Biology subjects

Saxe, R.

Publications and source records attributed to Saxe, R..

14 recordsLinked to original sources

bioRxiv2026

Mapping breast cancer lineage in radiation and immunotherapy using the REMAP mouse

We present REMAP (Recording Evolution in Mammary tumors via Active PyMT), a lineage-tracing mouse model that integrates inducible CRISPR recording with the MMTV-PyMT model of hormone receptor-positive (HR+) breast cancer. Inducible Cas9 drives editing of MARC1 homing guide RNAs (hgRNAs), generating heritable lineage marks, and enables reconstruction of clonal relationships. Using REMAP, we profiled tumor evolution and response to radiation combined with anti-PD1 immunotherapy. Treatment reduced tumor burden locally and systemically, and single-cell RNA sequencing revealed remodeling of the tumor microenvironment (TME). We identified metastatic clones present across primary tumors and distant sites, which exhibited elevated epithelial-mesenchymal transition (EMT) programs as a heritable clonal state. Treatment reduced EMT-associated transcriptional programs and reshaped immune composition, with radiation driving clonal expansion of T cells and reduced repertoire diversity. In contrast, cancer-associated fibroblast clones spanned multiple transcriptional states, indicating substantial stromal plasticity. Together, REMAP enables high-resolution coupling of clonal history and cellular state in vivo, revealing that tumor progression, metastasis, and therapeutic response are governed by heritable lineage programs.

cancer biology↗

bioRxiv2026

The emergence of the language system in the toddler brain

Toddlerhood is a time when childrens language competence undergoes a dramatic transformation, making it a key period to examine the emergence of the brains language system. Functional magnetic resonance imaging data from 29 awake toddlers (19-36 months) scanned on a child-friendly language task reveal that, already at this young age, areas in the left frontal and temporal cortex respond more to comprehensible language (i.e., videos of puppets speaking in English) than the control condition (matched videos with incomprehensible audio). Although the magnitude of response to language is substantially weaker than in adults, the topography is already adult-like, challenging claims that the frontal component or left-hemispheric dominance do not emerge until later in life.

neuroscience↗

bioRxiv2025

The cortical scene processing network emerges in infancy, prior to independent navigation experience

Sighted people rely on vision to recognize and navigate the local environment. By adulthood, human cortex contains at least three regions that respond selectively to visual scene information, but it remains unknown when or how these regions develop. One hypothesis is that scene selectivity emerges gradually in regions that initially prefer certain low-level visual features (e.g., peripheral visual input, high spatial frequencies, rectilinearity), and then exposure to the visual statistics of natural scenes drives the emergence of scene selective responses. However, both aspects of this hypothesis remain to be tested: how early scene selectivity first arises in human development, and whether it is driven by passive exposure to visual statistics. We therefore collected functional magnetic resonance imaging data from awake 2-9-month-old infants while they watched videos of real-world scenes with ego-motion, as well as faces, objects, and scrambled videos. We found stronger responses to scenes than control conditions in the location of all three scene regions. Scene-selective responses could not be explained by low-level visual properties of the stimuli, and were found in infants as young as 2-5 months old, with no evidence of age-related change. We also measured infants experience independently navigating (e.g., crawling), which was not necessary for the development of scene-selectivity. In sum, cortical regions are scene-selective in human infants prior to independent navigation, and after only limited exposure to visual scene statistics. Significance statementDespite extensive work on the functional organization of scene processing in the human adult visual cortex, little is known about the developmental origins of category selectivity for visual scenes. Here we used fMRI in awake human infants to discover that all three regions of the known visual scene processing system are present within the first few months of life - the youngest age yet detected. Scene-selective cortex therefore develops after only a few months of limited visual exposure, and prior to active experience using visual scene information to plan and guide independent navigation (e.g., by crawling). These findings provide a fundamental constraint on theories of how scene selectivity develops in high-level visual cortex.

neuroscience↗

bioRxiv2025

Hierarchical Lineage Tracing Reveals Diverse Pathways of AML Treatment Resistance

