Biology subjects

Koch, E. M.

Publications and source records attributed to Koch, E. M..

7 recordsLinked to original sources

bioRxiv2026

Brain dynamics supporting high cognitive performance reorganize after midlife

Quantifying functional brain aging trajectories at scale remains a fundamental challenge due to the scanner-bound limitations of traditional neuroimaging. Here, we deploy whole-head Time-Domain functional Near-Infrared Spectroscopy (TD-fNIRS) to map task-evoked cortical dynamics during a 30-minute cognitive battery across the adult lifespan (N = 302, age 18-87, 45% racial or ethnic minority). We developed a robust General Cognitive Factor (GCF) tracking age-related performance decline (r = -0.57, p < 0.0001). Analysis of brain activity patterns revealed systemic, age-dependent neural dedifferentiation, highlighting a distinct neurocognitive inflection point around age 55. Prior to this threshold, high performers exhibit more variable neural activation across tasks; post-age 55, high performance is sustained through reduced spatial differentiation, signaling a compensatory strategy. Furthermore, subjective anxiety and depression disrupt these compensatory mechanisms, and subjective cognitive complaints register as distinct neural signatures before behavioral GCF decline manifests. Together, these findings establish a scalable framework for mapping functional brain health across the human lifespan, uncovering the neural mechanics of cognitive resilience and vulnerability before behavioral decline manifests.

neuroscience↗

bioRxiv2024

Genetic association data are broadly consistent with stabilizing selection shaping human common diseases and traits

Results from genome-wide association studies (GWAS) enable inferences about the balance of evolutionary forces maintaining genetic variation underlying common diseases and other genetically complex traits. Natural selection is a major force shaping variation, and understanding it is necessary to explain the genetic architecture and prevalence of heritable diseases. Here, we analyze data for 27 traits, including anthropometric traits, metabolic traits, and binary diseases--both early-onset and post-reproductive. We develop an inference framework to test existing population genetics models based on the joint distribution of allelic effect sizes and frequencies of trait-associated variants. A majority of traits have GWAS results that are inconsistent with neutral evolution or long-term directional selection (selection against a trait or against disease risk). Instead, we find that most traits show consistency with stabilizing selection, which acts to preserve an intermediate trait value or disease risk. Our observations also suggest that selection may reflect pleiotropy, with each variant influenced by associations with multiple selected traits.

genomics↗

bioRxiv2024

Time-Domain Diffuse Optical Tomography for Precision Neuroscience

AbstractRecent years have witnessed a rise in research utilizing neuroimaging for precision neuromedicine, but clinical translation has been hindered by scalability and cost. Time Domain functional Near Infrared Spectroscopy (TD-fNIRS), the gold standard of optical neuroimaging techniques, offers a unique opportunity in this domain since it provides superior depth sensitivity and enables resolution of absolute properties unlike its continuous wave counterparts. However, current TD systems have limited commercial availability, slow sampling rates, and sparse head coverage. Our team has overcome the technical challenges involved in developing a whole-head time-domain diffuse optical tomography (TD-DOT) system. Here, we present the system characterization results using standardized protocols and compare them to the state-of-the-art. Furthermore, we showcase the system performance in retrieving cortical activation maps during standard hemodynamic, sensory, and motor tasks. A combination of the system performance, signal quality, and ease-of-use can enable future studies aimed at investigating TD-DOT clinical applications.

bioengineering↗

bioRxiv2024

Reliability of brain metrics derived from a Time-Domain Functional Near-Infrared Spectroscopy System

