Biology subjects

Rosso, M.

Publications and source records attributed to Rosso, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Structured recurrence of latent neural processes predicts memory recognition performance

Understanding cognition requires explaining not only which neural processes are engaged, but how their relationships evolve through time. We tested whether the recurrent organization of low-dimensional whole-brain dynamics relates to auditory recognition behaviour beyond activation magnitude. After a brief learning phase, 65 participants underwent magnetoencephalography (MEG) while recognizing three-, five-, and seven-sound auditory sequences, presented unchanged or with a single early or late tone alteration. Broadband Brain Network Estimation via Source Separation (BROAD-NESS) identified broadband latent networks from source-reconstructed activity and represented their joint activation as trajectories through a multidimensional state space; recurrence quantification analysis characterized their temporal organization. Memorized melodies elicited more recurrent states and longer, more deterministic and persistent recurrence structures, together with lower divergence, than changed melodies. Across participants, structured recurrence was consistently associated with higher accuracy and faster responses, whereas recurrence frequency showed no consistent behavioural association. After adjustment for condition, melody length, their interaction, and matched root-mean-square activation amplitude, recurrence measures increased marginal R2 by 0.273. Nested participant-wise cross-validation reduced held-out prediction error by 11.81% (95% CI: 4.01%-17.65%). These findings support a view of cognition in which performance depends critically on how low-dimensional neural processes jointly organize and evolve over time, beyond how strongly they are activated.

neuroscience↗

bioRxiv2026

Ageing reshapes the resting-state network landscape of the human brain

Ageing alters brain rhythms and large-scale functional organisation, but whether these changes reflect isolated effects or a coordinated reconfiguration remains unclear. We applied Frequency-resolved Network Estimation via Source Separation (FREQ-NESS) to source-reconstructed resting-state MEG from 164 healthy younger and older adults across two independent datasets. FREQ-NESS revealed that ageing reshaped the frequency-resolved organisation of whole-brain networks. Older adults showed a slower alpha-network peak and a flatter decay of network prominence from alpha into beta frequencies, together with changes in entropy across the spectrum. These spectral changes were accompanied by shifts in the spatial expression of dominant networks along the lateral, posterior-anterior, and inferior-superior spatial axes. Rather than following a uniform anatomical shift, the direction of age differences varied across frequencies. Together, these findings show that healthy ageing is associated with a reshaped configuration of endogenous brain networks, characterised not simply by a uniform loss of network organisation, but by selective reconfiguration of the prominence and spatiotemporal expression of whole-brain activity across frequencies.

neuroscience↗

bioRxiv2026

Preserved Spontaneous Interpersonal Entrainment during Rhythmic Synchronization in Autism Spectrum Disorder

PurposeInterpersonal entrainment, defined as the tendency of interacting individuals to temporally align their behaviours, is considered a key mechanism supporting social interactions through predictive and multisensory processes. Autism Spectrum Disorder (ASD), characterized by social and communication difficulties, has been associated with atypical predictive and multisensory integration processes, which may affect spontaneous entrainment to others actions during rhythmic interactions. MethodsThe present study investigated spontaneous interpersonal entrainment in 24 autistic and 22 neurotypical young adults using a unidirectional adaptation of the drifting metronomes paradigm developed by Rosso et al. (2021). Participants synchronized their finger tapping with an auditory metronome while either seeing or not seeing a partners hand movements performing the same task at a slightly different tempo. Individual synchronization performance was assessed using asynchrony measures and computational modelling of sensorimotor synchronization, while interpersonal coordination dynamics were quantified using joint recurrence analysis. ResultsVisual exposure to the partners hand movements significantly increased tapping variability while simultaneously enhancing spontaneous interpersonal entrainment. Contrary to previous findings, these effects were comparable across groups, suggesting similar sensitivity to spontaneous low-level interpersonal coupling under stable and predictable conditions. ConclusionOverall, the findings support accounts proposing selective rather than generalized atypicalities in predictive processing and interpersonal entrainment in ASD.

neuroscience↗

bioRxiv2026

Gaming Addiction Transmission: Interpersonal Neural Pathways Revealed by HYPER-NESS