Cancer cells adapt to treatment, leading to the emergence of clones that are more aggressive and resistant to anti-cancer therapies. We have a limited understanding of the development of treatment resistance as we lack technologies to map the evolution of cancer under the selective pressure of treatment. To address this, we developed a hierarchical, dynamic lineage tracing method called FLARE (Following Lineage Adaptation and Resistance Evolution). We use this technique to track the progression of acute myeloid leukemia (AML) cell lines through exposure to Cytarabine (AraC), a front-line treatment in AML, in vitro and in vivo. We map distinct cellular lineages in murine and human AML cell lines predisposed to AraC persistence and/or resistance via the upregulation of cell adhesion and motility pathways. Additionally, we highlight the heritable expression of immunoproteasome 11S regulatory cap subunits as a potential mechanism aiding AML cell survival, proliferation, and immune escape in vivo. Finally, we validate the clinical relevance of these signatures in the TARGET-AML cohort, with a bisected response in blood and bone marrow. Our findings reveal a broad spectrum of resistance signatures attributed to significant cell transcriptional changes. To our knowledge, this is the first application of dynamic lineage tracing to unravel treatment response and resistance in cancer, and we expect FLARE to be a valuable tool in dissecting the evolution of resistance in a wide range of tumor types.

cancer biology↗

bioRxiv2025

Data retention in awake infant fMRI: Lessons from more than 750 scanning sessions

Functional magnetic resonance imaging (fMRI) in awake infants has the potential to reveal how the early developing brain gives rise to cognition and behavior. However, awake infant fMRI poses significant methodological challenges that have hampered wider adoption. The present work takes stock after the collection of a substantial amount of awake infant fMRI data across multiple studies from two labs at different institutions. These data were leveraged to glean insights on participant recruitment, experimental design, and data acquisition that could be useful to consider for future studies. Across 766 fMRI sessions with awake infants aged 1-36 months, the authors explored the factors that influenced how much usable data were obtained per session. The age of an infant predicted whether they would successfully enter the scanner (younger more likely) and, if they did enter, the number of minutes of functional data collected (linear, younger more) and retained after preprocessing with lab-specific protocols or harmonized motion exclusion thresholds (quadratic, 12-24 months more than younger and older). The amount of functional data retained was also influenced by assigned sex (female more), experimental paradigm (movies better than blocks and events), and stimulus content (social better than abstract). There were many differences in the research approach between labs making head-to-head comparisons difficult, but Yale was more likely to get infants into the scanner, MIT collected more data from infants who entered, and the amount of data retained after preprocessing did not differ statistically between labs (9 minutes). In addition, the authors assessed the value of attempting to collect multiple experiments per session, an approach that yielded more than one usable experiment averaging across all sessions. Although any given scan is unpredictable, these findings support the feasibility of awake infant fMRI and suggest practices to optimize future research.

neuroscience↗

bioRxiv2024

A stimulus-computable rational model of habituation in infants and adults

How do we decide what to look at and when to stop looking? Even very young infants engage in active visual selection, looking less and less as stimuli are repeated (habituation) and regaining interest when novel stimuli are subsequently introduced (dishabituation). The mechanisms underlying these looking time changes remain uncertain, however, due to limits on both the scope of existing formal models and the empirical precision of measurements of infant behavior. To address this, we developed the Rational Action, Noisy Choice for Habituation (RANCH) model, which operates over raw images and makes quantitative predictions of participants looking behaviors in a classic visual habituation paradigm. In a series of pre-registered experiments, we exposed infants and adults to stimuli for varying durations and measured looking time to familiar and novel stimuli. We found that these data were well captured by RANCH. Using RANCHs stimulus-computability, we also tested its out-of-sample predictions about the magnitude of dishabituation in a new experiment in which we manipulated the similarity between the familiar and novel stimulus. By framing looking behaviors as rational decision-making, this work identified how the dynamics of learning and exploration guide our visual attention from infancy through adulthood.

animal behavior and cognition↗

bioRxiv2024

Precision fMRI reveals that the language network exhibits adult-like left-hemispheric lateralization by 4 years of age

In adults, left hemisphere (LH) damage often leads to aphasia, but many cases of early damage leave linguistic processing intact, with a functional language system developing in the right hemisphere. To explain this early apparent equipotentiality of the two hemispheres for language, some have proposed that the language system is more bilateral during early development and becomes increasingly left-lateralized with age. We examined language lateralization using fMRI in two large developmental cohorts (total n=273 children aged 4-16 years; n=107 adults). Strong, adult-like LH lateralization (in response magnitude and activation volume) was evident by age 4, although other features of the LH language network showed protracted development, including the magnitude of language response and the strength of functional connectivity. Thus, although the RH can take over language function in some cases of early brain damage, this plasticity occurs in spite of adult-level LH bias present by age 4 years.

