Biology subjects

Behrens, T.

Publications and source records attributed to Behrens, T..

11 recordsLinked to original sources

bioRxiv2026

A Mechanistic Theory Unifying Value and Schema in the Prefrontal Cortex

Animals exhibit behavioural flexibility by making reward-optimal decisions in unfamiliar situations. Computing value from minimal reward feedback requires leveraging known structure in the world. The Prefrontal Cortex (PFC) plays a pivotal role in both value computation and learning world structure, however mechanistic explanations for each---within the frameworks of Reinforcement Learning and Cognitive Maps---are largely distinct. We develop a mechanistic model of PFC that unifies value and structure through behavioural flexibility. In this model, value acts as a control signal that gates structured working memory representations of the current context in order to ultimately control behaviour. This is a significant departure from the conventional perspective of value, in which it is used for action readout. Critically, this model generalises to novel contexts without the need for additional synaptic plasticity. We demonstrate that recurrent neural networks (RNNs) meta-trained with either reinforcement learning or supervised learning recapitulate this exact model on various value-based tasks. These results not only provide a parsimonious explanation of both the value and schema frameworks of PFC function, but also propose a new mechanistic interpretation of the role of PFC in flexible decision making.

neuroscience↗

bioRxiv2025

Fully Human Stem Cell-Derived BBB Model for Clinical Disease Modeling and Neurotropic AAV selection

The blood-brain barrier (BBB) is a highly functionalized vascular interface which regulates the exchange of substances between the neural parenchyma and its periphery. BBB leakage, leading to its uncontrolled permeability, is increasingly recognized to facilitate the onset of neuropathologies and aggravate their clinical progression. In vitro models of the BBB have rapidly evolved into elaborated structures that mimic its spatial architecture and multicellular nature. However, their cellular components are currently highly heterogeneous in origin and maturation state. Here, we have developed novel procedures to establish reproducible and scalable sources of endothelial, mural and astroglial cells generating a fully human pluripotent stem cell (hPSC)-derived BBB model, termed thBBBA. hPSC-derived BBB cell types are readily assembled into thBBBAs that develop mature functional properties with high barrier impermeability. Mature thBBBAs can also be generated by frozen hPSC-derived cell samples, providing a simple and scalable off-the-shelf system for general use. thBBBAs were instrumental in identifying the critical pathological role of an IL-6 autocrine source in disrupting thBBBA integrity, increasing its permeability to NMDAR antibodies from autoimmune encephalitis patients, and revealing the therapeutic effects of tocilizumab in this setting. Additionally, we have shown that thBBBAs are an invaluable system for ranking the clinical readiness of novel engineered AAV neurotropic capsids, previously selected in animal models or in vitro systems.

neuroscience↗

bioRxiv2025

Development of Replay-DMN Coordination Predicts Entorhinal Grid Codes

Neural replay, the reactivation of experience-related activity patterns during offline periods, has been implicated in organising memories into cognitive maps. However, how replay processes mature through childhood and adolescence remains unclear. Here we studied 106 participants aged 8-25 who learned a hidden two-dimensional (2D) associative structure and then underwent magnetoencephalography (MEG) during a map-based inference task and post-task rest to detect spontaneous replay. We found that during post-task rest, younger individuals relied primarily on replay alone to represent the 2D relationships, whereas older individuals showed increasingly precise timing alignment between replay events and activity in the default mode network (DMN), particularly when replay occurred at the trough of a DMN theta oscillation. Such replay-DMN coupling predicted the strength of a grid-cell-like code in the entorhinal cortex identified in this cohort with fMRI. Furthermore, resting-state fMRI revealed that DMN functional connectivity strengthened with age, in parallel with reduced reliance on replay and more efficient inference performance. These results reveal a developmental progression in which replay shifts from an isolated process in youth to a coordinated DMN mechanism by adulthood. This transition predicts the maturation of grid-like schema representations, shedding light on how children gradually build internal knowledge structures to support flexible inference.

