quantification

I3-BC: Image-Based Infiltrating Immune Cell Detection and Outcomes in Breast Cancer Clinical Trials

PROJECT SUMMARY Tumor infiltrating lymphocytes (TILs) represent an accessible biomarker of the tumor-immune microenvironment (TIME) in breast cancer, demonstrating consistent association with response to neoadjuvant chemotherapy and outcomes in HER2-positive and triple-negative breast cancer. Despite efforts to standardize TIL enumeration from hematoxylin and eosin stained tumor slides, TILs have not gained widespread adoption due to inter- observer variability, and time limitations in pathologic assessment, among others. Further, other key elements of the microenvironment, such as tumor-associated macrophages (TAMs), do not yet have standardized approaches for quantification or characterization. As a result, there is no assessment of the TIME for the vast majority of breast cancers diagnosed in the US and around the world. However, the rapid growth of digital pathology offers the potential to leverage computational approaches to overcome these limitations and democratize access to TIL and TAM enumeration. The overall goal of this project is to determine if computational approaches to TILs (existing) and TAMs (to be developed within this grant) are comparable to pathologist- enumerated TILs and TAMs and, further, associated with relevant patient outcomes from two phase III breast cancer clinical trials. Prior to project initiation, we have developed both a compute-intensive artificial intelligence- based TILs approach, an open source software (QuPath)-based TILs approach, and expertise in RNAseq-based immune quantification. We will first focus on TILs - benchmarking the two computational and RNAseq immune approaches against pathologist TIL counts (‘gold standard’) then evaluating association of each with event-free survival in two completed clinical trials (Aim 1). In parallel, we will develop a novel computational approache to enumerate and phenotype TAMs by using immunohistochemical staining for macrophage markers on the same slide with standard H&E, then apply in the same two clinical trials (Aim 2). Our approach is innovative because we will benchmark diverse approaches at scale in relevant clinical studies. The study is significant because we will determine if computational approaches to TILs/TAMs align with pathologist estimates and clinical outcomes, then ensure these algorithms are available to the community. Our long-term goal is to democratize computational TIL and TAM enumeration as pathology decision-support to facilitate integration of accessible tumor-immune microenvironment into clinical trials and care.

Development of an Optical and Colorimetric Biosensor for the Quantification of Microrna 184 for Late Life Depression

Spatial and Single Cell Genomics for Next Generation Neuroscience

The advent of next generation sequencing ushered in a ten-year period of exuberant technology development, enabling the quantification of gene expression and epigenetic features within individual cells, and within intact tissue sections.  In this seminar, I will outline our technological contributions, beginning with the development of Drop-seq, a method for high-throughput single cell analysis, followed by the development of Slide-seq, a technique for measuring genome-wide expression at 10 micron spatial resolution.  Using a combination of these techniques, we recently constructed a comprehensive cell type atlas of the adult mouse brain, positioning cell types within individual brain structures.  I will discuss the major findings from this dataset, including emerging principles of neurotransmission, and the localization of disease gene signatures to specific cell types.  Finally, I will introduce a new spatial technology, Slide-tags, that unifies single cell and spatial genomics into a single, highly scalable assay.

Nature over Nurture: Functional neuronal circuits emerge in the absence of developmental activity

During development, the complex neuronal circuitry of the brain arises from limited information contained in the genome. After the genetic code instructs the birth of neurons, the emergence of brain regions, and the formation of axon tracts, it is believed that neuronal activity plays a critical role in shaping circuits for behavior. Current AI technologies are modeled after the same principle: connections in an initial weight matrix are pruned and strengthened by activity-dependent signals until the network can sufficiently generalize a set of inputs into outputs. Here, we challenge these learning-dominated assumptions by quantifying the contribution of neuronal activity to the development of visually guided swimming behavior in larval zebrafish. Intriguingly, dark-rearing zebrafish revealed that visual experience has no effect on the emergence of the optomotor response (OMR). We then raised animals under conditions where neuronal activity was pharmacologically silenced from organogenesis onward using the sodium-channel blocker tricaine. Strikingly, after washout of the anesthetic, animals performed swim bouts and responded to visual stimuli with 75% accuracy in the OMR paradigm. After shorter periods of silenced activity OMR performance stayed above 90% accuracy, calling into question the importance and impact of classical critical periods for visual development. Detailed quantification of the emergence of functional circuit properties by brain-wide imaging experiments confirmed that neuronal circuits came ‘online’ fully tuned and without the requirement for activity-dependent plasticity. Thus, contrary to what you learned on your mother's knee, complex sensory guided behaviors can be wired up innately by activity-independent developmental mechanisms.

Brain chart for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure.

