Distinctive biophysical features of human cell-types: insights from studies of neurosurgically resected brain tissue.

Electrophysiological characterization of live human tissue from epilepsy patients has been performed for many decades. Although initially these studies sought to understand the biophysical and synaptic changes associated with human epilepsy, recently, it has become the mainstay for exploring the distinctive biophysical and synaptic features of human cell-types. Both epochs of these human cellular electrophysiological explorations have faced criticism. Early studies revealed that cortical pyramidal neurons obtained from individuals with epilepsy appeared to function "normally" in comparison to neurons from non-epilepsy controls or neurons from other species and thus there was little to gain from the study of human neurons from epilepsy patients. On the other hand, contemporary studies are often questioned for the "normalcy" of the recorded neurons since they are derived from epilepsy patients. In this review, we discuss our current understanding of the distinct biophysical features of human cortical neurons and glia obtained from tissue removed from patients with epilepsy and tumors. We then explore the concept of within cell-type diversity and its loss (i.e., "neural homogenization"). We introduce neural homogenization to help reconcile the epileptogenicity of seemingly "normal" human cortical cells and circuits. We propose that there should be continued efforts to study cortical tissue from epilepsy patients in the quest to understand what makes human cell-types "human".

Investigating microglia-neuron crosstalk by characterizing microglial contamination in human and mouse patch-seq datasets.

Microglia are cells with diverse roles, including the regulation of neuronal excitability. We leveraged Patch-seq to assess the presence and effects of microglia in the local microenvironment of recorded neurons. We first quantified the amounts of microglial transcripts in three Patch-seq datasets of human and mouse neocortical neurons, observing extensive contamination. Variation in microglial contamination was explained foremost by donor identity, particularly in human samples, and additionally by neuronal cell type identity in mice. Gene set enrichment analysis suggests that microglial contamination is reflective of activated microglia, and that these transcriptional signatures are distinct from those captured via single-nucleus RNA-seq. Finally, neurons with greater microglial contamination differed markedly in their electrophysiological characteristics, including lowered input resistances and more depolarized action potential thresholds. Our results generalize beyond Patch-seq to suggest that activated microglia may be widely present across brain slice preparations and contribute to neuron- and donor-related electrophysiological variability in vitro.

Robust differences in cortical cell type proportions across healthy human aging inferred through cross-dataset transcriptome analyses.

Age-related declines in cognitive function are driven by cell type-specific changes in the brain. However, it remains challenging to study cellular differences associated with healthy aging as traditional approaches scale poorly to the sample sizes needed to capture aging and cellular heterogeneity. Here, we employed cellular deconvolution to estimate relative cell type proportions using frontal cortex bulk gene expression from individuals without psychiatric conditions or brain pathologies. Our analyses comprised 8 datasets and 6 cohorts (1142 subjects and 1429 samples) with ages of death spanning 15-90 years. We found aging associated with profound differences in cellular proportions, with the largest changes reflecting fewer somatostatin- and vasoactive intestinal peptide-expressing interneurons, more astrocytes and other non-neuronal cells, and a suggestive "U-shaped" quadratic relationship for microglia. Cell type associations with age were markedly robust across bulk-and single nucleus datasets. Altogether, we present a comprehensive account of proportional differences in cortical cell types associated with healthy aging.

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.

Experience-Dependent Changes in Myelin Basic Protein Expression in Adult Visual and Somatosensory Cortex.

An experience-driven increase in oligodendrocytes and myelin in the somatosensory cortex (S1) has emerged as a new marker of adult cortical plasticity. That finding contrasts with the view that myelin is a structural brake on plasticity, and that contributes to ending the critical period (CP) in the visual cortex (V1). Despite the evidence that myelin-derived signaling acts to end CP in V1, there is no information about myelin changes during adult plasticity in V1. To address this, we quantified the effect of three manipulations that drive adult plasticity (monocular deprivation (MD), fluoxetine treatment or the combination of MD and fluoxetine) on the expression of myelin basic protein (MBP) in adult rat V1. In tandem, we validated that environmental enrichment (EE) increased cortical myelin by measuring MBP in adult S1. For comparison with the MBP measurements, three plasticity markers were also quantified, the spine markers drebrin E and drebrin A, and a plasticity maintenance marker Ube3A. First, we confirmed that EE increased MBP in S1. Next, that expression of the plasticity markers was affected in S1 by EE and in V1 by the visual manipulations. Finally, we found that after adult MD, MBP increased in the non-deprived V1 hemisphere, but it decreased in the deprived hemisphere, and those changes were not influenced by fluoxetine. Together, the findings suggest that modulation of myelin expression in adult V1 may reflect the levels of visually driven activity rather than synaptic plasticity caused by adult plasticity.

Observing painful events in others leads to a temporally extended general response facilitation in the self.

Excitability in the motor cortex is modulated when we observe other people receiving a painful stimulus (Avenanti et al., Nat Neurosci 8(7):955-960, 2005). However, the task dependency of this modulation is not well understood, as different paradigms have yielded seemingly different results. Previous neurophysiological work employing transcranial magnetic stimulation (TMS) suggests that watching another person's hand being pierced by a needle leads to a muscle specific inhibition, assessed via motor evoked potentials. Results from previous behavioural studies suggest that overt behavioural responses are facilitated due to pain observation (Morrison et al., Cereb Cortex 17:2214-2222, 2007b; Morrison et al., Cognition 104:407-416, 2007a). There are several paradigmatic differences both between typical TMS studies and behavioural studies, and within behavioural studies themselves, that limit our overall understanding of how pain observation affects the motor system. In the current study, we combine elements of typical TMS experimental designs in a behavioural assessment of how pain observation affects overt behavioural responding. Specifically, we examined the muscle specificity, timing, and direction of modulation of motor responses due to pain observation. To assess muscle specificity, we employed pain and non-pain videos from previous TMS studies in a Go/No-Go task in which participants responded by either pressing a key with their index finger or with their foot. To assess timing, we examined response times for Go signals presented at 0 or 500 ms after the video. Results indicate that observation of another individual receiving a painful stimulus leads to a non-effector specific, temporally extended response facilitation (e.g., finger and foot facilitation present at 0 and 500 ms delays), compared to observation of non-pain videos. This behavioural facilitation effect differs from the typical motor inhibition seen in TMS studies, and we argue that the effects of pain observation on the motor system are state-dependent, with different states induced via task instructions. We discuss our results in light of previous work on motor responses to pain observation.