Biology subjects

Lak, A.

Publications and source records attributed to Lak, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Magnetic molecular nanorulers enable combinatorial biosensing and determine distances at the molecular level

Molecular nanorulers are essential tools for mapping intramolecular distances and studying nucleic acid and protein interactions. Here, we present MARs (MAgnetic molecular nanoRulers), a fundamentally new class of nanorulers based on measuring the magnetization dynamics of rationally engineered and ultra-responsive colloidal magnetic nanoparticles with magnetic particle spectrometry (MPS). By tuning the grafting density of DNA receptors on MARs, we reveal surface molecular crowding as a simple, yet programmable parameter to tune the response of MARs over a broad range of target DNA concentrations. We show that MARs can distinguish target binding positions along receptor strands by regulating how much the binding effect is translated into the response. Combining their switchable binding-to-response and DNA hairpins, we show that MARs can resolve the full combinatorial space of four short DNA targets (24-1) in a one-design-for-all fashion, with blind assays achieving 80% best-prediction accuracy. By modelling MPS response of MARs using the Fokker-Planck equation, we demonstrate that their response is well predictable. Using biotinylated DNA constructs and calibrating their lengths for different numbers of base pair, we reveal that MARs can determine the distance between bound monostreptavidin and their surface with a dynamic distance range of up to 13 nm and a resolution of 1.3 {+/-} 0.2 nm. Our study establishes a new class of molecular nanorulers for resolving conformational changes in nucleic acids and measuring distances at the molecular level in free solution via an adaptable, simple, and rapid workflow, making MARs highly promising for high throughput screening assays.

biophysics↗

bioRxiv2026

Mind the gap between functional groups and surface of magnetic nanoparticles for highly specific magnetic-based protein assays in biological medium

Magnetic readout-based assays are compatible with unprocessed biological samples as unbound background molecules do not interfere with magnetic signal. Yet, a true challenge is their poor specificity and susceptibility of magnetic nanoparticles (MNPs) to clusters in complex biological media, hampering their true advancement. Here, we demonstrate that the spatial organization of functional groups at the external periphery of custom magnetic nanoparticles by harnessing ultra-dense double-stranded DNA results in an efficient antibody conjugation with good accessibility toward antigen. By labeling our MNPs with anti-S protein neutralizing IgG antibody, we showcase the detection of S1 subunit of SARS-CoV-2 Spike protein in a wash-free fashion in less than five minutes in nM regime using magnetic particle spectrometer. By mixing our IgG-labelled MNPs with DMEM cell culture (10-20% FBS serum), we sense the S1 proteins in a one-pot fashion with high specificity. Our results show that by having the ultra-dense dsDNA shell on MNPs, the entropic cost of an irreversible protein binding to particle surface is high, thus allowing the formation of dynamic protein corona on the DNA shell that can be replaced with S1 protein with high affinity. When the azide moieties are placed at the close proximity of MNPs by using non-functional dsDNA, antibody conjugation becomes inefficient, to a level not sufficient for S1 protein detection. Our study highlights the importance of spatial organization of functional moieties on the nanoscale on magnetic nanoparticles for highly specific assays in biologically complex media.

biochemistry↗

bioRxiv2026

Magnetic DNA Origami Nanorotors

Self-assembled DNA nanostructures show great promise as functional devices, highly configurable materials, and in nanorobotics. Magnetic control can provide a powerful actuation mechanism in a broad range of contexts, since it affords a high-level of external control, it is biocompatible, and orthogonal to chemical or electrical stimuli. Here we demonstrate magnetic molecular nanoactuators by leveraging the unique site-specificity of DNA origami to assemble highly anisotropic magnetic nanocubes on high-aspect ratio DNA origami bundles. We traced and controlled 100s of our DNA origami nanorotors at the single-rotor level and demonstrated their programmable magnetic clamping and controlled rotation under uniform and rotating magnetic fields. By varying the population and inter-particle spacing of the nanocubes, magnetic torque values in the order of 10-100 pN nm are achieved at field strengths < 10 mT. Monte Carlo simulations reveal that assembly of nanocubes on DNA origami rotors leads to collective magnetic properties, with numerically estimated torque values in good agreement with the experiments. Our magnetic nanorotors offer a foundation for biocompatible nanorobotics, as well as high-throughput magnetic force and torque tweezers.