neuroscience↗

bioRxiv2024

Representation of navigational affordances and ego-motion in the occipital place area

Humans effortlessly use vision to plan and guide navigation through the local environment, or "scene". A network of three cortical regions responds selectively to visual scene information, including the occipital (OPA), parahippocampal (PPA), and medial place areas (MPA) - but how this network supports visually-guided navigation is unclear. Recent evidence suggests that one region in particular, the OPA, supports visual representations for navigation, while PPA and MPA support other aspects of scene processing. However, most previous studies tested only static scene images, which lack the dynamic experience of navigating through scenes. We used dynamic movie stimuli to test whether OPA, PPA, and MPA represent two critical kinds of navigationally-relevant information: navigational affordances (e.g., can I walk to the left, right, or both?) and ego-motion (e.g., am I walking forward or backward? turning left or right?). We found that OPA is sensitive to both affordances and ego-motion, as well as the conflict between these cues - e.g., turning toward versus away from an open doorway. These effects were significantly weaker or absent in PPA and MPA. Responses in OPA were also dissociable from those in early visual cortex, consistent with the idea that OPA responses are not merely explained by lower-level visual features. OPA responses to affordances and ego-motion were stronger in the contralateral than ipsilateral visual field, suggesting that OPA encodes navigationally relevant information within an egocentric reference frame. Taken together, these results support the hypothesis that OPA contains visual representations that are useful for planning and guiding navigation through scenes.

neuroscience↗

bioRxiv2023

Left-hemisphere cortical language regions respond equally to dialogue and monologue

Much of the language we encounter in our everyday lives comes in the form of conversation, yet the majority of research on the neural basis of language comprehension has used input from only one speaker at a time. 20 adults were scanned while passively observing audiovisual conversations using functional magnetic resonance imaging. In a block-design task, participants watched 20-second videos of puppets speaking either to another puppet (the "dialogue" condition) or directly to the viewer ("monologue"), while the audio was either comprehensible (played forward) or incomprehensible (played backward). Individually functionally-localized left-hemisphere language regions responded more to comprehensible than incomprehensible speech but did not respond differently to dialogue than monologue. In a second task, participants watched videos (1-3 minutes each) of two puppets conversing with each other, in which one puppet was comprehensible while the others speech was reversed. All participants saw the same visual input but were randomly assigned which characters speech was comprehensible. In left-hemisphere cortical language regions, the timecourse of activity was correlated only among participants who heard the same character speaking comprehensibly, despite identical visual input across all participants. For comparison, some individually-localized theory of mind regions and right hemisphere homologues of language regions responded more to dialogue than monologue in the first task, and in the second task, activity in some regions was correlated across all participants regardless of which character was speaking comprehensibly. Together, these results suggest that canonical left-hemisphere cortical language regions are not sensitive to differences between observed dialogue and monologue.

neuroscience↗

bioRxiv2021

Face-Selective Responses Present in Multiple Regions of the Human Infant Brain

In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher level social functions. When in development does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance neuroimaging (fMRI) datasets to create a sample size twice the size of previous reports (n=65 infants, 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activations maps revealed a significant response to faces compared to non-face visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest (fROI) analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development. Significance StatementSocial cognition often begins with face perception. In adults, several cortical regions respond robustly to faces, yet little is known about when and how these regions first arise in development. To test whether face selectivity changes in the first year of life, we combined two datasets, doubling the sample size relative to previous reports. In the approximate location of the fusiform face area (FFA), superior temporal sulcus (STS), and medial prefrontal cortex (MPFC) but not occipital face area (OFA), face selectivity was present in the youngest group. These findings demonstrate that face-selective responses are present across multiple lobes of the brain very early in life.

neuroscience↗

bioRxiv2021

Using child-friendly movie stimuli to study the development of face, place, and object regions from age 3 to 12 years

