Biology subjects

Martini, J.

Publications and source records attributed to Martini, J..

4 recordsLinked to original sources

bioRxiv2026

Non-invasive tracking of ripple-like activity during human sleep using MEG

Hippocampal ripples are considered a key mechanism of sleep-dependent memory consolidation. In humans, however, their direct investigation has relied on invasive recordings from patients with epilepsy, because EEG provides limited access to fast activity from deep medial temporal structures. Here, we tested whether source-resolved magnetoencephalography can reveal physiologically meaningful ripple-like activity during NREM sleep in healthy humans. These events showed hallmarks expected of sleep ripples: they were most prominent in medial temporal regions and embedded within slow oscillation (SO)-spindle dynamics, occurring preferentially during SO up-states and spindle centers. To test mnemonic relevance, we combined sleep MEG with targeted memory reactivation, in which learning cues were replayed during sleep. TMR improved memory performance, and later remembered cues preferentially recruited medial temporal ripple-like events alongside cortical spindles. Ripple-like events also coincided with enhanced item-specific reactivation during successful TMR. Together, these findings establish MEG as a non-invasive window onto hippocampo-cortical memory dynamics during sleep.

neuroscience↗

bioRxiv2026

Integrating epigenomic features reveals principles of chromatin-state organization

The coordinated activities of histone modifications and chromatin-associated proteins establish chromatin states that regulate genome function and cellular identity. However, the organizational principles that distinguish chromatin states across cell types remain incompletely understood. Here, we integrated genome-wide profiles of CTCF, H3K27ac, H3K9ac, H3K27me3, and H3K9me3 at 1-kb resolution to generate a unified representation of chromatin organization in human cells. Unsupervised embedding resolved five principal chromatin states corresponding to constitutive heterochromatin, CTCF-associated architectural chromatin, transcriptionally active chromatin, mixed repressive chromatin, and Polycomb-associated chromatin. Comparative analyses of HCT116 and K562 cells revealed that cell-type-specific epigenomic differences arise predominantly through remodeling of Polycomb-associated chromatin, whereas the remaining chromatin states exhibit broadly similar epigenomic signatures and comparatively limited remodeling. Consistent with this observation, principal component analysis identified H3K27me3 as the primary contributor to genome-wide epigenomic divergence, whereas CTCF represented a secondary contributor. Integration with Hi-C data further demonstrated that CTCF-associated chromatin is strongly enriched at chromatin loop anchors and other local architectural features, linking chromatin-state organization to three-dimensional genome architecture. Together, our findings identify distinct chromatin-state classes that organize the human epigenome and reveal Polycomb-associated chromatin as a key determinant of cell-type-specific epigenomic differences.

genomics↗

bioRxiv2025

Hexagonal modulation of theta rhythmic attentional sampling of visual space

Spatial attention improves visual perception by selecting behaviorally relevant sensory signals. Traditionally, attention has been conceptualized as a static spotlight, while recent evidence posited that attention operates as a moving spotlight that samples visual space sequentially in discrete snapshots that are clocked by theta rhythms ([~]3-8 Hz). While theta rhythmic attentional sampling has mainly been observed in fronto-parietal and occipital areas, theta oscillations also hallmark entorhinal-hippocampal grid-cell networks, which encode physical space in hexagonal patterns that guide overt exploration and navigation. We hypothesized that visual attention might rely on the same underlying principles and sample visual space in a hexagonal, grid-like configuration. To test this hypothesis, twenty participants performed a cue-guided attention task that probed behavioral performance as a function of space and time. Reaction times were assessed as a function of spatial location and varying cue-target intervals, which revealed prominent, spatially-structured theta rhythms. Specifically, higher theta power was evident at spatial locations that were aligned to multiples of 60{degrees}, consistent with an underlying hexagonal organization. Participants that exhibited stronger hexagonal sampling relied less on the spatial cue to guide their attentional allocation. In sum, these findings suggest that covert visual attention relies on an underlying hexagonal grid-like structure known from the entorhinal-hippocampal system and highlight that theta rhythms reflect a common organizing principle for spatial cognition. Significance StatementAttention prioritizes sensory inputs to optimize behavior. But how does attention sample the environment in space and time? Here, we demonstrate that attentional sampling of visual space is not uniform, but preferentially explores locations that are oriented along a hexagonal pattern, reminiscent of the spatial configuration of entorhinal-hippocampal grid cells. Moreover, covert attentional sampling was clocked by theta oscillations (3-8 Hz). In sum, these findings provide evidence for a shared neural basis of underlying spatial attention and navigation and reveal that theta rhythms orchestrate sampling behaviors in space and time as a unifying principle underlying spatial cognition.

neuroscience↗

bioRxiv2024

Modelling biological and resource fluxes in fluvial meta-ecosystems

Meta-ecosystem theory predicts that cross-ecosystem flows of energy, nutrients, and organisms have important implications for local community assembly and ecosystem functioning. Developments in the theory also have the potential to enhance our understanding of biodiversity-ecosystem functioning relationships. Meta-ecosystem theory is particularly well-suited to the study of rivers, because water flow forces strong spatial interrelationships among connected ecosystems. However, models that address flows of both resources and organisms and explicitly link both are lacking. We present a model and associated R-package for cross-ecosystem flows of both resources and organisms that can be used to predict their distribution in river networks, as well as meta-ecosystem functioning. The model incorporates feedbacks between these two crucial components--resource concentrations represent niche dimensions for organisms, modifying the colonisation and extinction dynamics and different locations in the network, and organisms also consume resources, thereby modifying the concentrations that are transported downstream. To illustrate the capabilities of the model, we present an in silico experiment and analysis, as well as providing sample code.

ecology↗