Biology subjects

Madsen, K. H.

Publications and source records attributed to Madsen, K. H..

17 recordsLinked to original sources

bioRxiv2026

Age-Related Differences in Bimanual Coordination Are Associated with Increased Cerebellar Activity and Reduced Frontal Recruitment

Bimanual coordination declines in late adulthood, but the neural mechanisms underlying these changes remain unclear. Age-related differences in brain activity have been interpreted either as compensatory recruitment of frontal cognitive control regions or as a shift toward feedback-based control, supported by sensory and cerebellar processing systems. To investigate these hypotheses, we examined brain activity, using fMRI in twenty-three younger and twenty-three older adults performing a bimanual visuomotor pinch-force task with different task complexities. Behaviourally, older adults showed lower accuracy than younger adults, particularly when task demands increased. Neuroimaging results revealed general age-dependent increases in activity within posterior cerebellar lobules VI-VII, regions overlapping with the classical oculomotor vermis and implicated in visuomotor adaptation, movement calibration, and error-based motor learning. In addition, during the more demanding task condition, older adults showed a greater increase in activation of anterior cerebellar lobules IV-V and a decrease in activation of the medial frontal pole (BA10). No consistent age-related increases or decreases in task related activation was observed in parieto-frontal regions. Moreover, better task performance across age groups was associated with lower activation in frontal cognitive control regions, including the superior medial frontal gyrus and right inferior frontal gyrus. Together, these results suggest increased feedback- and error-related sensorimotor processing in older adults involving the cerebellum and frontal cortex.

neuroscience↗

bioRxiv2025

Blunted response of caudal locus coeruleus to arousing stimuli in Parkinson's Disease

Parkinsons disease (PD) causes progressive degeneration of noradrenergic neurons in the locus coeruleus (LC), contributing to non-motor symptoms. Using neuromelanin-sensitive ultra-high field (7T) MRI, we previously identified a reduction in neuromelanin signal in the caudal LC, indicating a rostro-caudal gradient of noradrenergic cell loss. Caudal LC degeneration was associated with greater severity of non-motor symptoms such as orthostatic hypotension and apathy. In the current study, we expanded the PD cohort to further validate the structure-symptom relationships within the LC and investigate how degeneration along the rostro-caudal LC axis affects arousal-related functional responsivity. To this end, 71 people with PD in the ON-medication state and 40 age- and sex-matched healthy controls underwent clinical assessments and 7T magnetization transfer-weighted (MTw) MRI to quantify structural changes along the rostro-caudal LC axis. A subgroup of 30 people with PD and 27 controls underwent 7T fMRI to assess LC responsivity to arousing auditory and visual stimuli in two fMRI sessions on separate days. Healthy controls were scanned twice without medication, while people with PD were studied on and off dopaminergic medication in counterbalanced order. In the PD group, MTw MRI confirmed a significant reduction of the regional neuromelanin signal in caudal LC relative to the control group (P = 0.0099). This structural disintegration correlated with orthostatic hypotension (P = 0.0087) and cognitive impairment (P = 0.036), corroborating its clinical relevance. Functional MRI revealed reduced activation of the caudal LC to arousing visual and auditory stimuli in people with PD relative to controls (P = 0.012). This difference reached statistical significance only in the ON-medication state, with a similar but non-significant trend in the OFF-medication state (P = 0.10). In an exploratory analysis of a smaller sub-sample, structural and functional caudal LC signals were significantly correlated in both people with PD and healthy controls (P = 0.0069). Together, the findings provide evidence for a rostro-caudal gradient of LC pathology in PD at both structural and functional levels. While structural MRI provides fine-grained insights into spatial gradients of disease-related pathology, functional MRI captures impaired functional responsivity of caudal LC. The presence of arousal-induced hypoactivation of caudal LC in the ON-medication state indicates that LC dysfunction extends beyond dopamine deficits in PD, highlighting complex interactions between dopaminergic and noradrenergic systems.

neuroscience↗

bioRxiv2025

Using magnetoencephalography to track the propagation of 40 Hz invisible spectral flicker