Scanning young children while watching short, engaging, commercially-produced movies has emerged as a promising approach for increasing data retention and quality. Movie stimuli also evoke a richer variety of cognitive processes than traditional experiments - allowing the study of multiple aspects of brain development simultaneously. However, because these stimuli are uncontrolled, it is unclear how effectively distinct profiles of brain activity can be distinguished from the resulting data. Here we develop an approach for identifying multiple distinct subject-specific Regions of Interest (ssROIs) using fMRI data collected during movie-viewing. We focused on the test case of higher-level visual regions selective for faces, scenes, and objects. Adults (N=13) were scanned while viewing a 5.5 minute child-friendly movie, as well as a traditional experiment with isolated faces, scenes, and objects. We found that just 2.7 minutes of movie data could identify subject-specific face, scene, and object regions. While successful, the movie approach was still less effective than a traditional localizer. Having validated our approach in adults, we then used the same methods on movie data collected from 3-12-year-old children (N=122). Movie response timecourses in 3-year-old childrens face, scene, and object regions were already significantly and specifically predicted by timecourses from the corresponding regions in adults. We also found evidence of continued developmental change, particularly in the face-selective posterior superior temporal sulcus. Taken together, our results reveal both early maturity and functional change in face, scene, and object regions, and more broadly highlight the promise of short, child-friendly movies for developmental cognitive neuroscience.

neuroscience↗

bioRxiv2020

The need to connect: Acute social isolation causes neural craving responses similar to hunger.

When people are forced to be isolated from one another, do they crave social interactions? To address this question, we used functional magnetic resonance imaging (fMRI) to measure neural responses evoked by food and social cues after participants (n=40) experienced ten hours of mandated fasting or total social isolation. After isolation, people felt lonely and craved social interaction. Midbrain regions showed selective activation to food cues after fasting and to social cues after isolation; these responses were correlated with self-reported craving. By contrast, striatal and cortical regions differentiated between craving food versus social interaction. Across deprivation sessions, we find that deprivation narrows and focuses the brains motivational responses to the deprived target. Our results support the intuitive idea that acute isolation causes social craving, similar to the way fasting causes hunger.

neuroscience↗

bioRxiv2018

Intersubject MVPD: Empirical Comparison of fMRI Denoising Methods for Connectivity Analysis

Noise is a major challenge for the analysis of fMRI data in general and for connectivity analyses in particular. As researchers develop increasingly sophisticated tools to model statistical dependence between the fMRI signal in different brain regions, there is a risk that these models may increasingly capture artifactual relationships between regions, that are the result of noise. Thus, choosing optimal denoising methods is a crucial step to maximize the accuracy and reproducibility of connectivity models. Most comparisons between denoising methods require knowledge of the ground truth: of what is the real signal. For this reason, they are usually based on simulated fMRI data. However, simulated data may not match the statistical properties of real data, limiting the generalizability of the conclusions. In this article, we propose an approach to evaluate denoising methods using real (non-simulated) fMRI data. First, we introduce an intersubject version of multivariate pattern dependence (iMVPD) that computes the statistical dependence between a brain region in one participant, and another brain region in a different participant. iMVPD has the following advantages: 1) it is multivariate, 2) it trains and tests models on independent folds of the real fMRI data, and 3) it generates predictions that are both between subjects and between regions. Since whole-brain sources of noise are more strongly correlated within subject than between subjects, we can use the difference between standard MVPD and iMVPD as a discrepancy metric to evaluate denoising techniques (where more effective techniques should yield smaller differences). As predicted, the difference is the greatest in the absence of denoising methods. Furthermore, a combination of removal of the global signal and CompCorr optimizes denoising (among the set of denoising options tested).

neuroscience↗

bioRxiv2016

Measuring and Modeling Transformations of Information Between Brain Regions with fMRI

In the study of connectivity in large-scale networks of brain regions, a standard assumption is made that the statistical dependence between regions is univariate and linear. However, brain regions encode information in multivariate responses, and neural computations are nonlinear. Multivariate and nonlinear statistical dependence between regions is likely ubiquitous, but it is not captured by current methods. To fill this gap, we introduce a novel analysis framework: fMRI responses are characterized as points in multidimensional spaces, and nonlinear dependence is modeled using artificial neural networks. Converging evidence from multiple experiments shows that nonlinear dependence 1) models mappings between brain regions more accurately than linear dependence, explaining more variance in left-out data; 2) reveals functional subdivisions within cortical networks, and 3) is modulated by the task participants are performing.

neuroscience↗