An optrode array for spatiotemporally-precise large-scale optogenetic stimulation of deep cortical layers in non-human primates.

Optogenetics has transformed studies of neural circuit function, but remains challenging to apply to non-human primates (NHPs). A major challenge is delivering intense, spatiotemporally-precise, patterned photostimulation across large volumes in deep tissue. Such stimulation is critical, for example, to modulate selectively deep-layer corticocortical feedback circuits. To address this need, we have developed the Utah Optrode Array (UOA), a 10×10 glass needle waveguide array fabricated atop a novel opaque optical interposer, and bonded to an electrically addressable µLED array. In vivo experiments with the UOA demonstrated large-scale, spatiotemporally precise, activation of deep circuits in NHP cortex. Specifically, the UOA permitted both focal (confined to single layers/columns), and widespread (multiple layers/columns) optogenetic activation of deep layer neurons, as assessed with multi-channel laminar electrode arrays, simply by varying the number of activated µLEDs and/or the irradiance. Thus, the UOA represents a powerful optoelectronic device for targeted manipulation of deep-layer circuits in NHP models.

Corrigendum: A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain.

[This corrects the article DOI: 10.3389/fnins.2021.668293.].

A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain.

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables [e.g., genes or proteins (p)] for each sample. This leads to a data structure that is high dimensional (p ≫ n) and introduces the curse of dimensionality, which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets where p ≫ n. Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparse k-means clustering [robust sparse k-means clustering (RSKC)] that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain's development.

A Primer on Constructing Plasticity Phenotypes to Classify Experience-Dependent Development of the Visual Cortex.

Many neural mechanisms regulate experience-dependent plasticity in the visual cortex (V1), and new techniques for quantifying large numbers of proteins or genes are transforming how plasticity is studied into the era of big data. With those large data sets comes the challenge of extracting biologically meaningful results about visual plasticity from data-driven analytical methods designed for high-dimensional data. In other areas of neuroscience, high-information content methodologies are revealing more subtle aspects of neural development and individual variations that give rise to a richer picture of brain disorders. We have developed an approach for studying V1 plasticity that takes advantage of the known functions of many synaptic proteins for regulating visual plasticity. We use that knowledge to rebrand protein measurements into plasticity features and combine those into a plasticity phenotype. Here, we provide a primer for analyzing experience-dependent plasticity in V1 using example R code to identify high-dimensional changes in a group of proteins. We describe using PCA to classify high-dimensional plasticity features and use them to construct a plasticity phenotype. In the examples, we show how to use this analytical framework to study and compare experience-dependent development and plasticity of V1 and apply the plasticity phenotype to translational research questions. We include an R package "PlasticityPhenotypes" that aggregates the coding packages and custom code written in RStudio to construct and analyze plasticity phenotypes.

Classification of Visual Cortex Plasticity Phenotypes following Treatment for Amblyopia.

Monocular deprivation (MD) during the critical period (CP) has enduring effects on visual acuity and the functioning of the visual cortex (V1). This experience-dependent plasticity has become a model for studying the mechanisms, especially glutamatergic and GABAergic receptors, that regulate amblyopia. Less is known, however, about treatment-induced changes to those receptors and if those changes differentiate treatments that support the recovery of acuity versus persistent acuity deficits. Here, we use an animal model to explore the effects of 3 visual treatments started during the CP (n = 24, 10 male and 14 female): binocular vision (BV) that promotes good acuity versus reverse occlusion (RO) and binocular deprivation (BD) that causes persistent acuity deficits. We measured the recovery of a collection of glutamatergic and GABAergic receptor subunits in the V1 and modeled recovery of kinetics for NMDAR and GABAAR. There was a complex pattern of protein changes that prompted us to develop an unbiased data-driven approach for these high-dimensional data analyses to identify plasticity features and construct plasticity phenotypes. Cluster analysis of the plasticity phenotypes suggests that BV supports adaptive plasticity while RO and BD promote a maladaptive pattern. The RO plasticity phenotype appeared more similar to adults with a high expression of GluA2, and the BD phenotypes were dominated by GABAA α1, highlighting that multiple plasticity phenotypes can underlie persistent poor acuity. After 2-4 days of BV, the plasticity phenotypes resembled normals, but only one feature, the GluN2A:GluA2 balance, returned to normal levels. Perhaps, balancing Hebbian (GluN2A) and homeostatic (GluA2) mechanisms is necessary for the recovery of vision.

Classic and Golli Myelin Basic Protein have distinct developmental trajectories in human visual cortex.

Traditionally, myelin is viewed as insulation around axons, however, more recent studies have shown it also plays an important role in plasticity, axonal metabolism, and neuroimmune signaling. Myelin is a complex multi-protein structure composed of hundreds of proteins, with Myelin Basic Protein (MBP) being the most studied. MBP has two families: Classic-MBP that is necessary for activity driven compaction of myelin around axons, and Golli-MBP that is found in neurons, oligodendrocytes, and T-cells. Furthermore, Golli-MBP has been called a "molecular link" between the nervous and immune systems. In visual cortex specifically, myelin proteins interact with immune processes to affect experience-dependent plasticity. We studied myelin in human visual cortex using Western blotting to quantify Classic- and Golli-MBP expression in post-mortem tissue samples ranging in age from 20 days to 80 years. We found that Classic- and Golli-MBP have different patterns of change across the lifespan. Classic-MBP gradually increases to 42 years and then declines into aging. Golli-MBP has early developmental changes that are coincident with milestones in visual system sensitive period, and gradually increases into aging. There are three stages in the balance between Classic- and Golli-MBP expression, with Golli-MBP dominating early, then shifting to Classic-MBP, and back to Golli-MBP in aging. Also Golli-MBP has a wave of high inter-individual variability during childhood. These results about cortical MBP expression are timely because they compliment recent advances in MRI techniques that produce high resolution maps of cortical myelin in normal and diseased brain. In addition, the unique pattern of Golli-MBP expression across the lifespan suggests that it supports high levels of neuroimmune interaction in cortical development and in aging.

Experience-dependent central vision deficits: Neurobiology and visual acuity.

Abnormal visual experience during childhood often leads to amblyopia, with strong links to binocular dysfunction that can include poor acuity in both eyes, especially in central vision. In animal models of amblyopia, the non-deprived eye is often considered normal and what limits binocular acuity. This leaves open the question whether monocular deprivation (MD) induces binocular dysfunction similar to what is found in amblyopia. In previous studies of MD cats, we found a loss of excitatory receptors restricted to the central visual field representation in visual cortex (V1), including both eyes' columns. This led us to ask two questions about the effects of MD: how quickly are receptors lost in V1? and is there an impact on binocular acuity? We found that just a few hours of MD caused a rapid loss of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor proteins across all of V1. But after a few days of MD, there was recovery in the visual periphery, leaving a loss of AMPA receptors only in the central region of V1. We reared animals with early MD followed by a long period of binocular vision and found binocular acuity deficits that were greatest in the central visual field. Our results suggest that the greater binocular acuity deficits in the central visual field are driven in part by the long-term loss of AMPA receptors in the central region of V1.