Biology subjects

Berman, S.

Publications and source records attributed to Berman, S..

8 recordsLinked to original sources

bioRxiv2026

Tasting from memory: reconstructing taste from visual cues in the human brain

Taste guides us toward nourishment and away from harm. Yet when we decide what to eat, taste only exists in memory, evoked by a cue. How the brain retrieves taste memories is almost entirely unknown. If memory re-creates experience, it should reproduce the brain's activation while tasting, even in the absence of taste. We scanned participants while they formed and then retrieved associations between tastes and visual cues. The gustatory cortex was engaged during retrieval and distinguished among remembered tastes, but not using the patterns it had formed while tasting. Patterns persisted instead in lateral parietal cortex, distinguishing individual tastes, not just taste-categories. Activity in the amygdala covaried with this same parietal region and amygdala activity predicted which associations were retained. Taste memory is not simply a re-creation of sensory experience, but a distinct representation, outside the taste system, yet specific enough to guide what we choose to eat.

neuroscience↗

bioRxiv2026

Extending structural surfaceomics to identify aberrant conformations of tumor surface proteins as potential immunotherapy targets

The complement of tumor cell surface proteins, or "surfaceome", is a rich source of potential immunotherapy targets. To move beyond expression-based target discovery, we previously described "structural surfaceomics," combining crosslinking mass spectrometry (XL-MS) with surface protein biotinylation to identify conformation-selective targets. In our prior work, we applied this method to a single model of acute myeloid leukemia (AML), identifying active integrin beta-2 as a promising target. Here, we expand structural surfaceomics to identify additional immunotherapy targets and surface protein biology across additional models of AML, multiple myeloma, and prostate cancer, as well as donor peripheral blood mononuclear cells. Utilizing these models and different chemical crosslinkers, we compile an extensive database of 5,209 crosslinks. We characterize both shared and unique crosslink-based features, identifying 1,612 disease model-specific crosslinks, including 212 potentially defining tumor-specific conformations based on distance constraint violations relative to AlphaFold predictions. We further implement a suite of emerging modeling tools to predict tumor-specific protein structures. We probe crosslinking patterns suggesting multiple myeloma-specific CD48 and AML-specific integrin 1/{beta}4 heterodimer conformations. This work establishes a resource for cancer structural biology by implementation of structural surfaceomics. Our findings also point toward more realistic protein design models, potentially enabling systematic detection of targetable cancer-specific epitopes for next-generation immunotherapies.

cancer biology↗

bioRxiv2025

ABCDscores: An R package for computing summary scores in the ABCD Study(R)

The ABCD Study(R) is the largest longitudinal research study of brain development and child health across the United States. The study generates a rich multimodal dataset, including file-based raw and derivative data and a curated tabulated dataset comprising data from a broad spectrum of research domains. Historically, summary scores in the tabulated dataset were computed using the electronic data capture system REDCap or external scripting solutions. However, this approach was rigid, unreliable, and lacked transparency around how scores were computed. Here, we introduce ABCDscores, an R software package that is used by the study to compute most non-proprietary summary scores included in the tabulated ABCD data resource and allows for customization to meet specific research needs. ABCDscores provides a flexible, open-source solution that uses R for transparent and reproducible scoring. The package is built to apply standard scoring methods across different types of assessments, ensuring consistent and accurate results even with large datasets. By simplifying complex scoring procedures into a user-friendly process, ABCDscores streamlines research workflows, reduces errors, and saves researchers valuable time. The package aims to improve analyses of data from the ABCD Study(R) and can serve as a model for the development of similar tools and a standardized framework for other research studies, fostering new discoveries and innovation in the field.

bioinformatics↗

bioRxiv2023

Robust Adaptive Deep Brain Stimulation Control of Non-Stationary Cortex-Basal Ganglia-Thalamus Network Models in Parkinson's Disease

Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinsons disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering the accurate and robust control of PD neural dynamics using current closed-loop DBS methods. Here, we develop a new robust adaptive closed-loop DBS method for regulating cortex-BG-thalamus network dynamics in PD. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated PD neural state while reducing the systems sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as a testbed to simulate various nonlinear and non-stationary neural dynamics for evaluating DBS methods. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms state-of-the-art on-off and LTI DBS methods. These results have implications for future designs of clinically-viable closed-loop DBS systems to treat PD and other neurological and neuropsychiatric disorders.

neuroscience↗

bioRxiv2021

Myelin contributes to microstructural growth in human sensory cortex during early infancy.

Development of cortical tissue during infancy is critical for the emergence of typical brain functions in cortex. However, how cortical microstructure develops during infancy remains unknown. We measured the longitudinal development of cortex from newborns to six-months-old infants using multimodal quantitative imaging of cortical microstructure. Here we show that infants cortex undergoes profound microstructural tissue growth during the first six months of human life. Comparison of postnatal to prenatal transcriptomic gene expression data demonstrates that myelination and synaptic processes are dominant contributors to this postnatal microstructural tissue growth. Using visual cortex as a model system, we find hierarchical microstructural growth: higher-level visual areas have less mature tissue at birth than earlier visual areas but grow at faster rates. This overturns the prevailing view that visual areas that are most mature at birth develop fastest. Together, in vivo, longitudinal, and quantitative measurements, which we validated with ex vivo transcriptomic data, shed new light on the rate, sequence, and specific biological mechanisms of developing cortical systems. Importantly, our findings propose a new hypothesis that cortical myelination is a key factor in cortical development during early infancy, which has significant implications for diagnosis of neurodevelopmental disorders and delays in infants.

