High synaptic threshold for dendritic NMDA spike generation in human layer 2/3 pyramidal neurons

Spine loss in depression impairs dendritic signal integration in human cortical microcircuit models

Major depressive disorder (depression) is associated with altered dendritic structure and function of cortical pyramidal neurons, due to decreased inhibition from somatostatin (SST) interneurons and loss of spines and associated synapses, as indicated in postmortem human studies. Dendrites mediate signal processing through synaptic integration and nonlinear properties including backpropagating action potentials and dendritic Na+ spikes that enhance the neuron's computational power. However, it is currently unclear how depression-related dendritic changes impact signal integration. Here, we integrated human neuronal data of active dendritic properties and spine loss in depression into detailed computational models of human cortical microcircuits. We show that spine loss dampens signal response, worsening signal detection impairment than due to reduced SST interneuron inhibition alone. Furthermore, altered intrinsic properties due to spine loss abolished nonlinear dendritic signal integration and impaired recurrent microcircuit activity. Our study mechanistically links cellular changes in depression to impaired dendritic processing in human cortical microcircuits.

Contrasting patterns of extrasynaptic NMDAR-GluN2B expression in macaque subgenual cingulate and dorsolateral prefrontal cortices

Expression of the N-methyl-D-aspartate receptor, particularly when containing the GluN2B subunit (NMDAR-GluN2B), varies across the prefrontal cortex (PFC). In humans, the subgenual cingulate cortex (SGC) contains among the highest levels of NMDAR-GluN2B expression, while the dorsolateral prefrontal cortex (dlPFC) exhibits a more moderate level of NMDAR-GluN2B expression. NMDAR-GluN2B are commonly associated with ionotropic synaptic function and plasticity and are essential to the neurotransmission underlying working memory in the macaque dlPFC in the layer III circuits, which in humans are afflicted in schizophrenia. However, NMDAR-GluN2B can also be found at extrasynaptic sites, where they may trigger distinct events, including some linked to neurodegenerative processes. The SGC is an early site of tau pathology in sporadic Alzheimer's disease (sAD), which mirrors its high NMDAR-GluN2B expression. Additionally, the SGC is hyperactive in depression, which can be treated with NMDAR antagonists. Given the clinical relevance of NMDAR in the SGC and dlPFC, the current study used immunoelectron microscopy (immunoEM) to quantitatively compare the synaptic and extrasynaptic expression patterns of NMDAR-GluN2B across excitatory and inhibitory neuron dendrites in rhesus macaque layer III SGC and dlPFC. We found a larger population of extrasynaptic NMDAR-GluN2B in dendrites of putative pyramidal neurons in SGC as compared to the dlPFC, while the dlPFC had a higher proportion of synaptic NMDAR-GluN2B. In contrast, in putative inhibitory dendrites from both areas, extrasynaptic expression of NMDAR-GluN2B was far more frequently observed over synaptic expression. These findings may provide insight into varying cortical vulnerability to alterations in excitability and neurodegenerative forces.

Contrasting patterns of extrasynaptic NMDAR-GluN2B expression in macaque subgenual cingulate and dorsolateral prefrontal cortices

