Giorgio A. Ascoli

The paper presents an automated machine learning pipeline for standardizing and correcting neural morphology reconstructions, achieving high accuracy in dendritic relabeling and structural normalization.

Hippocampome.org provides a resource for classifying neuron types in the rodent hippocampal formation, focusing on subicular neurons and their circuitry.

The paper mathematically proves that spatial periodicity in grid cell firing is the only solution to a neural sequence code for 2-D trajectories, explaining the hexagonal firing pattern and its functional role.

The paper introduces a pipeline to profile dendritic morphology of genetically-defined single neurons in the mouse brain, revealing morphological modules and age- or HD-associated changes.

This study shows a biologically realistic spiking neural network model of mouse CA3 can robustly perform auto-association and pattern completion through cell assemblies.

The paper describes improvements to NeuroMorpho.Org, a digital neuromorphology database, to accelerate data sharing and processing, reducing time from data identification to public release by 63.7%.

The paper uses a spiking continuous attractor network model with biophysically realistic parameters to reproduce grid cell firing patterns and spatial properties observed in rodents.

Hippocampome.org v2.0 provides data-driven computational simulations of rodent hippocampal circuits using expanded neuron type classifications and empirical data.

The paper quantifies the impact of data sharing in neuroscience by analyzing citations and reusage of neural morphology datasets.

The paper maps single cortical neurons across the human brain to profile morphological diversity and stereotypy using a new tomography approach.

The paper presents a tool that uses natural language processing and deep learning to automatically identify scientific publications describing digital reconstructions of neural morphology, achieving high accuracy and efficiency.

The paper defines neuron connectivity types (c-types) using morphology and connectivity data, showing they better capture subtype distinctions than other features.

BigNeuron benchmarks automatic neuron reconstruction algorithms using gold standard annotations and image quality metrics, showing that consensus methods outperform individual algorithms.

This study identifies the role of the zinc-BED transcription factor Bedwarfed in regulating dendritic growth and branching through transcriptional and translational mechanisms in Drosophila.

The paper provides a guide to the BRAIN Initiative Cell Census Network (BICCN) data ecosystem, its tools, and resources for analyzing brain cell types across species.

The paper uses connectivity-based neuronal classification to analyze Drosophila brain circuitry, revealing key communication pathways and their functional roles.

The paper presents a similarity search tool for comparing neural morphologies across species and brain regions using morphometric and vectorized descriptors.

This paper estimates the number of neuron types in the rodent hippocampal formation using literature mining and numerical optimization, providing population counts across anatomical regions.

This study identifies PP2A phosphatase as a regulator of cell-type specific dendritic morphology in Drosophila neurons, with distinct roles in promoting branching in Class IV neurons and restricting arborization in Class I neurons.

The paper generates a multimodal cell census and atlas of the mammalian primary motor cortex, revealing a unified molecular genetic landscape and cross-species taxonomy of cell types.

The paper provides a detailed cellular-resolution map of the mouse primary motor cortex, defining cell types and their connectivity.

The paper creates a multiscale connectivity atlas of the mouse BLA by analyzing circuit-tracing data to identify distinct projection neuron domains and their brain-wide targets.

This paper introduces a method to classify neurons based on their connectivity using a stochastic block model and spectral embedding, achieving accurate clustering even with noise and edge swaps.

The paper introduces MorphoHub, a platform for generating petabyte-scale multi-morphometry data, enabling high-quality analysis of neuronal structures in whole brain datasets.

The paper quantifies the distinct roles of microtubules and F-actin in shaping dendritic architecture using live imaging and computational modeling in Drosophila neurons.

The paper shows that networks of identical bursting neurons with inhibitory coupling exhibit itinerant dynamics and transient synchrony modes, unlike singlet-spiking neurons.

This study maps cortico-tectal projections in the mouse brain, identifying four collicular zones with distinct cortical inputs and subnetwork organization.

The paper uses operations research methods to estimate neuron type population sizes in the rodent hippocampus based on literature-derived properties.

The paper classifies firing patterns of hippocampal neuron types using automated protocols and identifies new subtypes and statistical associations between firing patterns and other properties.