Biology subjects

Tingley, D.

Publications and source records attributed to Tingley, D..

7 recordsLinked to original sources

bioRxiv2026

Schrodinger's mouse: human observation erases a drug-induced behavioral phenotype

Animal studies primarily rely on human monitoring for health and behavioral outcomes. The presence of a human, however, can induce stress and potentially alter experimental results. We sought to answer whether human observation alone is enough to change experimental outcomes and obscure the effect of interest. Our automated home-cage behavioral phenotyping system provided the ideal platform to test this hypothesis. Two cohorts received semaglutide (0.03 mg/kg, intraperitoneally) on separate consecutive days. The first cohort was recorded without inspection after dosing; the second underwent a brief visual health check with no handling. Recordings from the checked cohort on the preceding day, without injection or inspection, provided a matched baseline. A single brief check produced large, time-locked changes across the behavioral repertoire. The changes began before the cage door was opened, indicating a response to experimenter proximity. In addition to adding variance, the semaglutide-treated animals' behavior during observation was more similar to the no-injection baseline than to the semaglutide/no-check reference, transiently erasing the drug phenotype. Brief human observation is therefore not a neutral measurement operation; over the minutes surrounding it, it is a perturbation in itself that is large enough to mask the drug effect it is meant to record.

animal behavior and cognition↗

bioRxiv2026

A foundational in vivo platform for predicting human health outcomes

Rodents remain the workhorse of preclinical drug development, yet often fail to predict human clinical outcomes. Existing alternatives are similarly constrained. Cells in culture cannot recapitulate whole-organism physiology, and larger mammals cannot be studied at comparable throughput. Here we present a scalable, information-dense platform that can predict a drugs long-term human clinical outcomes from 24 hours of rodent behavior. A novel home-cage system continuously records behavior, generating thousands of features per hour. Models are trained on human clinical trial data to map these features onto outcomes including gastrointestinal adverse events, cardiac toxicity, neuropsychiatric side effects, and long-term weight loss. In addition to being an order of magnitude faster, the platform provides more accurate clinical predictions than standard long-term preclinical experiments. The approach readily extends to other outcomes, enabling rodents to serve as quantitative models for human clinical prediction.

pharmacology and toxicology↗

bioRxiv2025

Sex differences in GLP-1 signaling across species

Two billion humans are currently overweight or obese1. While glucagon-like peptide 1 receptor (GLP1R) agonists have emerged as the most promising treatment for this epidemic, side effects including nausea and vomiting constitute a significant obstacle to their use. Of the patients currently being treated, women represent nearly 70%. While early studies have noted sex differences in the response to these drugs, the nature of these differences remain poorly characterized. Using real world electronic medical record (EMR) data, we find that women experience more than double the rates of persistent nausea and vomiting when prescribed GLP1R agonists. To investigate this sex difference in greater detail, we developed novel, species-specific in vivo phenomic assays to quantify aversive behaviors. In both mice and rats, aversive responses to either semaglutide or tirzepatide were greater in females than males. To investigate the basis for this difference, we constructed a mouse single cell transcriptomic atlas of body and brain regions most relevant to the action of GLP-1. Using this atlas we find that multiple neuronal cell types involved in the processing of aversive stimuli and nausea had higher GLP1R expression in females than males. Heightened susceptibility of females to the aversive effects of GLP1R agonists could therefore involve increased activation of these brain circuits. Finally, we demonstrate that in mice, both the efficacy and tolerability of GLP1R agonists vary with the phase of the estrous cycle, being highest during proestrus (when estrogen levels peak) and lowest in diestrus (low estrogen levels). Similarly, we report that higher circulating estrogen levels in humans is associated with heightened risk of nausea and vomiting among women taking a GLP1R agonist. Based on these findings, we anticipate that women will continue to be disproportionately impacted by the adverse effects associated with all members of this drug class. Research to better understand and ultimately mitigate this heightened susceptibility is an important priority for new drug development in this area, and novel approaches to model the impact of endogenous hormone signaling will be critical to developing better treatments for more people.