Expression of the N-methyl-D-aspartate receptor, particularly when containing the GluN2B subunit (NMDAR-GluN2B) varies across the prefrontal cortex (PFC). In humans, the subgenual cingulate cortex (SGC) contains among the highest levels of NMDAR-GluN2B expression, while the dorsolateral prefrontal cortex (dlPFC) exhibits a more moderate level of NMDAR-GluN2B expression. NMDAR-GluN2B are commonly associated with ionotropic synaptic function and plasticity, and are essential to the neurotransmission underlying working memory in the macaque dlPFC in the layer III circuits afflicted in schizophrenia. However, NMDAR-GluN2B can also be found at extrasynaptic sites, where they may trigger distinct events, including some linked to neurodegenerative processes. The SGC is an early site of tau pathology in sporadic Alzheimer's Disease (sAD), which mirrors its high NMDAR-GluN2B expression. Additionally, the SGC is hyperactive in depression, which is treated with NMDAR antagonists. Given the clinical relevance of NMDAR in the SGC and dlPFC, the current study used immunoelectron microscopy (immunoEM) to quantitatively compare the synaptic and extrasynaptic expression patterns of NMDAR-GluN2B across excitatory and inhibitory neuron dendrites in the rhesus macaque SGC and dlPFC. We found a larger population of extrasynaptic NMDAR-GluN2B in dendritic shafts and spines of putative pyramidal neurons in SGC as compared to the dlPFC, while the dlPFC had a higher proportion of synaptic NMDAR-GluN2B. In contrast, in putative inhibitory dendrites from both areas, extrasynaptic expression of NMDAR-GluN2B was far more frequently observed over synaptic expression. These findings may provide insight into varying cortical vulnerability to alterations in excitability and to neurodegenerative forces.

Scope Statement

NMDAR are ionotropic receptors that contribute to neurotransmission and second messenger signaling events. NMDAR can induce a diverse array of neuronal events, in part due to variation in subunit composition and subcellular localization of receptor expression. Expression of the GluN2B subunit varies across the prefrontal cortex in humans. This subunit is highly expressed in the subgenual cingulate, an area associated with mood and emotion, and more moderately expressed in the dorsolateral prefrontal cortex, an area associated with cognitive processes. Extrasynaptic NMDAR, which often contain with the GluN2B subunit, have been linked to detrimental cellular events like neurodegeneration. Here, using high resolution electron microscopy in rhesus macaques, we found evidence that extrasynaptic NMDAR-GluN2B expression may be more prominent in subgenual cortex than in the dorsolateral prefrontal cortex. Conversely, synaptic NMDAR-GluN2B may be more prominent in the dorsolateral prefrontal cortex, consistent with their essential contribution to neuronal firing during working memory. These findings may help to illuminate the propensity of the subgenual cortex to tonic hyperactivity in major depression and its vulnerability to neurodegeneration in Alzheimer's disease, and may help to explain how rapid acting antidepressants exert therapeutic action across diverse neural circuits.

Supralinear dendritic integration in murine dendrite-targeting interneurons

Non-linear summation of synaptic inputs to the dendrites of pyramidal neurons has been proposed to increase the computation capacity of neurons through coincidence detection, signal amplification, and additional logic operations such as XOR. Supralinear dendritic integration has been documented extensively in principal neurons, mediated by several voltage-dependent conductances. It has also been reported in parvalbumin-positive hippocampal basket cells, in dendrites innervated by feedback excitatory synapses. Whether other interneurons, which support feed-forward or feedback inhibition of principal neuron dendrites, also exhibit local non-linear integration of synaptic excitation is not known. Here, we use patch-clamp electrophysiology, and two-photon calcium imaging and glutamate uncaging, to show that supralinear dendritic integration of near-synchronous spatially clustered glutamate-receptor mediated depolarization occurs in NDNF-positive neurogliaform cells and oriens-lacunosum moleculare interneurons in the mouse hippocampus. Supralinear summation was detected via recordings of somatic depolarizations elicited by uncaging of glutamate on dendritic fragments, and, in neurogliaform cells, by concurrent imaging of dendritic calcium transients. Supralinearity was abolished by blocking NMDA receptors (NMDARs) but resisted blockade of voltage-gated sodium channels. Blocking L-type calcium channels abolished supralinear calcium signalling but only had a minor effect on voltage supralinearity. Dendritic boosting of spatially clustered synaptic signals argues for previously unappreciated computational complexity in dendrite-projecting inhibitory cells of the hippocampus.

Advancing neural computation: experimental validation and optimization of dendritic learning in feedforward tree networks

OBJECTIVES

This study aims to explore the capabilities of dendritic learning within feedforward tree networks (FFTN) in comparison to traditional synaptic plasticity models, particularly in the context of digit recognition tasks using the MNIST dataset.