Brain stimulation with novel 40 Hz invisible spectral flicker (ISF) has been proposed as a therapy for Alzheimers disease, with leading hypotheses suggesting local promotion of glymphatic clearance of amyloid as the mechanism of action. Neural signals in the gamma range and their spatial propagation over the brain can be tracked using magnetoencephalography (MEG) with high temporal and good spatial detail. However, stimulation with 40 Hz ISF requires specialised hardware which causes electromagnetic interference (EMI) with MEG equipment. MEG measures the tiny magnetic fields of the brain, which are easily distorted by external magnetic fields. Using MEG to track the propagation of 40 Hz ISF requires multiple modifications to the experimental setup. These include, at least 1) an experimental design that promotes modulation of the neural signal, but not the artifact, 2) removal of all electronics not strictly necessary for light production from the stimulators, and 3) signal processing for 40 Hz EMI artifact suppression. Here, we present an MEG study on the cortical propagation of 40 Hz ISF. In two experiments, we investigate the modulation that visual and non-visual cognitive tasks have on the power and propagation of cortical activity induced by 40 Hz ISF. With the chosen experimental setup and design, the 40 Hz EMI artifact could not be entirely disentangled from the neural signal of interest, thus rendering inference on the spatial propagation of the 40 Hz signal impossible. Further improvements need to be implemented in a follow-up experimental design. We present potential solutions to allow for future investigation of 40 Hz ISF with MEG.

neuroscience↗

bioRxiv2024

Personalized electric field simulations of deformable large TMS coils based on automatic position and shape optimization

BackgroundTranscranial Magnetic Stimulation (TMS) therapies use both focal and unfocal coil designs. Unfocal designs often employ bendable windings and moveable parts, making realistic simulations of their electric fields in inter-individually varying head sizes and shapes challenging. This hampers comparisons of the various coil designs and prevents systematic evaluations of their dose-response relationships. ObjectiveIntroduce and validate a novel method for optimizing the position and shape of flexible coils taking individual head anatomies into account. Evaluate the impact of realistic modeling of flexible coils on the electric field simulated in the brain. MethodsAccurate models of four coils (Brainsway H1, H4, H7; MagVenture MST-Twin) were derived from computed tomography data and mechanical measurements. A generic representation of coil deformations by concatenated linear transformations was introduced and validated. This served as basis for a principled approach to optimize the coil positions and shapes, and to optionally maximize the electric field strength in a region of interest (ROI). ResultsFor all four coil models, the new method achieved configurations that followed the scalp anatomy while robustly preventing coil-scalp intersections on N=1100 head models. In contrast, setting only the coil center positions without shape deformation regularly led to physically impossible configurations. This also affected the electric field calculated in the cortex, with a median peak difference of [~]16%. In addition, the new method outperformed grid search-based optimization for maximizing the electric field of a standard figure 8 coil in a ROI with a comparable computational complexity. ConclusionOur approach alleviates practical hurdles that so far hampered accurate simulations of bendable coils. This enables systematic comparison of dose-response relationships across the various coil designs employed in therapy. HighlightsO_LIautomatic positioning and shape optimization of large deformable TMS coils C_LIO_LIensures adherence to the head anatomy and prevents coil-head intersections C_LIO_LIenable automatic electric field maximization in target brain regions C_LIO_LIoutperforms grid search for standard flat coils C_LIO_LIprovides accurate computational models of four coils used in clinical practice C_LI

neuroscience↗

bioRxiv2024

A Leadfield-Free Optimization Framework for Transcranially Applied Electric Currents

BackgroundTranscranial Electrical Stimulation (TES), Temporal Interference Stimulation (TIS), Electroconvulsive Therapy (ECT) and Tumor Treating Fields (TTFields) are based on the application of electric current patterns to the brain. ObjectiveThe optimal electrode positions, shapes and alignments for generating a desired current pattern in the brain vary between persons due to anatomical variability. The aim is to develop a flexible and efficient computational approach to determine individually optimal montages based on electric field simulations. MethodsWe propose a leadfield-free optimization framework that allows the electrodes to be placed freely on the head surface. It is designed for the optimization of montages with a low to moderate number of spatially extended electrodes or electrode arrays. Spatial overlaps are systematically prevented during optimization, enabling arbitrary electrode shapes and configurations. The approach supports maximizing the field intensity in target region-of-interests (ROI) and optimizing for a desired focality-intensity tradeoff. ResultsWe demonstrate montage optimization for standard two-electrode TES, focal center-surround TES, TIS, ECT and TTFields. Comparisons against reference simulations are used to validate the performance of the algorithm. The system requirements are kept moderate, allowing the optimization to run on regular notebooks and promoting its use in basic and clinical research. Conclusion(s)The new framework complements existing optimization methods that require small electrodes, a predetermined discretization of the electrode positions on the scalp and work best for multi-channel systems. It strongly extends the possibilities to optimize electrode montages towards application-specific aims and supports researchers in discovering innovative stimulation schemes. The framework is available in SimNIBS.

