Biology subjects

Verhoog, M. B.

Publications and source records attributed to Verhoog, M. B..

7 recordsLinked to original sources

bioRxiv2025

Human neurons undergo protracted functional maturation into adulthood

Summary ParagraphHuman cognitive development is uniquely prolonged1-3, reflecting the extended postnatal maturation of the cerebral cortex where cell-type differentiation4,5, synaptogenesis6,7, myelination8 and transcriptional regulation5,9,10 all follow protracted developmental timelines. However, when human cortical neurons reach functional electrophysiological maturity and how their developmental trajectory compares to other species remains unknown. Here we show through patch-clamp recordings of human temporal cortex from infancy to adulthood that supragranular pyramidal neurons exhibit pronounced neoteny of their functional properties, with physiological maturation continuing well into adulthood. Comparing human and mouse developmental trajectories reveals human neurons are on a much slower developmental timeline, maturing physiologically hundreds of times slower than mouse and 2-6 times slower than would be predicted from anatomical brain growth differences between species. This reflects a fundamentally different allometric relationship between physiological and anatomical maturation; while mouse neuronal physiology closely tracks brain growth, human physiological development follows its own extended timeline. This slow maturation results in different stages of cognitive development being supported by functionally distinct neuronal populations, with the progression from infancy to middle age characterized by specific electrophysiological profiles. Notably, a neuronal subtype thought to be human-specific, with electrophysiological traits that enhance computational capacity, appears only in late adolescence or early adulthood. This extreme protraction of neurophysiological development provides a cellular basis for prolonged human cognitive maturation, demonstrating that neuronal physiological neoteny represents a fundamental evolutionary adaptation in human brain development.

neuroscience↗

bioRxiv2024

Comprehensive Analysis of Human Dendritic Spine Morphology and Density: Exploring Diversity of Human Dendritic Spines

Dendritic spines, small protrusions on neuronal dendrites, play a crucial role in brain function by changing shape and size in response to neural activity. So far, in depth analysis of dendritic spines in human brain tissue is lacking. This study presents a comprehensive analysis of human dendritic spine morphology and density using a unique dataset from human brain tissue from 27 patients (8 females, 19 males, aged 18-71) undergoing tumor or epilepsy surgery at three neurosurgery sites. We used acute slices and organotypic brain slice cultures to examine dendritic spines, classifying them into the three main morphological subtypes: Mushroom, Thin, and Stubby, via 3D reconstruction using ZEISS arivis Pro software. A deep learning model, trained on 39 diverse datasets, automated spine segmentation and 3D reconstruction, achieving a 74% F1-score and reducing processing time by over 50%. We show significant differences in spine density by sex, dendrite type, and tissue condition. Females had higher spine densities than males, and apical dendrites were denser in spines than basal ones. Acute tissue showed higher spine densities compared to cultured human brain tissue. With time in culture, Mushroom spines decreased, while Stubby and Thin spine percentages increased, particularly from 7-9 to 14 days in vitro, reflecting potential synaptic plasticity changes. Our study underscores the importance of using human brain tissue to understand unique synaptic properties and shows that integrating deep learning with traditional methods enables efficient large-scale analysis, revealing key insights into sex- and tissue-specific dendritic spine dynamics relevant to neurological diseases. New and NoteworthyThis study presents a dataset of nearly 4,000 morphologically reconstructed human dendritic spines across different ages, gender, and tissue conditions. The dataset was further used to evaluate a deep learning algorithm for three-dimensional spine reconstruction, offering a scalable method for semi-automated spine analysis across various tissues and microscopy setups. The findings enhance understanding of human neurology, indicating potential connections between spine morphology, brain function, and the mechanisms of neurological and psychiatric diseases.

neuroscience↗

bioRxiv2023

Cell type-specific gene expression dynamics during human brain maturation

The human brain undergoes protracted post-natal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell type-specific gene expression dynamics. Here, using single nucleus (sn)RNA-seq on temporal lobe tissue, including samples of African ancestry, we build a joint paediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between paediatric and adult cell types, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in paediatric tissue. The new resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.

neuroscience↗

bioRxiv2021

Expansion of cortical layers 2 and 3 in human left temporal cortex associates with verbal intelligence