neuroscience↗

bioRxiv2019

Self-reported health behaviors and longitudinal cognitive performance: Results from the Wisconsin Registry for Alzheimer’s Prevention

BackgroundStudies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimers Prevention (WRAP), an Alzheimers disease risk-enriched cohort who were non-demented and in late midlife at baseline.\n\nMethodWe analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multi-domain cognitive composite, and secondary outcomes were immediate/delayed memory and executive function composites. Predictors of interest were self-reported measures of physical activity, cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) model averaging (MA) approach on a set of models including covariates and combinations of these 2- and 3-way interactions. The IT approach was selected due to the large number of interactions of interest and to avoid pitfalls of traditional model selection approaches.\n\nResultsModel-averaged results identified no significant modifiable behavior*age interactions in relationship to the primary composite outcome. In secondary outcomes, higher MIND diet scores associated with slower decline in executive function. Men showed faster decline than women on delayed memory, independent of health behaviors. There were no other significant interactions among any other health behaviors and cognitive trajectories.\n\nConclusionsWhen multiple covariates and health behaviors were considered simultaneously, there were limited weak associations with cognitive decline in this age range. These results may be explained alone or in combination by three alternative explanations: 1) the range of cognitive decline is in middle age is too small to observe relationships with health behaviors, 2) the putative associations of these health behaviors on cognition may not be robust in this age range, or 3) the self-reported measures of the health behaviors may not be optimal for predicting cognitive decline. More study may be needed that incorporates sensitive measures of health behaviors, AD biomarker profiles, and/or other disease comorbidities.

neuroscience↗

bioRxiv2018

Modelling conduction delays in the corpus callosum using MRI-measured g-ratio

Conduction of action potentials along myelinated axons is affected by their structural features, such as the axonal g-ratio, the ratio between the inner and outer diameters of the myelin sheath surrounding the axon. The effect of g-ratio variance on conduction properties has been quantitatively evaluated using single-axon models. It has recently become possible to estimate a g-ratio weighted measurement in vivo using quantitative MRI. Nevertheless, it is still unclear whether the variance in the g-ratio in the healthy human brain leads to significant differences in conduction velocity. In this work we tested whether the g-ratio MRI measurement can be used to predict conduction delays in the corpus callosum. We present a novel framework in which the structural properties of fibers (i.e. length and g-ratio, measured using MRI), are incorporated in a biophysical model of axon conduction, to predict conduction delays of long-range white matter fibers. We applied this framework to the corpus callosum, and found conduction delay estimates that are compatible with previously estimated values of conduction delays. We account for the variance in the velocity given the axon diameter distribution in the splenium, mid-body and genu, to further compare the fibers within the corpus callosum. Conduction delays have been suggested to increase with age. Therefore, we investigated whether there are differences in the g-ratio and the fiber length between young and old adults, and whether this leads to a difference in conduction speed and delays. We found small but significant differences between the predicted delays of the two groups in the motor fibers of the corpus callosum. We also found that the motor fibers of the corpus callosum have the fastest conduction estimates. Using the axon diameter distributions, we found that the occipital fibers have the slowest estimations, while the frontal and motor fiber tracts have similar estimates. Our study provides a framework for predicting conduction latencies in vivo. The framework could have major implications for future studies of white matter diseases and large range network computations. Our results highlight the need for improving additional in vivo measurements of white matter microstructure.

neuroscience↗

bioRxiv2017

Age-accelerated cognitive decline in asymptomatic adults with CSF β-amyloid

ObjectiveCompare cognitive and hippocampal volume (HCV) trajectories in asymptomatic middle-aged and older adults with positive cerebrospinal fluid (CSF) markers of {beta}-amyloid (A{beta}) or tau to adults without an AD-associated biomarker profile.\n\nMethod392 adults enrolled in a longitudinal cohort study (Wisconsin Registry for Alzheimers Prevention or Wisconsin Alzheimers Disease Research Center) completed a lumbar puncture and at least two biennial or annual neuropsychological evaluations. Cutoffs for A{beta}42, total tau, and phosphorylated tau were developed via receiver operating characteristic curve analyses on a sample of 78 participants (38 dementia, 40 controls). These cutoffs were applied to a separate sample of 314 cognitively healthy adults (mean age at CSF collection = 61.5) and mixed-effects regression analyses tested linear and quadratic interactions of biomarker group x age at each visit on cognitive and HCV outcomes.\n\nResults215 participants (69%) were biomarker negative (preclinical AD Stage 0), 46 (15%) were A{beta}+ only (preclinical AD Stage 1), 25 (8%) were A{beta}+ and tau+ (preclinical AD Stage 2), and 28 (9%) were tau+ only. Both Stage 1 and Stage 2 groups exhibited greater rates of linear decline on story memory and processing speed measures, and non-linear decline on list-learning and set-shifting measures compared to Stage 0. The tau+ only group did not significantly differ from Stage 0 in rates of cognitive decline.\n\nConclusionIn an asymptomatic at-risk cohort, elevated CSF A{beta} (with or without elevated tau) was associated with greater rates of cognitive decline, with the specific pattern of decline varying across cognitive measures.

neuroscience↗