biophysics↗

bioRxiv2026

Dorsal striatal dopamine integrates sensory and reward prediction errors to guide perceptual decisions

Perceptual decisions are shaped by expectations about sensory stimuli and rewards, learned through sensory and reward prediction errors. Dopamine is known to convey reward prediction errors that shape perceptual decisions. However, whether dopamine also signals sensory prediction errors during perceptual decision-making remains unknown. We recorded dopamine release in the dorsal striatum of mice performing a visual decision-making task while manipulating sensory and reward expectations. The two manipulations produced similar behavioral biases but elicited opposite dopamine signals, indicating that dopamine within the same striatal region encoded both sensory and reward prediction errors. Sensory prediction error signaling was specific to dopamine as striatal acetylcholine showed no such error signals. Optogenetically stimulating striatal dopamine at stimulus onset biased subsequent perceptual decisions, consistent with updating sensory expectations. A computational model learning from both sensory and reward prediction errors captured behavioral biases and dopamine data, revealing distinct but spatially overlapping dopaminergic teaching signals.

neuroscience↗

bioRxiv2025

Desensitization of opsin responses during all-optical interrogation depends on imaging parameters

SignificanceThe combination of two-photon calcium imaging and two-photon optogenetic stimulation, termed all-optical interrogation, provides spatial and temporal precision when recording and manipulating neural circuit activity in vivo. All-optical experiments often use red-shifted opsins in combination with green fluorescent reporters of neuronal activity. However, their excitation spectra still partially overlap, meaning that the imaging laser can excite the opsin. Though some care has been taken in the past to understand the effects of this spectral overlap, further work is required to understand its impact on the findings of all-optical studies. AimWe aimed to investigate whether two-photon imaging of the green fluorescent calcium reporter GCaMP6s at 920 nm increases the rate of desensitization in neurons expressing the red-shifted opsin C1V1. ApproachWe systematically varied either the inter-stimulus interval or the duration of two-photon calcium imaging during two-photon optogenetic stimulation of mouse layer 2/3 barrel cortex or visual cortex neurons. ResultsWe found that two-photon imaging at 920 nm increases the desensitization of photostimulation responses across trials in C1V1-expressing neurons - an effect that is exacerbated at shorter inter-stimulus intervals. Reduced photostimulation responses are not limited to targeted cells, and are found across the entire field of view. Such network effects are less pronounced at shorter imaging doses. ConclusionsOur results provide methodological optimizations that enable opsin desensitization to be mitigated in all-optical experiments. This will reduce an external source of trial-by-trial variability in future all-optical experiments.

neuroscience↗

bioRxiv2025

Deep three-photon functional imaging in the mouse cortex with adaptive optics

Three-photon (3P) microscopy enables functional non-invasive single-cell resolution imaging at greater depths than any other technique. A key challenge of deep imaging is tissue-induced optical aberration, which reduces the excitation confinement. Adaptive optics use deformable mirrors to compensate for optical distortions, hence correcting these aberrations. Here, we present a practical adaptive optics-assisted 3P imaging system for functional imaging in the mouse brain during behavior. We introduce hierarchical corrections that sequentially target aberrations caused by the microscope system, the cranial window, and tissue depth. We demonstrate the utility of this strategy in the prelimbic cortex, where large vasculature near the midline causes aberrations, and in the lateral somatosensory cortex, where side access leads to distinct wavefront distortions. In both regions, adaptive optics significantly improved imaging performance, restoring cellular visibility near vasculature and enhancing signal-to-noise ratio. Our work provides a practical framework for utilizing adaptive optics to improve 3P imaging during behavior.

neuroscience↗

bioRxiv2025

Mismatch-Assisted Toehold Exchange Cascades for Magnetic Nanoparticle-Based Nucleic Acid Diagnostics

