Anthony M. Zador

TissueFormer: Extending single-cell foundation models to predict population-level phenotypes

TissueFormer predicts population-level phenotypes from single-cell data, outperforming existing methods in predicting COVID-19 severity and cortical area identity.

Eigengene reveals invariant global spatial patterns across mouse and fish brain development

The paper shows that the eigengene, the principal component of gene expression, maintains an invariant global spatial pattern across mouse and zebrafish brain development, suggesting evolutionary conservation and a lineage-based explanation.

Discovery and shaping of decision strategies using adversarial stimuli in rats

The paper uses probe stimuli to uncover and modify decision strategies in rats performing a visual decision task, revealing strategy variation and adaptability to stimulus changes.

Brain-wide representations of prior information in mouse decision-making

Mice infer stimulus-side priors from recent choices; prior signals are decodable pre-stimulus in 24.0% to 30.2% of 242 brain regions, including early visual and motor areas.

A Brain-Wide Map of Neural Activity during Complex Behaviour

The paper presents a brain-wide neural activity map from 621,733 neurons across 139 mice performing a decision-making task, showing how neural activity encodes task variables across brain regions.

Massive Multiplexing of Spatially Resolved Single Neuron Projections with Axonal BARseq

The paper introduces axonal BARseq, a high-throughput method for mapping single-neuron projections in the brain, and demonstrates its application in mapping over 8,000 mouse auditory cortex neurons from a single brain.

Selective expansion of motor cortical projections in the evolution of vocal novelty

The paper identifies a 200% expansion of orofacial motor cortical projections to auditory and midbrain regions in singing mice, suggesting a mechanism for vocal behavior evolution.

Stochastic Wiring of Cell Types Enhances Fitness by Generating Phenotypic Variability

The paper uses a computational model to show that developmental stochasticity in neural wiring increases population fitness by generating phenotypic variability in unpredictable environments.

Early dynamics of excitation and inhibition maintain late frequency tuning in auditory cortex

The paper investigates how early inhibition shapes tone-evoked responses in auditory cortex by manipulating parvalbumin-expressing interneurons.

Stable sound decoding despite modulated sound representation in the auditory cortex

The paper investigates how auditory cortex encodes sound and non-sensory context, finding that neural activity reflects both stimuli and reward expectations, but the decoder remains stable despite variable sensory representations.

Data architecture for a large-scale neuroscience collaboration

The paper describes a modular data architecture for a neuroscience collaboration, enabling data contribution, access, and analysis across multiple labs.

Whole-cortex in situ sequencing reveals peripheral input-dependent cell type-defined area identity

The paper uses BARseq to analyze transcriptomic signatures in mouse cortex, showing that cell type composition defines area identity and is shaped by peripheral inputs.

Wiring logic of the early rodent olfactory system revealed by high-throughput sequencing of single neuron projections

The paper uses high-throughput sequencing to analyze neuronal projections in the mouse olfactory system and finds structured connectivity along the anterior-posterior axis.

Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics

The paper introduces ExBarSeq, a method for high-resolution multiplexing of barcodes and synaptic proteins in neurons, demonstrating its application in mouse brain tissue.

Diversity and task-dependence of task representations in V1 during freely-moving decisions

The paper examines how non-sensory task features are represented in rat V1 during a visual decision task, showing that both sensory and non-sensory information are integrated in a task-dependent manner.

Cellular Anatomy of the Mouse Primary Motor Cortex

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

Replicability of spatial gene expression atlas data from the adult mouse brain

The paper assesses the replicability of spatial gene expression data from the adult mouse brain between two datasets, finding that classification performance is higher within datasets than across platforms.

Standardized and reproducible measurement of decision-making in mice

This paper develops a standardized task for measuring decision-making in mice, showing reproducible results across multiple laboratories and providing a public dataset and tools.

Encoding innate ability through a genomic bottleneck

The paper explores how neural circuits can be compressed through a genomic bottleneck, showing that this compression can enhance transfer learning and suggest implications for AI design.

BARcode DEmixing through Non-negative Spatial Regression (BarDensr)

BarDensr demixes spatial transcriptomics data by modeling the imaging process and using convex optimization, achieving state-of-the-art signal recovery in dense or low-resolution data.

Corticostriatal Plasticity Established by Initial Learning Persists After Behavioral Reversal

This study shows that synaptic strength established during initial learning persists even after behavioral reversal in mice.

Integrating barcoded neuroanatomy with spatial transcriptional profiling reveals cadherin correlates of projections shared across the cortex

The paper introduces BARseq2 to map neuronal projections and gene expression in mice, finding shared cadherin signatures across cortical areas.

BRICseq bridges brain-wide interregional connectivity to neural activity and gene expression in single animals

BRICseq maps brain-wide connectivity, activity, and gene expression in single animals, showing gene expression patterns predict connectivity and activity correlations.

High-throughput mapping of long-range neuronal projection using in situ sequencing

The paper introduces BARseq, a method for high-throughput mapping of neuronal projections in the mouse auditory cortex, revealing novel projection types in specific cell subtypes.

A Critique of Pure Learning: What Artificial Neural Networks can Learn from Animal Brains

This paper argues that animal learning is not primarily driven by sophisticated algorithms but by innate, structured brain connectivity, suggesting a new direction for improving artificial neural networks.

SYNPLA: A synapse-specific method for identifying learning-induced synaptic plasticity loci

SYNPLA identifies learning-induced synaptic plasticity loci by detecting circuit-specific changes in synaptic strength.

Network cloning using DNA barcodes

The paper introduces a method to clone neural networks using DNA barcodes by solving a synthesis problem with efficient computational approaches.

Single-cell molecular connectomics of intracortically-projecting neurons

The paper develops ConnectID, a method linking connectome and transcriptome in single neurons, identifying transcriptional modules associated with axonal projections to specific cortical and subcortical targets.

A single-cell anatomical blueprint for intracortical information transfer from primary visual cortex

This study maps axonal projection patterns of 591 V1 neurons in mice, finding most neurons broadcast to multiple cortical targets rather than sending dedicated projections to single areas.

A computational framework for converting high-throughput DNA sequencing data into neural circuit connectivity.

The paper describes a computational framework to convert high-throughput DNA sequencing data into neural circuit connectivity using BOINC and applies it to pseudorabies virus experiments.