Gaming addiction may be contagious through social interaction. In team competitive video games, individuals of varying addiction levels are often paired. This raises the question of whether, and through what mechanisms, one individuals addiction level is affected by other players. Methodologically, addressing this question requires understanding both what happens between brains and within individual brains during a gaming session. To this end, we used HYPER-NESS (Hyper Brain Network Estimation via Source Separation), a novel analytical framework to decompose and weight the distinct contributions of inter-brain and intra-brain processes to social brain networks. We applied this framework to a hyperscanning fNIRS dataset where dyads were scanned while playing a video game together against experimenters. We found that inter-brain and intra-brain contributions to the social brain networks were differentially associated with changes in game reward and social reward sensitivity, depending on the addiction level of ones partner. Granger causality analysis of both social and individual brain networks revealed influences from the high-addiction partner to low-addiction partner. Furthermore, significant cross-frequency coupling was found selectively between low-addiction players, supporting the idea that this form of inter-brain interactions underpins the joint processing of task-relevant rewards. To our knowledge, these findings provide the first neural-level account for the hypothesis that gaming addiction propagates though dyadic social interaction.

neuroscience↗

bioRxiv2026

Efficient ageing: Simulated lesion of the structural connectome reveals optimised decline in the healthy ageing brain

Healthy ageing is associated with widespread white-matter change and altered connectome organisation, yet the link between local microstructural decline and whole-brain network communication remains unclear. Here we combined tract-based spatial statistics (TBSS) with probabilistic tractography and graph analysis to quantify the connectome-level consequences of age-sensitive white-matter hotspots. In two independent diffusion MRI datasets of healthy young and older adults (n = 144 total; Dataset 1: 77 participants; Dataset 2: 67 participants), we first identified age-sensitive fractional anisotropy clusters and then used them as constraints in a cross-dataset simulated-lesion framework. This allowed us to estimate how strongly each structural connection depended on age-sensitive tissue and to test the resulting network effects against matched-mass null lesions. Across both datasets, ageing hotspot lesioning reduced global efficiency, but consistently less than expected under the null model, indicating a less-than-random disruption of network integration. Age-sensitive tissue was disproportionately embedded in the brains integrative backbone: proportional degree loss was strongest in high-degree nodes, rich-club connections showed the greatest hotspot dependence, and nodewise losses were concentrated in frontal, cingulate and subcortical association systems, whereas posterior sensory and temporo-limbic regions were relatively spared. These findings suggest that healthy ageing reflects a selective and constrained reconfiguration of structural connectivity rather than simply pointing to uniform decline.

neuroscience↗

bioRxiv2026

Network reconfiguration preserves prediction error signallingin the aging brain

Cognitive aging is widely associated with a progressive weakening of predictive brain mechanisms. This view is supported by decades of electrophysiological studies reporting attenuated mismatch responses in older adults. Yet the literature remains inconsistent, suggesting that aging may not uniformly attenuate predictive processing. One possibility is that multiple predictive subsystems operate concurrently but have rarely been disentangled. Here we address this question by separating whole-brain networks underlying predictive processing in source-reconstructed magnetoencephalography (MEG) data from 77 younger and older adults performing the auditory local-global paradigm. Network decomposition revealed three temporally overlapping predictive subsystems with distinct functional profiles. Aging exerted selective effects across these networks. Sensory prediction error responses were enhanced within a network linking auditory cortices with medial cingulate regions, whereas responses associated with reorientation of attention and contextual pattern processing were attenuated in older adults. The level of multivariate recurrency across these networks was preserved with aging, while the processing of sensory violations induced more recurrency and less divergence relative to contextual violations in both groups. These findings challenge the prevailing view that predictive processing simply declines with age. Instead, aging redistributes predictive resources across distinct neural systems, amplifying sensory-based processes while weakening more cognitively demanding predictive mechanisms.

