Biology subjects

Liljeström, M.

Publications and source records attributed to Liljeström, M..

8 recordsLinked to original sources

bioRxiv2026

MEG-informed navigated TMS for individualized speech cortical mapping

Speech cortical mapping by means of navigated repetitive transcranial magnetic stimulation (SCM nrTMS) provides neurosurgeons with noninvasive prior information about individuals cortical speech network. Individualized mapping is required, since the exact locations and activation patterns of speech production show high variability between individuals. We hypothesized that magnetoencephalography (MEG) data of an individuals speech production could guide the SCM TMS process temporally and spatially, leading to higher error rates at MEG-defined locations with TMS pulse timings coinciding with MEG activity. 13 healthy subjects participated in MEG and TMS measurements, where the timing of the TMS pulse (PTI; picture-to-TMS interval) was adjusted based on the individuals MEG activation in a picture naming task. At the group level, significant correlations were observed between the latency of the peak MEG activation and the PTI that produced the highest speech error rate. The MEG peak preceded the best PTI by 132 ms (R=0.713, p=0.006) across the entire stimulation area in the lateral left hemisphere, and by 103 ms (R=0.673, p=0.012) in the left frontal regions. We found 17 combinations of PTI and stimulation area in which the subjects speech error rate increased significantly compared to their average error rate. Our findings suggest that optimal PTIs are highly individual, and that individualizing the PTI according to MEG activation provides a straightforward method for accounting individual variability in speech function and may increase the sensitivity and utility of SCM TMS.

neuroscience↗

bioRxiv2026

Test-retest reliable and site-robust Hidden Markov Model framework for discovering whole-brain beta activity

Sensorimotor beta activity (13-30 Hz) is a key neuronal signature in the human sensorimotor system, and its features can be effectively measured using functional brain imaging methods such as magnetoencephalography (MEG). In addition to its importance in healthy brain processing, beta activity has been shown to be altered in several neurological diseases, underscoring its potential as a biomarker. To serve as biomarkers, features must be reliably defined, stable across measurements and, ideally, amenable to automated analysis, yet current approaches to beta characterization require subjective decisions and manual work. We here describe a hidden Markov model (HMM) based approach to automatically segment beta events from source level MEG beta band activity into discrete high- and low-beta states. We demonstrate the differences between the proposed HMM based approach and a commonly used amplitude-envelope based approach to analyse high- and low-beta modulation. We show that the methods complement each other both when applied to resting data and task related passive movement data. Furthermore, we assess the test-retest reliability of the proposed pipeline within individuals using intraclass correlation coefficients (ICC), and test if HMM constructed at one measurement site can be applied to data acquired at another site, thereby evaluating its multisite transferability. We show that the proposed approach produces stable results within subjects and across sites for many of the features. The ICC values were excellent for high-beta state (86-100% of brain areas), while low-beta state test-retest reliability was more modest. Most of the features showed statistically significant differences between sites only in a few brain areas, indicating very good multisite stability. The proposed approach can serve as an automated, reproducible analysis pipeline for, e.g., clinical applications, and appears suitable for multi-site datasets.

neuroscience↗

bioRxiv2025

Magnetoencephalography reveals adaptive neural reorganization maintaining lexical-semantic proficiency in healthy aging

Although semantic cognition remains behaviorally stable with age, neuroimaging studies report age-related alterations in response to semantic context. We aimed to reconcile these inconsistent findings by combining behavioral and magnetoencephalography (MEG) measures and examined the neural mechanisms underlying lexical-semantic processing in healthy aging. Forty-six Finnish-speaking adults (25 female) across younger (22- 32 years) and older (62 - 69 years) cohorts performed a semantic congruency judgment task on word pairs. Both age groups performed the task with high accuracy, with older adults responding faster than young. While advancing age was not associated with impaired task performance, MEG revealed neural reorganization in the old compared to young adults. Young participants exhibited the canonical N400 effect in the left temporal cortex 300 - 400 ms post-stimulus, followed by a Late Positive Complex (LPC), whereas older adults showed less pronounced congruency effects, and the activation distribution was shifted toward frontal and bilateral regions. Despite the absence of the canonical N400 effect in older participants, multivariate time-resolved decoding demonstrated that the congruency effect was decodable from the MEG responses in both groups from [~]300 ms post-stimulus, indicating preserved sensitivity to congruency with age. Decoding performance correlated with response time, suggesting that increased neural separation between semantic concepts facilitates rapid decision-making. Critically, age groups were distinguishable based on their neural responses 300 - 800 ms post-stimulus, reflecting functional reorganization in older adults. Overall, our findings suggest that healthy aging involves adaptive reconfiguration of neural systems, supported by experience-driven strategies that preserve semantic proficiency despite broader age-related cognitive changes.

