whose brain volumes differ by a factor of 10^3 [#Mountcastle:1997]. 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 to date suggests that cortical columns range from 300-600µm diameter, even between species whose brain volumes differ by a factor of 10^3 [#Mountcastle:1997].
We parcellated the brain into distinct anatomical boundaries by using reference coordinates from a mouse line that expressed the tdtomato reporter in thalamocortical afferents (Fig. 1c,d). Patterns of thalamocortical axon terminal can be used to parcellate out areal boundaries of primary sensory cortical areas [wong riley 1979]. We matched these parcellations to a Allen brain atlas adult mouse reference image and than linearly scaled the remaining parcellations in our FOV on to the images of our recordings that contain functional boundaries (like in the domain centroid activation plot and in the domain frequency maps). We parcellated the brain into distinct anatomical boundaries by using reference coordinates from a mouse line that expressed the tdtomato reporter in thalamocortical afferents (Fig. 1c,d). Patterns of thalamocortical axon terminal can be used to parcellate out areal boundaries of primary sensory cortical areas [wong riley 1979]. We matched these parcellations to a Allen brain atlas adult mouse reference image and than linearly scaled the remaining parcellations in our FOV on to the images of our recordings that contain functional boundaries (like in the domain centroid activation plot and in the domain frequency maps).
Longer duration domains of activation occurred in the visual cortex and motor cortex (*Ns*, Fig. 2b,c). In the second postnatal week the size of cortical activity domains became larger in the frontal-motor and S1-limb/body regions [Supplementary Movie 2](../wholeBrain_blob/ackmanWholeBrainImaging-lo.mov).
There were longer activations on the order of seconds to tens of seconds in visual cortex driven by retinal waves [#Ackman:2012]. Long lasting wave-like activations also occured in motor cortex P2-5 (Fig 2 montage). There were longer activations on the order of seconds to tens of seconds in visual cortex driven by retinal waves [#Ackman:2012]. Long lasting wave-like activations also occured in motor cortex P2-5 (Fig 2 montage).
![ **Figure 1.** Calcium domains throughout neonatal mouse isocortex. **a** Experimental schematic. **b** Single image frame showing calcium domains in both hemispheres at postnatal day 3 (P3) and automatically detected domain masks. **c** Centroid positions for segmented domain masks from a 10 min recording. Points are overlaid on a reference map of primary sensory areas determined by thalamocortical inputs (red outlines). Notice rows of whisker barrels are evident in the structure of domain centroid positions. **d** Functional activity map at P3. Based on pixel activation frequency from all detected domains in a single 10 min recording. Map is overlaid on cortical areal parcellations. Notice localized maxima and minima of functional activity between areas that approximate known anatomical cortical area boundaries and the mirroring of map structure bilaterally. **e** Mean domain duration maps from 3 SNAP25-Ai103 mice. **f** Histograms showing domain durations distributions in the P2-5, P8-9, and P12-13 age groups and by cortical hemisphere (L, R). **g** Mean domain diameter maps from same 3 mice in e. **h** Histograms showing the distributions of domain diameters. **i** Mean domain frequency maps from same 3 mice in e. **j** Boxplot distributions of hemispheric domain frequencies.](figure1.png) ![ **Figure 1.** Calcium domains throughout neonatal mouse neocortex. **a** Experimental schematic. **b** Single image frame showing calcium domains in both hemispheres at postnatal day 3 (P3) and automatically detected domain masks. **c** Centroid positions for segmented domain masks from a 10 min recording. Points are overlaid on a reference map of primary sensory areas determined by thalamocortical inputs (red outlines). Notice rows of whisker barrels are evident in the structure of domain centroid positions. **d** Functional activity map at P3. Based on pixel activation frequency from all detected domains in a single 10 min recording. Map is overlaid on cortical areal parcellations. Notice localized maxima and minima of functional activity between areas that approximate known anatomical cortical area boundaries and the mirroring of map structure bilaterally. **e** Mean domain duration maps from 3 SNAP25-Ai103 mice. **f** Histograms showing domain durations distributions in the P2-5, P8-9, and P12-13 age groups and by cortical hemisphere (L, R). **g** Mean domain diameter maps from same 3 mice in e. **h** Histograms showing the distributions of domain diameters. **i** Mean domain frequency maps from same 3 mice in e. **j** Boxplot distributions of hemispheric domain frequencies.](figure1.png)