neuroscience↗

bioRxiv2026

Ibogaine is associated with reorganization of high-beta brain networks in veterans with post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is a debilitating condition that affects millions of veterans. A recent observational study in 30 veterans showed that a single dose of the atypical psychedelic ibogaine can be highly effective at treating PTSD up to twelve months later. Although a prior study demonstrated that ibogaine transiently alters electroencephalography (EEG) power in various frequency bands, the long-term, network-level neural mechanisms targeted by ibogaine are unclear. Here, we investigated whether ibogaine-related clinical improvements are associated with the reorganization of certain brain networks. We applied a novel framework, FREQuency-resolved brain Network Estimation via Source Separation (FREQ-NESS), to identify frequency-specific brain networks in resting-state EEG data acquired at baseline, three to four days after treatment (immediate-post), and one month after ibogaine. At both the immediate-post and one month-post timepoints, high-beta (24 and 25 Hz) networks shifted away from frontal areas and towards posterior regions, an effect that was replicated in an independent EEG dataset on ibogaine treatment for opioid use disorder. This posterior shift was significantly correlated with improvements in PTSD symptoms at both timepoints. Neural field modeling demonstrated that these posterior high-beta shifts are associated with increases in corticocortical, but not corticothalamic, connectivity. Our results are consistent with prior evidence implicating aberrant frontal beta-band activity in PTSD. Overall, we demonstrate that the reconfiguration of high-beta brain networks could be a robust biomarker for ibogaines therapeutic effects.

neuroscience↗

bioRxiv2026

Beyond where: When and how brain stimulation drives state transitions

Brain stimulation is increasingly used to treat neurological and psychiatric conditions, but stimulation sites and timing are typically chosen based on a priori assumptions from prior studies, not individualised mechanisms. Here, we investigate why some brain regions respond more to stimulation, when they respond best, and whether optimal targets for brain-state transitions are defined by functional anatomy (e.g. an auditory region in a resting-to-listening task transition), by system dynamics, or a combination of both. To do so, we build subject-specific whole-brain Hopf models fitted to MEG data, separating signals into five canonical frequency bands. We find that regions with a smaller oscillation radius and greater temporal variability respond more strongly to stimulation. Moreover, responsiveness was highly dependent on state and frequency band, with slower frequencies exhibiting phase-driven responsiveness, while faster ones depending more on network synchrony. Importantly, optimal nodes for transitioning between brain states are not defined by functional labels but rather by their dynamical regime. These results emphasise the value of mechanistic, personalised models for identifying when and where to stimulate the brain, and may help inform more precise brain-stimulation strategies.

neuroscience↗

bioRxiv2025

Shared and modality-specific brain networks underlying predictive coding of temporal sequences

Predictive coding posits that the brain continuously generates and updates internal models to anticipate incoming sensory input. While auditory and visual modalities have been studied independently in this context, direct comparisons using matched paradigms are scarce. Here, we employed magnetoencephalography (MEG) to investigate how the brain of 83 participants encodes and consciously recognises temporally unfolding sequences that acquire Gestalt-like structure over time, a feature rarely addressed in cross-modal research. Participants memorised matched auditory and visual sequences with coherent temporal structure and later identified whether test sequences were familiar or novel. Multivariate decoding revealed robust discrimination between the brain mechanisms underlying encoding and recognition of memorised and novel sequences, with sustained temporal generalisation in the auditory domain and time-specific responses in the visual domain. Using the BROAD-NESS pipeline, we identified modality-specific and supramodal brain networks. Auditory memory engaged auditory cortex, cingulate gyrus, and hippocampus, whereas visual memory involved orbitofrontal cortex and visual areas. Notably, both modalities recruited a shared network including hippocampus and medial cingulate during recognition. These findings provide compelling evidence for distinct and shared predictive learning mechanisms across sensory systems, advancing our understanding of how the brain integrates and evaluates temporally structured, Gestalt-like information.

neuroscience↗

bioRxiv2025

FREQ-NESS reveals age-related differences in frequency-resolved brain networks during auditory recognition and resting state

Understanding how brain networks operate across different frequencies during cognitive tasks, and how these dynamics change with age, remains a central challenge in cognitive neuroscience. While previous studies have focused on resting-state activity and passive listening, less is known about frequency-specific brain dynamics during event-related tasks that require active memory engagement. In this study, we extend the recently developed FREQ-NESS analytical pipeline by adapting it to event-related task and resting state source-reconstructed magnetoencephalography (MEG) data from 70 healthy participants. This method quantified the variance explained by frequency-specific brain networks, their spatial organization, and associated time-resolved power estimates. We found significant effects of age, condition, and their interaction in the variance explained by leading components at 1.07 Hz, 2.86 Hz, and 10.00 Hz. Younger adults exhibited stronger peaks at 1.07 and 2.86 Hz during the task and a more pronounced 10.00 Hz peak at rest, whereas older adults showed the opposite pattern. Time-frequency analysis revealed age- and condition-dependent desynchronization in the alpha and beta bands (7.10-22.90 Hz). These findings demonstrate the effectiveness of the adapted FREQ-NESS pipeline for event-related tasks and highlight the importance of frequency-resolved network analysis for characterizing age-related changes in active auditory memory processing.

