Biology subjects

Pedersen, A.

Publications and source records attributed to Pedersen, A..

5 recordsLinked to original sources

bioRxiv2026

Hippocampal CA1 neurons are crucial for sleep-associated memory formation in humans: The role of theta power during NREM sleep

The formation of long-term memory during sleep depends on the reactivation and redistribution of recently acquired mnemonic information during non-rapid eye movement (NREM) sleep. Animal studies suggest that hippocampal memory replay during slow-wave sleep is coordinated through the interaction of sharp-wave ripples, thalamocortical sleep spindles, and neocortical slow oscillations (SOs). However, direct evidence for the contribution of hippocampal network dynamics to sleep-dependent memory consolidation in humans remains limited. Here, we investigated sleep-dependent memory consolidation in patients (n=13) with transient global amnesia (TGA), a clinical syndrome associated with focal and transient lesions of the hippocampal CA1 region. Patients completed a verbal paired-associative learning task followed by nocturnal polysomnography and subsequent memory retrieval during the acute phase of TGA (acute condition) and again after clinical recovery (follow-up condition). Overnight memory consolidation was significantly impaired during the acute phase compared with the follow-up session. NREM EEG theta power (4-8 Hz) was reduced during the acute phase of TGA. Importantly, increases in theta power from the acute to the follow-up session predicted corresponding improvements in memory consolidation within individuals. In contrast, established NREM markers of sleep-dependent memory consolidation, including sleep spindle density, SO density, and SO-spindle coupling, did not differ between the acute and follow-up conditions. These findings suggest that transient hippocampal CA1 dysfunction disrupts sleep-related hippocampal network dynamics reflected in reduced NREM theta activity, which in turn is associated with impaired memory consolidation. Sleep-related theta oscillations may therefore represent a functional marker of hippocampal network integrity during sleep-dependent memory consolidation in humans.

neuroscience↗

bioRxiv2026

Post-encoding slow-wave amplitude during a daytime nap predicts pattern completion from sparse visual cues

Pattern completion refers to the reinstatement of a stored memory representation from partial or degraded cues. In this sense, it enables a form of cue-based generalization: the same memory representation can be retrieved across different, incomplete versions of the original input. Sleep supports hippocampus-dependent memory consolidation and may facilitate such flexible retrieval, but it remains unclear whether post-encoding sleep improves visual pattern completion from degraded cues. Previous sleep studies have mainly examined mnemonic discrimination or relational memory, leaving open whether sleep directly enhances the recovery of learned visual scenes from sparse perceptual information. We tested this question using the Memory Image Completion (MIC) task in a polysomnographic within-subject sleep-wake design. Twenty-eight healthy young adults (14 female; mean age 23.4 {+/-} 3.1 years) encoded scene-label associations and were tested immediately and after either a 90-min daytime nap or a matched wake interval. During retrieval, learned and new scenes were presented at five levels of visual completeness. A separate pre-encoding baseline nap assessed individual sleep physiology without prior learning. Sleep did not generally improve performance across all retrieval conditions. Instead, it selectively enhanced consolidation of learned scenes when visual cues were maximally degraded (p = .001) indicating increased pattern completion. No corresponding sleep effect was found for new scenes (all p > .31), suggesting that the benefit was specific to the recovery of previously encoded scene representations. Slow-wave amplitude during the post-encoding nap predicted consolidation of learned scenes under the most degraded condition (p = .011; FDR-corrected p = .042), whereas baseline slow-wave amplitude did not (p > .11). These findings suggest that post-encoding sleep facilitates cue-based recovery of learned visual representations from strongly degraded input, and that this benefit is linked to slow-wave amplitude during post-encoding sleep. Together, these results link sleep-dependent consolidation to visual pattern-completion-like retrieval and extend previous work on sleep-related memory transformation from verbal and relational paradigms to the recovery of learned scene representations from degraded cues.

neuroscience↗

bioRxiv2026

Glutamate transporter xCT is important for cGAS-dependent interferon responses to DNA and to HSV-1

Metabolic reprogramming is a key component of antiviral immunity, yet how metabolite transport regulates innate immune signaling remains incompletely understood. Here, we show that infection with herpes simplex virus 1 (HSV-1) and stimulation with cytosolic DNA induce the cellular export of glutamate via the xCT (SLC7A11) transporter and that inhibition of xCT reduces cellular resistance to viral replication. Mechanistically, xCT inhibition impaired cGAS-STING signaling by reducing DNA-induced cGAMP production, thereby diminishing type I interferon (IFN/{beta}) responses and downstream induction of interferon-stimulated genes. Interestingly, modulating intracellular glutamate levels through inhibition of other glutamate pathways, e.g., glutaminolysis or glutamate import, also affected cellular IFN responses, suggesting that glutamate is a central control knob for DNA sensing. Finally, we demonstrate that HSV-1 suppresses xCT expression via a mechanism dependent on the immediate early viral protein ICP27, thereby promoting viral replication by limiting cGAS-dependent IFN induction. Together, these findings identify xCT-dependent glutamate transport as a critical metabolic regulator of cGAS-STING-mediated antiviral immunity.

immunology↗

bioRxiv2025

MAVS is Important for Antiviral Defense Against InfluenzaA Virus in a Human Respiratory Epithelium Model

The respiratory epithelium is an important immunological barrier and the first line of defense against influenza A virus. In mice and in various cellular systems, induction of type I interferons (IFN/{beta}) during IAV infections is known to depend on cytosolic RNA sensors RIG-I and MDA5 and on the adaptor molecule MAVS. Until now, it has not been possible to directly test the importance of MAVS for induction of IFNs and for resistance to IAV infection in primary human respiratory epithelium. Here, we used CRISPR-Cas9 to establish MAVS-deficient cultures of primary human respiratory epithelium using the air-liquid interphase culture system. Using this setup, we show that MAVS is indeed required for the induction of type I and type III IFNs and subsequently for the induction of IFN-stimulated genes in response to IAV infection in human primary respiratory epithelium. Finally, we demonstrate that MAVS is important for restricting viral replication in this model. In conclusion, we demonstrate that MAVS plays a non-redundant protective role during IAV infection in primary human respiratory epithelium.

immunology↗

bioRxiv2018

Feasibility of Functional MRI at Ultralow Magnetic Field via Changes in Cerebral Blood Volume

We investigate the feasibility of performing functional MRI (fMRI) at ultralow field (ULF) with a Superconducting QUantum Interference Device (SQUID), as used for detecting magnetoencephalography (MEG) signals from the human head. While there is negligible magnetic susceptibility variation to produce blood oxygenation level-dependent (BOLD) contrast at ULF, changes in cerebral blood volume (CBV) may be a sensitive mechanism for fMRI given the five-fold spread in spin-lattice relaxation time (T1) values across the constituents of the human brain. We undertook simulations of functional signal strength for a simplified brain model involving activation of a primary cortical region in a manner consistent with a blocked task experiment. Our simulations involve measured values of T1 at ULF and experimental parameters for the performance of an upgraded ULFMRI scanner. Under ideal experimental conditions we predict a functional signal-to-noise ratio of between 3.1 and 7.1 for an imaging time of 30 minutes, or between 1.5 and 3.5 for a blocked task experiment lasting 7.5 minutes. Our simulations suggest it may be feasible to perform fMRI using a ULFMRI system designed to perform MRI and MEG in situ.

neuroscience↗