neuroscience↗

bioRxiv2024

Fast FEM-based Electric Field Calculations for Transcranial Magnetic Stimulation

ObjectiveTo provide a Finite-Element Method (FEM) for rapid, repeated evaluations of the electric field induced by transcranial magnetic stimulation (TMS) in the brain for changing coil positions. ApproachPreviously, we introduced a first-order tetrahedral FEM enhanced by super- convergent patch recovery (SPR), striking a good balance between computational efficiency and accuracy (Saturnino et al 2019 J. Neural Eng. 16 066032). In this study, we refined the method to accommodate repeated simulations with varying TMS coil position. Starting from a fast direct solver, streamlining the pre- and SPR-based post-calculation steps using weight matrices computed during initialization strongly improved the computational efficiency. Additional speedups were achieved through efficient multi-core and GPU acceleration, alongside the optimization of the volume conductor model of the head for TMS. Main ResultsFor an anatomically detailed head model with [~]4.4 million tetrahedra, the optimized implementation achieves update rates above 1 Hz for electric field calculations in bilateral gray matter, resulting in a 60-fold speedup over the previous method with identical accuracy. An optimized model without neck and with adaptive spatial resolution scaled in dependence to the distance to brain grey matter, resulting in [~]1.9 million tetrahedra, increased update rates up to 10 Hz, with [~]3% numerical error and [~]4% deviation from the standard model. Region-of-interest (ROI) optimized models focused on the left motor, premotor and dorsolateral prefrontal cortices reached update rates over 20 Hz, maintaining a difference of <4% from standard results. Our approach allows efficient switching between coil types and ROI during runtime which greatly enhances the flexibility. SignificanceThe optimized FEM enhances speed, accuracy and flexibility and benefits various applications. This includes the planning and optimization of coil positions, pre-calculation and training procedures for real-time electric field simulations based on surrogate models as well as targeting and dose control during neuronavigated TMS.

neuroscience↗

bioRxiv2023

Exploring an EM-algorithm for banded regression in computational neuroscience

Regression is a principal tool for relating brain responses to stimuli or tasks in computational neuroscience. This often involves fitting linear models with predictors that can be divided into groups, such as distinct stimulus feature subsets in encoding models or features of different neural response channels in decoding models. When fitting such models, it can be relevant to allow differential shrinkage of the different groups of regression weights. Here, we explore a framework that allow for straightforward definition and estimation of such models. We present an expectation-maximization algorithm for tuning hyperparameters that control shrinkage of groups of weights. We highlight properties, limitations, and potential use-cases of the model using simulated data. Next, we explore the model in the context of a BOLD fMRI encoding analysis and an EEG decoding analysis. Finally, we discuss cases where the model can be useful and scenarios where regularization procedures complicate model interpretation.

neuroscience↗

bioRxiv2022

Dynamic involvement of premotor and supplementary motor areas in bimanual pinch force control