neuroscience↗

bioRxiv2025

Neural oscillatory dynamics in joint action: distinct contributions of entrainment and beta modulation to self/other integration

Temporal coordination plays a pivotal role in human activities, enabling effective communication and collaboration. Yet, the neural mechanisms supporting this ability remain poorly understood. Recent research suggests that synchronized beta modulation across individual brains, as measured via EEG hyperscanning, may reflect a shared sensorimotor framework underpinning interpersonal synchronization. Building on the idea that self-other integration is a key mechanism in this process, behavioral studies have shown that adopting a partners first-person visual perspective (1P) enhances interpersonal coordination, as opposed to the natural second-person perspective (2P). Here, we used the body-swap illusion in immersive virtual reality to directly manipulate embodied perspective and investigate its neural consequences. Specifically, we examined how this illusion modulates beta activity and neural entrainment during joint rhythmic action. Forty participants (N=40), randomly paired into twenty dyads, performed a joint finger-tapping task while wearing head-mounted displays for immersive virtual environments. In coupled conditions, the visual scene was manipulated so that participants viewed their partners hand from a 1P perspective, as if it belonged to their own body, or from a natural 2P perspective. In uncoupled control conditions, participants saw their own hand in 1P and 2P, without perceiving any information about their partners tapping. EEG hyperscanning revealed that both neural entrainment (measured as the convergence of low-frequency oscillations) and beta modulation (changes in [~]20 Hz power linked to partner- generated movements) occurred in 1P and 2P visually coupled conditions. However, only beta modulation was selectively enhanced when participants experienced their partners hand from a 1P perspective. These findings suggest that while neural entrainment reflects a general mechanism for tracking a partners rhythmic behavior, beta modulation specifically supports the integration of the others effector into ones bodily representation.

neuroscience↗

bioRxiv2025

LSD reconfigures the frequency-specific network landscape of the human brain

Lysergic acid diethylamide (LSD) and other psychedelic substances profoundly alter human consciousness. While several studies have demonstrated changes in brain function and connectivity associated with psychedelics, we still have a limited understanding of how LSD reshapes brain networks operating across different frequency bands. In this study, we applied the recently developed FREQ-NESS method to MEG data from 14 healthy participants who received LSD under four conditions: eyes-closed with or without music and eyes-open with or without a video stimulus. LSD significantly restructures canonical networks in the alpha and beta bands. Relative to broadband brain activity, it enhances the prominence of high alpha (12.1, 13.3 Hz) across all experimental conditions and high beta (25.3 Hz) in three conditions. Conversely, LSD decreases the prominence of low beta (18.1, 19.3 Hz) in both Open and Closed conditions and low alpha (8.5 Hz) in the latter. In addition, LSD substantially alters the spatial distributions or topographies of the networks. Under LSD, the low alpha (8.5 Hz) network shifts anteriorly toward the motor cortex, while high alpha (12.1, 13.3 Hz) becomes more localized to the visual cortex. Low beta (18.1, 19.3 Hz) expands over the temporal and occipital cortices, whereas high beta (25.3, 26.5 Hz) topographies remain unchanged. Our findings provide critical insights into the specific frequencies and spatial networks in which LSD modulates brain connectivity, adding nuance to prevailing theories about network disintegration under psychedelics. Significance statementPsychedelic substances such as lysergic acid diethylamide (LSD) profoundly alter perception and cognition, yet their effect on brain activity across different frequency bands remains unclear. Using FREQ-NESS applied to MEG data, we show that LSD reorganizes brain networks by enhancing high-frequency alpha and beta rhythms while suppressing lower-frequency counterparts. These changes occur across various experimental conditions and shift the spatial distribution of brain activity, particularly in motor and visual regions. Our findings suggest that LSD modulates brain connectivity in a frequency- and region-specific manner, offering new insights into how psychedelics alter consciousness. This work advances our understanding of LSDs neural effects, which may be relevant for therapeutic applications and models of brain function.

neuroscience↗

bioRxiv2024

BROADband brain Network Estimation via Source Separation (BROAD-NESS)

