Biology subjects

de Kock, C. P. J.

Publications and source records attributed to de Kock, C. P. J..

9 recordsLinked to original sources

bioRxiv2026

A Detailed Model for Understanding the Human Neocortex

The neocortex underlies cognitive abilities that set humans apart from other species. Although Ramon y Cajal initiated its study in the 19th century, much about its fundamental properties remain poorly understood. Biologically detail modeling, has been shown to serve as a tool to understand the modeled system better. By comparing computational models for different species we can highlight functional differences between them, find their anatomical or physiological basis and thus improve our understanding of cortical function. In this study we built a detailed model of a human cortical microcircuit following an established workflow. We compared the human data and results against a previously published reconstruction of rat cortical circuitry. To parametrize the human model, we gathered new original data on human morphological reconstructions, axonal bouton densities, single cell and synaptic recordings. We combined them with data available in the literature and open-sourced databases. We also developed various strategies to overcome the missing data, such as generalizing or adapting data from rodents. The resulting model consists of seven columnar units with similar characteristics. Each column has a radius of 476 {micro}m, a height of 2622 {micro}m, a volume of 1.86 mm3, a total cell density of 24,186 cells/mm3, on the order of 35,000 cells, around 12 million connections and approximately 47 million synapses. Comparing the rat and the human model showed that the human cortex is less dense in terms of cell bodies than the rodent cortex. Human cells have more complex branching, but lower bouton densities than rodent cells. However, the number of connections between cell types is similar.

neuroscience↗

bioRxiv2022

Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling

Human cortical pyramidal neurons are large, have extensive dendritic trees, and yet have surprisingly fast input-output properties: rapid subthreshold synaptic membrane potential changes are reliably encoded in timing of action potentials (APs). Here, we tested whether biophysical properties of voltage-gated sodium (Na+) and potassium (K+) currents in human pyramidal neurons can explain their fast input-output properties. Human Na+ and K+ currents exhibited more depolarized voltage-dependence, slower inactivation and faster recovery from inactivation compared with their mouse counterparts. Computational modeling showed that despite lower Na+ channel densities in human neurons, the biophysical properties of Na+ channels resulted in higher channel availability and contributed to fast AP kinetics stability. Finally, human Na+ channel properties also resulted in a larger dynamic range for encoding of subthreshold membrane potential changes. Thus, biophysical adaptations of voltage-gated Na+ and K+ channels enable fast input-output properties of large human pyramidal neurons. One-Sentence SummaryBiophysical properties of Na+ and K+ ion channels enable human neurons to reliably encode fast inputs into output.

neuroscience↗

bioRxiv2022

Structural and functional specializations of human fast spiking neurons support fast cortical signaling

Fast spiking interneurons (FSINs) provide fast inhibition that synchronizes neuronal activity and is critical for cognitive function. Fast synchronization frequencies are evolutionary conserved in the expanded human neocortex, despite larger neuron-to-neuron distances that challenge fast input-output transfer functions of FSINs. Here, we test in human neurons from neurosurgery tissue which mechanistic specializations of human FSINs explain their fast-signaling properties in human cortex. With morphological reconstructions, multi-patch recordings, and biophysical modeling we find that despite three-fold longer dendritic path, human FSINs maintain fast inhibition between connected pyramidal neurons through several mechanisms: stronger synapse strength of excitatory inputs, larger dendrite diameter with reduced complexity, faster AP initiation, and faster and larger inhibitory output, while Na+ current activation/inactivation properties are similar. These adaptations underlie short input-output delays in fast inhibition of human pyramidal neurons through FSINs, explaining how cortical synchronization frequencies are conserved despite expanded and sparse network topology of human cortex. Teaser/one-sentence summarySpecializations of fast spiking human neurons ensure fast signaling in human cortex.

neuroscience↗

bioRxiv2021

Task complexity temporally extends the causal requirement for visual cortex in perception

The transformation of sensory inputs into behavioral outputs is characterized by an interplay between feedforward and feedback operations in cortical hierarchies. Even in simple sensorimotor transformations, recurrent processing is often expressed in primary cortices in a late phase of the cortical response to sensory stimuli. This late phase is engaged by attention and stimulus complexity, and also encodes sensory-independent factors, including movement and report-related variables. However, despite its pervasiveness, the nature and function of late activity in perceptual decision-making remain unclear. We tested whether the function of late activity depends on the complexity of a sensory change-detection task. Complexity was based on increasing processing requirements for the same sensory stimuli. We found that the temporal window in which V1 is necessary for perceptual decision-making was extended when we increased task complexity, independently of the presented visual stimulus. This window overlapped with the emergence of report-related activity and decreased noise correlations in V1. The onset of these co-occurring activity patterns was time-locked to and preceded reaction time, and predicted the reduction in behavioral performance obtained by optogenetically silencing late V1 activity (>200 ms after stimulus onset), a result confirmed by a second multisensory task with different requirements. Thus, although early visual response components encode all sensory information necessary to solve the task, V1 is not simply relaying information to higher-order areas transforming it into behavioral responses. Rather, task complexity determines the temporal extension of a loop of recurrent activity, which overlaps with report-related activity and determines how perceptual decisions are built.

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↗

bioRxiv2020

A Theory for the Emergence of Neocortical Network Architecture

It has become increasingly clear that the neurons in the cerebral cortex are not randomly interconnected. This wiring specificity can result from synapse formation mechanisms that interconnect neurons depending on their activity or genetically defined identity. Here we report that in addition to these synapse formation mechanisms, the structural composition of the neuropil provides a third prominent source by which wiring specificity emerges in cortical networks. This structurally determined wiring specificity reflects the packing density, morphological diversity and similarity of the dendritic and axonal processes. The higher these three factors are, the more recurrent the topology of the networks. Conversely, low density, diversity and similarity yield feedforward networks. These principles predict connectivity patterns from subcellular to network scales that are remarkably consistent with empirical observations from a rich body of literature. Thus, cortical network architectures reflect the specific morphological properties of their constituents to much larger degrees than previously thought.

neuroscience↗

bioRxiv2019

Thalamus drives two complementary input strata of the neocortex in parallel

Sensory information enters the neocortex via thalamocortical axons that define the major input layer 4. The same thalamocortical axons, however, additionally innervate the deep output layers 5/6. How such bistratification impacts cortical processing remains unknown. Here, we find a class of neurons that cluster specifically around thalamocortical axons at the layer 5/6 border. We show that these border stratum cells are characterized by extensive horizontal axons, that they receive strong convergent input from the thalamus, and that this input is sufficient to drive reliable sensory-evoked responses, which precede those in layer 4. These cells are hence strategically placed to amplify and relay thalamocortical inputs across the cortical area, for example to drive the fast onsets of cortical output patterns. Layer 4 is therefore not the sole starting point of cortical processing. Instead, parallel activation of layer 4 and the border stratum is necessary to broadcast information out of the neocortex.

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↗