Sensitive, simple, and rapid detection of nucleic acid sequences at point-of-care (POC) settings is still an unmet quest. Magnetic readout assays combined with toehold-mediated strand displacement (TMSD)-based circuits are amplification- and wash-free, essential features for contributing to this demand. Nevertheless, nonenzymatic TMSD circuits are slow with low sensitivity for early disease diagnostics. Here, we propose novel mismatch-assisted toehold exchange (MATE) magnetic cascades, wherein magnetic susceptibility increases by dissociation of magnetic nanoparticles (MNPs) from engineered magnetic clusters upon detecting nucleic acid target in solution. The MATE relies on the generation of an allosteric toehold (TH) by spontaneous dissociation to efficiently recycle the target, amplify magnetic signal output, and enhance the assays kinetics. We show that introducing a mismatch in the allosteric TH domain enhances the overall declustering kinetics 7-fold, as also confirmed with oxDNA simulations, with the largest effect gained for the mismatch closest to where the branch migration by the target ends. By integrating MATE into magnetic diagnostics cascades, we demonstrate 3.6-fold better limit-of-detection (LoD) and 12-fold shorter assay time compared to our previous circuit design. Our work makes a major leap towards bringing MNP-based diagnostics much closer to the clinical POC settings by offering a simple, rapid, isothermal, and nonenzymatic assay workflow.

biochemistry↗

bioRxiv2025

The superior colliculus gates dopamine responses to conditioned stimuli in visual classical conditioning

In classical Pavlovian conditioning, it is well-established that midbrain dopamine neurons respond to conditioned stimuli (CS) that predict a reward. However, how the dopamine neurons associate a neutral CS to a reward remains unknown. Here, we show that the superior colliculus (SC) develops neuronal responses to a visual CS during conditioning, which in turn drive the responses of dopamine neurons. Visual responses in the SC were only potentiated when a behaviorally meaningful time interval separated the visual stimulus and reward. Potentiation also required the convergence of visual, dopamine and serotonin inputs to the SC. Importantly, blocking potentiation of the visual response was sufficient to suppress the dopamine responses following a CS. These results reveal a mechanism for how the brain forms associations between unconditioned stimuli and behaviorally meaningful visual information during classical conditioning.

neuroscience↗

bioRxiv2024

Brain-wide population activity during reaching integrates action-mediated goal expectation

Anticipating the outcomes of actions is central to goal-directed behaviour, but how such expectations are encoded across the brain during ongoing movement remains unclear. To address this, we recorded spiking activity from cortical and subcortical regions using multiple Neuropixels probes simultaneously in head-fixed mice performing a water-reaching task. We found that distributed neural population dynamics were strongly modulated by the availability of reward beyond their encoding of forelimb kinematics. Principal component analysis revealed conserved population dynamics across brain regions and sessions that depended on reach amplitude and reward availability. Generalized linear models revealed outcome-related encoding within region-specific population dynamics, in addition to kinematic encoding, with the strongest outcome signals expressed in frontal cortico-thalamic regions. Unsupervised cluster analysis further identified outcome-encoding subpopulations that were enriched in frontal cortices and disproportionally contributed to the shared global latent dynamics. Together, these findings demonstrate that action-mediated outcome expectations are encoded in movement-related population dynamics that are shaped by functional clusters of neurons across the brain.

neuroscience↗

bioRxiv2024

Distinct representations of economic variables across regions and projections of the frontal cortex

Economic decision-making requires evaluating information about available options, such as their expected value and economic risk. Previous studies have shown that frontal cortical neurons encode these variables, but how this encoding is structured across different frontal regions and projection pathways remains unclear. We developed a decision-making task for head-fixed mice in which we varied the expected value and risk associated with reward-predicting stimuli. Using large-scale electrophysiology and projection-specific optotagging across multiple frontal regions, we identified distinct spatial gradients for these variables, with stronger expected value coding in dorsal regions and stronger risk coding in medial regions. We then demonstrated that this encoding further depends on the neuronal projections: frontal neurons projecting to the dorsomedial striatum and claustrum differentially encoded economic variables. Our findings illustrate that frontal cortical representation of economic variables is jointly determined by spatial organization and downstream connectivity of neurons, revealing a structured, multi-scale code for economic variables.

neuroscience↗

bioRxiv2024

Policy complexity suppresses dopamine responses

Limits on information processing capacity impose limits on task performance. We show that animals achieve performance on a perceptual decision task that is near-optimal given their capacity limits, as measured by policy complexity (the mutual information between states and actions). This behavioral profile could be achieved by reinforcement learning with a penalty on high complexity policies, realized through modulation of dopaminergic learning signals. In support of this hypothesis, we find that policy complexity suppresses midbrain dopamine responses to reward outcomes, thereby reducing behavioral sensitivity to these outcomes. Our results suggest that policy compression shapes basic mechanisms of reinforcement learning in the brain.

neuroscience↗

bioRxiv2024

An orexin-sensitive subpopulation of layer 6 neurons regulates cortical excitability and anxiety behaviour.