neuroscience↗

bioRxiv2025

Ambient temperature, clutch size, and daylight are the main drivers of incubation behavior in two neotropical swallows breeding 8,000 km apart

The central dilemma in incubation behaviour is how to allocate time between warming up the clutch and self-preservation activities outside the nest. It is assumed that incubating birds follow a classical framework in which the environmental temperature, the main variable influencing incubation behaviour, and bout duration show a non-linear relationship. In this context, incubating birds would maximize bout duration for most of the temperature range in which they breed. To determine whether this theoretical framework applies to species breeding at different latitudes under extremely different environmental conditions, we collected incubation data from two distant but breeding populations of Tachycineta swallows. T. leucopyga (Chillean swallow) breeds in Ushuaia, Argentina, and T. meyeni (mangrove swallow) breeds in Hill Bank, Belize. These populations do not overlap in terms of ambient temperature; they are exposed to different daylight conditions and the latitudinal differences influence life-history traits such as clutch size. Tachycineta swallows showed similar incubation consistency over 24 hours ([~]75% of nest attendance) but followed different behavioral strategies to achieve this consistency. Daylight duration limited incubation activity in mangrove swallows, but longer nocturnal incubation compensated for shorter days. Larger clutches only took their toll on the Chilean swallows, by shortening their incubation bouts and lengthening their foraging bouts, which affected the length of their daily activity. Overall, both swallow species showed incubation patterns adapted to the local conditions. They responded differently to increasing temperatures, but both species reduced their incubation effort whenever possible. Our results contrast with previous work where maximizing incubation effort was the rule. In our populations, females reduced their incubation effort as soon as weather conditions improved (i.e., increasing temperatures), changing the paradigm of incubation behaviour. Lay summary- In species where only the male or female incubates, they need to find a balance between the time they spend incubating in the nest and the time they spend foraging out of the nest. - The ambient temperature is the most important factor influencing the duration of both behaviours, and birds are thought to respond similarly to the same range of temperatures. - We studied the incubation behaviour of two species of swallows breeding in Belize and Argentina, respectively. - Both species incubated for a similar length of time in 24 hours, but each followed a different strategy depending on clutch size and daylight duration. - Their incubation behaviour was also related to ambient temperature, but differed between populations, suggesting adaptations to local conditions. - We cannot expect different species to show similar responses to ambient temperature under different conditions.

animal behavior and cognition↗

bioRxiv2025

Cortical functional connectivity across the adult lifespan and its relation to sensorimotor integration

The operation of the human brain relies on functional networks enabled by inter-areal oscillatory synchronization between neuronal populations. Although disruptions in this functional connectivity are associated with brain disorders, evidence on its healthy age-dependent variation and behavioral relevance remains limited. Utilizing magnetoencephalography (MEG) recordings from 576 adults aged 18-87 years, we investigated the evolution of resting-state functional connectivity (rs-FC) across the healthy adult lifespan. We observed age-related, frequency-specific changes in widespread cortical networks. Alpha-band (8-13 Hz) rs-FC decreased, while delta (1-4 Hz), theta (4-8 Hz), and gamma-band (40-90 Hz) rs-FC increased with age. Beta-band (13-30 Hz) rs-FC followed a non-linear trajectory, peaking in middle age. The global delta, theta, alpha, and beta-band patterns differed from concurrent changes in oscillatory power, underscoring their dissociable contributions. Notably, reduced beta-band rs-FC was associated with increased sensorimotor attenuation, indicating that changes in rs-FC are behaviorally relevant for sensorimotor function. These findings advance our understanding of healthy brain aging and highlight a link between resting-state brain activity and sensorimotor integration. Key pointsO_LIFunctional connectivity is altered across the healthy adult lifespan in a frequency-dependent manner C_LIO_LIChanges in source power do not explain global functional connectivity trajectories C_LIO_LIBeta-band connectivity at rest is associated with sensorimotor attenuation independent of age-related effects C_LI

neuroscience↗

bioRxiv2023

Test-retest reliability of MEG functional brain connectivity related to language processing

