Biology subjects

Anderson, N. L.

Publications and source records attributed to Anderson, N. L..

7 recordsLinked to original sources

bioRxiv2025

Targeting intracranial electrical stimulation to network regions defined within individuals causes network-level effects

Intracranial electrical stimulation (ES) is routinely used therapeutically, diagnostically, and to provide causal evidence in neuroscience studies. However, our understanding of the brain network-level effects of ES remains limited. We applied precision functional mapping (PFM), based on functional magnetic resonance imaging (fMRI), to define large-scale networks within individual epilepsy patients. We show that single-pulse electrical stimulation (SPES) and high-frequency electrical stimulation (HFES) are more likely to evoke within-network responses and elicit network-related behavioral effects, respectively, when applied near to a PFM-defined network region. Network-level effects were more likely when stimulating sites in white matter, in close proximity to the targeted network, and within a region predominantly occupied by the targeted network. Further, network-specific modulation may be achievable by applying lower current intensities at these sites. Our findings support that modulation of specific networks is achievable by targeting ES to a functional anatomic "sweet spot" that can be identified using PFM.

neuroscience↗

bioRxiv2025

Suppression of PP2A-B56α Drives EMT in EGFR Mutant Non-Small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related deaths in the United States and [~]50% of these patients present with metastatic disease at diagnosis. Epithelial-to-Mesenchymal Transition (EMT) is an important initiating step in the metastatic cascade that allows cells to acquire the migratory and invasive phenotypes necessary for dissemination. The transcriptional reprogramming that takes place during EMT has been well described in multiple cancer types; however, the posttranslational regulatory mechanisms that govern EMT are poorly understood. Protein Phosphatase 2A (PP2A) is serine/threonine (ser/thr) phosphatase that accounts for 50% of cellular ser/thr phosphatase activity and is critically important in regulating signaling homeostasis. PP2A dysregulation has been implicated in cell state regulation, EMT, and metastasis, but the roles of individual PP2A complexes are poorly understood. Our data indicate that suppression of the specific PP2A complex, PP2A-B56, results in decreased expression of epithelial markers and increased expression of mesenchymal markers consistent with EMT. These molecular changes are associated with migratory and invasive phenotypes both in vitro and in vivo. Furthermore, these migratory phenotypes can be rescued with B56 overexpression. Together, these findings implicate B56 as a key regulator of cellular plasticity and highlight the dynamic nature by which PP2A-B56 posttranslationally regulates NSCLC EMT.

cancer biology↗

bioRxiv2025

Distinct distributed brain networks dissociate self-generated mental states

Human cognition relies on two modes: a perceptually-coupled mode where mental states are driven by sensory input and a perceptually-decoupled mode featuring self-generated mental content. Past work suggests that imagined states are supported by the reinstatement of activity in sensory cortex, but transmodal systems within the canonical default network are also implicated in mind-wandering, recollection, and imagining the future. We identified brain systems supporting self-generated states using precision fMRI. Participants imagined different scenarios in the scanner, then rated their mental states on several properties using multi-dimensional experience sampling. We found that thinking involving scenes evoked activity within or near the default network, while imagining speech evoked activity within or near the language network. Imagining-related regions overlapped with activity evoked by viewing scenes or listening to speech, respectively; however, this overlap was predominantly within transmodal association networks, rather than adjacent unimodal sensory networks. The results suggest that different association networks support imagined states that are high in visual or auditory vividness. TeaserDifferent large-scale brain networks support imagining of visual and audiolinguistic mental content.

neuroscience↗

bioRxiv2024

Intrinsic functional connectivity delineates transmodal language functions

Communication involves the translation of sensory information (e.g., heard words) into abstract concepts according to abstract rules (e.g., the meaning of those words). Accordingly, using language involves an interplay between unimodal brain areas that process sensory information and transmodal areas that respond to linguistic input regardless of the input modality (e.g., reading sentences vs. listening to speech). Previous work has shown that intrinsic functional connectivity (iFC), when performed within individuals, can delineate a distributed language network that overlaps in detail with regions activated by a reading task. The network was widely distributed across multiple brain regions, recapitulating an organization that is characteristic of association cortex, and which suggests that the distributed language network serves transmodal, not unimodal, functions. Here, we tested whether the distributed language network encapsulates transmodal functions by assessing its degree of overlap with two language tasks, one auditory (i.e., listening to speech) and one visual (i.e., reading sentences). The results show that the distributed language network aligns well with regions activated by both tasks, supporting a transmodal function. Further, the boundaries of the distributed language network along the lateral temporal cortex serve as a good proxy for the division between transmodal language and auditory functions: presentation of sounds (i.e., filtered, incomprehensible speech) evoked activity that was largely outside of the distributed language network but closely followed the network boundaries. These findings support that individualized iFC estimates can delineate the division between sensory-linked and abstract linguistic functions. We conclude that within-individual iFC may be viable for language mapping in individuals with aphasia who cannot perform language tasks in the scanner.

neuroscience↗

bioRxiv2023

Predicting the subjective intensity of imagined sensory experiences from electrophysiological measures of oscillatory brain activity.