Auditory memory enables the recognition of sound sequences by integrating sensory input with memory traces and predictive mechanisms. While predictive coding has been proposed as a key framework for this process, the large-scale brain networks supporting it remain poorly understood. Using BROADband brain Network Estimation via Source Separation (BROAD-NESS), we provide three fundamental insights into the neural organisation of auditory memory and predictive coding. First, auditory cortices participate in two distinct, orthogonal whole-brain networks, expanding on the conventional view focused on forward and backward information flow between single brain regions. One network involves the medial cingulate gyrus, while the other integrates prefrontal and hippocampal regions, inferior temporal cortex, and insula. Second, we present evidence for a dual-stream mechanism in auditory memory recognition, which both parallels and diverges from the well-established dual-stream hypothesis in vision. Third, predictive coding in conscious auditory memory is supported by large-scale networks generating confirmed predictions and prediction errors. While previous studies examined predictive coding in isolated regions or pairwise connections, our findings reveal how whole-brain networks coordinate these processes, highlighting fine-grained spatial gradients and distinct temporal dynamics. These findings enhance our understanding of auditory perception, memory, and prediction, as well as their underlying basis in whole-brain dynamical networks.

neuroscience↗

bioRxiv2024

FREQuency-resolved brain Network Estimation via Source Separation (FREQ-NESS)

The brain is a dynamic system whose network organization is often studied by focusing on specific frequency bands or anatomical regions, leading to fragmented insights, or by employing complex and elaborate methods that hinder straightforward interpretations. To address this issue, a new analytical pipeline named FREQuency-resolved Network Estimation via Source Separation (FREQ-NESS) is introduced. This is designed to estimate the activation and spatial configuration of simultaneous brain networks across frequencies by analyzing the frequency-resolved multivariate covariance between whole-brain voxel time series. FREQ-NESS is applied to source-reconstructed magnetoencephalography (MEG) data during resting state and isochronous auditory stimulation. Results reveal simultaneous, frequency-specific brain networks during resting state, such as the default mode, alpha-band, and motor-beta networks. During auditory stimulation, FREQ-NESS detects: (1) emergence of networks attuned to the stimulation frequency, (2) spatial reorganization of existing networks, such as alpha-band networks shifting from occipital to sensorimotor areas, (3) stability of networks unaffected by auditory stimuli. Furthermore, auditory stimulation significantly enhances cross-frequency coupling, with the phase of attuned auditory networks modulating the gamma band amplitude of medial temporal lobe networks. In conclusion, FREQ-NESS effectively maps the brains spatiotemporal dynamics, providing a comprehensive view of brain function by revealing simultaneous, frequency-resolved networks and their interaction.

neuroscience↗

bioRxiv2023

Auto-STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications

BackgroundSystematic reviews, i.e., research summaries that address focused questions in a structured and reproducible manner, are a cornerstone of evidence-based medicine and research. However, certain systematic review steps such as data extraction are labour-intensive which hampers their applicability, not least with the rapidly expanding body of biomedical literature. ObjectiveTo bridge this gap, we aimed at developing a data mining tool in the R programming environment to automate data extraction from neuroscience in vivo publications. The function was trained on a literature corpus (n=45 publications) of animal motor neuron disease studies and tested in two validation corpora (motor neuron diseases, n=31 publications; multiple sclerosis, n=244 publications). ResultsOur data mining tool Auto-STEED (Automated and STructured Extraction of Experimental Data) was able to extract key experimental parameters such as animal models and species as well as risk of bias items such as randomization or blinding from in vivo studies. Sensitivity and specificity were over 85 and 80%, respectively, for most items in both validation corpora. Accuracy and F-scores were above 90% and 0.9 for most items in the validation corpora. Time savings were above 99%. ConclusionsOur developed text mining tool Auto-STEED is able to extract key experimental parameters and risk of bias items from the neuroscience in vivo literature. With this, the tool can be deployed to probe a field in a research improvement context or to replace one human reader during data extraction resulting in substantial time-savings and contribute towards automation of systematic reviews. The function is available on Github.