Many bimanual activities of daily living require quick shifts between symmetric and asymmetric motor output generated by the right and left hand. Bimanual motor control has been mostly studied during continuous repetitive tasks, while little research has been carried out in experimental settings requiring dynamic changes in motor output generated by both hands. Here, we performed functional magnetic resonance imaging (MRI) while healthy volunteers performed a visually guided, bimanual pinch force task. This enabled us to map functional activity and connectivity of premotor and motor areas during bimanual pinch force control in different task contexts, requiring mirror-symmetric or inverse-asymmetric changes in discrete pinch force exerted with the right and left hand. The bilateral dorsal premotor cortex showed increased activity and effective coupling to the ipsilateral supplementary motor area (SMA) in the inverse-asymmetric context compared to the mirror-symmetric context of bimanual pitch force control. Compared to unilateral pinches, all bimanual pinch force conditions were characterized by an increased level of activation in the bilateral primary motor hand area (M1-HAND) and stronger coupling from SMA to the ipsilateral M1-HAND. Task-related activity of a cluster in the left caudal SMA scaled positively with the degree of synchronous initiation of bilateral pinch force adjustments, irrespectively of the task context. The results suggest that the dorsal premotor cortex mediates increasing complexity of bimanual coordination by increasing coupling to the SMA-M1 network.

neuroscience↗

bioRxiv2022

Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning

As a gateway for projections entering and exiting the cerebral cortex, the human thalamus processes information from sensory to cognition relevant to various neuropsychiatric disorders. It is composed of dozens of nuclei, which have been difficult to identify with clinical MR sequences. However, delineating thalamic nuclei accurately at an individual level is essential for precise neuromodulation treatment. Here, we not only identified the fine-grained thalamic nuclei using local diffusion properties in vivo but also employed a deep learning strategy to achieve highly reproducible individual-level parcellation. Using High-quality diffusion MRI (dMRI), we first constructed a fine-grained group thalamus atlas based on thalamic local diffusion features. Then, the high-probability core area of the group thalamus atlas was wrapped into the native space as prior guidance for individualized thalamus construction. Finally, we trained the semi-supervised multiple classification models to accurately construct the individualized thalamus atlas with single-subject local diffusion characteristics. Compared to group atlas registration and single-subject clustering strategies, our individualized thalamus atlas combines population commonality and individual specificity and is superior in depicting the individual thalamic nuclei boundaries. Besides, our atlas provides a more conspicuous capacity to capture the individual specificity of thalamic nuclei. Through the evaluation by 3.0T\7.0T and test-retest dMRI datasets, the proposed high-probability group prior guided individualized thalamus construction pipeline is robust and repeatable in different magnetic field strengths and scanning batches. In addition, the individual parcellation of the thalamic nuclei has a good correspondence with the histological atlas and captured both higher group consistency and inter-subjects variations, which could be a valuable solution for precision clinical treatment.

neuroscience↗

bioRxiv2021

Uncovering the Genetic Profiles Underlying the Intrinsic Organization of the Human Cerebellum

The functional diversity of the human cerebellum is largely believed to be derived more from its extensive connections rather than being limited to its mostly invariant architecture. However, whether and how the determination of cerebellar connections in its intrinsic organization interact with microscale gene expression is still unknown. Here we decode the genetic profiles of the cerebellar functional organization by investigating the genetic substrates simultaneously linking cerebellar functional heterogeneity and its drivers, i.e., the connections. We not only identified 443 network-specific genes but also discovered that their co-expression pattern correlated strongly with intra-cerebellar functional connectivity (FC). Ninety of these genes were also linked to the FC of cortico-cerebellar cognitive-limbic networks. To further discover the biological functions of these genes, we performed a "virtual gene knock-out" by observing the change in the coupling between gene co-expression and FC and divided the genes into two subsets, i.e., a positive gene contribution indicator (GCI+) involved in cerebellar neurodevelopment and a negative gene set (GCI-) related to neurotransmission. A more interesting finding is that GCI- is significantly linked with the cerebellar connectivity-behavior association and many recognized brain diseases that are closely linked with the cerebellar functional abnormalities. Our results could collectively help to rethink the genetic substrates underlying the cerebellar functional organization and offer possible micro-macro interacted mechanistic interpretations of the cerebellum-involved high order functions and dysfunctions in neuropsychiatric disorders.

neuroscience↗

bioRxiv2020

Does pericentral mu-rhythm power corticomotor excitability? A matter of EEG perspective

