James B. Ackman

Demixing signals in transcranial videos of neuronal calcium flux across the cerebral hemispheres is a key step before mapping features of cortical organization. Here we demonstrate that independent component analysis can optimally recover neural signal content in widefield recordings of neuronal cortical calcium dynamics captured at a minimum sampling rate of 1.5×10⁶ pixels per one-hundred millisecond frame for seventeen minutes with a magnification ratio of 1:1. We show that a set of spatial and temporal metrics obtained from the components can be used to build a random forest classifier, which separates neural activity and artifact components automatically at human performance. Using this data, we establish functional segmentation of the mouse cortex to provide a map of ~115 domains per hemisphere, in which extracted time courses maximally represent the underlying signal in each recording. Domain maps revealed substantial regional motifs, with higher order cortical regions presenting large, eccentric domains compared with smaller, more circular ones in primary sensory areas. This workflow of data-driven video decomposition and machine classification of signal sources can greatly enhance high quality mapping of complex cerebral dynamics.

Functional imaging of neural cell populations is critical for mapping intra− and inter−regional network dynamics across the neocortex. Recently we showed that an unsupervised machine learning decomposition of densely sampled recordings of cortical calcium dynamics results in a collection of components comprised of neuronal signal sources distinct from optical, movement, and vascular artifacts. Here we build a supervised learning classifier that automatically separates neural activity and artifact components, using a set of extracted spatial and temporal metrics that characterize the respective components. We demonstrate that the performance of the machine classifier matches human identification of signal components in novel data sets. Further, we analyze control data recorded in glial cell reporter and non−fluorescent mouse lines that validates human and machine identification of functional component class. This combined workflow of data−driven video decomposition and machine classification of signal sources will aid robust and scalable mapping of complex cerebral dynamics.

Recording neuronal group activity across the cortical hemispheres from awake, behaving mice is essential for understanding information flow across cerebral networks. Video recordings of cerebral function comes with challenges, including optical and movement-associated vessel artifacts, and limited references for time series extraction. Here we present a data-driven workflow that isolates artifacts from calcium activity patterns, and segments independent functional units across the cortical surface. Independent Component Analysis utilizes the statistical interdependence of pixel activation to completely unmix signals from background noise, given sufficient spatial and temporal samples. We also utilize isolated signal components to produce segmentations of the cortical surface, unique to each individual’s functional patterning. Time series extraction from these maps maximally represent the underlying signal in a highly compressed format. These improved techniques for data pre-processing, spatial segmentation, and time series extraction result in optimal signals for further analysis.

C57BL/6 mice exhibit spontaneous cerebellar malformations consisting of heterotopic neurons and glia in the molecular layer of the posterior vermis, indicative of neuronal migration defect during cerebellar development. Recognizing that many genetically engineered (GE) mouse lines are produced from C57BL/6 ES cells or backcrossed to this strain, we performed histological analyses and found that cerebellar heterotopia were a common feature present in the majority of GE lines on this background. Furthermore, we identify GE mouse lines that will be valuable in the study of cerebellar malformations including diverse driver, reporter, and optogenetic lines. Finally, we discuss the implications that these data have on the use of C57BL/6 mice and GE mice on this background in studies of cerebellar development or as models of disease.

Cortical columns are basic cellular and functional units of the cerebral cortex that are malformed in many brain disorders, but how they initially develop is not well understood. Using an optogenetic sensor in the mouse embryonic forebrain, we demonstrate that Ca²⁺ fluxes propagate bidirectionally within the elongated fibers of radial glial cells (RGCs), providing a novel communication mechanism linking the proliferative and postmitotic zones before the onset of synaptogenesis. Our results indicate that Ca²⁺ activity along RGC fibers provides feedback information along the radial migratory pathway, influencing neurogenesis and migration during early column development. Furthermore, we find that this columnar Ca²⁺ propagation is induced by Notch and fibroblast growth factor activities classically implicated in cortical expansion and patterning. Thus, cortical morphogens and growth factors may influence cortical column assembly in part by regulating long-distance Ca²⁺ communication along the radial axis of cortical development.

The cerebral cortex exhibits spontaneous and sensory evoked patterns of activity during early development that is vital for the formation and refinement of neural circuits. Identifying the source and flow of this activity locally and globally is critical for understanding principles guiding self-organization in the developing brain. Here we use whole brain transcranial optical imaging at high spatial and temporal resolution to demonstrate that dynamical patterns of neuronal activity in developing mouse neocortex consist of spatially discrete domains that are coordinated in an age, areal, and behavior- dependent fashion. Ongoing cortical activity displays mirror-symmetric activation patterns across the cerebral hemispheres and stereotyped network architectures that are shaped during development, with parietal-sensorimotor subnetworks functionally connected to occipital regions through frontal-medial cortical areas. This study provides the first broad description of population activity in the developing neocortex at a scope and scale that bridges the microscopic and macroscopic spatiotemporal resolutions provided by traditional neurophysiological and functional neuroimaging techniques. Mesoscale maps of cortical population dynamics within animal models will be crucial for future efforts to understand and treat neurodevelopmental disorders.

The morphological and functional development of the vertebrate nervous system is initially governed by genetic factors and subsequently refined by neuronal activity. However, fundamental features of the nervous system emerge before sensory experience is possible. Thus, activity-dependent development occurring before the onset of experience must be driven by spontaneous activity, but the origin and nature of activity in vivo remains largely untested. Here we use optical methods to show in live neonatal mice that waves of spontaneous retinal activity are present and propagate throughout the entire visual system before eye opening. This patterned activity encompassed the visual field, relied on cholinergic neurotransmission, preferentially initiated in the binocular retina and exhibited spatiotemporal correlations between the two hemispheres. Retinal waves were the primary source of activity in the midbrain and primary visual cortex, but only modulated ongoing activity in secondary visual areas. Thus, spontaneous retinal activity is transmitted through the entire visual system and carries patterned information capable of guiding the activity-dependent development of complex intra- and inter-hemispheric circuits before the onset of vision.

Development of eye-specific segregation and binocularity in the superior colliculus, dorsal lateral geniculate nucleus and primary visual cortex is partly attributed to the timing of spontaneous retinal waves, in which bursts of activity are thought to act through a Hebbian learning rule to guide circuit refinement. This study uses the latest optogenetic tools to provide definitive evidence for the binocular activity timing rule—and the specific temporal features of activity—in dictating binocularity development in the mouse visual system. Binocular competition is thought to drive eye-specific segregation in the developing visual system, potentially through Hebbian synaptic learning rules that are sensitive to correlations in afferent activity. Altering retinal activity can disrupt eye-specific segregation, but little is known about the temporal features of binocular activity that modulate visual map development. We used optogenetic techniques to directly manipulate retinal activity in vivo and identified a critical period before eye opening in mice when specific binocular features of retinal activity drive visual map development. Synchronous activation of both eyes disrupted segregation, whereas asynchronous stimulation enhanced segregation. The optogenetic stimulus applied was spatially homogenous; accordingly, retinotopy of ipsilateral projections was markedly perturbed, but contralateral retinotopy was unaffected or even improved. These results provide direct evidence that the synchrony and precise temporal pattern of binocular retinal activity during a critical period in development regulates eye-specific segregation and retinotopy in the developing visual system.