neuroscience↗

bioRxiv2022

Evidence for HARKing in mouse behavioural tests of anxiety

Anxiety disorders are among the most common mental health conditions needing new and better treatments. Research and development of anxiolytic drugs using animal models heavily rely on behavioural tests, most of which measure anxiolytic effects by increased exploratory activity in potentially threatening environments. However, interpretation of such tests is ambiguous because reduced exploratory activity can reflect either anxiety or sedation by the compound. Based on a systematic review of the sensitivity of mouse behavioural tests of anxiety to anxiolytic drugs, we analysed outcomes of 206 studies testing the effect of diazepam in either the open-field test or the hole-board test, as outcomes of these tests showed substantial variation in both direction and strength of the drug effect. Surprisingly, we found that both the rationale given for using the test, whether to detect anxiolytic or sedative effects, and the predicted effect of diazepam, anxiolytic or sedative, strongly depended on the reported test results. The most likely explanation for such strong dependency is post-hoc reasoning, also called hypothesizing after the results are known (HARKing). HARKing can invalidate study outcomes and hampers evidence synthesis by inflating effect sizes. It may also lead researchers into blind alleys, put patients in clinical trials at risk, and waste animals, time, and resources for inconclusive research.

animal behavior and cognition↗

bioRxiv2022

Rearing environment persistently modulates the phenotype of mice

The phenotype of an organism results from its genotype and the influence of the environment throughout development. Even when using animals of the same genotype, independent studies may test animals of different phenotypes, resulting in poor replicability due to genotype-by-environment interactions 1-4. Thus, genetically defined strains of mice may respond differently to experimental treatments depending on their rearing environment 5. However, the extent of such phenotypic plasticity and its implications for the replicability of research findings have remained unknown. Here, we examined the extent to which common environmental differences between rearing facilities modulate the phenotype of genetically homogeneous (inbred) mice. We conducted a comprehensive multi-center study, where inbred mice from the same breeding stock were reared in five different facilities throughout early life and adolescence, before being transported to a single test laboratory. We found persistent effects of rearing facility on the composition and heterogeneity of the gut microbial community. These effects were paralleled by persistent differences in body weight and in the behavioural phenotype of the mice. Furthermore, we show that common variation among rearing facilities is strong enough to influence epigenetic patterns in neurons at the level of chromatin organization. We detected changes in chromatin organization in the regulatory regions of genes involved in nucleosome assembly, neuronal differentiation, synaptic plasticity and regulation of behavior. Our findings demonstrate that common environmental differences between rearing facilities may produce facility-specific phenotypes, from the molecular to the behavioural level. We expect our findings to stimulate further research into the mechanisms and drivers of these epigenetic changes mediated by the laboratory environment. Furthermore, they highlight an important limitation of inferences from single-laboratory studies and a need to account for the animals environmental background in study design to produce robust and replicable findings.

neuroscience↗

bioRxiv2021

Reliability of Mouse Behavioural Tests of Anxiety: a Systematic Review and Meta-Analysis on the Effects of Anxiolytics.

Animal research on anxiety and anxiety disorders relies on valid animal models of anxiety. However, the validity of widely used rodent behavioural tests of anxiety has repeatedly been questioned, as they often fail to produce consistent results across independent replicate studies using different study populations or different anxiolytic compounds. In this study, we assessed the sensitivity of behavioural tests of anxiety in mice to detect anxiolytic effects of drugs prescribed to treat anxiety in humans. To this end, we conducted a pre-registered systematic review of studies reporting tests of anxiolytic compounds against a control treatment using common behavioural tests of anxiety in mice. PubMed and EMBASE were searched on August 21st 2019 for studies published in English and 814 papers were identified for inclusion. Risk of bias was assessed based on Syrcles risk of bias tool and the Camarades study quality checklist on a randomly selected subsample of 180 papers. Meta-analyses on effect sizes of treatments using standardized mean differences (Hedges g) showed that only two of 17 test measures reliably detected effects of anxiolytic compounds other than diazepam. Further, we report considerable variation in both direction and size of effects of most anxiolytics on most outcome variables, indicating poor replicability of test results. This was corroborated by high heterogeneity in most test measures. Finally, we found an overall high risk of bias. Our findings indicate a general lack of sensitivity of common behavioural tests of anxiety in mice to anxiolytic compounds and cast serious doubt on both construct and predictive validity of most of those tests. The use of animals to model human conditions can be justified only if the expected results are informative, reproducible, and translatable. In view of scientifically valid and ethically responsible research, we call for a revision of behavioural tests of anxiety in mice and the development of more predictive tests.

neuroscience↗