neuroscience↗

bioRxiv2023

A cognitive map for value-guided choice in ventromedial prefrontal cortex

The prefrontal cortex is crucial for economic decision-making and representing the value of options. However, how such representations facilitate flexible decisions remains unknown. We reframe economic decision-making in prefrontal cortex in line with representations of structure within the medial temporal lobe because such cognitive map representations are known to facilitate flexible behaviour. Specifically, we framed choice between different options as a navigation process in value space. Here we show that choices in a 2D value space defined by reward magnitude and probability were represented with a grid-like code, analogous to that found in spatial navigation. The grid-like code was present in ventromedial prefrontal cortex (vmPFC) local field potential theta frequency and the result replicated in an independent dataset. Neurons in vmPFC similarly contained a grid-like code, in addition to encoding the linear value of the chosen option. Importantly, both signals were modulated by theta frequency - occurring at theta troughs but on separate theta cycles. Furthermore, we found sharp-wave ripples - a key neural signature of planning and flexible behaviour - in vmPFC, which were modulated by accuracy and reward. These results demonstrate that multiple cognitive map-like computations are deployed in vmPFC during economic decision-making, suggesting a new framework for the implementation of choice in prefrontal cortex.

neuroscience↗

bioRxiv2023

Replay-triggered Brain-wide Activation in Humans

The consolidation of discrete experiences into a coherent narrative shape our cognitive map, providing a structured mental representation of our experiences. Neural replay, by fostering crucial hippocampal-cortical dialogue, is thought to be pivotal in this process. However, the brain-wide engagement coinciding with replay bursts remains largely unexplored. In this study, by employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of replay. We find that during mental simulation, the strength of on-task replay, as detected via EEG, correlates with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Intriguingly, increased replay strength also enhances the functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing cognitive map. Furthermore, during the post-learning resting state, we observed a positive association between increased task-related reactivation, hippocampal activity, and augmented connectivity to the entorhinal cortex. Our findings elucidate the neural mechanism of human replay in both time and space, providing novel insights into dynamics of replay and associated brain-wide activation.

neuroscience↗

bioRxiv2021

Spatiotemporally Resolved Multivariate Pattern Analysis for M/EEG

An emerging goal in neuroscience is tracking what information is represented in brain activity over time as a participant completes some task. Whilst EEG and MEG offer millisecond temporal resolution of how activity patterns emerge and evolve, standard decoding methods present significant barriers to interpretability as they obscure the underlying spatial and temporal activity patterns. We instead propose the use of a generative encoding model framework that simultaneously infers the multivariate spatial patterns of activity and the variable timing at which these patterns emerge on individual trials. An encoding model inversion allows predictions to be made about unseen test data in the same way as in standard decoding methodology. These SpatioTemporally Resolved MVPA (STRM) models can be flexibly applied to a wide variety of experimental paradigms, including classification and regression tasks. We show that these models provide insightful maps of the activity driving predictive accuracy metrics; demonstrate behaviourally meaningful variation in the timing of pattern emergence on individual trials; and achieve predictive accuracies that are either equivalent or surpass those achieved by more widely used methods. This provides a new avenue for investigating the brains representational dynamics and could ultimately support more flexible experimental designs in future. HIGHLIGHTSO_LIWe introduce SpatioTemporally Resolved MVPA (STRM), an approach that explicitly models how successive stages of stimulus processing are distributed in both space and time in M/EEG data. C_LIO_LIWe show that STRM is broadly applicable to diverse types of M/EEG data and outputs meaningful and interpretable maps of how neural representations evolve in space and time at millisecond resolution. C_LIO_LIThe trial-specific deviations in activity pattern timings identified by STRM are not random, but vary systematically with inter-trial differences in behavioural, cognitive and physiological variables. C_LIO_LIThese methods result in predictive accuracy metrics that are mostly equivalent to, or a modest improvement on, conventional methods. C_LI

neuroscience↗

bioRxiv2021

Generative replay for compositional visual understanding in the prefrontal-hippocampal circuit

Understanding the visual world is a constructive process. Whilst a frontal-hippocampal circuit is known to be essential for this task, little is known about the associated neuronal computations. Visual understanding appears superficially distinct from other known functions of this circuit, such as spatial reasoning and model-based planning, but recent models suggest deeper computational similarities. Here, using fMRI, we show that representations of a simple visual scene in these brain regions are relational and compositional - key computational properties theorised to support rapid construction of hippocampal maps. Using MEG, we show that rapid sequences of representations, akin to replay in spatial navigation and planning problems, are also engaged in visual construction. Whilst these sequences have previously been proposed as mechanisms to plan possible futures or learn from the past, here they are used to understand the present. Replay sequences form constructive hypotheses about possible scene configurations. These hypotheses play out in an optimal order for relational inference, progressing from predictable to uncertain scene elements, gradually constraining possible configurations, and converging on the correct scene configuration. Together, these results suggest a computational bridge between apparently distinct functions of hippocampal-prefrontal circuitry, and a role for generative replay in constructive inference and hypothesis testing.