Vision outside of the visual system (in Drosophila)

We seek to understand the control of behavior – by animals, their brains, and their neurons. Reiser and his team are focused on the fly visual system, using modern methods from the Drosophila toolkit to understand how visual pathways are involved in specific behaviors. Due to the recent connectomics explosion, they now study the brain-wide networks organizing visual information for behavior control. The team combines explorations of visually guided behaviors with functional investigations of specific cell types throughout the fly brain. The Reiser lab actively develops and disseminates new methods and instruments enabling increasingly precise quantification of animal behavior.

Magnetic Resonance Measures of Brain Blood Vessels, Metabolic Activity, and Pathology in Multiple Sclerosis

The normally functioning blood-brain barrier (BBB) regulates the transfer of material between blood and brain. BBB dysfunction has long been recognized in multiple sclerosis (MS), and there is considerable interest in quantifying functional aspects of brain blood vessels and their role in disease progression. Parenchymal water content and its association with volume regulation is important for proper brain function, and is one of the key roles of the BBB. There is convincing evidence that the astrocyte is critical in establishing and maintaining a functional BBB and providing metabolic support to neurons. Increasing evidence suggests that functional interactions between endothelia, pericytes, astrocytes, and neurons, collectively known as the neurovascular unit, contribute to brain water regulation, capillary blood volume and flow, BBB permeability, and are responsive to metabolic demands. Increasing evidence suggests altered metabolism in MS brain which may contribute to reduced neuro-repair and increased neurodegeneration. Metabolically relevant biomarkers may provide sensitive readouts of brain tissue at risk of degeneration, and magnetic resonance offers substantial promise in this regard. Dynamic contrast enhanced MRI combined with appropriate pharmacokinetic modeling allows quantification of distinct features of BBB including permeabilities to contrast agent and water, with rate constants that differ by six orders of magnitude. Mapping of these rate constants provides unique biological aspects of brain vasculature relevant to MS.

Consciousness, falsification and epistemic constraints

Consciousness is a phenomenon unlike any other studied in natural science. Yet when building theories and designing experiments, we often proceed as if this were not the case. In this talk, I present two recent investigations of mine which explore the implications of consciousness' unique epistemic context for scientific theory building and experimental design. The first investigation is concerned with falsifications of theories of consciousness and identifies a rather deep problem in the usual scheme of testing theories. The second is an axiomatization and subsequent formalization of some of consciousness' more problematic epistemic features that allows to precisely quantify where the usual scientific methodology ceases to be applicable. For both cases, I indicate ways to resolve the problem.

Co-development of accommodation and vergence and quantification of their interaction

Bernstein Conference 2024

Semi-supervised quantification and interpretation of undirected human behavior

COSYNE 2023

Quantification of nonsense-free correlation uncovers the interaction between top-down and bottom-up sources of behavioral correlation in mouse V1

COSYNE 2025

Automated quantification and 3D colocalization analysis of fluorescent nuclear markers with an ImageJ macro: example of a reproducible, traceable and accessible workflow for biologists

Machine learning-based dendritic spine segmentation and quantification​

Machine-learning histopathological segmentation and quantification of tauopathies in classic vs rapidly progressive forms of Alzheimer’s disease

Non-invasive transcranial whole brain angiography and hemodynamic quantification at the microscopic scale in rodents

Non-invasive in vivo brain inflammation quantification using a far-red fluorescent reporter mouse

Quantification of axonal projections from neurons located in layers 2/3, 5 and 6 of mouse barrel cortex

Quantification of infra-slow brain signals using graphene microtransistors (gSGFETs)

Quantification of neonatal motor activity after brain injury

Quantification of Regional and Interspecies Astrocyte Involvement in Synapses

A quick, easy and cost-efficient method for the hippocampal subregion specific differential quantification of 5mC and 5hmC

Virus-mediated astrocyte cAMP quantification

Visualization and High-throughput Quantification of Akt Activity in Live-Cell Neuroinflammatory Models

AI-driven image analysis for label-free quantification of chemotherapeutic cytotoxicity in glial cells

FENS Forum 2024

Control of epileptiform discharges by electric fields: Quantification of fields and neural effects

FENS Forum 2024

High-sensitivity quantification of AAV neutralization from preclinical model and human sera

FENS Forum 2024

A Neurofilament-L reporter cell line for the quantification of early neuronal differentiation: A bioassay for neurotrophic activities

FENS Forum 2024

Quick & accurate neuron population quantification: An interactive, deep-learning accelerated method for neuron population quantification in mice brains

FENS Forum 2024

Validation of template-based attenuation correction for in vivo quantification of the serotonin transporter using positron emission tomography

FENS Forum 2024

Web-based speech transcription tool for efficient quantification of memory performance

FENS Forum 2024