The expansion of supragranular cortical layers is thought to have enabled evolutionary development of human cognition and language. However, whether increased volume of supragranular cortical layers can actually support greater cognitive and language abilities in humans has not been demonstrated. Here, we find that subjects with higher general and verbal intelligence test (VIQ) scores have selectively expanded layers 2 and 3 only in the left temporal cortex, an area associated with language and IQ-test performance. This expansion is accompanied by lower neuron densities and larger cell-body size. Furthermore, individuals with higher VIQ scores had neurons with larger dendritic trees in left temporal cortex, potentially impacting their function. Indeed, neurons of subjects with higher VIQ scores had faster action potential upstroke kinetics, which improves information processing. These data show that expansion of supragranular layer volume, cortical and cellular micro-architecture and function are associated with improved verbal mental ability in human subjects.

neuroscience↗

bioRxiv2021

Neuronal morphology and physiology, functional brain networks and memory in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of therapy-resistant TLE patients, who underwent fMRI, MEG and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.

neuroscience↗

bioRxiv2018

A cellular basis of human intelligence

It is generally assumed that human intelligence relies on efficient processing by neurons in our brain. Behavioral and brain-imaging studies robustly show that higher intelligence associates with faster reaction times and thicker gray matter in temporal and frontal cortical areas. However, no direct evidence exists that links individual neuron activity and structure to human intelligence. Since a large part of cortical grey matter consists of dendrites, these structures likely determine cortical architecture. In addition, dendrites strongly affect functional properties of neurons, including action potential speed. Thereby, dendritic size and action potential firing may constitute variation in cortical thickness, processing speed, and ultimately IQ.\n\nTo investigate this, we took advantage of brain tissue available from neurosurgery and recorded from pyramidal neurons in the medial temporal cortex, an area showing high association between cortical thickness, cortical activity and intelligence. Next, we reconstructed full dendritic structures of recorded neurons and combined these with brain-imaging data and IQ scores from the same subjects. We find that high IQ scores and large temporal cortical thickness associate with larger, more complex dendrites of human pyramidal neurons. We show in silico that larger dendrites enable pyramidal neurons to track activity of synaptic inputs with higher temporal precision, due to fast action potential initiation. Finally, we find that human pyramidal neurons of individuals with higher IQ scores sustain faster action potentials during repeated firing. These findings provide first evidence that human intelligence is associated with neuronal complexity, action potential speed and efficient information transfer in cortical neurons.

neuroscience↗

bioRxiv2018

Human cortical pyramidal neurons: From spines to spikes via models

We present the first-ever detailed models of pyramidal cells from human neocortex, including models on their excitatory synapses, dendritic spines, dendritic NMDA- and somatic/axonal- Na+ spikes that provided new insights into signal processing and computational capabilities of these principal cells. Six human layer 2 and layer 3 pyramidal cells (HL2/L3 PCs) were modeled, integrating detailed anatomical and physiological data from both fresh and post mortem tissues from human temporal cortex. The models predicted particularly large AMPA- and NMDA- conductances per synaptic contact (0.88 nS and 1.31nS, respectively) and a steep dependence of the NMDA-conductance on voltage. These estimates were based on intracellular recordings from synaptically-connected HL2/L3 pairs, combined with extra-cellular current injections and use of synaptic blockers. A large dataset of high-resolution reconstructed HL2/L3 dendritic spines provided estimates for the EPSPs at the spine head (12.7 {+/-} 4.6 mV), spine base (9.7 {+/-} 5.0 mV) and soma (0.3 {+/-} 0.1 mV), and for the spine neck resistance (50 - 80 M{Omega}). Matching the shape and firing pattern of experimental somatic Na+-spikes provided estimates for the density of the somatic/axonal excitable membrane ion channels, predicting that 134 {+/-} 28 simultaneously activated HL2/L3- HL2/L3 synapses are required for generating (with 50% probability) a somatic Na+ spike. Dendritic NMDA spikes were triggered in the model when 20 {+/-} 10 excitatory spinous synapses were simultaneously activated on individual dendritic branches. The particularly large number of basal dendrites in HL2/L3 PCs and the distinctive cable elongation of their terminals imply that ~25 NMDA- spikes could be generated independently and simultaneously in these cells, as compared to ~14 in L2/3 PCs from the rat temporal cortex. These multi-sites nonlinear signals, together with the large (~30,000) excitatory synapses/cell, equip human L2/L3 PCs with enhanced computational capabilities. Our study provides the most comprehensive model of any human neuron to-date demonstrating the biophysical and computational distinctiveness of human cortical neurons.

neuroscience↗