neuroscience↗

bioRxiv2020

Experience replay supports non-local learning

To make effective decisions we need to consider the relationship between actions and outcomes. They are, however, often separated by time and space. The biological mechanism capable of spanning those gaps remains unknown. One promising, albeit hypothetical, mechanism involves neural replay of non-local experience. Using a novel task, that segregates direct from indirect learning, combined with magnetoencephalography (MEG), we tested the role of neural replay in non-local learning in humans. Following reward receipt, we found significant backward replay of non-local experience, with a 160 msec state-to-state time lag, and this replay facilitated learning of action values. This backward replay, combined with behavioural evidence of non-local learning, was more pronounced in experiences that were of greater benefit for future behavior, as predicted by theories of prioritization. These findings establish rationally targeted non-local replay as a neural mechanism for solving complex credit assignment problems during learning. One Sentence SummaryReverse sequential replay is found, for the first time, to support non-local reinforcement learning in humans and is prioritized according to utility.

neuroscience↗

bioRxiv2017

Strong positive biodiversity-productivity relationships in a subtropical forest experiment

Forest ecosystems contribute substantially to global terrestrial primary productivity and climate regulation, but, in contrast to grasslands, experimental evidence for a positive biodiversity-productivity relationship in highly diverse forests is still lacking1. Here, we provide such evidence from a large forest biodiversity experiment with a novel design2 in subtropical China. Productivity (stand-level tree basal area, aboveground volume and carbon and their annual increment) increased linearly with the logarithm of tree species richness. Additive partitioning3 showed that increasing positive complementarity effects combined with weakening negative selection effects caused a strengthening of the relationship over time. In 2-species mixed stands, complementary effects increased with functional distance and selection effects with vertical crown dissimilarity between species. Understorey shrubs reduced stand-level tree productivity, but this effect of competition was attenuated by shrub species richness, indicating that a diverse understorey may facilitate overall ecosystem functioning. Identical biodiversity-productivity relationships were found in plots of different size, suggesting that extrapolation to larger scales is possible. Our results highlight the potential of multi-species afforestation strategies to simultaneously contribute to mitigation of climate change and biodiversity restoration.

ecology↗

bioRxiv2017

Simultaneous representation of a spectrum of dynamically changing value estimates during decision making

Decisions are based on value expectations derived from experience. We show that dorsal anterior cingulate cortex and three other brain regions hold multiple representations of choice value based on different time-scales of experience organized in terms of systematic gradients across the cortex. Some parts of each area represent value estimates based on recent reward experience while others represent value estimates based on experience over the longer term. The value estimates within these four brain areas interact with one another according to their temporal scaling. Some aspects of the representations change dynamically as the environment changes. The spectrum of value estimates may act as a flexible selection mechanism for combining experience-derived value information with other aspects of value to allow flexible and adaptive decisions in changing environments.

neuroscience↗

bioRxiv2017

Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection

While the impact of common genetic variants on gene expression response to cellular stimuli has been analyzed in depth, less is known about how stimulation modulates the genetic control of isoform usage. Analyzing RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to viral infection and stimulation with type I interferon. We identified more than a thousand single nucleotide polymorphisms associated with isoform usage (isoQTLs), > 40% of which are independent of expression QTLs for the same gene. Compared to eQTLs, isoQTLs are enriched for splice sites and untranslated regions, and depleted of sequences upstream of annotated transcription start sites. Both eQTLs and isoQTLs in stimulated cells explain a significant proportion of the disease heritability attributed to common genetic variants. At the IRF7 locus, we found alternative promoter usage in response to influenza as a possible mechanism by which DNA variants previously associated with immune-related disorders mediate disease risk. At the ERAP2 locus, we shed light on the function of the major haplotype that has been maintained under long-term balancing selection. At baseline and following type 1 interferon stimulation, the major haplotype is associated with absence of ERAP2 expression while the minor haplotype, known to increase Crohns disease risk, is associated with high ERAP2 expression. Surprisingly, in response to influenza infection, the major haplotype results in the expression of two uncharacterized, alternatively transcribed, spliced and translated short isoforms. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in the innate immune response, and in the case of ERAP2, may confer a historical fitness advantage in response to virus.

genomics↗