systems biology↗

bioRxiv2025

Simultaneous, real-time tracking of many neuromodulatory signals with Multiplexed Optical Recording of Sensors on a micro-Endoscope

Dozens of extracellular molecules jointly impact a given neuron, yet we lack methods to simultaneously record many such signals in real time. We developed a probe to track ten or more neuropeptides and neuromodulators using spatial multiplexing of genetically encoded fluorescent sensors. Cultured cells expressing one sensor at a time are immobilized at the front of a gradient refractive index (GRIN) lens for 3D two-photon imaging in vitro and in vivo. The sensor identity and detection sensitivity of each cell are determined via robotic dipping of the probe into wells containing various ligands and concentrations. Using this probe, we detected stimulation-evoked release of multiple neuromodulators in acute brain slices. We also tracked endogenous and drug-evoked changes in cerebrospinal fluid composition in the awake mouse lateral ventricle, which triggered downstream activation of the choroid plexus epithelium. Our approach offers a first step towards quantitative, real-time, high-dimensional tracking of brain fluid composition.

neuroscience↗

bioRxiv2023

Investigating egocentric tuning in hippocampal CA1 neurons using simulated data

Navigation requires integrating sensory information with a stable schema to create a dynamic map of an animals position using egocentric and allocentric coordinate systems. In the hippocampus, place cells encode allocentric space, but their firing rates may also exhibit directional tuning within egocentric or allocentric reference frames. We compared experimental and simulated data to assess the prevalence of tuning to egocentric bearing (EB) among hippocampal cells in rats foraging in an open field. Using established procedures, we confirmed egocentric modulation of place cell activity in recorded data; however, simulated data revealed a high false positive rate. When we accounted for false positives by comparing with shuffled data that retain correlations between the animals direction and position, only a very low number of hippocampal neurons appeared modulated by EB. Our study highlights biases affecting false positive rates and provides insights into the challenges of identifying egocentric modulation in hippocampal neurons.

neuroscience↗

bioRxiv2019

Position-theta-phase model of hippocampal place cell activity applied to quantification of running speed modulation of firing rate

Spiking activity of place cells in the hippocampus encodes the animals position as it moves through an environment. Within a cells place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position-theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time and condition, generates realistic place cell simulation data, and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields, and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.\n\nSignificanceThe hippocampus is heavily studied in the context of spatial navigation, and the format of spatial information in hippocampus is multifaceted and complex. Furthermore, the hippocampus is also thought to contain information about other important aspects of behavior such as running speed, though there is not agreement on the nature and magnitude of their effect. To understand how all of these variables are simultaneously represented and used to guide behavior, a theoretical framework is needed that can be directly applied to the data we record. We present a model that captures well-established spatial-encoding features of hippocampal activity and provides the opportunity to identify and incorporate novel features for our collective understanding.

neuroscience↗

bioRxiv2019

Routing of non-mnemonic hippocampal ripples to subcortical structures

The mnemonic functions of hippocampal sharp wave ripples (SPW-Rs) have been studied extensively. Because hippocampal outputs affect not only downsteam cortical structures but also subcortical targets, we examined the impact of SPW-Rs on the firing patterns of lateral septal (LS) neurons in behaving rats. A large fraction of SPW-Rs were temporally locked to high frequency oscillations (HFOs; 120-180 Hz) in LS. SPW-R to LS HFOs coupling was strongest during NREM sleep, followed by waking immobility. However, coherence and spike-LFP coupling between the two events were low, suggesting that HFOs are generated locally within the LS GABAergic population. This hypothesis was supported by optogenetic induction of HFOs in LS. Spiking of LS neurons was independent from the sequential order of spiking in SPW-Rs but, instead, correlated strongly with the magnitude of excitatory synchrony of the hippocampal output. Thus, LS is strongly activated by SPW-Rs and may convey hippocampal population events to its motivation and action-inducing targets in the hypothalamus and brainstem.

neuroscience↗