With the growing interest in establishing brain-based biomarkers for precision medicine, there is a need for noninvasive, scalable neuroimaging devices that yield valid and reliable metrics. Kernels second-generation Flow2 Time-Domain Functional Near-Infrared Spectroscopy (TD-fNIRS) system meets the requirements of noninvasive and scalable neuroimaging, and uses a validated modality to measure brain function. In this work, we investigate the test-retest reliability (TRR) of a set of metrics derived from the Flow2 recordings. We adopted a repeated-measures design with 49 healthy participants, and quantified TRR over multiple time points and different headsets--in different experimental conditions including a resting state, a sensory, and a cognitive task. Results demonstrated high reliability in resting state features including hemoglobin concentrations, head tissue light attenuation, amplitude of low frequency fluctuations, and functional connectivity. Additionally, passive auditory and Go/No-Go inhibitory control tasks each exhibited similar activation patterns across days. Notably, areas with the highest reliability were in auditory regions during the auditory task, and right prefrontal regions during the Go/No-Go task, consistent with prior literature. This study underscores the reliability of Flow2-derived metrics, supporting its potential to actualize the vision of using brain-based biomarkers for diagnosis, treatment selection and treatment monitoring of neuropsychiatric and neurocognitive disorders.

neuroscience↗

bioRxiv2023

Change in brain asymmetry reflects level of acute alcohol intoxication and impacts on inhibitory control

Alcohol is one of the most commonly used substances and frequently abused, yet little is known about the neural underpinnings driving variability in inhibitory control performance after ingesting alcohol. This study was a single-blind, placebo-controlled, randomized design with participants (N=48) completing three study visits. At each visit participants received one of three alcohol doses; namely, a placebo dose (equivalent Blood Alcohol Concentration (BAC) = 0.00%), a low dose of alcohol (target BAC=0.04%), or a moderate dose of alcohol (target BAC=0.08%). To measure inhibitory control, participants completed a Go/No-go task paradigm twice during each study visit, once immediately before dosing and once after, while their brain activity was measured with time-domain functional near-infrared spectroscopy (TD-fNIRS). BAC and subjective effects of alcohol were also assessed. We report decreased behavioral performance for the moderate dose of alcohol, but not the low or placebo doses. We observed right lateralized inhibitory prefrontal activity during go-no-go blocks, consistent with prior literature. Using standard and novel metrics of lateralization, we were able to significantly differentiate between all doses. Lastly, we demonstrate that these metrics are not only related to behavioral performance during inhibitory control, but also provide complementary information to the legal gold standard of intoxication (i.e. BAC).

neuroscience↗

bioRxiv2022

A mutation rate model at the basepair resolution identifies the mutagenic effect of Polymerase III transcription

De novo mutations occur with substantially different rates depending on genomic location, sequence context and DNA strand1-4. The success of many human genetics techniques, especially when applied to large population sequencing datasets with numerous recurrent mutations5-7, depends strongly on assumptions about the local mutation rate. Such techniques include estimation of selection intensity8, inference of demographic history9, and mapping of rare disease genes10. Here, we present Roulette, a genome-wide mutation rate model at the basepair resolution that incorporates known determinants of local mutation rate (http://genetics.bwh.harvard.edu/downloads/Vova/Roulette/). Roulette is shown to be more accurate than existing models1,6. Roulette has sufficient resolution at high mutation rate sites to model allele frequencies under recurrent mutation. We use Roulette to refine estimates of population growth within Europe by incorporating the full range of human mutation rates. The analysis of significant deviations from the model predictions revealed a 10-fold increase in mutation rate in nearly all genes transcribed by Polymerase III, suggesting a new mutagenic mechanism. We also detected an elevated mutation rate within transcription factor binding sites restricted to sites actively utilized in testis and residing in promoters.

genetics↗

bioRxiv2019

Population-specific causal disease effect sizes in functionally important regions impacted by selection

Many diseases and complex traits exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We developed a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and applied S-LDXR to genome-wide association summary statistics for 31 diseases and complex traits in East Asians (EAS) and Europeans (EUR) (average NEAS=90K, NEUR=267K) with an average trans-ethnic genetic correlation of 0.85 (s.e. 0.01). We determined that squared trans-ethnic genetic correlation was 0.82x (s.e. 0.01) smaller than the genome-wide average at SNPs in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes were more population-specific in functionally important regions, including conserved and regulatory regions. In analyses of regions surrounding specifically expressed genes, causal effect sizes were most population-specific for skin and immune genes and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.

genetics↗