BackgroundElectroencephalography (EEG) and single-pulse transcranial magnetic stimulation (spTMS) of the primary motor hand area (M1-HAND) have been combined to explore whether the instantaneous expression of pericentral mu-rhythm drives fluctuations in corticomotor excitability, but this line of research has yielded diverging results. ObjectivesTo re-assess the relationship between the mu-rhythm power expressed in left pericentral cortex and the amplitude of motor potentials (MEP) evoked with spTMS in left M1-HAND. Methods15 non-preselected healthy young participants received spTMS to the motor hot spot of left M1-HAND. Regional expression of mu-rhythm was estimated online based on a radial source at motor hotspot and informed the timing of spTMS which was applied either during epochs belonging to the highest or lowest quartile of regionally expressed mu-power. Using MEP amplitude as dependent variable, we computed a linear mixed-effects model, which included mu-power and mu-phase at the time of stimulation and the inter-stimulus interval (ISI) as fixed effects and subject as a random effect. Mu-phase was estimated by post-hoc sorting of trials into four discrete phase bins. We performed a follow-up analysis on the same EEG-triggered MEP data set in which we isolated mu-power at the sensor level using a Laplacian montage centered on the electrode above the M1-HAND. ResultsPericentral mu-power traced as radial source at motor hot spot did not significantly modulate the MEP, but mu-power determined by the surface Laplacian did, showing a positive relation between mu-power and MEP amplitude. In neither case, there was an effect of mu-phase on MEP amplitude. ConclusionThe relationship between cortical oscillatory activity and cortical excitability is complex and minor differences in the methodological choices may critically affect sensitivity.

neuroscience↗

bioRxiv2020

Optimizing the Electric Field Strength in Multiple Targets for Multichannel Transcranial Electric Stimulation

ObjectiveMost approaches to optimize the electric field pattern generated by multichannel Transcranial Electric Stimulation (TES) require the definition of a preferred direction of the electric field in the target region(s). However, this requires knowledge about how the neural effects depend on the field direction, which is not always available. Thus, it can be preferential to optimize the field strength in the target(s), irrespective of the field direction. However, this results in a more complex optimization problem. ApproachWe introduce and validate a novel optimization algorithm that maximizes focality while controlling the electric field strength in the target to maintain a defined value. It obeys the safety constraints, allows limiting the number of active electrodes and allows also for multi-target optimization. Main ResultsThe optimization algorithm outperformed naive search approaches in both quality of the solution and computational efficiency. Using the amygdala as test case, we show that it allows for reaching a reasonable trade-off between focality and field strength in the target. In contrast, simply maximizing the field strength in the target results in far more extended fields. In addition, by maintaining the pre-defined field strengths in the targets, the new algorithm allows for a balanced stimulation of two or more regions. SignificanceThe novel algorithm can be used to automatically obtain individualized, optimal montages for targeting regions without the need to define preferential directions. It will automatically select the field direction that achieves the desired field strength in the target(s) with the most focal stimulation pattern.

bioengineering↗

bioRxiv2020

Multimodal finger-printing of the human precentral cortex forming the motor hand knob

Transcranial magnetic stimulation (TMS) of the precentral hand knob can evoke motor evoked potentials (MEP) in contralateral hand muscles. Biophysical modelling points to the dorsal premotor cortex (PMd) in the superficial crown-lip region as primary site of TMS-induced neuronal excitation. Here, we used a sulcus-aligned MRI-informed TMS mapping approach to determine the optimal site (hotspot) for evoking MEPs in the precentral hand knob. Individual precentral hotspot location varied along the rostro-caudal axis. Individuals with a more rostral location had longer MEP latencies. Spatiotemporal "hotspot rostrality" was associated with higher precentral myelin-related signals, stronger movement-related activation of PMd in the precentral crown, and higher temporal precision during paced finger tapping. Together, our multimodal mapping approach provides first-time evidence for behaviourally relevant, structural and functional phenotypic variation in the crown of human precentral motor hand knob. The results have important implications for physiological and interventional TMS studies targeting the precentral hand knob.

neuroscience↗

bioRxiv2019

Comparing and Validating Automated Tools for Individualized Electric Field Simulations in the Human Head