METHODS

We employed FFTNs with nonlinear dendritic segment amplification and Hebbian learning rules to enhance computational efficiency. The MNIST dataset, consisting of 70,000 images of handwritten digits, was used for training and testing. Key performance metrics, including accuracy, precision, recall, and F1-score, were analysed.

RESULTS

The dendritic models significantly outperformed synaptic plasticity-based models across all metrics. Specifically, the dendritic learning framework achieved a test accuracy of 91%, compared to 88% for synaptic models, demonstrating superior performance in digit classification.

CONCLUSIONS

Dendritic learning offers a more powerful computational framework by closely mimicking biological neural processes, providing enhanced learning efficiency and scalability. These findings have important implications for advancing both artificial intelligence systems and computational neuroscience.

Molecular mechanisms of the specialization of human synapses in the neocortex

Synapses of the neocortex specialized during human evolution to develop over extended timescales, process vast amounts of information and increase connectivity, which is thought to underlie our advanced social and cognitive abilities. These features reflect species-specific regulations of neuron and synapse cell biology. However, despite growing understanding of the human genome and the brain transcriptome at the single-cell level, linking human-specific genetic changes to the specialization of human synapses has remained experimentally challenging. In this review, we describe recent progress in characterizing divergent morphofunctional and developmental properties of human synapses, and we discuss new insights into the underlying molecular mechanisms. We also highlight intersections between evolutionary innovations and disorder-related dysfunctions at the synapse.

Net synaptic drive of fast-spiking interneurons is inverted towards inhibition in human FCD I epilepsy

Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs.

The plasticity of pyramidal neurons in the behaving brain

Neurons are plastic. That is, they change their activity according to different behavioural conditions. This endows pyramidal neurons with an incredible computational power for the integration and processing of synaptic inputs. Plasticity can be investigated at different levels of investigation within a single neuron, from spines to dendrites, to synaptic input. Although most of our knowledge stems from the in vitro brain slice preparation, plasticity plays a vital role during behaviour by providing a flexible substrate for the execution of appropriate actions in our ever-changing environment. Owing to advances in recording techniques, the plasticity of neurons and the neural networks in which they are embedded is now beginning to be realized in the in vivo intact brain. This review focuses on the structural and functional synaptic plasticity of pyramidal neurons, with a specific focus on the latest developments from in vivo studies. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Aging-associated weakening of the action potential in fast-spiking interneurons in the human neocortex

Aging is associated with the slowdown of neuronal processing and cognitive performance in the brain; however, the exact cellular mechanisms behind this deterioration in humans are poorly elucidated. Recordings in human acute brain slices prepared from tissue resected during brain surgery enable the investigation of neuronal changes with age. Although neocortical fast-spiking cells are widely implicated in neuronal network activities underlying cognitive processes, they are vulnerable to neurodegeneration. Herein, we analyzed the electrical properties of 147 fast-spiking interneurons in neocortex samples resected in brain surgery from 106 patients aged 11-84 years. By studying the electrophysiological features of action potentials and passive membrane properties, we report that action potential overshoot significantly decreases and spike half-width increases with age. Moreover, the action potential maximum-rise speed (but not the repolarization speed or the afterhyperpolarization amplitude) significantly changed with age, suggesting a particular weakening of the sodium channel current generated in the soma. Cell passive membrane properties measured as the input resistance, membrane time constant, and cell capacitance remained unaffected by senescence. Thus, we conclude that the action potential in fast-spiking interneurons shows a significant weakening in the human neocortex with age. This may contribute to the deterioration of cortical functions by aging.

