Netanel Ofer

For nearly 150 years, textbooks have described dendritic morphology as optimized for efficient synaptic voltage transfer from spines to the soma, implemented as a tubular design respecting Rall’s 3/2 rule for impedance matching at branch points. Here, we reveal that this view is an oversimplification. Using multiple high-resolution imaging techniques, we demonstrate that dendrites in cortical and hippocampal neurons exhibit nanoscale constrictions, termed dendritic shaft constrictions (DSCs), with diameters ranging from ∼100 to 500 nanometers in mice. We also identified DSCs in human hippocampal and cortical neurons. We provide theoretical and experimental lines of evidence that these constrictions effectively partition the dendrite into distinct electrical compartments, shaping dendritic integration of synaptic potentials.

Dendritic spines, small protrusions covering the dendrites of most neurons, are fundamental elements of synaptic connectivity, yet their network-level organization remains poorly understood. Here we leverage the large-scale MICrONS volumetric electron microscopy dataset of mouse primary visual cortex to explore the connectivity logic of dendritic spines across multiple spatial scales. Our analysis provides structural support for the “connectivity and diversity” hypothesis, showing that, for both excitatory and inhibitory neurons, dendritic spine density correlates with the number and the diversity of presynaptic partners. We further show that the preference for excitatory axons to form synapses on spines increases with distance from the soma. In addition, we find that spines serve as postsynaptic targets for high-output neurons (“out hubs”). We finally uncover an input/output correlation, in which neurons that share their input also preferentially target spines through their axonal output. These correlations persist across network sizes, consistent with a scale-invariant structural organization of cortical connectivity. We hypothesize that dendritic spines provide a structural substrate for network-level cooperation, by enabling distributed cortical activity to propagate through parallel synchronous chains, potentially amplified by nonlinear voltage responses at the spine and cellular level. These findings suggest that dendritic spines are key structural mechanisms for neuronal ensembles, attractor dynamics, and pattern completion.

Dendritic spines are nano-scale compartments that host the majority of excitatory synapses on cortical pyramidal neurons (PNs); hundreds of spines/PN also receive an inhibitory synapse (dually-innervated spines, DiSs). Using analytic theory and detailed biophysical models of ~2,000 densely reconstructed spines, we show that recurrent spine-neck narrowing substantially increases spine-neck resistance (R _neck ), and that elevated R _neck accelerates spine-head voltage dynamics, shortening spinous postsynaptic potentials by up to ~3-fold. R _neck improves the tracking of high-frequency synaptic inputs and strongly modulates Ca ²⁺ signaling and the potency and temporal precision of inhibitory gating in DiSs. This work identifies R _neck as a dynamic "knob", directly linking spine ultrastructure to information processing and plasticity in cortical PNs and circuits, yielding testable experimental predictions. Our "biophysics of connectomics" paradigm naturally raises computational-oriented questions, including how inhibitory "gates" in dendritic spines expand context-dependent computations, implement single-cell and network-level routing, and enable selective encoding of precise temporal patterns.

The propagation of action potentials along axons is traditionally considered to be reliable, as a consequence of the high safety factor of action potential propagation. However, numerical simulations have suggested that, at high frequencies, spikes could fail to invade distal axonal branches. Given the complex morphologies of axonal trees, with extensive branching and long-distance projections, spike propagation failures could be functionally important. To explore this experimentally in vivo , we used an axonal-targeted calcium indicator to image action potentials at axonal terminal branches in superficial layers from mouse somatosensory cortical pyramidal neurons. We activated axons with an extracellular electrode, varying stimulation frequencies, and computationally extracted axonal morphologies and associated calcium responses. We find that axonal boutons have higher calcium accumulations than their parent axons, as was reported in vitro . But, contrary to previous in vitro results, our data reveal spike failures in a significant subset of branches, as a function of branching geometry and spike frequency. The filtering is correlated with the geometric ratio of the branch diameters, as expected by cable theory. These findings suggest that axonal morphologies contribute to signal processing in the cortex.