Most people can conjure images and sounds that they experience in their minds. There are, however, marked individual differences. Some people report that they cannot generate imagined sensory experiences at all (aphantasics) and others report that they have unusually intense imagined experiences (hyper-phantasics). These individual differences have been linked to activity in sensory brain regions, driven by feedback. We would therefore expect imagined experiences to be associated with specific frequencies of oscillatory brain activity, as these can be a hallmark of neural interactions within and across regions of the brain. Replicating a number of other studies, relative to meditation we find that the act of engaging in imagining auditory or visual sensations is linked to reductions in the power of oscillatory brain activity across a broad range of frequencies, with prominent peaks in the alpha band (8-12 Hz). This oscillatory activity, however, did not predict individual differences in the subjective intensity of imagined experiences. For imagined audio experiences, these were rather predicted by reductions within the theta (6 - 9 Hz) and gamma (33 - 38 Hz) bands, and by increases in beta (15 - 17Hz) band activity. For imagined visual experiences these were predicted by reductions in lower (14 - 16Hz) and upper (29 - 32 Hz) beta band activity, and by an increase in mid-beta band (24 - 26 Hz) activity. Our data suggest that there is sufficient ground truth to the subjective reports that people use to describe the intensity of their imagined sensory experiences such that these can be predicted by the power of distinct rhythms of brain activity.

neuroscience↗

bioRxiv2022

A comprehensive single cell data analysis of in lymphoblastoid cells reveals the role of Super-enhancers in maintaining EBV latency

We probed the lifecycle of EBV on a cell-by-cell basis using single cell RNA sequencing (scRNA-seq) data from nine publicly available lymphoblastoid cell lines (LCL). While the majority of LCLs comprised cells containing EBV in the latent phase, two other clusters of cells were clearly evident and were distinguished by distinct expression of host and viral genes. Notably, both were high expressors of EBV LMP1/BNLF2 and BZLF1 compared to another cluster that expressed neither gene. The two novel clusters differed from each other in their expression of EBV lytic genes, including glycoprotein gene GP350. The first cluster, comprising GP350-LMP1hi cells, expressed high levels of HIF1A and was transcriptionally regulated by HIF1-. Treatment of LCLs with Pevonedistat, a drug that enhances HIF1- signaling, markedly induced this cluster. The second cluster, containing GP350+LMP1hi cells, expressed EBV lytic genes. Host genes that are controlled by super-enhancers (SEs), such as transcription factors MYC and IRF4, had the lowest expression in this cluster. Functionally, the expression of genes regulated by MYC and IRF4 in GP350+LMP1hi cells were lower compared to other cells. Indeed, induction of EBV lytic reactivation in EBV+ AKATA reduced the expression of these SE-regulated genes. Furthermore, CRISPR-mediated perturbation of the MYC or IRF4 SEs in LCLs induced the lytic EBV gene expression, suggesting that host SEs and/or SE target genes are required for maintenance of EBV latency. Collectively, our study revealed EBV associated heterogeneity among LCLs that may have functional consequence on host and viral biology. ImportanceEpstein-Barr virus (EBV) establishes a life-long latency program within host cells. As such, EBV immortalized lymphoblastoid cells (LCLs) often carry the latent EBV genome and only a small percentage of LCLs containing lytic EBV. However, the cellular programs that distinguish latent from lytic cells and the heterogeneity of cells in latent or lytic phases remains poorly explored. To explore these unknowns, we reanalyzed publicly available single cell RNA-seq data from nine LCLs. This approach permitted the simultaneous study of cells in both latent and lytic phases. We identified three cell populations with distinct lytic/latent activity and further characterized the transcriptomes of these cells. We also identified a new role of super-enhancers in regulating EBV lytic replication. Collectively, our studies revealed EBV associated heterogeneity among LCLs that contribute to EBV life cycle and biology.

microbiology↗

bioRxiv2019

Multiplexed measurement of protein biomarkers in high-frequency longitudinal dried blood spot (DBS) samples: characterization of inflammatory responses

A detailed understanding of changes in blood protein biomarkers occuring in individuals over time would enable truly personalized approaches to health and disease monitoring. Such measurements could reveal smaller, earlier departures from normal baseline levels of biomarkers thus allowing better disease detection and treatment monitoring. Current practice, however, generally involves infrequent, sporadic biomarker testing, and this undersampling likely fails to capture important biological phenomena. Here we report the use of a robust multiplex immuno-mass spectrometric method (SISCAPA) to measure a panel of clinically-relevant proteins in a unique collection of 1,522 dried blood spots collected longitudinally by 8 individuals over periods of up to 9 years, with daily sampling during some intervals. Analytical workflow CVs of 2-6% for most assays were achieved by normalizing DBS plasma volume using a set of 3 minimally varying proteins, facilitating temporal analysis of both high- and low-amplitude biomarker changes compared to personalized baselines. The biomarkers included a panel of 9 positive and 5 negative acute phase response (inflammatory) proteins, allowing longitudinal analysis of inflammation markers associated with major and minor infections, influenza vaccination, recovery from hip-replacement surgery and Crohns disease. The results illustrate complex time-dependent \"biomarker trajectories\" on multiple timescales and provide a basis for detailed personalized models of inflammation dynamics. The striking stability of most biomarker protein levels over time, combined with the convenience of self-sampling and low cost of multiplexed measurements using mass spectrometry, provide a new window into the temporal dynamics of disease processes. The extensive results obtained using this high throughput approach offer a new source of precision biomarker big data amenable to machine learning approaches and application to more personalized health monitoring.

systems biology↗