Variation and convergence in the morpho-functional properties of the mammalian neocortex

Man's natural inclination to classify and hierarchize the living world has prompted neurophysiologists to explore possible differences in brain organisation between mammals, with the aim of understanding the diversity of their behavioural repertoires. But what really distinguishes the human brain from that of a platypus, an opossum or a rodent? In this review, we compare the structural and electrical properties of neocortical neurons in the main mammalian radiations and examine their impact on the functioning of the networks they form. We discuss variations in overall brain size, number of neurons, length of their dendritic trees and density of spines, acknowledging their increase in humans as in most large-brained species. Our comparative analysis also highlights a remarkable consistency, particularly pronounced in marsupial and placental mammals, in the cell typology, intrinsic and synaptic electrical properties of pyramidal neuron subtypes, and in their organisation into functional circuits. These shared cellular and network characteristics contribute to the emergence of strikingly similar large-scale physiological and pathological brain dynamics across a wide range of species. These findings support the existence of a core set of neural principles and processes conserved throughout mammalian evolution, from which a number of species-specific adaptations appear, likely allowing distinct functional needs to be met in a variety of environmental contexts.

Biophysical Modeling of Frontocentral ERP Generation Links Circuit-Level Mechanisms of Action-Stopping to a Behavioral Race Model

Human frontocentral event-related potentials (FC-ERPs) are ubiquitous neural correlates of cognition and control, but their generating multiscale mechanisms remain mostly unknown. We used the Human Neocortical Neurosolver's biophysical model of a canonical neocortical circuit under exogenous thalamic and cortical drive to simulate the cell and circuit mechanisms underpinning the P2, N2, and P3 features of the FC-ERP observed after Stop-Signals in the Stop-Signal task (SST; N = 234 humans, 137 female). We demonstrate that a sequence of simulated external thalamocortical and corticocortical drives can produce the FC-ERP, similar to what has been shown for primary sensory cortices. We used this model of the FC-ERP to examine likely circuit-mechanisms underlying FC-ERP features that distinguish between successful and failed action-stopping. We also tested their adherence to the predictions of the horse-race model of the SST, with specific hypotheses motivated by theoretical links between the P3 and Stop process. These simulations revealed that a difference in P3 onset between successful and failed Stops is most likely due to a later arrival of thalamocortical drive in failed Stops, rather than, for example, a difference in the effective strength of the input. In contrast, the same model predicted that early thalamocortical drives underpinning the P2 and N2 differed in both strength and timing across stopping accuracy conditions. Overall, this model generates novel testable predictions of the thalamocortical dynamics underlying FC-ERP generation during action-stopping. Moreover, it provides a detailed cellular and circuit-level interpretation that supports links between these macroscale signatures and predictions of the behavioral race model.

Morpho-electric diversity of human hippocampal CA1 pyramidal neurons

Hippocampal pyramidal neuron activity underlies episodic memory and spatial navigation. Although extensively studied in rodents, extremely little is known about human hippocampal pyramidal neurons, even though the human hippocampus underwent strong evolutionary reorganization and shows lower theta rhythm frequencies. To test whether biophysical properties of human Cornu Amonis subfield 1 (CA1) pyramidal neurons can explain observed rhythms, we map the morpho-electric properties of individual CA1 pyramidal neurons in human, non-pathological hippocampal slices from neurosurgery. Human CA1 pyramidal neurons have much larger dendritic trees than mouse CA1 pyramidal neurons, have a large number of oblique dendrites, and resonate at 2.9 Hz, optimally tuned to human theta frequencies. Morphological and biophysical properties suggest cellular diversity along a multidimensional gradient rather than discrete clustering. Across the population, dendritic architecture and a large number of oblique dendrites consistently boost memory capacity in human CA1 pyramidal neurons by an order of magnitude compared to mouse CA1 pyramidal neurons.

Computational Modeling of Extrasynaptic NMDA Receptors: Insights into Dendritic Signal Amplification Mechanisms