Comparing electric field simulations from individualized head models against in-vivo recordings is important for direct validation of computational field modeling for transcranial brain stimulation and brain mapping techniques such as electro- and magnetoencephalography. This also helps to improve simulation accuracy by pinning down the factors having the largest influence on the simulations. Here we compare field simulations from four different automated pipelines, against intracranial voltage recordings in an existing dataset of 14 epilepsy patients. We show that ignoring uncertainty in the simulations leads to a strong bias in the estimated linear relationship between simulated and measured fields. In addition, even though the simulations between the pipelines differ notably, this is not reflected in the correlation with the measurements. We discuss potential reasons for this apparent mismatch and propose a new Bayesian regression analysis of the data that yields unbiased estimates enabling robust conclusions to be reached.

bioengineering↗

bioRxiv2019

Efficient Electric Field Simulations for Transcranial Brain Stimulation

ObjectiveTranscranial magnetic stimulation (TMS) and transcranial electric stimulation (TES) modulate brain activity non-invasively by generating electric fields either by electromagnetic induction or by injecting currents via skin electrodes. Numerical simulations based on anatomically detailed head models of the TMS and TES electric fields can help us to understand and optimize the spatial stimulation pattern in the brain. However, most realistic simulations are still slow, and their numerical accuracy and the factors that influence it have not been evaluated in detail so far. ApproachWe present and validate a new implementation of the Finite Element Method (FEM) for TMS and TES that is based on modern algorithms and libraries. We also evaluate the convergence of the simulations and give estimates for the discretization errors. Main resultsComparisons with analytical solutions for spherical head models validate our new FEM implementation. It is five to ten times faster than previous implementations. The convergence results suggest that accurately capturing the tissue geometry in addition to choosing a sufficiently high mesh density is of fundamental importance for accurate simulations. SignificanceThe new implementation allows for a substantial increase in computational efficiency of TMS and TES simulations. This is especially relevant for applications such as the systematic assessment of model uncertainty and the optimization of multi-electrode TES montages. The results of our systematic error analysis allow the user to select the best tradeoff between model resolution and simulation speed for a specific application. The new FEM code will be made openly available as a part of our open-source software SimNIBS 3.0.

bioengineering↗

bioRxiv2019

No trace of phase: Corticomotor excitability is not tuned by phase of pericentral mu-rhythm

BackgroundThe motor potentials evoked by transcranial magnetic stimulation (TMS) over the motor hand area (M1-HAND) show substantial inter-trial variability. Pericentral mu-rhythm oscillations, might contribute to inter-trial variability. Recent studies targeting mu-activity based on real-time electroencephalography (EEG) reported an influence of mu-power and mu-phase on the amplitude of motor evoked potentials (MEPs) in a preselected group with strong pericentral mu-activity. Other studies that determined mu-power or mu-phase based on post-hoc trial sorting according in non-preselected individuals were largely negative.\n\nObjectivesTo reassess if cortico-spinal activity is modulated by the mu-rhythm, we applied single-pulse TMS to the M1-HAND conditional on the phase of the intrinsically expressed pericentral mu-rhythm in 14 non-preselected healthy young participants.\n\nMethodsTMS was given at 0, 90, 180, and 270 degrees of the mu-phase. Based on the absence of effects of mu-phase or mu-power when analyzing the mean MEP amplitudes, we also computed a linear mixed effects model, which included mu-phase, mu-power, inter-stimulus interval (ISIs) as fixed effects, treating the subject factor as a random effect.\n\nResultsMixed model analysis revealed a significant effect of mu-power and ISI, but no effect of mu-phase and no interactions. MEP amplitude scaled linearly with lower mu-power or longer ISIs, but these modulatory effects were very small relative to inter-trial MEP variability.\n\nConclusionOur largely negative results are in agreement with previous offline TMS-EEG studies and point to a possible influence of ISI. Future research needs to clarify under which circumstances the responsiveness of human the M1-HAND to TMS depends on the synchronicity with mu-power and mu-phase.\n\nHighlightsO_LIPhase-triggered TMS at four distinct phases of the ongoing mu-oscillations is technically feasible in non-preselected young volunteers\nC_LIO_LITargeting the ongoing mu-activity did not reveal consistent modulatory effect of mu-phase on corticospinal excitability in a non-preselected group\nC_LIO_LIMixed-effects analysis revealed a weak but significant effect of pre-stimulus mu-power and ISI on corticospinal excitability\nC_LI

neuroscience↗

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↗