Biology subjects

Raykov, P. P.

Publications and source records attributed to Raykov, P. P..

3 recordsLinked to original sources

bioRxiv2025

Complementary MR measures of white matter and their relation to cardiovascular health and cognition

Magnetic Resonance Imaging (MRI) offers many ways to non-invasively estimate the properties of white matter (WM) in the brain. In addition to the various metrics derived from diffusion-weighted MRI, one can estimate total WM volume from T1-weighted MRI, WM hyper-intensities from T2-weighted MRI, myelination from the T1:T2 ratio, or from the magnetisation-transfer ratio (MTR). Here we utilise the presence of all of these MR contrasts in a population based life-span cohort of 650 healthy adults [CamCAN cohort] to identify the latent factors underlying the covariance of 11 commonly-used WM metrics. Four factors were needed to explain 89% of the variance, which we interpreted in terms of 1) fibre density / myelination, 2) free-water / tissue damage, 3) fibre-crossing complexity and 4) microstructural complexity. These factors showed distinct effects of age and sex. To test the validity of these factors, we related them to measures of cardiovascular health and cognitive performance. Specifically, we ran path analyses 1) linking cardio-vascular measures to the WM factors, given the idea that WM health is related to cardiovascular health, and 2) linking the WM factors to cognitive measure, given the idea that WM health is important for cognition. Even after adjusting for age, we found that a vascular factor related to pulse pressure predicted the WM factor capturing free-water / tissue damage, and that several WM factors made unique predictions for fluid intelligence and processing speed. Our results show that there is both complementary and redundant information across common MR measures of WM, and their underlying latent factors may be useful for pinpointing the differential causes and contributions of white matter health in healthy aging.

neuroscience↗

bioRxiv2025

Hippocampus responds to mismatches with predictions based on episodic memories but not generalised knowledge

Prediction errors drive learning by signalling a mismatch between our expectations and reality. The hippocampus plays a key role in mismatch detection, but it is not known what information the hippocampus uses to form expectations. Here we show that the human hippocampus bases its expectations on episodic memories and not generalised schematic knowledge. Across three fMRI experiments, we demonstrate that the hippocampus is selectively engaged by mismatches with episodic memories of specific events. In contrast, mismatches with schematic knowledge activate regions of the Semantic Control and Multiple Demand Networks, as well as subcortical regions involved in prediction error signalling. Notably, mismatches with episodic memories also engage the Default Mode Network. Overall, our findings provide direct support for some models of learning via mismatch detection and refute models that propose the hippocampus plays a wider role as a more generalised mismatch detector.

neuroscience↗

bioRxiv2018

Shared contextual knowledge strengthens inter-subject synchrony and pattern similarity in the semantic network

To understand a dialogue we need to know the specific topics that are being discussed. This enables us to integrate our knowledge of what was said previously, in order to interpret the current dialogue. Here, we selectively manipulated knowledge about the narrative content of dialogues between two people, presented in short videos. The videos were clips taken from television situation comedies and the speech in the first-half of the clip could either be presented normally (high context) or spectrally rotated in order to render it unintelligible (low context). Knowledge of the preceding narrative boosted memory for the following dialogues as well as increased the inter-subject semantic similarity of recalled descriptions of the dialogues. Sharing knowledge of the preceding narrative across participants had two effects on fMRI markers of neural processing: (1) it strengthened temporal inter-subject correlations in regions including the left angular (AG) and inferior frontal gyri (IFG), and (2) it increased spatial inter-subject pattern similarity in the bilateral anterior temporal lobes (ATL). We argue that these brain regions, which are known to be involved in semantic processing, support the activation and integration of prior knowledge, which helps people to better understand and remember dialogues as they unfold.

neuroscience↗