| | duration (s) | diameter (µm) | frequency (hemisphere-min^-1) | | | duration (s) | diameter (µm) | frequency (hemisphere-min^-1) |
| ------ | ------------ | ----------------- | ----------------------------- | | ------ | ------------ | ----------------- | ----------------------------- |
@@ -50,6 +53,8 @@ There were longer activations on the order of seconds to tens of seconds in visu
![ **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 color maps of waves in visual cortex and motor cortex at P5. **d** Time projection color maps of interareal activations at P13. **e** Scatterplots of wave motion index as function of domain diameter. **f** Mean wave motion index over development.](figure2.png)
@@ -65,16 +70,6 @@ Variation in the strength of correlation between cortical areas and the motor mo
![ **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** Cortical activity (active fraction) in each hemisphere after onset of gas anesthetic. **c** Cortical activity and coincident motor activity signals. Gray shading indicates active and quiet motor periods determined by the half-rise and decay times from peak in the low pass filtered motor signal. Active pixel fraction traces for motor (M1,M2), somatosensory (HL,FL,T; barrel), and visual (V1,V2) cortex shown at bottom of panel. Red links show synchronized motor movements and brain activity with different cortical regions. **d** Single frame domain masks for times indicated in **c**. **e** Pixel activation frequency maps during quiet and active motor periods. **f** Cross-correlation functions between cortical regions and motor movement signals. Notice the general negative correlation between motor activity and all cortex activity signals (r = , p = ) and the high positive correlation between motor and S1-limb/body signals (r = 0.3019, p < 2.2e-16).](figure3.png) ![ **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** Cortical activity (active fraction) in each hemisphere after onset of gas anesthetic. **c** Cortical activity and coincident motor activity signals. Gray shading indicates active and quiet motor periods determined by the half-rise and decay times from peak in the low pass filtered motor signal. Active pixel fraction traces for motor (M1,M2), somatosensory (HL,FL,T; barrel), and visual (V1,V2) cortex shown at bottom of panel. Red links show synchronized motor movements and brain activity with different cortical regions. **d** Single frame domain masks for times indicated in **c**. **e** Pixel activation frequency maps during quiet and active motor periods. **f** Cross-correlation functions between cortical regions and motor movement signals. Notice the general negative correlation between motor activity and all cortex activity signals (r = , p = ) and the high positive correlation between motor and S1-limb/body signals (r = 0.3019, p < 2.2e-16).](figure3.png)
Low pass filtered Moving averages of cortical and motor activity at 10 s and >70 s windows.
Percentage of cortical activity which exhibits corr with motor signal:
lenActvFraction>0 | fracCorr | timeCorr_s | fracCorrPos | timeCorrPos_s | fracCorrNeg | timeCorrNeg_s
--- | --- | --- | --- | --- | --- | ---
2161 | 0.30032 | 129.8 | 0.27441 | 118.6 | 0.025914 | 11.2
## Cortical activity is mirrored between the hemispheres ## Cortical activity is mirrored between the hemispheres
@@ -90,17 +85,6 @@ To understand the patterns and how they interact we first looked at correlation
**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.
## Developing cortical activity consists of distinct subnetworks ## 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 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.
@@ -108,7 +92,7 @@ We then calculated a matrix of pearsons correlation coefficients based on the pi
We found many similarities but some striking differences as a function of age. We found many similarities but some striking differences as a function of age.
![ **Figure 5.** Subnetworks in developing isocortex. **a** Correlation matrix of domain activity among cortical areas. Colormap indicates Pearson's r correlation coefficient values. **b** Graph of functional connections for r > 0.15. Community structure detected with hierarchical clustering are indicated in 4 colors. Notice that S1-limb/body regions form a distinct subgraph (red). **c** Map of cortical area associations for r > 0.1.](figure5.png) ![ **Figure 5.** Subnetworks in developing neocortex. **a** Correlation matrix of domain activity among cortical areas. Colormap indicates Pearson's r correlation coefficient values. **b** Graph of functional connections for r > 0.15. Community structure detected with hierarchical clustering are indicated in 4 colors. Notice that S1-limb/body regions form a distinct subgraph (red). **c** Map of cortical area associations for r > 0.1.](figure5.png)