Single-nucleotide polymorphism (SNP) markers have great potential to identify individuals, family relations, biogeographical ancestry, and phenotypic traits. In many forensic situations, DNA mixtures of a victim and an unknown suspect exist. Extracting SNP profiles from suspect’s samples can be used to assist investigation or gather intelligence. Computational tools to determine inclusion/exclusion of a known individual from a mixture exist, but no algorithm for extraction of an unknown SNP profile without a list of suspects is available. Here, we present an advanced haplotype-based HMM algorithm (AH-HA), a novel computational approach for extracting an unknown SNP profile from whole genome sequencing (WGS) of a two-person mixture. AH-HA utilizes techniques similar to the ones used in haplotype phasing. It constructs the inferred genotype as an imperfect mosaic of haplotypes from a reference panel of the target population. It outperforms more simplistic approaches, maintaining high performance through a wide range of sequencing depths (500×–5×). AH-HA can be applied in cases of victim–suspect mixtures and improves the capabilities of the investigating forces. This approach can be extended to more complex mixtures with more donors and less prior information, further motivating the development of SNP-based forensics technologies.

Dendritic spines have diverse morphologies, with a wide range of head and neck sizes, and these morphological differences likely generate different synaptic and functional properties. To explore how this morphological diversity differs across species we analyzed 3D confocal reconstructions of ~8,000 human spines and ~1,700 mouse spines, labeled by intracellular injections in fixed tissue. Using unsupervised machine-learning algorithms, we computationally separated spine heads and necks and systematically measured morphological features of spines in apical and basal dendrites from cortical pyramidal cells. Human spines had unimodal distributions of parameters, without any evidence of morphological subtypes. Their spine necks were longer and thinner in apical than in basal spines, and spine head volumes of an 85-years-old individual were larger than those of a 40-years-old individual. Human spines overall had longer and thicker necks and bigger head volumes than mouse spines. Our results indicate that human spines form part of a morphological continuum, are larger and longer than those of mice, and become larger with increasing adult age. These morphological differences in spines across species could generate functional differences in biochemical and electrical spine compartmentalization, or in synaptic properties, across species and ages.

Dendritic spines’ electrical function?: Dendritic spines are small protrusions that cover the dendrites of most neurons in the brain. Their electrical properties are still controversially discussed. Cornejo et al . used an array of techniques to investigate the degree of voltage attenuation by dendritic spine necks in pyramidal neurons of the mouse neocortex. Spines not only synchronously depolarized in response to backpropagating action potentials, but local and transient depolarization also occurred. Isolated depolarization in individual spines reflected localized synaptic activation. A significant voltage gradient between dendritic spine and dendrite indicated that spines may constitute elementary electric compartments. The spine neck resistance is thus not negligible and may substantially contribute to the regulation of synaptic efficacy in the central nervous system. —PRS

Dendritic spines are membranous protrusions that receive essentially all excitatory inputs in most mammalian neurons. Spines, with a bulbous head connected to the dendrite by a thin neck, have a variety of morphologies that likely impact their functional properties. Nevertheless, the question of whether spines belong to distinct morphological subtypes is still open. Addressing this quantitatively requires clear identification and measurements of spine necks. Recent advances in electron microscopy enable large‐scale systematic reconstructions of spines with nanometer precision in 3D. Analyzing ultrastructural reconstructions from mouse neocortical neurons with computer vision algorithms, we demonstrate that the vast majority of spine structures can be rigorously separated into heads and necks, enabling morphological measurements of spine necks. We then used a database of spine morphological parameters to explore the potential existence of different spine classes. Without exception, our analysis revealed unimodal distributions of individual morphological parameters of spine heads and necks, without evidence for subtypes of spines. The postsynaptic density size was strongly correlated with the spine head volume. The spine neck diameter, but not the neck length, was also correlated with the head volume. Spines with larger head volumes often had a spine apparatus and pairs of spines in a post‐synaptic cell contacted by the same axon had similar head volumes. Our data reveal a lack of morphological subtypes of spines and indicate that the spine neck length and head volume must be independently regulated. These results have repercussions for our understanding of the function of dendritic spines in neuronal circuits.