Cortical layer 6 (L6) neurons uniquely respond to orexin - a neuropeptide influencing arousal and emotion. We show that Drd1a-Cre+ neurons in the prefrontal cortex are selectively sensitive to orexin and regulate prefrontal network activation in vitro and in vivo. Chronically silencing these neurons impairs orexin-induced prefrontal activation and reduces anxiety-like behaviour, indicating that orexin-responsive L6 neurons modulate emotional states and may be a substrate for anxiety regulation.

neuroscience↗

bioRxiv2024

An axonal brake on striatal dopamine output by cholinergic interneurons

Depolarisation of distal axons is necessary for neurons to translate somatic action potentials into neurotransmitter release. Studies have shown that striatal cholinergic interneurons (ChIs) can directly drive ectopic action potentials in dopamine (DA) axons and trigger DA release. However, here we show that this action occurs within a broader context of axonal signal integration whereby activation of ChIs and depolarisation of DA axons by nicotinic receptors (nAChRs) limits the subsequent depolarisation and release of DA in response to ensuing activity. We demonstrate that activation of ChIs and nAChRs in ex vivo mouse striatum, even when it does not trigger DA release that is detectable by fast-scan cyclic voltammetry, limits DA release for [~]100 ms by depressing subsequent axonal depolarisation and calcium summation. This axonal brake on DA release is stronger in dorsal than ventral striatum, and is unrelated to DA depletion. In vivo, antagonism of nAChRs in dorsal striatum elevated extracellular DA levels and promoted conditioned place-preference, underscoring its physiological relevance. Our findings reveal that under physiological conditions in vivo, ChIs acting via nAChRs dynamically attenuate DA output driven by DA neuron activity, leading to a predominantly inverse relationship between ACh and DA signalling that varies continuously with ChI activity.

neuroscience↗

bioRxiv2024

Determination of Absolute Intramolecular Distances in Proteins by Anomalous X-ray Scattering Interferometry

Biomolecular structures are typically determined using frozen or crystalline samples. Measurement of intramolecular distances in solution can provide additional insights into conformational heterogeneity and dynamics of biological macromolecules and their complexes. The established molecular ruler techniques used for this (NMR, FRET, and EPR) are, however, limited in their dynamic range and require model assumptions to determine absolute distance (distributions). Here, we introduce anomalous X-ray scattering interferometry (AXSI) for intramolecular distance measurements in proteins, which are labeled at two sites with small gold nanoparticles of 0.7 nm radius. We apply AXSI to two different cysteine-variants of maltose binding protein in the presence and absence of its ligand maltose and find distances in quantitative agreement with single-molecule FRET experiments. Our study shows that AXSI enables determination of absolute intramolecular distance distributions under virtually arbitrary solution conditions and we anticipate its broad use to characterize protein conformational ensembles and dynamics.

biophysics↗

bioRxiv2023

Striatal dopamine reflects individual long-term learning trajectories

Learning from naive to expert occurs over long periods of time, accompanied by changes in the brains neuronal signals. The principles governing behavioural and neuronal dynamics during long-term learning remain unknown. We developed a psychophysical visual decision task for mice that allowed for studying learning trajectories from naive to expert. Mice adopted sequences of strategies that became more stimulus-dependent over time, showing substantial diversity in the strategies they transitioned through and settled on. Remarkably, these transitions were systematic; the initial strategy of naive mice predicted their strategy several weeks later. Longitudinal imaging of dopamine release in dorsal striatum demonstrated that dopamine signals evolved over learning, reflecting stimulus-choice associations linked to each individuals strategy. A deep neural network model trained on the task with reinforcement learning captured behavioural and dopamine trajectories. The models learning dynamics accounted for the mices diverse and systematic learning trajectories through a hierarchy of saddle points. The model used prediction errors mirroring recorded dopamine signals to update its parameters, offering a concrete account of striatal dopamines role in long-term learning. Our results demonstrate that long-term learning is governed by diverse yet systematic transitions through behavioural strategies, and that dopamine signals exhibit key characteristics to support this learning.

neuroscience↗

bioRxiv2023

Dopamine encoding of novelty facilitates efficient uncertainty-driven exploration