The number of studies examining changes in functional connectivity of the human brain is increasing rapidly. In this magnetoencephalography (MEG) study, we examined the reliability of dynamic connectivity related to language processing in a picture naming test-retest paradigm, using data collected from the same participants on two separate days. We determined the connections that were reliable across both days and also examined the behavioral, functional, and structural properties underlying this reliability. A particularly salient finding among a rich set of results was a reliable pattern of beta connectivity increase in the left motor and frontal regions (0-400 ms and 400-800 ms after stimulus onset) and gamma connectivity decrease in the bilateral motor regions (800-1200 ms) which we suggest to represent the motor preparation of speech production. Furthermore, the reliable connections tended to be more frequently associated with the behavioral performance than the non-reliable ones. Finally, the reliable connections were also linked to stronger functional connectivity, as well as to stronger structural connectivity and shorter structural path length, as determined through diffusion MRI (magnetic resonance imaging). Overall, this study defines reliable language-related functional connectivity and introduces practices that may increase reliability. AUTHOR SUMMARYResearch applying connectivity metrics in neuroimaging has increased rapidly during recent years. Hence, the focus has also been to define the best methods for increasing the reliability of connectivity estimation. This study determined reliable functional connectivity from MEG data related to language processing. Moreover, we defined what makes a connection reliable by studying the behavioral, functional, and structural properties underlying the reliable connections.

neuroscience↗

bioRxiv2020

Picture naming yields highly consistent cortical activation patterns: test-retest reliability of magnetoencephalography recordings

Reliable paradigms and imaging measures of individual-level brain activity are paramount when reaching from group-level research studies to clinical assessment of individual patients. Magnetoencephalography (MEG) provides a direct, non-invasive measure of cortical processing with high spatiotemporal accuracy, and is thus well suited for assessment of functional brain damage in patients with language difficulties. This MEG study aimed to identify, in a picture naming paradigm, source-localized evoked activity and modulations of cortical oscillations that show high test-retest reliability across measurement days in healthy individuals, demonstrating their applicability in clinical settings. For patients with a severe language disorder picture naming can be a challenging task. Therefore, we also determined whether a semantic judgement task ( is this item living) with a spoken response ( yes/no) would suffice to induce comparably consistent activity within brain regions related to language production. The MEG data was collected from 19 healthy participants on two separate days. In picture naming, evoked activity was consistent across measurement days (intraclass correlation coefficient (ICC)>0.4) in the left frontal (400-800 ms after image onset), sensorimotor (200-800 ms), parietal (200-600 ms), temporal (200-800 ms), occipital (400-800 ms) and cingulate (600-800 ms) regions, as well as the right temporal (600-800 ms) region. In the semantic judgement task, consistent evoked activity was spatially more limited, occurring in the left temporal (200-800 ms), sensorimotor (400-800 ms), occipital (400-600 ms) and subparietal (600-800 ms) regions, and the right supramarginal cortex (600-800 ms). The naming task showed typical beta oscillatory suppression in premotor and sensorimotor regions (800-1200 ms) but other consistent modulations of oscillatory activity were mostly observed in posterior cortical regions that have not typically been associated with language processing. The high test-retest consistency of MEG evoked activity in the picture naming task testifies to its applicability in clinical evaluations of language function, as well as in longitudinal MEG studies of language production in clinical and healthy populations.

neuroscience↗

bioRxiv2018

Analysis of functional connectivity and oscillatory power using DICS: from raw MEG data to group-level statistics in Python

Communication between brain regions is thought to be facilitated by the synchronization of oscillatory activity. Hence, large-scale functional networks within the brain may be estimated by measuring synchronicity between regions. Neurophysiological recordings, such as magnetoencephalography (MEG) and electroencephalography (EEG), provide a direct measure of oscillatory neural activity with millisecond temporal resolution. In this paper, we describe a full data analysis pipeline for functional connectivity analysis based on dynamic imaging of coherent sources (DICS) of MEG data. DICS is a beamforming technique in the frequency-domain that enables the study of the cortical sources of oscillatory activity and synchronization between brain regions. All the analysis steps, starting from the raw MEG data up to publication-ready group-level statistics and visualization, are discussed in depth, including methodological considerations, rules of thumb and tradeoffs. We start by computing cross-spectral density (CSD) matrices using a wavelet approach in several frequency bands (alpha, theta, beta, gamma). We then provide a way to create comparable source spaces across subjects and discuss the cortical mapping of spectral power. For connectivity analysis, we present a canonical computation of coherence that facilitates a stable estimation of all-to-all connectivity. Finally, we use group-level statistics to limit the network to cortical regions for which significant differences between experimental conditions are detected and produce vertex-and parcel-level visualizations of the different brain networks. Code examples using the MNE-Python package are provided at each step, guiding the reader through a complete analysis of the freely available openfMRI ds000117 \"familiar vs. unfamiliar vs. scrambled faces\" dataset. The goal is to educate both novice and experienced data analysts with the \"tricks of the trade\" necessary to successfully perform this type of analysis on their own data.

neuroscience↗