Dendritic structures play a pivotal role in the computational processes occurring within neurons. Signal propagation along dendrites relies on both passive conduction and active processes related to voltage-dependent ion channels. Among these channels, extrasynaptic N-methyl-D-aspartate channels (exNMDA) emerge as a significant contributor. Prior studies have mainly concentrated on interactions between synapses and nearby exNMDA (100 nm-10 µm from synapse), activated by presynaptic membrane glutamate. This study concentrates on the correlation between synaptic inputs and distal exNMDA (>100 µm), organized in clusters that function as signal amplifiers. Employing a computational model of a dendrite, we elucidate the mechanism underlying signal amplification in exNMDA clusters. Our findings underscore the pivotal role of the optimal spatial positioning of the NMDA cluster in determining signal amplification efficiency. Additionally, we demonstrate that exNMDA subunits characterized by a large conduction decay constant. Specifically, NR2B subunits exhibit enhanced effectiveness in signal amplification compared to subunits with steeper conduction decay. This investigation extends our understanding of dendritic computational processes by emphasizing the significance of distant exNMDA clusters as potent signal amplifiers. The implications of our computational model shed light on the spatial considerations and subunit characteristics that govern the efficiency of signal amplification in dendritic structures, offering valuable insights for future studies in neurobiology and computational neuroscience.

A biologically inspired repair mechanism for neuronal reconstructions with a focus on human dendrites

Investigating and modelling the functionality of human neurons remains challenging due to the technical limitations, resulting in scarce and incomplete 3D anatomical reconstructions. Here we used a morphological modelling approach based on optimal wiring to repair the parts of a dendritic morphology that were lost due to incomplete tissue samples. In Drosophila, where dendritic regrowth has been studied experimentally using laser ablation, we found that modelling the regrowth reproduced a bimodal distribution between regeneration of cut branches and invasion by neighbouring branches. Interestingly, our repair model followed growth rules similar to those for the generation of a new dendritic tree. To generalise the repair algorithm from Drosophila to mammalian neurons, we artificially sectioned reconstructed dendrites from mouse and human hippocampal pyramidal cell morphologies, and showed that the regrown dendrites were morphologically similar to the original ones. Furthermore, we were able to restore their electrophysiological functionality, as evidenced by the recovery of their firing behaviour. Importantly, we show that such repairs also apply to other neuron types including hippocampal granule cells and cerebellar Purkinje cells. We then extrapolated the repair to incomplete human CA1 pyramidal neurons, where the anatomical boundaries of the particular brain areas innervated by the neurons in question were known. Interestingly, the repair of incomplete human dendrites helped to simulate the recently observed increased synaptic thresholds for dendritic NMDA spikes in human versus mouse dendrites. To make the repair tool available to the neuroscience community, we have developed an intuitive and simple graphical user interface (GUI), which is available in the TREES toolbox (www.treestoolbox.org).

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".

Shared and divergent principles of synaptic transmission between cortical excitatory neurons in rodent and human brain

Information transfer between principal neurons in neocortex occurs through (glutamatergic) synaptic transmission. In this focussed review, we provide a detailed overview on the strength of synaptic neurotransmission between pairs of excitatory neurons in human and laboratory animals with a specific focus on data obtained using patch clamp electrophysiology. We reach two major conclusions: (1) the synaptic strength, measured as unitary excitatory postsynaptic potential (or uEPSP), is remarkably consistent across species, cortical regions, layers and/or cell-types (median 0.5 mV, interquartile range 0.4-1.0 mV) with most variability associated with the cell-type specific connection studied (min 0.1-max 1.4 mV), (2) synaptic function cannot be generalized across human and rodent, which we exemplify by discussing the differences in anatomical and functional properties of pyramidal-to-pyramidal connections within human and rodent cortical layers 2 and 3. With only a handful of studies available on synaptic transmission in human, it is obvious that much remains unknown to date. Uncovering the shared and divergent principles of synaptic transmission across species however, will almost certainly be a pivotal step toward understanding human cognitive ability and brain function in health and disease.

Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair

Due to its complex and multifaceted nature, developing effective treatments for epilepsy is still a major challenge. To deal with this complexity we introduce the concept of degeneracy to the field of epilepsy research: the ability of disparate elements to cause an analogous function or malfunction. Here, we review examples of epilepsy-related degeneracy at multiple levels of brain organisation, ranging from the cellular to the network and systems level. Based on these insights, we outline new multiscale and population modelling approaches to disentangle the complex web of interactions underlying epilepsy and to design personalised multitarget therapies.