When facing an unfamiliar environment, animals need to explore to gain new knowledge about which actions provide reward, but also put the newly acquired knowledge to use as quickly as possible. Optimal reinforcement learning strategies should therefore assess the uncertainties of these action- reward associations and utilise them to inform decision making. We propose a novel model whereby direct and indirect striatal pathways act together to estimate both the mean and variance of reward distributions, and mesolimbic dopaminergic neurons provide transient novelty signals, facilitating effective uncertainty-driven exploration. We utilised electrophysiological recording data to verify our model of the basal ganglia, and we fitted exploration strategies derived from the model to data from behavioural experiments. We also compared the performance of directed exploration strategies inspired by our basal ganglia model with classic variants of upper confidence bound (UCB) strategy in simulation. The exploration strategies inspired by the basal ganglia model performed better than the classic algorithms in simulation in some cases, and we found qualitatively similar results in fitting model to behavioural data compared with the fitting of more idealised normative models with less implementation level detail. Overall, our results suggest that transient dopamine levels in the basal ganglia that encode novelty could contribute to an uncertainty representation which efficiently drives exploration in reinforcement learning. Author summaryHumans and other animals learn from rewards and losses resulting from their actions to maximise their chances of survival. In many cases, a trial-and-error process is necessary to determine the most rewarding action in a certain context. During this process, determining how much resource should be allocated to acquiring information ("exploration") and how much should be allocated to utilising the existing information to maximise reward ("exploitation") is key to the overall effectiveness, i.e., the maximisation of total reward obtained with a certain amount of effort. We propose a theory whereby an area within the mammalian brain called the basal ganglia integrates current knowledge about the mean reward, reward uncertainty and novelty of an action in order to implement an algorithm which optimally allocates resources between exploration and exploitation. We verify our theory using behavioural experiments and electrophysiological recording, and show in simulations that the model also achieves good performance in comparison with established benchmark algorithms.

neuroscience↗

bioRxiv2023

Temporal regularities shape perceptual decisions and striatal dopamine signals

Perceptual decisions should depend on sensory evidence. However, such decisions are also influenced by past choices and outcomes. These choice history biases may reflect advantageous strategies to exploit temporal regularities of natural environments. However, it is unclear whether and how observers can adapt their choice history biases to different temporal regularities, to exploit the multitude of temporal correlations that exist in nature. Here, we show that mice adapt their perceptual choice history biases to different temporal regularities. This adaptation is well captured by a normative reinforcement learning algorithm with multi-trial belief states, comprising both current trial sensory and previous trial memory states. We demonstrate that striatal dopamine tracks predictions of the model and behavior, pointing towards the involvement of dopamine in forming adaptive history biases. Our results reveal the adaptive nature of perceptual choice history biases, and shed light on their underlying computational principles and neural implementation.

neuroscience↗

bioRxiv2023

Mouse frontal cortex nonlinearly encodes sensory, choice and outcome signals

Frontal area MOs (secondary motor area) is a key brain structure in rodents for making decisions based on sensory evidence and on reward value. In behavioral tasks, its neurons can encode sensory stimuli, upcoming choices, expected rewards, ongoing actions, and recent outcomes. However, the information encoded, and the nature of the resulting code, may depend on the task being performed. We recorded MOs population activity using two-photon calcium imaging, in a task requiring mice to integrate sensory evidence with reward value. Mice turned a wheel to report the location of a visual stimulus following a delay period, to receive a reward whose size varied over trial blocks. MOs neurons encoded multiple task variables, but not all of those seen in other tasks. In the delay period, the MOs population strongly encoded the stimulus side but did not significantly encode the reward-size block. A correlation of MOs activity with upcoming choice could be explained by a common effect of stimulus on those two correlates. After the wheel turn and the feedback, the MOs population encoded choice side and choice outcome jointly and nonlinearly according to an exclusive-or (XOR) operation. This nonlinear operation would allow a downstream linear decoder to infer the correct choice side (i.e., the side that would have been rewarded) even on zero contrast trials, when there had been no visible stimulus. These results indicate that MOs neurons flexibly encode some but not all variables that determine behavior, depending on task. Moreover, they reveal that MOs activity can reflect a nonlinear combination of these behavioral variables, allowing simple linear inference of task events that would not have been directly observable.

neuroscience↗