Focus on neuroscience methods

In this special issue, we present a series of reviews, perspectives and commentaries that highlight advances in methods and analytical approaches and provide guidelines and best practices in various areas of neuroscience.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

The Organization for Human Brain Mapping presents its best practices report for reproducible EEG and MEG research, highlighting issues and main recommendations in this Perspective.

In this Primer article, Bijsterbosch and colleagues provide an accessible discussion of the challenges faced in analytical representations of functional brain organization and provide clear recommendations to unite a fractionated field.

Chiaradia and Lancaster review applications and limitations of brain organoids, placing them in context with other technologies and describing how these methods are heavily informed by in vivo development.

This Review discusses two high-throughput techniques—massively parallel reporter assays (MPRAs) and CRISPR screens—focusing on their potential to validate non-coding genetic risk variants in human stem cell models of complex brain disorders.

This review summarizes advances in electrical, optical and microfluidic neural interfaces with characteristics that suggest near-term potential for broad deployment to the neuroscience community.

Behavioral quantification is changing neuroscience. Pereira et al. provide an overview of the latest advances in motion tracking and behavior prediction and discuss how these methods are used to understand the brain in ways not previously possible.

A method for parameterizing electrophysiological neural power spectra into periodic and aperiodic components is introduced, addressing limitations of common approaches. The method is validated in simulation and demonstrated on real data applications.

This work develops PSID, a dynamic modeling method to dissociate and prioritize neural dynamics relevant to a given behavior.

The authors present an edge-centric model of brain connectivity. Edge networks are stable across datasets, and their structure can be modulated by sensory input. When clustered, edge networks yield pervasively overlapping functional modules.

Kuan, Phelps, et al. used synchrotron X-ray imaging and deep learning to map dense neuronal wiring in fly and mouse tissue, enabling examination of individual cells and connectivity in circuits governing motor control and perceptual decision-making.

This study describes a series of new gene-regulatory sequences that restrict expression of viral transgenes to specific interneuron subtypes, allowing for selective monitoring and manipulation of their activity from mice to humans.

Garcia-Marques et al. present CLADES, an innovative approach to study neuronal lineages based on CRISPR. Inspired by synthetic biology, CLADES relies on a system of genetic switches to activate and inactivate reporter genes in a predetermined order.

SPARC is an all-genetic toolkit to express effectors in precise proportions of neurons. This method enables imaging of individual neurons and manipulation of neuronal subpopulations.

Deschloroclozapine (DCZ) is a broadly useful chemogenetic agonist for studies using nonhuman primates and mice. DCZ rapidly and reversibly activates DREADDs, and its binding can be visualized noninvasively by positron emission tomography.

Makin and colleagues decode speech from neural signals recorded during a preoperative procedure, using an algorithm inspired by machine translation. For one participant reading from a closed set of 50 sentences, decoding accuracy is nearly perfect.

Sey et al. report a computational tool, H-MAGMA, that extracts neurobiological insights from brain-disorder GWAS by linking risk variants to their cognate genes using chromatin interaction profiles from human brain tissue.

A chemogenetic approach was developed for cell-type-specific drug-inducible protein synthesis inhibition in mice. It was used to show that consolidation of long-term aversive memories requires rapid neuronal protein synthesis in the amygdala.

Human stem cell-derived microglia integrate into mouse brain, displaying transcriptome signatures of microglia directly isolated from human brain and providing a chimeric model to study human-specific aspects of Alzheimer’s disease and other brain diseases.

An event-based machine learning model developed to detect fluorescent astrocytic activity and neurotransmitter dynamics enables new and accurate approaches to quantifying physiology in brain slices and in vivo.

Fecher et al. devise an approach to isolate cell-type-specific mitochondria from the mouse CNS. They demonstrate proteomic diversity of cerebellar mitochondria covering bioenergetics, calcium handling and organelle contact sites.

A peroxidase-based labeling method allows simultaneous visualization of multiple cell types using electron microscopy without the need for spectral separation, enabling identification of synapses between genetically defined neuronal populations.

A modified brain-organoid culture generates extensive axon outgrowth with specific tract-like patterns. Organoid tracts connect neurons across distant sites and can innervate and stimulate co-cultured mouse spinal cord tissue to elicit muscle contractions.

The authors generate 3D brain organoids containing oligodendrocytes, astrocytes, and neurons derived from human pluripotent stem cells. These human oligodendrocytes are transcriptionally similar to primary cells and mature to myelinate axons.

Inhibitory interneurons shape neuronal activity of cortical principal neurons. Yetman et al. developed a genetic strategy to elucidate the organization of inhibitory neuron subtypes sending inputs to principal neurons.

Using a deep learning approach to track user-defined body parts during various behaviors across multiple species, the authors show that their toolbox, called DeepLabCut, can achieve human accuracy with only a few hundred frames of training data.